Public Integrity Alliance, Inc, et al v. City of Tucson, et al

Filing

FILED OPINION (SIDNEY R. THOMAS, WILLIAM A. FLETCHER, RONALD M. GOULD, RICHARD A. PAEZ, MARSHA S. BERZON, RICHARD R. CLIFTON, CONSUELO M. CALLAHAN, MORGAN B. CHRISTEN, JACQUELINE H. NGUYEN, JOHN B. OWENS and MICHELLE T. FRIEDLAND) AFFIRMED. Judge: MSB Authoring, FILED AND ENTERED JUDGMENT. [10110917]

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Last Updated August 23, 2016

Voting Restrictions in Place for 2016 Presidential Election
In 2016, 15 states will have new voting restrictions in place for the first time in a presidential
election. The new laws range from strict photo ID requirements to early voting cutbacks to
registration restrictions.
Those 15 states are: Alabama, Arizona, Georgia, Indiana, Kansas, Mississippi, Nebraska, New
Hampshire, Ohio, Rhode Island, South Carolina, Tennessee, Texas, Virginia, and Wisconsin.
(This number decreased from 17 to 15 when the Fourth Circuit Court of Appeals struck down a
series of voting restrictions in North Carolina in late July 2016, and a federal court enjoined
North Dakota’s photo ID law in August 2016. Despite a recent court victory mitigating the
impact of Texas’s restrictive voter ID law, the state is still included because its requirement is
more restrictive than what was in place for the 2012 presidential election.)
This is part of a broader movement to curtail voting rights, which began ucsothe 2010 election,
after n
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Overall, 20 states have new restrictions in effect since the 2010 midterm election. This page
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Click here for an interactive version of this page.
Here are more details on those restrictive laws:

Alabama – A photo ID was required to vote starting for the first time in 2014. Passed in
2011 by a Republican-controlled state legislature and signed by a GOP governor, the ID law
initially required preclearance under Section 5 of the Voting Rights Act. But the measure was
allowed to go into effect after the U.S. Supreme Court gutted that provision in 2013.
Alabama also passed a law in 2011 requiring voters to provide documentary proof of
citizenship when registering to vote. That requirement had been on hold, but on January 29,
2016, the Election Assistance Commission sent a letter to the state indicating that proof of
citizenship would be added to the national voter registration form instructions.
Arizona – In 2016, a Republican-controlled legislature passed a bill limiting collection of
mail-in ballots and making it a felony to knowingly collect and turn in another voter’s
completed ballot, even with that voter’s permission (the law has exceptions for direct family
members, caregivers, and postal-service employees). Gov. Doug Ducey (R) signed the bill,
and the law will take effect during summer 2016. See below for details on other past

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restrictions in play.
Florida – In 2011, Florida’s Republican-controlled legislature passed a series of laws, signed
by Gov. Rick Scott (R), making it harder to vote. First, lawmakers reduced the early voting
period, which contributed to long lines in the 2012 election. The legislature responded in
2013 by restoring some of the early voting days, but there are still fewer early balloting
opportunities today than before the 2011 cutbacks. Second, Florida passed new restrictions
on voter registration drives. With the help of the Brennan Center, the most onerous aspects of
this law were enjoined by a federal court in August 2012. Finally, Gov. Scott reversed a prior
executive action that had made it easier to restore voting rights to people with past criminal
convictions. In effect, the state now permanently disenfranchises most citizens with past
felony convictions.
Georgia – In 2009, a Republican-controlled legislature passed a law requiring voters to
provide documentary proof of citizenship when registering to vote. That requirement had
been on hold, but on January 29, 2016, the Election Assistance Commission sent a letter to
the state indicating that proof of citizenship would be added to the national voter registration
form instructions. In 2011, a Republican-controlled legislature also reduced the early voting
period from 45 to 21 days, and cut early voting the weekend before Election Day. Both laws
were signed by a GOP governor.

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Illinois – In 2011, a Democratic-controlled legislature restricted voter registration drive rules
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does not apply to groups. only using the national mail-in voter registration form. The measure
was signed by a Democratic governor.
Indiana – In 2013, a Republican-controlled legislature passed a measure authorizing
additional party-nominated election officers to demand proof of identification.1 The law was
signed by a GOP governor. It was in effect for the first time in a major election in November
2014.
Iowa – In 2011, Gov. Terry Branstad (R) reversed a prior executive action that had made it
easier to restore voting rights to people with past criminal convictions. In effect, the state
now permanently disenfranchises most citizens with past felony convictions.
Kansas – In 2011, a Republican-controlled legislature passed a photo ID requirement.
Lawmakers also passed a bill mandating documentary proof of citizenship to register to vote.
Both measures were signed by a GOP governor. The documentary proof of citizenship
requirement has been the subject of multiple lawsuits. A 2014 federal court ruling had found
the requirement unenforceable on the federal mail-in voter registration form, but in January
1

This law subjects voters to an additional and duplicative voter identification requirement that did not exist before
the law was enacted. If, however, precinct election officials always enforce the voter ID requirement in a uniform
manner, this law may not have a restrictive effect.

2

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2016, the Election Assistance Commission’s Executive Director announced that documentary
proof of citizenship would be added to the national voter registration form instructions for
Kansas, as well as Alabama and Georgia. That action is the subject of an ongoing lawsuit.
Separately, a federal court ruled that documentary proof of citizenship could not be required
for voters who register at DMV offices under the federal “motor voter” law. Meanwhile, the
state is attempting to prohibit individuals who register at DMV offices and do not provide
documentary proof of citizenship from voting in state and local elections. In July 2016, a
state court temporarily blocked this “dual registration” system for the August 2, 2016
primary election. The requirement remains in effect for those using the state voter
registration form.
Mississippi – A photo ID was required to vote starting for the first time in 2014. Passed in
2011 by a voter referendum, the ID law initially required preclearance under Section 5 of the
Voting Rights Act. But the measure was allowed to go into effect after the U.S. Supreme
Court gutted that provision in 2013.
Nebraska – In 2013, state lawmakers reduced the early voting period from a minimum of 35
days to no more than 30 days. This restriction was in effect for the first time in a major
election in 2014. Nebraska’s unicameral legislature is technically nonpartisan, but it is
generally controlled by Republicans. The measure was signed by a GOP governor.

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photographed at the polls. The photograph will be affixed to an affidavit.
Ohio – In 2014, a Republican-controlled state legislature passed a series of voting
restrictions, which were signed by a GOP governor. Lawmakers cut six days of early voting
— eliminating “Golden Week,” during which voters could register and cast a ballot all in one
trip — and changed absentee and provisional ballot rules. Both restrictions are subject to
ongoing litigation. In 2014, Secretary of State Jon Husted (R) also issued a directive reducing
early voting on weekday evenings and weekends. In 2015, state officials and voting rights
advocates settled a separate ongoing lawsuit over the early voting hours, which restored one
day of Sunday voting and added early voting hours on weekday evenings. The settlement is
in place through 2018.
Rhode Island – A photo ID was requested to vote starting for the first time in 2014. There is
an affidavit alternative for voters without a photo ID. The bill — which passed through a
Democratic-controlled legislature and was signed by an independent governor in 2011 — is
significantly less restrictive than other ID laws because it accepts a broad range of IDs with a
voter’s name and photograph. A previous version of the law allowed non-photo IDs.
South Carolina – A photo ID was requested to vote starting for the first time in a major
election in 2014. There is an affidavit alternative for voters without a photo ID. The measure
3

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passed in 2011 through a Republican-controlled legislature and was signed by a GOP
governor, but it was put on hold by a federal court until after the 2012 election. During the
course of that litigation, the state interpreted the law in a way that makes it much less
restrictive than other ID requirements.
South Dakota – In 2012, a Republican-controlled legislature passed a law making it harder
to restore voting rights to people with past criminal convictions. It was signed by a GOP
governor.
Tennessee – A Republican-controlled legislature passed a law in 2011 requiring photo ID to
vote. Lawmakers made it even more restrictive in 2014 by limiting acceptable IDs to those
issued by the state or federal government. The new version was in effect for the first time in a
major election in 2014. In 2011, lawmakers also reduced the early voting period and passed a
law requiring documentary proof of citizenship to register to vote. All were signed by a GOP
governor. The proof of citizenship measure applies only to individuals flagged by state
officials as potential non-citizens based on a database check.
Texas – In 2011, a Republican-controlled legislature passed a restriction on voter registration
drives and a strict photo ID law. Both measures were signed by a GOP governor. In 2012, a
federal court blocked the photo ID law under Section 5 of the Voting Rights Act. The state
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then implemented the requirement after the U.S. Supreme Court of Tucs
gutted Section 5 in 2013,
and a photo ID was required to vote for the first time in. a . City election in 2014. In July
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and signing a declaration.
Virginia – A photo ID was required to vote starting for the first time in 2014. Lawmakers
also passed a bill restricting third-party voter registration, which requires groups receiving 25
or more registration forms to register with the state and reduces the amount of time from 15
to 10 days to deliver the applications. The state Senate is evenly divided among Democrats
and Republicans, but the GOP lieutenant governor cast the tie-breaking vote on the photo ID
law. The state House is controlled by Republicans. Both measures were signed by a GOP
governor in 2013. In 2015, a Republican-controlled legislature passed a bill to amend the
photo ID law to add student IDs issued by private schools to the list of acceptable IDs (the
law currently allows public school IDs). The bill was signed by a Democratic governor and
takes effect in 2016. A challenge to the law failed in May 2016 but is on appeal.
West Virginia – In 2011, a Democratic-controlled legislature reduced the early voting period
from 17 to 10 days. The measure was signed by a Democratic governor.
Wisconsin – A photo ID is required to vote for the first time in a presidential election in
2016. There is also a restriction on individual voter registration, which passed and went into
effect in 2011. On July 19, 2016, a federal trial court issued a preliminary injunction of the
photo ID requirement, instructing that voters who lack photo ID must be able to cast a
4

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regular ballot in November after completing an affidavit. Wisconsin has appealed that
decision. On August 10, 2016, the Seventh Circuit put the preliminary injunction on hold,
meaning that Wisconsin’s law is currently in effect without an affidavit alternative for those
without ID. In 2014, the legislature also reduced early voting hours on weekdays and
eliminated them entirely on weekends. These cuts were in effect for the first time in 2014.
They are currently on hold after a July 29, 2016 trial court decision finding the restrictions
were intentionally racially discriminatory. That decision also ruled the photo ID law could
not be implemented without providing a safety net for those without ID. The voting
restrictions were passed by a Republican-controlled legislature in 2011 and 2014, and signed
by a GOP governor.
Other Notable Developments:
Arizona – In 2004, voters approved a referendum requiring documentary proof of citizenship
to register to vote. In June 2013, the U.S. Supreme Court invalidated this measure as it
applied to the federal voter registration form, but it remains in place for the state registration
form. Arizona joined Kansas, which has a similar law, in a suit to force the U.S. Election
Assistance Commission to change the federal form to allow the two states to require such
documents. Those changes were denied after years of litigation, but Kansas’s form was
changed through a separate process in January 2016. Arizona’s remains unchanged.

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Arkansas – A Republican-controlled legislature passed v.photo ID law in 2013, overriding a
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Montana – A Republican-controlled legislature approved a referendum measure to repeal
Election Day registration, which voters rejected in November 2014. Gov. Steve Bullock (D)
had vetoed a previous effort to repeal Election Day registration.

North Carolina – A Republican-controlled state legislature passed a series of voting
restrictions in 2013, which were signed by a GOP governor. Lawmakers eliminated same-day
registration, reduced the early voting period, ended pre-registration for 16- and 17-year-olds,
and instituted a strict photo ID requirement, among a number of other restrictive changes.
The measures were in effect for the first time in 2014 (except for the ID requirement, which
was slated to go into effect in 2016). In June 2015, lawmakers softened the photo ID
requirement, creating an option for voters to attest to a reasonable impediment to obtaining
an ID, and vote a provisional ballot that will be counted unless there is a problem with the
attestation. In July 2016, the Fourth Circuit Court of Appeals struck down the state’s voting
restrictions, ruling that they were passed with racially discriminatory intent. It also ruled that
the “reasonable impediment” exception was not a sufficient remedy for the ID law’s harm.
North Dakota – In 2015, a Republican-controlled legislature passed a bill, signed by a GOP
governor, making the state’s voter ID law — already in effect in the 2014 election — more
restrictive by providing that only four types of IDs would be accepted to vote, either inperson or absentee: a current North Dakota driver’s license or non-driver photo ID, a tribal
5

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ID, or a long-term care certificate. On August 1, 2016, a federal trial court issued a
preliminary injunction, ordering North Dakota to provide a “fail-safe” option for voters
without photo ID if the state intends to enforce the law. The state indicated it will not appeal
the ruling, and will allow a broad range of IDs to cast a ballot in the 2016 election.

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United States Government Accountability Office

Report to Congressional Requesters

September 2014

ELECTIONS
Issues Related to
State Voter
Identification Laws
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This report was revised on February 27, 2015, to clarify information
about one source of data on voter records on pages 83 and 161.
This clarification had no impact on the conclusions of our report.

GAO-14-634

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September 2014

ELECTIONS
Issues Related to State Voter Identification Laws
Highlights of GAO-14-634, a report to
congressional requesters

Why GAO Did This Study

What GAO Found

The authority to regulate U.S. elections
The studies GAO reviewed on voter ownership of certain forms of identification
is shared by federal, state, and local
(ID) documents show that most registered voters in the states that were the
officials. Congress has addressed
focus of these studies possessed the selected forms of state-issued ID, and the
major functional areas in the voting
direct costs of required ID vary by state. GAO identified 10 studies of driver’s
process, such as voter registration.
license and state ID ownership, which showed that estimated ownership rates
However, the responsibility for
among all registered voters ranged from 84 to 95 percent, and that rates varied
administration of state and federal
by racial and ethnic groups. For example, one study estimated that 85 percent of
elections resides at the state level. In
White registered voters and 81 percent of African-American registered voters in
2002 Congress passed the Help
one state had a valid ID for voting purposes. The costs and requirements to
America Vote Act (HAVA), which
obtain certain forms of ID, including a driver’s license, state ID, or free state ID,
requires states to request ID from first
vary by state. GAO identified direct costs for these forms of ID in 17 states that
time voters who register by mail, when
require voters to present a photo or government-issued ID at the polls and do not
they register to vote or cast a ballot for
allow voters to affirm their own identities, and found that driver’s license direct
the first time, and to permit individuals
costs, for example, range from $14.50 to $58.50. son
to vote a provisional ballot if they do
f Tuc
not have the requisite ID. Numerous
ity o 6
Another 10 studies GAO reviewed. showed mixed effects of various forms of
v C All 101
states have enacted additional laws to
state voter ID requirementsIon .
, nc turnout.1, 20 studies examined general elections
3
e
address how an individual may register
before 2008, and l1ianc 10 studies also included the 2004 through 2012
l of the
gust
to vote or cast a ballot. As of June
ity A Five ofn Au 10 studies found that ID requirements had no
generaltegr
2014, 33 states had enacted
n elections. ved o these
statistically archi
blic I 42 significant effect on turnout; in contrast 4 studies found decreases in
requirements for all eligible voters to n Pu
i
turnout and 1 found an increase in turnout that were statistically significant.
61
show ID before casting a ballottatd
ci e the o. 15-1
N GAO conducted a quasi-experimental analysis to compare voter turnout in
polls on Election Day.
GAO was asked to review issues
related to voter ID laws. This report
reviews (1) what available literature
indicates about voter ownership of and
direct costs to obtain select IDs; (2)
what available literature and (3)
analyses of available data indicate
about how, if at all, voter ID laws have
affected turnout in select states; (4) to
what extent provisional ballots were
cast due to ID reasons in select states;
and (5) what challenges may exist in
using available information to estimate
the incidence of in-person voter fraud.
GAO reviewed relevant literature to
identify 10 studies that estimated
selected ID ownership rates. GAO
reviewed the studies’ analyses and
determined that these studies were
sufficiently sound to support their
results and conclusions. GAO also
reviewed state statutes and websites
to identify acceptable forms of voter ID
View GAO-14-634. For more information,
contact Rebecca Gambler at [phone]
or [e-mail] or Nancy R. Kingsbury
at [phone] or [e-mail]

Kansas and Tennessee to turnout in the four comparison states that did not have
changes in their voter ID requirements from the 2008 to 2012 general elections.
In selecting these states from among 14 potential states that modified their ID
requirements and 35 potential comparison states, GAO applied criteria to ensure
that the states did not have other factors present in their election environments
that may have significantly affected turnout. GAO selected states that did not
experience contemporaneous changes to other election laws that may have
significantly affected voter turnout; had presidential general elections where the
margin of victory did not substantially change from 2008 to 2012 and all other
statewide elections, such as U.S. Senate races, were non-competitive in both the
2008 and 2012 general elections; and ballot questions were not present,
noncompetitive, or similarly competitive in both the 2008 and 2012 general
elections. GAO analyzed three sources of data on turnout among eligible and
registered voters, including data from official voter records and a nationwide
survey. GAO’s evaluation of voter turnout suggests that turnout decreased in two
selected states—Kansas and Tennessee—from the 2008 to the 2012 general
elections (the two most recent general elections) to a greater extent than turnout
decreased in the selected comparison states—Alabama, Arkansas, Delaware,
and Maine. GAO’s analysis suggests that the turnout decreases in Kansas and
Tennessee beyond decreases in the comparison states were attributable to
changes in those two states’ voter ID requirements. GAO found that turnout
among eligible and registered voters declined more in Kansas and Tennessee
than it declined in comparison states—by an estimated 1.9 to 2.2 percentage
points more in Kansas and 2.2 to 3.2 percentage points more in Tennessee—
and the results were consistent across the different data sources and voter
populations used in the analysis.
United States Government Accountability Office

Highlights of GAO-14-634 (Continued)
Case: 15-16142,

in selected states and the price for
certain forms of ID.

09/02/2016, ID: 10110917, DktEntry: 68-2, Page 9 of 216
To further assess the validity of the results of this analysis, GAO (1) compared
Kansas and Tennessee with different combinations of comparison states and
with individual comparison states, and (2) controlled for demographic
characteristics that can affect turnout, such as age, education, race, and sex.
GAO also conducted an analysis using survey data on registrants from Kansas
and Tennessee and a nationwide comparison group of all states other than the
selected comparison states. These additional analyses produced consistent
results. GAO’s estimates are limited to turnout in the 2012 general election in
Kansas and Tennessee and do not apply to other states or time periods.

GAO also reviewed relevant literature
and identified 10 other studies that
estimated the effect of voter ID laws on
turnout. GAO reviewed the studies’
design, implementation, and analyses,
and determined that the studies were
sufficiently sound to support their
results and conclusions. Further, GAO
GAO also estimated changes in turnout among subpopulations of registrants in
compared turnout in two states—
Kansas and Tennessee—that changed
Kansas and Tennessee according to their age, length of voter registration, and
ID requirements from the 2008 to 2012
race or ethnicity. In both Kansas and Tennessee, compared with the four
general elections with turnout in four
comparison states, GAO found that turnout was reduced by larger amounts:
selected states—Alabama, Arkansas,
among registrants, as of 2008, between the ages of 18 and 23 than among
Delaware, and Maine—that did not.
registrants between the ages of 44 and 53;
GAO used a quasi-experimental
among registrants who had been registered less than 1 year than among
approach, a type of policy evaluation
registrants who had been registered 20 years or more; and
that compares how an outcome
among African-American registrants than among White, Asian-American, and
changes over time in a treatment group
Hispanic registrants. GAO did not find consistent reductions in turnout among
that adopted a new policy, to a
comparison group that did not make
Asian-American or Hispanic registrants compared to White registrants, thus
the same change. GAO selected states
suggesting that the laws did not have larger effects among these subgroups.
for evaluation that did not have other
A small portion of total provisional ballots in Kansas and Tennessee were cast for
factors in their election environments
ID reasons in 2012, and less than half were counted. In Kansas, 2.2 percent of
that also may have affected turnout,
such as significant changes to other
all provisional ballots in 2012 were cast due to ID reasons, and 37 percent of
election laws. GAO analyzed three
these provisional ballots were counted. In Tennessee, 9.5 percent of all
sources of turnout data for the 2008
provisional ballots in 2012 were cast due to ID reasons and 26 percent were
and 2012 general elections: (1) data on
counted. Provisional ballots cast for ID reasons may not be counted for a variety
cson
eligible voters, using official voter
of Tu the voter not providing valid ID
of reasons in Kansas and Tennessee,ity
. C including
records compiled by the United States
during or following an election. . v
2016
ncGAO’s analysis showed that provisional ballot use
Elections Project at George Mason
ce, I andust 31,
increased betweenian 2008 g 2012 general elections by 0.35 percentage
University, (2) data on registered
All the 0.17 u
points inegrity and d on A percentage points in Tennessee, relative to all
Kansas
voters, using state voter databases
t
e by
otherIn
that were cleaned by a vendor through ublic comparison states combined; these findings are not generalizable.
rchiv
a
142
data-matching procedures to removen P
ed i
Challenges exist in using available information to estimate the incidence of initand (3) o. 15-16
c
voters who had died or moved,
N person voter fraud. For the purposes of this report, “incidence” is defined as the
data on registered voters, as reported
number of separate times a crime is committed during a specific time period.
to the Current Population Survey
Estimating the incidence of crime involves using information on the number of
conducted by the U.S. Census Bureau.
GAO also analyzed data from Kansas
and Tennessee election officials on the
number of provisional ballots cast for
ID reasons in the 2012 general
election, and data from the Election
Assistance Commission’s Election
Administration and Voting Survey on
the number of provisional ballots cast
in select states in 2008 and 2012.
GAO reviewed relevant literature and
identified 5 studies that attempted to
identify instances of in-person voter
fraud. GAO reviewed the studies’
analyses, and determined that these
studies were sufficiently sound to
support their results and conclusions.
GAO also interviewed election officials
in 46 states and the District of
Columbia and officials from federal
agencies that maintain federal crime
data to determine how, if at all,
instances of in-person voter fraud are
tracked in state and federal databases.

crimes known to law enforcement authorities—such as crime data submitted to a
central repository based on uniform offense definitions—to generate a reliable
set of crime statistics. Based on GAO’s review of studies by academics and
others and information from federal and state agencies, GAO identified various
challenges in information available for estimating the incidence of in-person voter
fraud that make it difficult to determine a complete picture of such fraud. First, the
studies GAO reviewed identified few instances of in-person voter fraud, but
contained limitations in, for example, the completeness of information sources
used. Second, no single source or database captures the universe of allegations
or cases of in-person voter fraud across federal, state, and local levels, in part
because responsibility for addressing election fraud is shared among federal,
state, and local authorities. Third, federal and state agencies vary in the extent
they collect information on election fraud in general and in-person voter fraud in
particular, making it difficult to estimate the incidence of in-person voter fraud.
In comments on draft report excerpts the Kansas, Tennessee, and Arkansas
Secretary of State Offices disagreed with GAO’s criteria for selecting treatment
and comparison states and Kansas and Tennessee questioned the reliability of
one dataset used to assess turnout. GAO notes that any policy evaluation in a
non-experimental setting cannot account for all unobserved factors that could
potentially impact the results. However, GAO believes its methodology was
robust and valid as, among other things, GAO’s selection of treatment and
comparison states controlled for factors that could significantly affect voter
turnout, and GAO used three data sources it determined to be reliable to assess
turnout effects.
United States Government Accountability Office

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Contents

Letter

1
Background
Studies Show That Most Registered Voters Have State-Issued
IDs; Direct Costs to Obtain Such IDs Vary Among States
Studies Generally Focused on Elections Prior to 2008 and
Showed Mixed Effects of Voter ID Requirements on Voter
Turnout
Our Analysis Suggests that Decreases in General Election
Turnout in Kansas and Tennessee from 2008 to 2012 Beyond
Decreases in Comparison States Are Attributable to Changes in
Voter ID Requirements
A Small Portion of Total Provisional Ballots in Two States Were
Cast for ID Reasons in 2012, and Less Than Half Were
Counted
cson
Challenges Exist in Using Available Information to Estimate the
of Tu
City
Incidence of In-Person Voter. Fraud 016
nc. v 31, 2 Our Evaluation
I
Agency and Third Party, Comments and
nce
ust

Appendix I

ug
Allia
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nte rcCharacteristics of Voters Who Voted and Registered
Demographic
blic I 2 a h
in Pu through4Different Methods
d
161
cite
. 15No

9
21

34

44

57
62
74

91

Appendix II

Objectives, Scope, and Methodology

108

Appendix III

Bibliography of Identification (ID) Ownership, Voter Turnout and InPerson Voter Fraud Studies Reviewed for This Report

122

Driver’s License and Nondriver State ID Costs in Selected States,
as of July 2014

126

Voter Turnout Analysis Design

128

Appendix IV

Appendix V

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Appendix VI

Voter Turnout Analysis Methods, Data Sources, and Additional
Results

146

Appendix VII

Additional Provisional Ballot Analysis

185

Appendix VIII

Selected Federal Databases and the Types of Information They
Contain

188

Comments from the Arkansas Secretary of State’s Office
n

189

Appendix IX

Appendix X

Appendix XI

Appendix XII

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Comments fromllianKansas Secretary of State
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GAO Contact and Staff Acknowledgments

191

193

200

Tables
Table 1: Summary of Findings from Studies That Estimate
Selected Identification (ID) Ownership
Table 2: Cost to Obtain Birth Certificate by State, as of July 2014
Table 3: Summary of Studies on the Effects of Voter Identification
(ID) Requirements on Overall Voter Turnout
Table 4: Provisional Ballot Totals and Rates in 2012 General
Election for Kansas and Tennessee
Table 5: Change in Provisional Ballot Usage between 2008 and
2012 General Elections, in Treatment and Comparison
States60
Table 6: Comparison of Change in Provisional Ballot Usage
between 2008 and 2012 General Elections in Treatment
and Comparison State Groups

22
32
36
59

61

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Table 7: Summary of Findings and Methods from Studies That
Attempted to Identify Instances of In-Person Voter Fraud
Table 8: Possible Statutory Provisions under Which In-Person
Voter Fraud Could Be Prosecuted
Table 9: Driver’s License and Nondriver Identification (ID) Costs in
Selected States
Table 10: Potential Treatment States
Table 11: Comparison State Selection Results
Table 12: Characteristics of Treatment and Comparison States
Table 13: Competitiveness of U.S. House of Representatives
Races in Alabama, Arkansas, Delaware, and Maine (2012
and 2008 General Elections)
Table 14: Eligible Voter Turnout Estimates by State and Year,
Using Official Vote Totals
n
Table 15: Effects of Changes in Voter ID Requirements on 2012
ucso
of and Tennessee, Using
Eligible Voter Turnout in KansasT
City 016
Official Vote Totalsc. v.
n
1, 2
,I
Table 16: Effectsliofnce ugusVoter ID Requirements on 2012
a Changes in t 3
Al
n
grity ive VoterA
nteRegisteredd o Turnout in Kansas and Tennessee,
c I Using h
i
2 arc Voter Registration and History Databases
Publ
d in 15-1614 Effects of Changes in Voter ID Laws on 2012
Table 17:
cite
No.
Registered Voter Turnout in Kansas and Tennessee, by
Racial and Ethnic Subgroups, Using Voter Registration
and History Databases
Table 18: Effects of Changes in Voter ID Laws on 2012
Registered Voter Turnout in Kansas and Tennessee, by
Length of Registration, Using Voter Registration and
History Databases
Table 19: Effects of Changes in Voter ID Laws on 2012
Registered Voter Turnout in Kansas and Tennessee, by
Age in 2008, Using Voter Registration and History
Databases
Table 20: Effects of Changes in Voter ID Requirements on 2012
Registered Voter Turnout in Kansas and Tennessee,
Using Registrant-Level Sample from Voter Registration
and History Databases
Table 21: Effects of ID Requirements on 2012 Registered Voter
Turnout in Kansas and Tennessee, Using Current
Population Survey
Table 22: Change in Provisional Ballot Usage between 2008 and
2012 General Elections, in Treatment and Comparison
States

65
118
126
134
138
141

145
160

161

169

171

173

175

180

184

185

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Table 23: Comparison of Change in Provisional Ballot Usage
between 2008 and 2012 General Elections in Treatment
and Comparison State Groups
Table 24: Selected Federal Databases and the Types of
Information They Contain

186
188

Figures
Figure 1: The Voting Process
Figure 2: States that Enacted Identification Requirements or
Changed Acceptable Type of Document or Issuing
Authority, by Year, from 2002 through 2013
cson
Figure 3: Map of States that Have Enacted Voter Identification (ID)
of Tu
ty
Requirements, as c. v. Ci 2014 16
of June
0
n
31, 2
Figure 4: License ance, I
and Nondriver State Identification (ID) Costs in
li States,August 2014
l
Selected
n as of July
rity A
e GAO Analysis
nt5:g rchived o of the Effects of Voter Identification (ID)
Figure
cI
i
2a
Publ
d in 15-1614Requirement Changes on Turnout in the 2012 General
ite
c
Election in Kansas and Tennessee
No.
Figure 6: GAO Analysis of the Effects of Voter Identification (ID)
Requirement Changes on Turnout in the 2012 General
Election in Kansas and Tennessee by Age (as of 2008),
Race, and Length of Registration
Figure 7: Voting Method by Race in the 2008, 2010, and 2012
General Elections
Figure 8: Voting Method by Education Level in the 2008, 2010,
and 2012 General Elections
Figure 9: Voting Method by Age in the 2008, 2010, and 2012
General Elections
Figure 10: Voting Method by Income Level in the 2008, 2010, and
2012 General Elections
Figure 11: Voting Method by Employment Status in the 2008,
2010, and 2012 General Elections
Figure 12: Voting Method by Length of Time at Residence in the
2008, 2010, and 2012 General Elections
Figure 13: Voting Method by Sex in the 2008, 2010, and 2012
General Elections
Figure 14: Registration Method by Race in the 2008, 2010, and
2012 General Elections

11

16
18
30

49

54
93
94
95
96
97
98
99
101

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Figure 15: Registration Method by Education Level in the 2008,
2010, and 2012 General Elections
Figure 16: Registration Method by Age in the 2008, 2010, and
2012 General Elections
Figure 17: Registration Method by Income Level in the 2008,
2010, and 2012 General Elections
Figure 18: Registration Method by Employment Status in the
2008, 2010, and 2012 General Elections
Figure 19: Registration Method by Length of Time at Residence in
the 2008, 2010, and 2012 General Elections
Figure 20: Registration Method by Sex in the 2008, 2010, and
2012 General Elections
Figure 21: Yearly Change in Turnout in Treatment and
Comparison States, 1984 to 2012 General Elections

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102
103
104
105
106
107
142

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Abbreviations:
ACTS II
Automated Case Tracking System II
cson
of Tu
ANES
American National Election Studies
. City
6
ATT
average , Inc. v effect 01 the treated
treatment 1, 2 for
t3
ce
s
n
CCES
Cooperative Congressional Election Study
Allia o ugu
grity Current n A
CPSInte
d Population Survey
ic
chive
DMV
Publ 6142 ar Department of Motor Vehicles
in
DOJ
Department of Justice
cited o. 15-1
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Election Assistance Commission
EAVS
Election Administration and Voting Survey
EOUSA
Executive Office for United States Attorneys
FJC
Federal Judicial Center
HAVA
Help America Vote Act
ID
identification
IDB
Integrated Database
LIONS
Legal Information Office Network System
MOV
margin of victory
NVRA
National Voter Registration Act
PACER
Public Access to Court Electronic Records
UOCAVA
Uniformed and Overseas Citizens Absentee Voting Act
USEP
United States Elections Project
USSC
United States Sentencing Commission
This is a work of the U.S. government and is not subject to copyright protection in the
United States. The published product may be reproduced and distributed in its entirety
without further permission from GAO. However, because this work may contain
copyrighted images or other material, permission from the copyright holder may be
necessary if you wish to reproduce this material separately.

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441 G St. N.W.
Washington, DC 20548

September 19, 2014
The Honorable Patrick Leahy
Chairman
Committee on the Judiciary
United States Senate
The Honorable Richard Durbin
Chairman
Subcommittee on the Constitution, Civil Rights and Human Rights
Committee on the Judiciary
United States Senate

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The Honorable Bernard, Sanderst
n
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United States Senate on A
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c
N United States Senate
The Honorable Charles Schumer
United States Senate

As of June 2014, 33 states had enacted requirements for all eligible
voters to show identification (ID) before casting a ballot at the polls on
Election Day. 1 The authority to regulate elections in the United States is
shared by federal, state, and local officials, contributing to the prevalence
and diversity of these laws. Deriving its authority from various
constitutional sources, depending upon the type of election, Congress
has passed legislation addressing major functional areas in the voting
process such as voter registration and prohibitions against discriminatory
voting practices. 2 Nevertheless, the responsibility for the administration of
state and federal elections resides at the state level, and state statutes
regulate various aspects of elections, including registration and Election

1
This includes states in which ID requirements are not currently in effect because, for
example, the law is legislated to go into effect at a later date or the law has been enjoined
pursuant to litigation. Vote-by-mail states are not included.
2

These include the National Voter Registration Act of 1993, the Help America Vote Act of
2002, and the Voting Rights Act of 1965, among others.

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Day procedures. Within each state, responsibility for managing, planning,
and conducting elections is largely a local process, residing with about
10,500 local election jurisdictions nationwide.
In 2002, Congress passed the Help America Vote Act (HAVA) in
response to problems reported during the 2000 presidential election with
respect to voter registration lists, absentee ballots, ballot counting, and
antiquated voting systems. 3 Among other provisions, HAVA required
states to request identification from first-time voters who register by mail,
either when they register to vote or when they cast a ballot for the first
time. HAVA also required states to permit individuals to vote a provisional
ballot if they do not have the requisite identification or if they are not on
the official list of registered voters. In the 12 years since Congress passed
HAVA, states have implemented major election reforms, amended their
election codes, or made other changes to their election procedures in
cson
order to comply with HAVA’s provisions, Tu
of including those related to voter
. City
6
ID for first-time voters. Numerous states0have enacted additional laws to
nc. v 31, 2 1
ce, I gu register to vote or cast a ballot. 4 In
address how an individual may st
n
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particular, rity states n A made substantive changes to their election
g manyived o have
nte procedures related to voter ID requirements beyond those
codes
blic I or 2 arch
in Pu established by HAVA. Proponents of these ID requirements suggest that
d
1614
cite
. 15- may help prevent voter fraud and improve voter confidence in the
No they
election system, while opponents suggest that the requirements may
create an undue burden for some voters.
In October 2012, we issued a report on state voter ID requirements for all
eligible voters, including requirements to show identification prior to voting
at the polls on Election Day and the types of documents that satisfy these
requirements, provisions for no-excuse absentee voting by mail and in-

3

Pub. L. No. 107-252, 116 Stat. 1666 (2002) (codified as amended at 42 U.S.C. §§ 15301545).
4

Under section 5 of the Voting Rights Act of 1965, as amended, 42 U.S.C. § 1973c,
covered jurisdictions may not change their election practices or procedures until they
obtain federal “preclearance” for the change. The jurisdictions targeted for “coverage” are
those states or localities evidencing discriminatory voting practices, based upon a
triggering formula, as defined in section 4 of the Voting Rights Act, 42 U.S.C. § 1973b. In
June 2013, the Supreme Court ruled in Shelby County v. Holder that section 4 of the
Voting Rights Act is unconstitutional. 133 S. Ct. 2612 (2013). The effect of this decision is
that the jurisdictions identified by the coverage formula in section 4(b) no longer need to
seek preclearance for new voting changes (unless they are covered by a separate court
order entered under section 3(c) of the Voting Rights Act).

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person early voting, and requirements for voter registration drives
conducted by nongovernmental organizations (third parties), among other
things. 5
You asked us to review the implications for voters of changes in state
voter ID requirements, such as potential costs to voters and any effect on
voter turnout for elections. This report addresses the following questions:
What does available literature indicate about the proportion of voters
who have selected ID documents, and what are the direct costs to
voters to obtain documents needed to satisfy state voter ID
requirements?
What do existing studies indicate about how, if at all, voter ID laws
have affected turnout?

on

What does our analysis of availablef data s
Tuc indicate about how, if at all,
ty o
iaffected6
changes in voter ID laws.have
v. C
1 turnout in selected states?

, Inc

1, 20

3
e
To what extent were provisional ballots cast because of ID reasons
gust
llianc
ity A in two n Au
andegr
counted ed o selected states during the 2012 election, and how
Int
iv
blicdid provisional ballot use in those states change after the adoption of
arch
in Pu -16142 laws?
cited o. 15 voter ID
N
What challenges, if any, exist in using available information at the
federal and state levels to estimate the incidence of in-person voter
fraud?
In addition, we reviewed information related to the demographic
characteristics of voters who voted and registered through different
methods. This information can be found in appendix I.
To identify what available literature indicates about proportions of voters
who have selected ID documents, we conducted a literature review to
identify relevant studies. We identified 10 studies that estimate selected
ID ownership rates through a review of online databases that catalog
legal proceedings, peer-reviewed journal articles, conference
proceedings, and research institute publications. Two GAO social
scientists reviewed the 10 studies and determined that the design,
implementation, and analyses of the studies were sufficiently sound to

5

GAO, Elections: State Laws Addressing Voter Registration and Voting on or before
Election Day, GAO-13-90R (Washington, D.C.: Oct. 4, 2012).

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support the studies’ results and conclusions based on generally accepted
social science principles. To determine the direct costs to voters to obtain
selected documents required to satisfy state voter ID requirements, we
first reviewed state statutes and legislative websites to identify those
states with requirements for all eligible voters to present identification
documents that fall into one of three categories (1) photo only,
government issued; (2) photo only, can be non-government issued; (3)
non-photo, government issued. 6 We excluded states that allow all voters
without ID to affirm their own identity at the polling place in order to cast a
regular ballot, since there would be no cost to the voter. We also
excluded states that allow non-photo, non-government forms of
identification because these costs can vary widely and are difficult to
obtain. 7 As of June 2014, we identified 17 states that met these criteria. 8
We reviewed state statutes, information provided by states to voters, and
relevant state websites to identify acceptableson of voter ID in each
types
uc
state and the price for each selected ID. T confirmed price information
of We
City 016
for selected IDs with statenofficials to,ensure accuracy.
c. v.
2
I

31
e,
lianc August
Alexisting studies indicate about how voter ID laws have
To identifyrity
eg what v d on
c Int turnout iine
affected 2 arch selected states, if at all, we reviewed the literature on
bli
in Pu this1topic. Specifically, we identified 10 studies that estimate the effect of
614
cited o. 15N voter ID laws on turnout. We identified these studies through a search of
various online databases that catalog legal proceedings, peer-reviewed
journal articles, conference proceedings, and research institute
publications. Two GAO social scientists and a GAO statistician reviewed
each of the 10 studies and determined that the design, implementation,

6
States requiring government-issued ID include those where there is an exception for a
school ID.
7
Some states allow voters to provide a utility bill, a bank statement, or a pay-check,
among other documents, as voter identification. It would be difficult to measure the cost to
obtain these non-photo and non-government issued IDs, and the specifics of the cost
would vary based on the voter and the type of document allowed to be presented.
8
The 17 states in our scope are Alabama, Arkansas, Florida, Georgia, Indiana, Kansas,
Mississippi, North Carolina, North Dakota, Oklahoma, Pennsylvania, Rhode Island, South
Carolina, Tennessee, Texas, Virginia, and Wisconsin. These 17 states include those in
which ID requirements are not currently in effect because, for example, the law is
legislated to go into effect at a later date or the law has been enjoined pursuant to
litigation. See, e.g., Applewhite v. Commonwealth, 2014 WL 184988 (Pa. Commw. Ct.
Jan. 17, 2014); Frank v. Walker, 2014 WL 1775432 (E.D. Wis. Apr. 29, 2104). As of June
2014, litigation was pending in Arkansas, North Carolina, Oklahoma, Texas and
Wisconsin.

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and analyses of the studies were sufficiently sound to support the studies’
results and conclusions based on generally accepted social science
principles.
For our evaluation of available data to determine how, if at all, voter ID
laws have affected turnout in selected states, we used a quasiexperimental approach. This approach is a type of policy evaluation that
compares how an outcome changes over time in a “treatment” group that
adopted a new policy, as compared with a “comparison” group that did
not make the same change. As in controlled experiments, researchers
using this approach analyze separate groups before and after one group
changed a policy. We compared changes in voter turnout from the 2008
to the 2012 general election—the most recent general election cycle—in
selected treatment states that implemented changes to voter ID
requirements (Kansas and Tennessee) with selected comparison states
cson
that did not implement changes to their fvoter ID requirements (Alabama,
o Tu
. ity 2 that
6
Arkansas, Delaware, and Maine)C
nc. v during01 time period. Our quasice, I gust 31,
experimental comparison group design accounts for factors other than
n
u
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voter ID requirementson Acould affect voter turnout. We selected Kansas
grity ived that
nte rch from among 14 potential treatment states and Alabama,
and I
blic Tennessee
a
142
in Pu Arkansas, Delaware, and Maine from among 35 potential comparison
ited o. 15-16
c
N states. In making these selections, we took steps to ensure that states
included in our analysis did not have other factors present in their election
environments that may have significantly affected turnout. For example,
we selected treatment and comparison states that had the following
characteristics: did not experience contemporaneous changes to other
election laws that may have significantly affected voter turnout on Election
Day; had presidential general elections where the margin of victory did
not substantially change from 2008 to 2012 and all other statewide
elections, such as U.S. Senate races, were non-competitive in both the
2008 and 2012 general elections; ballot questions were not present,
noncompetitive, or similarly competitive in both elections within a state;
and had official voter history data that were sufficiently reliable for the
purposes of our analysis. 9 We used three data sources for our analysis of
voter ID requirement effects on voter turnout: official voter records in the

9
Significant changes in presidential election margins of victory suggests that voters may
have been subjected to more intense efforts by campaigns and interest groups to affect
turnout. This imbalance in voter mobilization efforts—which academic research has shown
to be effective in some conditions—is an important potential factor that could affect
turnout.

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United States Elections Project’s (USEP) database; official voter records
enhanced for improved accuracy by a vendor; and survey responses in
the Current Population Survey (CPS). 10 For each of these sources, we
reviewed documentation describing steps taken by the data managers to
ensure data reliability and tested the data for anomalies that could
indicate reliability concerns. We found each of the three sets of data
sufficiently reliable for the purposes of our review. The results of our
analysis of voter ID requirement effects on voter turnout cannot be
generalized beyond Kansas and Tennessee. We provide additional
details on the scope and steps of our analysis later in this report.
To determine how frequently provisional ballots were cast because of ID
reasons and counted during the 2012 election for Kansas and
Tennessee, the 2 selected states that modified voter ID requirements, we
analyzed data from the Election Assistance Commission’s (EAC) Election
cson
Administration and Voting Survey (EAVS) u the total number of ballots
of T on
ity
cast and the total numbernc.provisional 016
of v. C
, 2 ballots cast in the 2012 general
I
elections in thoseiance, 11gustalso analyzed 2012 statewide data
2 states. We 31
All
n Au
provided gritelection officials in the Kansas and Tennessee Secretaries of
by y
e
nte ron ithed o
v
State
blic I offices ch number of provisional ballots cast for ID reasons and
a
in Pu the16142 of provisional ballots cast for ID reasons that were counted,
cited o. 15- number
N by state. 12 To determine how provisional ballot use in Kansas and

10

The USEP’s database provides voter turnout data for eligible voters by calculating the
total number of people in each state who were at least 18 years old and who were likely to
be eligible to vote, after subtracting totals of people known to be ineligible, such as noncitizens and convicted felons in some states. The official voter records enhanced by a
vendor provide turnout information for registered voters. The vendor enhances the data by
cleaning them to improve reliability (e.g., by removing duplicate entries, deceased
registrants, and registrants who may have moved out of state) and by matching additional
variables for analysis from commercial sources. The CPS, conducted by the U.S. Census
Bureau, asks a nationwide sample of adults questions about their registered voter status
and whether they voted in the most recent election.

11
The Election Assistance Commission administers the biennial Election Administration
and Voting Survey, which is an instrument used to collect state-by-state data on the
administration of federal elections. The survey is divided into two parts. The first part
captures quantitative data pertaining to the National Voter Registration Act, the Uniformed
and Overseas Citizens Absentee Voting Act (UOCAVA), and other election administration
issues such as the counting of provisional ballots and poll worker recruitment. The second
part is the Statutory Overview, which asks state officials to respond to a series of openended questions about their states’ election laws, definitions, and procedures.
12

This included provisional ballots cast for ID reasons related to an ID requirement for all
eligible voters, not ID requirements for first-time voters who register by mail pursuant to
HAVA.

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Tennessee changed after those states’ voter ID laws were changed, we
analyzed EAVS data on the total number of ballots cast and the total
number of provisional ballots cast in the 2008 and 2012 general elections
in Kansas and Tennessee and in the 4 comparison states selected for
objective two. We used these data to calculate the provisional ballot
usage rate by state in 2008 and 2012. To assess the reliability of the
2008 and 2012 EAVS data as well as data provided to us by Kansas and
Tennessee election officials, we analyzed the completeness of EAVS
provisional ballot data for 2008 and 2012 and interviewed EAC officials
and officials from the Kansas and Tennessee Secretaries of State offices
regarding their data collection and quality control processes. We found
the data to be sufficiently reliable for the purposes of our review. Our
findings on provisional ballots are not generalizable beyond our specific
treatment and comparison states.

cson

To determine what challenges, if any, of Tuin using available information
exist
ity
at the federal and state levels v. C
. to estimate16 incidence of in-person voter
20 the
nc
ce, I gust 31,
fraud, we first developed a standard definition of in-person voter fraud by
llian
u
analyzing rity A court cases to determine how courts have
grelevanted on A
nte rcin-person voter fraud, as well as activities that are not
characterized v
blic I 42 a hi
in Pu considered to be encompassed by the term. 13 For the purposes of this
61
cited o. 15-1
N report, we have defined in-person voter fraud as involving a person who
(1) attempts to vote or votes; (2) in person at the polling place; and (3)
asserts an identity that is not the person’s own, whether it be that of a
fictional registered voter, dead registered voter, a false identity, or
whether the voter uses a fraudulent identification. We shared our
definition with Department of Justice (DOJ) and state election officials and
integrated their feedback, as appropriate. We also conducted a literature
review of relevant academic literature, organizational studies, peerreviewed journals, books, and other regularly cited research published
from 2004 through April 2014 to identify the extent to which these sources
contain data on in-person voter fraud. 14 We identified and reviewed more
than 300 studies to determine whether they (1) contained data related to
in-person voter fraud and (2) included a description of the methodology

13

This was necessary because there is no standard federal definition for in-person voter
fraud.
14

“Organizational studies” refers to those studies published by non-governmental
organizations, such as the Heritage Foundation and the Brennan Center for Justice.
Studies produced by state-level agencies are not included in the literature review, but are
discussed in our report.

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used for collecting the data related to in-person voter fraud. 15 We
identified five studies that met these criteria. Two GAO analysts and, as
applicable, a GAO statistician reviewed each of the five studies and
determined that the design, implementation, and analyses of the studies
were sufficiently sound to support the studies’ results and conclusions
based on generally accepted social science principles. We found that
these studies used various sources and methodologies in their efforts to
provide estimates on in-person voter fraud.
At the federal level, we identified federal databases that contain
information on investigations, prosecutions, and convictions of federal
crimes, including the Legal Information Office Network System (LIONS)
database, managed by DOJ’s Executive Office for United States
Attorneys (EOUSA); the Automated Case Tracking System II (ACTS II)
database, managed by DOJ’s Criminal Division;nthe Integrated Database,
cso
managed by the Federal Judicial Center Tu
of (FJC) in the federal judiciary;
. City
6
and the Oracle database managed by 201United States Sentencing
nc. v 31, the 16
e I
t
Commission (USSC)cin ,the federal judiciary. We reviewed each
n
ugus
Allia
database’s iassociated n A
gr ty ived o codebooks and interviewed relevant federal
te
ic In
officials from ch
Publ 6142 arthe four agencies who manage the databases to understand
in how,
cited o. 15-1 if at all, cases of in-person voter fraud are categorized and tracked
N within each database. On the basis of interviews with agency officials and
the review of relevant court cases we conducted to develop a definition
in-person voter fraud, we compiled a list of 14 possible federal statutory
provisions under which our definition of in-person voter fraud could be
prosecuted (see app. II).
At the state level, we interviewed election officials in 46 states and the
District of Columbia. 17 We corroborated the information we gathered
through these interviews by reviewing state statutes related to election
fraud and in-person voter fraud and the documentation that officials from
27 states provided to us related to the incidence of election fraud. We
reviewed the format and content of the documentation provided, as well

15

We excluded studies that reported on previously compiled data or anecdotal reports of
in-person voter fraud, including those reported in the media.

16

According to DOJ officials, while EOUSA manages LIONS, district U.S. Attorney offices
are responsible for maintaining the accuracy and integrity of the data.

17

We also contacted election officials from the 4 remaining states, but they declined to be
interviewed.

