STATE OF FLORIDA et al v. UNITED STATES DEPARTMENT OF HEALTH AND HUMAN SERVICES et al

Filing 83

NOTICE Errata re Exhibits in support of 82 Defendants' Motion for Summary Judgment by TIMOTHY F GEITHNER, KATHLEEN SEBELIUS, HILDA L SOLIS, UNITED STATES DEPARTMENT OF HEALTH AND HUMAN SERVICES, UNITED STATES DEPARTMENT OF LABOR, UNITED STATES DEPARTMENT OF THE TREASURY (Attachments: # 1 Table of Exhibits, # 2 Exhibit 1, # 3 Exhibit 2, # 4 Exhibit 3, # 5 Exhibit 4, # 6 Exhibit 5, # 7 Exhibit 6, # 8 Exhibit 7, # 9 Exhibit 8, # 10 Exhibit 9, # 11 Exhibit 10, # 12 Exhibit 11, # 13 Exhibit 12, # 14 Exhibit 13, # 15 Exhibit 14, # 16 Exhibit 15, # 17 Exhibit 16, # 18 Exhibit 17, # 19 Exhibit 18, # 20 Exhibit 19, # 21 Exhibit 20, # 22 Exhibit 21, # 23 Exhibit 22, # 24 Exhibit 23, # 25 Exhibit 24, # 26 Exhibit 25, # 27 Exhibit 26, # 28 Exhibit 27, # 29 Exhibit 28, # 30 Exhibit 29, # 31 Exhibit 30, # 32 Exhibit 31, # 33 Exhibit 32, # 34 Exhibit 33, # 35 Exhibit 34, # 36 Exhibit 35, # 37 Exhibit 36, # 38 Exhibit 37, # 39 Exhibit 38, # 40 Exhibit 39, # 41 Exhibit 40, # 42 Exhibit 41, # 43 Exhibit 42, # 44 Exhibit 43) (BECKENHAUER, ERIC)

STATE OF FLORIDA et al v. UNITED STATES DEPARTMENT OF HEALTH AND HUMAN SERVICES et al

Doc. 83 Att. 9

Exhibit 8

Dockets.Justia.com

June E. O'Neill Baruch College and City University of New York Dave M. O'Neill Baruch College and City University of New York

WHO ARE THE UNINSURED?
An Analysis of America's Uninsured Population, Their Characteristics and Their Health

T

he Employment Policies Institute (EPI) is a nonprofit research organization dedicated to studying public policy issues surrounding employment growth. In particular, EPI research focuses on issues that affect entry-level

employment. Among other issues, EPI research has quantified the impact of new labor costs on job creation, explored the connection between entry-level employment and welfare reform, and analyzed the demographic distribution of mandated benefits. EPI sponsors nonpartisan research that is conducted by independent economists at major universities around the country.

Dr. June O'Neill is Wollman Distinguished Professor of Economics in the Wasserman Department of Economics and Finance and Director of the Center for the Study of Business and Government, Zicklin School of Business, Baruch College, City University of New York (CUNY). She is also a Research Associate of the National Bureau of Economic Research (NBER) and an American Enterprise Institute (AEI) Adjunct Scholar. She served as director of the Congressional Budget Office, 1995-1999, and chaired the Board of Scientific Counsellors of the National Center for Health Statistics, 2003-2007. Among her publications is a recent article written jointly with Dave O'Neill that compares differences between the U.S. and Canada in health status, health care and inequality of health outcomes. Dr. Dave O'Neill is a Senior Research Associate at the Center for the Study of Business and Government and an Adjunct Professor of Economics in the Wasserman Department of Economics and Finance, Baruch College, CUNY. Before joining the Center Dr. O'Neill had a long career as an economist in both the academic and policy sectors, working at the Nathan Kline Institute for Psychiatric Research and at private policy institutes and the federal government in Washington D.C. including the U.S. Bureau of the Census and the General Accounting Office. He has published in the fields of labor economics, health and welfare policy.

Acknowledgements
The authors are grateful to Mei Liao for excellent research assistance.

WHO ARE THE UNINSURED?
An Analysis of America's Uninsured Population, Their Characteristics and Their Health
June E. O'Neill Baruch College and City University of New York Dave M. O'Neill Baruch College and City University of New York

1090 Vermont Avenue, NW Suite 800 Washington, DC 20005

WHO ARE THE UNINSURED?
An Analysis of America's Uninsured Population, Their Characteristics and Their Health
June E. O'Neill Baruch College and City University of New York Dave M. O'Neill Baruch College and City University of New York

Table of Contents
Executive Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Estimating the Number of Involuntarily Uninsured . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Personal Characteristics by Insurance Status and their Impact . . . . . . . . . . . . . . . . . . . . . . 15 Health Resources Obtained by the Uninsured . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 Lack of Insurance and Health Outcomes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 Summary and Concluding Comments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

WHO ARE THE UNINSURED?
An Analysis of the Characteristics of Americans Without Health Insurance
Executive Summary
hen reformers talk about our healthcare system, they repeatedly cite the number of uninsured Americans as one of the primary problems in need of a solution. In 2006, the Census Bureau estimates of the uninsured reached 47 million, representing approximately 16 percent of the population. While this number has dominated nearly all healthcare policy debates, it unfortunately remains a relatively coarse measurement and provides little substantive information about the uninsured that can be used to craft effective policy solutions. For example, it is often assumed--without any quantitative evidence--that nearly all of these uninsured individuals lack coverage because they are unable to afford it. Furthermore, the lack of health insurance is often equated with a lack of healthcare, despite the fact that individuals without coverage often receive medical services from a wide variety of sources within the healthcare system. As the country moves closer to a serious debate over healthcare reform, whether these assumptions reflect reality will make a significant difference to the policy outcome. Unless we have a better understanding of the characteristics of the uninsured population, the solutions proposed may, in practice, be poorly targeted and ultimately ineffective. This study attempts to increase knowledge in the field of health policy by examining some of the characteristics of those without health insurance. The authors calculate the percentage of uninsured Americans that could likely afford health coverage. Drs. June and David O'Neill of the Baruch College, City University of New York use data from a number of surveys to determine what percentage of the nearly 47 million uninsured Americans lack health insurance because they are likely unable to afford it--classifying them as "involuntarily" uninsured. They find that at least 43 percent of Americans in the 18­64 year-old age group have incomes at or above 2.5 times the poverty line, indicating they likely have the means to obtain healthcare coverage and thus may be classified as "voluntarily" uninsured. To further examine this classification, the authors then compare the characteristics of the voluntarily and involuntarily uninsured with the characteristics of the privately insured population. The authors find the most striking differences when comparing the involuntarily uninsured to the privately insured. For example, roughly one-third
Who Are The Uninsured? Employment Policies Institute

