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<h1 itemprop="headline">Improving the Measurement of Retirement Income of the Aged Population</h1>
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<div id="hByline">by <span itemprop="author">Irena Dushi and Brad Trenkamp</span><br><abbr class="spell">ORES</abbr> Working Paper <abbr title="Number">No.</abbr> 116 (released January 2021)</div>
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<p id="synopsis" itemprop="description">Research has shown that survey-reported income measures, particularly pension and retirement income, suffer from reporting errors, which lead to biased estimates of income and poverty of the aged population. Two of the Social Security Administration's main publications—<i><a href="/policy/docs/statcomps/income_pop55/index.html">Income of the Population 55 or Older</a></i> and the <i><a href="/policy/docs/chartbooks/income_aged/index.html">Income of the Aged Chartbook</a></i>—are published biennially and are based exclusively on publicly available data from the <abbr>U.S.</abbr> Census Bureau. In this paper, we use data from the Census' 2016 Current Population Survey (<abbr class="spell">CPS</abbr>) Annual Social and Economic Supplement (<abbr class="spell">ASEC</abbr>) merged with administrative data—Internal Revenue Service (<abbr class="spell">IRS</abbr>) tax records and Social Security earnings and benefit records—to examine whether and to what extent using these additional data improves income estimates. We also compare those estimates with public-use data from the 2016 Health and Retirement Study (<abbr class="spell">HRS</abbr>), which has the reputation of being a reliable source of income measures for the aged population. We find that for the population aged 65 or older, supplementing the <abbr class="spell">CPS</abbr> <abbr class="spell">ASEC</abbr> with <abbr class="spell">IRS</abbr> and Social Security administrative data results in a higher estimate of pension income's share of aggregate income, less estimated reliance on Social Security, and a lower estimated rate of poverty. Furthermore, we find that the <abbr class="spell">HRS</abbr> provides better estimates of the income of the aged population than the public-use <abbr class="spell">CPS</abbr> data.</p>
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<hr />
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<div class="eightypercent">
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<p>The authors are with the Office of Research, Office of Research, Evaluation, and Statistics, Office of Retirement and Disability Policy, Social Security Administration.</p>
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<p><i>Acknowledgments:</i> We received helpful comments from Lynn Fisher, Bruce Meyer, Joshua Mitchell, Kathleen Romig, Julie Topoleski, and Robert Weathers. We also thank Adam Bee and Joshua Mitchell for their guidance.</p>
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<p>Working papers are unedited papers prepared by staff in the Office of Research, Evaluation, and Statistics and published on our website as a resource for future research initiatives and to encourage discussion among the wider research community. The findings and conclusions presented in this paper are those of the authors and do not necessarily represent the views of the Social Security Administration.</p>
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<p>Questions or comments should be directed to the authors at <a href="mailto:research@ssa.gov">research@ssa.gov</a>.</p>
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</div>
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</div>
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<div class="abbrtable">
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<table>
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<caption>Selected Abbreviations</caption>
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<colgroup span="1" style="width:25%"></colgroup>
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<colgroup span="1"></colgroup>
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<tbody>
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<tr>
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<td><abbr class="spell">ASEC</abbr></td>
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<td>Annual Social and Economic Supplement</td>
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</tr>
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<tr>
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<td><abbr class="spell">CPS</abbr></td>
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<td>Current Population Survey</td>
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</tr>
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<tr>
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<td><abbr class="spell">HRS</abbr></td>
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<td>Health and Retirement Study</td>
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</tr>
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<tr>
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<td><abbr class="spell">IRA</abbr></td>
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<td>individual retirement account</td>
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</tr>
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<tr>
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<td><abbr class="spell">IRS</abbr></td>
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<td>Internal Revenue Service</td>
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</tr>
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<tr>
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<td><abbr class="spell">PUF</abbr></td>
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<td>public-use file</td>
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</tr>
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<tr>
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<td><abbr class="spell">SSA</abbr></td>
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<td>Social Security Administration</td>
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</tr>
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<tr>
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<td><abbr class="spell">SSI</abbr></td>
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<td>Supplemental Security Income</td>
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</tr>
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</tbody>
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</table>
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</div>
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<h2>Introduction</h2>
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<p>Measuring the income of the <abbr>U.S.</abbr> population overall and of the aged in particular is an important issue for both researchers and policymakers. Accurate measurement of retirement income in national surveys is a challenge. The <abbr>U.S.</abbr> Census Bureau's Current Population Survey (<abbr class="spell">CPS</abbr>) is no exception, and recent research has reinvigorated a debate about the adequacy of its retirement income measures. This has been of unique interest to the Social Security Administration (<abbr class="spell">SSA</abbr>), which publishes a biennial statistical series on the income sources of the aged population using data from the <abbr class="spell">CPS</abbr>.</p>
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<p><abbr class="spell">SSA</abbr>'s Office of Research, Evaluation, and Statistics (<abbr class="spell">ORES</abbr>) has published statistics on the income of the aged population based on public-use <abbr class="spell">CPS</abbr> data since 1976.<sup><a href="#mn1" id="mt1">1</a></sup> Two of its well-known and commonly cited publications are <i><a href="/policy/docs/statcomps/income_pop55/index.html">Income of the Population 55 or Older</a></i> and <i><a href="/policy/docs/chartbooks/income_aged/index.html">Income of the Aged Chartbook</a></i>. These publications provide estimates, overall and separately by demographic groups, of the prevalence and the amount of income from different sources (such as earnings, Social Security, pensions, and assets); total money income; the importance of different income sources relative to total income; shares of aggregate income by source; and poverty status; all broken out by various demographic characteristics.</p>
