10
Income and Poverty Measurement in Surveys of Health Insurance Coverage

John L. Czajka

Mathematica Policy Research, Inc.


Each year the Census Bureau produces a set of state-level estimates of children under age 19 in families with incomes at or below 200 percent of the federal poverty level and the subset of these who are without health insurance coverage. The estimates, which are derived from the Annual Social and Economic Supplement (ASEC) to the monthly Current Population Survey (CPS), were mandated by Congress for the purpose of allocating federal funds for matching state expenditures under the Children’s Health Insurance Program (CHIP), but they have become a critical source of data for monitoring the states’ progress in reducing the number of low-income uninsured children. Because the CPS ASEC samples for most states are not large enough to support estimates of low-income uninsured children at satisfactory levels of precision, the Census Bureau combines 3 years of data to produce the estimates for each year. Even with 3 years of data, however, the estimates for many states are still not as precise as might be desired, and the need to combine 3 years of data makes the estimates less sensitive to year-to-year change in the number of low-income uninsured children. While this reduced sensitivity may have merits for funding allocation, it limits the usefulness of the estimates for monitoring state levels of health insurance coverage among low-income children.

With the recent reauthorization of CHIP, Congress made provision for potential enhancements to the annual estimates of low-income uninsured children while simultaneously ending their role in CHIP funding allocation. One of the options that the law mandates the Census Bureau to consider is to supplement or replace the CPS estimates with alternative



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10 Income and Poverty Measurement in Surveys of Health Insurance Coverage John L. Czajka Mathematica Policy research, Inc. Each year the Census Bureau produces a set of state-level estimates of children under age 19 in families with incomes at or below 200 percent of the federal poverty level and the subset of these who are without health insurance coverage. The estimates, which are derived from the Annual Social and Economic Supplement (ASEC) to the monthly Current Popula- tion Survey (CPS), were mandated by Congress for the purpose of allocat- ing federal funds for matching state expenditures under the Children’s Health Insurance Program (CHIP), but they have become a critical source of data for monitoring the states’ progress in reducing the number of low-income uninsured children. Because the CPS ASEC samples for most states are not large enough to support estimates of low-income uninsured children at satisfactory levels of precision, the Census Bureau combines 3 years of data to produce the estimates for each year. Even with 3 years of data, however, the estimates for many states are still not as precise as might be desired, and the need to combine 3 years of data makes the esti - mates less sensitive to year-to-year change in the number of low-income uninsured children. While this reduced sensitivity may have merits for funding allocation, it limits the usefulness of the estimates for monitoring state levels of health insurance coverage among low-income children. With the recent reauthorization of CHIP, Congress made provision for potential enhancements to the annual estimates of low-income unin - sured children while simultaneously ending their role in CHIP funding allocation. One of the options that the law mandates the Census Bureau to consider is to supplement or replace the CPS estimates with alternative 10

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110 EStIMAtInG HEALtH InSurAnCE CoVErAGE for CHILDrEn estimates drawn from the American Community Survey (ACS)—a rela- tively new Census Bureau survey with an annual sample that is 30 times that of the CPS ASEC supplement. With its ability to support not only state, but also substate estimates, the ACS would appear particularly well suited to serve as the principal source of data for monitoring the number of low-income uninsured children. For this reason, measures of health insurance coverage were added to the ACS questionnaire in 2008. Although much attention is being focused on the quality of these new estimates of health insurance coverage as a major factor in the choice between the CPS or the ACS, the quality of the income data collected in the ACS may be as important in determining its ultimate viability as a source of annual estimates of low-income children and low-income unin- sured children. Arguably, the measurement of income is more challenging than the measurement of health insurance coverage, which requires only binary responses as opposed to dollar amounts. For income measure- ment, the CPS holds clear advantages over the ACS. For one, the CPS is the official source of annual estimates of income and poverty in the United States, whereas the ACS collects comparatively little information on personal income and does so through a questionnaire that two-thirds of the respondents complete without the assistance of an interviewer and submit by mail. Given these potential limitations, do the ACS income data measure up to the CPS sufficiently well to warrant their use in producing the mandated annual estimates of low-income children and low-income uninsured children? Policy analysts also have reason to be interested in the ACS as a potential data source for a wide variety of analyses of state and local variation in health insurance coverage, and income is likely to play a key role in many such analyses. For such applications, the demands placed on the ACS income data are likely to exceed those that must be met in providing satisfactory estimates of low-income children. This paper compares estimates of income obtained from the ACS and the CPS. Selected comparisons include a third survey as well—the National Health Interview Survey (NHIS), which is sponsored and designed by the National Center for Health Statistics (NCHS) with field - work conducted by the Census Bureau. In certain respects the design of the NHIS resembles that of the ACS, with interviews conducted on a rolling basis throughout the calendar year. The measurement of health insurance coverage is a major element of the NHIS, but the measurement of income is much more limited than even that in the ACS. Two other surveys, the Survey of Income and Program Participation (SIPP) and the Household Component of the Medical Expenditure Panel Survey (MEPS) also collect data on both income and health insurance coverage, but their longitudinal designs are less well suited to monitoring the number of low-