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as testimonial evidence from the original interviews and subsequent
correspondence with state officials. This review allowed us to better
understand the way in which the information was collected and compiled,
and to identify any potential limitations associated with the provided
information. We also reviewed how responsibility for addressing election
fraud was distributed among various state and local agencies, in an effort
to determine whether the information provided by the state represented a
complete account of the in-person voter fraud allegations, investigations,
prosecutions, or convictions that occurred within the state. More
information on our objectives, scope, and methodology can be found in
appendix II.
We conducted this performance audit from January 2013 to August 2014
in accordance with generally accepted government auditing standards.
Those standards require that we plan and perform the audit to obtain
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Background

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N The basic goal of the election system in the United States is that all

eligible voters have the opportunity to cast their votes and have their valid
ballots counted accurately. All levels of government share responsibility in
the U.S. election process, and the election system is highly decentralized.
States are responsible for the administration of their own elections as well
as federal elections. Accordingly, states regulate various aspects of
elections including registration procedures, absentee voting requirements,
early voting requirements, establishment of polling places, provision of
Election Day workers, testing and certification of voting equipment, and
counting and certification of the vote. 18 At the federal level, Congress has
the authority to affect the administration of elections in certain ways.
Congress’ authority to regulate elections derives from various
constitutional sources, depending on the type of election. 19 Congress has

18

As described by the Supreme Court, “the States have evolved comprehensive, and in
many respects complex, election codes regulating in most substantial ways, with respect
to both federal and state elections, the time, place, and manner of holding primary and
general elections, the registration and qualifications of voters, and the selection and
qualification of candidates.” Storer v. Brown, 415 U.S. 724, 730 (1974).

19

Congress’ authority to regulate congressional elections derives primarily from Article I,
Section 4, Clause 1 of the Constitution (known as the Elections Clause).

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enacted federal legislation to address voter registration, voter
identification, absentee voting, accessibility provisions for the elderly and
handicapped, and prohibitions against discriminatory practices, among
other issues.
Further, just as responsibility for the overall U.S. election process is
shared among various levels of government, the responsibility for
identifying and investigating allegations of fraud may be shared by local,
state, and federal authorities. Election fraud allegations may be reported
to local, county, or state election officials; law enforcement; or county or
state attorneys, among others. Depending on the state, any of a number
of authorities may have, or share, jurisdiction to investigate and prosecute
the allegations. Allegations of election fraud may also be investigated and
prosecuted at the federal level.

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of Tu
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Figure 1: The Voting Process

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Registration

States have established a variety of requirements for individuals to
present identification when they register to vote. With the exception of
North Dakota, all states and the District of Columbia generally require
citizens to register before voting. Typically, state eligibility provisions
require, at minimum, that a person be a U.S. citizen, at least 18 years of
age, and a resident of the state, with some states requiring a minimum
residency period. Citizens apply to register to vote in various ways, such
as at motor vehicle agencies, by mail, at local voter registrar offices, or
through third-parties. 20 Election officials process registration applications
and compile and maintain the list of registered voters to be used
throughout the administration of an election.

20

Federal law does not generally address third-party voter registration organizations, but
many states have enacted laws regulating how registration drives by third parties may be
conducted, by whom, and other aspects of voter registration efforts by nongovernmental
organizations.

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cited

Although voter registration is not a federal requirement, Congress has
passed two laws that regulate voter registration in those states that
require it. The National Voter Registration Act of 1993 (NVRA), also
known as the “motor voter” law, established registration procedures
designed, in part, to “increase the number of eligible citizens who register
to vote in elections for Federal office. . . protect the integrity of the
electoral process . . . [and] ensure that accurate and current voter
registration rolls are maintained.” 21 The NVRA expanded the number of
locations and opportunities for eligible citizens to apply to register to vote.
In addition to any other method of voter registration provided for under
state law, the NVRA prescribes three methods of registering voters for
federal elections: (1) when they obtain a driver’s license, (2) by mail using
the federal voter registration form provided by the EAC, or (3) at offices
that provide public assistance and services to persons with disabilities
and other state agencies and offices. 22 In addition to accepting the federal
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. 15No In 2002, Congress passed HAVA, which requires states to collect

specified types of identification from certain first-time voters who register
by mail and establish a single, uniform, statewide, computerized voter
registration list for conducting elections for federal office. 24 Under HAVA,
states must require that registrants who apply by mail and who have not
previously voted in a federal election in the state provide certain specified
types of identification with their mail application, and if they do not provide
such identification with their application, these first-time mail registrants

21

42 U.S.C. § 1973gg.

22

42 U.S.C. § 1973gg-2. Certain states are exempt from the NVRA, including North
Dakota—which has no voter registration requirement—and Idaho, Minnesota, New
Hampshire, Wisconsin, and Wyoming—which have election-day registration. The NVRA
does not apply to states where either (1) under law that is in effect continuously on and
after August 1, 1994, there is no voter registration requirement for any voter in the state
for a federal election or (2) under law that was is in effect continuously on and after, or
enacted prior to, August 1, 1994, all voters in the state may register to vote at the polling
place at the time of voting in a general election for federal office. Id.

23

42 U.S.C. §§ 1973gg-4(a)(2), 1973gg-7(b).

24

42 U.S.C. § 15483.

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are to provide the identification at the polls or a copy of such identification
when voting by mail. 25 Under HAVA, in order not to show identification
when voting, mail registrants must have provided either their driver’s
license number or at least the last four digits of their Social Security
number when applying to register, which must match with an existing
state identification record; or have provided in their application a copy of
the following specified identification:
a current and valid photo identification; or
a copy of a current utility bill, bank statement, government check,
paycheck, or other government documentation that shows the name
and address of the voter. 26
HAVA specifies that these are minimum requirements and should not be
construed to prevent states from establishingselection administration
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certain 31, specified provisions. 27
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25

Id. The NVRA also allows states to require all first-time voters who register by mail to
vote in person at the polling place, where the voter’s identity can be confirmed. 42 U.S.C.
§ 1973gg-4(c).

26

42 U.S.C. § 15483.

27

For example, Alaska law limits the types of acceptable forms of identification that firsttime voters who register by mail may provide in order to register if they do not have a
driver’s license or do not provide the last four digits of their Social Security number. Alaska
does not permit using a utility bill, bank statement, government check, paycheck, or other
government document that shows the name and address of the voter. Instead, Alaska
specifies that applicants may provide a state identification card, current and valid photo
identification, birth certificate, passport, or hunting and fishing license.

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Voting
Absentee Voting or
Early Voting

States have established alternatives for voters to cast a ballot other than
at the polls on Election Day, including absentee voting and early voting. 28
All states and the District of Columbia have provisions allowing voters to
cast their ballots before Election Day by voting absentee, with variations
on who may vote absentee, whether the voter needs to provide an
excuse, and the time frames for applying for and submitting absentee
ballots. 29 As of the 2012 general election, most states—35 and the District
of Columbia—provided an opportunity for voters to cast a ballot prior to
Election Day without providing an excuse, either by no-excuse absentee
voting or early voting, or both. 30 Some states also permitted registered
voters to apply for an absentee ballot on a permanent basis so those
voters automatically receive an absentee ballot in the mail prior to every
election without providing an excuse or reason for voting absentee.
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t reported in October 2012, in some
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31
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cited o. 15-1 their absentee ballot, or both. The identifying information that voters
N are required to provide when voting absentee varies—with some states
requiring that voters provide documentary identification, such as a driver’s
license number, Social Security number, or copy of an acceptable

28

Absentee voting is a process that allows citizens to cast a vote when they are unable to
vote at their precinct on Election Day and is generally conducted by mail. Early voting is
any process by which a voter may cast a ballot in person, without providing an excuse,
prior to Election Day, regardless of the name the state gives to that process. A state may
provide for both in-person absentee voting and early voting. For example, in Alaska, which
provides both, according to the Alaska Secretary of State’s website, the difference
between in-person absentee and early voting is that an early voter is already determined
to be eligible to vote at the time of voting, and thus the voter’s ballot is placed directly in
the ballot box to be counted and tabulated along with those of other eligible voters on
Election Day. With in-person absentee voting, the voter’s eligibility is not verified at the
time of voting, and thus the voter’s ballot is placed inside an absentee voting envelope—
pending subsequent verification—prior to being placed in the ballot box.

29

Examples of excuses a voter may provide for not voting on Election Day include being
sick, having a disability, being out of the country, or having religious commitments.

30

GAO-13-90R.

31

Id.

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document, and other states requiring information that does not involve an
underlying document, such as the voter’s signature or date of birth.
In addition to allowing absentee voting, some states allow early voting. In
general, early voting allows voters from any precinct in the jurisdiction to
cast their votes in person without providing an excuse before Election
Day either at one specific location or at one of several locations. Voters
who choose to vote in-person during the designated early voting period
may be subject to the same state voter identification requirements as
voters who vote in-person on Election Day. As we reported in January
2012, implementation and characteristics of early voting—such as the
dates, times, and locations—also vary among states, and in some cases,
among the jurisdictions within a state. 32 Information on the demographic
characteristics of early voters can be found in appendix I.

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In-Person Voting on
Election Day

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As of June 2014, 33 states had enacted Tu
ity o requirements for voters to show
some form of ID at the polls . v.Election 016 33 Such ID requirements
on C
2 Day.
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have been cited las nce,
an attempt to help ensure the integrity of the voting
s
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process onity
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Inte rch ve
attempt to vote. iFourteen states and the District of Columbia do not have
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32

GAO, Elections: Views on Implementing Federal Elections on a Weekend, GAO-12-69
(Washington, D.C.: Jan. 12, 2012).
33

These requirements are in addition to identification requirements applicable to first-time
voters who register by mail pursuant to HAVA. The states are Alabama, Alaska, Arizona,
Arkansas, Connecticut, Delaware, Florida, Georgia, Hawaii, Idaho, Indiana, Kansas,
Kentucky, Louisiana, Michigan, Mississippi, Missouri, Montana, New Hampshire, New
Mexico, North Carolina, North Dakota, Ohio, Oklahoma, Pennsylvania, Rhode Island,
South Carolina, South Dakota, Tennessee, Texas, Utah, Virginia, and Wisconsin. These
states include those with laws that are either currently in effect or scheduled to go into
effect prior to a future election pursuant to state legislation, including those laws that have
been the subject of litigation. For example, the Federal District Court for the Eastern
District of Wisconsin recently found Wisconsin’s voter ID law unconstitutional, Frank v.
Walker, 2014 WL 1775432 (E.D. Wis. Apr. 29, 2104), as did the Commonwealth Court in
Pennsylvania with respect to that state’s ID law, Applewhite v. Commonwealth, 2014 WL
184988 (Pa. Commw. Ct. Jan. 17, 2014). Many of these state voter identification laws
have been the subject of controversy and litigation. The Supreme Court addressed the
constitutionality of Indiana’s voter identification law in 2008 in Crawford v. Marion County
Election Board, 553 U.S. 181, and upheld the law. The lead opinion identified several
purported state interests justifying Indiana’s law, such as deterring and detecting voter
fraud, justifying the burdens that the law imposed on voters and potential voters. The
dissent, in contrast, found that given no evidence of in-person voter fraud in the state,
Indiana had failed to justify the practical limitations on voting rights created by the law. As
of June 2014, litigation was pending in Arkansas, North Carolina, Oklahoma, Texas and
Wisconsin.

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documentary identification requirements. 34 Figure 2 shows the year in
which states enacted identification requirements since HAVA was
enacted, as well as the year when states made changes to their
identification requirements that resulted in a change in the type of
acceptable ID (i.e., photo or non-photo) or the acceptable issuing
authority (i.e., generally government-issued or nongovernment-issued). 35
Figure 2: States that Enacted Identification Requirements or Changed Acceptable
Type of Document or Issuing Authority, by Year, from 2002 through 2013

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Notes: Dates listed are generally when states enacted provisions, as opposed to when provisions
went into effect or are legislated to go into effect. “At HAVA” indicates provisions were in effect at the
time HAVA was enacted. States are repeated when they enacted laws that changed the type of
document accepted (non-photo to photo) or acceptable issuing authority (nongovernment to generally
government issued only). Colorado, Oregon and Washington vote-by-mail states and are not included
in this figure.

34

The remaining three states, Colorado, Oregon and Washington, are vote-by–mail states
and do not require voters to provide identification when casting a ballot by mail; although
Colorado and Washington have identification requirements for voters who opt to vote in
person. States may have additional verification requirements, such as signature matching
at the polling place.

35

These include state ID requirements for all eligible voters at the polls on Election Day. In
addition to enacting new identification requirements and amending the type of document
accepted and acceptable issuing authority, states also changed the processes for voters
who do not present acceptable identification on Election Day, generally concurrent with
these other changes.

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a

In 2006, Missouri also enacted a voter ID requirement that required government-issued photo
identification to vote, but that provision was held to be unconstitutional by the Missouri Supreme
Court and is no longer in effect.
b

Michigan’s voter ID law was enacted prior to HAVA, but due to an opinion by the Michigan Attorney
General concluding that the requirement was unconstitutional, it was not enforced until after it was
held to be constitutional by the Supreme Court of Michigan in 2007.
c

Rhode Island’s voter ID law, enacted in 2011, legislated additional requirements to go into effect in
2014. These changes will require photo identification only, as opposed to allowing documents that do
not include a photograph, such as a birth certificate.

d

Wisconsin enacted a new voter ID law that as of June 2014 was enjoined by federal and Wisconsin
state courts.
e

New Hampshire’s voter ID law, which was enacted in 2012 and amended in 2013, provides for
additional changes to go into effect in 2015.

f

Pennsylvania’s voter ID law was partially in effect for the 2012 election but has been permanently
enjoined by the Pennsylvania Commonwealth Court. The Pennsylvania Governor issued a statement
that the commonwealth will not pursue an appeal to the Pennsylvania Supreme Court to overturn the
Commonwealth Court’s decision.

on
T cs
of IDulaws beyond those required by
Of those states that have enacted ivoter 6
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nc. v ID31, 201
I
HAVA, the forms of acceptable
vary. Specifically, 20 states have
st
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enacted requirements that uguID provided contain a photograph of the
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voter, whereashived
c Int arc 13 states have enacted requirements for a voter to
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provide identifying documentation that does not contain a photograph,
d in 15-1614the voter’s Social Security card or a utility bill or a bank statement
ite
c
No. such as
36

with the voter’s name and address on it. See figure 3 for a map of states
that have enacted voter identification requirements, which may be in
effect or scheduled to go into effect pursuant to legislation, regardless of
litigation status, as of June 2014.

36

While the ID requirements generally apply to all voters, states may have exceptions for
certain categories of voters. For example, in Kansas, voters with a permanent physical
disability or those whose religious beliefs prohibit photographic identification are exempt
from the photographic ID requirement. In Indiana, a voter who votes in person at a
precinct polling place that is located at a state-licensed care facility where the voter
resides is not required to provide proof of ID.

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Figure 3: Map of States that Have Enacted Voter Identification (ID) Requirements, as of June 2014

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Notes:
This map includes states with enacted requirements that are currently in effect or scheduled to go into
effect by legislation, regardless of the status of litigation. Some state laws may be enjoined pursuant
to court order. In particular, as of June 2014, Pennsylvania’s ID law was enjoined, Applewhite v.
Commonwealth, 2014 WL 184988 (Pa. Commw. Ct. Jan. 17, 2014), as was Wisconsin’s, Frank v.
Walker, 2014 WL 1775432 (E.D. Wis. Apr. 29, 2104). New Hampshire’s and North Carolina’s new
voter ID laws are scheduled to go into effect in 2015 and 2016, respectively.
a

Colorado, Oregon and Washington are vote-by-mail states, but laws in these states require that
there be places for voters to cast a ballot in person. Colorado law provides that voters who do not
have acceptable identification may cast a provisional ballot. If it is verified that a voter who cast a
provisional ballot is eligible to vote based on information the voter provided with the provisional ballot

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and a check of state databases, the provisional ballot will be counted. Oregon does not have
identification requirements for voters who cast a ballot by mail or in person. Washington law has
identification requirements applicable to voters who cast a ballot in-person, requiring that voters
provide photo identification, or vote by provisional ballot (which will be counted if the signature on the
ballot declaration matches the signature in the voter’s registration record). For voters who cast a
ballot by mail, the ballot will be counted if the signature on the ballot declaration matches the
signature in the voter’s registration record; there are no additional documentary identification
requirements.
b

In certain states, this exception applies to student IDs only, whereas in other states any identification
issued by an education institution may be acceptable (e.g., employee ID). North Dakota additionally
provides an exception for a long term care identification certificate (provided by a North Dakota
facility) and Pennsylvania provides an exception for identification issued by a Pennsylvania care
facility.

Provisional Ballots

Under HAVA, states are required to permit individuals, under certain
circumstances, to cast a provisional ballot in federal elections. For
example, voters who claim to be eligible to vote and registered in the
n
jurisdiction they desire to vote in but whose cso
names do not appear on the
of Tu to cast provisional ballots in
polling place registration list are to ibe allowed
. C ty 016
nc. v a 31, 2does not have the requisite ID at
I
a federal election. In addition, if voter
st
nce,
the polls, HAVA lrequires Augu voter be allowed to cast a provisional
A lia on that the
ity
r
ballot. teg HAVA, election officials receiving provisional voter
n Under ived
blic I 42 archto determine whether such individuals are eligible to vote
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ited o. 15-16 state law. If an individual is determined to be eligible, HAVA
c
under
N
specifies that such individual’s provisional ballot be counted as a vote in
that election in accordance with state law.
In states with voter ID requirements, there is variety in how states
administer the provisional ballot processes when a voter does not have
acceptable ID, including the way in which states determine whether the
ballot will be counted. Of the 33 states that have an identification
requirement for all eligible voters, 18 provide casting a provisional ballot
as the only process for voters without acceptable identification. 37 Of these
18 states, 15 require some or all voters to provide the election authority

37

Of the remaining 15 states, 1 state does not provide an alternative process if a voter
does not have acceptable ID; 10 allow the voter to verify his or her identity and cast a
regular ballot; and 4 allow for a voter’s identity to be verified by elections officials and vote
a regular ballot; and, of those 4, 3 additionally allow for the voter to cast a provisional
ballot.

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with acceptable identification within a specified time period after the
election as the only means to have the provisional ballot counted. 38

Post-election Activities

Following the close of the polls on Election Day, election officials and poll
workers complete steps such as securing equipment and ballots,
transferring votes to a central location for counting and determining the
outcome of the election. Votes counted include those cast on Election
Day, absentee ballots, early votes (where applicable), and provisional
ballots. While preliminary results are available usually by the evening of
Election Day, the certified results are generally not available until days
later.

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38

In Ohio, for example, if a voter does not provide acceptable identification the voter may
cast a provisional ballot and either (1) write the voter’s driver’s license or state
identification card number or the last four digits of the voter’s social security number on
the provisional ballot envelope; or (2) appear at the office of the board of elections not
later than the seventh day after Election Day and provide the required identification.

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Studies Show That
Most Registered
Voters Have StateIssued IDs; Direct
Costs to Obtain
Such IDs Vary
Among States
Studies Report that
We reviewed 10 studies that estimated rates of ownership of driver’s
licenses or state-issued IDs in selected states or nationwide. 39 Nine of
Majority of Registered
these studies of driver’s license and state ID son
Voters Have a Driver’s
c ownership in selected states
and the one nationwide survey showedfthat, depending upon the study,
o Tu
ity
License or State-Issued
6
estimated ownership rates c. v. C registered voters ranged from 84 to 95
namong31, 201
I
ID; ID Ownership Rates
percent, as shown ince, 1. 40 st example, in one of the studies, the
table guFor
n
u
Allia
North Carolina State Board of Elections estimated that up to 95 percent of
Vary by Race and
grity ived on A
nte voters statewide had a driver’s license or state-issued ID as of
registered
blic I 42 arch
Ethnic Group
1
in Pu
cited

6
March
15-1 2013, based on an analysis the board completed that matched
No.

39

A nationwide survey of 2012 general election voters found that between 84 and 90
percent of voters reported they used a driver’s license or state ID card when voting in
states that require voters to show photo ID (Stewart, 2013). The survey also found that 64
percent of voters reported using a driver’s license or state ID card when voting in states
where acceptable ID includes nonphoto ID. We reviewed three additional studies related
to ID ownership, but excluded them because we determined there was either insufficient
information provided about the study’s methodology or implementation, or the study was
outside the scope of our work. Those studies were: Barreto, Matt A.; Stephen A. Nuno,
and Gabriel R. Sanchez. “Voter ID Requirements and the Disenfranchisement of Latino,
Black, and Asian Voters.” Paper presented at the 2007 American Political Science
Association Annual Conference, Chicago, IL, September 1, 2007; McDonald, Michael P.
“May I See Your ID, Please? Measuring the Number of Eligible Voters with Photo
Identification.” Paper presented at the California Institute of Technology and
Massachusetts Institute of Technology Voter Identification and Registration Conference,
Cambridge, MA, October 2006; and Sanchez, Gabriel R. “The Disproportionate Impact of
Photo-ID Laws on the Minority Electorate,” 2011. In Latino Decisions, accessed April 15,
2014, http://www.latinodecisions.com/blog/2011/05/24/the-disproportionate-impact-ofstringent-voter-id-laws.
40

We had two GAO social scientists review each of the 10 studies to determine whether
the design, implementation, and analyses of the study were sufficiently sound to support
the study’s results and conclusions based on generally accepted social science principles.

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voter registration and Department of Motor Vehicles (DMV) records. 41 In
another study, focused on Indiana, researchers used a survey of
registered voters and, according to that survey, estimated that 84 percent
of registered voters statewide had a valid photo ID that could be used for
voting purposes as of October 2007. 42 Three of the 10 studies also
estimated ownership of selected IDs among individuals eligible to vote,
but not necessarily registered to vote, and 2 of 3 reported slightly lower ID
ownership rates among that population as compared with ownership rates
for registered voters. The 10 studies we reviewed used either database
queries or surveys to estimate selected ID ownership rates. Specifically, 6
of the 10 studies relied upon database queries where the researchers
matched voter registration records to ID databases, such as driver’s
license and state ID databases, to estimate ID ownership rates. Four of
the 10 studies used surveys to elicit responses on ID ownership from
potential voters.
son

f Tuc
ity o 6
1
. v. C
Table 1: Summary of Findings from Studies That Estimate Selected Identification (ID) 20
, Inc st 31, Ownership
ce
n
ugu
Allia
Study author
grity ived on A
te
and date
Results: ID ownership among population
h
ic In
cResults: ID
b
Publ 6142 ar ownership overalla
Scope
Methods
published
sub-groups
in
d
1
cite Database51
Ansolabehere.
Texas
86 percent of all
Holders of driver’s license, state ID card, or
No. queries
matching records of
registered voters to
driver’s license/state
ID card or gun permit
records; results as of
April 2012

June 2012

Barreto, Nuño,
and Sanchez.
January 2009

Indiana

registered voters had
gun permits:
driver’s license, state ID - 89 percent of registered Whites
card, or gun permit
- 83 percent of registered Hispanics
- 79 percent of registered African-Americans

Survey of registered
voters and adult
non-registered
residents, completed
October 2007

- 84 percent of all
registered voters had
c
valid photo ID
- 81 percent of all
eligible adults had valid
photo ID

- 85 percent of all registered White voters and
83 percent of eligible White adults had valid
photo ID
- 81 percent of all registered AfricanAmerican voters and 72 percent of eligible
African-American adults had valid photo ID

41

North Carolina State Board of Elections (April 2013). As of June 2014, North Carolina
voters were not required to provide documentation at the polls in order to vote on Election
Day. However, the state legislature passed a voter ID statute in August 2013 that is
scheduled by legislation to go into effect in 2016.

42
Barreto, Nuño, Sanchez (January 2009). Indiana voters must show a governmentissued photo ID at the polls on Election Day. The ID requirement was implemented in
2005.

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Study author
and date
published

Scope

Methods

Results: ID
a
ownership overall

Results: ID ownership among population
b
sub-groups

Barreto and
Sanchez.
April 2012

Milwaukee
County, WI

Survey of registered
voters and adult
non-registered
residents, completed
January 2012

91 percent of all
registered and 91
percent of eligible voters
had acceptable, nonf
expired photo ID

- 94 percent of registered White and 93
percent of eligible White voters had
acceptable, non-expired photo ID
- 85 percent of registered African-American
j
and 87 percent of eligible African-American
voters had acceptable, non-expired photo ID
- 89 percent of registered Latino and 85
percent of eligible Latino voters had
acceptable, non-expired photo ID

Barreto,
Sanchez, and
Walker.
July 2012

Pennsylvania

Survey of registered
voters and adult
non-registered
residents, completed
July 2012

- 87 percent of
registered voters had
d
valid photo ID
- 86 percent of eligible
voters had valid
photo ID

- 88 percent of registered and 86 percent of
eligible Whites had valid photo ID
- 86 percent of registered and 87 percent of
e
eligible African-Americans had valid photo ID
- 83 percent ofn
o registered and 82 percent of
e
eligible ucs
THispanics had valid photo ID

Beatty.
April 2012

Wisconsin

f
ity o
. v. C -912016 of White registered voters had a
Database queries
89 percent ,of nc
, percent
I all
sa 31
nce
matching records of
registered voters had t
Alliadriver’s Augu or valid driver’s license or state ID card
DMV-issued driver’s rity valid d on license
-84 percent of African-American registered
eg
ve
licenses and state ID rcstate ID
c Int
voters had a valid driver’s license or state ID
bliregistered a hi
u
e
2
card
in Pwith -1
dcards recordsg614
ite voter . 15
c
-75 percent of Hispanic registered voters had
No
e
a valid driver’s license or state ID card
-84 percent of Asian-American registered
voters had a valid driver’s license or state ID
e
card
-94 percent of Native American registered
voters had a valid driver’s license or state
e
ID card

Bullock III and
Hood III.
March 2007

Georgia

Database queries
matching records of
DMV-issued photo ID
(driver’s license and
state ID cards) with
registered voter
records; results as of
October 2006

Hood III.
May 2012

Wisconsin

Database queries
91 percent of all
matching records of
registered voters had
DMV-issued driver’s
valid identification
licenses and state ID
cards with registered
voter records; results as
of June 2012

Page 23

93 percent of all
registered voters had
valid identification

Probability of registered voter not possessing
a valid driver’s license or state ID card, by
race:
- White: 0.037
e
- African-American: 0.068
e
- Hispanic: 0.073
e
- Asian-American: 0.042
Did not analyze results by population
sub-groups

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Study author
and date
published

Results: ID
a
ownership overall

Scope

Methods

North Carolina
State Board of
Elections.
April 2013

North Carolina

Database queries
95 percent of records
h
matching records of
matched
DMV-issued driver’s
licenses and state ID
cards with registered
voter records; results as
of March 2013

Stewart.
June 2012

South Carolina

Results: ID ownership among population
b
sub-groups

Database queries
matching records of
DMV-issued driver’s
licenses and state ID
cards, and passport and
military IDs with
registered voter records;
grity
results as of Aprile
c Int 2012

i
2
Publ
d in 15-1614
ite
c
No.

Page 24

Numbers of registered voters who did not
match ID records after all queries, by race
(rates not provided in study):
- White: 172,613
- African-American: 107,681
- Asian-American: 4,067
- Native American or Alaska
Native: 3,773
- Other: 7,663
- Two or more races: 4,383
- Undesignated: 18,463

93 percent of active
Percentage of active registered voters
registered voters
possessing a valid driver’s license or state ID
son
possessed a valid
card, byuc
of T race:
driver’s license or state ityWhite: 94.5 percent
. v. C - 2016
ID card; 95 percent of
, Inc voters 31,African American: 90.5 percent
activence
registered
st Allia ona Augu
- Hispanic: 90.0 percent
possessed valid
d
driver’s license, state ID - Native American: 89.9 percent
hive
arccard, passport, or
- Mixed: 85.6 percent
military ID
- Other: 87.1 percent
Percentage of active registered voters
possessing a valid driver’s license, state ID
card, passport, or military ID, by race:
- White: 96.1 percent
e
- African-American: 91.7 percent
e
- Hispanic: 93.3 percent
e
- Native American: 91.7 percent
e
- Mixed: 87.7 percent
e
- Other: 91.6 percent

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Study author
and date
published
Stewart.
Fall 2013

Scope

Methods

Nationwide

Survey of registered
voters in each state and
the District of Columbia
March 2012

Results: ID
a
ownership overall

Results: ID ownership among population
b
sub-groups

91 percent of registered
voters had driver’s
license; 80 percent had
valid license;
41 percent of registered
voters had passport;
35 percent had valid
i
passport

- 93 percent of White registered voters had
any driver’s license, and 84 percent had a
valid license
- 79 percent of African American registered
voters had any driver’s license, and 63
percent had a valid license
- 90 percent of Hispanic registered voters had
any license, and 73 percent had a valid
license
- 41 percent of White registered voters had
any passport, and 35 percent had a valid
passport
- 28 percent of African-American registered
voters had any passport, and 25 percent had
on
a valid passport
Tucs
ofpercent of Hispanic registered voters had
ty49 6
v. Ci any passport, and 42 percent had a valid
201
passport
t 31,
s

nc.
ce, I gu
n
Allia on Au
Source: GAO analysis of studies that estimate ID ownership rates. | GAO-14-634 grity
d
te
ic In
Notes: Full citations hi these studies are listed in appendix III.
c forve
Publ 6142 ar noted, all estimates are significant at least at the 0.05 level of statistical
in aUnless otherwise
cited o. 15-1
N significance.
b

Unless otherwise noted, all sub-group estimates and differences between White and other racial or
ethnic groups are significant at least at the 0.05 level of statistical significance.
c

Valid photo ID in Indiana, as defined in the survey, included a current driver’s license, state ID card,
or other government issued photo ID that includes the voter’s full legal name.

d

Valid photo ID in Pennsylvania, as defined in the survey, included non-expired photo IDs that listed
the voter’s name substantially conforming to the name on the voter registration roll.

e

According to the study, difference from White significance not reported.

f

Acceptable, non-expired photo ID in Wisconsin, as defined in the survey, included driver’s license,
state ID, military ID and passport, if they were current or had expired only after the previous statewide
general election.

g

The date of the database queries is not evident in the study.

h

In order to determine the voters who have a North Carolina DMV-issued photo ID, the State Board of
Elections used database queries to compare voter records with records in the North Carolina
Department of Motor Vehicles customer database. The board used 29 queries, such as matches
based on exact first and last name and Social Security number or driver’s license number and date of
birth. Using these queries, as voters were matched with records in the North Carolina Department of
Motor Vehicles database, their records were removed from further queries, and only the remaining
unmatched State Board of Elections records were used in subsequent queries. The State Board of
Elections reported that 81 percent of records matched based on the first query only—exact first and
last name and North Carolina Department of Motor Vehicles customer number—and 95 percent of
records matched based on the end result of completing all 29 queries.
i

Valid license is defined in this study as a driver’s license that had not expired, showed the name
under which the voter was registered, and listed the voter’s current address. Valid passport is defined
as one that had not expired and showed the name under which the voter was registered. The
researchers determined voters with valid and non-valid driver’s licenses and passports by including
survey questions that asked respondents about each of these circumstances.

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As shown in Table 1, estimates of ID ownership rates among racial and
ethnic groups varied across the nine studies that analyzed such data. For
example, according to seven of the studies, ID ownership among AfricanAmerican registered voters was lower than among White registered
voters in the population evaluated—nationwide, Georgia, Indiana, South
Carolina, Texas, Wisconsin statewide, and Milwaukee County in
Wisconsin. The eighth study found similar rates of ID ownership statewide
between African-Americans and Whites in Pennsylvania, and the ninth
study did not estimate rates of ownership among these demographic
groups in North Carolina. ID ownership rates among Hispanic registered
voters were also estimated to be lower than those of White registered
voters in seven of the studies. The remaining three studies did not
provide estimates of ID ownership rates among Hispanic registered
voters.

cson

Three studies included analysis thatyidentified various factors that may
of Tu
. Cit 20studies did not provide analysis
affect ID ownership rates; the v
remaining 6
Inc. t 31, 1
of factors potentially ce,
associated with ID ownership. The studies that
llian
ugus
analyzedgrity A reportedA
factors d on several findings, including the following:
e

t
hive
ic In
2 arc
Publ Transportation. Bareto and others (2012) identified one factor that
in
614
cited o. 15-1
could affect ID ownership rates as access to transportation. In
N

Pennsylvania, among eligible voters, 41.6 percent of individuals who
reported that they do not have regular access to any kind of
transportation reported lacking a valid photo ID, and 29.7 percent of
those who reported not having a car, but reported access to some
other kind of transportation, such as a bus, bicycle, or train, also
reported lacking a valid ID. In comparison, 11.1 percent of those who
reported having regular access to a car also reported lacking a valid
ID.
Valid or expired IDs. Bareto and others (2012) conducted analyses
to determine if the rate of ownership of IDs was affected by whether
respondents reported that their ID was valid or had expired. The
authors found that large percentages of eligible voters in
Pennsylvania stated in survey responses that they owned photo ID
(98.6 percent). However, when asked follow-up questions about
whether the photo ID had an expiration date and was current, the
percentage of eligible voters with a non-expired photo ID dropped to
87 percent. Similarly, Stewart (2013) reported that estimated rates of
reported driver’s license ownership declined by 11 percent nationwide
(from 91 to 80 percent) when considering if the license was expired,
or showed a different name or address than the one they had
registered under.

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Possession of underlying documents. Bareto and others (2012)
identified possession of required underlying documents as a factor
that may affect ID ownership rates. According to their analysis of
survey responses, an estimated 1.7 million eligible Pennsylvanians
lacked necessary documentation to obtain valid photo ID as of July
2012. Necessary documentation included a proof of citizenship,
identity, and Pennsylvania residency. Similarly, Bareto and Sanchez
(2012) reported that an estimated 92,000 eligible voters in Milwaukee
County, Wisconsin lacked the necessary documentary proof of
citizenship, identity, and residency needed to apply for a Wisconsin
driver’s license or state ID card.
The studies that estimate ID ownership rates are subject to limitations,
based on our review. First, the results of the nine state-level studies
cannot be generalized beyond the states evaluated, as the results of
cson
those studies were based on state-specific data. Conversely, the
of Tu
remaining study, which was basedity a nationwide survey, provides an
. v. C on 016
, I a st 31, not
estimate for the nation as ncwhole, but2 for individual states. A second
u
ance Au studies that use surveys to estimate
limitation isity Alli to those g
specific
grrates.ved on of the public where respondents are asked to
te
ownership rchi Surveys
ic In
a
Publ 6142 whether or not they have valid identification, are registered to
in self-report
ited o. 15-1 or have voted are dependent on the extent to which respondents
c
N vote,
provide accurate responses, a fact that may lead to misrepresentations. 43
Instead of relying on respondents’ self-reporting, in one study we
reviewed, the authors attempted to address possible inaccuracies in
survey respondents’ reports of their voter registration status by obtaining
a sample of registered voters from the state’s public statewide voter file
and cross-checking the list with the Secretary of State’s office to verify
registration status. Through this effort, the authors were able to validate
the sample voters’ reported registration status. However, the authors did
not similarly validate survey respondents’ reports on whether or not they
owned valid ID. Studies that match voter registration records with driver’s
license or state-issued ID records rely on official records rather than
potentially inaccurate information provided by survey respondents.
However, official lists of registered voters may include registered voters
who are ineligible to vote, because of reasons such as moving out of a

43

Stephen Ansolabehere and Eitan Hersh, “Validation: What Big Data Reveal about
Survey Misreporting and the Real Electorate,” Political Analysis 20 (2012): 437-459.

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jurisdiction, death, or a felony conviction. Voter registration records may
not reflect these changes in eligibility status. 44

Direct Costs to Obtain
State-Issued ID Vary
by State

Of the 33 states that had enacted a voter identification requirement as of
June 2014, 17 states have requirements for voters to present photo or
government issued ID at the polls prior to voting and do not allow voters
to affirm their own identity in order to cast a regular ballot. The costs and
requirements to obtain certain forms of ID, including a driver’s license,
nondriver state ID, or free state ID, vary by state. 45 All 17 states allow a
driver’s license or state-issued nondriver ID, among the most common
types of ID presented to vote, as an acceptable form of ID. 46 Sixteen of
the 17 states also provide a free ID to eligible voters. 47 However, there
may be costs associated with obtaining the documents citizens must
present to obtain a free ID. See figure 4 and appendix IV for more
cson

of Tu
. City 2016
nc. v
ce, I gust 31,
n
u
Allia
grity ived on A
nte Ansolabehere and Eitan Hersh, “The Quality of State Voter Registration
44 c I
i
blStephen arch
in Pu Records:42
d
161 A State-by-State Analysis.” Working paper, Cal-Tech/MIT Voting Technology
cite
Project
. 15- and the Institute for Quantitative Social Science, Harvard University, July 14, 2010.
No
45

We selected states whose voter ID requirements fell into one of three categories (1)
photo only, government issued; (2) photo only, can be nongovernment issued; (3)
nonphoto, government issued. We also excluded states that allow all voters without ID to
cast a regular ballot by affirming their own identity at the polling place, since there would
be no cost to the voter in this situation. For example, in Tennessee, a voter who is indigent
and unable to obtain proof of identification without payment of a fee or a voter who has a
religious objection to being photographed may execute an affidavit of identity and then be
permitted to vote. States requiring government-issued ID include those where there is an
exception for a school ID.

46

Additional ID documents that meet state voter ID requirements may include handgun
permits, student ID, and tribal ID, among others. In some states, certain populations may
be exempt from the requirement that acceptable identification contain a photograph of the
voter; for example, in Pennsylvania, if the voter has a religious objection to being
photographed, a valid-without-photo driver’s license or a valid-without-photo identification
card issued by the Department of Transportation may be used. Certain federal IDs are
also allowed, but the cost of those IDs is standard across states. A U.S. passport can be
obtained for $110 plus a $25 processing fee. A passport card, which may be used to enter
the United States from Canada, Mexico, the Caribbean, and Bermuda at land border
crossings or sea ports of entry, costs $30 to $55 plus a $25 processing fee. Members of
the U.S. military can obtain a uniformed services ID card free of charge.

47

Pennsylvania’s voter ID was permanently enjoined on January 14, 2014, by the
Pennsylvania Commonwealth Court. Applewhite v. Commonwealth, 2014 WL 184988 (Pa.
Commw. Ct. Jan. 17, 2014). This injunction extended to issuance of free voter ID by the
Pennsylvania Department of Transportation and Department of State.

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information about state ID requirements and the associated direct costs of
selected IDs, as of July 2014.

cson
of Tu
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6
nc. v 31, 201
ce, I gust
n
u
Allia
grity ived on A
nte rch
blic I
a
in Pu -16142
ited o. 15
c
N

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Interactive graphic Figure 4: License and Nondriver State Identi cation (ID) Costs in Selected States,
as of July 2014

Wash.
Mont.

Maine

N.Dak.
Minn.

Ore.
Idaho

Vt.
Wis.d

S.Dak.
Wyo.

Nev.

Mich.

Nebr.

Iowa

Ohio
cson
Md.
Ind.
of Tu
ity
W.Va.
Colo.
16
. v. C
Mo.
, Inc st 31, 20
Kans.
Va.
nce
Ky.
Allia on Augu
y
d
egrit
N.C.
c Int archive
i
Tenn.
Publ 6142
Okla.
Ariz.
in
Ark.
cited N.Mex. 5-1
1
S.C.
No.
Miss.
Tex.

N.H.
Mass.
Conn.
R.I.

Pa.c
Ill.

Utah

Calif.

N.Y.

Ala.

N.J.
Del.
D.C.

Ga.

La.

Fla.b
States with (1) photo only, government issued ID;(2) photo
only, can be non-government issued ID; or (3) nonphoto,
government issued ID requirementsa
States that offer a free form of voter identification
Source: GAO analysis of state information and data; Map Resources (map). | GAO-14-634

Note: States with voter ID requirements that allow all voters to affirm their own identity at the polls and
vote a regular ballot were excluded from our analysis.
The “nondriver identification” category does not include nondriver ID issued for voting purposes.
aAs

of June 2014, in effect or legislated to go into effect, regardless of litigation status.
Government-issued ID includes states where there is an exception for a school ID.
bFlorida

allows as acceptable identification photo ID that may be nongovernment issued.

cPennsylvania’s

voter ID law was partially in effect for the 2012 election but has been permanently
enjoined by the Pennsylvania Commonwealth Court. Pennsylvania’s Governor issued a statement
that the commonwealth will not pursue an appeal to the Pennsylvania Supreme Court to overturn the
Commonwealth Court’s decision.

dWisconsin

enacted a new voter ID law that, as of June 2014, was enjoined by federal and Wisconsin
state courts.
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The direct costs to obtain an ID that meets state voter ID requirements
and the terms of acceptable IDs vary by state. Specifically, states may
have different licenses based on age of the applicant and may provide a
range of options with regard to the length of time a driver’s license or
other form of ID is valid. States may also charge other associated fees for
drivers, which can affect the cost to the voter. For example, drivers in
North Carolina pay $32 for an 8 year driver’s license while drivers in
Rhode Island pay $32 for a driver’s license that is valid for a maximum of
5 years and an additional $26.50 fee for the required road test. 48 Citizens
seeking to obtain a nondriver ID in Georgia can choose from either a 5year ID card for $20 or an 8-year ID card for $32, and Kansas offers a 6year nondriver ID for $14, plus an $8 photo fee.
A voter may be required to present documentation to obtain a driver’s
license, a nondriver ID, or a free ID. The typeson documents that a voter
cs of
would need to present to obtain a driver’s license, a nondriver ID, or a
of Tu
City
6
free ID vary by state and could .include2various combinations of
nc. v 31, 01
I
t
c provideusome examples:
documents. Below wee,
g s
llian

Au
yA
egrit ived on
ntobtain chdriver’s license in Indiana, a driver must provide various
I
blicTo
ar a
in Pu -16142of documentation, including proof of identity; identity documents
forms
d
cite
15 may include a U.S. birth certificate, a U.S. passport, or a U.S.
No.
consular report of birth abroad.
In Kansas, any citizen can obtain a nondriver state ID at the
Department of Motor Vehicles by providing proof of identity and
Kansas residency. 49
To obtain a free ID in Alabama, voters without a photo ID are required
to provide a nonphoto ID with full legal name and date of birth,
documentation proving they are registered to vote in the state, and

48

Rhode Island charges a $32 fee for an individual’s first license and license renewals are
$41.50.

49

To fulfill the identity requirement, birth certificates are also available at no cost in Kansas
to enable an individual to assert his or her identity to obtain an ID without incurring any
direct costs. Kansas residency may be established using a utility bill, mail from a financial
institution, a Kansas Voter Registration Card, educational institution transcript forms or
grade cards for the current school year, a letter from a social welfare institution, or an
identification certificate issued by the Kansas Department of Corrections to an offender,
among others.

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documentation showing name and address as reflected in the voter
registration record. 50
In general, examples of types of documents individuals can present to
obtain a driver’s license, nondriver state ID, or free ID could include a
birth certificate, Social Security card, or other proof of identification or
residency. Individuals may already have these documents, which can be
used for other purposes, such as for enrolling in school, obtaining a
passport, and obtaining a marriage certificate, among others. For
individuals without these documents, the cost to obtain one of these
documents to establish identity varies by state. Table 2 provides
information on the costs, as of July 2014, of one type of document—the
birth certificate—which, among the 17 states, is a common type of
document individuals could present, among others, to obtain a driver’s
license, non-driver state ID, or free ID. 51
son

f Tuc
ity o 6
v. C 201
Table 2: Cost to Obtain BirthInc.
,
, Certificate by State, as of July 2014
st 31
nce
Allia on Augu
State egrity
Cost of birth certificate
nt
ved
a
Alabama
$15
blic I 42 archi
1
in Pu Arkansas
6
$12
cited o. 15-1
N
Florida
$9
Georgia
Indiana
Kansas

$25
$10
b

$15

50

According to the Alabama Secretary of State’s legal counsel, a voter obtaining a free ID
from the Alabama Secretary of State’s office or a county board of registrar’s office does
not need to independently provide documentation showing he or she is registered to vote
in the state and documentation showing his or her name and address as reflected in the
voter registration record because this information can be verified electronically in
Alabama’s voter registration system.

51

As previously stated, the types of documents and combinations of documents that an
individual could present to obtain a driver’s license, nondriver state ID, or free ID vary by
state. Given this variation, we focused on obtaining and presenting information on costs
for a state birth certificate, which is a common type of document individuals could present
among the 17 states we reviewed. Other types of documents that could be presented in
certain states include a Social Security card or other federal forms of ID; these federal
forms of ID may have costs, but those costs are standard across states, and are therefore
not discussed in this review. In addition, other types of documents could be presented in
certain states, but we excluded them from our review, as the costs and combinations of
documents vary across the states.

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State

Cost of birth certificate

Mississippi

$15

North Carolina

$24

North Dakota

$7

Oklahoma

$15

Pennsylvania

$20

Rhode Island

$20

South Carolina

$12

Tennessee

$8

Texas

$22

Virginia

$12

Wisconsin

$20

c

Source: GAO analysis of publicly available state birth certificate cost information. | GAO-14-634
a

cson
of Tu
City
b
A birth certificate may be provided at nov. for the2016 of obtaining required voter ID in
nc. cost 31, purposes
I
Kansas.
nce, ug st
c
Allia before 1949u required to pay $15 to obtain a birth certificate.
Citizens born in y
Tennessee n A
are
do
egrit
c Int archive
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2
Publ
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ite
c
No.
A birth certificate may be provided at no cost for the purposes of obtaining required voter ID in
Alabama.

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Studies Generally
Focused on Elections
Prior to 2008 and
Showed Mixed
Effects of Voter ID
Requirements on
Voter Turnout

We reviewed 10 studies that estimated effects of state voter ID
requirements on turnout, nine of which examined earlier general
elections, that is before the 2008 general election, and 1 study examined
general elections from 2004 through 2012. 52 The studies used various
approaches to estimate the effects of state voter ID requirements on
turnout. In general, most of the studies used one data source, such as
surveys or official voter records, to make their estimates, and 1 of the 10
studies used data from both surveys and official voter records. The
studies, conducted by various researchers, showed mixed results and
analyzed how various non-photo and photo identification laws affected
turnout in presidential or congressional elections nationwide and in one
state. The ID laws evaluated varied across states, ranging from
requirements for voters to state their name to presenting a governmentissued photo ID, and the assessment in 9 of the studies grouped and
compared states according to ID law requirements. 53 These studies are
n
ucso
useful for understanding potential effectsT voter ID requirements on
of of
ity
voter turnout; however, thec. v. C face016
n studies 1, 2 limitations in available data used
I
in the analyses andnce,potentialtfor other factors to obscure the effects of
s 3
a the A
Allireviewed.ugu
n
ity
the requirements ed o
tegr

ic In
chiv
Publ 6142 ar
in
cited o. 15-1
N
52

We reviewed six additional studies related to the effects of state voter ID requirements
on voter turnout, but excluded them from our report because of limitations in the studies’
scope or methods for estimating effects. Those studies were: Ansolabehere, Stephen.
“Effects of Identification Requirements on Voting: Evidence from the Experiences of
Voters on Election Day.” PS: Political Science & Politics, January 2009: 127-130; Bullock
III, Charles S and M.V. Hood III. “Worth a Thousand Words? An Analysis of Georgia’s
Voter Identification Statute.” American Politics Research, vol. 36, no. 4 (2008): 555-579;
Cobb, Rachel V., D. James Greiner, and Kevin M. Quinn. “Can Voter ID Laws Be
Administered in a Race-Neutral Manner? Evidence from the City of Boston in 2008.”
Quarterly Journal of Political Science, vol. 7 (2012): 1-33; Gomez, Brad T. “Uneven
Hurdles: The Effect of Voter Identification Requirements on Voter Turnout.” Paper
presented at the Annual Meeting of the Midwest Political Science Association, Chicago,
IL, April 2007; Lott, John R. Evidence of Voter Fraud and the Impact that Regulations to
Reduce Fraud have on Voter Participation Rate (August 2006), forthcoming; and Pitts,
Michael J. “Photo ID, Provisional Balloting, and Indiana’s 2012 Primary Election.”
University of Richmond Law Review, vol. 47, no.3 (2013): 939-957.

53

The study that did not group states was focused on turnout effects in one state
(Indiana). The remaining nationwide studies generally grouped states by type of ID
requirement, such as by states that require voters to state their name, states that require
voters to present ID or a voter registration card, and states that require photo ID. Also, ID
requirements studied include those that do not require voters to present documentation at
the polls. For example, voters may be required to provide a signature as a form of
identification, which is verified by election officials as matching the voter’s signature
provided when the voter registered.

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Researchers seeking to isolate the effect of voter ID laws must
disentangle these effects from the many other factors associated with the
decision to vote or with aggregate turnout in an election. In 9 of the 10
studies we reviewed, researchers combined data from all states to assess
the effect of voter ID laws on turnout. In 7 of the 10 studies, researchers
combined data across multiple elections. This approach helps ensure that
enough data are available for analysis and potentially increases the
breadth of the findings to more states and time periods. However, a broad
analysis also introduces the possibility that factors varying across states
or over time may explain turnout decisions, rather than voter ID laws
themselves. For example, 1 study noted that changes to ballot access
policies—such as absentee and early voting policies—and competitive
elections during the time period examined could explain changes in voter
turnout among voters subject to ID laws. 54 Studies that analyze turnout
across multiple states and elections are vulnerable to bias from these
cson
kinds of alternative explanations that areTu
of unique to particular states and
ity
6
time periods; this vulnerabilityv. C be mitigated, in part, with attention to
nc. can31, 201
I
research designlliance, appropriate statistical analysis and
including gust
n Au
interpretation. A contrast, multiple-state studies that examine only one
grity In
nteperiodhived o
election
blic I 42 arc risk confounding the effects of election laws with existing
in Pu differences across states that cannot be controlled for using readily
d
161
cite
. 15No available demographic data, such as differences in political culture.
As shown in table 3, of the 10 studies we reviewed, 5 found that state
voter ID requirements had no statistically significant effects on voter
turnout nationwide, and 5 studies found that changes in voter ID
requirements had statistically significant effects on voter turnout. Among
the 5 studies that showed statistically significant effects, 1 of the studies
found an increase in voter turnout nationwide of 1.8 percentage points.
The other 4 studies that showed statistically significant effects found that
voter ID requirements decreased voter turnout, and the estimated
decreases ranged from 1.5 to 3.9 percentage points.

54

Dropp (2013).