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3

of the involuntarily uninsured are high school dropouts, compared to approximately 7 percent of the privately insured population. A disproportionately large percentage of the involuntarily uninsured are young, a third are immigrants, close to half are single without children, and close to 40 percent did not work during the year. Indeed, many of these demographic differences--which are not necessarily shared by the voluntarily uninsured--may contribute to the differences in health coverage. A productive conversation about health policy must also separate the concept of a lack of health coverage from a lack of healthcare. Individuals without adequate health insurance still receive medical care from a variety of sources. The authors look at the utilization of certain services--in particular, screening for cancer--and find that the uninsured may indeed receive less care than those who are privately insured. However, when compared with screening rates for Canadians (who largely receive healthcare coverage through a nationalized, single-payer system), the uninsured in the United States actually compare favorably. To further determine whether lack of coverage means lack of service, the authors also report estimates of the dollar amounts of healthcare resources obtained by the uninsured in total. The estimates indicate that on a per-capita basis, the uninsured receive about 40 percent of the amount of health resources received by those with insurance. Interestingly, the involuntarily uninsured receive more than half of the total and the voluntarily uninsured less, because "safety net" providers generally distribute resources to lower income people. After determining the characteristics of the uninsured and discovering that being uninsured does not necessarily mean an individual has no access to health services, the authors turn to the question of mortality. A lack of care is particularly troubling if it leads to differences in mortality based on insurance status. Using data from

the Health and Retirement Survey, the authors estimate differences in mortality rates for individuals based on whether they are privately insured, voluntarily uninsured, or involuntarily uninsured. Overall, they find that a lack of health insurance is not likely to be the major factor causing higher mortality rates among the uninsured. The uninsured--particularly the involuntarily uninsured--have multiple disadvantages that are associated with poor health. Designing effective health policy requires full information about the composition of the uninsured, including an assessment about whether long-held assumptions are supported by evidence. This includes understanding the factors contributing to a lack of insurance and information about the true consequences of that lack of coverage, particularly the effect on the uninsured population's utilization of health services and the effect on mortality. This study shows that a large fraction of the uninsured could likely afford health coverage. In addition, it shows that the involuntarily uninsured are demonstrably different from the privately insured. Finally, the authors show that while the uninsured use fewer health services, they still receive a large amount of care, and there is little discernable difference in mortality based on insurance status. As we begin to engage in this important debate, priority should be placed on policy solutions that have the best chance of being effective. Policies that focus, at least at first, on providing coverage and services to the involuntarily uninsured--the truly at-risk--will accomplish the most and take us much further in improving the overall health of the nation.

Kristen Lopez Eastlick Senior Research Director Employment Policies Institute

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Employment Policies Institute Who Are The Uninsured?

The Involuntarily and Voluntarily Uninsured: Characteristics, Healthcare, and Health Status
Each year the Census Bureau reports its estimate of the total number of adults and children in the U.S. who lacked health insurance coverage during the previous calendar year.1 The number of Americans reported as uninsured in 2006 was 47 million, which was close to 16 percent of the U.S. population (Table 1). This number has come to have a large impact on the debate over healthcare reform in the United States. However, there is a great deal of confusion about the significance of the uninsured numbers. Many people believe that the number of uninsured signifies that almost 50 million Americans are without healthcare simply because they cannot afford a health insurance policy and as a consequence, suffer from poor health, and premature death.2 However this line of reasoning is based on a distorted characterization of the facts. Although it is important that we be concerned about the provision of resources to those who are too

poor to afford medical care, policy action to address the problem should be guided by informed discussion of this complex issue. More careful analysis of the statistics on the uninsured shows that many uninsured individuals and families appear to have enough disposable income to purchase health insurance, yet choose not to do so, and instead self-insure. We call this group the "voluntarily uninsured" and find that they account for 43 percent of the uninsured population. The remaining group--the "involuntarily uninsured"--makes up only 57 percent of the Census count of the uninsured. A second important point is that while the uninsured receive fewer medical services than those with private insurance, they nonetheless receive significant amounts of healthcare from a variety of sources--government programs, private charitable groups, care donated by physicians and hospitals, and care paid for by out-of-pocket expenditures. Third, although the involuntarily uninsured by some estimates appear to have a significantly shorter life expectancy than those who are privately insured or voluntarily uninsured, it is difficult to establish cause and effect. We find that

TABLE 1. Number and Percent Uninsured In 2006
All Ages Ages <65 Ages 18­64 Population (000's) 296,824 260,789 186,688 Uninsured (000's) 46,995 46,453 37,792 % Uninsured 15.8 17.8 20.2

Note: The data source is the Current Population Survey (CPS) microdata files. Insurance status is reported for the prior calendar year (2006) in the March 2007 CPS.

1

The health insurance question is part of the annual March Current Population Survey (CPS). Most research has concluded that although the CPS intends to count the number of persons who were uninsured at all times during the previous year, many survey respondents instead report their insurance status at the time of the March interview. This results in a larger number of uninsured. See below for further discussion. 2 The Institute of Medicine (2003) has promulgated an estimate that lack of insurance in the United States causes 18,000 preventable deaths each year based on a study by Franks et al. (1993). Families USA, in a series of reports called "Dying for Coverage", uses the IOM estimates to show the number of people in each state who die because of lack of insurance. As we show below, the Franks result has a large margin of uncertainty. Moreover, the IOM conclusion is contravened by studies showing that the higher observed mortality of the uninsured is in large part attributable to their socioeconomic disadvantages. 5

Who Are The Uninsured? Employment Policies Institute

differences in mortality according to insurance status are to a large extent explained by factors other than health insurance coverage--such as education, socioeconomic status, and health-related habits like smoking. In this paper, we analyze data from a number of surveys to measure three aspects of the uninsured problem--the relative numbers and characteristics of those who are voluntarily and involuntarily uninsured; the amounts and types of medical services they obtain; and the size of the differential in health outcomes associated with lack of insurance. Our results have implications for a number of issues related to the formulation of policies that would extend coverage to the uninsured and to the costs of those policies. One is that it is primarily the involuntarily uninsured that would require a net addition to government spending to attain acceptable levels of health services. Moreover, because the involuntarily insured already utilize publicly funded medical resources, the cost of extending insurance coverage to them is likely to add less to public expenditures than the total cost of the coverage. Thus, our estimates of the number of uninsured who are involuntarily uninsured, and the cost of the health services they are likely to receive, are important ingredients for estimating the net cost of insurance reform--i.e., the additional amount of resources that would be required to provide medical services to those who currently lack access due to their low incomes.3 The recognition that some of the uninsured are voluntarily uninsured also informs the debate about mandating coverage for all uninsured people, as opposed to focusing only on coverage for the involuntarily uninsured. Man-

dating coverage for those who choose to self-insure and can afford it enlarges the government's role beyond what is necessary and forces an expenditure on an unwilling group. (However, one could argue that it would be reasonable to require the voluntarily uninsured to purchase low-cost catastrophic insurance in view of externalities to the public when accidents or other unexpected health emergencies lead to unusually high medical expenditures.) Finally, our findings on how the health status and health outcomes of the involuntarily uninsured compare with those of the insured have implications for the pace at which reforms should be implemented and how radical they need to be.