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111 InCoME AnD PoVErty MEASurEMEnt income uninsured children than those of the CPS, the ACS, or the NHIS, and, like the NHIS, their samples are not designed for state-level estima - tion. For this reason, this paper does not include comparative estimates from these other surveys. Following an overview of income measurement and other features that differentiate among the three surveys, I present findings from two empirical analyses comparing the surveys. The first set of findings is drawn from a recent, comprehensive, and systematic assessment of the income data in eight major surveys and their utility for policy-related analyses. This research was conducted by Mathematica Policy Research, Inc., and its subcontractor, Denmead Services & Consulting, under a con - tract with the Office of the Assistant Secretary for Planning and Evalua - tion in the U.S. Department of Health and Human Services.1 The second set of findings, which is restricted to the CPS and the ACS, was prepared to examine specific issues related to the use of income data in the analysis of health insurance coverage.2 The paper closes with a brief assessment of the implications of these findings for applications of income and health insurance data from the three surveys. INCOME MEASUREMENT IN HOUSEHOLD SURVEyS Despite its wide use in analysis of social and economic phenomena and its critical role in policy analysis, income is difficult to measure well in household surveys. Surveys with a major focus on income devote hun - dreds of questions to its measurement, whereas surveys that emphasize other topics may devote just a few questions to capturing income. Ideally, those who design the income modules of surveys would be able to draw on established practice to determine how to obtain with a given number of questions the best all-around measure of income or the best measure focusing on a specific application. Such is not the case, however. The most rigorous study of income measurement conducted in the United States to date, by the Income Survey Development Program, was focused on the collection of comprehensive data on income and laid the cornerstone for the design of the SIPP, but it did not shed much light on how a survey could most effectively get by with less. Indeed, the Mathematica study suggests that the SIPP approach, with its focus on monthly income, may be less effective than simpler approaches to measuring, say, annual earn - ings or even total annual income. Below I provide a brief overview of income measurement in the CPS, the ACS, and the NHIS and then discuss 1 Czajka and Denmead (2008). 2 Some of these findings were presented at the annual meeting of the American Association for Public Opinion Research, May 13-16, 2010, Chicago.

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112 EStIMAtInG HEALtH InSurAnCE CoVErAGE for CHILDrEn other differences among the surveys that have implications for the respec- tive survey estimates of income and poverty. DIFFERENCES IN THE MEASUREMENT OF INCOME ACROSS SURVEyS As the official source of annual income and poverty estimates for the United States, the CPS in a sense defines how these constructs should be measured. Thus one can refer to the CPS income concept (pretax money income as defined in the survey), the CPS family (two or more persons living in the same household and related by blood, marriage, or adop - tion), and CPS residence rules (which include in a household any usual members who are temporarily living elsewhere). The CPS collects data on the presence of more than 50 sources of income and captures up to 24 annual dollar amounts for each sample member age 15 and older. The reported incomes of individual family members at the time of the interview are summed to obtain a measure of total family income for the preceding calendar year. By contrast, the ACS collects income for up to eight sources for each sample person age 15 and older, combining many sources for which the CPS collects separate reports. The eight sources listed in the questionnaire are 1. wages, salary, commissions, bonuses, or tips from all jobs (prior to deductions); 2. self-employment income from own nonfarm businesses or farm businesses, including proprietorships or partnerships; 3. Interest, dividends, net rental income, royalty income, or income from estates and trusts; 4. Social Security or Railroad Retirement; 5. Supplemental Security Income; 6. any public assistance or welfare payments from the state or local welfare office; 7. retirement, survivor, or disability pensions; and 8. any other sources of income received regularly such as veterans’ payments, unemployment compensation, child support, or ali- mony (not to include lump-sum payments). This last source serves as a catchall for individual sources that are not explicitly mentioned in the ACS but are identified explicitly in the CPS questionnaire. In addition, each of the preceding sources is captured by multiple questions in the CPS. CPS interviews are conducted in person or by telephone using

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11 InCoME AnD PoVErty MEASurEMEnt computer-assisted personal interviewing (CAPI) or computer-assisted telephone interviewing (CATI). By contrast, about two-thirds of the ACS responses are collected by mail, using a mailout-mailback questionnaire. Most of the remaining responses are collected by CAPI, with the remain- der being collected by CATI. The CATI/CAPI responses are collected from a sample of nonrespondents to the mail questionnaire. Unlike the CPS, responding to the ACS is mandatory by law, and the Census Bureau obtains an overall response rate of about 97 percent (weighted to reflect the sampling of nonrespondents to the mail questionnaire). The response rate for the monthly labor force component of the CPS reaches the low 90s, but an additional 8 percent or more of the respondents to the labor force questionnaire do not complete the ASEC supplement interview. The NHIS collects total family income from a single question asked of the family respondent. Earnings from employment are collected from all persons aged 18 and older, but this is separate from and not recon - ciled with reported family income. The NHIS interviews are conducted in person using CAPI, and they make extensive use of flash cards—but not for income. Both the CPS and the NHIS ask their respondents to report their income for the previous calendar year. In the ACS, respondents are asked to report their income for the past 12 months. For persons completing the ACS at the beginning of the year, the past 12 months are January through December of the prior year; for persons completing the survey at the end of the year, the past 12 months are December of the prior year through November of the current year. Thus, the income data collected from ACS households during a given calendar year span a 23-month period centered on December of the prior year.3 To convert the ACS income to a common reference period—specifically, the calendar year in which the data were collected—the Census Bureau applies an inflation adjustment, defined as the ratio of the average monthly price index for the survey year to the average index for the reference period. These monthly adjustment factors are used internally and are applied to published estimates, but the ACS public-use file contains only an average adjustment factor for the 12 survey months, because the Census Bureau has elected not to reveal the survey month. To calculate income relative to poverty, the Census Bureau adjusts the poverty thresholds rather than the reported income. That is, the income reported for a given reference period is divided by the average monthly 3 Income reported in ACS published data and online tables that are based on internal files is adjusted across the rolling reference period to the same real dollars, based on the consumer price index. Income in ACS public-use files is not adjusted for inflation, although an average inflation factor is provided.