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Table 3: Summary of Studies on the Effects of Voter Identification (ID) Requirements on Overall Voter Turnout

Study authors

Time
parameters

Data sources

Type of voter ID
law evaluated

Scope of
analysis

Election type

Direction and
magnitude of
effects of ID
requirements on
c
overall turnout

No statistically significant effects on turnout
Erikson and
Minnite (2009)

2002 and 2006

Survey (Current
Population
Survey)

Range of
requirements
(state name to
photo ID
required)

Nationwide

Congressional

No effects

Muhlhausen and
Sikich (2007)

2004

Survey (Current
Population
Survey)

Range of
requirements
(state name to
photo ID
required)

Nationwide

Presidential

No effects

Mycoff, Wagner,
and Wilson
(2007)

Mycoff, Wagner,
and Wilson
(2009)

cson
of Tu
ty
2000 to 2006
Official voter
Range of
Nationwide
Presidential and
v. Ci 2016
records and
requirements , Inc.
congressional
1,
survey (American (state lliance
name to
ust 3
g
National Electiongrphoto ID
n Au
ity A
e
nte required) d o
Studies)ic I
iv
arch
ubl
2004 to 2006 d in P
Survey 16142 Range of
Nationwide
Congressional
cite (Cooperative
requirements
. 15No
Congressional
(state name to
Election Survey)

Vercellotti and
2004
a
Andersen (2009)

Range of
requirements
(non-photo to
photo ID
requirements)

No effects

photo ID
required)

Survey
(Current
Population
Survey)

No effects

Page 36

Nationwide

Presidential

No effects

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Study authors

Time
parameters

Data sources

Type of voter ID
law evaluated

Scope of
analysis

Election type

Direction and
magnitude of
effects of ID
requirements on
c
overall turnout

Statistically significant effects on turnout at aggregate or voter level
Alvarez, Bailey,
and Katz (2011
b
and 2008)

De Alth (2009)

Dropp (2013)

2000 to 2006

Survey (Current
Population
Survey)

Range of
requirements
(state name to
photo ID
required)

Nationwide

Presidential and
congressional

cson
of Tu
2002 and 2006
Official voter
Range of
Nationwide
Congressional
. City
6
nc. v 31, 201
records
requirements e, I
(non-photo to
gust
llianc
ity A ID d on Au
rphoto e
nteg requirements)
v
blic I 42 archi
in Pu -161
cited o. 15
N

2004 through
2012

Official voter
records

Page 37

Range of
requirements
(state name to
photo ID
required)

Nationwide

Presidential and
congressional

Decreased
predicted
probability of
voting by 1.5 to 2
percentage
points for voters
in photo ID states
compared with
voters in states
that required
voters to state or
sign their names
Decreased
county-level
turnout—
compared with
states with no ID
requirement, a
2.2 percentage
point decline for
non-photo ID
requirements,
and a 1.6
percentage point
decline for photo
ID requirements
Decreased statelevel turnout in
states that
changed ID
requirements
compared with
those states with
no ID
requirements in
midterm elections
from 3.7 to 3.9
percentage
points, with no
effect on
presidential
d
elections

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Study authors

Time
parameters

Milyo (2007)

2002 and 2006

Vercellotti and
2004
a
Andersen (2006)

Direction and
magnitude of
effects of ID
requirements on
c
overall turnout

Data sources

Type of voter ID
law evaluated

Scope of
analysis

Election type

Official voter
records

Photo ID
requirements

Indiana

Congressional

Increased county
level turnout from
period prior to ID
requirements—
1.8 percentage
points

Survey (Current
Population
Survey)

Range of
requirements
(state name to
photo ID
required)

Nationwide

Presidential

Lower state-level
turnout—
approximately 3
percentage
points for states
that required
voters to show
any ID compared
with those states
that required
voters to state
e
their name

cson
of Tu
. City
6
nc. v 31, 201
ce, I gust
n
u
Allia
grity ived on A
nte | GAO-14-634
Source: GAO analysis of studies that estimate the effects of ID requirements on turnout.
blic I
arch
We identified these studies through a search of several online databases that catalog peerin Pu Notes:6142
reviewed
cited o. 15-1 journal articles, conference proceedings, and research institute publications for studies
N published from January 1, 2003 to May 2013, with subsequent searches to locate any additional

material through March 2014. We had two social scientists and, as applicable, a statistician, review
each of the 10 studies to determine whether the design, implementation, and analyses of the study
were sufficiently sound to support the study’s results and conclusions based on generally accepted
social science principles. A variety of studies broadly examine aspects of the implementation of voter
ID laws, but the sub-set of studies cited here estimate effects of voter ID laws on voter turnout. A
description of our literature review methodology is provided in appendix II and full citations for studies
listed here are provided in appendix III.
a

We reviewed two studies by Vercellotti and Andersen evaluating potential ID law effects on voter
turnout during the 2004 general election. They found differing results, generally because different
methods of analysis were used. In their 2006 study, the researchers divided states into five groups,
each with varying degrees of ID requirements, to assess effects of the requirements on turnout. The
ID requirements ranged from stating one’s name to providing a photo ID. In the 2009 study, the
researchers divided states into three groups—states that required photo or non-photo ID
requirements for the first time in the 2004 presidential election, states that had those requirements in
a prior election, and all remaining states that did not require voter ID.
b

We reviewed the published study (2011), as well as the working paper that led to the published study
(2008).
c

Unless otherwise noted, all estimates are significant at least at the 0.05 level of statistical
significance.

d

The study does not report standard errors, but states the differences are significantly distinguishable
from zero.
e

Significant at the 0.05 level of statistical significance, using a one-tailed statistical test.

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In addition to evaluating potential effects of ID requirements on overall
turnout, 5 of the 10 studies we reviewed examined effects of changes in
voter ID requirements on various racial and ethnic sub-groups and
provided estimates that we determined were sufficiently reliable for our
reporting purposes. Of these 5 studies, 3 identified statistically significant
effects of voter ID requirements for various racial and ethnic sub-groups
and two did not find statistically significant effects. 55 The 3 studies that
estimated statistically significant effects, and that we determined were
sufficiently reliable, found different effects for minority voters, as
compared with White voters:
Dropp (2013). In his study estimating the effects of changes in voter
ID requirements on voter turnout nationwide, Dropp estimated the
effects on African-American, non-white, and White registered voters
where voters’ race was identified using a vendor’s model to predict
son
the race of registered voters listedof Tuc official voter record
in states’
. in ty
databases. 56 For the change Ci turnout6
between the 2004 and 2008
nc. v found 201
,
general elections, e, I studyst 31 no significant effects by race or
c the gu
n
Allia
ethnicity,ywith the on Au
grit ived exception of a 1 percentage point increase in state
Inte
iclevel turnout for Hispanics. For the 2006 to 2010 midterm elections,
ch
Publ the 42 ar reported that the effect on state-level turnout was a 1
1 study
in
6
cited o. 15-1
percentage point decrease for African-Americans, Whites, and nonN
Whites (estimated separately). For general elections held between
2004 and 2010, the study reported that the state level turnout effects
identified were a 2 percentage point decline for African-Americans, a
1.25 percentage point decline for non-Whites, and 0.5 percentage
point increase for Whites. 57
Vercellotti and Andersen (2006 and 2009). In their studies
estimating the effects of voter ID requirements on voter turnout

55

Muhlhausen and Sikich (2007) reported results for racial sub-groups that they found to
be statistically significant. However, we determined that the methods used to quantify the
sub-group results they presented were not sufficiently reliable, and therefore have not
included those in the report.

56

The author did not describe which racial groups were included in the non-white category
for analysis. Some states require registered voters to identify their race when registering
to vote. For those states, the vendor reports what registered voters indicate as their race.
For states that do not require self-reporting of race, the vendor classifies each voter’s race
based on other characteristics kept in official voter records and U.S. Census information.

57

For each of these estimates, the researcher did not report standard errors, but asserts
that the differences are significantly distinguishable from zero.

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nationwide, Vercellotti and Andersen also estimated effects on
African-American, Asian-American, Hispanic, and White voters by
including survey respondents’ self-reported ethnic or racial identities
in their analysis. Using this method, the 2006 study found that the
predicted probability that Hispanics would vote in states that required
non-photo identification was about 10 percentage points lower than in
states where Hispanic voters were required to give their names.
According to the 2006 study, the difference was about 6 percentage
points lower for African-Americans and Asian-Americans, and about 2
percentage points lower for White voters (the gap widened to 3.7
percentage points lower for White voters when comparing rates for
photo identification with rates for stating one’s name). 58 The 2009
study, which assessed the likelihood of voting among those living in
states with an ID law first enacted in 2004, found that Hispanics in
these states were 2 percent less likely to have reported voting in
son
2004.
f Tuc

ity o 6
. v. C effects1of voter ID requirements for
0
c
The other 2 studies that, examined31, 2
e In us
lianc groups,t did not find statistically significant
l
various racial and ethnic Aug
n
rity A
nteg rchived o
effects.
cI
i
2a
Publ
d in 15-1614
ite
c
Alvarez, Bailey, and Katz (2011 and 2008). 59 In their study, Alvarez,
No.

Bailey, and Katz estimated the effects of changes in voter ID
requirements on voter turnout for racial sub-groups by including
survey respondents’ self-reported ethnic or racial identities in their
analysis. The authors estimated that the decrease in turnout of
requiring photo IDs as compared with stating or signing names is
larger for Whites than for non-Whites. Specifically, the results indicate
a decrease in the probability of voting in states with photo ID
requirements relative to those requiring voters to state their name is
approximately 4 percentage points for Whites and approximately 2
percentage points for non-Whites. However, according to the
information presented in the study, we determined that the results are
too imprecisely estimated to support the conclusion that racial

58

The difference for Hispanics was distinguishable from zero at the 0.05 level of statistical
significance, and each difference for African-American, Asian Americans, and whites was
distinguishable from zero at the 0.01 level.

59

We reviewed the published study (2011), as well as the working paper that led to the
published study (2008).

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differences in the effects of voter ID requirements on voter turnout
exist.
Milyo (2007). In his study, Milyo estimated the effects of changes in
voter ID requirements on voters in Indiana for minority groups by
evaluating effects at the county level using U.S. Census Bureau data
on the proportion of different races residing within each county. 60
Milyo estimated an increase in turnout of 0.07 percentage points for
counties with a greater percentage of minority residents and 0.29
percentage points for counties with a greater percentage of
populations in poverty, but reported that the estimates are not
statistically significant.
The studies we reviewed identified various theories or factors that could
help provide insights regarding the studies’ varying estimated effects of
changes in voter ID requirements on voter turnout. For example, Dropp
cson
of Tu
(2013) and Gomez (2008) noted that changes in voter ID requirements
City
could contribute to decreases v. voter 2016 by requiring voters to
nc. in 31, turnout
I
st
nce,
present necessary documents that certain segments of the population,
Allia on Augu
y
itbe lessd
r
who tendgto
nte
ive familiar with the electoral system, are less likely to
blic Ithan2others. In contrast, Dropp (2013) has suggested that changes to
own 4 arch
in Pu ID 161
ited o. 15-laws could increase turnout by intensifying efforts by political
c
N campaigns and interest groups to help eligible voters obtain the required
ID, which also could increase their propensity to vote.
Estimating the extent to which there may be effects, if any, of changes in
voter ID laws on voter turnout is challenging, regardless of how the laws
operate, because of limitations in the available data and the potential for
other factors to obscure the effects of interest. For example, 7 of the 10
studies we reviewed used survey responses to estimate the effect of ID
requirements on voter turnout. 61 In these studies, the authors used survey
data from a representative sample of voting-age adults contacted shortly
after a general election occurred in order to measure respondents’ turnout

60

Milyo defines minority groups as non-white or Hispanic.

61

In one of the 7 studies, the authors used both survey responses and official voter
records (Mycoff, Wagner, and Wilson, 2007).

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and various other characteristics, such as race and age. 62 A key strength
of surveys is that they can enable estimates of the effects of ID laws for
subgroups of the population because they include more detailed
demographic information than official voter files. However, political
scientists have found that surveys produce higher estimates of turnout
than official records maintained by election administrators. Possible
explanations for this discrepancy between survey responses and actual
records include memory limitations and respondents indicating they had
voted when they had not, because of positive social attitudes toward
voting among some groups of respondents. 63 Impact estimates of voter ID
laws can be inaccurate if the survey respondents who are more likely to
be affected by the laws are also more likely to report their turnout
inaccurately (see app. VI).
Four of the studies we reviewed used official son records obtained from
voter
uc
election administrators to estimateity oeffect of changes in voter ID
the f T
requirements on voter turnout. Official 2016should be the authoritative
. v. C , data
, Incweaknesses in how voter records are
31
record of turnout.iance
ll However, st
Aalso causeugu and can lead to an underestimation of
A
maintainedity
egr can d on error
c Int as a rchive
i
turnout 2 a proportion of registered eligible voters. In particular, official
Publ
4
d in 15-161registered voters do not necessarily identify those who are on the
lists of
cite
. list of registered voters but ineligible to vote in any one election. A person
No
may have been eligible to vote several years ago, and therefore was
placed on the registration rolls, but subsequently moved out of the
jurisdiction or state, died, or committed a crime that makes him or her
ineligible to vote. Registration and voter history records may not reflect
this change in eligibility, depending on the extent to which records are
updated. When records are not current, a person may be categorized as

62

Specifically, five studies used data from the Voting and Registration Supplement of the
Current Population Survey (CPS), administered by the U.S. Census Bureau, one study
used data from the American National Election Studies (ANES) survey (produced through
a collaboration of Stanford University and the University of Michigan), and one study used
data from the Cooperative Congressional Election Study (CCES) survey (produced by
Harvard University). The U.S. Census Bureau conducts the CPS monthly to measure
unemployment and other workforce data, but adds a battery of voter participation
questions to the November survey in even-numbered years to coincide with the
presidential and midterm congressional elections. Administered since 1948, the ANES
survey is conducted just after biennial national elections. During presidential elections, the
ANES is also conducted just before the election.

63

Ansolabehere and Hersh, “Validation: What Big Data Reveal about Survey Misreporting
and the Real Electorate,”437-459.

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a registered non-voter for a particular election, when in fact the person
should not have been included in the eligible population for that election.
In addition, election administrators may not always record a registered
and eligible voter as having cast a ballot in official voter history files,
because of record-keeping issues at polling places or central offices. 64
Finally, the existing research provides limited evidence regarding the
effects on turnout of the requirements for government-issued, photo IDs
that states have adopted in recent years. All but 1 of the studies we
reviewed analyzed turnout in elections from 2002 through 2006, but 6 of
the 8 states with requirements for a voters to present a governmentissued photo ID as of the 2012 general election implemented the
requirements after the 2006 general election. 65 If ownership rates varied
across various types of ID, impact estimates for prior elections and laws
n
that allowed more forms of ID would not necessarily resemble estimates
ucso
for more recent elections and ID laws of T allowed fewer forms of ID.
that
ity

16
. v. C
, Inc st 31, 20
ce
n
ugu
Allia
grity ived on A
te
ic In
ch
Publ 6142 ar
in
cited o. 15-1
N

64

Ansolabehere and Hersh, “The Quality of State Voter Registration Records: A State-byState Analysis.” Pew Center for the States, Election Initiatives. Inaccurate, Costly, and
Inefficient: Evidence that America’s Voter Registration System Needs and Upgrade.
February 2012, http://www.pewstates.org/research/reports/inaccurate-costly-andinefficient-85899378437.

65

The six states that implemented government-issued photo ID requirements after the
2006 general election and as of the 2012 general election are: Georgia (2008 presidential
election), Idaho (2010 midterm election), Kansas (2012 presidential election), Michigan
(2008 presidential election), Pennsylvania (2012 presidential election), and Tennessee
(2012 presidential election). The remaining two states that implemented governmentissued photo ID requirements as of the 2006 general election are: Indiana (2006 midterm
election) and South Dakota (2004 presidential election). When requirements were
implemented is not necessarily when legislated to go into effect, due to litigation.

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Our Analysis
Suggests that
Decreases in General
Election Turnout in
Kansas and
Tennessee from 2008
to 2012 Beyond
Decreases in
Comparison States
Are Attributable to
Changes in Voter ID
Requirements

To examine the extent to which changes in voter ID requirements affected
voter turnout in selected states, if at all, from the 2008 to 2012 general
elections, we designed an evaluation that used multiple data sources, and
we selected two treatment and four comparison states for evaluation. In
comparison to most of the other studies which focused on elections prior
to 2008, our analysis focused on the extent of any changes in voter
turnout from the 2008 to 2012 general elections—the two most recent
general elections. Further, in comparison to most of the other studies, our
analysis used multiple data sources, including both surveys and official
voter records, and we selected treatment and comparison states by
controlling for factors other than changes in voter ID requirements that
could have affected turnout in the selected states. (App. V describes the
design of this analysis in more detail.)

Data sources and quasi-experimental design. Because of concerns
cson
that surveys may overestimate and y of Tu
official voter records may
. it 20 6
underestimate voter turnout,.we C
nc v analyzed1both types of data in order to
,
e I results we
assess the sensitivity of, any gust 31 would obtain from our analysis.
ianc
Allwe usedAu from the November 2008 and 2012 Voting
The surveyity
r data d on were
Integ rch supplements of the Current Population Survey (CPS),
c Registrationive
i
and
2a
Publ
conducted
d in 15-1614 by the U.S. Census Bureau. The CPS provided data for
ite
c
No. 92,360 respondents in 2008 and 94,311 respondents in 2012, after we
selected only those respondents who said they were U.S. citizens of
voting age and registered to vote. Political scientists use CPS data to
study how the decision to vote is associated with individual
characteristics, laws, political campaigning, and election administration
practices. 66 The CPS measures registration and turnout, along with
various demographic and economic variables, such as race, income,
residential mobility, and population density.
In addition to survey data, we analyzed two versions of official voter
turnout records for selected states. At the individual voter level, we
analyzed official state data on registered voters and turnout history,
sometimes known as voter registration and history files. We obtained

66

See, for example, Raymond E. Wolfinger, and Steven J. Rosenstone. Who Votes? New
Haven, Connecticut: Yale University Press, 1980; Luke Keele and William Minozzi, “How
Much is Minnesota Like Wisconsin? Assumptions and Counterfactuals in Causal Inference
with Observational Data.” Political Analysis (2013): 1-24; Robert S. Erikson and Lorrane
C. Minnite. “Modeling Problems in the Voter Identification—Voter Turnout Debate.”
Election Law Journal (2009): 85-101.

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these data from a commercial vendor who took steps to improve their
reliability and to supplement the official state data with additional voter
demographics from the U.S. Census Bureau and commercial sources
(see app. VI). At the state level, we analyzed data provided by the United
States Elections Project (USEP) at George Mason University. USEP data
consist of vote or ballot totals reported by election administrators, along
with estimates of the population of each state who are eligible to vote.
This source provides an estimate of state-level turnout as a share of the
eligible voting population, rather than of the registered voting population
covered by the CPS and official voter databases.
We used a quasi-experimental comparison group design to account for
factors other than voter ID requirements that could affect voter turnout. A
quasi-experimental comparison group design is a type of policy
evaluation that compares how an outcome changes over time in a
cson
“treatment” group that adopted a new of Tu with how an outcome
policy
ity
67
6
changes in a “comparison” c. v. C
not
n group that did1 make the same change.
1, 20 analyze separate groups
,I
As in controlled lliance
experiments, ust 3
gresearchers
ty A d on A changed a policy.
iafter one groupu
before and
egr

t
ic In
chive
Publ 6142 ar
in The
cited o. 15-1variation across states in the use of voter ID laws, along with their
N staggered adoption over time, makes a quasi-experimental analysis

possible. Our treatment and comparison groups included all registered or
eligible voters in selected states that did and did not modify ID laws in a
certain time period. Within each group, we estimate how turnout changed
by comparing time periods before and after the reform, and then we
calculate how the change varied between groups, known as a differencein-difference. If turnout changed by a greater amount in the states that
adopted voter ID laws, evidence would suggest that ID laws affected
turnout.
Quasi-experiments have a number of strengths for estimating the effects
of election administration practices, as noted by academic studies. 68 The

67

GAO, Designing Evaluations, GAO-12-208G (Washington, DC: Jan. 31, 2012); Debra J.
Rog, “Constructing Natural ‘Experiments’.” In Handbook of Practical Program Evaluation,
Joseph P. Wholey, Harry P. Hatry, and Kathryn E. Newcomer, eds. San Francisco:
Jossey-Bass Publishers, 2010.

68

Luke Keele and William Minozzi, “How Much is Minnesota Like Wisconsin? Assumptions
and Counterfactuals in Causal Inference with Observational Data.” Political Analysis
(2013): 1-24; Michael J. Hanmer, Discount Voting: Voting Registration Reforms and Their
Effects. New York: Cambridge University Press, 2009.

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longitudinal nature of the analysis holds constant any differences between
the treatment and comparison groups that do not change by large
amounts over short periods of time. In our analysis, these could include
differences across voters (and implicitly states) in age, education, income,
race, political interest, residential mobility, state political culture, and
partisanship, which may be correlated with both voter turnout and the
presence of voter ID laws. Political science research has consistently
shown that individual differences across citizens—and implicitly across
the jurisdictions in which they live—largely explain the decision to vote or
not to vote. 69 For this reason, a quasi-experimental design is well suited
to estimating the effect of legal reforms designed to change the voting
process, because it holds constant many of the most important
confounding variables.

cited

Treatment and comparison state selection.on reviewing voter ID
cs After
requirements, legal changes, and election u
of T environments across states
. City
6
from 2002 through 2012, we.selected Kansas and Tennessee as the
nc v 31, 201
I
treatment group land ce,
Alabama, st
Arkansas, Delaware, and Maine as the
n
ugu 70
A lia
comparisontgroup for on A
gri y ived our analysis. The treatment group states had the
Inte characteristics:
following2 arch
ublic

in P -1614
15
No.
They implemented government-issued photo ID requirements

between the 2008 and 2012 general elections that also required
voters to follow-up with election officials with acceptable ID in order to
have their votes counted if they attempt to vote without acceptable ID.

69
Raymond E. Wolfinger, and Steven J. Rosenstone. Who Votes? New Haven, CT: Yale
University Press, 1980. Steven J. Rosenstone and John Mark Hansen. Mobilization,
Participation, and Democracy in America. New York: MacMillan, 1993.
70

In 2004, Kansas amended its election laws to provide for ID requirements for all firsttime voters. In 2011, Kansas added new photo ID requirements for all eligible voters,
effective January 1, 2012. In 2003, Tennessee added a form of acceptable ID to its
existing ID requirement, allowing voters to present a valid voter’s registration certificate in
addition to a Tennessee driver’s license, Social Security card, a credit card bearing the
voter’s signature, or other document bearing the voter’s signature. In 2011, Tennessee
amended the voter ID requirement to require voters to present state or federal
government-issued, photo ID, which was effective on January 1, 2012. In Tennessee, a
voter who is indigent and unable to obtain proof of identification without payment of a fee
or a voter who has a religious objection to being photographed may execute an affidavit of
identity and may then be permitted to vote. More information about Kansas and
Tennessee voter ID laws for all eligible voters to cast a ballot at the polls on Election Day
and how those laws have changed since HAVA was enacted can be found in GAO-1390R.

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They did not experience contemporaneous changes to other election
laws that may have significantly affected voter turnout on Election
Day.
They had presidential general elections where the margin of victory
did not substantially change from 2008 to 2012 and all other statewide
elections, such as U.S. Senate races, were non-competitive in both
the 2008 and 2012 general elections. 71
There was a minimal presence of ballot questions in the 2008 and
2012 general elections.
They had official voter history data that were sufficiently reliable for
the purposes of our analysis.
The comparison group states had the following characteristics:

n

ucso

f
They did not implement substantivelyT
ity o amended voter ID laws between
the 2008 and 2012 general .elections.16
. v C , 20
Inc
ce,

st 31

llian
They had election cyclesgu statewide elected offices that were
u for
it A
grtoythose d on A
similar
e of the selected treatment states.
nte
hiv
cI

i
c
Publ They2 ar
d in 15-1614 did not experience contemporaneous changes to other election
cite
laws that may have significantly affected voter turnout on Election
No.
Day.
They had presidential general elections where the margin of victory
did not substantially change from 2008 to 2012 and all other statewide
elections, such as U.S. Senate races, were non-competitive in both
the 2008 and 2012 general elections.
Ballot questions were not present, noncompetitive, or similarly
competitive in both elections within a state.
Two of the four comparison states were geographically proximate to
the treatment states.
The states had official voter history data that were sufficiently reliable
for the purposes of our analysis.

71

We considered a change in the margin of victory of less than 10 percentage points to be
a non-substantial change in the margin of victory for a presidential race. The margin of
victory for the presidential general election changed by 7 percentage points in Kansas and
5 percentage points in Tennessee from 2008 to 2012. In addition, we considered an
election noncompetitive if the margin of victory was greater than 20 percent.

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For a complete description of our design, including data sources and
state selection process used, see appendix V.
Results of our analysis. According to the results of our quasiexperimental analysis, voter turnout decreased in Kansas and Tennessee
from the 2008 to the 2012 general elections to a greater extent than
turnout decreased in selected comparison states—Alabama, Arkansas,
Delaware, and Maine. Our analysis suggests that the turnout decreases
in Kansas and Tennessee beyond decreases in comparison states were
attributable to changes in the two states’ voter ID requirements. As shown
in figure 5, turnout declined in all six of the states we analyzed between
2008 and 2012, but it declined by a larger amount in Kansas and
Tennessee than in the four comparison states. 72 Compared with changes
in turnout in all the comparison states combined, we estimate that turnout
for eligible voters declined by an additional 3.0on
cs percentage points in
Kansas and by an additional 2.7 percentage points in Tennessee.
of Tu
ity
Compared with changes in c. v. C in all016 comparison states combined
n turnout 1, 2 the
I
and depending onance,
the source of t 3
sturnout data analyzed, we estimate that
Alli on Augu of registered voters declined by an
ity general population
turnout egrthe
for
ed
nt
additional ar h v
blic I 421.9ctoi2.2 percentage points in Kansas and by an additional 2.2
Pu
in to 3.2 1
6
cited o. 15-1 percentage points in Tennessee. (See app. VI for a more complete
N description of our findings on voter turnout.) We designed our analysis to
hold constant other factors that may have affected turnout; by doing so,
our design increases the likelihood that decreases in turnout in Kansas
and Tennessee are attributable to changes in voter ID requirements,

72

To calculate voter turnout in the 2008 and 2012 general elections, we divided the
number of individuals who voted by the population of registered or eligible voters.
Specifically, for our analysis of the enhanced state voter databases, we calculated turnout
by dividing the number of individuals officially recorded as having voted by the number of
voters listed as registered within state voter registration databases. For our analysis of the
CPS, we divided the number of individuals who self-reported to have voted in the survey
by the number of self-reported registered voters within each state. For the USEP data
source, we divided the number of individuals officially reported to have voted by the
voting-eligible population. The voting-eligible population is the voting age population
adjusted for segments of the population that are not eligible to vote, such as non-citizens
or ineligible felons.

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rather than other factors such as changes in voter demographics,
campaign mobilization, or other election administration laws. 73
Figure 5: GAO Analysis of the Effects of Voter Identification (ID) Requirement
Changes on Turnout in the 2012 General Election in Kansas and Tennessee

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u
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c
N

Note: Change in turnout using enhanced state voter databases and the Current Population Survey
are derived from multivariate statistical analyses (see app. VI, tables 16 and 21). Estimates of
changes in ID requirement effects on voter turnout have a margin of error at the 95 percent
confidence level. Depending on the source of the data, we estimated margins of error using statistical
models or standard methods for calculating differences in proportions among independent samples
(see app. VI). Specifically, the United States Elections Project estimates have a margin of error of +/0.12 percent for Kansas and +/- 0.09 percent for Tennessee. The enhanced state voter database
estimates have a margin of error of +/- 0.12 percentage points for Kansas and +/- 0.09 percentage
points for Tennessee. For the comparison state changes in turnout calculated from the enhanced
state voter databases, we used weighting to make the distribution of voters in the comparison states

73

In its letter commenting on excerpts from our draft report, Kansas’ Secretary of State’s
Office stated that photo ID laws are intended to reduce or eliminate fraudulent voting and
that if lower overall turnout occurs after implementation of a photo ID law, some of the
decrease may be attributable to the prevention of fraudulent votes.

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similar to the distribution of voters in Kansas and Tennessee. Specifically, in this analysis, we
weighted the distribution of comparison state voters in the categories of age, race, and registration
year so that the distribution of registered voters was similar across these characteristics to the
distribution in Kansas and Tennessee in 2012. We also limited our analysis to the subset of voters
who were registered prior to the 2008 election and potentially eligible to vote in either election. This
weighting approach was completed only for the analysis using the enhanced state voter database.
The Current Population Survey estimates have a margin of error of +/- 3.5 percentage points for
Kansas and +/- 2.8 percentage points for Tennessee.

To validate the results of our analysis, we (1) compared Kansas and
Tennessee with both different combinations of comparison states and
individual comparison states, and (2) controlled for demographic
characteristics that can affect turnout. According to these additional
analyses, we found that greater turnout decreases in Kansas and
Tennessee compared with individual and different combinations of
comparison states, and controlling for demographic characteristics, were
on
most likely attributable to changes in voterucsrequirements rather than
of T ID
ity
other factors.
16
. v. C

0
c
31, 2
e, In
lianc We gust
l
Multiple comparisons. Au compared turnout changes in Kansas and
rity A ed on
nteg with iturnout changes in various combinations of comparison
Tennessee rch v
blic I
a
using
in Pu states142 the three datasets, to determine if any particular comparison
ited o. 15-16or combination of comparison states could bias our results.
c
N state

According to our analysis of the different data sets, we found that the
decrease in turnout was greater in both Kansas and Tennessee than the
turnout decreases for different combinations of comparators. For
example, using USEP data, we found that turnout declined in Kansas 3.1
percentage points more than the pooled decline of Alabama and
Arkansas. 74 Similarly, we found that turnout in Tennessee declined 2.9
percentage points more than the pooled decline in Alabama and
Arkansas. We also found similar patterns of declines in turnout when
Kansas and Tennessee were compared with individual states. For
example, according to CPS data, the turnout decline in Kansas was 2.3
percentage points greater than the decline in Alabama, 3.5 percentage
points greater than the decline in Arkansas, 5.6 percentage points greater

74

When selecting comparison states, Alabama and Arkansas were most comparable to
Kansas and Tennessee, because of geographic proximity to Kansas and Tennessee and
similarity in historical turnout patterns. See app. V for a more detailed explanation of our
analysis of historical turnout patterns.

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than the decline in Delaware, and 4.7 percentage points greater than the
decline in Maine. 75
Demographic controls. We included demographic controls in our
analysis when analyzing changes in turnout using CPS data. The CPS
data allow for additional demographic data to be included in our analysis,
which permits us to determine if turnout changes persist when other
demographic factors are considered. We also specified a model that
allowed different rates of change in turnout between 2008 and 2012 for
different demographic subgroups, to control for the possibility that trends
in turnout may not be parallel within demographic groups if political
campaigns or interest groups disproportionately encouraged turnout
among some groups in one year but not another, even though our design
ensures that overall levels of competition were similar at the state level
(see app. VI). After making these adjustments on age, education,
cs for
employment status, family income, tmaritalu
of T status, race, and sex, we
. iy
found that the greater decreasesC turnout6in Kansas and Tennessee
nc. v in 1, 201
I
persisted. We estimated that turnout in Kansas decreased by 1.9
nce, ugust 3
Allia onthan turnout decreased in all comparison states
percentageitpoints more A
r y
Integ rchived
c turnoutain Tennessee decreased by 2.2 percentage points more than
i
and
2
Publ
turnout decreased in all comparison states. We obtained similar results
d in 15-1614
ite
c
No. after applying similar controls in an analysis of voter-level data from the
commercially enhanced state voter databases (see app. VI).
Our analysis of the enhanced state voter databases provided sufficient
numbers of records to reliably estimate the effects of changes in state
voter ID laws separately for various sub-groups of age, race or ethnicity,
and length of voter registration. To estimate the extent to which changes
in voter ID laws affected turnout among these sub-groups, we estimated
the difference-in-difference separately for each sub-group, and compared
how these estimates varied across sub-groups. According to this
analysis, we found that changes in turnout were larger among registrants
who were younger, African-American, or recently registered in our two
treatment states, relative to the comparison states pooled, and our
analysis suggests that these changes are attributable to the states’

75

The CPS estimates using Alabama or Arkansas as comparison states, respectively, are
er, these results are consistent with those
that we obtained from samples that pool data from a large number of registrants in
multiple comparison states (see app. VI, tables 16, 20, and 21). The latter estimates are
distinguishable from zero at conventional levels of significance.

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changes in voter ID laws, because we held other factors constant that
could have otherwise affected turnout. The differences between groups
described below are each statistically distinguishable from zero. Our
estimates by sub-group appear in figure 6, and margins of error for each
estimate provided are listed in appendix VI.
Age. In Kansas, the turnout effect among registrants who were 18
years old in 2008 was 7.1 percentage points larger in size than the
turnout effect among registrants between the ages of 44 and 53. The
change in turnout in Tennessee was reduced among 18 year-old
registrants by 1.3 percentage points more than among 44 to 53 yearolds. The same effects among registrants between the ages of 19 and
23 were 3.6 percentage points larger in Kansas and 1.2 percentage
points larger in Tennessee.
Race or ethnicity. In both Kansas and Tennessee we found that
cson
of Tu
turnout was reduced by larger amounts among African-American
. City
6
registrants, as compared. with Asian-American, Hispanic, and White
nc v 31, 201
ce, I gustturnout was reduced among Africanregistrants. We n
estimate that
u
Allia
American registrants A 3.7 percentage points more than among
grity ived on by
nte in ch
I
blicWhites ar Kansas and 1.5 percentage points more than among Whites
in Pu -16142
cited o. 15 in Tennessee. However, we did not find reductions in turnout among
N
Asian-American or Hispanic registrants, as compared with White
registrants, thus suggesting that the laws did not have larger effects
on these registrants. 76
Length of registration. In Kansas, the reduction in turnout for people
registered to vote within 1 year prior to Election Day 2008 was 5.2
percentage points larger in size than for people registered to vote for
20 years or longer prior to Election Day 2008. In Tennessee, the
effect on turnout for people registered to vote within 1 year prior to
Election Day 2008 was 4.6 percentage points larger than the effect for
people registered to vote for 20 years or longer prior to Election Day
2008. The effect of ID laws changes may vary according to length of
registration, for several reasons. For example, more recently
registered voters may be less familiar with the requirement for
establishing their identities at the polls and may be less likely to have

76

We found different effects among Hispanic registrants, as compared to White
registrants, in alternative versions of our analysis that used various combinations of the
comparison states (see app. VI, table 17). Unlike the effects among African-American
registrants, these effects were not consistently higher or lower or statistically
distinguishable from zero.

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current identification documents. Alternatively, longer registrants may
be more familiar with the voting process and more likely to pay
attention to changes in requirements. Length of registration may also
serve as an approximate measure of the time period a voter has
remained in a community as a registered voter, to the extent that
people register to vote when they move into a state, such as when
obtaining a new driver’s license. A short period of registration, for
example, is a possible indicator of a voter who may have recently
moved into a community. Moreover, length of registration should be
no longer than length of residence, since people must be legal
residents of a state to become registered voters. 77
Figure 6 shows our analysis of the estimated effects of voter ID
requirement changes on turnout in the 2012 general election in Kansas
and Tennessee by age, race, and length of registration.
n

cso
of Tu
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6
nc. v 31, 201
ce, I gust
n
u
Allia
grity ived on A
nte rch
blic I
a
in Pu -16142
ited o. 15
c
N

77

In its letter commenting on excerpts from our draft report, Tennessee’s Secretary of
State’s Office noted that most newly registered voters were sent a voter guide that
explained the voter ID law and that voters registered for longer periods of time may not be
as familiar with ID requirements.

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Figure 6: GAO Analysis of the Effects of Voter Identification (ID) Requirement Changes on Turnout in the 2012 General
Election in Kansas and Tennessee by Age (as of 2008), Race, and Length of Registration

cson
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6
nc. v 31, 201
ce, I gust
n
u
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in Pu -16142
ited o. 15
c
N

Although the design of our analysis effectively controls for a variety of
alternative explanations and sources of bias, several limitations may
apply.
Our results cannot be generalized beyond Kansas and Tennessee.
Our impact estimates are limited to changes in turnout among Kansas
and Tennessee eligible or registered voters between the 2008 and 2012
general elections and do not necessarily apply to other states or time
periods. Our results cannot be generalized to states that adopted
substantially different ID requirements, particularly states that allow forms
of ID such as utility bills, bank statements, and affidavits. To reliably
generalize our findings, replication of our analysis is necessary for other
ID laws, states, time periods, and subgroups of voters.

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The recent adoption of the ID laws we analyzed in Kansas and
Tennessee further limits the generalizability of our results. The effects we
estimated between the 2008 and 2012 general elections—with 2012
being the first general presidential election when the laws were in effect—
may not persist over time if, in the future, voters adjust to requirements
that were new in 2012 and obtain the necessary ID. In contrast, efforts by
political and government entities to inform voters about newer ID laws in
the first election after adoption may have the effect of mitigating the laws’
effects. In subsequent elections, these efforts may wane, and the impact
of the ID law changes on turnout may increase. 78 This type of education
campaign may affect voter turnout in ways that are difficult to measure
and may change over time. 79
Quality of comparison states. The validity of our impact estimates
largely depends on the quality of the matched on
comparison states we
ucs
selected. In principle, the comparison of T provide examples of turnout
states
. City
6
rates that Kansas and Tennessee might0have had if these states had not
nc. v 31, 2 1
c forI gust
adopted requirementse, government-issued photo IDs (also known as
n
u
Allia
counterfactual potential outcomes). 80 We believe our comparison
grity ived on A
nte rch
analyses are sufficiently strong, because our choice of comparison states
blic I
a
in Pu holds 142
d
5-16constant a number of factors, including voter characteristics that do
ite
c
1
No. not change substantially over time (e.g., sex and race); election
schedules; campaign competition for state and federal offices and ballot
questions; changes to other election administration laws; and, to a lesser
extent, election day weather conditions and broadcast media exposure.
As previously described, to mitigate the risk of bias in selecting a matched
comparison group, we calculated impact estimates for various
combinations of treatment and comparison states and obtained similar
results.
Alternative explanations. Alternative factors may explain the change in
turnout between our treatment and comparison states, despite the many

78

Election officials in both Kansas and Tennessee launched voter education campaigns
prior to the 2012 election to inform voters of the new ID requirements.

79

One study we reviewed examined the possibility of education campaign effects when
analyzing the effect of ID laws, but did not produce conclusive findings (Dropp, 2013).

80

Guido W. Imbens and Jeffrey W. Wooldridge, “Recent Developments in the
Econometrics of Program Evaluation,” Journal of Economic Literature, vol. 47, no. 1, 67.9.

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factors that are held constant by our choice of states, time periods, and
statistical methods. Examples of such unobserved factors include voter
mobilization campaigns for state legislative and municipal elective offices,
local ballot propositions, and changes to state laws and practices beyond
those we reviewed. We believe these factors are likely to be idiosyncratic
and not likely to systematically affect the change in turnout for all voters in
the treatment states more strongly than in the comparison states,
because of a wide variety of local factors that may influence local and
state legislative voter mobilization efforts. Nevertheless, any policy
evaluation in a non-experimental setting, such as ours, cannot account for
all unobserved factors that could bias or confound impact estimates with
certainty. 81
Limited number of treatment and comparison states. By selecting
treatment and comparison states where other on
csfactors that affect turnout
are unlikely to be operating, we have a fhigher level of confidence that our
o Tu
City
6
results do not reflect the impact. of factors1that were not held constant.
nc. v 31, 20
I
However, the costance, design tapproach is less precise estimates of
of this gus
u
Alli
how voter rityrequirementA
g ID ived on changes affect turnout, because a smaller
nteof voters, states, and time periods produce fewer data for
number
blic I 4 arch
in Pu statistical2analysis and generally larger margins of error. Generally, with
d
161
cite
. 15- volumes of data for use in a statistical analysis, estimates may be
No larger
produced with smaller margins of error. However, given the large
variation in state election environments that can affect turnout, there is a
risk that a broader analysis that included additional states and time
periods would produce more precise yet biased estimates of the effects of
changes in voter ID requirement on voter turnout.

81

W. G. Cochran, 1965, “The Planning of Observational Studies of Human Populations,”
Journal of the Royal Statistical Society, Series A, 128 (2): 234-266.

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A Small Portion of
Total Provisional
Ballots in Two States
Were Cast for ID
Reasons in 2012,
and Less Than Half
Were Counted

Provisional ballots are cast by voters at the polls whose eligibility to vote
is unclear and must be determined at a later date by election officials. In
Kansas and Tennessee, as in other states that use provisional ballots,
voters may cast a provisional ballot for a variety of reasons. For example,
a voter may lack sufficient ID to meet the state’s or HAVA’s
requirements, 82 or a voter’s name may not appear on the voter
registration list where he or she intended to vote. 83

In both Kansas and Tennessee, a voter who casts a provisional ballot for
ID reasons must provide appropriate identification at a later time specified
by law to ensure that his or her ballot is counted. 84 If a voter does not
provide appropriate identification during the specified time period, the
provisional ballot is not counted. In Kansas, a voter who casts a
provisional ballot must provide a valid form of identification to the county
election officer in person or provide a copy by on or electronic means
csmail
before between 8:00 a.m. and 10:00 a.m. on the Monday following an
of Tu
City 016
election, when the countync. v. of canvassers meets. At this meeting, the
board
1, 2
,I
county election officere ugust 3
lianc presents copies of identification received from
l
nA
r ty A
provisional ivoters ed othe corresponding provisional ballots, and the
nteg rchiv and
c I determines the validity of a voter’s identification and whether the
i
board 2 a
Publ
d in 15-1614 be counted. In Tennessee, in order to have a provisional ballot
ballot will
cite
No. counted, the voter must provide evidence of identification to the
administrator of elections at the county election office or other designated
location by the close of business on the second business day after the

82

HAVA requires states to provide a provisional ballot process for voters in certain
circumstances, including for first-time voters who register by mail but have not provided
acceptable identification as required by HAVA, among other situations.

83

Tennessee has two types of provisional ballots, according to officials in its Secretary of
State’s office. A voter who fails to provide required ID at the polling place receives an
orange ballot, and a voter whose eligibility is uncertain for any other reason receives a
green ballot, such as when the voter’s name does not appear on the registration list at the
polling place. Tennessee Secretary of State officials stated that orange provisional ballots
are not to be issued to voters who lack HAVA-required identification (for example, a firsttime voter who registered by mail who did not provide ID when registering). According to
officials from the Tennessee Secretary of State’s office, a green provisional ballot is to be
issued in Tennessee for issues related to HAVA-required identification.

84

“ID reasons” refers to ID requirements that apply to all eligible voters, not HAVA ID
requirements.

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election. The voter must also sign an affidavit affirming that he or she is
the same person who cast the provisional ballot. 85
If a provisional ballot is cast for multiple reasons, one of which is that the
voter does not have appropriate photo identification, the reason actually
recorded may vary between the two states. Kansas officials in the
Secretary of State’s office stated that the county election officer is
responsible for deciding which reason is assigned to the provisional
ballot, and this determination may vary depending upon individual
circumstances. Tennessee officials in the Secretary of State’s office
stated that in this situation, poll workers are instructed to categorize the
provisional ballot as having been cast for lack of a photo ID, and to use
an orange provisional ballot designated for this purpose.
We analyzed data from the 2012 EAVS conducted by the EAC and 2012
cson
election data provided to us by the ty of Tuand Tennessee Secretary of
Kansas
i
State offices to determinenc. v. C
the number 20provisional ballots cast in the
of 16
I
c and g extent ,
2012 general election e, theust 31 to which provisional ballots were
lian
u
86 ty Al
i
to A
counted.grAccording onour analysis, few provisional ballots were cast for
nte inchived and Tennessee in 2012, relative to total provisional
ID reasons
blic I 42 ar Kansas
in Pu ballots cast and total ballots cast. In Kansas, 1,115,281 total ballots were
d
161
cite
. 15- in the 2012 general election; of those ballots, 38,865 were
No cast
provisional ballots and, according to data provided by the Kansas
Secretary of State’s office, 838 of those provisional ballots, or 2.2 percent,
were cast for ID reasons. In Tennessee, 2,480,182 total ballots were cast
in the 2012 general election; of those ballots, 7,089 were provisional
ballots and, according to data provided by the Tennessee Secretary of

85

Other states differ in how officials determine whether a provisional ballot cast for ID
reasons will be counted. For example, in Florida, those ballots will be counted if the voter’s
signature on the provisional ballot matches the signature in the registration record and the
voter has voted in the proper precinct.

86

The EAVS is an instrument used to collect state-by-state data on the administration of
federal elections. According to EAC’s survey methodology, states vary in their approaches
to and completeness of their election data collection and their responses to the EAVS.
Most states relied, at least to some degree, upon centralized voter-registration and voter
history databases, which allow state election officials to respond to each survey question
with information from the local level. Other states collected relatively few election data at
the state level and instead relied on cooperation from local jurisdiction election offices to
complete the survey. Some states were not able to provide data in all the categories
requested in the survey and some did not provide data for all of their local jurisdictions.
Kansas and Tennessee reported data to EAVS for all local jurisdictions for the 2012
general election.

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State’s office, 673 of those provisional ballots, or 9.5 percent, were cast
for ID reasons. In Kansas, 37 percent of provisional ballots cast for ID
reasons ultimately were counted, and in Tennessee 26 percent were
ultimately counted. Provisional ballots cast for ID reasons may not be
counted for a variety of reasons in Kansas and Tennessee, including the
voter not providing a valid ID during or following an election. Table 4
provides additional information on the numbers and types of ballots cast
and the percentage of provisional ballots counted in Kansas and
Tennessee in the 2012 general election.
Table 4: Provisional Ballot Totals and Rates in 2012 General Election for Kansas and Tennessee

State

Total
ballots cast

Percentage of
Total prototal ballots
visional that were proballots
visional

Total provisional
ballots cast
for e,
ID
ianc
Allreasons

Percentage
Total proPercentage
of provisional
visional
of total provisional ballots son ballots cast
c cast
for ID
ballots that of Tu for ID
y
reasons
that
were Cit
cast
16
. v.for ID , 20that were reasonswere
Inc
1
ust 3
counted
counted
ugreasons

Percentage
of provisional
ballots cast
for non-ID
reasons
that were
counted

y
on A
d 838
egrit
3.48
2.16
306
37
65
c Int archive
i
Tennessee
2,480,182
7,089 ub
0.29
673
9.49
178
26
23
P l 6142
in
ited ando. 15-1 (EAVS) conducted by the U.S. Election Assistance Commission (EAC) and 2012 election data provided by the Kansas and
c
Source: GAO analysis of the 2012 Election Administration
N Voting Survey
Tennessee Secretaries of State. | GAO-14-634
Kansas

1,115,281

38,865

Using the EAVS data, we also analyzed the extent to which the use of
provisional ballots changed, if at all, between the 2008 and 2012 general
elections in Kansas and Tennessee and relative to our comparison states
of Alabama, Arkansas, Delaware, and Maine. Delaware, Kansas, and
Tennessee provided data to the EAVS for all jurisdictions in their state in
each year, but data were missing for some jurisdictions in the other
states. 87 In our analysis, data for Alabama, Arkansas, and Maine include
only data from jurisdictions in those states that reported data on
provisional ballot usage for both the 2008 and 2012 general elections.
Our analysis shows that the rate of provisional ballot usage, overall,

87

Alabama did not provide data on the total number of provisional ballots cast for 7.46
percent of jurisdictions in 2008 and 22.39 percent of jurisdictions in 2012. Arkansas did
not provide data on the total number of provisional ballots cast for 10.67 percent of
jurisdictions in 2008 and 2.67 percent of jurisdictions in 2012. Maine did not provide data
on the total number of provisional ballots cast for 28.86 percent of jurisdictions in 2008
and 0.20 percent of jurisdictions in 2012.

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increased slightly between the 2008 and 2012 general elections in
Kansas and Tennessee. The rate of provisional ballot usage also
increased slightly in Arkansas and Delaware, though the increases were
smaller than in Kansas and Tennessee. Table 5 describes the change in
provisional ballot usage between the 2008 and 2012 general elections in
treatment and comparison states.
Table 5: Change in Provisional Ballot Usage between 2008 and 2012 General Elections, in Treatment and Comparison States

State

Percentage of total ballots
that were provisional in 2008

Change in provisional ballot
Percentage of total ballots usage between 2008 and 2012
a
that were provisional in 2012
general elections

Kansas

3.18

3.48

0.30

Tennessee

0.17

0.29

0.12

Alabama

0.47

0.29

Arkansas

0.20

on

ucs
f T0.24
ity o 6
Delaware
0.09
0.11
1
. v. C
, Inc st 31, 20 0.04
ce
Maine
0.05ian
ugu
All
b
grity0.34 ed on A
Alabama/Arkansas pooled
0.27
nte
v
b
blic I 42 archi
Delaware/Maine pooled
0.07
0.07
in Pu -161
b ited
5
All comparison states pooled c
0.26
0.21
1
No.

-0.18
0.04
0.01
-0.01
-0.07
0.00
-0.05

Source: GAO analysis of U.S. Election Assistance Commission’s Election Administration and Voting Survey (EAVS) 2008 and 2012 data from jurisdictions in selected states that provided data in response
to EAVS in both 2008 and 2012. | GAO-14-634

Notes: This table includes only those jurisdictions that provided data to state officials in response to
the EAVS in both 2008 and 2012. The full EAVS data sets for 2008 and 2012 include jurisdictions that
did not report data in 1 or both years. Those jurisdictions that did not provide data in both years have
been excluded from the analysis.
a

The change in provisional ballot usage between 2008 and 2012 may not equal the percent of total
ballots that were provisional in 2012 minus the percent of total ballots that were provisional in 2008
due to rounding in subtraction.
b

”Pooled” rates of provisional ballot use reflect the grouped states’ combined total provisional ballots
divided by the grouped states’ combined total ballots cast. Because of the quasi-experimental design
of our study, we assume that the comparison states are interchangeable and thus can be pooled
together to create an additional group for analysis. The larger size of this pooled group reduces the
statistical uncertainty of our estimates.