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<p>This paper examines the question of whether or not the <abbr class="spell">CPS</abbr> Annual Social and Economic Supplement (<abbr class="spell">ASEC</abbr>), also known as the “March <abbr class="spell">CPS</abbr>,”<sup><a href="#mn2" id="mt2">2</a></sup> is a reliable data source for reporting income statistics for the aged population. To do this we compare results taken directly from the <abbr class="spell">CPS</abbr> <abbr class="spell">ASEC</abbr> public-use file (<abbr class="spell">PUF</abbr>) with alternative data files that supplement the survey data with matched administrative records from <abbr class="spell">SSA</abbr> and the Internal Revenue Service (<abbr class="spell">IRS</abbr>). We also compare results of the publicly available version of the March <abbr class="spell">CPS</abbr> with that of the University of Michigan's Health and Retirement Study (<abbr class="spell">HRS</abbr>).</p>
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<p>This paper proceeds as follows. The next section discusses the relevant literature, including recent work that motivated this paper. The third section provides background and describes the data and methods we used for our analysis, focusing on income definitions from the various data files. The fourth section presents statistical results, focusing on comparisons of the distribution of aggregate income by source, population distribution by income, prevalence of income by source, the relative importance of Social Security, and poverty status. The final section discusses the implications of our results and provides concluding remarks. Appendices provide the income and poverty definitions used in the <abbr class="spell">CPS</abbr> and the <abbr class="spell">HRS</abbr>.</p>
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<h2>Literature Review</h2>
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<p>For years, there has been an ongoing discussion about the underreporting of retirement income in the <abbr class="spell">CPS</abbr>, with a wide acknowledgment that although underreporting exists, the <abbr class="spell">CPS</abbr> is still one of the best sources of information about the income of the <abbr>U.S.</abbr> population because of its large sample size, broad array of information collected, and periodicity. However, a 2017 study by Census Bureau economists Adam Bee and Joshua Mitchell renewed interest in that discussion. With the benefit of new linkages to administrative data, they were able to quantify the misreporting problem at the observation level, whereas prior research has focused on comparisons of aggregates across surveys and administrative data.</p>
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<p>The studies conducted prior to Bee and Mitchell (2017) did not have the benefit of direct linkages to administrative microdata, and many therefore relied on comparisons of survey and administrative-data aggregates to study income underreporting in the <abbr class="spell">CPS</abbr>. Several studies used the <abbr class="spell">IRS</abbr>'s Statistics of Income (<abbr class="spell">SOI</abbr>) series to compare aggregate measures of pension benefits. Using data from the 1990 <abbr class="spell">SOI</abbr>, Schieber (1995) asserted that the <abbr class="spell">CPS</abbr> undercounts pension and annuity income by as much as <span class="nobr">one-third</span>. In a follow-up study, Woods (1996) noted that although there are concerns about comparing the two datasets, Schieber's assessment that the <abbr class="spell">CPS</abbr> is missing large portions of pension income relative to the <abbr class="spell">SOI</abbr> data was correct. More recently, Chen, Munnell, and Sanzenbacher (2018) compared results of the <abbr class="spell">CPS</abbr> and four other national survey datasets with administrative aggregates from the <abbr class="spell">IRS</abbr>'s <abbr class="spell">SOI</abbr> and Social Security administrative data published in <abbr class="spell">SSA</abbr>'s <i><a href="/policy/docs/statcomps/supplement/index.html">Annual Statistical Supplement to the Social Security Bulletin</a></i>. They concluded, as prior researchers have, that the <abbr class="spell">CPS</abbr> misses large portions of retirement income. Interestingly, they found that the other four national surveys were much better than the <abbr class="spell">CPS</abbr> for capturing retirement income.<sup><a href="#mn3" id="mt3">3</a></sup></p>
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<p>Bee and Mitchell (2017) examined the extent and magnitude of measurement and reporting errors for different income sources by comparing the 2013 <abbr class="spell">CPS</abbr> reports with information from administrative data from <abbr class="spell">SSA</abbr> and <abbr class="spell">IRS</abbr>. They compared amounts reported in the <abbr class="spell">CPS</abbr> and amounts validated by linking the <abbr class="spell">CPS</abbr> results with the administrative data for five types of income: earnings, Social Security benefits, Supplemental Security Income (<abbr class="spell">SSI</abbr>) payments, interest and dividends, and “retirement income” (comprising pension benefits and retirement account distributions). The authors found that, among all households headed by an individual aged 65 or older in 2012, median household income was 30 percent higher in the administrative records than in the <abbr class="spell">CPS</abbr> ($44,400 versus $33,800). As a result, the poverty rate for persons aged 65 or older when estimated using public-use <abbr class="spell">CPS</abbr> data (9.1 percent) was 2.2 percentage points higher than the estimate using <abbr class="spell">CPS</abbr> results validated with administrative data (6.9 percent).</p>
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<p>Bee and Mitchell (2017) also showed that the difference in estimated income is mainly due to underreporting of retirement income (from both defined benefit pensions and defined contribution retirement account withdrawals) and that the discrepancy in median income between survey and administrative data increased from about 20 percent in 1990 to about 30 percent in 2012. This finding reveals that the discrepancy, attributable mainly to <abbr class="spell">CPS</abbr>' failure to capture many retirement account distributions, arose at a time when retirement accounts and withdrawals from such accounts became more prevalent. Notably, the authors found that about 46 percent of the aged <abbr class="spell">CPS</abbr> respondents who report no income from retirement accounts actually have such income, according to the administrative records (a false negative type of error). Moreover, according to administrative records, persons with only individual retirement account (<abbr class="spell">IRA</abbr>) distributions are much less likely to report those distributions (thereby generating a higher false negative rate) than persons with distributions only from employer-sponsored defined contribution plans (false negative rates of 81 percent and 40 percent, respectively). Because of underreporting of retirement income, the <abbr class="spell">CPS</abbr> overstates the importance of Social Security to total income. When comparing the public-use <abbr class="spell">CPS</abbr> data with <abbr class="spell">CPS</abbr> data that have been supplemented with administrative data, the authors found that the proportion of persons aged 65 or older who rely on Social Security for at least 50 percent of their family income differed significantly (55 percent and 42 percent, respectively). Furthermore, the proportion of those relying on Social Security for at least 90 percent of their family income differed even more widely, at 26 percent versus 12 percent, respectively.</p>
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<h2>Data and Methods</h2>
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<p>We compare income and poverty statistics for the aged using four alternative data files. We derive the estimates presented here from two major household surveys (the 2016 March <abbr class="spell">CPS</abbr> and the 2016 wave of the <abbr class="spell">HRS</abbr>) and administrative data from <abbr class="spell">SSA</abbr> and <abbr class="spell">IRS</abbr>. The data files consist of:</p>
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<ol>
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<li><abbr class="spell">CPS</abbr> public-use data (the <abbr class="spell">CPS</abbr> <abbr class="spell">PUF</abbr>),</li>