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11 EStIMAtInG HEALtH InSurAnCE CoVErAGE for CHILDrEn threshold for that reference period. The estimates of income relative to poverty derived in this manner are reported on the public-use file. OTHER DIFFERENCES AMONG THE SURVEyS In addition to these differences in the measurement of income, there are several additional differences that users need to take into account. First, the surveys represent populations at different times. The CPS ASEC is conducted primarily in March, with additional interviews in Feb- ruary and April. The survey is weighted to represent the population as of March 1.4 Both the ACS and the NHIS represent an average of populations over a calendar year. The ACS is weighted to July 1 population totals, and the four segments of the NHIS are weighted, separately, to February 1, May 1, August 1, and November 1 of the survey year, then combined to create a single annual weight on the public-use file, with an effective reference date of mid-June. Second, the CPS includes in the household any college students liv - ing away from home, whereas the NHIS and the ACS do not. The NHIS samples and interviews students independently and conducts interviews in dormitories to collect data from students in campus housing, which the CPS does not do. The ACS follows decennial census practice in counting college students where they live at the time of the interview, although it did not begin to collect data from residents of dormitories and other group quarters until 2005.5 Third, both the CPS and the ACS define the family unit to include only those persons residing in the same housing unit who are related by blood, marriage, or adoption. The NHIS family definition is more expansive, including unmarried partners (and any relatives living with them) and foster children in the same family. Differences in the residence rules and the family definition affect the number and composition of CPS, ACS, and NHIS families. This, in turn, has implications for the measurement of poverty, which is defined at the family level. Fourth, while employing the same family definition as the CPS, the ACS does not collect data on relationships among persons who are unre - lated to the householder. Thus, if a household includes the householder 4 CPS ASEC interviews are conducted in February, March, and April in the week that includes the 19th. Historically, the annual income supplement was conducted solely in March, so a March-based weight was appropriate. The population estimates that are used as controls in the CPS and other surveys have a reference data corresponding to the first of each month as key components of these population estimates—births and deaths—are collected by calendar month. 5 Until 2005, students living in dormitories were excluded from the ACS universe, and the population totals used in weighting the survey were adjusted accordingly.

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11 InCoME AnD PoVErty MEASurEMEnt and a husband, wife, and child who are all unrelated to the householder, the ACS would report this as a householder and three unrelated individu- als, and none of the relationships among the three family members would be recorded. SURVEy ESTIMATES OF INCOME AND POVERTy, 2002 The estimates reported in this section, for calendar year 2002, were adjusted in order to make the estimates as comparable as possible. Under the heading Adjustments to Enhance Comparability, the adjustments that were applied to the surveys included in this paper are described. Total Income compares survey estimates of total income, both in the aggregate and by quintile of family income. The next section examines earned and unearned income aggregates and quintiles. Under Poverty, survey esti - mates of the number of persons and the fraction of the population classi- fied as poor and near-poor among the population as a whole and among children, nonelderly adults, and the elderly are compared. It also pro- vides estimates of the impact of the NHIS family definition on measured poverty. Finally, Aspects of Data Quality examines alternative measures of income data quality, including allocation of missing data due to item nonresponse and the prevalence of rounding. Adjustments to Enhance Comparability The adjustments that were applied to the eight surveys covered by Czajka and Denmead (2008) were designed to make the estimates compa- rable in terms of income reference period, universe, income concept, and family concept. Most of the adjustments addressed features of the surveys other than the three covered here. I mention adjustments that affected the CPS, the ACS, and the NHIS. ACS income data were multiplied by the aver- age adjustment factor described above. Because of differential inclusion and weighting of members of the active-duty armed forces, all families includ- ing such members were removed. Unrelated children under age 15 were also removed, as they are excluded from official estimates of poverty. The most complex adjustment involved the creation of CPS families within the subset of NHIS families that included members based on the broader NHIS family concept—specifically, unmarried partners and their children as well as foster children. In each case, the family members were reassembled into two or more CPS families, and the income of the original family was appor- tioned among the new families. I did not attempt to adjust for differences in survey timing, which means that the NHIS estimates will reflect a slightly larger population than the CPS estimates, and both surveys’ estimates will reflect a larger population than the ACS estimates.

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11 EStIMAtInG HEALtH InSurAnCE CoVErAGE for CHILDrEn Total Income As a summary statistic, total or aggregate income is appealing for its simplicity and its use of all of the income data collected in each sur- vey. However, aggregate income is heavily dependent on the amount of income captured from the upper end of the income distribution, which holds the least interest for policy analysis. In presenting estimates of aggregate income, I include a breakdown by quintile of family income, which makes it possible to compare the surveys with respect to their collection of income from different segments of the income distribution. Table 10-1 presents estimates of aggregate income for the whole popula- tion and by quintile of family income for the three surveys.6 It also shows these amounts as a percentage of the corresponding amounts for the CPS. There is no gold standard for estimates of income, nor do I mean to sug - gest that the CPS estimates are the best. But because the CPS is the official source of household income and poverty statistics for the United States, expressing other survey estimates of income as a percentage of the CPS provides a useful standardization. Aggregate income ranges from $6.12 trillion in the NHIS to $6.47 trillion in the CPS—a spread of just 5 percent. That is, with a single ques - tion the NHIS captures 95 percent as much total income as the CPS; with a simple instrument primarily filled out by respondents rather than a trained interviewer, the ACS captures 98 percent as much total income as the CPS. In examining income by quintile, one finds that the ACS aggregates lie within a percentage point of the CPS aggregates (both above and below) through the first three quintiles before dropping to 98 and 97 per- cent, respectively, of the CPS in the fourth and fifth quintiles. The NHIS compares least favorably in the bottom quintile, capturing only 85 percent as much total income as the CPS (and the ACS). This fraction rises to a peak of 98 percent in the fourth quintile before falling back to 94 percent in the top quintile. Aggregates in the top quintile may be affected by outliers and by differences in survey practice with respect to the topcoding of public-use data. For example, the CPS assigns the means of topcoded values as their respective topcodes, which preserves overall means and totals, but not all surveys do this for all income items. For this reason, the survey aggregates are summed through the bottom four quintiles. Through four quintiles, the ACS captures 99.1 percent as much total income as the CPS, and the NHIS improves only marginally to 95.3 percent. 6 In each survey, each of the five quintiles contains the same number of people (weighted) except when the numbers are affected by heaping at quintile boundaries.