Our analysis of changes in provisional ballot usage rates between the
2008 and 2012 general elections in the treatment and comparison states
showed that Kansas and Tennessee increased their usage of provisional
ballots by 0.35 percentage points and 0.17 percentage points,
respectively, between the two elections, relative to all other comparison
states combined, as shown in table 6. These quasi-experimental,
“difference-in-difference” estimates control for other factors that could
have affected election outcomes such as the presence of competitive

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cited

races for statewide or federal offices, voter characteristics that do not
change substantially over time (e.g., race), controversial ballot questions,
and the voter mobilization activities of campaigns. For these reasons, our
analysis suggests that the increased usage of provisional ballots in
Kansas and Tennessee from the 2008 to 2012 general elections relative
to the comparison states is attributable to changes in those two states’
changes in voter ID requirements. Moreover, positive effects on
provisional ballots are consistent with our findings that decreases in voter
turnout in Kansas and Tennessee in the 2012 general election beyond
decreases in the comparison states were attributable to those two states’
changes in voter ID requirements, as casting a provisional ballot that is
ultimately not counted is one way in which turnout could have
decreased. 88 However, our choice of comparison states was not
specifically designed to account for unique factors changing between
2008 and 2012 that could explain the changesinn
c o provisional ballot usage,
such as changes to state systems of registering voters and requirements
of Tu
. ity
6
for when provisional ballotscmustC cast.1As a result, factors other than
n . v be , 20
I
new voter ID lawsance,
may havegust 31
contributed to the increase in provisional
lli
u
ballot usage. 89A d on A
grity These findings are not generalizable beyond our specific
nte and hive
I
treatment arccomparison states.
ublic
2

in P -1614
15
No.

Table 6: Comparison of Change in Provisional Ballot Usage between 2008 and 2012 General Elections in Treatment and
Comparison State Groups
State

Kansas (%)

a

All comparison states pooled

0.12 (0.011)

0.35 (0.046)

a

Delaware/Maine pooled

0.18 (0.013)

0.30 (0.046)

Alabama/Arkansas pooled

Tennessee (%)

0.37 (0.047)

a

0.17 (0.011)

Source: GAO analysis of U.S. Election Assistance Commission’s Election Administration and Voting Survey (EAVS) 2008 and 2012 data from jurisdictions in selected states that provided data in response
to the EAVS in both 2008 and 2012. | GAO-14-634

88

Alternatively, registrants could have chosen not to attempt to vote at all. A final
possibility is that registrants attempted to vote, could not provide adequate ID, and chose
not to cast a provisional ballot.

89

For example, in its letter commenting on excerpts from the draft report, Tennessee’s
Secretary of State’s Office stated that in June 2011 Tennessee's provisional statute was
amended to allow any voter whose eligibility was challenged by an election official to cast
a provisional ballot. With this amendment, according to the letter, Tennessee extensively
trained its election officials regarding the usage of the provisional ballot throughout 2012
as well as the new photo ID requirements. Tennessee identified these as factors that
contributed to increased usage of provisional ballots.

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Notes: Entries in parentheses are 95 percent margins of error (e.g., +/- 0.047 percentage points). This
table analyzes data from jurisdictions that provided data in response to the EAVS in both 2008 and
2012. The full EAVS data sets for 2008 and 2012 include jurisdictions that did not report data in 1 or
both years. Those jurisdictions that did not provide data in both years have been excluded from the
analysis.
a

”Pooled” rates of provisional ballot use reflect the grouped states’ combined total provisional ballots
divided by the grouped states’ combined total ballots cast. Because of the quasi-experimental design
of our study, we assume that the comparison states are interchangeable and thus can be pooled
together to create an additional group for analysis. The larger size of this pooled group reduces the
statistical uncertainty of our estimates.

In addition, we analyzed the EAVS data to determine how provisional
ballot rates changed over time in our treatment and comparison states
using data reported by all jurisdictions in those states (e.g., to include all
jurisdictions responding to the EAVS in either 2008 or 2012). We
conducted this additional analysis to determine if missing data affected
o
the results of our analysis in which we excludedn
Tucs jurisdictions that did not
ofEAVS. In our second analysis, we
ty
report data for both the 2008 and 2012
v. Ci first6
obtained results similar ,tonc.
those in3our201 analysis, indicating that our
t 1,
ce I gmissing data did not affect our conclusion
exclusion of y Allian
jurisdictions with us
u
A
d n
egrit
that provisional ballot o
c Int archive usage increased in Kansas and Tennessee from
i
the
to
Publ 20082 the 2012 general election relative to comparison states.
d in 15-1614 VII provides more detailed information on the results of this
ite
Appendix
c
No. additional analysis.

Challenges Exist in
Using Available
Information to
Estimate the
Incidence of InPerson Voter Fraud

A variety of factors affect efforts to estimate the incidence of in-person
voter fraud, making it difficult to produce complete estimates. 90 For the
purposes of this report, incidence is defined as the number of separate
times a crime is committed for a specific time period. Estimating the
incidence of crime generally involves using information on the number of
crimes known to law enforcement authorities—such as crime data
submitted to a central repository within states based on uniform offense
definitions—to generate a reliable set of crime statistics. However, even
when crime data are centrally collected, the true incidence of crime can
be difficult to determine due to the potential for crimes not to be

90

For the purposes of this report, we have defined “in-person voter fraud” as involving a
person who (1) attempts to vote or votes; (2) in person at the polling place; and (3) asserts
an identity that is not the person’s own, whether it be that of a fictional registered voter,
dead registered voter, a false identity, or whether the voter uses a fraudulent identification.
In-person voter fraud is also often referred to as “voter impersonation fraud.”

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reported. 91 We have reported that crimes of fraud, in particular, are
difficult to detect, as those involved are engaged in intentional
deception. 92 For example, in the areas of Medicare fraud and Internal
Revenue Service refund fraud involving identity theft, we have reported
that reliable estimates of the extent of such fraud are not known. 93 In
addition, with regard to identity fraud, in March 2002 we reported that no
single hotline or database captured the universe of identity theft victims
and that it was difficult to fully or accurately measure the prevalence of
identity theft. 94 Although not necessarily the same as other types of fraud,
the incidence of in-person voter fraud can be difficult to estimate. We
reviewed studies conducted by academic researchers and others on
efforts to identify instances of in-person voter fraud. We also reviewed
information from federal and state agencies on election fraud. Based on
our review of these information sources, we found that various challenges
and limitations in information available for estimating the incidence of incson
of Tu
person voter fraud make it difficult ito determine a complete estimate of
ty

16
. v. C
, Inc st 31, 20
ce
n
ugu
Allia
grity ived on A
te
ic In
ch
Publ 6142 ar
in
cited o. 15-1
N

91

Like other crimes, instances of in-person voter fraud may occur that are never identified
by or reported to officials. This is due, in part, to challenges associated with identifying this
type of fraud, as both successful fraud and deterred fraud may go undetected. In addition,
it has been suggested that without a personal identification requirement it is difficult to
detect in-person voter fraud. See, e.g., Crawford v. Marion Cnty. Election. Bd., 472 F.3d
949, 953 (7th Cir. 2007); In re Request for Advisory Opinion Regarding Constitutionality of
2005 PA 71, 740 N.W.2d 444, 457-58 (Mich. 2007). However, others have suggested that
in-person voter fraud in particular may be more easily detectible. See, e.g., Crawford v.
Marion Cnty. Election Bd., 553 U.S. 181, 227 (2008) (Souter, J., dissenting) (stating that
“there is reason to think that impersonation of voters is the most likely type of fraud to be
discovered”) (internal citations omitted).

92

GAO, Medicare: Progress Made to Deter Fraud, but More Could Be Done,
GAO-12-801T (Washington, D.C.: June 8, 2012).

93

GAO-12-801T and GAO, Identity Theft: Total Extent of Refund Fraud Using Stolen
Identities is Unknown, GAO-13-132T (Washington, D.C.: Nov. 29, 2012).

94

GAO, Identity Theft: Prevalence and Cost Appear to be Growing, GAO-02-363
(Washington, D.C.: Mar. 1, 2002).

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such fraud. 95 For example, based on our own review of federal and state
information sources, we identified challenges such as there is no single
source of information on possible instances of in-person voter fraud and
variation exists among federal and state sources in the extent to which
they collect information on election fraud.
The studies we reviewed identified few instances of in-person voter fraud,
and while they provide information on efforts to estimate in-person voter
fraud, limitations in the populations studied and sources used make it
difficult to use these studies to determine a complete estimate of the
incidence of in-person voter fraud. In particular, we reviewed five
research studies, 96 five studies by state agencies, and information
provided by DOJ. The five studies by researchers we reviewed as part of
our literature review used various methods and sources of information to
n
identify instances of in-person voter fraud. Table 7 describes the
ucso
approaches used in each study andy of limitations we or the studies’
the T
. Cit 2016
authors identified.
nc. v
,
I

st 31
nce,
Allia on Augu
y
d
egrit
c Int archive
i
Publ 6142
in
cited o. 15-1
N
95

We conducted a literature review to identify studies that attempted to identify instances
of in-person voter fraud among the populations studied and sources used. We reviewed
more than 300 studies and determined that five attempted to collect data on in-person
voter fraud using a systematic methodology. The remaining studies either did not provide
sufficient information about the methodology used for us to evaluate it, or relied on
anecdotal examples of fraud as their basis for analysis. One study we reviewed but did not
include among the five profiled here attempted to determine the extent to which reports
submitted to the Supreme Court in defendants’ and amicus briefs in Crawford v. Marion
County Election Board, 553 U.S. 181, contained supporting evidence for allegations of inperson voter fraud but the description of the study’s methodology did not provide sufficient
information for us to evaluate the methods used. (Justin Levitt, “Election Deform: The
Pursuit of Unwarranted Electoral Regulation,” Election Law Journal, vol. 11 (1), 2012). For
additional detail regarding our methodology, see app. II.

96

The five studies include John S. Ahlquist, Kenneth R. Mayer, and Simon Jackman,
“Alien Abduction and Voter Impersonation in the 2012 U.S. General Election: Evidence
from a Survey List Experiment,” October 30, 2013, forthcoming. Election Law Journal; Ray
Christensen and Thomas J. Schultz, “Identifying Election Fraud Using Orphan and Low
Propensity Voters,” American Politics Research, vol. 42 (2), 2014; M.V. Hood III and
William Gillespie, “They Just Do Not Vote Like They Used To: A Methodology to
Empirically Assess Election Fraud,” Social Science Quarterly, vol. 93 (1), 2012; Lorraine
C. Minnite, The Myth of Voter Fraud. Ithaca: Cornell University Press, 2010; and Corbin
Carson, “Exhaustive Database of Voter Fraud Cases Turns Up Scant Evidence That It
Happens,” News21, Aug. 12, 2012, http://votingrights.news21.com/article/election-fraudexplainer/, accessed July 24, 2014.

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Table 7: Summary of Findings and Methods from Studies That Attempted to Identify Instances of In-Person Voter Fraud
Study author
and date
published
Ahlquist, Mayer,
and Jackman.
October 2013

Scope

Methods

Nationwide

cited

Results

Limitations

Used a survey list experiment to detect No significant
The authors note that their
fraud, particularly voter impersonation
indicators of voter
findings were necessarily
fraud. In this method, commonly used in impersonation fraud limited to the prevalence of
survey research to detect sensitive
in the 2012 general voters casting fraudulent
behaviors, survey respondents were
election.
ballots, not the number of
randomly assigned to one of two groups
fraudulent ballots cast. In
and were presented with a list of
principle a tiny number of
activities they may have engaged in
people could have cast many
during the prior election (such as
thousands of fraudulent
attending a rally, or reading about the
ballots, but the authors viewed
election in the news). In one version of
that as unlikely because
the experiment, one list included
casting in-person ballots,
engaging in in-person voter fraud
fraudulent or otherwise, is time
on
(“casting a ballot under a name that was
Tucs intensive.
of
not my own”); the other list was identical
The authors note that their
City 016
but did not include in-person voter fraud. . v.
survey has limited statistical
, Inc st 31, 2
e
Instead, the second list included an
power. The authors state that
lianc to Augu
activity respondents ty Al
were unlikely n
a much larger sample would
o
griattended a political
d
have engagedtin (“I
be required to detect a very
In e r candidate
c event for a chive in my
fundraising
bli
a
small difference between the
in Pu town.”).142
home -16 Respondents were asked
two groups evaluated for the
5 of these activities, rather than
how 1
study. If the incidence of voter
No.many activities, they had
which specific
fraud is rare, the study sample
engaged in. The researchers
is not large enough to detect it
hypothesized that the difference
with statistical certainty. The
between the numbers of items selected
authors estimate that a sample
by respondents in the two groups would
of 260,000 individuals would
provide an indication of the prevalence
be required to reliably detect
of in-person voter fraud.
low levels of voter fraud, such
as 1 percent. The authors’
sample included 1,000 U.S.
citizens age 18 and over.

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Study author
and date
published
Christensen and
Schultz. January
2014

Scope

Methods

Ohio; Miami,
Florida; and
Dagget County,
Utah

cited

Results

Limitations

Used a five-step methodology that
No suspicious
The authors assume that
combined both qualitative and statistical anomalies found in
fraudulent ballots will be
analysis of voting records. Specifically,
voting patterns.
created in a coordinated
to determine the extent to which
fashion by the perpetrators of
evidence of in-person voter fraud
the fraud, using the names of
existed, the authors looked at orphan
unlikely voters (i.e., orphan or
votes and voters with the lowest
low propensity voters). The
propensity to vote based on official
authors note that this
turnout data in local jurisdictions within
assumption is generally valid
three states. The authors defined
because of the severe
orphan votes as votes cast in a lowconsequences for any
profile election by a voter who did not
campaign if even a small
vote in the preceding and subsequent
number of votes are cast in the
high-profile elections. Propensity to vote
names of people who later
in a specific election was calculated
attempt to vote.
using that person’s past and future
on authors indicate that the
s The
voting record and other voter
f Tuc older the elections, the fewer
ity o 6
characteristics. After identifying
the number of actual voters in
v. C 201
jurisdictions with unusual patterns of Inc.
that election that were
,
cethe gust 31,
n
orphan and low-propensitylvoters,
included in their analysis,
Al iaresearch u
authors conducted rity
extensive
nA
since voting and registration
ntegtherchived o
to assessc I
whether
observed
records are publicly available
blihad an innocent explanation
a
anomaly
only for those voters currently
in Puas -16142 housing when
(such15 university
registered to vote.
.
No
encountering multiple new registrants at
We determined that the
the same address).
method used is not based
entirely on statistical
calculations, but requires
professional judgment as to
the likelihood that jurisdictions
with suspicious numbers of
orphan and low propensity
voters experienced fraud or
that there is a plausible
alternative explanation other
than fraud to account for the
results.

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Study author
and date
published
Hood III and
Gillespie. March
2012

Minnite. 2010

Scope

Methods

Georgia

ed

Results

Limitations

Used data mining and record linkage
Five questionable
The authors indicate that the
techniques to match registration and
votes cast in the
county registrars associated
voter history files to listings of recently
November 2006
with the 5 questionable votes
deceased individuals to search for
general election in
did not respond to their
fraudulent votes being cast on behalf of Georgia.
requests for information; if
such registrants. Process involved (1)
provided, information from the
linking registration and death files by
registrars may have clarified
county, manually eliminating cases
the status of the 5
where race or ethnicity, sex, or middle
questionable votes identified.
name did not match; (2) matching the
remaining cases of deceased registered
voters to Georgia’s voter history
database in order to identify individuals
voting in the November 2006 election;
(3) checking the validity of the records
by cross-referencing these cases with
cson
the Social Security Death Index; and (4)
of Tu
ty
systematically investigating each of the
v. Ci 2016
resulting cases through examination Inc.
of
,
e,
st 31
absentee ballot request formsnc
lli
Abya and n Augu
y
certification forms signed
in-person
do
egrit
voters, generally obtainedifrom county
c Int arch ve
bli
registrars.
142
in Pu

-16

cit
15
Federal court
Analyzed 10 years of federal court
Forty eight individual
No.
records and data records and data from 4 states to search voter defendants
for instances of voter fraud.
from 4 states
charged with
violating federal
election laws from
1996-2005. These
cases may or may
not include instances
of in-person voter
fraud. One possible
state-level case of
in-person voter fraud
in New Hampshire.

Page 67

According to the author,
multiple state offices share
responsibility for handling
complaints and for
investigating and prosecuting
voter fraud allegations, making
obtaining complete information
on all potential instances of
voter fraud difficult.
The author notes that federal
case information is difficult to
review because the nature of a
crime can be difficult to identify
in charging documents,
records may be duplicates
because some data are annual
and cases extend across fiscal
years, data entry errors exist,
and the coding schemes in the
database reviewed were not
reliable.

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Study author
and date
published
News21. August
2012

Scope

Methods

Results

Nationwide

Made public records requests to federal,
state, and local election and law
enforcement officials and reviewed court
documents, official records, and media
reports to collect information on over
2,000 election fraud cases from 2000 to
2011 in an attempt to determine how
many involved in-person voter fraud.

10 confirmed cases
of in-person voter
fraud among the
over 2,000 election
fraud cases
identified.

cited

Limitations

According to News21
documentation, News21
submitted public records
requests to each of the 50
states’ departments of
elections and secretaries of
state. News21 also contacted
each state’s attorney general
and nearly 1,000 additional
county district attorneys. Some
state officials did not respond
to the request for information,
and some jurisdictions did not
provide any information to
News21 because their
computer systems
on
cs capability to searchlacked the
for election
of Tu
fraud cases.
. City 2016
nc. v
In some states’ responses to
ce, I gust 31,
n
News21, important details
Allia on Au
rity
about the case, including the
nteg rchived
circumstances of the alleged
blic I 42 a
fraud, were missing, and
in Pu -161
News21 was unable to
. 15
No
categorize the type of election
fraud or the responsible party,
such as a voter or election
official.

Source: GAO analysis of studies that attempted to identify instances of in-person voter fraud among the populations studied and sources used. | GAO-14-634

These five studies provide useful information on efforts to identify
instances of in-person voter fraud among the populations studied and
sources used. However, as shown in table 7, the studies have limitations
that affect their usefulness in estimating the complete incidence of inperson voter fraud. For example, two of the studies sought to identify
actual instances of in-person voter fraud, but there are limitations in the
completeness of information contained within the sources of information
used, such as information from federal or state data sources and
newspaper articles. 97 The three remaining studies used proxy measures
for determining whether in-person voter fraud may exist, including sample

97

These studies are: Minnite (2010) and News21 (2012).

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surveys of voters, aberrations in voter turnout patterns, and votes cast in
the names of deceased individuals. 98 These measures are indicators of
whether in-person voter fraud may have occurred within the populations
studied, but do not precisely or directly estimate how frequently in-person
voter fraud occurs. These challenges limit the extent to which information
from these studies can be used to determine a complete estimate of the
incidence of in-person voter fraud.
Five states provided us with investigative studies that focused on specific
types of election fraud. 99 The studies matched official records of voting
activity to other data sources, and then investigated any identified
discrepancies. Of the studies states provided to us, one included some
information on allegations of in-person voter fraud; the four remaining
state studies generally focused on issues such as double-voting, voting
n
by ineligible voters such as non-citizens or felons, or instances of
ucso
absentee ballot fraud, activities which of Toutside our definition of infall
. City
person voter fraud. The one .study that2016
nc v 31, included some information on
I
allegations of in-person,voter ust examined instances of votes cast in
fraud
nce
Allia on Aug in one state. It examined about 200
ity
r
the name of deceased persons
nteg
ved
questioned votes
blic I 42 archi that were cast in the November 2010 election and
Pu
in ultimately determined that all but 5 of the questioned votes could be
61
cited o. 15-1
N attributed to errors by state or local officials—including clerical errors,
data matching errors, errors in scanning voter registration forms, and the
issuance of absentee ballots in the wrong name—or to applications for
absentee ballots by voters who died before the election. For the
remaining 5 allegations, the study could not conclusively determine
whether in-person voter fraud occurred. In conducting this study, the
South Carolina State Law Enforcement Division reviewed documentation
of the questioned votes, such as poll lists and voter registration records,
to determine whether the questioned votes occurred as a result of clerical

98

These studies are: Ahlquist, Mayer, and Jackman (2012); Christensen and Schultz
(2013); and Hood III and Gillespie (2012).

99

Flynn, Julie. Investigation of Suspected Dual Voting in November 2008 and 2009
Elections, a special report prepared for the Maine Secretary of State, January 2012;
General Assembly of Maryland, Department of Legislative Reference, Report of the Task
Force to Review the State’s Election Law (Annapolis, MD: Dec. 31, 1995); South Carolina
Law Enforcement Division, Preliminary Inquiry—Alleged Dead Voter Fraud—2010 SC
General Election (Columbia, SC: May 11, 2012); State of Colorado, Secretary of State,
Non-Citizens on Colorado’s Voting Roles: Problems and Solutions (Denver, CO: Aug. 16,
2012); State of Utah, Office of the Legislative Auditor General, Driver’s Licenses Issued to
Undocumented Aliens (Salt Lake City, UT: Feb. 8, 2005).

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error, such as marking the wrong individual as having voted, or for some
other reason, such as fraud. 100 This study provides useful information on
the results of a review of votes cast in the name of deceased persons in
one election in one state. However, as the study focused on the
investigation of a specific type of alleged in-person voter fraud—votes
cast in the name of deceased persons—it does not provide information
needed for estimating the overall incidence of in-person voter fraud.
In addition, with regard to DOJ, in July 2014, the department submitted a
declaration as part of a court filing in litigation regarding a state voter ID
law. 101 In that declaration, the Director of the Elections Crimes Branch of
the Public Integrity Section of the Criminal Division stated that a review of
data from DOJ’s case management systems—the Automated Case
Tracking System (ACTS II) managed by DOJ’s Criminal Division and the
Legal Information Office Network System (LIONS) managed by the
cson
Executive Office for U.S. Attorneyst(EOUSA)—and certain publicly
of Tu
iy
6
available and related court c. v. C indicated that there were no apparent
n records 1, 201
ce, I gust 3
cases of in-person voter impersonation charged by DOJ’s Criminal
n
u
Allia
Division orriby U.S. Attorney’s offices anywhere in the United States, from
g ty ived on A
nte rch 3, 2014. 102 We were not able to obtain more detailed
2004
blic I through July
a
142
in Pu information on DOJ’s methodology, because the case was ongoing at the
d
5-16
ite
c
1
No. time of our review.
For the purposes of our review, we obtained and reviewed information
from federal and state agencies, as well those studies noted above that
attempted to determine instances of in-person voter fraud, to determine
the extent to which information from these sources could be used to
estimate the incidence of in-person voter fraud. Based on our review of
these information sources, we found that limitations with these available
sources make it difficult to determine a complete estimate of in-person
voter fraud. The key factors we identified that made this difficult include
that there is no single source of information on possible instances of in-

100

The report cited multiple instances where election officials allocated the vote of a father
or son to their deceased relative of the same name.
101

Veasey v. Perry, No. 13-193 (S.D. Tex. July 7, 2014), ECF No. 390-2.

102

In its filing, for the purposes of its database review, DOJ defined “in-person voter
impersonation” as the use of the name of another person to obtain and vote a ballot while
physically present at the polls. For a description of each database and the types of
information each contains, see appendix VIII.

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person voter fraud and that variation exists among federal and state
sources in the extent to which they collect information on election fraud.
No single source of information on possible instances of in-person
voter fraud. As with other types of fraud, there is no single source or
database that captures the universe of allegations or cases of in-person
voter fraud across federal, state, and local levels, making it difficult to
determine a complete estimate of the incidence of in-person voter fraud.
This is in part due to the fact that responsibility for addressing election
fraud is shared among federal, state, and local authorities. As discussed
earlier in this report, state and local authorities are responsible for the
administration of state and federal elections, and state statutes regulate
various aspects of elections, including activities associated with election
fraud broadly, and in-person voter fraud specifically. For election fraud
committed during federal elections, states andon
localities share jurisdiction
Tucs Division and United
f
with federal authorities, including DOJ’s Criminal
ity o
Within 2 given
States Attorneys’ Offices. 103 . v. C any 016 state, various state and
, Inc
31,
local agencies maynceresponsible for identifying, investigating, and
lia be August
Al
y
prosecutingtelection fraud, and information may not be shared among the
d on
egri
c Int For rchive allegations of election fraud may be reported to any
i
entities. aexample,
2
Publ
combination
d in 15-1614 of local, county, or state election officials; law enforcement;
ite
c
No. or county or state prosecutors, among others. Similarly, the investigation
and prosecution of these allegations may be conducted by local or state
law enforcement or prosecutors. Of the 46 states that responded to our
requests for interviews, state election officials in 34 states reported that
multiple agencies or units are responsible for identifying and investigating
allegations of election fraud. 104 Of those states, officials in 28 states
reported that local or county officials are at least partially responsible for
addressing election fraud. In another 3 states, state officials reported that
local or county officials are exclusively responsible for identifying and
investigating allegations of election fraud. In these 31 states where local

103

Federal jurisdiction over election fraud is established in elections when a federal
candidate is on the ballot. In the absence of a federal candidate on the ballot, federal
jurisdiction may be obtained where facts exist to support the application of federal criminal
laws that potentially apply to both federal and non-federal elections. According to DOJ,
these generally include election frauds that involve the necessary participation by public
officers, voting by noncitizens, and fraudulently registered voters.
104

We excluded the District of Columbia from this portion of our analysis because officials
told us that election fraud cases are referred directly to the U.S. Attorney’s Office for the
District of Columbia.

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or county officials have some responsibility for addressing election fraud,
allegations, investigations, prosecutions, and convictions are not
necessarily reported to officials at the state level. For example, election
officials in 1 state reported that allegations made at the county level can
be referred directly to the county attorney without ever involving statelevel officials. Given the multiple entities that may be involved in
indentifying, investigating, or prosecuting in-person voter fraud, it is
difficult to obtain data sufficient to support an incidence determination.
Two of the studies we reviewed that used federal and state sources to
attempt to identify instances of in-person voter fraud also faced
challenges as a result of the shared responsibility for addressing election
fraud. For example, News21, an educational journalism program,
gathered, organized, and analyzed reported cases of election fraud.
News21 contacted state and local officials in son states to compile a
all 50
Tuc 2000 through 2011. 105 In
database of cases involving election fraud from
ty of
v. Ci 2016
some cases, state and local .officials contacted referred News21 to the
c
1,
e, In
county district attorneys, who ust 3referred them back to the secretary of
lianc Aug then
Al of elections. Similarly, Minnite found that multiple
state oregrity
departmentd on
c Int archiveresponsibility for handling complaints in these states
i
state
2
Publ 6offices share
and 14
d in 15-1that policies for investigating and prosecuting voter fraud complaints
ite
c
No. are not uniform within these states.
Federal and state agencies vary in the extent to which they collect
information on election fraud. Federal and state agencies vary in the
extent to which they collect and maintain information on election fraud in
general and in-person voter fraud in particular, making it difficult to
estimate the incidence of in-person voter fraud. For example, at the
federal level, various databases may include information on federal
investigations, prosecutions, and convictions involving in-person voter
fraud. In particular, we identified four federal databases that could contain
such information. Two of these databases are managed by DOJ
components—the LIONS database and the ACTS II database; the other
two databases are managed by components of the federal judiciary—the
Integrated Database, managed by the Federal Judicial Center (FJC) and
an Oracle database, managed by the United States Sentencing

105

Corbin Carson, “Exhaustive Database of Voter Fraud Cases Turns Up Scant Evidence
That It Happens” News21, Aug. 12, 2012, accessed July 24, 2014,
http://votingrights.news21.com/article/election-fraud-explainer/.

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Commission (USSC). 106 These four databases potentially contain the
universe of all federal in-person voter fraud investigations, prosecutions,
and convictions that have been reported to these entities. However, given
the types of data maintained on cases in each database, officials from
each agency said it would be challenging to identify these cases because
there is no specific code for identifying or tracking in-person voter fraud in
the four databases. For example, the FJC’s Integrated Database stores
information on criminal cases filed in federal district court, and the
USSC’s Oracle database collects information solely on defendants
convicted for federal crimes. Although each of these two databases has
codes that identify type of criminal offense, neither has any specific code
for election crimes.
Further, from our interviews with officials from the four federal agencies,
we identified 14 different statutory provisions son which in-person voter
c under
fraud may be prosecuted. However,yunderu
of T each of these 14 statutes, a
. Cit
6
variety of conduct other than. in-person voter fraud may be prosecuted,
nc v 31, 201
I
making searching ance,
by statutegust a database over inclusive. 107
within
li

Au
y Al
egrit hiv on
ntalso varieded the extent to which they collected and maintained
States
in
blic I 42 arc
in Pu information on election fraud more broadly or in-person voter fraud in
d
161
cite
15No. particular. 108 Of the 46 states we interviewed for our review, 27 states

provided documentation to us related to election fraud, and this
documentation was in a variety of formats. For example, seven states that

106

For a description of each database and the types of information each contains, see
appendix VIII. We identified these databases through discussions with agency officials
and our review of relevant literature.
107

For example, 18 U.S.C § 911 sets forth the offense of falsely and willfully representing
oneself to be a citizen of the United States, which may encompass conduct and actions
beyond in-person voter fraud. Additionally, 42 U.S.C § 1973i(c) involves, among other
things, knowingly or willfully giving false information as to name, address, or period of
residence in the voting district for the purpose of establishing voter registration eligibility,
which is a separate and distinct offense from in-person voter fraud. Agency officials stated
that in-person voter fraud could be prosecuted under either of these statutes, depending
on the facts and circumstances of the case.
108

As mentioned above, jurisdiction for in-person voter fraud is shared by federal, state,
and local authorities. DOJ officials said that determining the incidence of allegations of
voter fraud would require contacting states, because most election administration is
carried out at the state level and that states have first level jurisdiction. These officials told
us that whether or not the federal agencies learn of an incident of voter fraud generally
depends on two factors (1) which official first receives the allegation and (2) whether the
state involves the federal government, among other things.

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became aware of fraud allegations through hotlines or online complaint
forms provided us with spreadsheets containing information such as the
date of the complaint, the name and contact information of the individual
making the complaint, or an open-ended narrative field describing the
alleged election law violation. Most of the documentation provided by the
27 states was not sufficiently detailed for us to determine whether inperson voter fraud was involved. In addition, 5 of the 27 states provided
documentation that was focused on instances of election fraud that had
been determined to warrant investigation or prosecution by a specific unit
within the state responsible for addressing election fraud or by the state’s
attorney general. These states’ documentation did not necessarily include
all allegations of election fraud made to state-level authorities, because
reports made to local authorities were not necessarily included. 109 As a
result, the documentation we reviewed did not provide a complete picture
of instances of in-person voter fraud within theon
cs state, even where
documentation was provided to us.ty of Tu

. Ci
6
nc. v 31, 201
ce, I gust
The literature welireviewed identified similar challenges associated with
l an
u
variation gritheA dstates collected on in-person voter fraud. For
in ty data on A
nte News21e
example, archiv analyzed 2,068 election fraud cases from 2000 through
blic I
in Pu 2011, 142acknowledged limitations with the data it received. According to
6
cited o. 15-1 but
N the study, some state officials did not respond to requests for information,
and some jurisdictions did not provide any information to News21
because jurisdiction officials reported that their computer systems lacked
the capability to search for election fraud cases. In some states’
responses to News21, important details about the case were missing,
including the circumstances of the alleged fraud. In these cases, News21
could not categorize the type of election fraud or the responsible party,
such as a voter or election official.

Agency and Third
Party Comments and
Our Evaluation

We provided a draft of this report to DOJ, EAC, FJC, and USSC for their
review and comment. None had comments on the draft report.
We also provided excerpts of the draft report to the Secretaries of State
Offices of each of the six treatment and comparison states we selected
for our review. The excerpts for each treatment state–Kansas and

109

In addition, as previously discussed, five states provided us with investigative studies
that focused on specific types of election fraud.

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Tennessee–included a full description of the methodology we employed
in our study to select the treatment and comparison states and the
findings that specifically pertained to each state regarding the costs of
selected voter ID documents, the effects of changes in voter ID
requirements on turnout and the overall number of provisional ballots
cast, and the total number of provisional ballots cast and counted for ID
reasons. The excerpts for each of the comparison states–Alabama,
Arkansas, Delaware, and Maine—included a description of the
methodology we employed to select the comparison states, and those
findings that pertained to each state regarding the costs of selected voter
ID documents, if applicable, and changes in provisional ballot usage
between the 2008 and 2012 elections. 110 The Secretary of State Offices
of Arkansas, Kansas, and Tennessee provided written comments on the
excerpts provided to them for review, which are reproduced in full in
appendixes IX, X, and XI, and incorporated in on report as appropriate.
cs the
The Office of the Secretary of State y oAlabama provided technical
of f Tu
it
comments on the excerpt nc. v. C for 2016 which we incorporated as
provided
, review,
I
appropriate. Stateance, officials in Delaware and Maine reviewed the
election gust 31
Alli had Au
report excerpts andd on no comments.
grity
e

t
ic In
chive
Publ 6142 ar
in Overall,
cited o. 15-1 the Secretary of State Offices in Kansas and Tennessee stated
N that they believe that the report is flawed, and Tennessee officials noted

that they do not confirm the data we used. The Secretary of State Offices
from these two states disagreed with the methodology of our study,
raising two common points of disagreement. First, the Offices in both
states disagreed with aspects of the design of our study, specifically the
criteria we used to select treatment and comparison states. Kansas and
Tennessee asserted that their states were different from the states with
which they were being compared, and thus our comparisons were flawed.
Kansas and Tennessee stated that the larger declines in turnout that we
found in their states, versus declines in the comparison states, could be
explained by factors other than changes in their states’ voter ID laws,
occurring in either their own states or the comparison states. The
Secretary of State’s Office in Arkansas also raised a number of concerns
regarding the criteria we used to select it as a comparison state, including
that there was no election for any statewide office in 2008 and 2012,
there was no major party opposition in the 2008 races, and there was a

110

As of June 2014, neither Delaware nor Maine required all eligible voters to present
either a government issued ID or a photo ID at the polls prior to voting.

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change in political climate between 2008 and 2012. Second, the state
election offices in both Kansas and Tennessee questioned the validity of
one of the data sources we used to measure turnout—the voter history
and registration data that we purchased from Catalist LLC. Tennessee
questioned the reliability of these data, stating that the vendor is not a
neutral party, but an explicitly “progressive” data firm and its list of clients
includes a number of organizations opposed to voter ID laws. Tennessee
also stated that the Secretary of State’s Office had no record of Catalist
obtaining data from the Secretary of State after 2010, and thus could not
attest to the accuracy or reliability of the 2012 data supplied to us by
Catalist. Further, both Kansas and Tennessee questioned the validity of
the vendor’s estimates of registrants’ race, which are based on an
algorithm supplied by a third party. The Secretary of State’s Offices in
both states therefore took issue with our analyses that showed greater
declines in turnout among African-American registrants in their respective
cson
states than among African-American registrants in the comparison states.
of Tu
y

. Cit
6
nc. v 31, 201
I
ce raisedust other issues of disagreement. First, it
In addition, Tennessee ,
two
llian
ug
noted that rour A d onof changes in voter turnout by age and race using
g ity analyses A
e
nte Population Survey (CPS) as a data source are inconsistent
v
the I
blicCurrentarchi
in Pu with 6142 sub-group analyses reported by CPS. Second, regarding our
cited o. 15-1 official
N analysis of provisional ballot usage, Tennessee stated that it believes we
ignored unique factors that contributed to the increased use of provisional
ballots in that state, compared to use of provisional ballots in the
comparison states.
We address each of these comments below.
Selection of Treatment and Comparison States
Regarding the design of our study, we believe that we used appropriate
criteria, and correctly applied the criteria to select our treatment and
comparison states. As we discuss on pp. 46-47 of our report, and pp.
130-135 of appendix V, after we identified states for the treatment group,
we then applied additional selection criteria to ensure that the treatment
group states we selected did not have other changes that could plausibly
account for any changes in voter turnout between the 2008 and 2012

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general elections. 111 Specifically, in selecting Kansas and Tennessee as
our treatment states, we selected states that did not experience changes
in other election laws or practices between 2008 and 2012 that could
substantially affect turnout and had similar election environments in 2008
and 2012 in terms of, for example, competitiveness of races and
presence and competitiveness of ballot initiatives, among other things. As
described in table 10 on pp. 134-135, we first conducted a legal analysis
for each of the potential treatment states to determine if relevant election
laws or procedures changed contemporaneously with the changes to the
potential treatment states’ ID laws. In its response, Tennessee noted that
officials responsible for the administration of elections changed
substantially at the state and local levels, and approximately thirty pieces
of legislation were passed during the time between the 2008 and 2012
elections. Tennessee also noted that the political climate in the state
changed substantially from 2008 to 2012, withon Tennessee House of
cs the
Representatives majority party switchingTu2008. We did not consider
of in
ity
changes in administrativenc. v. C in 2016 offices as part of our
positions election
,
I
selection criteria,lias we,did not st 31 literature or research showing that
nce ugu identify
Al a onto significantly affect voter turnout. We also
y
such changes are likely A
egrit hiv d
c Int changeseto Tennessee election legislation and determined that
i
reviewed arc
2
Publ
none 1 the
d in 15-16of4 changes was likely to substantially affect turnout based on
ite
c
No. our legal review of those changes. 112 In addition, according to academic
research on voting behavior in American politics, the party control of state
legislatures is not is not among the variables identified as being
associated with turnout in presidential general elections.

111

We identified as potential treatment states those that had implemented government
issued photo ID requirements between the 2008 and 2012 general elections that also
generally required voters to follow up with elections officials with acceptable ID in order to
have their votes counted if they attempt to vote without acceptable ID.
112

For example, we reviewed for all potential treatment states laws related to early voting
and no-excuse absentee voting because the enactment of such laws may have a
significant impact on voter turnout. Tennessee law, which provides for an early voting
period, was amended in 2011 to shorten the early voting period by ending early voting 7
days, as opposed to 5 days, prior to the election for a presidential preference primary.
Because this change only related to the presidential preference primary, we concluded it
was not likely to substantially affect voter turnout for the 2008 or 2012 general elections. In
addition to laws related to early and no-excuse absentee voting, we reviewed enacted
election-related legislation for each treatment state for changes related to Election Day
registration, felon disenfranchisement, and third-party registration, as well as for other
legal changes that could significantly affect voter turnout, such as those related to voter
mobilization or education efforts.

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In addition to our legal analysis, we collected data on the competitiveness
of statewide and federal elections in the potential treatment states in
order to ensure that changes over time in voter mobilization efforts by
campaigns were not likely to affect voter turnout in 2008 or 2012. We
considered a race to be competitive if the margin of victory was fewer
than 20 percentage points. As discussed on pp. 132-133 of our report,
and shown in Table 12 on p. 141, using a number of indicators of
competitiveness, including whether a statewide race (such as for U.S.
Senate or Governor) was held in the state in 2008 or 2012, or the margin
of victory for races that were held—the presidential race, races for U.S.
Senate and U.S. House of Representative, races for other statewide
offices, and ballot questions—our analysis indicated that Kansas and
Tennessee had generally noncompetitive general election environments
in both 2008 and 2012.

cson

Tu
In their responses, Kansas and Tennessee stated that the 2012 election
y of
. Cittheir016
was particularly non-competitive in
respective states, and further,
v
Inc. t 31, 2
that the states weance, as comparison states had higher levels of
chose
lli
ugus
competitiontin A d making these states inappropriate comparators.
gri y 2012, on A
te
hive
ic In
Kansas noted that it had no statewide political campaigns in 2012 other
2 arc
Publ 614presidential campaign, and presidential campaigns typically are
in
than
cited o. 15-1 the
N not active in Kansas; for example, Kansas noted there were no get-outthe-vote efforts in 2012. Tennessee noted, among other things, that the
strength of the U.S. Senate campaigns differed in 2008 and 2012, and
that the state drew minimal campaign dollars from the presidential
campaigns to drive turnout in 2012. Kansas and Tennessee also stated
that salient electoral issues in 2012 in Alabama, Arkansas, Delaware, and
Maine made them inappropriate comparators. For example, Kansas
noted that Maine had a race for U.S. Senate in 2012, whereas Kansas did
not, and Tennessee noted that Arkansas, Alabama, and Maine all had
controversial issues on their ballots in 2012.
The discussion below explains how we considered these factors when
applying our methodology and why we believe our approach is
appropriate for selecting treatment states and comparison states. We
selected comparison states where the patterns in electoral competition
did not substantially change from the 2008 to the 2012 general election
and were similar to the patterns in the treatment states. Differences
between the treatment and comparison states in any one year do not bias
impact estimates, so long as these differences are constant across years,
and the statistical properties of the difference-in-difference methods we
use to estimate impact ensures that factors that may vary over time would
not bias our estimates, as we discuss on pp. 148-149. Further, as we

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discuss on pp. 135-145, we used several criteria to choose states which
matched Kansas and Tennessee in election cycles and the
competitiveness of statewide races. We attempted to match U.S. Senate
and gubernatorial election schedules in comparator states with those of
Kansas and Tennessee, so as to avoid choosing states having
mobilization efforts different from the treatment states that might
differentially drive turnout. We examined the competitiveness of the
presidential races, races for statewide offices, and ballot initiatives in the
comparison states we selected by examining the margins of victory in
these races. Table 12 on p. 141 shows the results of efforts to match
comparison states with treatment states in terms of the margins of victory,
indicating that the states generally matched election cycles, and, where
they did not, margins of victory for races held were greater than 20
percent. On pages 142-144, we also discuss in detail our analysis of
statewide ballot races in the 4 comparison states, to ensure that there
cson
were no particularly salient or competitive u
of Tballot questions that might have
. City
6
affected voter turnout inconsistently across both elections (i.e.,
nc. v 31, 201
ce, I gus in
contributed to increased turnout t 2008 but not 2012, or vice versa).
lian

l
u
rity A ed n A
nteg rtohselect o
v
Our I
comparison states was similar to the process we
blic process c i
a
1 select treatment states. We repeated our legal analysis for each
in Pu used6to42
d
1
cite
15No. potential comparison state to ensure that none of these states

experienced changes in election law and procedures from 2008 to 2012
that could have substantially affected turnout. Arkansas, in its response,
noted that the state passed a number of measures impacting absentee
voting; during our selection process we reviewed the amendments
identified and determined that these changes and others enacted were
unlikely to substantially affect turnout. 113

113

For example, under Arkansas law, a designated bearer—a person identified and
authorized by the applicant to obtain from the county clerk or to deliver to the county clerk
the applicant's ballot—may obtain absentee ballots for not more than 2 voters; we
identified amendments to this law in 2011 that required the county clerk to notify the
prosecuting attorney if the county clerk knows or reasonably suspects that a designated
bearer has more than 2 absentee ballots in his or her possession, and provided that the
county clerk cannot accept any absentee ballots from a designated bearer who does not
sign the voter register under oath (the requirement for a signature under oath by the
designated bearer did not change). We determined that these changes were unlikely to
substantially affect voter turnout because they enacted additional procedures for county
clerks and did not impose any new requirements for voters or designated bearers.

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Moreover, Kansas stated that it is not appropriate to compare Kansas to
states that had any statewide race, such as Maine. In selecting the four
comparison states, we selected two states—Alabama and Arkansas—
that also had no U.S. Senate races in 2012, no gubernatorial races in
either 2008 or 2012, and no competitive presidential races, like Kansas.
Although Alabama and Arkansas had races for U.S. Senate in 2008,
neither race was competitive, with margins of victory equal to 27 and 59
percent, respectively, and therefore were unlikely to have experienced
unusually high turnout. For similar reasons, we believe that our other two
comparison states, Delaware and Maine, remain appropriate
comparators, because their U.S. Senate races in 2012 were not
competitive, with margins of victory equal to 37 and 21 percent,
respectively. Nevertheless, to test the robustness of our results to
alternative choices of comparison states, we estimated the effect of ID
laws using different combinations of comparison states and obtained
cson
consistent results across the multiple of Tu
comparisons.
y

. Cit
6
nc. v 31, 201
I
c that g U.S.
Tennessee also notede, its ust Senate race in 2012 was nonn
u
Allia
competitiveitcompared to A race in 2008. Our test for evaluating U.S.
gr y ived on the
nte rch
Senate
blic I races among potential treatment states was either that a race was
2a
in Pu not1614because 2008 or 2012 was not a U.S. Senate election year in the
d
5- held
ite
c
1
No. state or that a U.S. Senate race that was held had at least a 20 percent
margin of victory, indicating that the race was not competitive and not
likely to experience unusually high turnout. In the case of Tennessee,
U.S. Senate races were held in both 2008 and 2012, each with a 34
percent margin of victory, indicating similar levels of competitiveness and
consequential effect on voter turnout. As with Kansas, when conducting
our analysis related to voter turnout, we used multiple combinations of
treatment and comparison states, as well as a nationwide comparison
group, to determine if our results were consistent across the selected
states. As shown in appendix VI, the results are consistent across
multiple comparisons.
With regard to Tennessee’s specific concerns about ballot issues in
Alabama, Arkansas, and Maine, we examined ballot questions as part of
our selection process for treatment and comparison states. We collected
data on the margin of victory for all statewide ballot questions in each
state, and systematically searched news media and other electronic
information databases to ensure that there were no particularly salient or
competitive ballot questions that might affect voter turnout inconsistently
across both elections (i.e., contributed to increased turnout in one year
but not the next, or vice versa). As a result, we selected comparison
states that had no ballot questions, noncompetitive questions, or similarly

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competitive questions present in both the 2008 and 2012 general
elections, as described in appendix V. The relevant question for our
analysis regarding comparison state qualifications is how the election
environments compared within each state between the 2008 and 2012
general elections, rather than whether each comparison states’ election
environment was similar to Tennessee in 2012. This is because we
compared changes in turnout within each comparison state to changes in
turnout within Kansas and Tennessee to determine whether or not there
were any effects of voter ID law changes. We conducted extensive
sensitivity tests of our results by comparing Kansas and Tennessee to
individual comparison states, multiple groups of comparison states, and a
nationwide comparison group, and found our results to be consistent.
Further, Tennessee noted that in 2012, Alabama had an amendment
dealing with health care reform and an amendment dealing with racial
cson
segregation and poll taxes on the ballot. Tu
of Tennessee noted that both
. City
6
amendments should have increased turnout. In analyzing the
nc. v 31, 201
I
competitiveness lof nce,
Alabama’sust
ballot initiatives in 2008 and 2012, we
l ia
ug
found that rthe A d onwere similarly competitive in both years.
g ity initiatives A
e
nte rchifound that in 2012, 11 questions were on the ballot, and 3
v
Specifically,
blic I 42 a we
1
in Pu were6competitive, whereas in 2008, 6 questions were on the ballot and 5
cited o. 15-1
N were competitive (that is, where the margins of victory were less than 20
percent). The presence of several competitive ballot questions in both
2008 and 2012 created a similar potential for overall voter mobilization
and engagement in both years. Further, according to our analysis, the
ballot question on health care reform cited in Tennessee’s comments has
a margin of victory of 18 percent (close to our criteria of 20 percent being
considered noncompetitive), while the ballot question on eliminating
specific race based language in the Alabama Constitution was
noncompetitive, with a margin of victory of 21 percent. Nevertheless, to
ensure that our overall analysis of any effects of voter ID law changes by
race or ethnicity were not affected by individual state-level issues, we
conducted our analysis using other comparison states, which yielded
similar effects.
Tennessee also noted that Arkansas had controversial gambling issues
and a marijuana issue on the 2012 ballot, which, in their view, makes
Arkansas an inappropriate comparator. Arkansas also noted the presence
of these initiatives, stating that the controversial gambling initiatives were
physically on the 2012 ballot, but due to Arkansas Supreme Court rulings
close to Election Day, the votes cast were not counted. Arkansas noted
that many voters probably were not aware of the court’s decision to not
count the votes and the fact that both issues were on the ballot could

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have impacted turnout. In reviewing Arkansas’ ballot initiatives in 2008
and 2012, we found that Arkansas voter turnout was not likely to have
been affected to a greater degree in 2012 or 2008 by ballot questions
because each election had one competitive, salient ballot question race,
with the remaining questions either noncompetitive or not on salient
topics, as discussed in appendix V. The competitive and salient question
was related to medical marijuana in 2012 (margin of victory of 3 percent),
as noted in Tennessee’s comment, and to limiting adoptions to married
cohabitants in 2008 (margin of victory of 14 percent). This scenario of
similarly salient and competitive ballot questions in both the 2008 and
2012 general elections suggests that ballot questions likely would have
affected turnout similarly in both elections. In addition, our review of the
2008 ballot question media coverage in Arkansas indicated substantial
campaigning related to the ballot question on limiting adoptions to married
cohabitants, suggesting that voter mobilizationon
efforts in the 2008 general
Tucsthe medical marijuana
election were not unlike efforts in 2012,f when
ity o 6
question was on the ballot. c. v. C
201

31,
e, In
lianc August
Al two 2012 gambling initiatives noted by Tennessee and
With regardty the d on
egri to
c Int our hive
i
Arkansas, arcanalysis of statewide ballot questions that could affect
2
Publ
turnout was
d in 15-1614 based on officially reported results. In this case, we did not
ite
c
No. evaluate the gambling initiatives since votes for those initiatives were

cast, but not counted, and were subsequently not reported in the official
2012 Arkansas general election results. We acknowledge the possibility
that the initial salience and subsequent confusion about the gambling
initiatives could have affected turnout. However, our use of multiple
comparison states controls for the bias specific to any particular
comparison. Our analysis of voter turnout included versions that excluded
Arkansas, the results of which mirrored our general findings, as shown in
appendix VI.
Tennessee also noted that Maine had the issue of same sex marriage on
the ballot in 2012, and believed that a significant amount of money was
spent to support and oppose the measure. We found that five ballot
questions were on Maine’s 2012 general election ballot, two of which
were competitive. Three questions were on the 2008 general election
ballot, two of which were competitive. The presence of competitive and
salient ballot questions in both years suggests that voter mobilization was
unlikely to have been higher in one of the elections versus the other.
However, consideration of Maine’s 2012 same-sex marriage initiative, as
well as competitive imbalances between the 2008 and the 2012 general
elections in Maine’s two congressional districts, led us to conduct our
analysis both with and without Maine included among our comparison

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states to ensure the validity of our findings. Our results were consistent
under both approaches to the analysis, as described in appendix VI,
suggesting that our results are robust to concerns about Maine’s election
environment.
Finally, Tennessee noted that Delaware is an inappropriate comparison
state because it had Joe Biden on the ballot as Vice President in 2012.
Joe Biden was on the ballot in Delaware as a vice presidential candidate
in both 2008 and 2012, and thus we believe his candidacy would likely
have had similar effects in both elections and would not have affected our
results.
In summary, we believe that our use of two treatment states and multiple
comparison groups strengthens our findings and makes them robust to
potential sources of bias in any particular state or year. This design
cson
allowed us to analyze turnout changes f Tu treatment groups against
o in our
City
several plausible comparators. .In addition,6 CPS data allowed us to
nc. v 31, 201 the
I
conduct a versionance, analysist including all states other than Kansas or
of the
s
Alli on Augu
Tennessee,ty described in appendix VI. A nationwide comparison group
gri as ived
te
ic In
mitigates anych caused by choosing particular comparison states,
bias
Publ 6142 arpotentially biasing factors, such as the voter mobilization due
because the
d in 15-1
cite
No. to campaigns or ballot propositions, would need to have been
systematically unbalanced over time in the remaining 48 states and the
District of Columbia. Using this nationwide comparison group, we
obtained results similar to those using the states we chose to purposively
control for specific factors that can change over time, such as electoral
competition and other changes to election administration laws.
Selection and Use of Data Sources
The Secretary of State Offices in Kansas and Tennessee took issue with
the validity of the voter history and registration data we purchased from
Catalist LLC., one of three data sources we used to analyze voter turnout.
Tennessee noted that it had no record of Catalist’s purchasing data from
the state since 2010. Tennessee also noted that Catalist’s stated
progressive goals and clients make its data invalid. We took steps to
assess the reliability of the data we used from Catalist and found the data
sufficiently reliable for the purposes of our review. For example, we
reviewed assessments of Catalist data reliability conducted by other
researchers and, as we note on pp. 164-165 of our report, political
scientists have extensively analyzed the reliability of Catalist’s data on
voter registration and turnout history, and have specifically examined the
potential for political bias. This independent, third-party research,

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published in two peer-reviewed journals of academic research that focus
on methods of political analysis, found no evidence of systematic bias in
the data Catalist provides. 114 In one of these publications, peer reviewers
accepted Catalist data as sufficiently unbiased and reliable to validate
another common source of data on voter turnout—post-election surveys
of the general population. In addition, a study that used Catalist data was
submitted as evidence by the Department of Justice in its case against
Texas before a 3-judge panel of the U.S. District Court for the District of
Columbia in June 2012. 115
In addition to review by third-parties, we independently assessed the
reliability of the data and took measures to ensure that the use of data
from this particular source would not bias our results. First, we used other
data sources—the CPS and the United States Elections Project—to
produce parallel impact estimates when possible. Using these other data
cson
sources, we found results consistent with those using Catalist data, as
of Tu
ity
described in appendix VI. nc. v. C we 2016
Second, , assessed the data’s reliability and
I
1
found it sufficiently nce, forust 3
reliable g our purposes, as described in appendix VI.
u
Alliaincluded reviewing documentation on the
The steps rity took d on A
we
nteg
ve
completeness and
blic I 42 archi consistency of the voter files compared to official
Pu
in election
61
cited o. 15-1 results; comparing estimates of the change in turnout to
N estimates from other data sources; and interviewing Catalist staff
regarding the entity’s data management processes and controls.
Further, we took additional steps to assess how, if at all, Catalist’s file
acquisition process might have affected the reliability of data we
analyzed, in response to Tennessee’s concern about having last provided
its voter file to Catalist in 2010. Before we initially released our report,
Catalist confirmed that the source of the Tennessee voter file was the
Tennessee Secretary of State’s Office. This file included voter history
data for the 2012 general election. After we released our report, we
learned from Catalist that it obtained the voter files for Tennessee and
Alabama through the states' Democratic parties. On November 13, 2014
a representative from the Democratic Party in Tennessee confirmed in

114

Stephen Ansolabehere and Eitan Hersh, 2012, “Validation: What Big Data Reveal
About Survey Misreporting and the Real Electorate,” Political Analysis 20: 437-459.
Stephen Ansolabehere, Eitan Hersh, and Kenneth Shepsle, 2012, "Movers, Stayers, and
Voter Registration," Quarterly Journal of Political Science 7 (4): 333-363.
115

Texas v. Holder, No. 12-128 (D.D.C. June 30, 2012).