Estimates Of The Number Of Involuntarily Uninsured
Estimates of the involuntarily uninsured necessarily depend on a judgment about the level of family or individual income consistent with ability to pay. The concept of need, however, is not easy to determine because it can be influenced by a large number of factors, and it is difficult to assign weights to each in order to compile a single index of need.4 Like the poverty threshold, an index of ability to pay for health insurance is bound to differ with the eye of the beholder. We base our estimates of the voluntarily and involuntarily uninsured on family income expressed as a multiple of the poverty rate and choose a single level for each family type, based on the reasoning explained below. We accept some arbitrariness in exchange for simplicity, an important policy consideration. Yet we find

3

Note that we have not addressed the question of the effect that a government subsidy for the involuntarily uninsured would have on those who currently have private insurance yet have incomes that would qualify them for such a subsidy. Covering all persons who qualify by reason of income (and family size) would involve a transfer from private to public financing, but would not require a net addition to total health resources. 4 Bundorf and Pauly (2006) investigate the "affordability" of coverage based on an array of factors. Using different definitions of affordability, they find that insurance could be viewed as affordable for between one-quarter and three-quarters of the uninsured, depending on the definition selected. 6

Employment Policies Institute Who Are The Uninsured?

that our distinction between the involuntary and voluntar y groups is highly useful in analysis of health behavior and health outcomes. Despite the subjectivity involved, as one looks up and down the income distribution, there are clearly some income situations that would not cause controversy if classified as income at which health insurance is affordable. For example, a $10,000 health insurance policy would represent only 6.7 percent of the income of a married couple with no dependent children and a family income of $150,000 a year. It is likely that uninsured couples without children at such high income levels are voluntarily uninsured, as the purchase of health insurance would not require them to seriously cut back their spending on necessities such as food and housing. At the other end of the spectrum, a $10,000 insurance policy would represent 40 percent of the income of a couple with children and a family income of $25,000; a $6,000 policy would be almost a quarter of their income. Most would conclude that the uninsured in those situations are involuntarily uninsured. It becomes more of a challenge to distinguish the involuntar y from the voluntary when we consider the 23.7 million uninsured persons who are in households with incomes between $25,000 and $75,000 who make up 50.5 percent of the uninsured. In this range, it is obviously more difficult to determine a reasonable standard for "ability-to-pay"--i.e. the dollar amount of income an individual or family unit must have in order to afford a given policy premium. In the remainder of this section, we present our estimates of ability-to-pay threshold incomes and then provide our estimates of the number of involuntarily and voluntarily uninsured. We present estimates for the U.S. as a whole and for individual states. We also present estimates from different surveys and for different points in time. After presenting crosstabulations of Current Population Survey (CPS) data on

the personal characteristics of individuals by their insurance status, we use regression analysis to estimate the net effects of each of the personal characteristics--and the premium cost of health insurance--on the probability that an individual is insured.

Ability-to-Pay Thresholds
Our basic approach to determining who among the uninsured are involuntary or voluntary is to observe the proportion of individuals at various income levels who obtained coverage from private insurers or were uninsured (where income level is measured as multiples of the poverty line for each family type). We assume that the greater the proportion who obtain private coverage at a given income level, the more likely it is that those at the same income level who remain uninsured are voluntarily uninsured. Since those who obtain public insurance of some kind (such as Medicaid, Medicare, or TriCare) do not face the problem of ability to pay, including them in the analysis would obscure the relationship we are trying to measure--namely, the level of income at which it becomes too difficult to purchase insurance. We therefore exclude the publicly insured from this part of our analysis. The premise that guides our thinking is that there is an underlying distribution of individuals/family units ranked by their preferences for health insurance coverage, and this distribution depends on health status, risk aversion, and other personal characteristics. We also assume that when income rises, people at a given level of taste or preference for insurance will likely spend more on health coverage. (In other words, health insurance is what economists call a "normal good.") However, those with a relatively low taste for health insurance may not increase their purchase of insurance very much, if at all, as income rises. Thus, we can observe a small proportion of higher income individuals who remain uninsured, and they will be individuals who place the lowest value

Who Are The Uninsured? Employment Policies Institute

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TABLE 2. Percent with Private Insurance by Family Income Expressed as a Multiple of the Poverty Threshold, Persons Ages 18­64, 2006
< 1.25 × pov. level Total population excluding those with public insurance (000's) Privately insured as percent of total population excluding publicly insured MEMO: Total population (in 000's) Uninsured With public insurance With private insurance 16,619 35.6 1.25­2.5 × pov. level 27,803 60.8 2.5­3.75 × pov. level 28,885 79.2

3.75 ×
pov. level 89,202 88.6

25,093 10,708 8,474 5,910

33,883 10,885 6,080 16,918

32,256 6,008 3,371 22,876

95,456 10,191 6,254 79,011

Note: The poverty level multiples are based on the ratios of total family income by family type divided by the relevant poverty threshold for that family type as estimated by the Census Bureau. Public insurance includes Medicare, Medicaid, CHAMPUS, VA, and other military healthcare. The data source is the Current Population Survey (CPS) microdata files, March 2007.

on healthcare. At the other end of the income distribution are those who have relatively low incomes, yet purchase health insurance. This group likely assigns a high value to health insurance, either because they have poor perceived health or are highly risk averse. At the lowest income levels, of those remaining uninsured, there will be a number of persons who value insurance but simply cannot afford it. This is the underlying conceptual model that has guided our assignment of the numbers of voluntarily and involuntarily uninsured. Table 2 shows the distribution in 2006 of uninsured and insured individuals by income, expressed as a multiple of the poverty level. The poverty threshold differs by family type and size, so the number of individuals at each multiple of the poverty level depends on both their income level and their distribution by family type and size. The percentage of all individuals (excluding those with public coverage) who obtain private coverage rises to 89 percent for those in families with incomes equal to or greater than 3.75 times their poverty threshold and to 79 percent for those with incomes between 2.5 and

3.75 times their poverty threshold. In view of the large percentages covered at those levels, we consider uninsured units with incomes above 2.5 times the poverty threshold to be voluntarily uninsured. Among families with incomes below 2.5 times the poverty level, the percentage obtaining private insurance drops to 61 percent for those with incomes between 1.25 and 2.5 their poverty thresholds and then falls even more sharply to 36 percent for those with incomes less than 1.25 times their poverty thresholds. Given the relatively low percentages covered at income levels below 2.5 times the poverty line, we assume that all individuals and families without private health insurance at those levels are involuntarily uninsured. Therefore, all persons and households without insurance and at incomes greater than 2.5 times their poverty line are assumed to be voluntarily uninsured. Table 3 shows how our estimates of the percent of the uninsured would vary depending on the income level used to delineate two groups. The results are shown at

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Employment Policies Institute Who Are The Uninsured?