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11 InCoME AnD PoVErty MEASurEMEnt TABLE 10-1 Aggregate Income by Quintile of Family Income: Three Surveys Income Estimate CPS ACS NHIS Billions of Dollars Aggregate Income, All Persons 6,468.40 6,346.30 6,116.20 Family Income Quintile Lowest 370.50 368.70 313.70 Second 774.10 778.40 717.70 Third 1,090.20 1,087.40 1,058.40 Fourth 1,446.80 1,415.80 1,420.70 Highest 2,786.70 2,696.00 2,605.80 Sum Through Four Quintiles 3,681.70 3,650.30 3,510.40 Percentage of CPS Aggregate Income, All Persons 100.00 98.10 94.80 Family Income Quintile Lowest 100.00 99.50 84.70 Second 100.00 100.60 92.70 Third 100.00 99.70 97.10 Fourth 100.00 97.90 98.20 Highest 100.00 96.70 93.50 Sum Through Four Quintiles 100.00 99.10 95.30 SOURCE: Mathematica Policy Research, Inc., from tabulations of calendar year 2002 income from the 2003 CPS ASEC supplement; the 2003 NHIS; and prior 12 months income, inflation- adjusted to calendar year 2002, from the 2002 ACS. Because the CPS and the NHIS are weighted to population totals almost a year later than the ACS, the ACS is at a comparative disad - vantage for the measurement of aggregate income. One can compensate by putting aggregate income on a per capita basis. Table 10-2 compares the three surveys with respect to per capita income by quintile. By this measure, the ACS captures 99.8 percent as much total income as the CPS, and the NHIS, which is weighted to slightly larger population totals than the CPS, declines to 94.2 percent of the CPS total. ACS per capita income equals or exceeds CPS per capita income through the first three quintiles and is within 0.4 percentage points in the fourth quintile and within 1.6 percentage points in the top quintile. Putting income on a per capita basis has an uneven impact on the NHIS estimates, which implies that the weighted NHIS sample is not distributed as uniformly by quintile as the other two surveys. A likely explanation is discussed below.

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11 EStIMAtInG HEALtH InSurAnCE CoVErAGE for CHILDrEn TABLE 10-2 Average Income Per Capita by Quintile of Family Income: Three Surveys Income Estimate CPS ACS NHIS Billions of Dollars Aggregate Income, All Persons 22,893.00 22,854.00 21,558.00 Family Income Quintile Lowest 6,513.00 6,526.00 5,528.00 Second 13,789.00 14,259.00 12,649.00 Third 19,293.00 19,576.00 18,493.00 Fourth 25,604.00 25,496.00 25,151.00 Highest 49,316.00 48,543.00 46,114.00 Percentage of CPS Aggregate Income, All Persons 100.00 99.80 94.20 Family Income Quintile Lowest 100.00 100.20 84.90 Second 100.00 103.40 91.70 Third 100.00 101.50 95.90 Fourth 100.00 99.60 98.20 Highest 100.00 98.40 93.50 SOURCES: Mathematica Policy Research, Inc., from tabulations of calendar year 2002 in - come from the 2003 CPS ASEC supplement; the 2003 NHIS; and prior 12 months income, inflation-adjusted to calendar year 2002, from the 2002 ACS. Earned and Unearned Income Economists divide income into earned and unearned. Earnings include wages and salaries plus self-employment income. Earnings account for 82.8 percent of total income in the CPS, 82.1 percent in the ACS, and 86.0 percent in the NHIS (see Table 10-3).7 The similarity between the ACS and the CPS hides a difference in the composition of earnings in the two surveys. The ACS captures 4 percent less wage and salary income than the CPS but 19 percent more self-employment income, which raises the ACS earned income to 97.3 percent of the CPS total. The ACS also captures slightly more (2.2 percent) unearned income than the CPS, which contributes to an overall total income that is 98.1 percent of the CPS total. The NHIS does not collect unearned income, but the difference between total income and earned income collected in the NHIS implies unearned income that is 77 percent 7 Recall that total family income and earnings by individual family members are measured independently in the NHIS and not reconciled.