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<li><abbr class="spell">HRS</abbr> public-use data (the <abbr class="spell">HRS</abbr> <abbr class="spell">PUF</abbr>),<sup><a href="#mn4" id="mt4">4</a></sup></li>
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<li>Restricted <abbr class="spell">CPS</abbr> data that we have linked with administrative data from <abbr class="spell">SSA</abbr> (the “<abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr>” data file), and</li>
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<li>Restricted <abbr class="spell">CPS</abbr> data that we have linked with administrative data from <abbr class="spell">SSA</abbr> and <abbr class="spell">IRS</abbr> (the “<abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr>+<abbr class="spell">IRS</abbr>” data file).</li>
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</ol>
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<p>The administrative data from <abbr class="spell">SSA</abbr> provide information on earnings, Social Security benefit receipt, and <abbr class="spell">SSI</abbr> payment receipt. The <abbr class="spell">IRS</abbr> administrative data include information on retirement income from sources other than Social Security, including income generated from asset holdings. Restricted-access <abbr class="spell">CPS</abbr> data were linked to the <abbr class="spell">SSA</abbr> and <abbr class="spell">IRS</abbr> data using an anonymized unique identifier on a secure Census Bureau server.<sup><a href="#mn5" id="mt5">5</a></sup></p>
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<p>The analysis presented here is primarily concerned with the family income of persons aged 65 or older.<sup><a href="#mn6" id="mt6">6</a></sup> Unless otherwise stated—for example, in our analysis of aggregate income—the focus is on family income. A detailed discussion about the numerous methods researchers have devised to determine what counts as income is beyond the scope of this work. For this analysis, we follow the recommendations of Anguelov, Iams, and Purcell (2012) and count all distributions from retirement accounts as income, including infrequent and periodic withdrawals. This includes payments from both defined benefit and defined contribution plans, and traditional and Roth <abbr class="spell">IRA</abbr> withdrawals, but excludes transfers between tax-preferred accounts, such as rollovers and conversions. This method was also employed by Bee and Mitchell (2017) and, as they pointed out, the nature of the administrative data lends itself to counting all withdrawals that permanently leave tax-preferred accounts as income.</p>
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<h3><abbr class="spell">CPS</abbr> <abbr class="spell">ASEC</abbr></h3>
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<p>The <abbr class="spell">CPS</abbr> <abbr class="spell">ASEC</abbr> is a survey of a nationally representative sample of the <abbr>U.S.</abbr> noninstitutionalized population. The survey collects information on income from different sources—such as earnings, Social Security, pensions, assets, and government transfer programs—that the household (each family or household member) received during the prior year. In addition, the <abbr class="spell">CPS</abbr> collects detailed demographic information, including but not limited to age, gender, race/ethnicity, marital status, and household composition. As such, the <abbr class="spell">CPS</abbr> has long been a source for national estimates of household income and poverty rates across different population subgroups.</p>
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|
<p>As discussed in the previous section, several studies have been critical of the <abbr class="spell">CPS</abbr> over the years. These studies have emphasized that the <abbr class="spell">CPS</abbr> inadequately measures income from assets and tax-advantaged retirement accounts (such as <span class="nobr">401(k)</span> plans and <abbr class="spell">IRA</abbr>s), resulting in estimates that understate the importance of such accounts. Consequently, <abbr class="spell">CPS</abbr> results overstate the contribution of Social Security benefits (Iams and Purcell 2013; Fisher 2008; Davies and Fisher 2009; Miller and Schieber 2013; Munnell and Chen 2014). The Census Bureau has been receptive to these studies, and in 2015 fielded a redesigned survey instrument aimed at improving the collection of income data by implementing a number of changes. These included eliminating redundant questions to reduce query fatigue and revising the order of the income questions to target the most likely sources of income. In addition, a “dual-pass” approach was implemented that first asks about sources of income and then about the amounts from each source. Lastly, the 2015 <abbr class="spell">CPS</abbr> (2014 reference year) asked separate questions about retirement account withdrawals and distributions and collected information on property income.</p>
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|
<p>Prior to the full implementation of the redesigned questionnaire in 2015, the 2014 March <abbr class="spell">CPS</abbr> randomly selected ⅜ of the sample to receive the new questionnaire, while the remaining ⅝ of the sample received the traditional <abbr class="spell">CPS</abbr> questionnaire. Comparisons made using the split-sample design from the 2014 <abbr class="spell">CPS</abbr> (2013 reference year) indicated that among aged households, the estimated real median income of the redesign respondents was 4.6 percent higher than that of respondents to the traditional questionnaire. In addition, estimates of the prevalence of retirement income other than Social Security were about 50 percent higher using the redesigned versus traditional questionnaire and the aggregate value of that income was about 22 percent higher. Interestingly, both the estimated prevalence and the aggregate value of Social Security income were only about 2 percent greater using the redesigned questionnaire, suggesting that the traditional <abbr class="spell">CPS</abbr> instrument measured Social Security relatively well (Semega and Welniak 2015).</p>
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|
<p>This study has the advantage of using the 2016 March <abbr class="spell">CPS</abbr>, the second year of full implementation of the redesigned questionnaire. In addition, we follow Bee and Mitchell (2017) and match the <abbr class="spell">CPS</abbr> results with administrative data from <abbr class="spell">SSA</abbr> and <abbr class="spell">IRS</abbr>.<sup><a href="#mn7" id="mt7">7</a></sup> This allows us to compare our findings with their work, which evaluated the <abbr class="spell">CPS</abbr> prior to the redesign, using matched data up to reference year 2012. Of central interest is the question of whether underreporting of retirement income remained as prevalent in 2015 as it was prior to the <abbr class="spell">CPS</abbr> redesign in 2012. Although the <abbr class="spell">CPS</abbr> interviews took place in 2016, the reference year for all income measures (defined in <a href="#appA">Appendix A</a>) is the previous calendar year (2015).</p>
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|
<p>We validated data on several income sources for <abbr class="spell">CPS</abbr> respondents by using an identifier that allowed us to link their 2016 <abbr class="spell">CPS</abbr> responses (reporting income in 2015) to administrative records. For the respondents with an identifier (about 90 percent of respondents aged 65 or older), we replaced the values reported in the <abbr class="spell">CPS</abbr> with values from the administrative records. For the remaining respondents we used self-reported values from the <abbr class="spell">CPS</abbr>. For linked respondents, administrative records from <abbr class="spell">SSA</abbr> allowed us to validate Social Security benefits (retirement and disability), <abbr class="spell">SSI</abbr> payments, and earnings from employment, resulting in the <abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr> data file. <abbr class="spell">IRS</abbr> administrative records allowed us also to validate income from retirement accounts (defined benefit and defined contribution employer-sponsored plans, and withdrawals from <abbr class="spell">IRA</abbr>s), and income from interest and dividends, resulting in the <abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr>+<abbr class="spell">IRS</abbr> file.</p>
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|
<h3><abbr class="spell">HRS</abbr></h3>