TABLE 3. Differences in the Percent of the Uninsured Classified as Involuntarily Uninsured Under Alternative Income Cut-off Points, Persons by Family Type, Ages 18-64, 2006
Total Total Pop. % Uninsured (000's) Uninsured (000's) Not Married Without Children Not Married With Children Married Without Children Married With Children Total 63,776 21,462 48,077 53,373 186,688 28.9 29.7 11.4 14.1 20.2 18,429 6,364 5,487 7,512 37,792 Percent of total uninsured classified as involuntarily uninsured at different income cut-offs <2.0 × <2.5 × <3.0 × pov. level pov. level pov. level 43.6 59.0 31.4 57.7 47.2 52.9 67.4 39.9 71.3 57.1 60.2 73.0 50.1 79.7 64.8

Note: The poverty level multiples are based on the ratios of total family income by family type divided by the relevant poverty threshold for that family type as estimated by the Census Bureau. The data source is the CPS microdata files, March 2007.

three different income levels expressed as multiples of the poverty threshold and the numbers are disaggregated by family type. At an income level of less than two times the poverty line (where a person is considered to be involuntarily uninsured), the involuntarily uninsured make up 47 percent of the total uninsured. At a level of less than three times the poverty line, 65 percent of the total uninsured would be classified as involuntarily uninsured. At the intermediate cut-off of less than 2.5 times the poverty level--the one we ultimately select for our analysis--the involuntarily uninsured are 57 percent of the total uninsured. However, even assuming that only those with incomes exceeding 3 times the poverty line are voluntarily uninsured (a relatively conservative estimate of ability-to-pay), the involuntarily uninsured would be only 65 percent of the "official" number of uninsured persons. The most common number used to measure the uninsured refers to the entire population including those ages

65 and over, almost all of whom are covered by Medicare as well as children under the age of 18. (Differences by age group in the number and percent uninsured are shown in Table 1.) We restrict our analysis to the population ages 18­64, adults who can be viewed as making health insurance coverage decisions. As a broad check on the validity of our numbers, we have also estimated the number uninsured and their distribution by voluntary and involuntary status using two other major surveys that measure the uninsured and some of their characteristics--the Medical Expenditure Panel Survey (MEPS) and the National Health Interview Survey (NHIS). Questions on health insurance coverage vary in concept across surveys and these conceptual differences can lead to wide differences in survey estimates of the number of uninsured. A major conceptual difference in definitions is the time period over which a person's insurance status is measured. Three time periods are commonly used. One refers to those who are uninsured for a full year, another to the

Who Are The Uninsured? Employment Policies Institute

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person's status at the time of the interview (called "point in time" measure), and a third measures whether an individual has ever been without health insurance during a particular year. Because of the relatively high turnover in insurance status, the "ever uninsured" question results in the largest estimates of the number of uninsured. The most stringent definition leading to the smallest estimates is "full-year uninsured." The MEPS is a panel survey that interviews individuals several times during the year and asks about their insurance status at the time of the interview and for each month in the past 3­5 months. The MEPS data can be combined to produce all three measures. In 2003, estimates of the uninsured based on MEPS indicated 33.7 million uninsured full-year, 48.1 million uninsured at a point in time, and 62.9 million uninsured at any time during the year (ASPE, September, 2005). The NHIS also collects data that enables estimates under the three definitions but interviews less frequently during the year than MEPS.

Every March the CPS asks only one question on insurance status, and attempts to uncover those uninsured for a full year over the previous calendar year. However, an answer to the CPS question requires recall over the prior 13 to 15 months. Studies comparing estimates of the uninsured from the CPS and other surveys have concluded that it is likely that some respondents, perhaps confused by the long recall period, report their current insurance status, producing an estimate that is closer to the point-in-time concept.5 In Table 4, we compare results from the three surveys on the number of uninsured ages 18­64 and on the division of the uninsured into the involuntary and voluntary categories. The NHIS and CPS estimates of the total uninsured are quite similar even though the CPS is intended to show full-year uninsured, and the NHIS, the uninsured at a point in time. The CPS estimates are also larger than MEPS, which is a better measured full-year uninsured estimate. The similarity of the CPS with the NHIS and that they share differences with the MEPS estimates appear to confirm the view that the CPS estimates are closer to a point-in-time estimate.

TABLE 4. Comparison of Different Survey Estimates of the Number Insured and Uninsured by Voluntary/Involuntary Status (Ages 18-64)
Method of Estimate
1)

Number Uninsured Total Involun. Volun. 21.6 million 21.6 million 16.6 million 16.2 million 14.9 million 14.6 million

Uninsured a Percent of Total Population Total 20.3 20.0 17.0 Involun. Volun. 11.6 11.9 9.0 8.7 8.2 7.9

Percent Distribution of the Uninsured Involun. Volun. 57.1 59.2 53.1 42.9 40.8 46.9

Current Population Survey (CPS) 2006 National Health Interview (NHIS) 2006 Medical Expenditure Panel (MEPS) 2005
1)

Full year 37.8 (retrospective million question) 36.5 Point in time million 2) Full year 31.3 (panel data) million

The CPS question is retrospective and refers to those who reported in March 2007 they had no health insurance at any time in the prior calendar year. But many may report health insurance status at the time of the March survey. See discussion in text. 2) MEPS is a panel survey. The full-year uninsured refer to people who reported no insurance for each of the 12 months. Note: See Table 3 for definition of involuntarily and voluntarily uninsured. Authors' estimates using the microfiles of stated surveys.
5

See ASPE, Sept. 2005; U.S. Bureau of the Census, 2007; Congressional Budget Office (CBO) May, 2003.

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Employment Policies Institute Who Are The Uninsured?

The CPS and NHIS estimates of the involuntarily uninsured are also quite similar. The income data in MEPS are much less detailed than the CPS or NHIS data, and therefore, the estimates of the involuntarily uninsured are more difficult to compare in detail with the CPS. However, we can conclude from these results that the CPS, despite definitional differences, is reasonably valid for describing the insured and uninsured as well the voluntarily and involuntarily uninsured in the U.S. We rely on the CPS for much of our analysis because of its large sample size and superior data on income, employment, education, and various demographic characteristics.

2000 and then increased to 20.3 percent in 2006 (Table 5). The involuntarily uninsured as a percentage of the total population similarly declined from 11.1 percent in 1994 to 9.8 percent in 2000 and then rose again, but only back to 11.6 percent. Thus, while both series moved in the same direction between 1994 and 2006, the involuntarily uninsured increased more slowly than the total uninsured, and consequently, made up a smaller proportion of the uninsured in 2006 than in 1994. Table 6 shows the variation across states in the percentage of the total population that we estimate to be involuntarily uninsured, the percentage voluntarily insured, and the total percentage uninsured. The variation in the total percent uninsured is quite large, ranging from 30.1 percent in Texas to only 11.2 percent in Minnesota. Expressed as a ratio, Texas has 2.7 times the percentage of uninsured as Minnesota. The variation in the per-

Changes in the Percent Uninsured over Time and Across the U.S. States
Over the years 1994 to 2006, the total number of uninsured as a percentage of the population 18­64 declined slightly from 18.5 percent in 1994 to 17.9 percent in