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11 InCoME AnD PoVErty MEASurEMEnt TABLE 10-3 Contribution of Earned and Unearned Income to Total Income: Three Surveys Income Estimate CPS ACS NHIS Billions of Dollars Total Income 6,468.40 6,346.30 6,118.20 Earned Income 5,354.30 5,207.90 5,261.40 Wages and salaries 5,026.30 4,817.20 n/a Self-employment 328.00 390.70 n/a Unearned Income 1,114.10 1,138.30 854.80 Percentage of Total Income Total Income 100.00 100.00 100.00 Earned Income 82.80 82.10 86.0 Wages and salaries 77.70 75.90 n/a Self-employment 5.10 6.20 n/a Unearned Income 17.20 17.90 14.0 Percentage of CPS Income by Source Total Income 100.00 98.10 94.60 Earned Income 100.00 97.30 98.30 Wages and salaries 100.00 95.80 n/a Self-employment 100.00 119.10 n/a Unearned Income 100.00 102.20 76.70 NOTE: n/a = not available. SOURCES: Mathematica Policy Research, Inc., from tabulations of calendar year 2002 in - come from the 2003 CPS ASEC supplement; the 2003 NHIS; and prior 12 months income, inflation-adjusted to calendar year 2002, from the 2002 ACS. of the CPS total. This implied shortfall is simply an indication that the NHIS does not do as well in obtaining total income with its single ques- tion as it does in collecting earned income from all adults. 8 Comparing survey estimates of earned income by quintile of family income, one finds, interestingly, that both the ACS and the NHIS have more earnings in the lowest quintile of family income than does the CPS (see Table 10-4). The additional earnings range from 12 to 17 percent of the CPS total. The ACS has progressively less total earnings relative to the CPS as the quintile increases. The NHIS, in contrast, has progressively more aggregate earnings relative to the CPS over quintiles two through four. 8 In the 2002 NHIS, more than a fifth of individuals were in families with more reported total earnings than total family income. Each of these families would have implied negative unearned income.

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10 EStIMAtInG HEALtH InSurAnCE CoVErAGE for CHILDrEn TABLE 10-13 Reporting of Rounded Values by Source of Income by Survey Among Positive Dollar Amounts Below $52,500 Income Source and Level of Rounding CPS ACS NHIS Earnings Percentage divisible by $5,000 27.80 29.60 39.80 Percentage divisible by $10,000 15.80 17.40 22.90 Percentage of income in range 82.10 82.40 80.90 Wages and Salaries Percentage divisible by $5,000 27.20 29.70 n/a Percentage divisible by $10,000 15.40 17.40 n/a Percentage of income in range 82.20 82.70 n/a Social Security Percentage divisible by $5,000 0.60 4.30 n/a Percentage divisible by $10,000 0.40 1.90 n/a Percentage of income in range 100.00 100.00 n/a Retirement Income Percentage divisible by $5,000 4.50 8.00 n/a Percentage divisible by $10,000 2.70 4.30 n/a Percentage of income in range 95.60 95.40 n/a Total Personal Income Percentage divisible by $5,000 13.70 19.70 n/a Percentage divisible by $10,000 7.80 11.50 n/a Percentage of income in range 84.60 84.20 n/a Total Family Income Percentage divisible by $5,000 11.00 16.20 35.60 Percentage divisible by $10,000 6.20 9.50 20.90 Percentage of income in range 66.90 66.00 60.30 NOTES: Allocated amounts are excluded from each source. Family income for the NHIS is based on the NHIS family, which is the level at which family income was reported. n/a = not available. SOURCES: Mathematica Policy Research, Inc., from tabulations of calendar year 2002 in - come from the 2003 CPS ASEC supplement and the 2003 NHIS and prior 12 months income, inflation-adjusted to calendar year 2002, from the 2002 ACS. by comparing young adults aged 18 to 24 by college enrollment, relative income, and the percentage lacking health insurance coverage. Poor and Near-Poor For 2007 the ACS estimated a slightly higher poverty rate than the CPS, at 13.0 versus 12.5 percent, and a slightly smaller fraction between

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11 InCoME AnD PoVErty MEASurEMEnt 100 and 200 percent of poverty (near-poor), at 17.7 versus 18.0 percent (see Table 10-14). The total fraction of the population estimated as low income (below 200 percent of poverty) was essentially identical in the two surveys: 30.6 percent in the ACS versus 30.5 percent in the CPS. For 2008, when the United States entered a deep recession in the latter part of the year, the CPS showed an increase of 0.7 percentage points in both the percentage poor and the percentage near-poor, yielding an increase of 1.4 percentage points in the percentage of the population classified as low income. The ACS, with its longer reference period, showed little change between 2007 and 2008, with the poverty rate rising by just 0.2 percentage points and the fraction near-poor remaining essentially unchanged. The fraction of the population classified as low income rose by just 0.3 per- centage points in the ACS, leaving the ACS a full percentage point below the CPS. These changes are consistent with the expectation that the ACS should be slower to respond to economic changes. In effect, the same pattern can be seen among children, with no differ- ence between the two surveys in the percentage with low income in 2007 but the CPS moving more than a full percentage point above the ACS in 2008 (Table 10-15). Among nonelderly adults, the ACS had a percentage point higher fraction classified as low income in 2007 but showed only a 0.4 TABLE 10-14 Estimates of the Poor and Near-Poor: CPS and ACS, 2007 and 2008 2007 2008 Estimate CPS ACS CPS ACS Millions of Persons All Persons 297.81 293.42 300.10 295.32 Poverty Status Poor 37.22 38.01 39.74 39.03 Near-poor 53.64 51.84 56.04 52.33 Total Low Income 90.86 89.85 95.77 91.36 Percentage of the Population All Persons 100.00 100.00 100.00 100.00 Poverty Status Poor 12.50 13.00 13.20 13.20 Near-poor 18.00 17.70 18.70 17.70 Total Low Income 30.50 30.60 31.90 30.90 NOTES: The poor have a family income below the poverty threshold. The near-poor have a family income at or above the poverty threshold but below twice the poverty threshold. SOURCES: Mathematica Policy Research, Inc., from tabulations of poverty status in calen - dar years 2007 and 2008 from the 2008 and 2009 CPS ASEC supplements and the 2007 and 2008 ACS.