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<p>The <abbr class="spell">HRS</abbr> is the most comprehensive national longitudinal survey of Americans aged 51 or older.<sup><a href="#mn8" id="mt8">8</a></sup> The first <abbr class="spell">HRS</abbr> interviews took place in 1992, with follow-up interviews conducted every other year since then. The main goal of the <abbr class="spell">HRS</abbr> is to provide data that allow researchers to examine interactions between social, economic, health, and psychological factors in the retirement decisions of older adults during <span class="nobr">pre-and</span> post-retirement years. By conducting in-depth interviews, it also provides a broad array of information on topics such as employment, income, wealth, and other characteristics of the population aged 51 or older. Another advantage of the <abbr class="spell">HRS</abbr> is that it asks respondents for their consent to link their survey information with earnings and benefits information from Social Security administrative records. Furthermore, the <abbr class="spell">HRS</abbr> is more systematic than the <abbr class="spell">CPS</abbr> in collecting information on pensions, retirement-plan account balances, and their distributions. If <abbr class="spell">HRS</abbr> respondents, when asked, do not report the amount of income or wealth, then they are asked follow-up questions about the dollar amount using an “unfolding brackets” approach to identify the range limits of the missing data item.</p>
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|
<p>Czajka and Denmead (2008) showed that <abbr class="spell">HRS</abbr>-reported household income amounts in 2002, among people aged 51 or older, were substantially higher (by <span class="nobr">20–30</span> percent) than amounts reported in the <abbr class="spell">CPS</abbr>; and while both samples had similar demographic characteristics, the <abbr class="spell">HRS</abbr> respondents were less likely to live alone than were their <abbr class="spell">CPS</abbr> counterparts. The authors conclude that “<abbr class="spell">HRS</abbr> incomes are higher than those of the Census Bureau surveys, but resolving whether this is due to better measurement or over-representation of higher-income families must be left to future research.”</p>
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|
<p>In this article, we use income information from the <abbr>RAND</abbr>-<abbr class="spell">HRS</abbr> user-friendly data file, which includes information from all interviews conducted from 1992 to 2016, as well as additional variables derived from survey reports, which are created in a consistent way across survey years. Specifically, we focus on the sample of people who were aged 65 or older in the 2016 wave and use only the income variables collected in that wave. For each respondent in the <abbr class="spell">HRS</abbr>, income measures include earnings, private pensions, Social Security benefits, income from government welfare programs, capital, and other sources. For married respondents, the spouse's income from those same sources is measured and available separately. The total household income is the sum of income the respondent received from all sources, and for married couples it includes incomes received by both the respondent and the spouse.<sup><a href="#mn9" id="mt9">9</a>,<a href="#mn10" id="mt10">10</a></sup> Although the interviews took place in 2016, the reference year for all income measures is the previous calendar year (2015). See <a href="#appB">Appendix B</a> for the <abbr class="spell">HRS</abbr> variable definitions.</p>
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|
<p>In an attempt to complement the <abbr class="spell">HRS</abbr> <abbr class="spell">PUF</abbr> and to provide a comparison for the <abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr> data file, we also created an <abbr class="spell">HRS</abbr>+<abbr class="spell">SSA</abbr> data file. For <abbr class="spell">HRS</abbr> survey respondents who provided consent, we matched survey reports with information from <abbr class="spell">SSA</abbr>'s restricted earnings and benefits records. For respondents with a match, we replaced survey information on earnings and Social Security benefits with the respective information from the administrative records. However, for our sample of interest, the match rate in 2016 (with income reference year 2015) was only 14 percent.<sup><a href="#mn11" id="mt11">11</a></sup> Given the low match rate, the results using the survey-only information (that is, <abbr class="spell">HRS</abbr> <abbr class="spell">PUF</abbr>) did not differ from those based on survey results augmented with administrative records (<abbr class="spell">HRS</abbr>+<abbr class="spell">SSA</abbr>). Hence, we decided not to report those results here.<sup><a href="#mn12" id="mt12">12</a></sup></p>
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<h3>Social Security Administrative Data</h3>
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<p>Previous research has shown that survey respondents may misreport their earnings or Social Security benefits (Dushi, Iams, and Trenkamp 2017; Iams and Purcell 2013; Meyer, Mok, and Sullivan 2015; Bricker and Engelhardt 2007; Bound, Brown, and Mathiowetz 2001; Pedace and Bates 2000; Bollinger 1998; Rodgers, Brown, and Duncan 1993). To account for reporting error, we use Social Security administrative records, which maintain information on annual earnings, Social Security benefits, and <abbr class="spell">SSI</abbr> payments. More specifically, we match survey data with restricted <abbr class="spell">SSA</abbr> records for about 90 percent of the sample in the 2016 <abbr class="spell">CPS</abbr>. The earnings information come from the Detailed Earnings Record file, which indicates the amount of covered or noncovered earnings, as well as self-reported earnings. It also contains detailed information on total compensation, earnings that are subject to Social Security and Medicare tax, and voluntary tax-deferred contributions to retirement accounts. Information about Social Security benefit amounts comes from the Payment History Update System file, which contains information on the net amount of benefits paid to a beneficiary as well as the amount of the Medicare premium paid on the beneficiary's behalf to the Centers for Medicare & Medicaid Services. Hence, the true (or gross) amount of Social Security benefits that a retired beneficiary is entitled to is the sum of net benefits and Medicare premiums. For respondents in our sample with a matched record, the estimated benefit amount in a given year is equal to the sum of monthly benefits received and the Medicare premiums paid. For those without a matched record in our sample, the estimated amount of benefits equals their self-reported amount. Finally, we use the information from the Supplemental Security Records file to obtain information about <abbr class="spell">SSI</abbr> receipt and payment amounts.</p>
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|
<h3><abbr class="spell">IRS</abbr> Administrative Data</h3>
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|
<p>We match data from two <abbr class="spell">IRS</abbr> administrative data files to the 2016 March <abbr class="spell">CPS</abbr>. The first of these files is composed of data taken from the <abbr class="spell">IRS</abbr> information return <span class="nobr">Form 1099-R.</span> The <span class="nobr">1099-R</span> data allow us to validate retirement income data from both defined benefit and defined contribution employer-sponsored plans, as well as withdrawals from <abbr class="spell">IRA</abbr>s. As Bee and Mitchell (2017) note, this file excludes data on direct rollovers, Section 1035 exchanges, and Roth <abbr class="spell">IRA</abbr> conversions, which is to our advantage, as we want to count only income that permanently leaves tax-preferred accounts.</p>
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<p>The second <abbr class="spell">IRS</abbr> administrative data file we use is composed of data from the <abbr class="spell">IRS</abbr> Form 1040. From this file, we are able to validate interest and dividend income for <abbr class="spell">CPS</abbr> respondents who filed an <abbr class="spell">IRS</abbr> Form 1040 for 2015. For <abbr class="spell">CPS</abbr> respondents who do not have a 1040 record, either because they did not file one (those with income under a certain amount are not required to file Form 1040) or they did not have interest or dividend income, we use the amount from the <abbr class="spell">CPS</abbr>. Because we are concerned with the <i>family income</i> of persons, we do not worry about splitting income from the Form 1040 for joint filers.<sup><a href="#mn13" id="mt13">13</a></sup></p>