TABLE 5. Number of Insured and Uninsured by Voluntary/Involuntary Status and by Type of Family: 1994­2006, Ages 18­64
Insured (in `000) 1994: Total Not Married Without Children Not Married With Children Married Without Children Married With Children 2000: Total Not Married Without Children Not Married With Children Married Without Children Married With Children 2006: Total Not Married Without Children Not Married With Children Married Without Children Married With Children 129,978 35,367 14,085 36,622 43,904 141,841 42,443 14,376 38,942 46,080 148,128 45,216 15,066 42,441 45,404 Uninsured (in `000) Total Involun. Volun. 29,425 17,687 11,738 13,641 7,398 6,243 4,398 2,990 1,408 4,792 2,259 2,533 6,593 5,039 1,554 30,935 16,992 13,943 14,202 7,250 6,952 5,222 3,351 1,871 5,239 1,990 3,249 6,272 4,401 1,871 37,792 21,593 16,199 18,430 9,757 8,673 6,364 4,287 2,077 5,487 2,190 3,297 7,513 5,360 2,153 Uninsured as % of Total Population Total Involun. Volun. 18.5 11.1 7.4 27.8 15.1 12.7 23.8 18.2 7.6 11.6 5.5 6.1 13.1 10.0 3.1 17.9 9.8 8.1 25.1 12.8 12.3 26.7 17.1 9.6 11.9 4.5 7.4 12.0 8.4 3.6 20.3 11.6 8.7 29.0 15.3 13.6 29.7 20.0 9.7 11.5 4.6 6.9 14.2 10.1 4.1

Note: For the definition of involuntarily and voluntarily uninisured, see text. Source: Current Population Survey (CPS) March 1995, 2001, and 2007.

Who Are The Uninsured? Employment Policies Institute

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TABLE 6. The Insured and Uninsured by Voluntary/Involuntary Status by State of Residence, Ages 18­64
Uninsured as % of Total Pop. Total1) Involun.1) Volun.1) By State Texas New Mexico Louisiana Florida Arkansas Arizona Oklahoma Mississippi California Nevada Oregon North Carolina Georgia Alaska Alabama Montana Utah South Carolina Colorado Kentucky Wyoming Tennessee Idaho New Jersey New York Illinois Maryland West Virginia Missouri Kansas Virginia Washington South Dakota Nebraska North Dakota Indiana New Hampshire Delaware
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2)

Insured (in `000)

Total 4,228 347 739 3,015 455 1,014 540 447 5,463 368 547 1,263 1,330 90 600 127 321 559 641 535 65 711 174 1,032 2,267 1,447 632 210 640 280 808 633 73 171 60 616 127 79

Uninsured (in `000) Involun. Volun. 2,590 233 422 1,747 304 619 380 327 2,889 219 305 785 779 47 431 89 192 297 341 348 33 424 104 506 1,225 761 308 127 379 181 450 328 49 104 38 356 60 41 1,638 114 316 1,268 151 394 160 120 2,574 148 242 477 551 43 169 38 128 262 300 187 31 287 70 526 1,042 686 324 83 260 99 358 305 24 67 22 260 67 38

30.1 29.8 28.8 27.3 26.4 26.0 26.0 25.0 24.0 23.6 23.0 22.7 22.0 21.5 21.3 21.2 21.1 21.1 20.7 20.4 20.3 19.8 19.6 18.9 18.9 18.1 17.8 17.8 17.7 17.0 16.7 15.6 15.6 15.6 15.3 15.2 15.1 14.8

18.4 20.0 16.4 15.8 17.7 15.9 18.3 18.3 12.7 14.0 12.8 14.1 12.9 11.2 15.3 14.9 12.6 11.2 11.0 13.3 10.3 11.8 11.7 9.3 10.2 9.5 8.7 10.7 10.5 11.0 9.3 8.1 10.5 9.5 9.7 8.8 7.1 7.7

11.7 9.8 12.3 11.5 8.8 10.1 7.7 6.7 11.3 9.5 10.2 8.6 9.1 10.3 6.0 6.4 8.4 9.9 9.7 7.1 9.7 8.0 7.9 9.7 8.7 8.6 9.1 7.0 7.2 6.0 7.4 7.5 5.1 6.1 5.6 6.4 8.0 7.1

9,816 817 1,830 8,045 1,266 2,892 1,541 1,343 17,308 1,194 1,828 4,304 4,720 328 2,223 471 1,201 2,092 2,457 2,082 255 2,884 715 4,416 9,737 6,545 2,920 973 2,982 1,371 4,020 3,415 394 926 333 3,427 715 454

Employment Policies Institute Who Are The Uninsured?

Uninsured as % of Total Pop. Total1) Involun.1) Volun.1) By State Michigan Iowa D. C. Ohio Massachusetts Pennsylvania Vermont Connecticut Maine Wisconsin Rhode Island Hawaii Minnesota
1) 2)

Insured (in `000)

Total 918 261 54 981 548 1,000 53 272 103 415 80 89 365 37,787

Uninsured (in `000) Involun. Volun. 552 160 31 554 256 540 23 129 61 249 42 45 183 21,643 367 102 23 426 293 460 29 143 42 167 37 44 182 16,144

2)

14.7 14.4 13.8 13.8 13.6 12.9 12.8 12.5 12.2 11.8 11.7 11.6 11.2 20.3

8.8 8.8 7.9 7.8 6.4 6.9 5.6 5.9 7.2 7.1 6.2 5.9 5.6 11.6

5.9 5.6 5.9 6.0 7.3 5.9 7.0 6.6 5.0 4.7 5.4 5.7 5.6 8.7

5,336 1,550 337 6,123 3,479 6,781 360 1,904 739 3,114 603 677 2,883 148,126

The sum may not add to the total due to rounding. Note: Ranked by percent uninsured of total population from the highest to lowest. Note: Involuntarily uninsured are those with family income less than 2.5 times the poverty threshold for their family type. The data source is the Current Population Survey microdata files, March 2007.

centage of those involuntarily uninsured ranges from 20.0 percent in New Mexico to 5.6 percent in Vermont and Minnesota. Thus, New Mexico has 3.6 times the percentage of those involuntarily uninsured as the two lowest States. Differences in state per capita income, measured by state Gross Domestic Product (GDP) (not shown in Table 6) help explain the variation in insurance coverage. A simple regression of the percent of the population ages 18­64 either insured or voluntarily uninsured on state GDP shows that for every $10,000 increase in state per-capita GDP, the percent either insured or voluntarily uninsured increases by about 7 percent (a statistically significant result). States like Texas and New Mexico, where the percent involuntarily uninsured is relatively high (and therefore the percent insured or voluntarily uninsured is low) would face a distinct challenge in achieving 100 percent coverage. Such a challenge would not be faced by states with high insurance coverage rates like Vermont and the other New England states, or Minnesota.

These results suggest that policies for extending public coverage to the uninsured should take into account interstate differences in both the percentage that are involuntarily uninsured and in state per capita income.