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12 EStIMAtInG HEALtH InSurAnCE CoVErAGE for CHILDrEn TABLE 10-15 Estimates of the Poor and Near-Poor Children Under 18: CPS and ACS, 2007 and 2008 2007 2008 Estimate CPS ACS CPS ACS Millions of Persons All Children Under Age 18 73.99 72.66 74.07 72.80 Poverty Status Poor 13.32 13.03 14.05 13.23 Near-poor 15.66 15.47 16.00 15.53 Total Low Income 28.98 28.50 30.05 28.76 Percentage of the Population All Children Under Age 18 100.00 100.00 100.00 100.00 Poverty Status Poor 18.00 17.90 19.0 18.20 Near-poor 21.20 21.30 21.60 21.30 Total Low Income 39.20 39.20 40.60 39.50 NOTES: The poor have a family income below the poverty threshold. The near-poor have a family income at or above the poverty threshold but below twice the poverty threshold. SOURCES: Mathematica Policy Research, Inc., from tabulations of poverty status in calen - dar years 2007 and 2008 from the 2008 and 2009 CPS ASEC supplements and the 2007 and 2008 ACS. percentage point increase in this fraction between 2007 and 2008, while the CPS fraction increased by 1.6 percentage points (see Table 10-16). Among the elderly, for whom the ACS finds substantially fewer near-poor, the ACS had a 4 percentage point lower fraction with low income in 2007 (see Table 10-17). This difference increased by 0.4 percentage points between 2007 and 2008. The more modest increase among the elderly versus the nonelderly is consistent with the elderly receiving more of their income from sources that are less affected by recession than children and working-age adults. Uninsured by Relative Income For the civilian noninstitutionalized population as a whole, the unin - sured rate measured in the CPS for 2008 was 15.4 percent. Using a very different approach to measuring health insurance coverage, the ACS obtained an uninsured rate of 15.2 percent (see Table 10-18). The other papers in this session address the differences in measurement and pos - sible reasons why the uninsured rates are nevertheless so close. When per- sons are classified by income relative to poverty, similar uninsured rates are also found in each of the four classes. The ACS has a somewhat lower rate among the poor (29.1 versus 30.5 percent) but a slightly higher rate

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1 InCoME AnD PoVErty MEASurEMEnt TABLE 10-16 Estimates of the Poor and Near-Poor Nonelderly Adults: CPS and ACS, 2007 and 2008 2007 2008 Estimate CPS ACS CPS ACS Millions of Persons All Adults Aged 18 to 64 187.03 184.53 188.25 185.32 Poverty Status Poor 20.35 21.52 22.03 22.12 Near-poor 28.28 28.23 30.00 28.63 Total Low Income 48.63 49.75 52.03 50.75 Percentage of the Population All Adults Aged 18 to 64 100.00 100.00 100.00 100.00 Poverty Status Poor 10.90 11.70 11.70 11.90 Near-poor 15.10 15.30 15.90 15.50 Total Low Income 26.00 27.0 27.60 27.40 NOTE: The poor have a family income below the poverty threshold. The near-poor have a family income at or above the poverty threshold but below twice the poverty threshold. SOURCES: Mathematica Policy Research, Inc., from tabulations of poverty status in calen - dar years 2007 and 2008 from the 2008 and 2009 CPS ASEC supplements and the 2007 and 2008 ACS. among the near-poor (25.9 versus 24.3 percent). For the combined, low- income population, the uninsured rates for the two surveys are therefore quite similar: 26.9 percent for the CPS and 27.3 percent for the ACS. The rates are essentially identical among persons between 200 and 400 percent of poverty, whereas the ACS rate is modestly lower among persons above 400 percent of poverty: 5.5 percent versus 6.0 percent in the CPS. Among children, the ACS uninsured rate is fractionally higher than the CPS at 9.9 versus 9.8 percent (see Table 10-19). Uninsured rates are equally similar among poor children, whereas the ACS uninsured rate is more than a percentage point higher among the near-poor: 15.9 versus 14.7 percent. As with the population as a whole, the ACS is 0.1 percentage point higher among children between 200 and 400 percent of poverty and 0.5 percentage points lower among children above 400 percent of poverty. The pattern changes for nonelderly adults, for whom the poor in the ACS are somewhat less likely to be uninsured than the poor in the CPS: 41.3 versus 44.0 percent (see Table 10-20). The ACS is a percentage point higher among the near-poor, and the differences among those above 200 percent of poverty are identical to those for children, even though the uninsured rates for nonelderly adults are more than twice as high as they are for children.

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1 EStIMAtInG HEALtH InSurAnCE CoVErAGE for CHILDrEn TABLE 10-17 Estimates of the Poor and Near-Poor Elderly: CPS and ACS, 2007 and 2008 2007 2008 Estimate CPS ACS CPS ACS Millions of Persons All Persons Aged 65 and Older 36.79 36.23 37.79 37.20 Poverty Status Poor 3.56 3.46 3.66 3.68 Near-poor 9.70 8.14 10.03 8.16 Total Low Income 13.26 11.59 13.69 11.84 Percentage of the Population All Persons Aged 65 and Older 100.00 100.00 100.00 100.00 Poverty Status Poor 9.70 9.50 9.70 9.90 Near-poor 26.40 22.50 26.60 21.90 Total Low Income 36.00 32.00 36.20 31.80 NOTE: The poor have a family income below the poverty threshold. The near-poor have a family income at or above the poverty threshold but below twice the poverty threshold. SOURCES: Mathematica Policy Research, Inc., from tabulations of poverty status in calen - dar years 2007 and 2008 from the 2008 and 2009 CPS ASEC supplements and the 2007 and 2008 ACS. TABLE 10-18 Number and Percentage Uninsured by Relative Income: All Persons, CPS and ACS, 2008 Estimate CPS ACS Uninsured Persons (millions) All Persons 46.25 44.76 Income Relative to Poverty Under 100% 12.12 11.37 100 to under 200% 13.64 13.54 200 to under 400% 13.80 13.63 400 or more 6.68 6.22 Low Income (under 200%) 25.76 24.91 Percentage Uninsured All Persons 15.40 15.20 Income Relative to Poverty Under 100% 30.50 29.10 100 to under 200% 24.30 25.90 200 to under 400% 14.80 14.90 400 or more 6.00 5.50 Low Income (under 200%) 26.90 27.30 SOURCE: Mathematica Policy Research, Inc., from tabulations of poverty status in calendar year 2002 from the 2003 NHIS.