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writing to having acquired the state voter data from the Tennessee
Secretary of State and providing these data directly to Catalist, without
alteration or modification on February 19, 2014. We analyzed additional
copies of the Tennessee voter file to obtain reasonable assurance that
Catalist’s file acquisition process did not affect the reliability of the data
we analyzed for our report. To do this, we obtained from Catalist the full
voter file that the company said it had obtained from the Tennessee
Democratic Party in February 2014. This was the data file that Catalist
said it used as input for its proprietary data cleaning and supplementation
processes, as discussed on pages 161-162 of this report. These
processes produced as output the file we analyzed in our report. We
matched the records in this source file to the Tennessee voter file that the
Democratic Party said it obtained directly from the Secretary of State on
February 19, 2014—which, after we issued our report, it provided to
Catalist to share with us. We found that 100 percent of the registrants in
cson
Catalist’s 2014 source file were in the of Tu
Democratic Party’s 2014 file. In
ity
addition, for all the key data . v. C we2016 in our analysis, 100 percent
ncvalues 1, used
ce, I
of the values, alongnwith all field t 3
s formats, names, and other metadata,
Allia on Augu
matchedgrity
exactly. d
e

t
hive
ic In
2 arc
Publ also matched the records in the source file to records in a version of
in We 614
cited o. 15-1
N the Tennessee voter file, dated February 9, 2009, that Catalist said it

obtained directly from the Tennessee Secretary of State, which was
consistent with the file’s metadata on ownership and times of creation and
modification. The formatting of all field names, formats, and codes in
these two files matched exactly. Of those registrants in the 2014 file who
were registered prior to February 9, 2009, 94.9 percent also appeared in
the Secretary of State’s version of the file in 2009. One would not expect
100 percent of all registrants we analyzed in 2014 to be present on the
file in 2009, due to moves, deaths, removals of inactive registrants, and
other changes to registration status. Moreover, for the registrants in the
source file, the data values we originally analyzed for these registrants
matched those in the Secretary of State’s 2009 file at rates of 95.2 to 99.8
percent, including turnout in the 2008 general election.
Further, following the issuance of our report, Catalist provided for our
review a copy of the agreement it had in place with the Alabama
Democratic Party for purchasing the state voter data. Catalist also sent us
a letter describing the process whereby the Alabama Democratic Party
would transmit the state voter data to Catalist upon receipt of the file from
the Alabama Secretary of State, in the form and manner as it was
received from the Office of the Alabama Secretary of State, and stated
that it had acquired the Alabama state voter data we analyzed in our

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report in such a manner on February 6, 2013. The Chair of the Alabama
Democratic Party also confirmed in writing on February 4, 2015, that,
although no current staff members were present at the time of the
delivery of the Alabama state voter file to Catalist in February 2013, under
the Alabama Democratic Party’s agreement with Catalist, the Alabama
voter file is obtained from the Secretary of State and provided without
alteration and modification to Catalist. Additionally, Catalist provided a
summary of analyses it had conducted on the state voter file it received
from the Alabama Democratic Party, including the file formats and
properties, translation codes and markings, and expected record counts
for the file, to assure itself of the source, suitability and sufficiency of the
voter data upon receipt from the party.
In sum, based on our reliability assessments before and after we initially
released our report, the written statements we on
received from Catalist and
ucs
TParties, and the documents we
f
the Tennessee and Alabama Democratic
ity o
received from Catalist, we conclude that Catalist's acquisition of the
. v. C , 2016
c
e, In
Tennessee and Alabama voter st 31
lianc Augu files through the state Democratic Parties
l
did not egritythe reliability of the data contained in those files. Moreover,
affect A d on
e
nt
i I
weccontinue rchiv
2 a to conclude that all of the data we obtained from Catalist
Publ 6sufficiently reliable for our purposes, based on the reliability
in were 14
cited o. 15-1
N assessments we conducted during the course of our review and after our
report was initially released; our review of the documents provided by
Catalist; and the fact that our results were consistent across multiple
comparison groups and multiple data sources.
Kansas and Tennessee also questioned whether Catalist accurately
estimates a registrant’s race. Specifically, Kansas and Tennessee
asserted that our analysis of turnout among African-American registrants
was flawed, due to the potential inaccuracy of these estimates. Two of the
states used in our analysis—Alabama and Tennessee—include
registrants’ race in their voter registration and history databases. These
data are included in official versions of voter registration and history
databases, and are preserved in the versions of the databases we
purchased from Catalist. The remaining four states we analyzed—
Arkansas, Delaware, Kansas, and Maine—have not collected racial data
on almost all registrants as part of their databases. For these registrants,
Catalist estimates race using an algorithm supplied by a commercial firm.
As part of our analysis, we assessed the reliability of Catalist’s estimated
racial data, derived by the algorithm, and found them sufficiently reliable
for the purposes of our review. To assess the reliability of these racial
estimates, we received a custom validation from Catalist, which

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compared the estimated race of registrants in North Carolina to the actual
race that registrants report to state election officials. This analysis found
that approximately 70 to 90 percent of registrants, depending on racial
group, coded by Catalist as “likely” or “highly likely” to self-identify with a
certain racial group did, in fact, identify with that group in official records.
Academic research has found similar levels of reliability. One study
matched racial estimates from Catalist’s voter files to a nationwide
survey, in which respondents were allowed to identify with various racial
groups. For at least 93 percent of survey respondents, Catalist’s
estimates matched the race that respondents identified for themselves.
Our review of the evidence allowed us to conclude that Catalist’s
estimates of race were sufficiently reliable for the purpose of calculating
impact estimates for various racial subgroups. However, we also
assessed the sensitivity of our results to potential racial misclassification
cson
by estimating effects separately for y of Tu and Tennessee, where 98.8
Alabama
it
6
and 63.4 percent of the racial v. C respectively, are provided by
nc. data, 1, 201
I
registrants directly. nce,
In addition, st 3
several versions of the analysis include
ugu
Allia
only registrants with self-reported race and/or age in these states. We
grity ived on A
te
ic In
obtained results similar to those we obtained using estimated racial data
a ch
Publ Arkansas,rDelaware, Kansas, and Maine.
in in -16142
cited o. 15

N

Tennessee also stated that CPS data contradict our assertion that
Tennessee saw a decline in voter participation among 18 to 24 year-olds
in the 2012 general election. First, Tennessee stated that the CPS
demonstrates that turnout among 18 to 24 year-olds was not statistically
different from the national average in 2012, but that turnout among this
group was statistically lower than the national average in 2008. Second,
Tennessee stated that in 2008, prior to passage of Tennessee’s photo ID
law, the CPS estimated that 59 percent of Non-Hispanic Blacks voted in
Tennessee, but that in 2012, after the implementation of the photo ID law,
61 percent of Non-Hispanic Blacks voted. Tennessee asserts that the
CPS supports higher turnout among the Non-Hispanic Black registrants,
rather than a decline. However, our analysis focuses on the question of
whether changes in turnout from 2008 to 2012 in our treatment states
were similar to changes from 2008 to 2012 in our comparison states, not
whether a subgroup in one state experienced a change in turnout over
that time. Additionally, our findings with respect to subgroups were
estimated from a statistical model based on the complete, respondentlevel public release file of CPS data. We did not use state-level CPS data
published by the Census Bureau. Notably, the Census Bureau measures
turnout as a proportion of registered voters who say they voted, did not
vote, or “don’t know” whether they voted. In contrast, our analysis adopts

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a common approach of treating the last group as having missing data.
Therefore, the published state-level CPS data cited by Tennessee do not
contradict our analysis and are not directly comparable.
Tennessee also stated that our draft report referred to individuals 18 and
younger and that no one under the age of 18 at the time of the election
was allowed to vote in Tennessee. We revised our description of age
group ranges analyzed in the report to reflect those age ranges as of
2008. Our analysis and results were not affected by the age group
description revisions.
Additional Comments
The Tennessee Secretary of State’s office also stated that our report is
incomplete regarding the factors that caused ann
so increase in the usage of
Tu to
provisional ballots in Tennessee. Accordingc Tennessee, to compare
ty of
the 2008 provisional numbersv. Ci 2012 provisional numbers and
. to the , 2016
c
e In
attribute the increase in,the usage31 provisional ballots to changes in
lianc August of
l
voter ID requirementson
ignores relevant factors specifically unique to
rity A
nteg rchived cited changes to its provisional ballot statute in
cI
Tennessee. Tennessee
i
2a
Publ
2011 14
d in 15-16that allowed voters to cast provisional ballots under additional
ite
c
No. circumstances and subsequent election official training as factors that it
states increased provisional ballot use. We acknowledge that increased
training and additional circumstances under which voters may have been
permitted to cast provisional ballots may have affected provisional ballot
usage in Tennessee. While we noted in our report that such factors might
exist generally, we have included Tennessee’s perspectives on why
provisional ballot usage increased in particular in Tennessee in relevant
sections of our report.
Further, with regard to data jurisdictions in Arkansas reported to EAVS on
provisional ballots, Arkansas noted that some counties may have
misunderstood what is required in EAVS and suggested that the data
may need to be reexamined. We determined that some local election
jurisdictions in some states, such as some jurisdictions in Arkansas, did
not consistently report provisional ballot information to the EAVS for both
the 2008 and 2012 elections. To increase the reliability of our analysis,
we analyzed provisional ballot data only for jurisdictions that reported
provisional ballot information in both 2008 and 2012 and, separately, for
all jurisdictions that reported provisional ballots in one or both years. In
our analyses we obtained similar results, indicating that our exclusion of
jurisdictions with missing data did not affect our conclusions.

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In addition, Kansas noted that, in its view, the analytically correct
comparison for Kansas in 2012 would be in Kansas in 2000, the last time
there were no U.S. Senate or statewide offices on the ballot. Kansas
stated that in 2000, statewide turnout in Kansas was 66.7 percent and
turnout in 2012 was 66.8 percent. Rather than comparing changes in
turnout between general elections within one state, we used a differencein-difference approach to compare how changes in turnout in our
treatment states from the 2008 to the 2012 general elections compared to
changes in turnout in our comparison states for the same elections, as a
difference-in-difference approach is a more robust method for analyzing
whether changes in voter ID laws had any effect on turnout on the
treatment states because we controlled for other factors that could affect
turnout. Thus, our difference-in-difference approach controls for all factors
that changed in similar ways over time in the states analyzed.
Comparisons within Kansas between the 2000 and 2012 elections would
cson
confound any effect of voter ID laws, which changed during this period,
of Tu
ity
6
and various other factors that v. C changed, such as salient political
nc. also31, 201
ce, I gus
issues, voter mobilization efforts tby campaigns and interest groups, and
llian
u
changes grity A electionA
to other d on administration policies.
e

t
hive
ic In
2 rc
Publ 614weabelieve that the design and implementation of our study were
in
Overall,
cited o. 15-1
N rigorous, due to the careful selection of appropriate treatment and

comparison states, the use of three different sources of turnout data, and
the application of a number of statistical techniques to control for
competing explanations for our results. Our overall findings of greater
turnout declines in treatment states than in comparison states are
consistent across the three datasets we used, occurred in both of our
treatment states in comparison with multiple constructions of the
comparison group, and withstood multiple tests of the sensitivity of our
results. This gives us confidence that the findings are most likely
attributable to changes in voter ID requirements rather than other factors.
However, as we have noted on pp. 55-56, any policy evaluation in a nonexperimental setting such as ours, cannot account for all unobserved
factors that could impact the results. For example, Kansas stated that
photo ID laws are intended to reduce or eliminate fraudulent voting, and if
lower overall turnout occurs after implementation of a photo ID law, some
of the decrease may be attributable to the prevention of fraudulent votes.
We have noted in our report the challenges in estimating the incidence of
in-person voter fraud, which would make any analysis of the effect of
voter ID laws in preventing in-person voter fraud difficult. Given these
difficulties, we did not attempt to test this explanation in our study, and
thus we cannot rule it out as a reasonable contributor to some of the
turnout declines we found.

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As agreed with your offices, unless you publicly announce the contents of
this report earlier, we plan no further distribution until 30 days from the
report date. At that time, we will send copies of this report to the Attorney
General, the Election Assistance Commission; the Federal Judicial
Center; the United States Sentencing Commission; the Secretary of State
Offices in Kansas, Tennessee, Alabama, Arkansas, Delaware, and
Maine; appropriate congressional committees and members; and other
interested parties. The report also is available at no charge on the GAO
website at http://www.gao.gov.

If you or your staff have any questions, please contact Rebecca Gambler
at [phone] or [e-mail], or Nancy Kingsbury at (202)
512-2700 or [e-mail]. Contact points for our Offices of
Congressional Relations and Public Affairs mayn found on the last page
o be
Tucs contributions to this report
f
of this report. GAO staff who made significant
ity o 6
are listed in appendix IX. c. v. C
201

31,
e, In
lianc August
Al
y
d on
egrit
c Int archive
i
2
Publ
d in 15-1614
ite
c
No.

Rebecca Gambler
Director, Homeland Security and Justice

Nancy Kingsbury, Ph.D.
Managing Director, Applied Research and Methods

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Appendix I: Demographic Characteristics of
Voters Who Voted and Registered through
Different Methods

Appendix I: Demographic Characteristics of
Voters Who Voted and Registered through
Different Methods
Voter Demographics by
Method of Voting

States have established alternatives for voters to cast a ballot other than
at the polls on Election Day, including absentee voting and early voting. 1
All states and the District of Columbia have provisions allowing voters to
cast their ballots before Election Day by voting absentee, with variations
on who may vote absentee, whether the voter needs to provide an
excuse, and the time frames for applying for and submitting absentee
ballots. 2 As of the 2012 general election, 27 states and the District of
Columbia allowed voters to cast an absentee ballot by mail without an
excuse; 33 states and the District of Columbia had laws providing for
early voting; and Oregon and Washington were vote-by-mail states. Using
data from the Voting and Registration Supplement to the U.S. Census
Bureau’s Current Population Survey (CPS), we identified the proportions
of voters in different demographic categories that reported that they voted
(1) in person on Election Day; (2) in person before Election Day; (3) by
n
mail on Election Day; or (4) by mail before Election Day. Our analysis
ucso
covered the 2008, 2010, and 2012ity of T and included the following
elections,
demographic characteristics: v. C , 2016
Inc.

st 31
nce,
Allia on Augu
race,grity
d
e
c Int archive
i
2
Publ education,
in
614
cited o. 15-1
age,
N
income,
employment status,

1

Absentee voting is a process that allows citizens to cast a vote when they are unable to
vote at their precinct on Election Day and is generally conducted by mail. Early voting is
any process by which a voter may cast a ballot in person, without providing an excuse,
prior to Election Day, regardless of the name the state gives to that process. A state may
provide for both in-person absentee voting and early voting. For example, in Alaska, which
provides both, according to the Secretary of State’s website, the difference between inperson absentee and early voting is that an early voter is already determined to be eligible
to vote at the time of voting, and thus the voter’s ballot is placed directly in the ballot box
to be counted and tabulated along with those of other eligible voters on Election Day. With
in-person absentee voting, the voter’s eligibility is not verified at the time of voting, and
thus the voter’s ballot is placed inside an absentee voting envelope—pending subsequent
verification—prior to being placed in the ballot box.
2

Examples of excuses a voter may provide for not voting on Election Day include being
sick, having a disability, being out of the country, or having religious commitments.

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Appendix I: Demographic Characteristics of
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Different Methods

residential mobility, 3 and
sex.
Additional details regarding our methodology can be found in appendix II.
Our analysis showed that the majority of individuals within each
demographic category voted in person on Election Day. The detailed
results of our analysis can be found in figures 7-13 below.

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3

This is defined as the length of time the voter has lived in the community in which he or
she voted.

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Different Methods

Figure 7: Voting Method by Race in the 2008, 2010, and 2012 General Elections

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Figure 8: Voting Method by Education Level in the 2008, 2010, and 2012 General Elections

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Figure 9: Voting Method by Age in the 2008, 2010, and 2012 General Elections

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Figure 10: Voting Method by Income Level in the 2008, 2010, and 2012 General Elections

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Figure 11: Voting Method by Employment Status in the 2008, 2010, and 2012 General Elections

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Figure 12: Voting Method by Length of Time at Residence in the 2008, 2010, and 2012 General Elections

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Different Methods

Figure 13: Voting Method by Sex in the 2008, 2010, and 2012 General Elections

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Voter Demographics by
Method of Registration

With the exception of North Dakota, all states and the District of Columbia
generally require citizens to register before voting. Citizens apply to
register to vote in various ways, such as at motor vehicle agencies, by
mail, at local voter registrar offices, or through third-parties. 4 We reported
in October 2012 that 30 states and the District of Columbia imposed
some requirement on organizations that conduct voter registration drives.
As of October 2012, 17 states did not impose any requirements on thirdparty voter registration; that is, persons and organizations may generally
conduct voter registration drives without restriction. In addition, 2 states—
New Hampshire and Wyoming—did not allow third-party voter registration
drives. Using data from the Voting and Registration Supplement to CPS,
we identified the proportions of registered citizens in different
demographic categories that reported that they had registered to vote (1)
at a government office (including a department of motor vehicles (DMV),
a public assistance agency such as a Medicaid or Food Stamps office, or

4

Federal law does not generally address third-party voter registration organizations.

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a town hall or county/government registration office) or a polling place; (2)
by mail or online; (3) through a registration drive or at a school, hospital or
campus; or (4) stated that they did not know how they registered or used
another method. Our analysis covered the 2008, 2010, and 2012
elections, and included the following demographic characteristics:
race,
education,
age,
income,
employment status,
residential mobility, 5 and

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ncour methodology can be found in appendix II.
I
Additional details regarding
st 31
nce,
g most demographic groups were more likely
We found that Allia
respondentsuin u
rity
on A
toic Integ chiregistered at a government office than through other
report having ved
2 r
Publ
methods. 6 a
d in 15-1614 The detailed results of our analysis can be found in figures 14cite
No. 20 below.
sex.

5
This is defined as the length of time the voter has lived in the community in which he or
she voted.
6
While our data distinguish respondents who registered at a government
office/DMV/public assistance agency/polling place from those who registered at another
site, we cannot verify that respondents who reported having registered at (for example)
schools or through a registration drive were actually registered by third parties or the
nature of any third party involved.

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Different Methods

Figure 14: Registration Method by Race in the 2008, 2010, and 2012 General Elections

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Appendix I: Demographic Characteristics of
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Different Methods

Figure 15: Registration Method by Education Level in the 2008, 2010, and 2012 General Elections

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Different Methods

Figure 16: Registration Method by Age in the 2008, 2010, and 2012 General Elections

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Different Methods

Figure 17: Registration Method by Income Level in the 2008, 2010, and 2012 General Elections

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Different Methods

Figure 18: Registration Method by Employment Status in the 2008, 2010, and 2012 General Elections

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Different Methods

Figure 19: Registration Method by Length of Time at Residence in the 2008, 2010, and 2012 General Elections

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Different Methods

Figure 20: Registration Method by Sex in the 2008, 2010, and 2012 General Elections

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Appendix II: Objectives, Scope, and
Methodology

Appendix II: Objectives, Scope, and
Methodology
Objectives

This report addresses the following questions:
1. What does available literature indicate about the proportion of voters
who have selected identification (ID) documents, and what are the
direct costs to voters to obtain documents needed to satisfy state
voter ID requirements?
2. What do existing studies indicate about how, if at all, voter ID laws
have affected turnout?
3. What does our analysis of available data indicate about how, if at all,
changes in voter ID laws have affected turnout in selected states?
4. To what extent were provisional ballots cast because of ID reasons
and counted in two selected states during the 2012 election, and how
did provisional ballot use in those states change after the adoption of
voter identification laws?
son

f Tuc

5. What challenges, if any, exist in y o available information at the
. Cit using 6
n to v 31, 201
federal and state levelsc. estimate the incidence of in-person voter
I
nce, ugust
fraud?
Allia
A

ty

tegri

d on

Inic In
addition, this report provides information related to the demographic
chive
Publ 6142 ar of early voters and voters registered through third parties.
in characteristics
cited o. 15-1 information can be found in appendix I.
N This

Proportion of Voters
Who Have Selected ID
Documents and Direct
Costs to Voters to Obtain
Documents Needed to
Satisfy Voter ID
Requirements

To determine what existing studies indicate about the proportion of voters
who have selected ID documents, we first conducted a literature review.
We targeted our literature search to databases that index peer-reviewed
journals such as Political Analysis, Election Law Journal, and Judicature.
We also broadened our search beyond articles published in peerreviewed journals to identify studies such as dissertations, conference
proceedings, or studies issued by research institutes or government
agencies. For example, we conducted both subject and keyword
searches in Academic OneFile, Article First, Dissertation Abstracts,
Online, ECO, JSTOR, NTIS, ProQuest, PolicyFile, PsycInfo, Social
SciSearch, and Worldcat. We performed these searches and identified
studies from January 1, 2003, to May 2013, with subsequent searches to
locate any new studies through March 2014.
In addition to performing searches of literature databases, we reviewed
the dockets of court cases that we identified as involving challenges to
state voter ID requirements in order to identify studies submitted to the
courts that may provide information on proportions of voters that have
selected forms of ID. Specifically, we identified relevant studies submitted

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Appendix II: Objectives, Scope, and
Methodology

in the following cases: Applewhite v. Pennsylvania, No. 330 MD 2012
(Pa. Commw. Ct.); Frank v. Walker, No. 11-01128 (E.D. Wis.); Texas v.
Holder, No. 12-00128 (D.D.C.); League of United Latin American Citizens
v. Deininger, No. 12-00185 (E.D. Wis.); South Carolina v. United States,
No. 12-203 (D.D.C.).
Through our literature search, we identified 10 studies that provided
sufficiently sound information on proportions of voters who have selected
ID documents. 1 A GAO social scientist read and assessed each study,
using a standardized data collection instrument. The assessment focused
on information such as the types of IDs examined, the research design
and data sources used, and methods of data analysis and subgroups
analyzed. The assessment also focused on the quality of the data used in
the studies as reported by the researchers, any limitations of data
sources for the purposes for which they weresused, and inconsistencies in
c on
reporting study results. A second GAO f Tu scientist reviewed each
o social
ity
completed data collectionnc. v. C to 016 the accuracy of the
instrument 2 verify
I
1,
information included.ce, determined that the studies were sufficiently
an We Aug st 3
Allitheiroresults u conclusions.
sound togrity
and
e support d n

t
ic In
chive
Publ 6142 ar
in To determine the direct costs to voters to obtain selected documents
cited o. 15-1
N required to satisfy state voter ID requirements, we first reviewed state

statutes and legislative websites to identify those states that had enacted
requirements for all eligible voters attempting to vote to present
identification documents that fall into one of three categories (1) photo
only, government issued; (2) photo only, can be nongovernment issued;
(3) nonphoto, government issued. 2 We excluded states that allow voters
without ID to cast a regular ballot by affirming their own identity at the
polling place, since there would be no cost to the voter in this situation.
We excluded states that allow nonphoto, nongovernment forms of
identification because costs to obtain these types of documents can vary

1

We excluded three additional studies because, after review, we determined there was
either insufficient information provided about a study’s methodology or implementation or
the study was outside the scope of our work. Those studies were: Barreto, Nuño, and
Sanchez (2007), McDonald (2006), and Sanchez (2011).
2

States requiring government-issued ID include those where there is an exception for a
school ID.

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Appendix II: Objectives, Scope, and
Methodology

widely and are difficult to obtain. 3 As of June 2014, 17 selected states met
these criteria. 4
We reviewed state statutes, voter education material, and relevant official
state websites to identify those types of ID required in each of the 17
states to satisfy the states’ voter ID requirements. All selected states
accepted driver’s licenses, the most commonly used form of identification
at the polls, and nondriver state IDs. During the course of our evaluation,
we reviewed state websites that contained information on costs for
driver’s licenses and nondriver state IDs in the 17 states. The state
websites we reviewed included those for states’ departments of motor
vehicles, departments of public safety, departments of driver services,
and departments of transportation, among others. Using information
obtained from these websites, we compiled the costs of driver’s licenses
and nondriver state IDs for the 17 selected states. We also collected
cson
information on any additional fees iassociated with obtaining one of these
of Tu
. C ty
forms of identification. 5 To confirm the 2016
nc. v 31, accuracy of these costs, we
e, I
contacted the appropriate statest
llianc
ugu officials in each state.

nA
rity A
nteg rchived o
c I researching driver’s license and nondriver ID costs in the 17 states,
i
While 2 a
Publ
d in 15-1614
we also obtained information on which of these 17 states provide some
cite
No. type of free identification card to voters who do not own one of the forms
of ID required to be presented at the polls before voting. Each state that

3
Some states allow voters to provide a utility bill, a bank statement, or a paycheck, among
others, as voter identification. It would be difficult to measure the cost to obtain these
nonphoto and nongovernment IDs and the specifics of the cost would vary greatly based
on the voter.
4
The states in scope are Alabama, Arkansas, Florida, Georgia, Indiana, Kansas,
Mississippi, North Carolina, North Dakota, Oklahoma, Pennsylvania, Rhode Island, South
Carolina, Tennessee, Texas, Virginia, and Wisconsin. These 17 states include those in
which ID requirements are not currently in effect because, for example, the law is
legislated to go into effect at a later date or the law has been enjoined pursuant to
litigation. See, e.g., Applewhite v. Commonwealth, 2014 WL 184988 (Pa. Commw. Ct.
Jan. 17, 2014); Frank v. Walker, 2014 WL 1775432 (E.D. Wis. Apr. 29, 2104). As of June
2014, litigation was pending in Arkansas, North Carolina, Oklahoma, Texas and
Wisconsin.
5

Alabama, Arkansas, Kansas, North Dakota, Rhode Island, South Carolina, and
Wisconsin require a test or exam fee when applying for a driver’s license. Kansas also
charges a “photo fee” when applying for a driver’s license or state ID. Oklahoma charges
an application fee in addition to a license fee when applying to obtain a driver’s license
and Tennessee charges an application fee when applying for either a driver’s license or a
state ID card.

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Appendix II: Objectives, Scope, and
Methodology

provides a form of free ID has its own requirements for voters to obtain
the free ID. We examined official state websites and identified these
requirements, which may include providing proof of identity, proof of
residency, Social Security number, and verification of voter registration,
among other requirements. In cases where additional documentation,
such as a birth certificate, is necessary to prove identity, we identified the
cost of these documents through official state websites. We confirmed the
requirements for free voter identification and the cost of required
documents with state officials.

Information from Selected
Studies on Any Effects
of State Voter ID Laws
on Turnout

To determine what existing studies and available data indicate about how
voter ID laws have affected turnout in selected states, if at all, we
reviewed the literature on this topic and analyzed turnout data in selected
states. Specifically, for the review of existing son
studies, we targeted our
Tuc
f
literature search to databases that index peer-reviewed journals such as
ity o
Political Analysis, Election Law.Journal,016 Judicature. We also
. v C , 2 and
Inc
t 31
broadened our searche,
lianc beyonduarticles published in peer-reviewed
ug s
Al studies such as dissertations, conference proceedings
A
journals tority
eg identifyed on
hi
c Int issuedvby research institutes or government agencies. For
ori studies arc
2
Publ
example,
d in 15-1614 we conducted both subject and keyword searches in various
ite
c
No. databases, including Academic OneFile, Article First, Dissertation
Abstracts, Online, ECO, JSTOR, NTIS, ProQuest, PolicyFile, PsycInfo,
Social SciSearch, and Worldcat. We performed these searches and
identified articles from January 1, 2003 to May 2013, with subsequent
searches to locate any additional material through March 2014. In
addition to searches of literature databases, we reviewed the dockets of
court cases that involved challenges to state voter ID requirements, such
as those listed in our description above for identifying studies that
estimate proportions of voters with selected ID documents, in order to
identify studies submitted to the courts that assessed the effects of state
voter ID requirement on turnout. During the course of this review, we did
not identify any studies submitted to the courts that provide relevant data
on the effects of voter ID laws on turnout.
Through our literature search, we identified 10 studies that provide
sufficiently sound information on possible effects, if any, of state voter ID

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Appendix II: Objectives, Scope, and
Methodology

requirements on voter turnout. 6 A GAO social scientist read and assessed
each study, using a data collection instrument. The assessment focused
on the research design and data sources used, methods of data analysis
and subgroups analyzed, the primary conclusions, and limitations that
could affect those conclusions based on generally accepted social
science principles. 7 The assessment also focused on the quality of the
data used in the studies as reported by the researchers and our
observations of any problems with missing data, any limitations of data
sources for the purposes for which they were used, and inconsistencies in
reporting study results. A second GAO social scientist reviewed each
completed data collection instrument to verify the accuracy of the
information included. A GAO statistician also reviewed each study and
completed the data collection instrument. We determined that these
studies were sufficiently sound to report their results; however, we
discuss limitations associated with these studies’ methodologies in this
cson
report.
of Tu
ity

16
. v. C
, Inc st 31, 20
ce
n
Allia on Augu
Our Evaluation of
For ouregrity
evaluationeof available data to identify how, if at all, changes in
Int
iv d
voter
Available Data on Any in Public ID4laws ch affect turnout, more detailed information on our scope
2 ar may
and 61
Effects of Changes cited No. 15-1methodology is presented in appendixes V and VI. In summary, we
in
selected treatment states—Kansas and Tennessee—that implemented

State Voter ID Laws on
Turnout in Selected States

changes to their voter ID requirements between the 2008 and 2012
general elections. We also selected comparison states—Alabama,
Arkansas, Delaware, and Maine—that did not implement changes to voter
ID requirements during the same time period. When selecting these
states for our analysis, we sought to minimize the presence of other
factors that could affect voter turnout, such as other changes to election
laws and election competitiveness. We then compared treatment and
comparison state changes in voter turnout from the 2008 to 2012 general
elections to determine what effect, if any, changes in state voter ID laws

6

We reviewed six additional studies related to the effects of state voter ID requirements on
voter turnout, but excluded them from our report due to limitations in the studies’ scope or
methods for estimating effects. Those studies were: Ansolabehere (2009), Bullock III and
Hood III (2008), Cobb et. al. (2012), Gomez (2008), Lott (2006), and Pitts (2013).
7

Social science research standards are discussed in the scientific literature. For example,
see Thomas D. Cook, and Donald T. Campbell, Quasi-experimentation: Design and
Analysis Issues for Field Settings (Boston: Houghton Mifflin, 1990); William R. Shadish,
Thomas D. Cook, and Donald T. Campbell, Experimental and Quasi-Experimental
Designs for Generalized Causal Inference (Boston: Houghton Mifflin, 2002); and GAO,
Designing Evaluations: 2012 Revision, GAO-12-208G (Washington, D.C.: January 2012).

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Appendix II: Objectives, Scope, and
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had on voter turnout in the treatment states of Kansas and Tennessee.
Our findings are not generalizable to states beyond Kansas and
Tennessee.

Provisional Ballot Use

To determine how frequently provisional ballots were cast because of ID
reasons and counted in selected states during the 2012 election, we
analyzed data from the Election Assistance Commission’s (EAC) Election
Administration and Voting Survey (EAVS) on the total number of ballots
cast and the total number of provisional ballots cast in the 2012 general
elections in Kansas and Tennessee. 8 More detailed information on our
criteria for selecting Kansas and Tennessee is provided in appendix V.
We also analyzed 2012 statewide data provided to us by Kansas and
Tennessee election officials on the number of provisional ballots cast for
identification reasons and the number of provisional ballots cast for
cson
identification reasons that were counted Tu
of during the 2012 general election.
. ity 2 and
6
To determine the reliability c. theC
n of v EAVS01 state data, we interviewed
,
I
EAC officials andiance, from st 3Kansas and Tennessee Secretary of
officials gu the 1
ll
u
State officesy A d on A data collection and quality control processes.
grit regarding their
e
nte rchthat the EAVS data collection procedures were sufficiently
v
We I
blic determined i
a
4 identify and correct duplicative or illogical data. In addition, we
in Pu strong1to2
6
cited o. 15-1
N reviewed the data provided by Kansas and Tennessee and published by
the EAC to describe the proportion of jurisdictions providing complete
provisional ballot data. We found the data to be sufficiently reliable for the

8

EAC administers the biennial EAVS, an instrument used to collect state-by-state data on
the administration of federal elections. The survey is divided into two parts. The first part
captures quantitative data pertaining to the National Voter Registration Act (NVRA), the
Uniformed and Overseas Citizens Absentee Voting Act (UOCAVA), and other election
administration issues such as the counting of provisional ballots and poll worker
recruitment. The second part is the Statutory Overview, which asks state officials to
respond to a series of open-ended questions about their states’ election laws, definitions,
and procedures. According to EAC’s survey documentation for the 2012 EAVS, states
varied in their approaches to data collection, the completeness of their election data, and
their response rate to questions on the EAVS. Most states relied, at least to some degree,
upon centralized voter-registration databases and voter history databases, which allowed
state election officials to respond to each survey question with information from the local
level. Other states collected relatively little election data at the state level and instead
relied on cooperation from local jurisdiction election offices to complete the survey. In
2012, some states were not able to provide data in all the categories requested in the
survey and some did not have data for all of their local jurisdictions. We confirmed data
from the EAVS on the total number of provisional ballots cast in Kansas and Tennessee
for the 2012 general election with Kansas and Tennessee election officials.

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Appendix II: Objectives, Scope, and
Methodology

purposes of determining how frequently provisional ballots were cast
because of ID reasons and counted in Kansas and Tennessee.
To determine how provisional ballot use in Kansas and Tennessee
changed from the 2008 to 2012 general elections, we analyzed EAVS
data on the total number of ballots cast and the total number of
provisional ballots cast in the 2008 and 2012 general elections in Kansas
and Tennessee and in the four comparison states selected for objective
three—Alabama, Arkansas, Delaware, and Maine. For details on how we
selected the four comparison states, see appendix V. We used these data
to calculate the provisional ballot usage rate—the total number of
provisional ballots cast for any reason divided by the total number of all
ballots cast—by treatment states and comparison states in 2008 and
2012. To assess the reliability of the 2008 and 2012 EAVS data, we
analyzed the completeness of EAVS provisional ballot data for the 2008
cson
and 2012 general elections and interviewed EAC officials regarding their
of Tu
. City
6
data collection and quality control processes. We determined that
nc. v 31, 201
I
c percentuoftlocal election jurisdictions in three of our
between 0.2 andli28.9 e,
n
ug s
Al a
six treatment and comparison states had missing data in the 2008 or
grity ived on A
te
ic I EAVS report. Three of our selected states had complete data for all
2012 n
ch
Publ 6142 ar
in jurisdictions within the state, for both years. To overcome this potential
cited o. 15-1
N limitation, and to determine how provisional ballot use changed between
the 2008 and 2012 general elections, we conducted analyses in two
different ways. First, we used EAVS data from all the local election
jurisdictions in the treatment and comparison states where nonmissing
data useful for our calculations (total ballots cast, total provisional ballots
cast) were available for both 2008 and 2012, omitting those local election
jurisdictions where data for one or both years were missing. We also
analyzed EAVS data from all the local jurisdictions in the treatment and
comparison states where data were available from EAVS in either 2008
or 2012, or both years. We present the first analysis in the body of our
report and the second analysis in appendix VII. The results of both
analyses are similar, regardless of the inclusion or exclusion of local
election jurisdictions with data missing for 1 year but not the other.
Consequently, we found the EAVS data to be sufficiently reliable for the
purposes of our review. Our findings on provisional ballots are not
generalizable beyond our specific treatment and comparison states.

Available Information on
the Incidence of In-Person
Voter Fraud

To determine what challenges, if any, exist in using available information
at the federal and state levels to estimate the incidence of in-person voter
fraud, we developed a standard definition of in-person voter fraud for
purposes of this report and conducted a literature review to identify

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Appendix II: Objectives, Scope, and
Methodology

relevant studies. At the federal level, we reviewed federal databases
containing federal crime investigation and court information and
interviewed relevant Department of Justice (DOJ) and judicial branch
officials. We also contacted state election officials and reviewed
information they provided to identify any challenges in using the
information they provided to estimate the incidence of in-person voter
fraud.

Definition of In-Person
Voter Fraud

The offense of “in-person voter fraud” is not readily defined in law, and,
according to DOJ and EAC officials, their agencies do not have a
definition of the term “in-person voter fraud.” 9 However, several federal
and state court decisions have discussed the concept of in-person voter
fraud. We used these court cases to develop a definition of in-person
voter fraud for the purposes of this report: In-person voter fraud involves a
person who (1) attempts to vote or votes; (2) son
c in person at the polling
place; and (3) asserts an identity that of not the person’s own, whether it
is Tu
. City
6
be that of a fictional registered voter, a2dead registered voter, a false
nc. v 31, 01
I
t
identity, or whether nce,
the voterguses a fraudulent identification.
us
llia

u
rity A ed on A
nteg this definition, we analyzed relevant court cases to determine
v
To I
blicdeveloparchi
in Pu how 6142 have characterized in-person voter fraud, as well as activities
cited o. 15-1 courts
N that are not considered to be encompassed by the term. Specifically, we

searched legal databases for court opinions that discussed the offense of
“in-person voter fraud,” “voter impersonation fraud,” or “in-person voter
impersonation fraud.” 10 We reviewed these legal opinions and selected
cases from the United States Supreme Court, United States Circuit Court
of Appeals, and state supreme courts—which are the most authoritative
sources of case law. We analyzed the following cases: Crawford v.
Marion County Election Bd., 553 U.S. 181 (2008); Democratic Nat’l
Comm. v. Republican Nat’l Comm., 673 F.3d 192 (3d Cir. 2012); ACLU of
New Mexico v. Santillanes, 546 F.3d 1313 (10th Cir. 2008); In re Request
for Advisory Opinion Regarding Constitutionality of 2005 PA 71, 740
N.W.2d 444 (Mich. 2007); and Weinschenk v. State, 203 S.W.3d 201

9
During the course of our review, in July 2014, DOJ developed a definition of “in-person
voter impersonation” for purposes of litigation.
10
Courts have used the terms “voter impersonation fraud,” “in-person voter fraud,” or “inperson voter impersonation fraud” to describe the same conduct. While the terms appear
somewhat distinct, they are generally used interchangeably.

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Appendix II: Objectives, Scope, and
Methodology

(Mo. 2006). 11 In reviewing these decisions, we found that the type of
conduct described as constituting in-person voter fraud and not
constituting in-person voter fraud was generally consistent among the
courts. Activities that the courts characterized as comprising in-person
voter fraud included, for example, any fraud addressed by a photo ID
requirement, a voter showing up at the polls and claiming to be someone
he or she is not, a voter who votes in the place of a dead registered voter
(so-called ghost-voting), and attempting to vote using a false identity,
among others. As part of our analysis, we also reviewed activities the
courts have characterized as not constituting in-person voter fraud to
guide our analysis, which include, among others, absentee ballot fraud,
felons and other disqualified individuals voting in their own names, voter
registration fraud, and fraud or misconduct by election officials. We
shared this definition of in-person voter fraud with relevant federal agency
officials and solicited and integrated their feedback, as appropriate.
son

Literature Review

f Tuc
ity o 6
v. C
1
We conducted a review ofnacademic literature, organizational studies,
I c.
,books, st 31, 20 regularly cited research
ce
peer-reviewed journals,
and other
llian
ugu
published rity A d on2004 through April 2014 to identify studies that
g from January A
te
e
ic In
attempted a chiv
Publ 6142 torestimate in-person voter fraud, using a documented as
in methodology. 12 We conducted this review using search terms such
cited o. 15-1
N “voter impersonation” and “voter fraud,” among others, in various

databases, including Academic OneFile, Article First, Dissertation
Abstracts, Online, ECO, JSTOR, NTIS, ProQuest, PolicyFile, PsycInfo,
Social SciSearch, and Worldcat. We identified and reviewed more than
300 studies to determine whether they (1) contained data related to inperson voter fraud and (2) included a description of the methodology
used for collecting the data related to in-person voter fraud. 13 We
identified six studies that met these criteria. Two GAO analysts and, as
applicable, a GAO statistician reviewed each of the six studies and
determined that the design, implementation, and analyses of the studies

11

These cases were identified in May 2013 in order to inform the design and conduct of
our work.

12

“Organizational studies” refers to those studies published by nongovernmental
organizations, such as the Heritage Foundation and the Brennan Center for Justice.
Studies produced by state-level agencies are not included in the literature review, but are
discussed below.

13

We excluded studies that reported on previously compiled data or anecdotal reports of
in-person voter fraud, including those reported in the media.

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Appendix II: Objectives, Scope, and
Methodology

were sufficiently sound to support the studies’ results and conclusions
based on generally accepted social science principles. We found that
these studies used various sources and methodologies in their effort to
provide estimates on in-person voter fraud.

Available Federal Information

To determine the extent to which federal information allows for identifying
the number of in-person voter fraud investigations, prosecutions, and
convictions, we identified federal databases that contain information on
the incidence of reported federal crimes. The databases include the
following:
Executive Office for U.S. Attorneys’ (EOUSA) Legal Information Office
Network System (LIONS), which tracks investigations and
prosecutions by U.S. Attorneys’ Offices.
Criminal Division’s Automated Case Tracking System II (ACTS II),
cson
of Tusystem for all cases and
which is an automated activity-tracking
. City
matters that are the,responsibility, of016 Criminal Division litigating
nc. v 31 2 DOJ’s
e I
t
attorneys. 14 llianc
ugus
A

rity
on A
Integ rchived
cFederalaJudicial Center’s Integrated Database (IDB), which contains
i
2
Publ federal
d in 15-1614 court case data that are routinely reported by the courts to the
ite
c
Administrative Office of the U.S. Courts.
No.
United States Sentencing Commission’s Oracle database, which
includes data on individual offenders extracted and analyzed from
sentencing documents submitted by federal courts to the
Commission.
None of the four databases includes data on unreported incidents of inperson voter fraud or allegations for which there is no associated
investigation or case. For each of these databases, we reviewed
codebooks and other database documentation and interviewed relevant
agency officials to ascertain (1) how data potentially related to in-person
voter fraud are collected and managed using these databases and (2)
whether in-person voter fraud cases can be identified directly from the
databases. On the basis of interviews with agency officials and the review
of relevant court cases we conducted to develop a definition of in-person
voter fraud, we compiled a list of 14 possible statutory provisions under

14

Investigations on which DOJ staff have worked for 30 minutes or more are referred to as
matters.

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Appendix II: Objectives, Scope, and
Methodology

which our definition of in-person voter fraud could be prosecuted (see
table 8). 15
Table 8: Possible Statutory Provisions under Which In-Person Voter Fraud Could Be Prosecuted
Statute

Description

18 U.S.C. § 2

Makes punishable as a principal one who aids and abets another in commission of substantive
offense

18 U.S.C. § 241

Conspiracy to deprive a person of civil rights

18 U.S.C. § 242

Deprivation of civil rights

18 U.S.C. § 371

Conspiracy to commit any offense against the United States or to defraud the United States

18 U.S.C. § 609

Use of military authority to influence the vote of a member of armed forces

18 U.S.C. § 611

Voting by aliens

18 U.S.C. § 911

False claim of U.S. citizenship

18 U.S.C. § 1015(f)
18 U.S.C. § 1341
18 U.S.C. § 1342
18 U.S.C. § 1343
42 U.S.C. § 1973i(c)

on
o
Use of the United States mails, or a private or commercial interstate carrier, to further a scheme or
. City
6
nc. v 31, 201
artifice to defraud
ce, I gust
an
Use of any fictitious nametor Alli
address for theu
purpose of carrying out any scheme mentioned in 18
gri y ived on A
U.S.C. § 1341 Inte
rch
blic
Use iof wire, radio, 142 a
n Pu -16 or television, to further a scheme or artifice to defraud
cited o. for registering to vote or voting, fraudulent registrations, and conspiracies to encourage
Payments 15
N
False statement or claim of citizenship in order to register or to ucs
f T vote

illegal voting

42 U.S.C. § 1973i(e)

Voting more than once

42 U.S.C. § 1973gg-10(2)

Fraudulent registration or voting

Source: GAO analysis of information provided by federal agency officials. | GAO-14-634

Available State Information

To identify any challenges associated with using available information at
the state level to estimate the incidence of in-person voter fraud, we
interviewed election officials in 46 states and the District of Columbia. 16
Because of differences in election administration across states, these
officials were located in various state offices, including state secretary of

15

Officials with whom we met stated that certain statutes are more likely to be used with
respect to the prosecution of in-person voter fraud, but that it is possible that any of these
provisions could be used, depending on the facts and circumstances of the case. We
relied on agency officials’ identification of statutes under which this conduct could be
prosecuted.