Summary on Determining the Number of Involuntarily Uninsured
We estimate that about 16 million of the population ages 18­64 reported as uninsured in 2006 are voluntarily uninsured in the sense that their incomes are high enough to enable them to afford a health insurance policy. That leaves 22 million who are involuntarily uninsured--that is, their incomes are below 2.5 times the poverty level, an income level at which the purchase of insurance would require considerable personal sacrifice. Thus, although 20 percent of the population ages 18­64 is uninsured, only 12 percent of the population and 57 percent of the uninsured are involuntarily uninsured. These are important distinctions because those who choose not to be insured are surely not in the same position as those who
Who Are The Uninsured? Employment Policies Institute

13

TABLE 7. Personal Characteristics by Insurance Status, Ages 18­64, March CPS 2007
Total Total Pop. (in `000) Total Pop. (% distribution) Gender (%) Male Female Age (%) 18­34 35­44 45­64 Education (%) HS dropout HS grad. Some college College grad. or higher Race/Ethnicity (%) White, non-Hispanic Black, non-Hispanic Other race, non-Hispanic Hispanic Immigrant status (%) Native born Foreign born, citizen Foreign born, non-citizen Foreign born by year came to the U.S. (100%) Before 1990 1990­99 2000­07 Marital and child status (%) Married, no children Married with children Not married, with children Not married, no children Employment Status in 2006 Never worked Wage and salary workers, worked all year Wage and salary workers, worked part year Self-employed workers, worked all year, Self-employed workers, worked part year 162,508 100.0% Privately Insured 124,716 76.7% 49.0 51.0 32.7 24.3 43.0 7.1 27.2 30.5 35.2 74.2 9.7 6.7 9.5 87.5 6.1 6.4 48.1 30.8 21.2 29.3 32.7 8.4 29.6 13.5 68.6 9.8 7.1 1.1 Total 37,792 23.3% 54.8 45.2 50.4 21.2 28.4 27.4 37.1 23.8 11.6 47.2 14.9 6.8 31.1 70.0 6.0 24.0 29.0 35.7 35.3 14.5 19.9 16.8 48.8 29.9 45.8 13.7 8.6 1.9 Uninsured Volun. 16,199 10.0% 61.5 38.6 48.7 19.6 31.7 20.4 36.2 27.0 16.3 53.7 12.7 7.3 26.3 74.0 6.8 19.2 34.1 35.3 30.5 20.4 13.3 12.8 53.5 19.5 52.9 12.9 12.7 2.0 Involun. 21,593 13.3% 49.8 50.2 51.7 22.4 25.9 32.7 37.8 21.4 8.1 42.4 16.6 6.4 34.7 67.1 5.3 27.7 26.0 35.9 38.1 10.1 24.8 19.9 45.2 37.8 40.5 14.3 5.6 1.9

14

Employment Policies Institute Who Are The Uninsured?

Total Family Income in 2006 (%) Family income <20,000 Family income 20,000­40,000 Family income 40,000­70,000 Family income >70,000

Privately Insured

Total 32.8 29.8 21.3 16.1

Uninsured Volun. 0.0 20.5 42.0 37.4

Involun. 57.5 36.8 5.8 0.0

6.1 15.3 26.9 51.7

Note: Voluntarily uninsured are those with family income equal to or exceeding than 2.5 times the poverty threshold for their family type. Involuntarily uninsured are those with family income less than 2.5 times the poverty threshold for their family type. All calculations are weighted. The demographic variables are reported as of March 2007. Employment status, income, and insurance status are reported for the prior calendar year (2006). Source: The CPS microdata files, March 2007.

might place a high value on insurance coverage but cannot afford to buy it. One observation of particular policy relevance is that the percent of the population that is either covered or voluntarily uninsured varies considerably across states. Moreover, the cross-state variation is strongly related to state per capita income.

tion with the CPS data to examine the effect of insurance costs on the decision of firms to provide benefits and of individuals to purchase private insurance in the individual's market.6 Table 7 provides data on the characteristics of individuals ages 18­64 classified by insurance status: privately insured, total uninsured, voluntarily uninsured, and involuntarily uninsured. (We exclude those with public insurance such as Medicaid and Medicare because the focus here is on the acquisition of private insurance.) The characteristics examined include gender, age, marital/family status, schooling attainment, income, employment status, racial and ethnic group, and immigrant status. Among the differences in characteristics, we note that compared to those with private insurance, the uninsured are more likely to be male (55 percent versus 49 percent) and under the age of 35 (50 percent versus 33 percent); they are much more likely to be unmarried and have no children (49 percent versus 29 percent). Compared to the privately insured, the uninsured are also almost four times as likely to be high school dropouts, more than three times as likely to be Hispanic, and close to four times as likely to be foreign-born non-citizens. Their

Personal Characteristics by Insurance Status and their Impact on the Probability of Being Uninsured
How do the demographic and economic characteristics of individuals differ between the insured and the uninsured and between the involuntarily and voluntarily uninsured? How do those factors interact to determine an individual's insurance status? We use data from the CPS to compare the demographic and socioeconomic characteristics of people in different insurance categories. We then use regression analysis to examine the effect of personal, social, and economic characteristics on the probability that a person is covered by private health insurance. We have also added data on insurance premium costs by state obtained from the Kaiser Family Founda6

The assumption that all individuals in a state face the same premium cost is not likely to be true, but the cross-state variation is likely to capture much of the variation across individuals. It would be extremely difficult to obtain insurance costs for all localities and types of families. 15

Who Are The Uninsured? Employment Policies Institute

incomes are substantially lower and a larger percentage never worked during the year or worked only part of the year. The involuntarily uninsured differ in some significant ways from the voluntarily uninsured. They are more likely to be Hispanic and to be foreign-born non-citizens and their educational level is considerably lower. One-third of the involuntarily uninsured are high school dropouts compared to 20 percent of the voluntarily uninsured and the involuntarily uninsured are almost twice as likely as the voluntarily uninsured to have never worked during the year. About 15 percent of the voluntarily uninsured were self-employed, a much larger proportion than the involuntarily uninsured or privately insured. The pattern of differences in characteristics by insurance status are roughly similar for women and men, but with some exceptions. (See Appendix Tables A and B for characteristics tabulated separately by sex.) A much larger percentage of women than men never worked during the year, and the difference is particularly large among the involuntarily uninsured (48 percent of involuntarily uninsured women never worked compared to 27 percent of men in this category). In addition, a much larger percentage of uninsured men than women are single and have no children, while uninsured women are more likely to be unmarried with children. What Table 7 does not consider are the possible inter-correlations between the different characteristics. Consequently, the net effects of the characteristics can differ from the observed gross associations shown in Table 7. The gross association between immigrant status and coverage might change significantly if educa7

tional attainment were held constant, since education affects coverage and it is correlated with immigrant status. To examine these net effects, we turn to multiple regression analysis. Our regression results are reported in Table 8. The dependent variable is a binary indicator variable: 1=insured and 0=uninsured.7 We conduct separate regressions for two different family types: "Married with Children" and "Not Married, No Children." We do this in part because family status can affect the decision to purchase insurance, even among individuals with the same education, income, and other characteristics. It is also the case that premium costs differ significantly for single and married couples, making it statistically difficult to conduct and interpret results for regressions combining the two types of families in a single regression. The basic data source for these regressions is the microdata file of the March 2007 CPS with the exception of the insurance premium data, which we obtained from the Kaiser Family Foundation.8 The premium cost is the average premium in the individual's state of residence for an employer-based premium, measured separately for a single individual with no children and for families with children. The March CPS measures demographic characteristics at the time of the March survey. However, insurance status and income are measured for the prior calendar year--2006. Therefore we use premium costs for 2006. We measure employment experience over the course of the prior calendar year because employer-based health insurance is the major source of private insurance. We interact self-employment status with work experience because of the obvious difference in the individual's role in the purchase decision.