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1 InCoME AnD PoVErty MEASurEMEnt TABLE 10-19 Number and Percentage Uninsured by Relative Income: Children Under 18, CPS and ACS, 2008 Estimate CPS ACS Uninsured Persons (millions) All Children Under Age 18 7.25 7.20 Income Relative to Poverty Under 100% 2.21 2.10 100 to under 200% 2.35 2.48 200 to under 400% 1.99 2.01 400 or more 0.70 0.61 Low Income (under 200%) 4.56 4.58 Percentage Uninsured All Children Under Age 18 9.80 9.90 Income Relative to Poverty Under 100% 15.70 15.90 100 to under 200% 14.70 15.90 200 to under 400% 8.60 8.70 400 or more 3.40 2.90 Low Income (under 200%) 15.20 15.90 SOURCE: Mathematica Policy Research, Inc., tabulations of the 2009 CPS ASEC supplement and the 2008 ACS. Uninsured rates among the elderly are not given much attention in the literature, as they are exceedingly low due to the broad coverage provided by Medicare, and the estimates are probably dominated by mea- surement error. Compared with the CPS, the ACS finds a markedly lower uninsured rate among the poor elderly—3.6 versus 6.2 percent—but at higher levels of relative income, the estimates are remarkably similar (see Table 10-21). Residency Among young Adults By asking that college students living away from home be counted at their place of residence at the time of the survey, the ACS departs from the CPS in a way that could lead to higher estimates of the college stu - dent population. College students living away from home are given two opportunities to be counted, in effect: once at school and once at home. While the ACS asks that students be counted at school, parents respond - ing to the survey may choose to count their children at home regardless. The fact that the ACS includes college dormitories in its sample frame while the CPS does not means that every college student has a chance to be counted twice in the ACS, whereas students in dormitories are pre - cluded from this possibility in the CPS.

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1 EStIMAtInG HEALtH InSurAnCE CoVErAGE for CHILDrEn TABLE 10-20 Number and Percentage Uninsured by Relative Income: Nonelderly Adults, CPS and ACS, 2008 Estimate CPS ACS Uninsured Persons (millions) All Nonelderly Adults 38.35 37.03 Income Relative to Poverty Under 100% 9.68 9.14 100 to under 200% 11.12 10.91 200 to under 400% 11.66 11.47 400 or more 5.88 5.50 Low Income (under 200%) 20.80 20.05 Percentage Uninsured All Nonelderly Adults 20.40 20.00 Income Relative to Poverty Under 100% 44.00 41.30 100 to under 200% 37.10 38.10 200 to under 400% 20.30 20.40 400 or more 7.50 7.00 Low Income (under 200%) 40.00 39.50 SOURCE: Mathematica Policy Research, Inc., from tabulations of the 2009 CPS ASEC supple- ment and the 2008 ACS. Comparative estimates from the two surveys for 2008 show 1.8 mil - lion more young adults aged 18-24 enrolled in college in the ACS than the CPS; 1.0 million fewer young adults not enrolled in college in the ACS than the CPS; and almost 0.9 million more young adults in total in the ACS than the CPS (see Table 10-22). Despite students in dormitories being excluded from the ACS poverty universe, it still finds a higher fraction of young adults to be poor (20.0 versus 18.4 percent). Virtually all of the difference is due to college students, whose poverty rate is 5 percentage points higher in the ACS than the CPS despite the exclusion of 18.7 per- cent of students from the ACS poverty universe. Among those who are not enrolled in college, virtually none is excluded from the ACS poverty universe, and the distribution of persons across the four classes of relative income is quite similar between the ACS and the CPS. It is clear from the comparative distributions that the students excluded from the poverty universe in the ACS are drawn from higher income levels, as that is where the ACS falls well short of the CPS. A comparison of uninsured rates by college enrollment and relative income provides clear evidence that the college students identified as poor in the ACS look more like students from higher income families in the CPS. The uninsured rate of 19.9 percent for poor college students in the ACS compares with 32.5 percent in the CPS, whereas both surveys