16

We also contacted election officials from the 4 remaining states, but they declined to be
interviewed.

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Appendix II: Objectives, Scope, and
Methodology

state or commonwealth offices, boards of elections, and lieutenant
governors’ offices. Upon the recommendation of the election officials we
spoke with, in 8 of the 46 states, we also contacted officials from
additional state agencies, such as the state attorney general or judicial
branch. We corroborated the information we gathered through these
interviews by reviewing the documentation the states provided to us
related to the incidence of election fraud and state statutes related to
election fraud and in-person voter fraud.
As a result of these interviews and our review of documentation the
officials provided, we determined that 27 states had some information
readily available at the state level related to election fraud. To determine
the extent to which the incidence of in-person voter fraud could be
estimated from the provided documentation, we reviewed the format and
content of the documentation provided, as well as testimonial evidence
cson
from the original interviews and subsequent correspondence with state
of Tu
. City
officials. This review allowed. us to better 16
nc v 31, 20 understand the way in which the
I
information was collected andust
nce, ug compiled, and to identify any potential
Allia on Athe provided information. We also reviewed
ity
limitations rassociated with
d
nteg rchiv for
c Iresponsibilitye addressing election fraud was distributed among
i
how
Publ 6142 a and local agencies, in an effort to determine whether the
in various
cited o. 15-1 state
N information provided by the state represented a complete account of the
in-person voter fraud allegations, investigations, prosecutions, or
convictions that occurred within the state.

Demographic
Characteristics of
Select Voters

To assess demographic differences in voting patterns and methods of
voter registration, we analyzed data from the Voting and Registration
Supplement to the U.S. Census Bureau’s Current Population Survey
(CPS). The supplement collects data from a representative national
sample of adults on the timing and method of voting and the method of
registration in November of every presidential and congressional election
year, in conjunction with the monthly CPS survey that also collects
demographic information such as race, ethnicity, age, labor force
participation, and income.
To examine the reliability of CPS data, we reviewed technical
documentation and conducted electronic data reliability testing. We also
examined our data to ensure logical consistency and that there were not
excessive missing data on our variables of interest. We found the data to
be sufficiently reliable for the purposes of our review.

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Appendix II: Objectives, Scope, and
Methodology

To conduct our analysis of demographic characteristics of early and
absentee voters, we merged separate variables on timing of voting
(before Election Day and on Election Day) and method of voting (in
person versus by mail) into one four-category variable, as shown below.
in person on Election Day,
in person before Election Day,
by mail on Election Day, and
by mail before Election Day.
CPS data do not identify whether early or absentee voting was through an
absentee process requiring a reason, through no-excuse absentee voting,
in person at a polling place, or by some other means.

on
Tucs
of characteristics of voters who
In an effort to analyze the demographic
. City
6
register through nongovernmental organizations, or third parties, we
nc. v 31, 201
t
ce, I the method of registration variable to highlight
n
collapsed information from ugus
Allia
grity i such n A
major categoriesved oas registration at a government office versus by
te
ic In
c
mail or online, h
Publ 6142 ar as shown below:
d in 15-1
cite
No.
government office (including a department of motor vehicle office,
public assistance agency, or polling place);
by mail or online;
through a registration drive or at a school, hospital, or campus; or
other method/don’t know.
While our data distinguish respondents who registered at a government
office/DMV/public assistance agency from those who registered at
another site, we cannot verify that respondents who reported having
registered at (for example) schools or through a registration drive were
actually registered by third parties or the nature of any third party
involved. Additionally, because the question concerns the last time an
individual registered, respondents may have difficulty recalling the
method of registration if it did not occur recently.

We collapsed data from our demographic variables of interest to highlight
specific comparisons, and analyzed cross tabulations of the proportion of
individuals in each demographic category that voted or registered by a
different method. We examined the following demographic variables:

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Appendix II: Objectives, Scope, and
Methodology

race,
education,
age,
income,
employment status,
residential mobility, 17 and
sex.
We were unable to analyze some variables that research has suggested
are associated with the propensity to vote early or be registered by a third
party (such as political interest or party affiliation) because the CPS does
not collect these data. Finally, because CPS data are based on a
cson
complex sample design, we applied generalized variance equations from
of Tu standard errors for our
the CPS technical documentation toygenerate
. Cit
6
nc. v 31, 201
estimates.
t
ce, I

n
ugus
Allia
grity ived on A
te
ic In
ch
Publ 6142 ar
in
cited o. 15-1
N

17

This is defined as the length of time the respondent has lived at his or her current
address.

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Appendix III: Bibliography of Identification (ID)
Ownership, Voter Turnout and In-Person Voter
Fraud Studies Reviewed for This Report

Appendix III: Bibliography of Identification
(ID) Ownership, Voter Turnout and In-Person
Voter Fraud Studies Reviewed for This Report
Studies GAO Reviewed
That Estimate ID
Ownership

Ansolabehere, Stephen. “Report on Racial Differences in Matching Voter
Registration Lists to Driver’s License and License to Carry Databases in
the State of Texas.” Paper submitted June 30, 2012, Texas v. Holder, No.
12- 0128 (D.D.C).
Barreto, Matt A. and Gabriel R. Sanchez. “Rates of Possession of
Accepted Photo Identification, among Different Subgroups in the Eligible
Voter Population, Milwaukee County, Wisconsin.” Expert report submitted
on behalf of plaintiffs April 23, 2012, in Frank v. Walker, No. 11-01128
(E.D. Wis.).
Barreto, Matt A.; Stephen A. Nuño, and Gabriel R. Sanchez. “The
Disproportionate Impact of Voter-ID Requirements on the Electorate—
New Evidence from Indiana.” PS: Political Science & Politics (January
2009): 111-116.
son

f Tuc
ity o Gabriel R. Sanchez. “Voter ID
Barreto, Matt A.; Stephen A..Nuño, and 016
v. C
, Inc st 31, 2 of Latino, Black, and Asian
Requirements and thee
llianc Disenfranchisement
ugu
ity presented at
Voters.” PaperA d on A the 2007 American Political Science
gr
te
ic In
Association Annual Conference, Chicago, Illinois, September 1, 2007.
chive
Publ 6142 ar
in
cited o. 15-1
N Barreto, Matt A.; Gabriel R. Sanchez, and Hannah Walker. “Rates of
Possession of Valid Photo Identification, and Public Knowledge of the
Voter ID Law in Pennsylvania.” Paper submitted July 16, 2012, in
Applewhite v. Commonwealth, No. 330 MD 2012 (Pa. Commw. Ct.)

Beatty, Leland. Declaration submitted April 23, 2012, in League of United
Latin American Citizens v. Deininger, No. 12-00185 (E.D. Wis.).
Bullock, Charles III and M.V. Hood III. “Worth a Thousand Words?: An
Analysis of Georgia’s Voter Identification Statute.” Paper presented at the
Annual Meeting of the Southwestern Political Science Association,
Albuquerque, New Mexico, March 2007.
Hood III, M.V. “Declaration of M.V. Hood III.” Paper submitted May 31,
2012, in League of United Latin American Citizens v. Deininger, No. 1200185 (E.D. Wis.)
McDonald, Michael P. “May I See Your ID, Please? Measuring the
Number of Eligible Voters with Photo Identification.” Paper presented at
the California Institute of Technology and Massachusetts Institute of
Technology Voter Identification and Registration Conference, Cambridge,
Massachusetts, October 2006.

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Appendix III: Bibliography of Identification (ID)
Ownership, Voter Turnout and In-Person Voter
Fraud Studies Reviewed for This Report

North Carolina State Board of Elections. April 2013 State Board of
Elections-Department of Motor Vehicles ID Analysis, a report prepared in
response to legislative and media inquiries. April 2013.
Sanchez, Gabriel R. “The Disproportionate Impact of Photo-ID Laws on
the Minority Electorate.” In Latino Decisions, accessed April 15, 2014,
http://www.latinodecisions.com/blog/2011/05/24/the-disproportionateimpact-of-stringent-voter-id-laws.
Stewart III, Charles. “Declaration of Charles Stewart III, PhD.” Paper
submitted June 26, 2012, in South Carolina v. Holder, 12 -203 (D.D.C.)
Stewart III, Charles. “Voter ID: Who Has Them? Who Shows Them?”
Oklahoma Law Review, vol. 66, no. 1 (2013): 21-52.

cson
of Tu
. ity 2016
Studies GAO Reviewed
Alvarez, R. Michael; Delia BaileyC
nc. v and, Jonathan N. Katz. “An Empirical
I
t 31
Bayes Approachliance,
to Estimating Ordinal Treatment Effects.” PS: Political
That Estimate Effects of
ugus
Al vol. n A(2011): 20-31. 1
y
Science &rPolitics, d o 19
eg it
Voter ID Requirements
c Int archive
i
2
Publ
on Voter Turnout
Ansolabehere, Stephen. “Effects of Identification Requirements on Voting:
d in 15-1614
ite
c
No. Evidence from the Experiences of Voters on Election Day.” PS: Political
Science & Politics, January 2009: 127-130.
Bullock III, Charles S., and M.V. Hood III. “Worth a Thousand Words? An
Analysis of Georgia’s Voter Identification Statute.” American Politics
Research, vol. 36, no. 4 (2008): 555-579.
Cobb, Rachel V.; D. James Greiner, and Kevin M. Quinn. “Can Voter ID
Laws Be Administered in a Race-Neutral Manner? Evidence from the City
of Boston in 2008.” Quarterly Journal of Political Science, vol. 7 (2012): 133.
De Alth, Shelley. “ID at the Polls: Assessing the Impact of Recent State
Voter ID Laws on Voter Turnout.” Harvard Law and Policy Review, vol. 3
(2009): 185-202.

1

We also reviewed the working paper that led to this published study: Alvarez, R. Michael;
Delia Bailey and Jonathan N. Katz. The Effect of Voter Identification Laws on Turnout,
Social Science Working Paper 1267R. California Institute of Technology: Pasadena,
California (2008).

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Appendix III: Bibliography of Identification (ID)
Ownership, Voter Turnout and In-Person Voter
Fraud Studies Reviewed for This Report

Dropp, Kyle A, Voter Identification Laws and Voter Turnout (May 2013),
forthcoming.
Erikson, Robert S. and Lorraine C. Minnite. “Modeling Problems in the
Voter Identification—Voter Turnout Debate.” Election Law Journal, vol. 8,
no. 2 (2009): 85-101.
Gomez, Brad T. “Uneven Hurdles: The Effect of Voter Identification
Requirements on Voter Turnout.” Paper presented at the Annual Meeting
of the Midwest Political Science Association, Chicago, Illinois, April 2007.
Lott, John R. Evidence of Voter Fraud and the Impact that Regulations to
Reduce Fraud have on Voter Participation Rate (August 2006),
forthcoming.

cson

Milyo, Jeffrey. The Effects of Photographic Identification on Voter Turnout
of Tu
. City 2016 Missouri: Institute of
in Indiana: A County-Level c. v
n Analysis (Columbia,
ce, I gust 31,
Public Policy, University of Missouri, 2007).
lian

l
n Au
rity A
nteg rchived oand Keri Weber Sikich. New Analysis Shows Voter
Muhlhausen,
blic I 42 a David B.
in Pu Identification Laws Do Not Reduce Turnout (Washington, D.C.: the
d
161
cite
. 15No Heritage Foundation, 2007).
Mycoff, Jason D.; Michael W. Wagner, and David C. Wilson. “The Effect
of Voter Identification Laws on Aggregate and Individual Level Turnout.”
Paper presented at the 2007 American Political Science Association
Annual Conference, Chicago, Illinois, August 2007.
Mycoff, Jason D.; Michael W. Wagner, and David C. Wilson. “The
Empirical Effects of Voter-ID Laws: Present or Absent.” PS: Political
Science & Politics, January 2009: 121-126.
Pitts, Michael J. “Photo ID, Provisional Balloting, and Indiana’s 2012
Primary Election.” University of Richmond Law Review, vol. 47, no.3
(2013): 939-957.
Vercellotti, Timothy and David Andersen. “Protecting the Franchise, or
Restricting It? The Effects of Voter Identification Requirements on
Turnout.” Paper presented at the 2006 American Political Science
Association Annual Conference, Philadelphia, Pennsylvania, August 31September 3, 2006.

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Appendix III: Bibliography of Identification (ID)
Ownership, Voter Turnout and In-Person Voter
Fraud Studies Reviewed for This Report

Vercellotti, Timothy, and David Andersen. “Voter-Identification
Requirements and the Learning Curve.” PS: Political Science & Politics
(January 2009): 117-120.

Studies GAO Reviewed
That Attempted to Identify
Instances of In-Person
Voter Fraud

Ahlquist, John S., Kenneth R. Mayer, and Simon Jackman. “Alien
Abduction and Voter Impersonation in the 2012 U.S. General Election:
Evidence from a Survey List Experiment,” October 30, 2013, forthcoming.
Election Law Journal.
Christensen, Ray and Thomas J. Schultz. “Identifying Election Fraud
Using Orphan and Low Propensity Voters,” American Politics Research,
vol. 42 (2), 2014.
Corbin Carson, “Exhaustive Database of Voter Fraud Cases Turns Up
cson
Scant Evidence That It Happens” News21, Aug. 12, 2012, accessed July
of Tu
City 016
24, 2014, http://votingrights.news21.com/article/election-fraud.
c. v.
2

31,
e, In
lianc August
Al William Gillespie. “They Just Do Not Vote Like They
Hood III, grity and d on
e M.V. hive
c Int AaMethodology to Empirically Assess Election Fraud,” Social
i
Used To: rc
2
Publ
Science
d in 15-1614Quarterly, vol. 93 (1), 2012.
ite
c
No.
Levitt, Justin. “Election Deform: The Pursuit of Unwarranted Election
Regulation,” Election Law Journal, vol. 11 (1), 2012.

Minnite, Lorraine C. The Myth of Voter Fraud. Ithaca: Cornell University
Press, 2010.

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Appendix IV: Driver’s License and Nondriver
State ID Costs in Selected States, as of July
2014

Appendix IV: Driver’s License and Nondriver
State ID Costs in Selected States, as of July
2014
Information in this appendix is also presented in figure 4 of the report.
Table 9 describes, for each selected state, the (1) driver’s license cost;
(2) non-driver ID cost; and (3) whether or not an ID for voting can be
obtained free of charge.
Table 9: Driver’s License and Nondriver Identification (ID) Costs in Selected States
a

State

Driver’s license cost

Nondriver ID cost

Free ID for voting

Alabama

$28.50 ($23.50 + $5 test fee)

$23.50

Yes

Arkansas

$25 ($20 + $5 test fee)

$5

Yes

Florida

$48

$25

No

Georgia

5-year: $20
8-year: $32

5-year: $20
8-year: $32

Yes

Indiana

4-year: $14.50, 5-year: $16, 6-year: $17.50
For certain drivers over 75: 3-year: $11
For drivers over 85: 2-year: $7

$11.50
Over 18: Free

Yes

Kansas

Mississippi
North Carolina

cson
of Tu
. City
6
nc. v 31, 201
I
$29 ($18 + $8 photo fee + $3 exam fee)
ce, $22 gust
ian Disabled/over 65: $18
u
Over 65: $23 ($12 + $8 photo fee + $3 exam fee)
y All
gritexamived on A
Under 21: $31 ($20 + $8 photo Inte $3
fee +
fee)
blic
arch
4-year: $24
$17
in Pu -16142
cited o. 15
8-year: $51
N
$32

b

Yes

Yes

$10

Yes

North Dakota

$25 ($15 + $5 written test fee + $5 road test fee)

$8

Yes

Oklahoma

$37.50 ($33.50 + $4 application fee)
Over 62: $21.25
Over age 65: Free

$20

Yes

Pennsylvania

$34.50
Over 65: $24

$27.50

Yes

Rhode Island

$58.50 ($32 + $26.50 road test fee)

$26.50
Over 59: no fee

Yes

South Carolina

5-year: $14.50 ($12.50 + $2 knowledge test fee)
10-year: $27 ($25 + $2 knowledge test fee)

Free

Yes

Tennessee

$19.50 ($17.50 + $2 application fee)

$9.50 ($7.50 + $2 application fee)

Yes

Texas

$25
Over 85: $9

$16
Over 60: $6

Yes

Virginia

$32

$10

Yes

Wisconsin

$43 ($28 + $15 skills exam fee)

$28

Yes

c

Source: GAO analysis of state information and data. | GAO-14-634

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Appendix IV: Driver’s License and Nondriver
State ID Costs in Selected States, as of July
2014

Notes:
a
b

The “Non-Driver ID Cost” category does not include non-driver ID issued for voting purposes.
Florida allows as acceptable identification photo ID that may be nongovernment issued.

c

Pennsylvania’s voter ID was permanently enjoined on January 14, 2014, by the Pennsylvania
Commonwealth Court. Applewhite v. Commonwealth, 2014 WL 184988 (Pa. Commw. Ct. Jan. 17,
2014). This injunction extended to issuance of free voter ID by the Pennsylvania Department of
Transportation and Department of State.

cson
of Tu
. City
6
nc. v 31, 201
ce, I gust
n
u
Allia
grity ived on A
nte rch
blic I
a
in Pu -16142
ited o. 15
c
N

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Appendix V: Voter Turnout Analysis Design

Appendix V: Voter Turnout Analysis Design

We conducted an evaluation of how, if at all, changes in requirements for
all eligible voters to present identification at the polls on Election Day—
referred to in this appendix as voter ID laws—in selected states affected
voter turnout. For our evaluation, we conducted a quasi-experimental
analysis that compared changes in voter turnout between two states that
implemented changes to voter ID requirements with changes in four
states that did not implement changes to voter ID requirements between
the 2008 and 2012 general elections. As part of our analysis, we took
steps to control for factors other than changes in ID requirements that
could affect voter turnout in either group of states. This appendix
summarizes the logic of a quasi-experimental design and our approach to
selecting states for analysis. Appendix VI discusses the methods of
analysis, data, and detailed results.

cson

A quasi-experiment is a type of policy of Tu
evaluation that compares how an
ity
outcome changes over time . va C
in . “treatment” group that adopted a new
2016
Inc
t 31,
policy, as compared ce, a “comparison” group that did not make the
with
gus
llian
change. 1grity A controlled experiments, researchers analyze separate
As with d on Au
te
ic In
c e
groups before hiv
Publ 6142 ar and after one of them changed a policy. Unlike in
in
controlled experiments, the assignment to groups is not randomized, and
cited o. 15-1
N the analyst cannot fully control the experiences of either group before or
after treatment.

Quasi-experimental
Analysis of Voter
Identification Laws
and Turnout

We used a quasi-experimental analysis to assess the effect, if any, of
changes in selected state voter ID laws on voter turnout. We used this
approach to account for the variation across states in the use of voter ID
laws and the staggered adoption of such laws over time, which makes a
quasi-experimental analysis possible. In this case, the treatment and
comparison groups include all registered or eligible voters in states that
did and did not change state ID laws in a certain time period (depending
on the data source). Within each group, by comparing turnout before and
after voter ID laws changed in the treatment group, we can estimate how
turnout changed, if at all, and then calculate how any change varied
between groups, known as a difference-in-difference. If turnout changed
by a greater or lesser amount in the treatment states than in the
comparison states, evidence would then suggest that changes in state
voter ID laws in the treatment states affected voter turnout. In contrast, if

1

See GAO-12-208G.

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Appendix V: Voter Turnout Analysis Design

turnout changes were similar in the treatment and comparison states,
then the evidence would suggest that changes in state voter ID laws in
the treatment states did not affect voter turnout.
Quasi-experiments have a number of strengths for estimating the effects
of election administration practices. 2 The longitudinal nature of the
analysis holds constant any differences between the treatment and
comparison groups that do not change by large amounts over short
periods of time. In our analysis, these could include differences across
citizens in age, education, income, race, political interest, residential
mobility, state political culture, and partisanship, which may affect turnout
and the propensity for a state to adopt voter ID laws. Political science
research has consistently shown that individual differences across
citizens—and implicitly across the jurisdictions in which they live—largely
explain the decision to vote. 3 For this reason,sa n
o quasi-experimental
Tuc legal reforms designed to
design is well suited to estimating the of
ity effect of
change the voting process,c. v. C , 2016 constant many of the
because it holds
In
31
confounding variablese, prior research has shown are most likely to
lianc that ugust
Al decision to vote.
ty
affect individuals’ ed on A
tegri

ic In
chiv
Publ 6142 ar
in A valid quasi-experimental analysis depends on the careful selection of
cited o. 15-1
N treatment and comparison states, in order to control for other factors that

may change over time in each group. 4 For example, if a treatment state
changed another election law or practice during the time period of
analysis, or saw more robust voter mobilization from political campaigns,
isolating the effect of ID laws, if any, becomes more difficult, since other
factors could have contributed to change in turnout. If turnout changed by
a smaller or larger amount in the treatment state than in the comparison

2

GAO, Campaign Finance Reform: Experiences of Two States That Offered Full Public
Funding for Political Candidates, GAO-10-390 (Washington, D.C.: May 28, 2010) used a
similar approach to estimate the effect of campaign finance laws in Arizona and Maine on
the competitiveness of elections. Previous studies of voter ID laws using a quasiexperimental design include Alvarez (2008), Dropp (2013), and Milyo (2007). Keele and
Minozzi (2013) identified quasi-experiments as one of several methods of causal inference
for election administration practices.
3
Wolfinger, and Rosenstone. Who Votes?; Rosenstone, and Hansen. Mobilization,
Participation, and Democracy in America.
4

William R. Shadish, Thomas D. Cook, and Donald T. Campbell, Experimental and QuasiExperimental Designs for Generalized Causal Inference (Boston: Houghton Mifflin
Company, 2002), 159.

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Appendix V: Voter Turnout Analysis Design

state, either the new voter ID law or the other legal or administrative
changes may have contributed to the change in turnout. Controlling for
other changes over time allows us to better isolate the effects of the
change in voter ID law, if an effect were to exist.
To carry out our quasi-experimental analysis, we identified treatment and
comparison states for which we could hold constant other factors that
vary over time, either through the selection of the states or statistical
methods. Our selection of states controlled for the presence of
competitive races for statewide or federal offices, controversial ballot
questions, and the voter mobilization activities of political campaigns. The
next section discusses our efforts to identify potential states for analysis,
based on the presence of these factors.

Treatment State Selection

cited

cson

Tu
In our October 2012 report, we described state voter ID laws that were in
y of
. Citand 016
effect for the 2012 general c. v
election 2 substantive changes to these
,
In
We used that report, combined with supplemental
laws since 2002.l5iance,
st 31
Aleffective Augu the laws, to identify candidate treatment
researchgrity
e on the ived on date of
c Int analysis.
states for arch
ubli

in P -16142
15
No. To select our treatment states from the 50 states and the District of
Columbia we applied the following criteria:

1. A voter ID requirement was adopted or substantively modified after
2002 and implemented as of the November 2012 general election.
2. Voter ID requirements required the voter present a photo ID
(government or non-government issued); a non-photo, governmentissued ID; or a nonphoto, non-government issued ID, with the
requirement that voters without acceptable ID at the polling place on

5

GAO-13-90R. Substantive changes were identified as of the time the Help America Vote
Act (HAVA) was enacted.

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Appendix V: Voter Turnout Analysis Design

Election Day to return within a specified amount of time with
acceptable ID in order for their provisional ballot to be counted. 6
3. The states had presidential general elections where the margin of
victory did not substantially change from 2008 to 2012 and all other
statewide elections, such as U.S. Senate races, were non-competitive
in both the 2008 and 2012 general elections.
4. The states did not experience contemporaneous changes to other
laws between the 2008 and 2012 general elections that may have
significantly affected voter turnout on Election Day.
Fourteen states met the first and second criteria above. After identifying
these states, we selected for further consideration the 4 states, of these
14, that implemented government-issued, photo ID requirements that also
required voters to follow up with election officials if acceptable ID was not
cson
presented at the polls on Election Day—Georgia, Indiana, Kansas, and
of Tu
y
Tennessee. 7 Voter ID policiesv. Cit
in these states are preferable for statistical
2016
nc. have speculated that photo ID
analysis, since previous studies t 31,
ce, I
us
an

ug
Alli
grity ived on A
nte rch
blic I 2 a
in Pu 6Ohio614Utah were excluded based on this criterion because these states generally
cited o. 15-1 and
N counted provisional ballots if the voter’s identify could be verified through other means and
only required voters in certain circumstances to return with acceptable ID. As part of the
identification requirements states have established for voting at the polls on Election Day,
states have also adopted processes for voters who do not provide the requisite
documentation at the polls to vote and have their ballots counted. There is variety in these
processes, with some states allowing voters to resolve the deficiency on Election Day, for
example by signing an affidavit attesting to their identity and providing identifying
information such as their address and date of birth, while others require the voter to return
to a local election office with acceptable documentation within a specified number of days
after the election. Under the Help America Vote Act (HAVA), states are required to permit
individuals, under certain circumstances, to cast a provisional ballot in federal elections.
For example, if a voter does not have the requisite identification at the polls, HAVA
requires that the voter be allowed to cast a provisional ballot. Under HAVA, election
officials receiving provisional voter information are to determine whether such individuals
are eligible to vote under state law. If an individual is determined to be eligible, HAVA
specifies that such individual’s provisional ballot be counted as a vote in that election in
accordance with state law.
7
We ruled out Alabama, Arizona, and Virginia as potential treatment states for analysis,
even though they generally require voters to follow up with the relevant election authority
to provide acceptable identification within a specified time period after the election in order
for the provisional ballots to be counted. Although the ID laws in those states generally
require additional action on the part of voters to have their ballots counted, these states
allow a larger number of types of ID to be used, including nongovernment issued
nonphoto IDs. In contrast, Georgia, Indiana, Kansas, and Tennessee allowed fewer types
of ID and also generally required voters without ID to follow-up with election officials and
provide acceptable identification in order for their ballots to be counted.

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Appendix V: Voter Turnout Analysis Design

requirements could affect turnout more strongly than other requirements
and it is easier to detect larger effects than smaller ones, if they exist. For
example, a previous evaluation of voter ID laws found that only photo ID
policies affected turnout, as compared with other ID policies, such as
requiring a non-photo ID. 8 In addition, analyzing policies that allow the
fewest forms of ID provides an upper limit on the effects of identification
laws in general, and focuses on the type of ID law that that many
legislatures have approved since 2008. Thirteen of the 17 states that
adopted requirements for photo and generally government-issued ID
since the passage of HAVA adopted their policies after 2008.
We conducted a legal analysis for Georgia, Indiana, Kansas, and
Tennessee to determine if election laws and procedures changed
contemporaneously with the changes to these states’ ID laws. We found
that legal changes in Georgia were sufficient son
c to eliminate it from
consideration as a treatment state, tbut f Tuthere were no significant
o that
iy
6
changes in the remaining nc. v. C to eliminate them from contention on
3 states
, 201
ce inI gust 3no-excuse absentee voting was
that basis. Specifically, , Georgia, 1
llian
u
enacted inrity A and on A
g 2005,ved expanded early voting hours were enacted in 2008.
ntefederal igeneral election for which the state’s ID requirement went
The first
blic I 42 arch
in Pu into effect was the November 2008 general election. Thus, the change in
d
161
cite
. 15-requirements between the relevant midterm or presidential election
No ID
occurred at the same time as other important changes in voting
procedures. The simultaneity of these changes makes it difficult to isolate
the effect of one law from the effect of another.
To determine whether competitive election environments were present in
the remaining potential treatment states—Indiana, Kansas, and
Tennessee—we conducted two evaluations. First, we evaluated the
change in competitiveness of the presidential race between the 2008 and
2012 general elections. We eliminated Indiana based on this analysis, but
retained Kansas and Tennessee. The competitiveness of the race for
President in Indiana changed substantially between the 2004 and 2008
general elections—from a margin of victory of 21 percent in 2004 to 1
percent in 2008. 9 Such a large change in competitiveness suggests that

8
Alvarez, Bailey, and Katz, (2010). These researchers defined the spectrum of voter ID
requirements as ranging from voters stating their name to photo ID requirements.
9
Margins of victory for the presidential races in Indiana were calculated based on official
vote total records published for the 2008 and 2012 general elections by the Clerk of the
U.S. House of Representatives.

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Appendix V: Voter Turnout Analysis Design

voters may have been subjected to more intense efforts by the
campaigns and interest groups to affect turnout. This imbalance in voter
mobilization efforts—which academic research has shown to be effective
in some conditions—is an important potential factor that could affect
turnout. 10 In contrast, the competitiveness of the presidential race in
Kansas and Tennessee did not change significantly between the 2008
and 2012 general elections. 11
Second, we collected data on the competitiveness of statewide and
federal elections in Kansas and Tennessee in order to ensure that
changes over time in voter mobilization efforts by campaigns were not
likely to affect voter turnout in 2008 or 2012. We considered a race
competitive if the margin of victory was less than 20 percentage points.
Our analysis indicated that Kansas and Tennessee had generally
noncompetitive election environments in both the 2008 and 2012 general
cson
elections. Neither Kansas nor Tennessee had statewide electoral races
of Tu
ity
with margins of victory ofInc. v. C 20 2016
less than , percentage points in either 2008 or
1
,
2012, with the exception of the st 3 presidential race in Kansas, which
ance
gu 2008
Allimargin Auvictory. Both states elect statewide officers,
had a 15grity
e percentved on of
c Int governors, in federal midterm election years. None of the nine
such
bli as archi
in Pu races 142 U.S. House of Representatives in Tennessee was
6
d
cite
15-1 for the
No. competitive in 2008, and one was competitive in 2012. Two of the four
races in Kansas for the U.S. House of Representatives were competitive
in 2008, and one of the same districts was competitive in 2012. No highly
competitive or consequential ballot questions appeared in Kansas in
either 2008 or 2012, and statewide ballot questions were not on the
general election ballot in Tennessee in either year. 12

10
Donald P. Green, and Alan S. Gerber. Get Out the Vote! How to Increase Voter Turnout.
Washington, DC: Brookings Institution Press, 2004.
11

The margin of victory for the presidential race in Kansas changed from 15 percent in
2008 to 22 percent in 2012; in Tennessee it changed from 15 percent in 2008 to 20
percent in 2012.

12

One ballot question appeared on the ballot in Kansas’s 2012 general election and no
ballot questions were present on the ballot for the 2008 general election. The ballot
question in 2012 sought to provide the Kansas legislature constitutional authority to adjust
watercraft property tax rates. In addition to the factors we considered, local ballot
questions may affect turnout in particular jurisdictions or precincts; we did not consider the
extent of local ballot questions in our analysis.

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Appendix V: Voter Turnout Analysis Design

In summary, the types of the voter ID laws that Kansas and Tennessee
adopted, combined with minimal contemporaneous changes in other
aspects of election administration, the offices and questions on the ballot,
and the competitiveness of those races, made these states the strongest
treatment states for analysis. 13 The characteristics of the 14 states we
considered as potential treatment states are listed in table 10.
Table 10: Potential Treatment States

State
Georgia

Indiana

Kansas

Federal midterm
or presidential
election when
voter
identification (ID)
change was first Type of ID
a
in effect
requirement

Process if voter
does not have
acceptable ID

2008 presidential
election

Provisional ballot +
follow-up

State requires both
government issued
photo ID and voter
follow-up if ID is not
provided at the poll
on Election Day?

Contemporaneous
changes to election
b
laws?

Yes

Yes

cson
of Tu
. City
6
nc. v 31, 201
e, I
cballot + gYest
s
n
2006 midterm
Photo only;
Provisional
Allia
Au u
follow-upd on
election
government egrity
t
issued onlyIn
ic
chive
Publ 6142 ar
in
2012 presidential Photo only;
Provisional ballot + Yes
cited o. 15-1
election
government
follow-up
N
Photo only;
government
issued only

No

No

issued only
Tennessee

2012 presidential
election

Photo only;
government
issued only

Provisional ballot +
follow-up

Yes

No

South Dakota

2004 presidential
election

Photo only;
government
issued only

Voter can verify
own identity

No

X

Idaho

2010 midterm
election

Photo only;
government
issued only

Voter can verify
own identity

No

X

13

In addition, the quality of state voter registration data was also an important
consideration when confirming Kansas and Tennessee as treatment states, as our
estimates of turnout percentages require accurate state records of registered voters at the
time of the 2008 and 2012 general elections. The vendor that provided enhanced state
registration records which we used for our analysis also provided documentation of data
quality for voter registration and history records across states. We used this information to
ensure that such data for Kansas and Tennessee were sufficiently reliable for our
analysis.

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Appendix V: Voter Turnout Analysis Design

Federal midterm
or presidential
election when
voter
identification (ID)
change was first Type of ID
a
in effect
requirement

Process if voter
does not have
acceptable ID

Michigan

2008 presidential
election

Photo only;
government
issued only

Voter can verify
own identity

New Hampshire

2012 presidential
election

Oklahoma

2012 presidential
election

State

Florida
Rhode Island

Alabama

State requires both
government issued
photo ID and voter
follow-up if ID is not
provided at the poll
on Election Day?

Contemporaneous
changes to election
b
laws?

No

X

Photo only; can be Voter can verify
nongovernment
own identity; can
be verified by
elections official

No

X

Can be nonphoto;
government
issued only

No

X

Provisional ballot +
do nothing

cson
of Tu
ty
6
v. Ci
nc. No 31, 201
2012 presidential Can be nonphoto; Provisional ballot +
ce, I gust
n
election
government
do nothing
u
Allia
issued only
grity ived on A
nte rch
I
2008 presidential Canublnonphoto; a
be ic
Provisional ballot + No
in P -16142 follow-up; can be
election
d nongovernment
cite
15
verified by elections
No.
Many changes
over time

Photo only; can be Provisional ballot;
nongovernment
do nothing

No

X
X

X

official

Arizona

2006 midterm
election

Can be nonphoto;
nongovernment.

Provisional ballot +
follow-up

No

X

Virginia

2012 presidential
election

Can be nonphoto;
nongovernment

Provisional ballot +
follow-up

No

X

Source: GAO analysis of state election laws. | GAO-14-634

Notes: Requirements are as of the 2012 general election. X indicates that analysis was not conducted
because the state was eliminated based on criteria in a previous column.
a

Refers to type of documents accepted and acceptable issuing entity. States requiring governmentissued ID include those where there is an exception for a school ID.
b

We reviewed election laws for changes that may significantly affect voter turnout, including changes
in no-excuse absentee voting, early voting, Election Day registration, felon disenfranchisement, and
third-party registration identifying states for further consideration as potential treatment states where
such changes were unlikely to affect turnout significantly.

Comparison State
Selection

To select comparison states, we applied four primary criteria to the
universe of 35 states that either had no ID requirement or had an ID
requirement that allowed voters to show a nonphoto, nongovernment ID

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Appendix V: Voter Turnout Analysis Design

as of the November 2012 general election. 14 This process ensured that
various confounding variables were held constant at the state level for the
treatment and comparison states. In effect, we applied “exact” matching
methods to balance state-level covariates. The criteria were as follows:
1. States did not implement changes to voter ID laws between the 2008
and 2012 general elections, when Kansas and Tennessee
implemented their amended ID requirements.
2. The election cycles for statewide elected offices were similar to those
of Kansas and Tennessee.
3. The states did not have competitive general elections for federal and
statewide elected offices and statewide ballot questions in 2008 and
2012.
4. The states did not experience contemporaneous changes to other
cson
of Tu
laws between the 2008 and 2012 general elections that may have
City 0 Election Day.
6
significantly affected voterv.
nc. turnout on 1
,2
I

1
,
ance Aug st 3
Allicriterion, we u
To apply grity
reviewed state voter ID requirements to
e the firstv d on
c Int states thatedid and did not implement changes to voter ID
identify 2 archi
bli
14
in Pu requirements between the 2008 and 2012 general elections. If a state
ited o. 15-16
c
N implemented changes to its ID requirements, we did not further consider it
for selection.
To apply the second criterion, we matched the election schedules for U.S.
Senate and governor’s offices—years in which the elections for these
offices are held—in the treatment and potential comparison states.
Matching election cycles controls for the presence of statewide political

14

Washington and Oregon were not included among potential comparators because both
states use vote-by-mail election systems. Pennsylvania and South Carolina were not
included among our universes of potential treatment or comparison states. Both states
enacted substantive changes to their ID requirements between 2002 and October 1, 2012
but the requirements in both states were subject to litigation and not fully implemented as
of the 2012 general election. Pennsylvania and South Carolina were also not included in
our universe of comparison states because the laws that were in effect in those states fell
outside the criterion for the types of laws we allowed for potential comparison states—no
ID requirement or one that allowed nonphoto, nongovernment IDs. Pennsylvania required
a photo ID (voters were allowed to cast a regular ballot if they did not present ID) and
South Carolina required a government issued ID. Louisiana was not included among our
potential treatment states because the state’s ID requirements were generally consistent
since HAVA was enacted, and it was not included among our potential comparison states
because it required photo ID.

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Appendix V: Voter Turnout Analysis Design

campaigns, which typically run programs to encourage turnout. These
voter mobilization efforts could coincide with changes to ID laws and bias
our impact estimates. In instances where the cycles did not precisely
match, we matched either the U.S. Senate cycle or the governors’ race
cycle (rather than both). We considered states that met any of these cycle
match requirements and excluded all others.
To apply the third criterion, we reviewed the competitiveness of general
elections in 2008 and 2012, using the margins of victory in state-wide
elections for federal, gubernatorial, and statewide political offices and for
statewide ballot questions. We sought to make the pattern in electoral
competition similar in the treatment and comparison states, particularly in
those cases where the election cycles did not precisely match.
To apply the fourth criterion, we reviewed election laws for changes that
cson
may significantly affect voter turnout, including changes in no-excuse
of Tu
ity Day6
absentee voting, early voting, v. C
nc. Election201 registration, felon
,
I
disenfranchisement, ce, third-party1
n and g st 3 registration, identifying states where
Allia on Auoruwere unlikely to affect turnout significantly.
y
such changes did not occur
d
egrit

t
hive
ic In
2 c
Publ addition ar these four criteria, we considered other factors that could
in In 614 to
cited o. 15-1
N affect turnout, such as geographic proximity to Kansas and Tennessee,

similarity in voter turnout histories between comparators and the
treatment states, and unique events, such as the effect of Hurricane
Sandy striking the East Coast 8 days before Election Day in 2012. 15 The
quality of state voter registration data was also an important consideration
when selecting comparison states, as our estimates of turnout
percentages require accurate state records of registered voters at the
time of the 2008 and 2012 general elections. 16 Table 11 lists the 35 states
considered as comparators and the rationale for exclusion or inclusion,

15

Geographic proximity to Kansas and Tennessee allows for potential similarities in
political culture, weather patterns, and media campaigns, all of which can affect turnout.
We measured historical turnout similarity by calculating the Euclidean distance between
turnout in Kansas and Tennessee, respectively, and each of the remaining states. We
used turnout data for the eight presidential general elections from 1980 through 2008,
defined as a state’s ratio of votes cast for President to its voting-eligible population, as
compiled by the United States Elections Project at George Mason University.

16

The vendor that provided enhanced state registration records which we used for our
analysis also provided documentation of data quality for voter registration and history
records across states. We used this information to inform our selection of comparison
states.

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Appendix V: Voter Turnout Analysis Design

based on the four main criteria. Table notes indicate when additional
factors, such as those listed above, were considered. As indicated in the
table, Alabama, Arkansas, Delaware, and Maine met all of our criteria and
were not eliminated from consideration because of other factors.
Table 11: Comparison State Selection Results
Passed criteria?
Potential comparison
a
states

1
Voter identification (ID)
requirements
substantively
unchanged?

2
Election cycles similar?

3
Noncompetitive
elections?

Yes

Alabama

Yes

Yes

Alaska

Yes

Yes

Arizona
Arkansas
California
Colorado
Connecticut
Delaware

b

4
No other legal changes
that could significantly
affect turnout?

n

No ucso
T

f
ity o
Yes
Yes
. v. C , 2No 6
01
nc
Yes
Yes ce, I
t 31 Yes
ian
ugus
AllYes
Yes
No
grity ived on A
e
c Int arch X
No ubli
X
2
P
d in 15-1614
Yes
Yes
No
cite
No.
Yes
Yes
Yes

Yes
X
X
Yes
X
X
X
Yes

District of Columbia

Yes

Yes

c

Hawaii

Yes

Yes

No

X

Illinois

Yes

Yes

Yes

No

Iowa

Yes

Yes

Yes

No

Kentucky

Yes

Yes

No

X

Maine

Yes

Yes

Yes

Yes

Maryland

Yes

Yes

No

X

Massachusetts

Yes

Yes

No

X

Minnesota

Yes

Yes

No

X

Mississippi

Yes

Yes

c

X

Missouri

Yes

No

X

X

Montana

Yes

Yes

No

X

Nebraska

Yes

Yes

No

X

Nevada

Yes

Yes

No

X

New Jersey

Yes

Yes

No

X

New Mexico

No

X

X

X

New York

Yes

Yes

Yes

c

Yes

c

X

North Carolina

Yes

Page 138

No

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Appendix V: Voter Turnout Analysis Design

Passed criteria?
Potential comparison
a
states

North Dakota

b

1
Voter identification (ID)
requirements
substantively
unchanged?

2
Election cycles similar?

3
Noncompetitive
elections?

4
No other legal changes
that could significantly
affect turnout?

Yes

No

X

X

Ohio

Yes

Yes

No

X

Texas

Yes

Yes

No

c

X

Utah

No

X

X

X

Vermont

Yes

No

X

X

Virginia

No

X

X

X

West Virginia

Yes

Yes

No

Wisconsin

Yes

Yes

No

Wyoming

Yes

Yes

X

n
ucso

X

c
of T
. City 2Yes 6
. v Clerk’s office 01election results produced by state election officials. |
c
Source: GAO analysis of state statutes, statutory changes, and election results provided by the U.S. House of Representatives 31,
and
e, In
GAO-14-634
lianc August
Althat an on was not completed because the state was eliminated based on
Notes: An egrity
t X indicates ved analysis
criteria n
blic I in a previoushi
arc column.
universe
in Pu The16142 of potential comparison states included states that allowed non-photo, non-government
issued
cited o. 15- IDs or had no voter ID requirement as of the November 2012 election.
N
Criteria for selection are as follows: (1) Criterion 1: Voter ID requirements remained the same
a

b

between the 2008 and 2012 general elections? (2) Criterion 2: State U.S. Senate and governors’
election cycles match with Kansas or Tennessee? If no, does at least one cycle (governors’ race or
U.S. Senate) match Kansas or Tennessee cycles? (3) Criterion 3: Margins of victory for U.S. Senate,
and governors’ races more than 20 percent in both 2008 and 2012; margin of victory for presidential
race changed less than 10 percentage points between 2008 and 2012 elections; ballot questions
either noncompetitive, or similarly competitive questions present in both elections? (4) Criterion 4: No
contemporaneous legal changes in the state that may have significantly affected voter turnout
between the 2008 and 2012 general elections?
c

Criterion not fully evaluated for this state because a separate factor eliminated the state, precluding
such analysis. Factors for each state are listed below:
District of Columbia. Historical voter turnout pattern was highly dissimilar (ranked 47th of 50
states in historical turnout similarity with both Kansas and Tennessee in general elections
from 1984 through 2012).
Mississippi. Voter registration data and history data were not sufficiently reliable for the
purposes of our analysis.
New York. Hurricane Sandy hit southern New York shortly before the November 2012
election, making comparison of voter turnout in 2008 and 2012 problematic.
North Carolina. The U.S. Senate race in North Carolina was competitive in 2008, with an 8
percent margin of victory, while no U.S. Senate race was held in 2012.
Texas. The U.S. Senate races in Texas were competitive in both 2008 (margin of victory of
12 percent) and 2012 (margin of victory of 16 percent).
Wyoming. Voter registration and history data were not sufficiently reliable for the purposes
of our analysis.

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Appendix V: Voter Turnout Analysis Design

As shown in table 12, we selected Alabama, Arkansas, Delaware, and
Maine as our comparison group of states because these 4 states most
closely matched Kansas and Tennessee on our selection criteria. For
example, changes to voter ID requirements were implemented in Kansas
and Tennessee but not in the comparison states; the election cycles are
similar; when races were held, they were noncompetitive; and none of the
states had other legal changes that would significantly affect turnout. In
addition, Alabama and Arkansas are geographically close to Kansas and
Tennessee, which takes advantage of any geographic similarities, such
as common weather conditions and regional political trends. 17 Consistent
with a strong counterfactual, historical year-to-year change in turnout in
the comparison states from 1984 through 2012 is similar to historical
changes in turnout in Kansas and Tennessee, as shown in figure 21.

cson
of Tu
. City
6
nc. v 31, 201
ce, I gust
n
u
Allia
grity ived on A
nte rch
blic I
a
in Pu -16142
ited o. 15
c
N

17

State border regions may experience similar factors that can affect turnout, such as
campaign media markets that overlap in border areas and weather patterns similar in
portions of the states on Election Day. Brad T. Gomez, Thomas G. Hansford and George
A. Krause, 2007, “The Republicans Should Pray for Rain: Weather, Turnout, and Voting in
U.S. Presidential Elections.” The Journal of Politics 69 (3): 649-663. Paul Freedman,
Michael Franz, and Kenneth Goldstein, 2004, “Campaign Advertising and Democratic
Citizenship.” American Journal of Political Science 48 (4): 723-741.

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Appendix V: Voter Turnout Analysis Design

Table 12: Characteristics of Treatment and Comparison States

State

Substantive
change in
identification
(ID)
requirements
between the
2008 and 2012
general
elections

Kansas

Yes

Tennessee

Yes

Alabama

No

Arkansas

No

+4 percentage
points

Yes

No

No

No

No

Delaware

No

-6 percentage
points

Yes

Yes

Yes

Yes

Yes

Maine

No

-2 percentage
points

Yes

Yes

No

No

No

Change in
presidential
election
margin of
victory (MOV),
2008 to 2012

Historical
turnout
Legal
similarity to
changes
Kansas and
between the
Tennessee
2008 and 2012 (ranking, of
general
the 50 states
elections that In general
could
elections,
significantly
1984 through
a
affect turnout 2012)

cson
of Tu
. City
6
nc. v 31, 201
ce, I gust
n No u
+7 percentage Yes
No
No llia
No
No
A
points
grity ived on A
nte rch
c
+5 percentage Yes
No
No
No
bliYesI
a No
points
in Pu -16142
d
5
cite
+1 percentage Yes No. 1 No
No
No
No
No
point

Kansas-10th
Yes
Tennessee-5th

No

Kansas-2nd
Yes
Tennessee-6th

No

Kansas-44th
Tennessee22nd

No

No

Kansas-23rd
Tennessee30th

No

Had 2008 U.S.
Senate
election, and
MOV

Had 2012 U.S.
Senate
election, and
MOV

Had 2008
Governor’s
election, and
MOV

Had 2012
Governor’s
election, and
MOV

Had 2012/
2008 other
statewide
office
elections

b

Geographically
proximate to
Kansas or
Tennessee

X

X

X

X

Source: GAO analysis of state statutes, statutory changes, and election results provided by the U.S. House of Representatives Clerk’s Office and election results produced by state election officials. | GAO-14-634
a

We measured historical turnout similarity by calculating a multivariate Euclidean distance between turnout in Kansas and Tennessee, respectively, and each of the
remaining states. We used turnout data for the eight presidential general elections from 1980 through 2008, defined as a state’s ratio of votes cast for President to its
voting-eligible population, as compiled by Michael MacDonald at the United States Elections Project, George Mason University. We differenced the turnout data between
elections to ensure that the distance measures reflected change over time, rather than cross-sectional variation. Since our difference-in-difference analysis holds
constant fixed differences across states, differenced turnout is the relevant lagged outcome measure for matching treatment and comparison states.
b

Delaware’s other statewide office elections in 2012 and 2008 were generally noncompetitive: Lieutenant Governor MOVs of 23
percent (2012) and 24 percent (2008) and Insurance Commissioner MOVs of 24 percent (2012) and 16 percent (2008).
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Appendix V: Voter Turnout Analysis Design

Historical turnout similarity between our treatment and comparison states
is depicted in Figure 21. The general turnout increases and decreases
trends among treatment and comparison states generally track one
another.
Figure 21: Yearly Change in Turnout in Treatment and Comparison States, 1984 to 2012 General Elections

cson
of Tu
. City
6
nc. v 31, 201
ce, I gust
n
u
Allia
grity ived on A
nte rch
blic I
a
in Pu -16142
ited o. 15
c
N

For the 4 comparison state candidates that were the best choices based
on the criteria applied above—Alabama, Arkansas, Delaware, and
Maine—we also examined ballot questions in the 2008 and 2012 general
elections. We collected data on the margin of victory for all statewide
ballot questions in each state, and systematically searched news media

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Appendix V: Voter Turnout Analysis Design

and other electronic information databases to ensure that there were no
particularly salient or competitive ballot questions that might affect voter
turnout inconsistently across both elections (i.e., increase turnout in 1
year but not the next, or vice versa). A summary of our ballot question
findings for the 4 states is presented below. We concluded that ballot
questions in the selected comparison states would not have significantly
affected turnout between the 2008 and 2012 general elections in the
comparison states.
Alabama. Eleven questions were on the 2012 general election ballot,
three of which were competitive (having MOVs of less than 20
percent). Six questions were on the ballot in the 2008 general
election, five of which were competitive. The presence of several
competitive ballot questions in both 2008 and 2012 created a similar
potential for voter mobilization and engagement in both years, such
on
that the presence of ballot questions Tucs
of was unlikely to have affected
turnout more in one election than the 16
other. Competitive ballot
. City
nc. v 31, 20 considered the following policy
questions in thence, I general election
2012
ust
lia
issues: iprohibitingon Aug
ty Al d requirements to participate in any health care
tegr hive
’s authority to tax
lic In
rc

2a
Pub
d in 15-1614
ite
c
No.

the 2008 general election, competitive ballot questions were: 4
questions that were statewide but specific to individual city taxation
issues (MOVs ranged from 1 percent to 16 percent) and one question
Arkansas. Three ballot questions were on the 2012 general election
ballot, each of which was competitive. Five questions were on the
2008 general election ballot, one of which was competitive. Voter
turnout was not likely to have been affected to a greater degree in
2012 or 2008 by the questions because each election had one
competitive, salient ballot question race, with the remaining questions
either noncompetitive or not on salient topics. The competitive and
percent) and to limiting adoptions to married cohabitants in 2008

Delaware. No ballot questions were present on the 2012 or 2008
general election ballots in Delaware.
Maine. Five ballot questions were on the 2012 general election ballot,
two of which were competitive. Three questions were on the 2008

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Appendix V: Voter Turnout Analysis Design

general election ballot, two of which were competitive. The presence
of competitive and salient initiatives in both years indicates that voter
turnout was not likely affected to a greater degree in one of the
elections versus the other. The competitive ballot questions in 2012
were a same-sex marriage initiat

percent) were on the ballot.
In addition to the presence and competitiveness of ballot questions, we
reviewed margins of victory for U.S. House of Representatives races in
the 2012 and 2008 general elections for Alabama, Arkansas, Delaware,
and Maine. As shown in table 13, Alabama had no competitive districts in
2012, but three of seven competitive districts in 2008. In Arkansas, two of
four districts were competitive in 2012 but none n
o were competitive in 2008.
Delaware’s at-large U.S. House district fwascs competitive in either year,
Tu not
ity o
and Maine had one of its two districts competitive in each year. To control
. v. C , 2016
c
for the general change inIn
31
e, competition between 2012 and 2008 in
lianc when ust
ug analyzing changes in voter turnout, we
Al
Alabama and Arkansas A
y
on
egrit
conducted the hived for the full states but also conducted a separate
c Int arc analysis
i
Publ
analysis 2
d in 15-1614of registrants living in non-competitive districts. Specifically, we
cite
No. excluded from our analysis registrants living in districts where U.S. House
of Representative races were competitive in 1 year but not the other.
These analyses are discussed in more detail in appendix VI.