The results shown here are based on only least squares (OLS) methodology. We also ran the same regression specifications using a logit model, which produced very similar results. 8 Kaiser bases their premium cost data on individual state averages tabulated from MEPS. We assume that premium costs relevant for the individuals in our data will be highly correlated with the state average for their state of residence and that costs for privately purchased insurance will be highly correlated with costs of employer premiums across states. 16

Employment Policies Institute Who Are The Uninsured?

Table 8 displays the mean characteristics and partial regression coefficients for each family type. The regression model is the same for each group and contains the personal characteristics measures listed as well as the variable specifying the average health premium cost by family type in the individual's state of residence. In addition, we include a state indicator variable for each state. These state fixed-effect variables are intended to reflect the otherwise unmeasured factors that could vary across states and affect insurance coverage such as the provision of public health services. In examining the means of the variables used in the regression equations, one can see that the annual insurance premiums are considerably higher for couples with children--a mean of $11,300 compared to $4,100. Not surprisingly, singles without children are younger--fifty percent are younger than 35 years of age compared to 27 percent of the married group. They also have less education and lower incomes. Turning now to the regression results, we find that those who are not married/no children are less likely to have insurance than those who are married with children (68 percent compared to 86 percent). They are also considerably more responsive to a change in premium cost than those who are married with children Thus, a $1,000 increase in the premium cost reduces the probability that the not-married/no-children individual has health insurance by 0.32. Estimated at the mean, that would imply an elasticity of demand close to ­2. In contrast, a $1,000 increase in the premium cost reduces the probability that a married individual with children has insurance by only 0.027, a highly inelastic response (­0.38) calculated at the mean. The difference in price sensitivity by family type is perhaps explained by the concern of parents
9

for the healthcare needs of their children. The relatively young ages of the single individuals, who tend to have fewer health problems, may also play a role. With respect to personal characteristics, we find that among those who are unmarried and have no children, women are more likely to have insurance than men (an increase of 6 percentage points). This result is consistent with that of other research that has found women to be more risk averse than men.9 Among those who are married with children, there is no significant difference by gender, which is to be expected given that spouses are likely to be jointly covered. Reaching ages 55­64, when health problems became more prominent is positevely and significantly associated with increased insurance coverage among the not-married/no-children group, but not among those married with children. However, only 3 percent of the married-with-children group is in the 55­64-year-old age group. Race has little effect on insurance among the marriedwith-children group. However, among the not-married/ no -children group, the black non-Hispanic population is less likely than white non-Hispanics to have private insurance (a 5 percentage point difference). Much stronger differences appear between Hispanics and other ethnic groups. Thus, the probability of having private insurance is 13 percentage points lower among Hispanics who are not married and without children than it is for corresponding non-Hispanic whites. Among those married with children, there is a 10 percentage point differential. Employment, as expected, also has significant effects on the probability of having private insurance, and again the effect is much greater among the not-married/no-children group. The self-employed have much lower rates of

The literature on gender differences in risk aversion is large and growing and refers to an array of behaviors. For example, studies find that women are more likely to use seatbelts than men (Waldron, McCloskey, & Earle, 2005); men are more likely to run yellow lights than women (Konecni, Ebbesen, & Konecni, 1976). In an extensive meta analysis, Byrnes, Miller, and Schaffer (1999) find substantial evidence that men are more likely to take risks than women. Also see Harris, Jenkins, and Glaser, 2006. 17

Who Are The Uninsured? Employment Policies Institute

TABLE 8. Regression Estimates of the Effect of Personal Characteristics and the Cost of Private Insurance on the Probability a Person Has Private Insurance, Ages 18­64
Mean Married with Not married children no children 0.493 0.456 (0.273) 0.694 0.033 (0.713) 0.161 0.056 0.071 0.144) 0.652 0.092 0.099 0.014 (0.095) 0.265 0.266 0.375 (0.036) 0.118 0.268 0.578 (0.807) 0.050 0.019 0.003 0.030 0.052 0.039 (0.502) 0.358 0.140 (0.586) 0.172 0.150 0.092 (0.158) 0.645 0.133 0.052 0.012 (0.134) 0.304 0.306 0.255 (0.219) 0.286 0.249 0.247 (0.847) 0.031 0.013 0.002 0.021 0.033 0.053 -0.006 -0.036 -0.044 -0.104 -0.145 -0.137 -0.84 -3.13 -1.60 -10.68 -18.39 -15.85 -0.003 -0.049 -0.066 -0.112 -0.159 -0.161 -0.19 -2.27 -1.25 -6.34 -10.88 -13.20 Married with children Coef. 0.003 T-stat 0.82 Not married no children Coef. 0.056 T-stat 11.21

Female Age Group (18­34)* 35­54 55­64 Race/Ethnicity (White, non-Hispanic)* Hispanic Black, non-Hispanic Other race, non-Hispanic Employment Status in 2006 (Never worked)* Wage and salary workers, worked all year Wage and salary workers, worked part year Self-employed workers, worked all year Self-employed workers, worked part year Education (Less than high school)* High school Some college grad. or higher College grad. or more Family income in 2006 (Family income <20,000)* Family income 20,000­40,000 Family income 40,000­70,000 Family income >70,000 Immigrant Status (Native born)* Foreign born citizen by year came to the U.S. Before 1990 1990­99 2000­06 Foreign born non-citizen by year came to the U.S. Before 1990 1990­99 2000­06

0.022 0.011

6.17 1.27

0.021 0.069

3.83 9.04

-0.103 -0.014 0.007

-17.89 -2.03 0.95

-0.127 -0.048 -0.037

-15.47 -6.36 -3.69

0.059 0.031 -0.038 -0.013

12.04 4.89 -5.75 -0.99

0.188 0.097 -0.041 -0.081

25.49 10.54 -3.20 -3.52

0.113 0.155 0.183

18.05 23.92 28.18

0.047 0.139 0.207

5.65 16.46 23.13

0.196 0.394 0.445

21.48 44.79 50.30

0.182 0.262 0.299

24.95 34.38 39.10

18

Employment Policies Institute Who Are The Uninsured?