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1 InCoME AnD PoVErty MEASurEMEnt TABLE 10-21 Number and Percentage Uninsured by Relative Income: Elderly Persons, CPS and ACS, 2008 Estimate CPS ACS Uninsured Persons (millions) All Persons Aged 65 and Older 0.65 0.54 Income Relative to Poverty Under 100% 0.22 0.13 100 to under 200% 0.17 0.15 200 to under 400% 0.15 0.15 400 or more 0.10 0.11 Low Income (under 200%) 0.39 0.28 Percentage Uninsured All Persons Aged 65 and Older 1.70 1.40 Income Relative to Poverty Under 100% 6.20 3.60 100 to under 200% 1.70 1.80 200 to under 400% 1.20 1.20 400 or more 0.90 0.80 Low Income (under 200%) 2.90 2.40 SOURCE: Mathematica Policy Research, Inc., from tabulations of the 2009 CPS ASEC supple- ment and the 2008 ACS. find uninsured rates around 20 percent for college students with incomes between 200 and 400 percent of poverty (see Table 10-23). Among those not enrolled in college, the ACS has somewhat higher uninsured rates in every category of relative income. I have no explanation for this. Regard - less of college enrollment, only 6 to 7 percent of young adults excluded from the ACS poverty universe are reported to be without health insur- ance coverage. IMPLICATIONS The principal findings can be summarized quite simply. At high levels of aggregation, the ACS produces estimates of income and health insur- ance coverage that look strikingly similar to those obtained from the CPS, despite notable differences in measurement. This suggests but by no means proves that, with its much larger sample size, the ACS could be used to develop direct estimates of low-income uninsured children at the state level and even lower levels of geography that would mimic what could be obtained from the CPS if it had a much bigger sample. Although the ACS seems to fare well with a modest set of income ques- tions, the NHIS illustrates potential adverse consequences from devoting

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1 EStIMAtInG HEALtH InSurAnCE CoVErAGE for CHILDrEn TABLE 10-22 Persons Aged 18 to 24 by College Enrollment and Relative Income: CPS and ACS, 2008 Estimate CPS ACS Millions of Persons All Persons Aged 18 to 24 28.47 29.31 Percentage of Persons Income Relative to Poverty 100.00 100.00 Outside the poverty universe 0.00 7.90 Under 100% 18.40 20.00 100 to under 200% 20.40 18.90 200 to under 400% 31.10 27.80 400% or more 30.00 25.40 Millions of Persons Enrolled in College 10.40 12.22 Percentage of Persons Income Relative to Poverty 100.00 100.00 Outside the poverty universe 0.00 18.70 Under 100% 15.60 20.70 100 to under 200% 16.70 12.90 200 to under 400% 28.10 21.10 400% or more 39.60 26.60 Millions of Persons Not Enrolled in College 18.07 17.08 Percentage of Persons Income Relative to Poverty 100.00 100.00 Outside the poverty universe 0.00 0.20 Under 100% 20.10 19.50 100 to under 200% 22.50 23.20 200 to under 400% 32.90 32.60 400% or more 24.50 24.60 SOURCE: Mathematica Policy Research, Inc., tabulations of the 2009 CPS ASEC supplement too few questions to income measurement—particularly among families at the low end of the income distribution. Also, differences between the ACS and the CPS begin to emerge as income and/or the population are disaggregated. Such differences are often but certainly not always consis- tent with differences in the two surveys’ approaches to measuring income, including reference period as well as the way that income is defined. For

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1 InCoME AnD PoVErty MEASurEMEnt TABLE 10-23 Percentage Uninsured among Persons Aged 18 to 24 by College Enrollment and Relative Income: CPS and ACS, 2008 Estimate CPS ACS All Persons Aged 18 to 24 28.80 28.60 Income Relative to Poverty Outside the poverty universe n/a 6.30 Under 100% 41.90 36.60 100 to under 200% 39.80 43.00 200 to under 400% 28.70 30.90 400% or more 13.40 15.90 Enrolled in College 19.10 15.90 Income Relative to Poverty Outside the poverty universe n/a 6.30 Under 100% 32.50 19.90 100 to under 200% 30.60 29.60 200 to under 400% 20.40 20.70 400% or more 8.10 9.00 Not Enrolled in College 34.40 37.70 Income Relative to Poverty Outside the poverty universe n/a 6.70 Under 100% 46.10 49.40 100 to under 200% 43.80 48.30 200 to under 400% 32.80 35.70 400% or more 18.30 21.20 NOTE: n/a = not available. SOURCE: Mathematica Policy Research, Inc., from tabulations of the 2009 CPS ASEC supple- ment and the 2008 ACS. example, in recent years the ACS lags the CPS in its response to changes in the economy—as it should, given the longer reference period in the ACS. This could be viewed as a drawback for many prospective uses of the ACS, but for state- and lower level estimates it is important to remem- ber that the Census Bureau combines 3 years of CPS data to produce the annual estimates of low-income uninsured children that the ACS would potentially replace. Compared with a 3-year moving average, the ACS data show greater rather than lesser sensitivity to economic change. The Census Bureau and the research community are only beginning to understand the implications of many aspects of ACS data collection. From the perspective of income measurement, the chief issues revolve around the ACS reference period and the ways that the Census Bureau has attempted to annualize the estimates, the residence rules for col- lege students living away from home, the small number of questions

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10 EStIMAtInG HEALtH InSurAnCE CoVErAGE for CHILDrEn used to capture the diverse sources of unearned income, and the absence of data on the relationships among persons who are unrelated to the householder. ACKNOWLEDGMENTS Much of the work presented herein was prepared by Mathematica Policy Research, Inc., under contract to the Office of the Assistant Secre - tary for Planning and Evaluation, U.S. Department of Health and Human Services and presented in a final report, “Income Data for Policy Analysis: A Comparative Assessment of Eight Surveys” dated December 23, 2008, and coauthored by Gabrielle Denmead. The findings and conclusions reported here are those of the author and do not necessarily represent the views of ASPE or HHS. REFERENCE Czajka, J.L., and Denmead, G. (2008). Income Data for Policy Analysis: A Comparative Assess- ment of Eight Surveys. Report from Mathematica Policy Research, Inc. Available: http:// www.mathematica-mpr.com/publications/pdfs/incomedata.pdf [October 2010].