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Appendix V: Voter Turnout Analysis Design

Table 13: Competitiveness of U.S. House of Representatives Races in Alabama,
Arkansas, Delaware, and Maine (2012 and 2008 General Elections)
State
Alabama

U.S. congressional
district

2012 margin
of victory

2008 margin
of victory

1
2
3
4
5
6
7

Arkansas

1
2

cson
of Tu
. 4City
6
nc. v 31, 201
ce, I Atgust
Delaware
large
n
Allia on Au 1
Maine egrity
d
t
ic In
chive
2
Publ 6142 ar
d in 15-1GAO analysis of election results provided by the U.S. House of Representatives Clerk’s Office. | GAO-14-634
Source:
cite
No.
3

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Appendix VI: Voter Turnout Analysis Methods,
Data Sources, and Additional Results

Appendix VI: Voter Turnout Analysis
Methods, Data Sources, and Additional
Results
To evaluate the extent to which changes in voter ID laws affected turnout
in Kansas and Tennessee, if at all, we applied several forms of
“difference-in-difference” methods to three different sources of data. Any
application of these methods must make certain assumptions to make
valid causal inferences with real-world data. In this appendix, we identify
these assumptions and justify them for our specific policy evaluation. We
describe the methods of data collection and analysis we used to estimate
the causal effects of interest. Finally, we present detailed estimates of
policy impact for each source of data we analyzed and for subgroups of
voters and alternative comparison groups. We show that the results
presented in the body of this report generally are not affected greatly by
the different data sources or methods we chose to use, or by the different
assumptions we made, except when using Maine in the comparison
group. 1

cson
of Tu
ity
Parameters of Interest
We use the Rubin Causalnc. v. C specify6 statistical parameters to
Model to 201 the
,
I
be estimated using nce,
observed data. 21
st 3 Registered voters, i {1, 2, …, N}, in
Alliaforotimeugu
A
the analysisty
egri states d n periods T {0, 1} make up the population of
i
c Int wherehTve
i
interest, 2 arc
T
Publ
d in 15-1614the 2012 general election. The treatment, D {0, 1}, equals 1 if a
denotes
cite
No. registrant was required to show government-issued, photo ID before
voting, according to the laws adopted by Kansas or Tennessee in this
time period, and equals 0 otherwise.
Each registrant has potential turnout decisions, YDT, that could be
observed for any combination of the time periods and treatment
conditions. Thus, in principle, four potential outcomes are possible for
each registrant, {Y00, Y10, Y01, Y11}, with the observed outcome at T equal
to Y.T = D * Y1T + (1 – D)* Y0T . However, in this application, no registrant
could have been exposed to the treatment at T = 0, so Y.0 = Y00 and Y.1 =
D * Y11 + (1 – D)* Y01.

1
When evaluating the robustness of our results, we removed Maine from the comparison
group in some of the analyses because of an imbalance in the competitiveness of
elections between the 2008 and 2012 general elections in that state.
2

Donald B. Rubin, 1974, “Estimating Causal Effects of Treatments in Randomized and
Nonrandomized Studies,” Journal of Educational Psychology 66 (5): 688-701.

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Appendix VI: Voter Turnout Analysis Methods,
Data Sources, and Additional Results

We seek to estimate two parameters: (1) the average treatment effect for
the treated (ATT) at T
n an exogenous vector of
covariates, X x, including both controls and subpopulations of interest,
and (2) the ATT at T
E(Y11 – Y01| D = 1, X = x)

(1)

Ex(E(Y11 – Y01| D = 1, X = x))

x

(2)

E(Y11 – Y01| D

The last line shows the unconditional ATT, which, by the law of iterated
n
expectations, equals the conditional ATTTucso
integrated over the distribution
3of
of X for the treatment states at . City
T
6

201
nc. v
ce, I gust 31,
n
Allia n Au
grityATT ed oATTx using difference-in-difference methods:
te
Difference-in-difference
We estimate chiv and
ic In
Publ 6142 ar
Estimators and Theirted in
ci
15-1
(3)
[E(Y.1 | D
X = x) - E(Y.0 | D
X = x)] No.
Assumptions
[E(Y.1 | D
Ex

X = x) - E(Y.0 | D

x)

X = x)]
(4)

[E(Y.1 | D

- E(Y.0 | D

[E(Y.1 | D

- E(Y.0 | D

-

3
Joshua D. Angrist and Jorn-Steffen Pischke, Mostly Harmless Econometrics (Princeton,
NJ: Princeton University Press, 2009), 56-57, 71. Jeffrey M. Wooldridge, Econometric
Analysis of Panel and Cross-Section Data, Cambridge, MA: MIT Press, 2003, 609.
Michael Lechner, “The Estimation of Causal Effects by Difference-in-Difference Methods.”
Foundations and Trends in Econometrics 4 (2010): 183. G.W. Imbens and Jeffrey M.
Wooldridge, “Recent Development in the Econometrics of Program Evaluation. Journal of
Economic Literature 47 (2009): 27.

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Appendix VI: Voter Turnout Analysis Methods,
Data Sources, and Additional Results

Replacing E(YDT | D = d, X = x) with the equivalent sample proportions
produces unbiased and consistent estimates of and . These
estimates equal and x under several assumptions, 4 which we apply to
the adoption of voter ID laws in Kansas and Tennessee below.
Common counterfactual trend: E(Y01 - Y00 | D = 1, X = x
X = x)

cited

E(Y01 - Y00 | D

Difference-in-difference methods require that the potential outcomes for
registrants who were and were not actually required to show voter ID
would have changed by the same amount over time (on average), if
Kansas and Tennessee did not change their requirements (withheld
treatment). This is the critical identifying assumption for difference-indifference estimates. Voters in the treatment and comparison states may
have different expected potential outcomes in on
cs either time period, so long
X = x) – E(Y00 | D
as this difference is constant over time:fE(Y00 | D
o Tu
ity
1=
= v C
0, X = x
Y01 | D 1, X c. x).– E(Y01 | D6 0, X = x). This is equivalent
, 20
e, In
to allowing an unobserved state t 31 effect” or a voter fixed effect when
lianc Augus“fixed
l
difference-in-differencen
designs are carried out using regression models
rity A
nteg data.ived o
fit c
blito Ipanel arch
u

in P -16142
15
No. Controlling for state and voter fixed effects is particularly important for

evaluating the effects of electoral administration practices, as previous
studies have argued. 5 Political science researchers have found that longterm differences across voters, such as education and political interest,
explain much more of the variation in turnout than factors that vary over
time, such as campaign mobilization efforts and administrative reforms to
make voting easier. 6 In addition, states vary widely in political and
election administration practices, demographics, and political culture. This
variation is associated with consistent, long-term differences in turnout at

4

For discussions of these assumptions, see Michael Lechner, “The Estimation of Causal
Effects by Difference-in-Difference Methods.” Foundations and Trends in Econometrics 4
(2010): 174-203.
5
Luke Keele and William Minozzi, “How Much is Minnesota Like Wisconsin? Assumptions
and Counterfactuals in Causal Inference with Observational Data.” Political Analysis
(2013): 1-24. Michael J. Hanmer, Discount Voting: Voting Registration Reforms and Their
Effects. New York: Cambridge University Press, 2009.
6
Raymond E. Wolfinger, and Steven J. Rosenstone. Who Votes? New Haven, CT: Yale
University Press, 1980. Steven J. Rosenstone and John Mark Hansen. Mobilization,
Participation, and Democracy in America. New York, NY: MacMillan Publishing, 1993.

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Appendix VI: Voter Turnout Analysis Methods,
Data Sources, and Additional Results

the state level. By holding constant these stable but influential variables
across voters and states, difference-in-difference methods account for a
large number of potential confounds, such as age, race, and pretreatment laws, practices, and political culture, which might otherwise
explain differences in turnout across voters at any one time. Moreover,
difference-in-difference methods control for common trends between
elections that affect turnout in both the treatment and comparison states,
such as novel political issues and foreign or economic crises that vary
over time at the national level. By accounting for these confounds by
design, difference-in-difference methods allow us to focus on controlling
for the smaller number of factors that varied over time within the
treatment states, but not the comparison states, between the 2008 and
2012 general elections, in order to isolate the causal effects of changes in
ID laws on turnout, if any.

cson

Since the voters subject to ID laws in of Tucannot be observed in the
2012
ity
counterfactual scenario in which C were6
. v. they, 201 never required to present ID,
Inc
31
X =ianise, identified, and the common trend or equivalent
E(Y01 | D
l x) c not ugust
Al
A
ty
stable bias iassumptions cannot be tested empirically. Instead, we support
tegr hived on
c Inassumptions through our selection of comparison states and our
i
these
2 arc
Publ 6 covariates in statistical analysis.
use
d in 15-1of14
cite
o.

N

We selected comparison states to ensure that the distributions of several
time-varying covariates at the state level were as similar as possible in
the treatment and comparison states (see appendix V). Our selection of
states to balance these specific covariates is similar to using exact
matching methods at the state level. 7 We matched on covariates that
political science research has identified to be correlated with turnout and
that can vary substantially over time. The covariates matched by design
included:

7
Exact matching methods produce two groups of units for analysis with identical values of
covariates. In contrast, other matching methods produce two groups that have
approximately the same distributions of the covariates.

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Appendix VI: Voter Turnout Analysis Methods,
Data Sources, and Additional Results

electoral competition (margin of victory) in campaigns for Presidential,
statewide, and U.S. House offices; 8
presence of elections to statewide offices (federal or state); 9
changes to other election administration laws, including no excuse
absentee voting, early voting, Election Day registration, felon
disenfranchisement, and third party registration; 10
geographic proximity and shared borders with the treatment states,
which implicitly controls for weather conditions on election day and
exposure opportunities to broadcast news media and campaign
advertising that cross state borders; 11 and
the number, visibility, and competitiveness of statewide ballot
questions. 12

son

While we could not achieve exact balance uc all of these covariates, we
of T on
. City 2016
found that choosing Alabama,vArkansas, Delaware, and Maine as
nc. constant
comparison states wouldIholdust 31, these covariates most effectively.
ce,
llian
ug
Becausegritycovariates of interest changed in similar ways over time in
the A
on A

d
te
ic In
chive
Publ 6142 ar
in
cited o. 15-1
N 8

Gary W. Cox and Michael C. Munger. 1989. “Closeness, Expenditures, and Turnout in
the 1982 U.S. House Elections.” American Political Science Review 83 (1): 217–31.
Michael P. McDonald and Caroline J. Tolbert, 2012, “Perceptions vs. Actual Exposure to
Electoral Competition and Effects on Political Participation.” Public Opinion Quarterly 76
(3): 538-554.
9

Mark A. Smith, 2001, “The Contingent Effects of Ballot Initiatives and Candidate Races
on Turnout.” American Journal of Political Science 45 (3): 700-706.
10

Paul Gronke, et al., 2008, “Convenience Voting,” Annual Review Of Political Science 11:
437-455. Raymond E Wolfinger, Benjamin Highton, and Megan Mullin, 2005, “How
Postregistration Laws Affect the Turnout of Citizens Registered to Vote.” State Politics and
Policy Quarterly 5 (1): 1-23. Barry C. Burden, et al., 2012, “Election Laws, Mobilization,
and Turnout: the Unanticipated Consequences of Election Reform,” American Journal of
Political Science 58 (1): 95-109.

11

Brad T. Gomez, Thomas G. Hansford and George A. Krause, 2007, “The Republicans
Should Pray for Rain: Weather, Turnout, and Voting in U.S. Presidential Elections.” The
Journal of Politics 69 (3): 649-663. Paul Freedman, Michael Franz, and Kenneth
Goldstein, 2004, “Campaign Advertising and Democratic Citizenship.” American Journal of
Political Science 48 (4): 723-741.

12

Caroline J. Tolbert, John A. Grummel, and Daniel A. Smith, 2001, “The Effects of Ballot
Initiatives on Voter Turnout in the American States.” American Politics Research 29 (6):
625-648. Matthew Childers and Mike Binder, 2012, “Engaged by the Initiative? How the
Use of Citizen Initiatives Increases Voter Turnout.” Political Research Quarterly 65 (1): 93103.

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these states and in the treatment states, the common counterfactual trend
(stable bias) assumption becomes more credible. Nevertheless, the
treatment and comparison states do not match exactly, which introduces
the potential for bias. Appendix V discusses the primary ways in which
the treatment and comparison states differ, and this appendix discusses
our strategy for mitigating bias that may result.
In some versions of our analysis, we use statistical models to control for
additional covariates beyond those controlled by design at the state level,
in order to further support the common counterfactual trend assumption.
Depending on the data available, our covariates include race, age, sex,
family income, marital status, education, length of registration (proxy for
residential mobility), labor force participation, and party registration.
Although difference-in-difference methods control for the main effects of
time-invariant covariates (e.g., race), includingon
covariates in statistical
Tucs
analysis can improve the precision of of estimates and, more important,
the
ity
control for interactions withc. v. C
time. Trends in6
201 potential outcomes may not be
n
ce, I g st 31,
parallel within demographic orupolitical groups if political campaigns or
llian
n Au
interestegrity Adisproportionately encouraged turnout among some
groups
ebut
nt in onecyear d o not another, even though our design ensures that
v
groups
blic I 42 ar hi
1
in Pu overall levels of competition were similar at the state level. Controlling for
6
cited o. 15-1
N interactions between these covariates and time further supports the
assumption that outcomes would have been parallel if the treatment were
absent.
Although the common counterfactual trend assumption is a critical
difference-in-difference identification assumption, several others are also
necessary, which we discuss below.
Stable unit treatment value
The stable unit treatment value assumption requires that changes in voter
ID laws in Kansas or Tennessee, respectively, must not have affected
turnout decisions in the other treatment state or in the comparison states.
This could occur if registrants in comparison states adjacent to the
treatment states mistakenly believed they were subject to the ID laws,
perhaps due to misinformation from residents of the treatment states or
news media sources that serve both sides of a state border, such as in
Kansas City, Kansas, or Memphis, Tennessee. If this were true, the
assumption that Y.1 D * Y11 + (1 – D)* Y01 would be false, because a
voter’s observed outcome would not depend solely on his or her own
treatment status.

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Our selection of comparison states makes this assumption both more and
less plausible. It is possible that registrants in areas of Arkansas and
Alabama near the borders of Kansas and Tennessee, respectively, could
incorrectly conclude that ID laws across the border applied to them.
Alternatively, if ID laws affected turnout by preventing registrants of ID
states from voting due to their lack of proper documentation, registrants in
the comparison states could not be affected by definition (assuming
perfect policy implementation). 13 In this scenario, the stable unit treatment
value assumption would be more reasonable, particularly in the interior
parts of Alabama and Arkansas and in Delaware and Maine, where the
lack of shared borders reduces the chance of cross-over. Our use of
Delaware and Maine as comparison states checks the sensitivity of our
estimates to this assumption.
Common support of the covariates: 0 < Pr(D son X = x) < 1 for all x

f Tuc
ity o 6
Since the expectations in nc. v. C 3 and 4 above are conditional on D
equations 201
ce I gu exist ,
and X, observations on ,X must st 31for all four combinations of D and T
n
u
Allia
in orderetorestimated x. n A “covariate overlap” exists when the fraction of
g ity ive o This
nt voters at X = x is greater than 0 and less than 1. By matching
treated
blic I 42 arch
in Pu comparison and treatment states on the variables described in Appendix
d
161
cite
. 15-we satisfied the common support assumption for state-level covariates
No V,
through design. In addition, matching avoids the risk of extrapolation bias
when using regression adjustments for state-level variables. 14 A limited
pool of potential comparison states exists with identical observed
changes to critical covariates between 2008 and 2012, because only 14
states since 2002 have adopted or implemented substantively modified
requirements for photo and/or government-issued ID or requirements for
registrants without these ID to follow-up. Sparse data increases the
chance of violating the common support assumption, such that no
comparison state can be observed for a given treatment state with an

13

At least two other mechanisms might produce spillover. First, registrants in the
comparison states who had misinformation could have chosen not to vote, regardless of
whether the policy legally affected them. Second, more registrants in comparison states
could choose to vote if ID policies improved their confidence in the integrity of elections.
Our use of Delaware and Maine as comparison states mitigates these risks, as well, due
to the lack of shared regional sources of information.

14

William G. Cochran and Donald B. Rubin, 1973, “Controlling Bias in Observational
Studies: a Review,” Sankhya: The Indian Journal of Statistics, Series A 35 (4): 417-466.
Daniel E. Ho, et al., 2007, “Matching as Nonparametric Preprocessing for Reducing Model
Dependence in Parametric Causal Inference,” Political Analysis 15: 199-206.

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identical set of covariates and the causal parameter of interest cannot be
identified. Our covariates of interest at the voter level are demographic
variables, such as age and race. Each type of voter should exist in the
treatment and comparison states in large samples, so the overlap
assumption should be satisfied. We tested this assumption by comparing
the empirical distribution of covariates in the treatment and comparison
states, and redefined the populations for which estimates apply when
common support is not achieved for the original populations of interest.
Covariates are exogenous
Our covariates must be independent of the potential outcomes and the
use of ID laws. The presence of an ID law is unlikely to affect the fixed or
long-term social and political characteristics that we plan to control for.
For example, age, race, or education are clearly not causally related
cson
(subsequent) to whether a registrant lives u a treatment state. These are
of Tin
. City
biological or social characteristics that 2016 administration practices
nc. v 31, election
I
cannot plausibly linfluence. Similarly, covariates such as party registration
nce, ugust
Al ia onare unlikely to be causally related to changes in
y
and lengthriof residence A
d
eg t
c Int and rchivedecisions between two consecutive Presidential
IDi laws
avoting
Publ 6142ID laws are only a minor consideration among many others
in elections.
cited o. 15-1
N when forming political beliefs and deciding where to live.
No pre-treatment effect: E(Y10 - Y00 | D

X=x

x.

Voter ID laws must not have influenced potential outcomes for the treated
before they were enacted. This assumption is almost certainly true in our
application. The ID laws in Kansas and Tennessee were not in effect for
the 2008 election, so they could not have been legally applied by
jurisdictions and formally affected the ability to vote. Moreover, voters
probably could not have anticipated the laws’ passage, and in any case,
would have no reason to make turnout decisions in 2008 based on
expected ID laws in 2012, given that the 2012 candidates were unknown.

Implementation Methods

Implementing difference-in-difference methods involves estimating the
conditional expectations in equations 3 and 4 above. In principle, the data
used for estimation could consist of aggregate counts or frequencies
across subgroups of a population, which could be combined into an
estimate for the entire population or a specific type of registrant by
averaging the estimates across the subgroups. Specifically, one could
estimate the conditional expectations in equations 3 and 4
nonparametrically by computing the sample analogues at X = x and then

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integrating these estimates over the post-treatment sample distribution of
x for the treatment states. This approach would produce average
difference-in-difference estimates either for the entire population or
subpopulations of voters having certain values of x. The identification
assumptions and standard statistical results ensure that the equivalent
conditional sample means equal the average treatment effect for the
treated in large samples. 15
Nevertheless, when the dimension of X is large, it can become
convenient to assume a parametric model for the conditional
expectations. This allows us to construct difference-in-difference
estimates with a linear regression model:
E(Yit | Dit, Tt, Xit

0

+

1Dit

+

2Tt

+

Dit * Tt + Xit

(5)

cson

f other variables and parameters
where Xit is a vector of covariates andoallTu
ity
16
are as defined previously.ncThe C
. v. estimated6
01 effect of changes in voter ID
I
31, 2
c additionaltamount by which turnout changes in the
laws is given by lli, thee,
n
ugus
A a
treatment rity relative to the comparison states. Note that this model
gstatesived on A
te
ic In
ch
could be estimated using either repeated observations on the same
Publ 6142 ar
in
registrants (panel data) or pooled, repeated cross-sections from the
cited o. 15-1
N population of interest. Covariates can be measured at either time, so long
as they are exogenous in both.
We estimated the effect of the changes in voter ID laws in Kansas and
Tennessee using multiple sources of data on voter turnout: official vote
totals, voter registration and history databases, and post-election surveys.
Because the level of analysis and availability of covariates varied across
sources, we used various combinations of the parametric and
nonparametric methods above to estimate the effects of interest, as well
as various approaches to estimating the uncertainty of these estimates.

15

Joshua D. Angrist and Jorn-Steffen Pischke, Mostly Harmless Econometrics (Princeton,
NJ: Princeton University Press, 2009), 56-57, 71. Jeffrey M. Wooldridge, Econometric
Analysis of Panel and Cross-Section Data, Cambridge, MA: MIT Press, 2003, 609.
Michael Lechner, “The Estimation of Causal Effects by Difference-in-Difference Methods.”
Foundations and Trends in Econometrics 4 (2010): 183. G.W. Imbens and Jeffrey M.
Wooldridge, “Recent Development in the Econometrics of Program Evaluation. Journal of
Economic Literature 47 (2009): 26-27.

16

We implicitly assume that Yit is the result of a partially random process, such that Yit | Dit,
Dit * Tt + Xit
Tt, Xit
0 + 1Dit + 2Tt +
it .

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cited

The literature in statistics and economics is currently conflicted about how
to assess the uncertainty of difference-in-difference estimates. On one
extreme, finite population sampling theory might view official data on
turnout decisions, either in the form of aggregate totals or voter-level data
in registration and history databases, as having zero sampling error. 17
Voting decisions and other characteristics are observed for the entire
population of registrants (assuming zero measurement error), so
difference-in-difference estimates could be viewed as comparisons of
population proportions that have no uncertainty. 18 These population
parameters identify ATT if the assumptions above hold. On the other
extreme, researchers have argued that difference-in-difference methods
suffer from a potential clustering problem. 19 These authors imply that
since we observe data on the same states and, in the case of panel data,
voters over time, clustered data generation processes can cause the
decision to vote to be correlated within states, on conditional on fixed
even
ucs
effects for states and time periods.itFor f T
o example, changes in turnout may
C y
be correlated over time around .long-term16 means, due to
nc. v 31, 20 state
,I
contemporaneousance uinust
lli changes g campaign mobilization efforts, the presence
Asalient races, and Election Day weather conditions for
of moreeorrless ed on A
g ity
c Int archivsame state.
i
registrants in the
2
Publ

in
1614
. 15- view our data as the product of a partially random process. A
No We

population of registrants decides whether to vote in a given time period,
given fixed registrant and environmental variables, such as education,
campaign mobilization, and ID requirements. This decision is a binary
Yi
Xi,
random variable with a conditional expectation E(Yi | Xi, T
T). We view data on turnout from official records or surveys, measured at
either the registrant or aggregate levels, as numerous draws from this

17

William G. Cochran, Sampling Techniques, John Wiley and Sons: New York, 1977.

18

For an alternative view on the precision of DID estimates, incorporating uncertainty with
respect to the choice of comparison groups, see Alberto Abadie, Alexis Diamond, and
Jens Hainmueller, 2010, “Synthetic Control Methods for Comparative Case Studies:
Estimating the Effect of California’s Tobacco Control Program.” Journal of the American
Statistical Association 105 (490): 493-505.

19

Marianne Bertrand, Ester Duflo, and Sendhil Mullainathan, 2004, “How Much Should We
Trust Difference-in-Difference Estimates?” The Quarterly Journal of Economics 119 (1):
249-275. Stephen G. Donald and Kevin Lang, 2007, “Inference with Difference-inDifferences and Other Panel Data.” The Review of Economics and Statistics 89 (2): 221233. Robert S. Erikson and Lorraine C. Minnite, 2009, “Modeling Problems in the Voter
Identification-Voter Turnout Debate.” Election Law Journal 8 (2): 85-101.

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conditional distribution, which may be non-independent within states,
counties, or other politically meaningful groups, depending on the extent
to which contextual variables such as campaign mobilization and changes
to state election administration practices are controlled.
Our selection of treatment and comparison states should hold constant
many sources of clustered turnout decisions. By matching states on
election schedules and electoral competition, we hold constant the
campaign mobilization efforts that might cause turnout to be correlated
among voters in the same states. Geographic matching approximately
holds constant Election Day weather conditions. The lack of
contemporaneous changes to other state election laws holds constant
administrative shocks (changes to jurisdictions’ practices over time).
Because these factors are implicitly controlled, we do not believe that
clustered sampling processes should substantially inflate standard error
cson
estimates when viewing the numberyof f Tu
oregistrants as the sample size. In
Cit
6
addition, our short panel of c. v.time periods reduces the impact of serial
n two 31, 201
c to I gust
correlation, according e, previous research of clustering in the context of
n
Allia o methods. 20
difference-in-differencen Au
grity
d
e

t
ic In
chive
Publ 6142 ar
in Despite
cited o. 15-1 this substantial control for contextual variables, we made
N adjustments for possible within-state and within-county clustering in

several versions of our analysis below. Several of the methods proposed
to adjust for clustered sampling processes produce correct variance
estimates only when the number of clusters and/or number of units within
each cluster becomes large. 21 Accordingly, we used several methods of
variance estimation that the literature has shown to work more effectively
in situations with a small number of time periods and clusters.
Specifically, we estimated using linear probability regression models fit
to registrant-level data from the Current Population Survey and state
voter registration and history files (enhanced by the commercial firm,
Catalist, LLC). In these analyses, we used “cluster-robust” variance

20

Marianne Bertrand, Ester Duflo, and Sendhil Mullainathan, 2004, “How Much Should We
Trust Difference-in-Difference Estimates?” The Quarterly Journal of Economics 119 (1):
261-262.

21

Jeffrey M. Wooldridge, 2003, “Cluster-Sample Methods in Applied Econometrics,” The
American Economic Review 93 (2): 134. Marianne Bertrand, Ester Duflo, and Sendhil
Mullainathan, 2004, “How Much Should We Trust Difference-in-Difference Estimates?”
The Quarterly Journal of Economics 119 (1): 261-262.

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estimators, which allow for observations to be arbitrarily correlated within
groups but independent across groups, conditional on the covariates and
design variables. 22 Versions of this analysis used state and state-county
clusters, since the decision to vote is most plausibly correlated within
counties in an analysis that holds constant several state-level factors
associated with turnout. However, turnout decisions also may be
correlated within counties in the same state, if any meaningful covariates
at the state level are unobserved. We estimated 95 percent confidence
intervals as

±

,.

Var

, where the degrees of freedom is a

function of the number of clusters, nc. Although in theory cluster-robust
methods estimate variances correctly only when nc is large, Monte Carlo
simulations have found that the method performs well in finite samples
with two time periods and six clusters—a structure similar to that of our
data. 23 Because sample sizes are large and all covariates are categorical,
cson
of Tu
the cluster-robust covariance matrixyestimators adjust for the
Cit
heteroskedasticity impliednby linear probability regression models fit to
c. v. 1, 2016
,I
n such ugust 3
registrant-level data, ce as equation 5 above, and model estimates of
Allia on [0,1]. 24 Moreover, a generalized linear model with
turnouttegribounded on A
are ty
d
hive
c In
ai
2 arc
Publspecification equivalent to equation 5 above does not allow for timein invariant
614
cited o. 15-1 25differences between groups (common trend), unlike linear
N models. Despite the validity of linear probability models in these
conditions and the limitations of generalized linear models, we replicated
4 versions of our results within a maximum absolute difference of 0.4
percentage points using identically specified logit models. 26
For analyses of aggregate turnout data, we assumed that turnout
decisions occur independently within each state and time period, and
estimated the variance of using the normal approximation for

22

Manuel Arellano, 1987, “Computing Robust Standard Errors for Within-Groups
Estimators,” Oxford Bulletin of Economics and Statistics 49 (4): 431-434.

23

Marianne Bertrand, Ester Duflo, and Sendhil Mullainathan, 2004, “How Much Should We
Trust Difference-in-Difference Estimates?” The Quarterly Journal of Economics 119 (1):
265, 270-271.

24
Jeffrey M. Wooldridge, Econometric Analysis of Cross-Section and Panel Data,
Cambridge, MA: MIT Press, 2002, 454-457.
25

Michael Lechner, “The Estimation of Causal Effects by Difference-in-Difference
Methods.” Foundations and Trends in Econometrics 4 (2010): 196-200.

26

The specific estimates replicated were rows 20 and 21 of table 20.

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differences in proportions across large, independent samples. Since is
a sum of independent proportions, the variance of its estimator using
, is equal to the sum of the variances across time
sample proportions,
periods and treatment conditions:
Var( )

Var((

-

)-(
(1

-

))

(6)

)

We calculate Var( ) similarly for subpopulations, replacing
and
with equivalent sub-sample quantities. We estimate 95 percent margins of
error using the normal approximation,

±

.

Var

.

cson
of Tu
. City
6
nc. v 31, 201
I
ce,analysis,t spanning three data sources and
s
Data and Results
Multiple versionsliofn
Al a our ugu
variousegrity
analytical ed on A found decreases in turnout in Kansas and
methods,
t
ic In
chiv
Tennessee beyond decreases in turnout in our comparison states, and
Publ 6142 ar
in our1
cited o. 15- analysis suggests that these differences are attributable to changes in
N voter ID laws in those states because we held constant other factors that
could have affected turnout. 27 Below, we discuss the three sets of data
we analyzed, the particular version of difference-in-difference methods we
applied, and detailed estimates of policy impact under various
assumptions. For each of the data sources, we reviewed documentation
describing steps taken by the data managers to ensure data reliability and
tested the data for anomalies that could indicate reliability concerns. We
found that each of the three sets of data was sufficiently reliable for the
purposes of our review.

Official Vote Totals

Our data on official vote totals come from United States Elections Project
at George Mason University. 28 The project collected data on the total
ballots and votes counted for the highest office in our six analysis states
in the 2008 and 2012 general elections, as part of a larger effort to
accurately estimate turnout among people eligible to vote. To calculate

27

This range excludes results for some comparison groups that included Maine.

28

We obtained these data from the project’s website
(elections.gmu.edu/voter_turnout.htm) on May 30, 2013.

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turnout rates, the project collected data on the total number of people in
each state who were at least 18 years old and who were likely to be
eligible to vote, after subtracting totals of people known to be ineligible,
such as non-citizens and convicted felons in some states. Thus, the data
available for analysis consisted of aggregate voting-eligible and votingage turnout rates for the treatment and comparison states in 2008 and
2012, along with the number of voters from whom the rates were
calculated.
Certified vote totals have several benefits, compared to other sources of
turnout data available. Vote and ballot totals reflect the results of state
vote certification processes to determine election outcomes. These totals
do not reflect the errors of recall and self-reporting that can affect election
surveys, which ask voters whether or not they voted. In addition, vote and
ballot totals do not reflect data entry errors that can occur when election
cson
administrators fail to update a registrant’s turnout history in official
of Tu
. ity 2016 29
records, or update these recordsC
nc. v incorrectly. Lastly, vote and ballot
,
I
t votes that election officials ultimately
totals include onlyance, ballotssor31
those
Alli on Augu
y
counted toward deciding the election outcomes. Voter ID laws may affect
egrit hived
c Int by requiring registrants without proper ID to cast provisional
i
turnout
2 arc
Publ
ballots, which election officials may or may not count pursuant to state
d in 15-1614
cite
No. law. Because vote and ballot totals only include provisional ballots that
were counted, they provide a unique measure of turnout as the votes
actually counted, rather than just attempted.
We estimated difference-in-differences by using aggregate data in which
we substituted the turnout rates for each group of states and time period
in equation (3). For each treatment state, we calculated separate
estimates for each comparison state individually, and created alternative
comparison groups by pooling the data for various combinations of states.
Because the difference-in-difference is a difference of proportions using
data on up to several million registrants, we used standard Normal
approximations for calculating the sampling error of proportions and their
95 percent confidence intervals, assuming independent observations
within states in an alternative version of our analysis below.

29

Stephen Ansolabehere and Eitan Hersh, 2012, “Validation: What Big Data Reveal About
Survey Misreporting and the Real Electorate.” Political Analysis 20: 437-459.

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Table 14 provides estimates of eligible-voter turnout in Kansas and
Tennessee, respectively, using various combinations of the comparison
states, along with the change in turnout between the 2008 and 2012
general elections. Turnout in both Kansas and Tennessee declined by
about 5 percentage points in this period, compared to declines of 1.9 to
3.0 percentage points in the comparison states. As shown in table 15,
these turnout estimates imply difference-in-difference impact estimates of
–2.1 to –3.2 percentage points in Kansas and –1.8 to –2.9 percentage
points in Tennessee. The relatively small variation in the effect estimates
suggests that our results are robust across multiple alternative choices of
comparison groups.
Table 14: Eligible Voter Turnout Estimates by State and Year, Using Official Vote
Totals
State

son (%)
2012

2008 (%) c
of Tu

. City 62.1
6
Kansas
nc. v 31, 201
ce, I gust
Tennessee
57.0
n
Allia on Au
Alabama grity
60.8
nte
ved
blic I 42 archi
Arkansas
52.5
in Pu -161
5
ited o. 1Delaware
65.7
c
N

Difference (%)

57.0

-5.1

52.2

-4.8

58.9

-1.9

50.5

-1.9

62.7

-3.0

Maine

70.6

68.1

-2.5

Alabama, Arkansas pooled

57.7

55.8

-1.9

Delaware, Maine pooled

68.7

66.0

-2.7

All comparison states pooled

60.2

58.1

-2.1

Source: GAO analysis of United States Elections Project data. | GAO-14-634

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Table 15: Effects of Changes in Voter ID Requirements on 2012 Eligible Voter
Turnout in Kansas and Tennessee, Using Official Vote Totals
Treatment state
Impact estimate, %
(margin of error) —
Kansas

Impact estimate, %
(margin of error) —
Tennessee

Alabama

-3.2 (0.12)

-2.9 (0.10)

Arkansas

-3.1 (0.14)

-2.9 (0.12)

Comparison state

Delaware

-2.1 (0.19)

-1.8 (0.18)

Maine

-2.5 (0.16)

-2.3 (0.14)

Alabama, Arkansas pooled

-3.1 (0.12)

-2.9 (0.10)

Delaware, Maine pooled

-2.3 (0.16)

-2.1 (0.14)

All comparison states pooled

-3.0 (0.12)

-2.7 (0.09)

cson
of Tu percentage points, with 95 percent
Note: Entries are difference-in-difference estimates scaled in
. City 2016
margins of error in parentheses (e.g.,c. v
n +/- 0.12 percentage points).
,
I
st 31
nce,
Allia on Augu
y
d
egrit
c Int vote rchive not allow for separate impact estimates among
i
Official
Publ 6142 atotals do
Voter Registration and
in
various
cited o. 15-1 subgroups of registrants, because they do not disaggregate the
History Databases
N
Source: GAO analysis of United States Elections Project data. | GAO-14-634

data according to subgroup membership. To address this limitation, we
conducted parallel analyses of voter registration and history databases to
check the robustness of our estimates using a different version of official
data, to estimate effects within subgroups of registrants, and to control for
additional variables at the voter level. We purchased access to a version
of voter registration and history databases maintained by state election
officials from Catalist, LLC. Catalist provides data on characteristics of
registrants and their turnout decisions in the 2008 and 2012 general
elections derived from official state data and commercial sources. Catalist
extensively cleans the official data to more accurately measure voter
eligibility. The firm collects official state data for all 50 states and the
District of Columbia from state governments and other sources and tracks
changes in the files over time. This allows the company to identify voters
who move across states lines, which avoids counting voters as eligible in
multiple states. In addition, Catalist matches the official data to the
National Change of Address Registry from the U.S. Postal Service, in
order to further identify registrants who have moved, and to the Death
Master File from the Social Security Administration, in order to identify
registrants who have died. Finally, Catalist applies a large number of
electronic reliability tests to the data, clarifies potential errors with state

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Data Sources, and Additional Results

officials, collapses duplicate records from the source data, and
documents unresolved problems with the source data. 30
After we initially released our report, we learned that Catalist obtained the
voter files for two of the six states we analyzed, Tennessee and Alabama,
through the states' Democratic Parties. On November 13, 2014 a
representative from the Democratic Party in Tennessee confirmed in
writing to having acquired the state voter data from the Tennessee
Secretary of State and providing these data directly to Catalist, without
alteration or modification on February 19, 2014. We took additional steps
to assess how, if at all, Catalist’s file acquisition process might have
affected the reliability of data we analyzed. Specifically, we analyzed
additional copies of the Tennessee voter file to obtain reasonable
assurance that Catalist’s file acquisition process did not affect the
reliability of the data we analyzed. To do this,swe obtained from Catalist
c on
the full voter file that the company said f Tu obtained from the
o it had
City
Tennessee Democratic Party v. February16
nc. in 31, 20 2014. This was the data file that
ce, I for t
Catalist said it usednas inputgusits proprietary data cleaning and
Allia on Au as discussed in the previous paragraph.
y
supplementation processes,
egrit hived
c Intprocesses produced as output the file we analyzed in our report.
i
c
These
Publ 6142 ar
We
d in 15-1matched the records in this source file to the Tennessee voter file that
cite
No. the Democratic Party said it obtained directly from the Secretary of State
on February 19, 2014—which, after we issued our report, it provided to
Catalist to share with us. We found that 100 percent of the registrants in
Catalist’s 2014 source file were in the Democratic Party’s 2014 file. In
addition, for all the key data values we used in our analysis, 100 percent
of the values, along with all field formats, names, and other metadata,
matched exactly.
We also matched the records in the source file to records in a version of
the Tennessee voter file, dated February 9, 2009, that Catalist said it
obtained directly from the Tennessee Secretary of State, which was
consistent with the file’s metadata on ownership and times of creation and
modification. The formatting of all field names, formats, and codes in
these two files matched exactly. Of those registrants in the 2014 file who
were registered prior to February 9, 2009, 94.9 percent also appeared in
the Secretary of State’s version of the file in 2009. One would not expect

30

We considered other commercial vendors of voter file data, but selected Catalist due to
the company’s archiving of voter files over time, the use of their data in peer-reviewed
publications, and validation of their estimated racial data by Catalist and third parties.

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100 percent of all registrants we analyzed in 2014 to be present on the
file in 2009, due to moves, deaths, removals of inactive registrants, and
other changes to registration status. Moreover, for the registrants in the
source file, the key data values we originally analyzed for these
registrants matched those in the Secretary of State’s file at rates of 98.5
to 99.8 percent, including turnout in the 2008 general election.
Further, following the issuance of our report, Catalist provided for our
review a copy of the agreement it had in place with the Alabama
Democratic Party for purchasing the state voter data. Catalist also sent us
a letter describing the process whereby the Alabama Democratic Party
would transmit the state voter data to Catalist upon receipt of the file from
the Alabama Secretary of State, in the form and manner as it was
received from the Office of the Alabama Secretary of State, and stated
that it had acquired the Alabama state voter data we analyzed in our
cson
report in such a manner on February 6,f 2013. The Chair of the Alabama
o Tu
. ity
Democratic Party also confirmedC writing 6 February 4, 2015, that,
nc. v in 1, 201 on
I
t3
although no currentnce, members were present at the time of the
staff
ug s
Allia onstate u
ity
delivery ofrthe Alabama A voter file to Catalist in February 2013, under
teg
ved
the In
Democratic Party’s agreement with Catalist, the Alabama
blicAlabamarchi
Pu voter6file 2 a
14 is obtained from the Secretary of State and provided without
in
cited o. 15-1
N alteration and modification to Catalist. Additionally, Catalist provided a
summary of analyses it had conducted on the state voter file it received
from the Alabama Democratic Party, including the file formats and
properties, translation codes and markings, and expected record counts
for the file, to assure itself of the source, suitability and sufficiency of the
voter data upon receipt from the party.
In sum, based on our reliability assessments before and after we initially
released our report, the written statements we received from Catalist and
the Tennessee and Alabama Democratic Parties, and the documents we
received from Catalist, we conclude that Catalist's acquisition of the
Tennessee and Alabama voter files through the state Democratic Parties
did not affect the reliability of the data contained in those files. Moreover,
we continue to conclude that all of the data we obtained from Catalist
were sufficiently reliable for our purposes, based on the reliability
assessments we conducted during the course of our review and after our
report was initially released; our review of the documents provided by
Catalist; and the fact that our results were consistent across multiple
comparison groups and multiple data sources.

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Catalist’s data on registrants’ race are particularly important for our
analysis. Some states, including Alabama and Tennessee, have
measured registrants’ self-reported race in their voter registration and
history databases. These data are included in official versions of voter
registration and history databases, and are preserved in the versions of
these databases we purchased from Catalist. Other states, including
Arkansas, Delaware, Kansas, and Maine, have not collected self-reported
racial data on almost all registrants as part of their databases. For these
registrants, Catalist estimates race using an algorithm supplied by a
commercial firm, CPM Ethnics.
To assess the reliability of these racial estimates, we received a custom
validation from Catalist, which compared the estimated race of registrants
in North Carolina to the actual race that registrants self-reported to state
election officials. This analysis found that approximately 70 to 90 percent
cson
of registrants, depending on racial group, coded by Catalist as “likely” or
of Tu
ity
6
“highly likely” to self-identify . v. C certain racial group did, in fact, identify
ncwith a31, 201
I
t
with that group iniance, records. Academic research has found similar
official
ll
ugus
levels of grity A Onenpeer-reviewed study matched racial estimates
reliability. d o A
te
ic Catalist’s hive files to a nationwide survey, in which respondents
fromIn
2 arc voter
Publ 6allowed to identify with various racial groups. For at least 93 percent
were
d in 15-1 14
cite
No. of survey respondents, Catalist’s estimates matched the race that
respondents identified for themselves. 31 This evidence allowed us to
conclude that Catalist’s estimates of race were sufficiently reliable for the
purpose of estimating impact estimates for various racial subgroups.
However, we assess the sensitivity of our results to potential racial
misclassification by estimating effects separately for Alabama and
Tennessee, where 98.8 and 63.4 percent of the racial data, respectively,
are provided by registrants directly. In addition, several versions of the
analysis include only registrants with self-reported race and/or age in
these states.
Several political scientists have used Catalist data to study voter turnout,
including to estimate the effects of changes in voter ID laws. One study
extensively evaluated the reliability of Catalist data, in part through
comparisons to official records, and found a high degree of
correspondence between the official and Catalist versions. This study

31

Stephen Ansolabehere and Eitan Hersh, “Validation: What Big Data Reveal About
Survey Misreporting and the Real Electorate,” Political Analysis 20 (2012): 453-454.

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was submitted as evidence by the Department of Justice in its case
against Texas before a 3-judge panel of the U.S. District Court for the
District of Columbia in June 2012. 32 Other studies using Catalist data
have been published in Political Analysis and the Quarterly Journal of
Political Science, which are both peer-reviewed scientific journals. 33
Nevertheless, we supplemented our analysis of Catalist’s data with
analyses of the two alternative sources of data described in this appendix
to mitigate the risk of relying on one source of data.
A final strength of Catalist data is that the company’s version of the official
voter databases allows us to identify people who were registered in the
past. Catalist archives state voter files over time and applies identifiers for
people who have been dropped from registration lists due to death,
moving, or other eligibility changes. Archiving allowed us to analyze a
n
consistent set of voters. Specifically, we selected registrants in the
ucso
Catalist database as of April 2014 iwho f T registered on or before
o were
. C ty registration was “active” (73.6
Election Day 2008 and whosevcurrent 2016
nc.
I
1,
percent of the analysis sample), t 3
nce, ugus “inactive” (8.1 percent) or “dropped”
Allia on Ainactive registrants are defined by each state.
y
(18.3 percent). Active and
egrit hiv d
c Intregistrants e generally people who have voted or interacted with
i
Active 2 arc
are
Publ
d in 15-1614administrators recently, while inactive registrants are generally
election
cite
No. people who do not meet the definition of “active” and are in the process of
potentially being dropped as registered voters, possibly due to death or
moving out of state. By selecting voters who were registered on or before
the 2008 election, including people who were dropped from the file
between 2008 and April 2014, we defined a consistent panel of voters for
analysis over time who could have participated in both elections of
interest.
We did not attempt to use specific criteria to identify eligible voters in
2008 and 2012, such as adjusting registration dates or voter history,
because the error in these methods would vary across years and states
and potentially bias difference-in-difference estimates that heavily rely on
over-time variation. Time-varying measurement error is a particularly

32

Texas v. Holder, No. 12-128 (D.D.C. June 30, 2012).

33

Stephen Ansolabehere and Eitan Hersh, 2012, “Validation: What Big Data Reveal About
Survey Misreporting and the Real Electorate,” Political Analysis 20: 437-459. Stephen
Ansolabehere, Eitan Hersh, and Kenneth Shepsle, 2012, “Movers, Stayers, and Voter
Registration,” Quarterly Journal of Political Science 7 (4): 333-363.

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Appendix VI: Voter Turnout Analysis Methods,
Data Sources, and Additional Results

important source of bias for difference-in-difference analysis, because it is
not controlled by design.
We assessed the sensitivity of our results to this method of constructing
an analysis population by excluding “dropped” voters from one set of
estimates. Our primary strategy of identifying registered voters included
people who were registered in 2008 but dropped from state voter files by
2012, and therefore were not eligible to vote in 2012. Our sensitivity
check considers how excluding these people affects our results—
essentially the opposing bias of our primary strategy. However, federal
law prevents states from dropping inactive registrants until after two
federal elections have occurred (4 years). Since our analysis of voter
databases in April 2014 occurred a maximum of six years after the
elections of interest, the voters registered to vote in the files we analyzed
likely closely approximate the registered voter on
populations as of Election
Tucs
Day 2008 and 2012.
y of

. Cit
6
nc. v 31, 201
I
c the gust
We could not analyze e, complete Catalist files at the registrant level,
n
u
Allia
due to the rterms of d on A
g ity ive our subscription to the data. As a result, we estimated
nte rchin equation 3 and 4 above using aggregate data on the
the I
blicparameters
a
in Pu full 16142
ited o. 15- population of registrants, in order to maximize the amount of data
c
N available for analysis. Because this approach limited our ability to analyze
a large number of covariates and subpopulations, we also analyzed a
sample of registrant-level data, which we describe below.
For our analysis of aggregate Catalist data, we calculated turnout rates
for G subsets of registrants formed by the cross-classification of race,
age, and year of registration (a proxy for residential mobility). For each
covariate cell, g {1, 2, … , G}, we estimated turnout separately for the
treatment and comparison states (D {0, 1}) in 2008 and 2012 (T {0,
1}). We combined these saturated conditional turnout estimates (or
estimates across mutually exclusive and exhaustive subgroups) to
estimate difference-in-difference parameters for the population of
registrants as

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Appendix VI: Voter Turnout Analysis Methods,
Data Sources, and Additional Results

[(

.

|D

X = g) - (

.

|D

X = g)] -

[(

.

|D

X = g) - (

.

|D

X = g)]

( )

(7)

(8)

[(

.

|D

-(

.

|D

[(

.

|D

-(

.

|D

-

( ) is the empirical probability mass on
where
cs function (sample
distribution) of g for the 2012 treatmentfstate sample. We constructed
o Tu
City
estimates for subpopulations of. registrants6
nc. v 31, 201 using similar calculations,
e, I
except that we averaged thegust
llianc A subgroup estimates over the marginal
Aconditionalu membership in the subpopulation.
y
distribution iof g ed on on
egr t
c Int archiv approach amounted to calculating weighted averages
i
Operationally, this
2
Publ
d in 15-1614
of subgroup-specific estimates, with the weights given by the sample
ite
c
No. proportion of the subgroup cells. Per the results above, estimates derived
from aggregate data can be interpreted as difference-in-differences and
as having held constant the covariates used to form the covariate cells
(age, race, and registration year) and their interactions with time. 34
Conditioning on the covariate cells makes our approach equivalent to
applying matching estimators with exact adjustment cells equal to the
cross-classified covariates above. 35
In table 16 below, we show difference-in-difference estimates for various
combinations of the comparison states and subpopulations of registered
voters. The top rows provide the effect when excluding registrants from
analysis if they were listed as dropped from the state’s voter file as of

34
Also see Jeffrey M. Wooldridge, Econometric Analysis of Cross-Section and Panel Data,
Cambridge, MA: MIT Press, 2002, 609. Michael Lechner, “The Estimation of Causal
Effects by Difference-in-Difference Methods.” Foundations and Trends in Econometrics 4
(2010): 183. G. W. Imbens and Jeffrey M. Wooldridge, “Recent Development in
Econometrics for Program Evaluation. Journal of Economic Literature 47 (2009): 26-27.
35

Joshua D. Angrist and Jorn-Steffen Pischke, Mostly Harmless Econometrics (Princeton,
NJ: Princeton University Press, 2009), 70-71.