Mean Married with Not married children no children Cost of health insurance premium in state of residence, 2006 (in $1,000) Adj. R-Square Dependent Variable (DV) mean (DV: Had private insurance in 2006 (1,0) Sample size 11.3 4.1

Married with children Coef. ­0.027 T-stat ­2.55

Not married no children Coef. ­0.322 T-stat ­4.90 0.237 0.682 28,106

0.304 0.858 38,079

* Variables in parenthesis are the reference group. Note: The model also contains a dummy variable for each state. Persons covered by public health insurance are excluded from the analysis. Source: The CPS microdata files, March 2007.

private insurance coverage than wage and salary workers (comparing those who work all year)--23 percentage points less among the not-married/no-children group and 10 percentage points less among married workers with children. Higher insurance costs likely account for the lower insurance coverage among the self-employed, who cannot take advantage of lower group rates available to firms. Presumably, wage and salary workers who work year round are more likely to be employed at a firm that offers insurance, and those who value insurance highly may seek employment in such firms. Education has a strong effect on the probability of having private insurance. Among the married-with-children group, the probability of coverage is 18 percentage points higher for college grads than it is for high school dropouts, and for the not-married/no-children group, the differential is even larger. Note also that these large effects of educational attainment are net effects holding income level constant. The regression results also demonstrate a powerful effect of income, and in this case, the effect is stronger for those married with children than it is for the not-married/no-children group. Those with high incomes are more likely to work in firms that offer health

insurance since the value of the tax subsidy for health insurance rises with wages. Immigrant status has large and interesting effects even though we are controlling for race/ethnicity, income, and education. We have measured three aspects of immigrant status--foreign-born citizen, foreign-born non-citizen, and how long the individual has been a resident of the U.S. Compared to native-born individuals, the foreign born who are citizens have somewhat less coverage while the foreign born who are not citizens have a considerably lower probability of coverage. This is generally the case for both marital status groups. Moreover, the differentials relative to the native-born group decline with increasing years spent in the U.S. In summary, our regression analysis indicates that personal characteristics such as educational attainment, immigrant status, and income are important factors in determining who is likely be insured by private insurance and who is likely to be uninsured, both voluntarily and involuntarily. In addition, our results have implications for projecting future trends in the size of the uninsured population. They suggest that the growth in personal income and educational attainment will lead to a decrease in the number of uninsured, while the growth in

Who Are The Uninsured? Employment Policies Institute

19

premium costs and in the immigrant population will lead to an increase in the uninsured. Long term planning for increasing insurance coverage should take these trends into account. Regarding the responsiveness of the purchase of private insurance to the cost of an insurance premium, either by the individual directly or through his or her employer, we find a significant demand elasticity for individuals who are not married and have no children, but not for married couples with children, who tend to have a higher level of private insurance and respond less to changes in its cost. With regard to non-cost factors, we find that educational attainment and immigrant status are the two most important determinants, other than income, of the probability a family or individual has private insurance coverage. We now turn to the issue of the extent to which uninsured persons use medical care resources.

the "safety net" that we use here are available for the uninsured as a whole, but some inferences can be drawn about the differences between the voluntarily and the involuntarily uninsured.

Medical Services Received by the Uninsured
We use data from the 2005 Medical Expenditure Panel Survey (MEPS) to measure the receipt of various medical services by adults classified according to insurance status. The MEPS concept of the uninsured is similar to that used by the CPS--namely, individuals who were not covered by insurance at any time in the year before they were interviewed. A summary of the results is shown in Table 9. We show the results by age and specify the time periods when the service was received. There are large differences between the insured and uninsured in the percent receiving particular services when the comparison is restricted to services received in the past two years. However, the differentials become smaller when the receipt period is measured within the past five years (the sum of the past two years and prior 3­5 years) and are smaller still when the comparison is for those who have "ever received" the service. Thus, 78 percent of the insured population had a routine check-up in the past two years compared to 50 percent of the uninsured, and the comparison narrows to 88 percent versus 68 percent when the period of receipt is within 5 years and 95 percent versus 84 percent when it is extended to "ever received". (Of course, for many procedures "ever" may be too long ago to be meaningful.) When it comes to cancer screening, 80 percent of insured women ages 40­64 had a mammogram within two years of the interview; and 87 percent when the period of receipt is extended to 5 years. That compares to 49 percent of uninsured women who had a mammogram within two years and

Health Resources Obtained by The Uninsured
Two types of measures are available for estimating the amount of healthcare resources obtained by the uninsured. One is based on answers to specialized health surveys that ask questions about the types of medical care services received over particular time periods. Answers to those questions can be derived for the insured and separately for the involuntarily and voluntarily uninsured. A second type of measure is based on estimates of the dollar cost of all types of medical care services received by the uninsured that are either paid for by the uninsured ("out of pocket") or are provided without charge by what has come to be called the "safety net"--various public and private charities as well as uncompensated care provided by hospitals and physicians. The data concerning
10

See Table 8 in O'Neill and O'Neill (2007), which provides comparisons of cancer screening in Canada and the U.S.

20

Employment Policies Institute Who Are The Uninsured?

65 percent when the period is within 5 years. However, those screening rates are relatively high even for uninsured women when compared with screening rates in Canada, a country with universal health coverage. The Canadian health survey reports that 65 percent of Canadian women ages 40­69 had a mammogram within the past 5 years, the same percentage as uninsured women in the U.S.10 When it comes to Pap Smears, Canadian women also have about the same rate of

screening over the past five years as uninsured women in the U.S. (80 percent), although those rates are below those of insured American women, among whom 92 percent were screened. Among U.S. men ages 40­64, 52 percent of those with insurance were screened for prostate cancer with a PSA test within the past 5 years, compared to 31 percent for men who are uninsured. (In Canada, the comparable percent is 16 percent.)

TABLE 9. Percent Received Selected Medical Services by Insurance Status and Age, MEPS 2005
Insured all 12 months Ages 18-64 Routine Check-Up % ever received routine check-up Past 2 years 3­5 years ago Blood Pressure Check % ever received blood pressure check Past 2 years 3­5 years ago Flu Shot % ever received flu shot Past 2 years 3­5 years ago Ages 20-64 PAPSMEAR TEST (Women only) % ever received PapSmear Test Past 2 years 3­5 years Ages 40-64 PSA TEST (Men only) % ever received PSA Test Past 2 years 3­5 years MAMMOGRAM (Women only) % ever received mammogram Past 2 years 3­5 years 95.08 78.40 9.42 99.29 93.17 4.33 48.52 34.96 7.25 84.08 50.43 17.16 93.78 71.79 14.39 29.79 17.05 5.31 83.74 48.54 18.28 94.69 72.36 14.91 29.25 15.29 5.86 84.47 52.62 15.86 92.74 71.14 13.78 30.42 19.07 4.69 Total Uninsured all 12 months Involun. Volun.

97.69 83.84 8.04

93.14 62.81 17.23

92.41 58.95 17.45

94.14 68.04 16.95

55.00 46.32 5.41 91.26 79.83 7.32

35.99 24.02 6.71 76.15 49.25 15.96

34.23 23.72 6.12 66.66 38.03 16.76

37.71 24.32 7.29 86.86 61.94 15.04

Note: Calculation excludes the small percentage that did not report whether they received the service or not. Source: MEPS 2005

Who Are The Uninsured? Employment Policies Institute

21

Table 9 also shows the same statistics on service receipt separately for the involuntarily and voluntarily uninsured. Generally speaking, we find no significant differences in the percent receiving the service between the two groups. The main exception is the higher rate of recent receipt of mammograms and pap smears by voluntarily uninsured women. As we show in (Table 12), the voluntarily uninsured not only have higher incomes than the involuntarily uninsured, but also have more education and other characteristics associated with good health, all of which may account for that difference. Early detection of cancer is important for cancer survival. In international comparisons of 5-year relative survival rates for specific cancers, the U.S. comes out at the top, and undoubtedly, the generally high rate of screening in the U.S. helps to account for that ranking.11 It is important to determine the extent to which the lower rates of screening of the uninsured, particularly of the involuntarily uninsured, are due to inability to pay, or if other factors, such as lack of information about available free serv