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<h3>A Brief Word on Income Not Captured by the Administrative Data</h3>
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|
<p>For the <abbr class="spell">CPS</abbr> records that we are able to match, the administrative data files described above capture the bulk of the income that respondents are likely to have. However, there are some income sources that the administrative data files either do not measure or may not measure well in some cases. Income data collected in the <abbr class="spell">CPS</abbr> that are not included in the administrative data files include unemployment insurance, workers' compensation, public assistance (other than <abbr class="spell">SSI</abbr>), rents/royalties/estates/trusts, educational assistance, alimony, child support, and <span class="nobr">in-kind</span> support from outside the household. For these income sources, we use the values reported in the <abbr class="spell">CPS</abbr>. Additionally, the Detailed Earnings Record includes only the taxable portion of self-employment earnings and likely misses earnings from the informal labor market.</p>
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<h2>Results</h2>
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<p>In this section, we present estimates from each of the four data files; the <abbr class="spell">HRS</abbr> <abbr class="spell">PUF</abbr>, the <abbr class="spell">CPS</abbr> <abbr class="spell">PUF</abbr>, the <abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr> file, and the <abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr>+<abbr class="spell">IRS</abbr> file. Table 1 provides a comparison of demographic characteristics between the <abbr class="spell">CPS</abbr> and <abbr class="spell">HRS</abbr> samples. Despite a fundamental difference in the survey designs (<abbr class="spell">CPS</abbr> is cross-sectional and <abbr class="spell">HRS</abbr> is longitudinal), the two samples of aged respondents exhibit similar demographic characteristics. The two samples differ, however, with respect to the number of persons in the family and the proportions who are Social Security beneficiaries. Similar to findings by Czajka and Denmead (2008) using the 2002 <abbr class="spell">HRS</abbr> wave, aged <abbr class="spell">HRS</abbr> respondents in 2016 are less likely to live alone or in a two-person family than their <abbr class="spell">CPS</abbr> counterparts are. Furthermore, the proportion of respondents who are Social Security beneficiaries is higher in the <abbr class="spell">HRS</abbr> than in the <abbr class="spell">CPS</abbr>.</p>
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<div class="table" id="table1">
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<table>
|
|
<caption><span class="tableNumber">Table 1. </span>Demographic characteristics of survey participants aged 65 or older, by age group and survey, 2016 (in percent)</caption>
|
|
<colgroup span="1" style="width:18em"></colgroup>
|
|
<colgroup span="10" style="width:4em"></colgroup>
|
|
<thead>
|
|
<tr>
|
|
<th rowspan="3" class="stubHeading" id="c1">Characteristic</th>
|
|
<th colspan="5" class="spanner" id="c2"><abbr class="spell">HRS</abbr></th>
|
|
<th colspan="5" class="spanner" id="c3"><abbr class="spell">CPS</abbr></th>
|
|
</tr>
|
|
<tr>
|
|
<th rowspan="2" id="c4" headers="c2">All</th>
|
|
<th colspan="4" class="spanner" id="c5" headers="c2">Age</th>
|
|
<th rowspan="2" id="c6" headers="c3">All</th>
|
|
<th colspan="4" class="spanner" id="c7" headers="c3">Age</th>
|
|
</tr>
|
|
<tr>
|
|
<th id="c8" headers="c2 c5"><span class="nobr">65–69</span></th>
|
|
<th id="c9" headers="c2 c5"><span class="nobr">70–74</span></th>
|
|
<th id="c10" headers="c2 c5"><span class="nobr">75–79</span></th>
|
|
<th id="c11" headers="c2 c5">80+</th>
|
|
<th id="c12" headers="c3 c7"><span class="nobr">65–69</span></th>
|
|
<th id="c13" headers="c3 c7"><span class="nobr">70–74</span></th>
|
|
<th id="c14" headers="c3 c7"><span class="nobr">75–79</span></th>
|
|
<th id="c15" headers="c3 c7">80+</th>
|
|
</tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr>
|
|
<th class="stub0" id="r1" headers="c1">Sex</th>
|
|
<td colspan="10"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r2" headers="r1 c1">Men</th>
|
|
<td headers="r1 r2 c2 c4">43.9</td>
|
|
<td headers="r1 r2 c2 c5 c8">45.1</td>
|
|
<td headers="r1 r2 c2 c5 c9">47.4</td>
|
|
<td headers="r1 r2 c2 c5 c10">44.1</td>
|
|
<td headers="r1 r2 c2 c5 c11">38.7</td>
|
|
<td headers="r1 r2 c3 c6">44.6</td>
|
|
<td headers="r1 r2 c3 c7 c12">47.1</td>
|
|
<td headers="r1 r2 c3 c7 c13">45.4</td>
|
|
<td headers="r1 r2 c3 c7 c14">45.8</td>
|
|
<td headers="r1 r2 c3 c7 c15">39.3</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r3" headers="r1 c1">Women</th>
|
|
<td headers="r1 r3 c2 c4">56.1</td>
|
|
<td headers="r1 r3 c2 c5 c8">54.9</td>
|
|
<td headers="r1 r3 c2 c5 c9">52.6</td>
|
|
<td headers="r1 r3 c2 c5 c10">55.9</td>
|
|
<td headers="r1 r3 c2 c5 c11">61.3</td>
|
|
<td headers="r1 r3 c3 c6">55.4</td>
|
|
<td headers="r1 r3 c3 c7 c12">52.9</td>
|
|
<td headers="r1 r3 c3 c7 c13">54.6</td>
|
|
<td headers="r1 r3 c3 c7 c14">54.2</td>
|
|
<td headers="r1 r3 c3 c7 c15">60.7</td>
|
|
</tr>
|
|
<tr class="topPad1">
|
|
<th class="stub0" id="r4" headers="c1">Race/ethnicity</th>
|
|
<td colspan="10"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r5" headers="r4 c1">Non-Hispanic white <sup>a</sup></th>
|
|
<td headers="r4 r5 c2 c4">80.2</td>
|
|
<td headers="r4 r5 c2 c5 c8">78.3</td>
|
|
<td headers="r4 r5 c2 c5 c9">79.3</td>
|
|
<td headers="r4 r5 c2 c5 c10">79.7</td>
|
|
<td headers="r4 r5 c2 c5 c11">84.0</td>
|
|
<td headers="r4 r5 c3 c6">84.7</td>
|
|
<td headers="r4 r5 c3 c7 c12">83.3</td>
|
|
<td headers="r4 r5 c3 c7 c13">84.5</td>
|
|
<td headers="r4 r5 c3 c7 c14">84.9</td>
|
|
<td headers="r4 r5 c3 c7 c15">86.7</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r6" headers="r4 c1">Non-Hispanic black <sup>b</sup></th>
|
|
<td headers="r4 r6 c2 c4">9.2</td>
|
|
<td headers="r4 r6 c2 c5 c8">10.4</td>
|
|
<td headers="r4 r6 c2 c5 c9">9.3</td>
|
|
<td headers="r4 r6 c2 c5 c10">8.5</td>
|
|
<td headers="r4 r6 c2 c5 c11">7.9</td>
|
|
<td headers="r4 r6 c3 c6">9.1</td>
|
|
<td headers="r4 r6 c3 c7 c12">9.9</td>
|
|
<td headers="r4 r6 c3 c7 c13">9.2</td>
|
|
<td headers="r4 r6 c3 c7 c14">9.2</td>
|
|
<td headers="r4 r6 c3 c7 c15">7.9</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r7" headers="r4 c1">Non-Hispanic other <sup>c</sup></th>
|
|
<td headers="r4 r7 c2 c4">2.7</td>
|
|
<td headers="r4 r7 c2 c5 c8">3.3</td>
|
|
<td headers="r4 r7 c2 c5 c9">2.9</td>
|
|
<td headers="r4 r7 c2 c5 c10">2.6</td>
|
|
<td headers="r4 r7 c2 c5 c11">1.9</td>
|
|
<td headers="r4 r7 c3 c6">4.5</td>
|
|
<td headers="r4 r7 c3 c7 c12">4.9</td>
|
|
<td headers="r4 r7 c3 c7 c13">4.6</td>
|
|
<td headers="r4 r7 c3 c7 c14">4.1</td>
|
|
<td headers="r4 r7 c3 c7 c15">4.0</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r8" headers="r4 c1">Hispanic (any race)</th>
|
|
<td headers="r4 r8 c2 c4">7.9</td>
|
|
<td headers="r4 r8 c2 c5 c8">8.0</td>
|
|
<td headers="r4 r8 c2 c5 c9">8.5</td>
|
|
<td headers="r4 r8 c2 c5 c10">9.2</td>
|
|
<td headers="r4 r8 c2 c5 c11">6.2</td>
|
|
<td headers="r4 r8 c3 c6">8.1</td>
|
|
<td headers="r4 r8 c3 c7 c12">8.8</td>
|
|
<td headers="r4 r8 c3 c7 c13">8.0</td>
|
|
<td headers="r4 r8 c3 c7 c14">7.7</td>
|
|
<td headers="r4 r8 c3 c7 c15">7.5</td>
|
|
</tr>
|
|
<tr class="topPad1">
|
|
<th class="stub0" id="r9" headers="c1">Marital status</th>
|
|
<td colspan="10"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r10" headers="r9 c1">Married</th>
|
|
<td headers="r9 r10 c2 c4">59.4</td>
|
|
<td headers="r9 r10 c2 c5 c8">69.0</td>
|
|
<td headers="r9 r10 c2 c5 c9">65.7</td>
|
|
<td headers="r9 r10 c2 c5 c10">60.1</td>
|
|
<td headers="r9 r10 c2 c5 c11">39.7</td>
|
|
<td headers="r9 r10 c3 c6">56.4</td>
|
|
<td headers="r9 r10 c3 c7 c12">64.6</td>
|
|
<td headers="r9 r10 c3 c7 c13">61.0</td>
|
|
<td headers="r9 r10 c3 c7 c14">57.6</td>
|
|
<td headers="r9 r10 c3 c7 c15">38.8</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r11" headers="r9 c1">Nonmarried</th>
|
|
<td headers="r9 r11 c2 c4">40.6</td>
|
|
<td headers="r9 r11 c2 c5 c8">31.0</td>
|
|
<td headers="r9 r11 c2 c5 c9">34.3</td>
|
|
<td headers="r9 r11 c2 c5 c10">40.0</td>
|
|
<td headers="r9 r11 c2 c5 c11">60.3</td>
|
|
<td headers="r9 r11 c3 c6">43.6</td>
|
|
<td headers="r9 r11 c3 c7 c12">35.4</td>
|
|