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Appendix VI: Voter Turnout Analysis Methods,
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April 2014 (but were registered on or before Election Day 2008). The
middle rows include these registrants. The bottom rows limit the analysis
to voters registered in counties that were not in several Congressional
districts that we identified as potentially having experienced more or less
electoral competition between 2008 and 2012 (see appendix V), which
further controls for campaign competition. These counties overlapped
districts with a margin of victory of less than 20 percentage points in
either 2008 or 2012.
Across all of versions of the analysis that do not use Maine as a
comparison, the effect of changes in voter ID requirements on registered
voter turnout ranged from –0.6 to –3.9 percentage points in Kansas and
from –1.1 to –3.2 percentage points in Tennessee. The consistency of our
estimates across various comparison states and subpopulations suggests
that our results are robust to various threats toon
validity at the state level,
cs
Tuvoter mobilization efforts, and
f
such as changes in campaign competition,
ity o
weather conditions on Election .Day. 2016
.v C
c

31,
e, In
lianc August
AlMaine n the comparison group are consistently larger
Estimates rity
using
as
n eg chived o
c Iint otherrversions of the analysis, though in the same direction. The
i
than
2a
Publ
larger effects with respect to Maine could reflect the presence of a salient
d in 15-1614
ite
c
No. ballot proposition in 2012 on same-sex marriage. If this proposition

caused turnout in 2012 to be higher than it would have been in Kansas
and Tennessee, impact estimates would be biased downward, given that
turnout declined in Kansas and Tennessee. In addition, the completeness
of Maine’s voter history database improved between 2008 and 2012, with
the votes recorded in the database accounting for 90.3 percent of the
certified vote in 2008 but 98.6 percent in 2012. This change in
measurement error over time could have caused similar bias in our
impact estimates, because it would not have been controlled by design
and would have uniquely affected a comparison state but not the
treatment states. For these reasons, estimates using Maine as a
comparison state may be somewhat inflated in size across all data
sources.

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Table 16: Effects of Changes in Voter ID Requirements on 2012 Registered Voter
Turnout in Kansas and Tennessee, Using Voter Registration and History Databases
Impact estimate, %
(margin of error)
- Kansas

Impact estimate, %
(margin of error)
- Tennessee

Excluding registrants dropped from voter file
All comparison states

-2.2 (0.12)

-3.2 (0.09)

Alabama

-0.6 (0.13)

-1.9 (0.11)

Arkansas

-2.2 (0.15)

-3.2 (0.13)

Delaware

-1.5 (0.21)

-2.2 (0.19)

Maine

-5.2 (0.18)

-5.9 (0.16)

Alabama, Arkansas pooled

-1.1 (0.12)

-2.4 (0.10)

Delaware, Maine pooled

-4.1 (0.15)

-4.6 (0.13)

cson
of Tu -3.5 (0.12)
All comparison states
. City
6
nc. v 31, 201 -1.8 (0.13)
Alabama
ce, I gust
lian
Arkansas rity Al
-3.8 (0.15)
n Au
g
nte rchived o
Delaware
-1.9 (0.20)
cI
i
Publ 6 2 a
-6.8 (0.17)
d in 1Maine 14
5-1
cite
No. Alabama, Arkansas pooled
-2.6 (0.12)
Including registrants dropped from voter file

Delaware, Maine pooled

-5.1 (0.15)

-2.9 (0.09)
-1.6 (0.11)
-3.1 (0.13)
-1.1 (0.19)
-6.0 (0.16)
-2.2 (0.10)
-4.1 (0.13)

Excluding registrants in Congressional districts with change in competition
All comparison states

-2.9 (0.18)

-1.7 (0.11)

Alabama

-2.1 (0.20)

-1.3 (0.13)

Arkansas

-3.9 (0.22)

-2.7 (0.17)

Delaware

-3.1 (0.24)

-1.3 (0.19)

Alabama, Arkansas pooled

-2.8 (0.19)

-1.8 (0.12)

Source: GAO analysis of state voter registration and history databases (commercially enhanced). | GAO-14-634

Note: Entries are difference-in-difference estimates scaled in percentage points, with 95 percent
margins of error in parentheses (e.g., +/- 0.12 percentage points). Some competition existed in 2008
or 2012 in each of Maine’s two districts, so no estimates appear for comparison groups that include
Maine.

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We estimated effects among three subpopulations of registrants,
according to the race, length of registration, and age. 36 The effects varied
across these subpopulations, with larger effects among African-American
registrants, younger registrants, and recent registrants.
When estimating effects separately by race, we found that turnout among
African-American registrants declined more than turnout among White
registrants in Kansas and Tennessee between the 2008 and 2012
general elections, and our analysis suggests that this difference is
attributable to changes in those states’ voter ID laws (see table 17). The
effect among African-Americans was -7.0 percentage points in Kansas
and -4.1 percentage points in Tennessee, using all comparison states,
compared to -3.2 percentage points among Whites in Kansas and -2.6
percentage points in Tennessee. 37 Expressed as a ratio, AfricanAmerican registrants were affected 2.2 and 1.6 n
times more strongly in
ucso
Kansas and Tennessee, respectively,of T White registrants. We found
than
City
6
similar results when comparing.African-American registrants to Asiannc. v 31, 201
ce I gust
American and Hispanic ,registrants, respectively. The effects among
n
u
Allia
Asian-American, White, and Hispanic registrants were similar to each
grity ived on A
te
nparticularly when considering the effects’ margins of error. In
other,
blic I 4 arch
in Pu addition, 2 found similar results using Alabama, Arkansas, and
d
161 we
cite
. 15No Delaware separately as comparison groups, and using the pooled
Alabama and Arkansas comparison group. However, we found AfricanAmerican registrants were less strongly affected relative to other groups
using Maine as a comparison group. Several confounding factors specific
to Maine, as discussed above and in appendix V, may explain this
difference. Using Delaware as the comparison group, the effects among
both African-American and Hispanic registrants were larger than among
Whites.

36

Some states require registered voters to identify their race when registering to vote. For
those states, the vendor reports what registered voters indicate as their race. For states
that do not require self-reporting of race, the vendor classifies each voter’s race based on
other characteristics kept in official voter records and U.S. Census information. We
recoded the racial category names used by the vendor (Asian, Black, Caucasian,
Hispanic) into the following category names (Asian-American, African-American, White,
and Hispanic). The vendor provided us with voter ages as of 2014. For the purposes of
our analysis, we adjusted the ages of these voters to be measured as of the 2008 general
election.

37

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To assess the potential effect of imputed racial data on our results, as
discussed above, we conducted a version of our analysis using only
registrant-reported racial data from Tennessee and Alabama, the only
states in our design with such data available. Using these data, we
estimated effects of -4.2 percentage points (+/- 0.3) among AfricanAmerican registrants, compared to -0.7 (+/- 0.1) percentage points among
White registrants. The limited number of Asian-American and Hispanic
registrants in these states prevented us from estimating separate effects
for these groups using registrant-reported data.
Table 17: Effects of Changes in Voter ID Laws on 2012 Registered Voter Turnout in
Kansas and Tennessee, by Racial and Ethnic Subgroups, Using Voter Registration
and History Databases
Impact estimate, %
n
(marginucerror) of so
of T Kansas
ity

16
. v. C
, Inc st 31, 20
ce
Asian-American Allian
-2.3 (1.4)
ugu
grity ived on A
African-American
-7.0 (0.5)
nte rch
ic I
Publ 6142 a
White
-3.3 (0.1)
in
5-1
cited o. 1Hispanic
-2.2 (0.9)
N
All comparison states

Other/unknown

Impact estimate, %
(margin of error) Tennessee
-1.3 (1.3)
-4.1 (0.2)
-2.6 (0.1)
-2.6 (1.1)

-6.6 (1.6)

-1.4 (1.7)

0.1 (1.7)

1.1 (1.6)

Alabama
Asian-American
African-American

-7.3 (0.5)

-4.6 (0.2)

White

-1.6 (0.2)

-1.0 (0.1)

0.9 (1.4)

0.8 (1.5)

-3.1 (2.0)

3.5 (2.1)

Asian-American

-4.8 (2.0)

-3.5 (1.9)

African-American

-7.6 (0.5)

-4.1 (0.3)

Hispanic
Other/unknown
Arkansas

White

-3.6 (0.2)

-2.8 (0.1)

Hispanic

-4.1 (1.2)

-5.0 (1.4)

Other/unknown

-5.6 (2.2)

-1.2 (2.3)

-3.6 (2.0)

-2.5 (1.9)

Delaware
Asian-American

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Impact estimate, %
(margin of error) Kansas

Impact estimate, %
(margin of error) Tennessee

African-American

-5.2 (0.6)

-2.1 (0.4)

White

-1.5 (0.2)

-0.9 (0.2)

Hispanic

-3.5 (1.2)

-3.9 (1.4)

Other/unknown

-6.9 (2.6)

-3.1 (2.7)

-3.9 (2.3)

-2.9 (2.3)

Maine
Asian-American
African-American

-5.9 (1.5)

-3.9 (1.4)

White

-7.0 (0.2)

-6.5 (0.2)

Hispanic

-2.3 (2.2)

-2.5 (2.2)

-9.6 (2.6)
on
Tucs
of
ity
Alabama, Arkansas pooled c. v. C
2016
n
ce, I gust 31,
Asian-American
-1.5 (1.5)
llian
ity A d on Au
r
African-American
-7.3 (0.5)
nteg
ve
blic I 42 archi
White
-2.3 (0.1)
in Pu -161
5
ited o. 1Hispanic
-1.7 (1.0)
c
N

-3.4 (2.7)

Other/unknown

Other/unknown

-0.4 (1.4)
-4.4 (0.2)
-1.7 (0.1)
-2.3 (1.2)

-4.7 (1.7)

0.2 (1.9)

Asian-American

-3.8 (1.7)

-2.7 (1.7)

African-American

-5.2 (0.6)

-2.1 (0.4)

White

-5.1 (0.2)

-4.5 (0.1)

Hispanic

-2.9 (1.1)

-3.2 (1.3)

Other/unknown

-8.9 (2.0)

-3.4 (2.2)

Delaware, Maine pooled

Source: GAO analysis of voter registration and history databases (commercially enhanced). | GAO-14-634

Note: Entries are difference-in-difference estimates scaled in percentage points, with 95 percent
margins of error in parentheses (e.g., +/- 1.3 percentage points). Estimates include registrants who
were dropped from the voter files prior to April 2014.

The effect of changes in voter ID laws in both Kansas and Tennessee
declined as the length of registration increased (see table 18). Between
the 2008 and 2012 general elections, compared to the comparison states
pooled, turnout declined by 7.5 percentage points more in Kansas and
5.5 percentage points more in Tennessee for people registered to vote
within the past year; turnout declined by 2.3 percentage points more in
Kansas and 1.4 percentage points more in Tennessee for people

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Appendix VI: Voter Turnout Analysis Methods,
Data Sources, and Additional Results

registered to vote for at least 20 years. We found similar patterns using
the other comparison states except those involving Maine, with the
interaction being particularly strong using Alabama and Delaware.
Table 18: Effects of Changes in Voter ID Laws on 2012 Registered Voter Turnout in
Kansas and Tennessee, by Length of Registration, Using Voter Registration and
History Databases
Impact estimate, %
(margin of error) - Kansas

Impact estimate, %
(margin of error) Tennessee

Registered for 0-1 year

-7.5 (0.3)

-5.5 (0.3)

Registered for 1-2 years

-4.2 (0.7)

-4.9 (0.5)

Registered for 3-4 years

-4.6 (0.4)

-4.3 (0.3)

All comparison states

cson
Registered for 5-9 years
-3.3
of Tu (0.2)
. City
6
Registered for 10-19 years
-2.1 (0.2)
nc. v 31, 201
,I
t
Registered for 20+ yearsce
-2.3 (0.3)
n
ugus
Allia
grity ived on A
te
ic In
ch
Alabama
Publ 6142 ar
in
-5.0 (0.4)
5-1
cited o. 1Registered for 0-1 year
N
Registered for 1-2 years
-2.1 (0.8)
Registered for 3-4 years

-2.2 (0.5)

-3.3 (0.2)
-1.6 (0.2)
-1.4 (0.2)

-3.5 (0.3)
-3.4 (0.6)
-2.4 (0.4)

Registered for 5-9 years

-1.3 (0.3)

-1.7 (0.2)

Registered for 10-19 years

-1.1 (0.3)

-0.8 (0.2)

Registered for 20+ years

-1.6 (0.3)

-0.8 (0.2)

Registered for 0-1 year

-13.4 (0.4)

-11.1 (0.4)

Registered for 1-2 years

-5.1 (0.8)

-5.8 (0.7)

Registered for 3-4 years

-4.3 (0.6)

-4.3 (0.5)

Registered for 5-9 years

-2.8 (0.3)

-2.9 (0.3)

Registered for 10-19 years

-1.8 (0.3)

-1.4 (0.2)

Registered for 20+ years

-1.4 (0.3)

-0.3 (0.3)

Registered for 0-1 year

-8.8 (0.7)

-6.3 (0.6)

Registered for 1-2 years

-0.5 (1.0)

-1.0 (0.9)

Registered for 3-4 years

-0.9 (0.7)

-0.6 (0.7)

Registered for 5-9 years

-1.0 (0.4)

-1.1 (0.4)

Arkansas

Delaware

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Appendix VI: Voter Turnout Analysis Methods,
Data Sources, and Additional Results

Impact estimate, %
(margin of error) - Kansas

Impact estimate, %
(margin of error) Tennessee

Registered for 10-19 years

-0.7 (0.4)

0 (0.3)

Registered for 20+ years

-1.0 (0.4)

-0.2 (0.3)

Registered for 0-1 year

-4.0 (0.5)

-0.7 (0.5)

Registered for 1-2 years

-9.2 (1.0)

-8.8 (0.9)

Registered for 3-4 years

-8.2 (0.6)

-7.2 (0.5)

Registered for 5-9 years

-7.0 (0.3)

-7.0 (0.3)

Registered for 10-19 years

-6.4 (0.4)

-5.9 (0.3)

Registered for 20+ years

-7.9 (0.4)

-6.4 (0.4)

Maine

cson
of Tu (0.3)
Registered for 0-1 year
-7.9
. City
6
nc. v 31, 201-3.5 (0.7)
Registered for 1-2 years ce, I
t
gus
llian
Registered for y Ayears on Au
-3.1 (0.5)
grit 3-4 ived
e
c Int for rchyears
i
Registered
5-9
-1.9 (0.2)
Publ 6142 a
d in 1Registered for 10-19 year
1
-1.4 (0.2)
5cite
No. Registered for 20+ years
-1.5 (0.3)
Alabama, Arkansas pooled

-5.9 (0.3)
-4.6 (0.5)
-3.2 (0.4)
-2.2 (0.2)
-1.0 (0.2)
-0.8 (0.2)

Delaware, Maine pooled
Registered for 0-1 year

-6.3 (0.5)

-4.1 (0.4)

Registered for 1-2 years

-5.4 (0.8)

-5.3 (0.7)

Registered for 3-4 years

-6.4 (0.5)

-5.6 (0.4)

Registered for 5-9 years

-5.5 (0.3)

-5.2 (0.2)

Registered for 10-19 years

-4.0 (0.3)

-2.9 (0.3)

Registered for 20+ years

-4.6 (0.3)

-3.3 (0.3)

Source: GAO analysis of voter registration and history databases (commercially enhanced). | GAO-14-634

Note: Entries are difference-inerror in parentheses (e.g., +/- 0.3 percentage points). Estimates include registrants who have been
dropped from the voter files prior to April 2014.

Lastly, we found that in both Kansas and Tennessee, as registrants’ age
increased, the effects of changes in voter ID laws had decreasing effects
on turnout (see Table 19). Pooling all comparison groups, turnout among
18 year-old registrants as of November 2008, declined by 9.0 percentage
points in Kansas and 4.1 percentage points in Tennessee between the
2008 and 2012 general elections, compared to reductions of 1.9

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Appendix VI: Voter Turnout Analysis Methods,
Data Sources, and Additional Results

percentage points and 2.8 percentage points among registrants between
the ages of 44 and 53. The same decline among registrants between the
ages of 19 and 23 was 5.5 percentage points in Kansas and 4.0
percentage points in Tennessee. Our analysis suggests that these
differences were attributable to changes in voter ID laws in Kansas and
Tennessee. This interaction persisted when using each comparison group
or state except those including Maine.

Table 19: Effects of Changes in Voter ID Laws on 2012 Registered Voter Turnout in
Kansas and Tennessee, by Age in 2008, Using Voter Registration and History
Databases
Impact estimate, %
(margin of error) son
cKansas

of Tu
. City 2016
nc. v
18
-9.0 (0.9)
ce, I gust 31,
lian
l
19-23
-5.5 (0.5)
n Au
rity A
nteg rchived o
24-33
-2.7 (0.3)
blic I
a
-2.7 (0.3)
in Pu 34-43 142
5-16
cited o. 144-53
-1.9 (0.2)
N
All comparison states

Impact estimate, %
(margin of error) Tennessee
-4.1 (0.7)
-4.0 (0.4)
-5.1 (0.2)
-3.7 (0.2)
-2.8 (0.2)

54-63

-1.3 (0.2)

-2.0 (0.2)

64-73

-0.8 (0.3)

-1.6 (0.3)

74+

-0.1 (0.4)

-1.7 (0.4)

18

-6.6 (1.0)

-2.3 (0.8)

19-23

-4.1 (0.6)

-3.2 (0.4)

24-33

-0.8 (0.4)

-3.9 (0.3)

34-43

-1.0 (0.3)

-2.5 (0.3)

44-53

-0.3 (0.3)

-1.6 (0.2)

54-63

0.2 (0.3)

-0.8 (0.2)

64-73

0.7 (0.3)

-0.4 (0.3)

74+

1.1 (0.5)

-0.4 (0.5)

-16.2 (1.1)

-10.8 (0.9)

19-23

-9.4 (0.7)

-6.9 (0.6)

24-33

-3.3 (0.4)

-5.0 (0.4)

Alabama

Arkansas
18

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Appendix VI: Voter Turnout Analysis Methods,
Data Sources, and Additional Results

Impact estimate, %
(margin of error) Kansas

Impact estimate, %
(margin of error) Tennessee

34-43

-2.4 (0.4)

-3.4 (0.3)

44-53

-1.6 (0.3)

-2.5 (0.3)

54-63

-1.1 (0.3)

-1.8 (0.3)

64-73

-0.1 (0.4)

-1.3 (0.3)

2.5 (0.5)

0.6 (0.5)

-12.6 (1.6)

-6.4 (1.5)

19-23

-6.3 (0.9)

-4.1 (0.8)

24-33

-0.8 (0.6)

-2.9 (0.5)

34-43

-1.0 (0.5)

-1.9 (0.5)

74+
Delaware
18

cson
44-53
of Tu-0.5 (0.4)
54-63
. City
6-0.8 (0.4)
nc. v 31, 201 -1.5 (0.5)
,I
e
64-73
gust
llianc
ity A d on Au
74+
-2.0 (0.8)
r
nteg
ve
blic I 42 archi
in Pu -161
5
ited o. 1Maine
c
N
18
-3.6 (1.5)

-1.5 (0.4)
-1.3 (0.4)
-2.2 (0.5)
-3.4 (0.8)

3.3 (1.3)

19-23

-3.3 (0.8)

-1.5 (0.7)

24-33

-6.0 (0.5)

-8.1 (0.5)

34-43

-6.3 (0.4)

-7.4 (0.4)

44-53

-5.4 (0.4)

-5.7 (0.3)

54-63

-4.8 (0.3)

-5.8 (0.3)

64-73

-4.7 (0.4)

-5.7 (0.4)

74+

-4.8 (0.6)

-5.9 (0.6)

Alabama, Arkansas pooled
18

-9.5 (0.9)

-4.7 (0.7)

19-23

-5.8 (0.5)

-4.4 (0.4)

24-33

-1.7 (0.4)

-4.4 (0.3)

34-43

-1.5 (0.3)

-2.8 (0.2)

44-53

-0.7 (0.3)

-1.9 (0.2)

54-63

-0.3 (0.2)

-1.2 (0.2)

64-73

0.4 (0.3)

-0.6 (0.3)

74+

1.5 (0.4)

-0.1 (0.4)

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Appendix VI: Voter Turnout Analysis Methods,
Data Sources, and Additional Results

Impact estimate, %
(margin of error) Kansas

Impact estimate, %
(margin of error) Tennessee

18

-7.1 (1.2)

-2.0 (1.1)

19-23

-4.6 (0.7)

-3.2 (0.5)

24-33

-4.4 (0.4)

-6.2 (0.4)

34-43

-4.7 (0.4)

-5.0 (0.3)

44-53

-3.9 (0.3)

-4.3 (0.3)

54-63

-3.4 (0.3)

-3.8 (0.3)

Delaware, Maine pooled

64-73

-3.4 (0.4)

-4.2 (0.3)

74+

-3.8 (0.6)

-5.3 (0.5)

Source: GAO analysis of voter registration and history databases (commercially enhanced). | GAO-14-634

Note: Entries are difference-in-difference estimates
error in parentheses (e.g., +/- 0.7 percentage points). Estimates exclude registrants who have been
dropped from the voter file prior to April 2014.

cson
of Tu
. City
6
nc. v 31, 201
ce, I gust
n
u
Allia
grity iv results A
We replicated the ed on of our aggregate analysis of voter registration
Voter Registration and
nte rch
I
blic historya
and
databases by analyzing a probability sample of records from
History Databases –
in Pu these 142 at the registrant level. 38 These data allowed us to check the
d
16 files
cite
Registrant-Level Analysis No. 15consistency of our results across levels of analysis and statistical

methods. In addition, the sample allowed us to more easily adjust for the
possibility of correlated residual variation among registrants living in the
same states, as we discuss above. Due to smaller sample sizes, we did
not attempt to estimate effects separately among subpopulations.
The sample consisted of 60,000 records per state, producing a total
sample size of 360,000. We selected registrants using an unequal
probability stratified sample design. We defined the strata as the crossclassification of state, race, age, and the year of registration. Within each
state, we allocated sample to strata proportionally with respect to their
distribution in the population. Because the population size varied across
states, this allocation produced unequal selection probabilities across
states. As a result, we constructed sampling weights equal to the inverse
of the sampling probabilities, and applied these weights in all analyses.
We assessed the reliability of the data by comparing the distributions of

38

As discussed above, the terms of our subscription constrained our ability to analyze the
complete commercial voter registration and history files at the registrant level.

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Appendix VI: Voter Turnout Analysis Methods,
Data Sources, and Additional Results

key variables, such as the strata, race, and age, in the sample and in the
population, and found no substantial differences.
To replicate our aggregate results, we estimated the difference-indifference parameter using linear probability regression models fit to the
registrant-level sample. Specifically, we estimated three versions of
equation 5 above:
E(Yit | Dit, Tt, Xit

0

+

1Dit

+

2Tt

+

Dit * Tt

(Model 1)

E(Yit | Dit, Tt, Xit

0

+

1Dit

+

2Tt

+

Dit * Tt + Xit

(Model 2)

E(Yit | Dit, Tt, Xit

0

+

1Dit

+

2Tt

+

Dit * Tt + Xit

+ Tt *Xit

(Model 3)

The covariates in Xit included age, length ofcson
registration, party
f Tu
registration, race, and sex. The. specification consisted of a series of
ity o 6
v C
indicators for each level, of each variable, in order to allow flexibly nonInc. t 31, 201
ce
llia with turnout. We coded Yit as 1 if the registrant
linear relationships n
ugus
ity Ain year nand 0 otherwise. In model three, we specified
ot A
gr
te
reported voting ived
ic In
ch
interactions r
Publ 6142 abetween time and the covariates, in order to allow for unique
in
trends
cited o. 15-1 (but not unique effect estimates) within different subgroups of
N registrants. We estimated the parameters’ standard errors using
heteroskedasticity-robust or, when we analyzed at least three states,
cluster-robust methods assuming state and state-county clusters. These
methods adjust for the hereroskedasticity implied by a linear probability
model, given that Yit is binary. In addition, the methods adjust for
potentially non-independent observations within states, due to
unobserved contextual covariates (such as local campaign mobilization).
Since turnout may be correlated among registrants living in the same
counties, due to a shared set of electoral offices and ballot questions (for
example), we also applied adjustments using state-county clusters.
Dit, Tt, Xit) are guaranteed to lie in the unit interval,
Estimates of Pr(Yit
because all of the covariates are discrete.
We estimated the models among the three subpopulations of registrants
we analyzed using aggregate data. First, we excluded registrants living in
U.S. House districts that we found to experience some change in
electoral competition between 2008 and 2012. Second, we excluded
registrants who were registered in the analysis states on or before
Election Day 2008 but had since been dropped from the files. Third, we
excluded registrants with imputed racial and/or age data. When these
data are missing from state voter registration and history files, Catalist

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Appendix VI: Voter Turnout Analysis Methods,
Data Sources, and Additional Results

imputes them using proprietary methods (as discussed above) or
matches data from commercial sources. We excluded these data from
one version of our analysis, in order to control for the possibility that
measurement or imputation error affected our results. Excluding imputed
data also provides more accurate parameter variance estimates, since
these data have additional imputation error that is not propagated when
analyzing the estimates as if they were ordinary observations. 39
Table 20 reports difference-in-difference impact estimates using these
various approaches (estimates of in models 1 through 3). Although our
estimates using aggregate and micro data are not exactly equivalent, they
support broadly similar conclusions about the effects of changes in ID
laws in Kansas and Tennessee on turnout. We estimate that reductions in
turnout by 3.6 percentage points in Kansas and 3.1 percentage points in
Tennessee are attributable to ID law changes onthose states, using all
cs in
comparison states, adjusting for clustered u
of T sampling within states,
. City
including registrants dropped from the 2016and applying the more
nc. v 31, files,
I
demanding control nce,
specification of model 3. By comparison, our
gust
Allia on Aanalysis produced estimates of -3.5 and -2.9
ty
inonparametric u
aggregate,
r
ed
nteg
percentage rchiv
blic I 42 apoints for Kansas and Tennessee, respectively (see table 16).
Pu
in
Our 61
cited o. 15-1regression impact estimates are not highly sensitive to the choice of
N comparison state, except that the estimates are somewhat higher using
comparison groups consisting of Maine alone or pooling Maine and
Delaware. Similarly, most of the impact estimates remain in the range of
-2 to -5 percentage points, regardless of whether we exclude registrants
who were dropped from the voter files, had imputed race and/or age data,
or lived in U.S. House districts that experienced some change in
competition. In sum, our analysis of the Catalist voter registration and
history files produces similar conclusions using either the aggregate
methods described above or the regression methods described here.
Our estimates using micro data have more uncertainty than our estimates
using complete voter files—an expected consequence of probability
sampling. Without adjusting for residual correlations within states, the 95
percent margins of error in table 20 can be about 7 to 8 times larger than
the margins of error for the aggregate analysis reported in table 16.
Adjusting for clustered sampling within states increases the margins of

39

Roderick J. A. Little and Donald B. Rubin, Statistical Analysis with Missing Data, 2nd ed.
(New York: John Wiley and Sons, 2002).

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Appendix VI: Voter Turnout Analysis Methods,
Data Sources, and Additional Results

error within the micro analysis by a factor of approximately 2 to 3 times.
Nevertheless, most of the micro estimates support the conclusion that
decreases in turnout in Kansas and Tennessee beyond decreases in
turnout in the comparison states were attributable to changes in the two
states’ voter ID requirements, with effects remaining significantly negative
states.
While these impact estimates are still sizable and negative, they are not
significant when using the pooled Delaware and Maine comparison group
and in several other specifications, such as those excluding registrants
living in House districts with some change in electoral competition.
However, the generally similar point estimates in the aggregate and micro
analysis, along with the fact that the micro estimates derive from a
probability sample, suggests that fitting the same models to the complete
cson
registrant-level data likely would produceTu
of significantly negative results.
. City
6
For example, consider the estimates in tables 16 and 20 for registrants
nc. v 31, 201
ce, I gu t
living in non-competitive Housesdistricts in Kansas, using all comparison
llian
u
states. egrity A these A
Comparing d on results suggests that the aggregate effect
e
nt of -2.9 ipercentage points would be negative and marginally
v
estimate
blic I 42 arch
1
in Pu significant at
6
cited o. 15-1
N +/- 3.0 percentage points from table 20.
Table 20: Effects of Changes in Voter ID Requirements on 2012 Registered Voter Turnout in Kansas and Tennessee, Using
Registrant-Level Sample from Voter Registration and History Databases

Comparison State

Model Special adjustment

Impact estimate, %
(margin of error)Kansas

Impact estimate, %
(margin of error) Tennessee

Alabama

1 None

-2.3 (0.8)

-1.4 (0.8)

Alabama

2 None

-2.3 (0.7)

-1.4 (0.8)

Alabama

3 None

-2.1 (0.8)

-1.8 (0.8)

Arkansas

1 None

-4.2 (0.8)

-3.4 (0.8)

Arkansas

2 None

-4.2 (0.7)

-3.4 (0.8)

Arkansas

3 None

-4.4 (0.8)

-3.7 (0.8)

Delaware

1 None

-3.8 (0.8)

-2.9 (0.8)

Delaware

2 None

-3.8 (0.8)

-2.9 (0.8)

Delaware

3 None

-3.2 (0.8)

-2.5 (0.8)

Maine

1 None

-7.3 (0.8)

-6.5 (0.8)

Maine

2 None

-7.3 (0.8)

-6.5 (0.8)

Maine

3 None

-6.5 (0.8)

-6.3 (0.8)

Alabama, Arkansas pooled

1 State clusters

-3.0 (3.4)

-2.1 (3.4)

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Appendix VI: Voter Turnout Analysis Methods,
Data Sources, and Additional Results

Comparison State

Model Special adjustment

Impact estimate, %
(margin of error)Kansas

Impact estimate, %
(margin of error) Tennessee

Alabama, Arkansas pooled

2 State clusters

-3.0 (3.4)

-2.1 (3.4)

Alabama, Arkansas pooled

3 State clusters

-2.9 (4.1)

-2.5 (3.3)

Delaware, Maine pooled

1 State clusters

-6.0 (6.2)

-5.2 (6.2)

Delaware, Maine pooled

2 State clusters

-6.0 (6.2)

-5.2 (6.2)

Delaware, Maine pooled

3 State clusters

-5.4 (5.3)

-4.9 (6.1)

All comparison states pooled

1 State clusters

-3.7 (2.8)

-2.9 (2.8)

All comparison states pooled

2 State clusters

-3.7 (2.8)

-2.9 (2.8)

All comparison states pooled

3 State clusters

-3.6 (2.8)

-3.1 (2.4)

All comparison states pooled

1 State-county clusters

-3.6 (0.9)

-2.9 (1.4)

All comparison states pooled

2 State-county clusters

-3.6 (0.9)

-2.9 (1.4)

All comparison states pooled

3 State-county clusters

-3.1 (1.3)

All comparison states pooled

1 State clusters, no competitive House

-2.0 (1.9)

-3.6 (0.8)
on
Tucs-4.4 (1.9)
of
ity
All comparison states pooled
2 State clusters, no competitive House c. v. C
16 -4.4 (1.9)
n
1, 20
,I
All comparison states pooled
3 State clusters, no competitivece
House gust 3
-3.6 (3.0)
lian
ty Al d on Au
idropped registrants
All comparison states pooled
1 State clusters, gr
-2.5 (2.9)
te no
v
ic In no droppede
blclusters, 2 archi registrants
All comparison states pooled
2 Pu
State
-2.5 (2.9)
614
d in 1 clusters, no dropped registrants
All comparison states pooled cite 3 State5-1
-2.5 (3.1)
No.

-2.0 (1.9)
-2.1 (1.7)
-3.1 (2.9)
-3.1 (2.9)
-3.2 (2.6)

All comparison states pooled

1 State clusters, no imputed race and/or age

-3.4 (2.4)

NA

All comparison states pooled

2 State clusters, no imputed race and/or age

-3.4 (2.4)

NA

All comparison states pooled

3 State clusters, no imputed race and/or age

-3.5 (2.6)

NA

Alabama

1 No imputed race and/or age

NA

-1.9 (0.9)

Alabama

2 No imputed race and/or age

NA

-1.9 (0.9)

Alabama

3 No imputed race and/or age

NA

-2.7 (0.9)

Source: GAO analysis of state voter registration and history databases (commercially enhanced) | GAO-14-634

Note: Entries are difference-inerror in parentheses (e.g., +/- 0.8 percentage points).

Current Population Survey

The Current Population Survey (CPS) Voting and Registration
Supplement served as our final source of data. Within several weeks after
the 2008 and 2012 federal general elections, the U.S. Census Bureau
asked a nationwide sample of adults a battery of questions about their
registered voter status and whether they voted in the election. The CPS
serves as a check on official data sources, because it measures turnout

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Appendix VI: Voter Turnout Analysis Methods,
Data Sources, and Additional Results

using the responses of survey respondents. Although self-reported
turnout is often biased upward, compared to official turnout rates, 40 the
CPS provides an opportunity to assess the sensitivity of our impact
estimates to a different source of measurement error. In addition, the
CPS provides a different set of covariates than are available in the
Catalist version of voter registration and history databases.
We pooled the 2008 and 2012 CPS data in order to estimate the effect of
changes in voter ID laws, if any, for the population of registered voters in
Kansas and Tennessee. We limited the sample to adult respondents
reporting that they were citizens of the United States and registered to
vote, and weighted all estimates using the person-level weights provided
by the CPS. Due to sample size limitations, we could not estimate
separate impact estimates for subpopulations using the CPS.

cson

f
We fit the same type of linear probability Tu
ity o regression models to the CPS
data as we fit to the sample ofvCatalist2016 registration and history data,
. . C , voter
c
31
e, In
except that the data consisteduoft repeated cross-sections:
lianc
g s
l

u
ty A
on A
te ri
nD gT ,rXhived + D +
E(Y
t
0
1 it
blic itI | it, a c it
in Pu -16142
d
cite
15
No. E(Yit | Dit, Tt, Xit
0 + 1Dit +
E(Yit | Dit, Tt, Xit

0

+

1Dit

+

2Tt

+

Dit * Tt

(Model 1)

2Tt

+

Dit * Tt + Xit

(Model 2)

2Tt

+

Dit * Tt + Xit

+ Tt *Xit

(Model 3)

The covariates in Xit included age, education, employment status, family
income, marital status, race, residential mobility, and sex. The
specification consisted of a series of indicators for each level of each
variable, in order to allow flexibly non-linear relationships with turnout. We
coded Yit as 1 if the respondent reported voting in year t and 0 otherwise,
treating “don’t know” responses as missing data. In model 3, we specified
interactions between time and the covariates, in order to allow for unique
trends (but not unique effects) within different subgroups of registrants.
We estimated the parameters’ standard errors using heteroskedasticityrobust or cluster-robust methods, assuming state or state-county clusters,
when we analyzed at least three states.

40

Stephen Ansolabehere and Eitan Hersh, “Validation: What Big Data Reveal about
Survey Misreporting and the Real Electorate.” Political Analysis 20: 437-459.

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Appendix VI: Voter Turnout Analysis Methods,
Data Sources, and Additional Results

We estimated the models above using various combinations of
comparison states. As with our analysis of official turnout data, this
approach tests the robustness of our results to plausible alternative
choices of comparison states and to specific imbalances in state-level
factors we discuss in appendix V, such as ballot questions and campaign
competition. However, we included an additional control group in our
analysis of CPS data: registrants living in all states other than the
treatment states (Kansas and Tennessee) and our standard comparison
states (Alabama, Arkansas, Delaware, and Maine). This alternative
control group assesses whether our results hold, even using all other
possible comparison states that we did not choose for analysis in
appendix V. In addition, the larger number of states included in the
analysis (45) increases the number of observed clusters and better
satisfies the asymptotic assumptions of cluster-robust variance estimation
methods.
son

f Tuc
ity o 6
The CPS data support similar v. C
nc. conclusions about the effect of changes in
, 201
ce, I gust from
voter ID laws on lturnout as made 31 the official data (see table 21).
l ian
u
Across egrity A assumptions we made when analyzing the CPS data, the
all of the d on A
nt effectivechanges in Kansas’s ID law ranged from -1.2
estimated
blic I 42 arch of
in Pu percentage points to -5.6 percentage points, with the exception of fitting
d
161
cite
. 15- 3 to respondents living in Alabama. The same effect estimates for
No model
Tennessee ranged from -1.4 to -5.0 percentage points (again excluding
model 3 for Alabama). Estimates using a single comparison state had
relatively large margins of error, in part due to these groups’ smaller
populations and sample sizes. When pooling data across respondents in
all comparison states, however, our estimates are distinguishable from
we made using much larger quantities of official data, suggesting that
declines in turnouts between the 2008 and 2012 general elections in
Kansas and Tennessee are attributable to changes in those states’ voter
ID laws.
Comparing results across models and the use of a nationwide
comparison group further supports the validity of our design. The lack of
substantial variation between model 1, which estimates only the raw
difference-in-difference, and models 2 and 3, which condition on
demographic covariates and their interactions with time, is consistent with
a strong design. If unobserved campaign or ballot question mobilization
changed between elections, and these efforts disproportionately affected
turnout among certain demographic groups of registrants, we would
expect controls for the interaction between time and the covariates to
affect the impact estimates. The stability of the estimates makes this

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Appendix VI: Voter Turnout Analysis Methods,
Data Sources, and Additional Results

scenario less likely. Similarly, the consistency in the estimates between
our comparison groups and a nationwide alternative suggests that our
specific choice of analysis states does not strongly affect the results.
Table 21: Effects of ID Requirements on 2012 Registered Voter Turnout in Kansas and Tennessee, Using Current Population
Survey

Model

Impact estimate, %
(margin of error) Kansas

Alabama

1

-2.3 (4.6)

-1.7 (5.0)

Alabama

2

-2.0 (4.7)

-1.4 (5.0)

Alabama

3

0.4 (5.0)

-0.6 (5.1)

Arkansas

1

-3.5 (5.0)

-2.8 (5.3)

Arkansas

2

-3.7 (5.0)

-3.6 (5.3)

3

-3.3 f(5.1)
o Tu

-3.8 (5.4)

Comparison state

Arkansas
Delaware
Delaware
Delaware
Maine
Maine
Maine

Impact estimate, %
(margin of error) Tennessee

cson
. City 016
1
-5.6
nc. v 31, 2(3.8)
ce, I gust -5.3 (3.9)
2
lian
u
t Al
gri3y ived on A
-5.3 (4.1)
nte rch
blic I 42 a
-4.7 (3.7)
1 1
in Pu
ited o. 15-16
2
-3.6 (3.6)
c
N

-5.0 (4.2)
-4.1 (4.3)
-4.6 (4.3)
-4.1 (4.1)
-3.1 (4.1)

3

-2.3 (3.8)

-3.2 (4.4)

Alabama, Arkansas pooled

1

-2.7 (2.0)

-2.1 (2.0)

Alabama, Arkansas pooled

2

-2.5 (3.0)

-2.2 (3.8)

Alabama, Arkansas pooled

3

-1.2 (7.8)

-1.7 (6.4)

Delaware, Maine pooled

1

-5.1 (1.6)

-4.4 (1.6)

Delaware, Maine pooled

2

-4.3 (3.3)

-3.4 (2.2)

Delaware, Maine pooled

3

-3.5 (5.4)

-3.6 (3.1)

All comparison states pooled

1

-3.2 (1.7)

-2.6 (1.7)

All comparison states pooled

2

-2.9 (1.9)

-2.5 (2.0)

All comparison states pooled

3

-1.9 (3.5)

-2.2 (2.8)

Nationwide, excluding comparison states

1

-2.7 (0.6)

-2.1 (0.6)

Nationwide, excluding comparison states

2

-2.8 (0.6)

-2.3 (0.6)

Nationwide, excluding comparison states

3

-2.7 (0.8)

-2.2 (0.7)

Source: GAO analysis of 2008 and 2012 Current Population Survey, Voting and Registration Supplement. | GAO-14-634

Note: Entries are difference-inerror in parentheses (e.g., +/- 4.6 percentage points).

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Appendix VII: Additional Provisional Ballot
Analysis

Appendix VII: Additional Provisional Ballot
Analysis
We analyzed data from the EAVS to determine how provisional ballot
rates changed over time in our treatment states (Kansas and Tennessee)
and comparison states (Alabama, Arkansas, Delaware, and Maine) using
data obtained about all jurisdictions in those states (e.g., to include all
jurisdictions from which data were obtained in the EAVS in either 2008 or
2012). We conducted this additional analysis to determine if missing data
affected the results of the analysis we discussed earlier in the report
regarding changes in provisional ballot rates over time in which we
excluded jurisdictions that did not report data for both the 2008 and 2012
EAVS. In our second analysis, as shown in tables 22 and 23, we obtained
results similar to those in our first analysis, indicating that our exclusion of
jurisdictions with missing data did not affect our conclusion that
provisional ballot usage increased in Kansas and Tennessee from the
2008 to the 2012 general election relative to ballot usage in comparison
states.
son

f Tuc
ity o 6
v. CUsage between 2008 and 2012 General
1
Table 22: Change in Provisional .
, Inc Ballot 31, 20
t
ce Comparison States
n
Elections, in Treatment and ugus
Allia
grity ived on A
te
Change in
ic In
ch
Publ 6142 ar
Percentage of
Percentage of
provisional ballot
in
total ballots that total ballots that
usage between
cited o. 15-1
N
were provisional were provisional
2008 and 2012
State

in 2008

in 2012

a

general elections

Kansas

3.18

3.48

0.30

Tennessee

0.17

0.29

0.12

c

-0.02

Alabama
Arkansas

b

0.34

d

0.20

0.32

e

0.04

0.11

0.01

g

0.00

0.24

Delaware

0.09

Maine

0.04

Alabama/Arkansas pooled

0.29

0.29

0.01

Delaware/Maine pooled

0.06

0.07

0.01

All comparison states
pooled

0.23

0.23

0.00

f

0.04

Source: GAO analysis of U.S. Election Assistance Commission’s Election Administration and Voting Survey (EAVS) 2008 and 2012
data from selected states. | GAO-14-634
a

The change in provisional ballot usage between 2008 and 2012 may not equal the percent of total
ballots that were provisional in 2012 minus the percent of total ballots that were provisional in 2008
due to rounding in subtraction.
b

In 2008, 7.46 percent of jurisdictions in Alabama did not report data on the total number of
provisional ballots cast.

c

In 2012, 22.39 percent of jurisdictions in Alabama did not report data on the total number of
provisional ballots cast.

d

In 2008, 10.67 percent of jurisdictions in Arkansas did not report data on the total number of
provisional ballots cast.

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Appendix VII: Additional Provisional Ballot
Analysis

e

In 2012, 2.67 percent of jurisdictions in Arkansas did not report data on the total number of
provisional ballots cast.
f

In 2008, 28.86 percent of jurisdictions in Maine did not report data on the total number of provisional
ballots cast.
g

In 2012, 0.20 percent of jurisdictions in Maine did not report data on the total number of provisional
ballots cast.

Table 23: Comparison of Change in Provisional Ballot Usage between 2008 and
2012 General Elections in Treatment and Comparison State Groups
State

Kansas (%)

Tennessee (%)

Alabama/Arkansas pooled

0.29 (0.047)

0.11 (0.012)

Delaware/Maine pooled

0.29 (0.046)

0.11 (0.011)

All comparison states pooled

0.30 (0.046)

0.11 (0.010)

cson
ofofTu (e.g., +/- 0.047 percentage points).
Notes: Entries in parentheses are 95 percentCity
margins error
16
. v.
, Inc st 31, 20
ce
n
ugu
Allia
grity ived on A
e
These tresultscinclude data provided by local election jurisdictions in
h
ic In
Publ 6142 ar to the EAVS in either 2008, 2012, or in both years. All
in selected states
cited o. 15-1
N jurisdictions in Delaware, Kansas, and Tennessee provided data to the

Source: GAO analysis of U.S. Election Assistance Commission’s Election Administration and Voting Survey (EAVS) 2008 and 2012
data from selected states. | GAO-14-634

EAVS in each year, but data were missing for some jurisdictions in either
year in the other states. Between 0.2 and 28.9 percent of the jurisdictions
in Alabama, Arkansas, and Maine did not provide data to the EAVS for 1
or both years (see notes for table 22).
Analyzing provisional ballot rates using data provided by all jurisdictions
responding to the EAVS in either 2008 or 2012 could, in principle,
produce biased results, given that data were missing for some
jurisdictions. However, we have no basis to conclude that the missing
data in this situation cause substantial bias. With the exception of
Alabama in 2012 and Maine in 2008, the rate of missing data was less
than 11 percent. Since the potential bias caused by missing data is
proportional to the amount of data that are missing, the relatively low
rates of missing data in our analysis has a similarly low risk of introducing
bias. This is true even if the jurisdictions that did not report data had
substantially different provisional ballot rates than those that did. 1

1

Roderick D. Little and Donald B. Rubin, Statistical Analysis with Missing Data, 2nd ed.
(Hoboken, New Jersey: John Wiley and Sons, 2002), 41-43.

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Appendix VII: Additional Provisional Ballot
Analysis

Consistent with this conclusion, our estimates of change over time are
similar across states, regardless of their rates of missing data. The larger
increase in provisional ballot rates among voters in Kansas and
Tennessee, compared with the change among voters in the other states,
is consistent with the results of our turnout analysis earlier in this report.
Finally, we obtained similar results when we conducted the analysis using
only jurisdictions that responded to the EAVS in both 2008 and 2012.
Together, this evidence suggests that the provisional ballot rate is not
highly sensitive to which jurisdictions chose to report data in a particular
year and supports our assumption that the missing data are not
consequential.

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Appendix VIII: Selected Federal Databases and
the Types of Information They Contain

Appendix VIII: Selected Federal Databases
and the Types of Information They Contain
Table 24 provides a description of each of the four databases we
identified that contain information on possible federal in-person voter
fraud investigations, prosecutions, and convictions.
Table 24: Selected Federal Databases and the Types of Information They Contain
Name of
database

Federal agency that manages
the database

Legal Information
Office Network
System (LIONS)

U.S. Department of Justice
Executive Office for United States
Attorneys

Automated Case
U.S. Department of Justice
Tracking System II Criminal Division
(ACTS II)

Integrated
Database

Oracle database

Description
Used to compile, maintain, and track
information relating to defendants,
crimes, criminal charges, court
events, and witnesses.

ianc

United States Sentencing
Commission

Investigations, prosecutions,
convictions

Tracks all cases and matters that are Investigations, prosecutions,
the responsibility of the Criminal
convictions
Division’s litigating sections. It
provides the Criminal Division's
cson
managers with reports and statistics T
of u
ty
for determining attorneyv. Ci
workloads 16
0
nc.
and productivity. I
31, 2
e,

ust

All
Contains federal courtg
n Au data such as
grity iviolations at the time of case
nte statute ved o
blic I
arch
filing and case termination that are
in Pu -16142routinely reported to the
15
Administrative Office of the U.S.
No.
Courts.

Federal Judicial Center

cited

Types of information included in
the data (investigations,
prosecutions, convictions)

Prosecutions, convictions

Contains data extracted and
Convictions
analyzed from sentencing documents
submitted by federal courts to the
United States Sentencing
Commission.

Source: GAO analysis of each database’s associated codebooks and interviews with agency officials. | GAO-14-634

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Appendix IX: Comments from the
Arkansas Secretary of State’s Office

Appendix IX: Comments from the
Arkansas Secretary of State’s Office

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Appendix IX: Comments from the
Arkansas Secretary of State’s Office

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Appendix X: Comments from the
Kansas Secretary of State

Appendix X: Comments from the
Kansas Secretary of State

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Appendix X: Comments from the
Kansas Secretary of State

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Appendix XI: Comments from the
Tennessee Secretary of State

Appendix XI: Comments from the
Tennessee Secretary of State

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Appendix XI: Comments from the
Tennessee Secretary of State

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Appendix XI: Comments from the
Tennessee Secretary of State

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Appendix XI: Comments from the
Tennessee Secretary of State

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Appendix XI: Comments from the
Tennessee Secretary of State

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Appendix XI: Comments from the
Tennessee Secretary of State

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Appendix XI: Comments from the
Tennessee Secretary of State

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Appendix XII: GAO Contact and Staff
Acknowledgments

Appendix XII: GAO Contact and Staff
Acknowledgments
GAO Contacts

Rebecca Gambler, [phone] or [e-mail]
Nancy Kingsbury, [phone] or [e-mail]

Staff
Acknowledgments

In addition to the contacts named above, Tom Jessor (Assistant Director),
Ben Atwater (Assistant Director), David Alexander (Assistant Director),
Colleen Candrl, Michele Fejfar (Assistant Director), Eric Hauswirth, Mitch
Karpman (Assistant Director), Lauren Kirkpatrick, Elizabeth Kowalewski,
Jean McSween, Anna Maria Ortiz (Assistant Director), Jan Montgomery,
Douglas Sloane (Assistant Director), Meghan Squires, Barbara Stolz,
Janet Temko-Blinder, and Jeff Tessin made significant contributions to
this report.

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(441117)

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