<td headers="r9 r11 c3 c7 c13">39.0</td>
|
|
<td headers="r9 r11 c3 c7 c14">42.4</td>
|
|
<td headers="r9 r11 c3 c7 c15">61.2</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub2" id="r12" headers="r9 r11 c1">Widowed</th>
|
|
<td headers="r9 r11 r12 c2 c4">23.3</td>
|
|
<td headers="r9 r11 r12 c2 c5 c8">10.1</td>
|
|
<td headers="r9 r11 r12 c2 c5 c9">15.2</td>
|
|
<td headers="r9 r11 r12 c2 c5 c10">24.7</td>
|
|
<td headers="r9 r11 r12 c2 c5 c11">48.2</td>
|
|
<td headers="r9 r11 r12 c3 c6">24.0</td>
|
|
<td headers="r9 r11 r12 c3 c7 c12">10.5</td>
|
|
<td headers="r9 r11 r12 c3 c7 c13">18.7</td>
|
|
<td headers="r9 r11 r12 c3 c7 c14">25.3</td>
|
|
<td headers="r9 r11 r12 c3 c7 c15">48.5</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub2" id="r13" headers="r9 r11 c1">Divorced</th>
|
|
<td headers="r9 r11 r13 c2 c4">12.5</td>
|
|
<td headers="r9 r11 r13 c2 c5 c8">15.1</td>
|
|
<td headers="r9 r11 r13 c2 c5 c9">13.9</td>
|
|
<td headers="r9 r11 r13 c2 c5 c10">11.7</td>
|
|
<td headers="r9 r11 r13 c2 c5 c11">8.2</td>
|
|
<td headers="r9 r11 r13 c3 c6">12.0</td>
|
|
<td headers="r9 r11 r13 c3 c7 c12">15.4</td>
|
|
<td headers="r9 r11 r13 c3 c7 c13">13.3</td>
|
|
<td headers="r9 r11 r13 c3 c7 c14">10.5</td>
|
|
<td headers="r9 r11 r13 c3 c7 c15">6.7</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub2" id="r14" headers="r9 r11 c1">Never married</th>
|
|
<td headers="r9 r11 r14 c2 c4">4.8</td>
|
|
<td headers="r9 r11 r14 c2 c5 c8">5.8</td>
|
|
<td headers="r9 r11 r14 c2 c5 c9">5.2</td>
|
|
<td headers="r9 r11 r14 c2 c5 c10">3.6</td>
|
|
<td headers="r9 r11 r14 c2 c5 c11">3.9</td>
|
|
<td headers="r9 r11 r14 c3 c6">5.2</td>
|
|
<td headers="r9 r11 r14 c3 c7 c12">6.7</td>
|
|
<td headers="r9 r11 r14 c3 c7 c13">4.8</td>
|
|
<td headers="r9 r11 r14 c3 c7 c14">4.4</td>
|
|
<td headers="r9 r11 r14 c3 c7 c15">3.9</td>
|
|
</tr>
|
|
<tr class="topPad1">
|
|
<th class="stub0" id="r15" headers="c1">Educational attainment</th>
|
|
<td colspan="10"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r16" headers="r15 c1">Less than high school diploma</th>
|
|
<td headers="r15 r16 c2 c4">15.1</td>
|
|
<td headers="r15 r16 c2 c5 c8">9.5</td>
|
|
<td headers="r15 r16 c2 c5 c9">14.4</td>
|
|
<td headers="r15 r16 c2 c5 c10">19.0</td>
|
|
<td headers="r15 r16 c2 c5 c11">20.5</td>
|
|
<td headers="r15 r16 c3 c6">14.6</td>
|
|
<td headers="r15 r16 c3 c7 c12">10.8</td>
|
|
<td headers="r15 r16 c3 c7 c13">13.2</td>
|
|
<td headers="r15 r16 c3 c7 c14">16.0</td>
|
|
<td headers="r15 r16 c3 c7 c15">20.8</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r17" headers="r15 c1">High school diploma or equivalent</th>
|
|
<td headers="r15 r17 c2 c4">33.1</td>
|
|
<td headers="r15 r17 c2 c5 c8">28.4</td>
|
|
<td headers="r15 r17 c2 c5 c9">33.8</td>
|
|
<td headers="r15 r17 c2 c5 c10">35.7</td>
|
|
<td headers="r15 r17 c2 c5 c11">37.2</td>
|
|
<td headers="r15 r17 c3 c6">33.2</td>
|
|
<td headers="r15 r17 c3 c7 c12">29.5</td>
|
|
<td headers="r15 r17 c3 c7 c13">32.4</td>
|
|
<td headers="r15 r17 c3 c7 c14">36.1</td>
|
|
<td headers="r15 r17 c3 c7 c15">37.4</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r18" headers="r15 c1">Some college</th>
|
|
<td headers="r15 r18 c2 c4">24.2</td>
|
|
<td headers="r15 r18 c2 c5 c8">28.7</td>
|
|
<td headers="r15 r18 c2 c5 c9">23.8</td>
|
|
<td headers="r15 r18 c2 c5 c10">21.8</td>
|
|
<td headers="r15 r18 c2 c5 c11">20.1</td>
|
|
<td headers="r15 r18 c3 c6">16.2</td>
|
|
<td headers="r15 r18 c3 c7 c12">17.0</td>
|
|
<td headers="r15 r18 c3 c7 c13">17.3</td>
|
|
<td headers="r15 r18 c3 c7 c14">16.3</td>
|
|
<td headers="r15 r18 c3 c7 c15">13.9</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r19" headers="r15 c1">College degree</th>
|
|
<td headers="r15 r19 c2 c4">27.6</td>
|
|
<td headers="r15 r19 c2 c5 c8">33.4</td>
|
|
<td headers="r15 r19 c2 c5 c9">28.1</td>
|
|
<td headers="r15 r19 c2 c5 c10">23.5</td>
|
|
<td headers="r15 r19 c2 c5 c11">22.2</td>
|
|
<td headers="r15 r19 c3 c6">35.9</td>
|
|
<td headers="r15 r19 c3 c7 c12">42.7</td>
|
|
<td headers="r15 r19 c3 c7 c13">37.1</td>
|
|
<td headers="r15 r19 c3 c7 c14">31.5</td>
|
|
<td headers="r15 r19 c3 c7 c15">28.0</td>
|
|
</tr>
|
|
<tr class="topPad1">
|
|
<th class="stub0" id="r20" headers="c1">Persons in family <sup>d</sup></th>
|
|
<td colspan="10"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r21" headers="r20 c1">1</th>
|
|
<td headers="r20 r21 c2 c4">28.1</td>
|
|
<td headers="r20 r21 c2 c5 c8">23.0</td>
|
|
<td headers="r20 r21 c2 c5 c9">24.0</td>
|
|
<td headers="r20 r21 c2 c5 c10">27.8</td>
|
|
<td headers="r20 r21 c2 c5 c11">40.6</td>
|
|
<td headers="r20 r21 c3 c6">32.1</td>
|
|
<td headers="r20 r21 c3 c7 c12">25.6</td>
|
|
<td headers="r20 r21 c3 c7 c13">29.3</td>
|
|
<td headers="r20 r21 c3 c7 c14">31.5</td>
|
|
<td headers="r20 r21 c3 c7 c15">45.0</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r22" headers="r20 c1">2</th>
|
|
<td headers="r20 r22 c2 c4">49.6</td>
|
|
<td headers="r20 r22 c2 c5 c8">54.6</td>
|
|
<td headers="r20 r22 c2 c5 c9">54.1</td>
|
|
<td headers="r20 r22 c2 c5 c10">51.0</td>
|
|
<td headers="r20 r22 c2 c5 c11">36.0</td>
|
|
<td headers="r20 r22 c3 c6">52.0</td>
|
|
<td headers="r20 r22 c3 c7 c12">56.1</td>
|
|
<td headers="r20 r22 c3 c7 c13">55.0</td>
|
|
<td headers="r20 r22 c3 c7 c14">54.6</td>
|
|
<td headers="r20 r22 c3 c7 c15">40.9</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r23" headers="r20 c1">3 or more</th>
|
|
<td headers="r20 r23 c2 c4">22.3</td>
|
|
<td headers="r20 r23 c2 c5 c8">22.4</td>
|
|
<td headers="r20 r23 c2 c5 c9">21.9</td>
|
|
<td headers="r20 r23 c2 c5 c10">21.2</td>
|
|
<td headers="r20 r23 c2 c5 c11">23.4</td>
|
|
<td headers="r20 r23 c3 c6">15.9</td>
|
|
<td headers="r20 r23 c3 c7 c12">18.3</td>
|
|
<td headers="r20 r23 c3 c7 c13">15.8</td>
|
|
<td headers="r20 r23 c3 c7 c14">13.9</td>
|
|
<td headers="r20 r23 c3 c7 c15">14.1</td>
|
|
</tr>
|
|
<tr class="topPad1">
|
|
<th class="stub0" id="r24" headers="c1">Social Security beneficiaries</th>
|
|
<td headers="r24 c2 c4">89.7</td>
|
|
<td headers="r24 c2 c5 c8">76.6</td>
|
|
<td headers="r24 c2 c5 c9">96.7</td>
|
|
<td headers="r24 c2 c5 c10">96.4</td>
|
|
<td headers="r24 c2 c5 c11">96.4</td>
|
|
<td headers="r24 c3 c6">82.1</td>
|
|
<td headers="r24 c3 c7 c12">71.4</td>
|
|
<td headers="r24 c3 c7 c13">86.0</td>
|
|
<td headers="r24 c3 c7 c14">87.7</td>
|
|
<td headers="r24 c3 c7 c15">89.7</td>
|
|
</tr>
|
|
<tr class="shaded topPad1">
|
|
<th class="stub0" id="r25" headers="c1">Total weighted count (thousands)</th>
|
|
<td headers="r25 c2 c4">50,152</td>
|
|
<td headers="r25 c2 c5 c8">17,067</td>
|
|
<td headers="r25 c2 c5 c9">12,177</td>
|
|
<td headers="r25 c2 c5 c10">8,432</td>
|
|
<td headers="r25 c2 c5 c11">12,476</td>
|
|
<td headers="r25 c3 c6">47,550</td>
|
|
<td headers="r25 c3 c7 c12">16,520</td>
|
|
<td headers="r25 c3 c7 c13">11,430</td>
|
|
<td headers="r25 c3 c7 c14">8,420</td>
|
|
<td headers="r25 c3 c7 c15">11,180</td>
|
|
</tr>
|
|
</tbody>
|
|
<tfoot>
|
|
<tr>
|
|
<td class="firstNote" colspan="11">SOURCE: Authors' calculations based on <abbr class="spell">HRS</abbr> (wave 13, 2016) and 2016 <abbr class="spell">CPS</abbr> <abbr class="spell">ASEC</abbr>.</td>
|
|
</tr>
|
|
<tr>
|
|
<td class="note" colspan="11">NOTES: Estimates are weighted using survey weights.
|
|
<div class="newNote">Rounded components of percentage distributions may not sum to 100.0.</div>
|
|
</td>
|
|
</tr>
|
|
<tr>
|
|
<td class="note" colspan="11">a. Identified in <abbr class="spell">CPS</abbr> as "white alone."</td>
|
|
</tr>
|
|
<tr>
|
|
<td class="note" colspan="11">b. Identified in <abbr class="spell">CPS</abbr> as "black alone."</td>
|
|
</tr>
|
|
<tr>
|
|
<td class="note" colspan="11">c. Identified in <abbr class="spell">CPS</abbr> as "Asian alone."</td>
|
|
</tr>
|
|
<tr>
|
|
<td class="lastNote" colspan="11">d. In the <abbr class="spell">HRS</abbr>, count is derived from the "family composition" variable in the <abbr>RAND</abbr> file that was created to define poverty thresholds and poverty rate.</td>
|
|
</tr>
|
|
</tfoot>
|
|
</table>
|
|
</div>
|
|
<p>We begin by discussing aggregate measures of income across the four different data files, looking specifically at how sources of income differ relative to each other and across the files.</p>
|
|
<h3>Aggregate Income</h3>
|
|
<p>In Table 2, we compare shares of aggregate income for the total <abbr>U.S.</abbr> population aged 65 or older, by income source, across the four data files.<sup><a href="#mn14" id="mt14">14</a></sup> The first thing to note here is that the results are relatively consistent across the <abbr class="spell">HRS</abbr> <abbr class="spell">PUF</abbr>, <abbr class="spell">CPS</abbr> <abbr class="spell">PUF</abbr>, and <abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr> data files. Comparing the aggregate shares based on the <abbr class="spell">CPS</abbr> <abbr class="spell">PUF</abbr> and <abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr> files, we see only slight shifts in earnings (from 30.6 percent to 29.4 percent) and Social Security (from 34.9 percent to 35.5 percent)—the two income categories for which administrative data most often replace survey results. The finding suggests that the <abbr class="spell">CPS</abbr> <abbr class="spell">PUF</abbr> measures earnings and Social Security benefits rather accurately, and is consistent with the findings of Bee and Mitchell (2017). However, clear differences emerge when comparing these files with the <abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr>+<abbr class="spell">IRS</abbr> file, in which pension income accounts for a much larger share of aggregate income than is reported in the <abbr class="spell">CPS</abbr>.<sup><a href="#mn15" id="mt15">15</a></sup> Specifically, in the <abbr class="spell">CPS</abbr> <abbr class="spell">PUF</abbr>, <abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr>, and <abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr>+<abbr class="spell">IRS</abbr> files, pension income accounts for 21.7 percent, 21.3 percent, and 35.9 percent of aggregate income, respectively. The 14 percentage-point difference suggests that while the <abbr class="spell">CPS</abbr> redesign may have somewhat improved the reporting of pension income or retirement account withdrawals, its success in improving the measurement of retirement income has been limited, a finding that is consistent with Bee and Mitchell (2017) and Chen, Munnell, and Sanzenbacher (2018). Particularly noteworthy is that in the <abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr>+<abbr class="spell">IRS</abbr> file, pension income accounts for the largest share of aggregate income, whereas in the <abbr class="spell">CPS</abbr> <abbr class="spell">PUF</abbr> and the <abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr> files, Social Security accounts for the largest share. Interestingly, while the <abbr class="spell">HRS</abbr> <abbr class="spell">PUF</abbr> data account for pension income better than the <abbr class="spell">CPS</abbr> <abbr class="spell">PUF</abbr> and <abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr> files, the share of aggregate income the <abbr class="spell">HRS</abbr> <abbr class="spell">PUF</abbr> attributes to pensions (25.0 percent) is still lower (by about 10 percentage points) than that in the <abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr>+<abbr class="spell">IRS</abbr> file. The share of aggregate income attributable to assets is almost the same across the four data files, whereas the “other” income share<sup><a href="#mn16" id="mt16">16</a></sup> is lower in all of the <abbr class="spell">CPS</abbr> data files than in the <abbr class="spell">HRS</abbr> data, with the lowest share being in the <abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr>+<abbr class="spell">IRS</abbr> file.</p>
|
|
<div class="table" id="table2">
|
|
<table>
|
|
<caption><span class="tableNumber">Table 2. </span>Percentage distribution of aggregate income among individuals aged 65 or older, by source: Measurements from four alternative data files, 2015</caption>
|
|
<colgroup span="1" style="width:14em"></colgroup>
|
|
<colgroup span="2" style="width:8em"></colgroup>
|
|
<colgroup span="2" style="width:8em"></colgroup>
|
|
<thead>
|
|
<tr>
|
|
<th rowspan="2" class="stubHeading" scope="colgroup">Income source</th>
|
|
<th colspan="2" class="spanner" scope="colgroup">Survey data (unmatched)</th>
|
|
<th colspan="2" class="spanner" scope="colgroup">Survey data matched with administrative records <sup>a</sup></th>
|
|
</tr>
|
|
<tr>
|
|
<th scope="col"><abbr class="spell">HRS</abbr> PUF</th>
|
|
<th scope="col"><abbr class="spell">CPS</abbr> PUF</th>
|
|
<th scope="col"><abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr></th>
|
|
<th scope="col"><abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr>+<abbr class="spell">IRS</abbr></th>
|
|
</tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr>
|
|
<th class="stub1" scope="row">Total</th>
|
|
<td>100.0</td>
|
|
<td>100.0</td>
|
|
<td>100.0</td>
|
|
<td>100.0</td>
|
|
</tr>
|
|
<tr class="topPad1">
|
|
<th class="stub0" scope="row">Earnings</th>
|
|
<td>25.6</td>
|
|
<td>30.6</td>
|
|
<td>29.4</td>
|
|
<td>24.7</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row">Social Security</th>
|
|
<td>31.7</td>
|
|
<td>34.9</td>
|
|
<td>35.5</td>
|
|
<td>29.9</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row">Pensions <sup>b</sup></th>
|
|
<td>25.0</td>
|
|
<td>21.7</td>
|
|
<td>21.3</td>
|
|
<td>35.9</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row">Asset income</th>
|
|
<td>9.6</td>
|
|
<td>8.8</td>
|
|
<td>8.9</td>
|
|
<td>7.5</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row">Other</th>
|
|
<td>8.1</td>
|
|
<td>4.0</td>
|
|
<td>4.9</td>
|
|
<td>2.0</td>
|
|
</tr>
|
|
<tr class="shaded topPad1">
|
|
<th class="stub0" scope="row">Weighted count (thousands)</th>
|
|
<td>50,152</td>
|
|
<td>47,550</td>
|
|
<td>47,550</td>
|
|
<td>47,550</td>
|
|
</tr>
|
|
</tbody>
|
|
<tfoot>
|
|
<tr>
|
|
<td class="firstNote" colspan="5">SOURCE: Authors' calculations based on <abbr class="spell">HRS</abbr> (wave 13, 2016), 2016 <abbr class="spell">CPS</abbr> <abbr class="spell">ASEC</abbr>, and administrative data from <abbr class="spell">SSA</abbr> and <abbr class="spell">IRS</abbr>. Income questions ask respondent about income received in the previous calendar year (2015).</td>
|
|
</tr>
|
|
<tr>
|
|
<td class="note" colspan="5">a. Approved for release by the Census Bureau's Disclosure Review Board (<abbr class="spell">CBDRB</abbr>-<abbr class="spell">FY</abbr>20-018).</td>
|
|
</tr>
|
|
<tr>
|
|
<td class="lastNote" colspan="5">b. Includes <abbr class="spell">IRA</abbr> withdrawals.</td>
|
|
</tr>
|
|
</tfoot>
|
|
</table>
|
|
</div>
|
|
<h3>Aged Population by Family Income</h3>
|
|
<p>We now focus on the distribution of persons aged 65 or older by family income level.<sup><a href="#mn17" id="mt17">17</a></sup> Table 3 shows the income distribution of this population for each of the four data files. In the two public data files (<abbr class="spell">HRS</abbr> <abbr class="spell">PUF</abbr> and <abbr class="spell">CPS</abbr> <abbr class="spell">PUF</abbr>) and the <abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr> file, the distributions look very similar. However, there are noticeable differences in the distribution from the <abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr>+<abbr class="spell">IRS</abbr> file, for which the general trend is a shift to the higher end of the income distribution. The effect of adding income from the <span class="nobr">Forms 1099-R</span> and 1040 results in a smaller proportion of individuals concentrated in the lowest family-income categories, shares more evenly distributed across the middle income levels, and higher proportions in the highest income categories. Individuals in the lowest three family income categories (below $15,000) comprise 9.9 percent of the aged population in the <abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr>+<abbr class="spell">IRS</abbr> data, compared with 12.5 percent and 13.7 percent in the <abbr class="spell">CPS</abbr> <abbr class="spell">PUF</abbr> and <abbr class="spell">HRS</abbr> <abbr class="spell">PUF</abbr>, respectively. Furthermore, those in the highest three categories (with family income of $50,000 and higher) comprise 53.7 percent of the population in the <abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr>+<abbr class="spell">IRS</abbr> data compared with 44.7 percent of the population when using the <abbr class="spell">CPS</abbr> <abbr class="spell">PUF</abbr> data or 45.7 percent of the population when using the <abbr class="spell">HRS</abbr> <abbr class="spell">PUF</abbr> data.</p>
|
|
<div class="table" id="table3">
|
|
<table>
|
|
<caption><span class="tableNumber">Table 3. </span>Percentage distribution of the population aged 65 or older, by family annual income: Measurements from four alternative data files, 2015</caption>
|
|
<colgroup span="1" style="width:14em"></colgroup>
|
|
<colgroup span="2" style="width:8em"></colgroup>
|
|
<colgroup span="2" style="width:8em"></colgroup>
|
|
<thead>
|
|
<tr>
|
|
<th rowspan="2" class="stubHeading" scope="colgroup">Family income ($)</th>
|
|
<th colspan="2" class="spanner" scope="colgroup">Survey data (unmatched)</th>
|
|
<th colspan="2" class="spanner" scope="colgroup">Survey data matched with administrative records <sup>a</sup></th>
|
|
</tr>
|
|
<tr>
|
|
<th scope="col"><abbr class="spell">HRS</abbr> PUF</th>
|
|
<th scope="col"><abbr class="spell">CPS</abbr> PUF</th>
|
|
<th scope="col"><abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr></th>
|
|
<th scope="col"><abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr>+<abbr class="spell">IRS</abbr></th>
|
|
</tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr>
|
|
<th class="stub1" scope="row">Total</th>
|
|
<td>100.0</td>
|
|
<td>100.0</td>
|
|
<td>100.0</td>
|
|
<td>100.0</td>
|
|
</tr>
|
|
<tr class="topPad1">
|
|
<th class="stub0" scope="row">Less than 5,000</th>
|
|
<td>1.7</td>
|
|
<td>2.3</td>
|
|
<td>1.3</td>
|
|
<td>0.8</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row"><span class="nobr">5,000–9,999</span></th>
|
|
<td>4.0</td>
|
|
<td>3.0</td>
|
|
<td>4.2</td>
|
|
<td>3.6</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row"><span class="nobr">10,000–14,999</span></th>
|
|
<td>8.0</td>
|
|
<td>7.2</td>
|
|
<td>6.9</td>
|
|
<td>5.5</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row"><span class="nobr">15,000–19,999</span></th>
|
|
<td>7.5</td>
|
|
<td>7.3</td>
|
|
<td>7.6</td>
|
|
<td>5.6</td>
|
|
</tr>
|
|
<tr class="topPad1">
|
|
<th class="stub0" scope="row"><span class="nobr">20,000–24,999</span></th>
|
|
<td>7.1</td>
|
|
<td>7.5</td>
|
|
<td>7.2</td>
|
|
<td>5.6</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row"><span class="nobr">25,000–29,999</span></th>
|
|
<td>5.8</td>
|
|
<td>6.8</td>
|
|
<td>6.6</td>
|
|
<td>5.3</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row"><span class="nobr">30,000–34,999</span></th>
|
|
<td>5.6</td>
|
|
<td>6.1</td>
|
|
<td>6.6</td>
|
|
<td>5.2</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row"><span class="nobr">35,000–39,999</span></th>
|
|
<td>5.2</td>
|
|
<td>5.7</td>
|
|
<td>5.8</td>
|
|
<td>5.8</td>
|
|
</tr>
|
|
<tr class="topPad1">
|
|
<th class="stub0" scope="row"><span class="nobr">40,000–44,999</span></th>
|
|
<td>4.9</td>
|
|
<td>4.6</td>
|
|
<td>5.2</td>
|
|
<td>4.7</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row"><span class="nobr">45,000–49,999</span></th>
|
|
<td>4.6</td>
|
|
<td>4.8</td>
|
|
<td>4.4</td>
|
|
<td>4.3</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row"><span class="nobr">50,000–74,999</span></th>
|
|
<td>15.4</td>
|
|
<td>15.6</td>
|
|
<td>16.2</td>
|
|
<td>18.2</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row"><span class="nobr">75,000–99,999</span></th>
|
|
<td>8.9</td>
|
|
<td>10.2</td>
|
|
<td>10.3</td>
|
|
<td>12.5</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row">100,000 or more</th>
|
|
<td>21.4</td>
|
|
<td>18.9</td>
|
|
<td>17.8</td>
|
|
<td>23.0</td>
|
|
</tr>
|
|
<tr class="shaded topPad1">
|
|
<th class="stub0" scope="row">Weighted count (thousands)</th>
|
|
<td>50,152</td>
|
|
<td>47,550</td>
|
|
<td>47,550</td>
|
|
<td>47,550</td>
|
|
</tr>
|
|
</tbody>
|
|
<tfoot>
|
|
<tr>
|
|
<td class="firstNote" colspan="5">SOURCE: Authors' calculations based on <abbr class="spell">HRS</abbr> (wave 13, 2016), 2016 <abbr class="spell">CPS</abbr> <abbr class="spell">ASEC</abbr>, and administrative data from <abbr class="spell">SSA</abbr> and <abbr class="spell">IRS</abbr>. Income questions ask respondent about income received in the previous calendar year (2015).</td>
|
|
</tr>
|
|
<tr>
|
|
<td class="note" colspan="5">NOTE: Rounded components of percentage distributions may not sum to 100.0.</td>
|
|
</tr>
|
|
<tr>
|
|
<td class="lastNote" colspan="5">a. Approved for release by the Census Bureau's Disclosure Review Board (<abbr class="spell">CBDRB</abbr>-<abbr class="spell">FY</abbr>20-018).</td>
|
|
</tr>
|
|
</tfoot>
|
|
</table>
|
|
</div>
|
|
<h3>Sources of Income</h3>
|
|
<p>Table 4 shows, for each of seven income sources, the proportion of people aged 65 or older with family income from that source, broken out by sex. The estimates indicate that the proportion of persons aged 65 or older reporting income from pension and <abbr class="spell">IRA</abbr> withdrawals in the <abbr class="spell">CPS</abbr> <abbr class="spell">PUF</abbr> is 47.2 percent, in contrast with a proportion of 69.0 percent in the <abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr>+<abbr class="spell">IRS</abbr> file. This represents a substantial difference (21.8 percentage points) between the proportion of <abbr class="spell">CPS</abbr> respondents who have income from retirement accounts and the proportion who report that income in the survey. This finding suggests that not only is the aggregate amount of pension and <abbr class="spell">IRA</abbr> income greater with the addition of the <abbr class="spell">IRS</abbr> administrative data (as shown in <a href="#table2">Table 2</a>), but so is the proportion of persons who have family income from this source.</p>
|
|
<div class="table" id="table4">
|
|
<table>
|
|
<caption><span class="tableNumber">Table 4. </span>Percentages of individuals aged 65 or older with family income, by source and sex: Measurements from four alternative data files, 2015</caption>
|
|
<colgroup span="1" style="width:14em"></colgroup>
|
|
<colgroup span="2" style="width:8em"></colgroup>
|
|
<colgroup span="2" style="width:8em"></colgroup>
|
|
<thead>
|
|
<tr>
|
|
<th rowspan="2" class="stubHeading" scope="colgroup">Income source</th>
|
|
<th colspan="2" class="spanner" scope="colgroup">Survey data (unmatched)</th>
|
|
<th colspan="2" class="spanner" scope="colgroup">Survey data matched with administrative records <sup>a</sup></th>
|
|
</tr>
|
|
<tr>
|
|
<th scope="col"><abbr class="spell">HRS</abbr> PUF</th>
|
|
<th scope="col"><abbr class="spell">CPS</abbr> PUF</th>
|
|
<th scope="col"><abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr></th>
|
|
<th scope="col"><abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr>+<abbr class="spell">IRS</abbr></th>
|
|
</tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr>
|
|
<td> </td>
|
|
<th colspan="4" class="panel" scope="rowgroup">All</th>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row">Social Security</th>
|
|
<td>93.1</td>
|
|
<td>86.0</td>
|
|
<td>89.5</td>
|
|
<td>89.5</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row">Asset income</th>
|
|
<td>54.3</td>
|
|
<td>68.4</td>
|
|
<td>68.4</td>
|
|
<td>69.2</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row">Pensions <sup>b</sup></th>
|
|
<td>59.2</td>
|
|
<td>47.2</td>
|
|
<td>47.2</td>
|
|
<td>69.0</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row">Earnings</th>
|
|
<td>35.6</td>
|
|
<td>40.7</td>
|
|
<td>45.0</td>
|
|
<td>45.0</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row">Veterans' benefits</th>
|
|
<td>10.2</td>
|
|
<td>5.6</td>
|
|
<td>5.6</td>
|
|
<td>5.6</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row">Cash public assistance</th>
|
|
<td>8.0</td>
|
|
<td>4.6</td>
|
|
<td>6.0</td>
|
|
<td>6.0</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row">Other <sup>c</sup></th>
|
|
<td>7.5</td>
|
|
<td>10.8</td>
|
|
<td>10.8</td>
|
|
<td>10.8</td>
|
|
</tr>
|
|
<tr class="shaded topPad1">
|
|
<th class="stub0" scope="row">Weighted count (thousands)</th>
|
|
<td>50,152</td>
|
|
<td>47,550</td>
|
|
<td>47,550</td>
|
|
<td>47,550</td>
|
|
</tr>
|
|
<tr>
|
|
<td> </td>
|
|
<th colspan="4" class="panel" scope="rowgroup">Men</th>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row">Social Security</th>
|
|
<td>92.2</td>
|
|
<td>84.7</td>
|
|
<td>88.7</td>
|
|
<td>88.7</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row">Asset income</th>
|
|
<td>57.7</td>
|
|
<td>70.6</td>
|
|
<td>70.6</td>
|
|
<td>71.4</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row">Pensions <sup>b</sup></th>
|
|
<td>60.6</td>
|
|
<td>48.5</td>
|
|
<td>48.5</td>
|
|
<td>69.2</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row">Earnings</th>
|
|
<td>42.1</td>
|
|
<td>44.2</td>
|
|
<td>48.6</td>
|
|
<td>48.6</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row">Veterans' benefits</th>
|
|
<td>12.8</td>
|
|
<td>7.5</td>
|
|
<td>7.5</td>
|
|
<td>7.5</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row">Cash public assistance</th>
|
|
<td>6.1</td>
|
|
<td>4.0</td>
|
|
<td>4.9</td>
|
|
<td>4.9</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row">Other <sup>c</sup></th>
|
|
<td>8.6</td>
|
|
<td>8.5</td>
|
|
<td>8.5</td>
|
|
<td>8.5</td>
|
|
</tr>
|
|
<tr class="shaded topPad1">
|
|
<th class="stub0" scope="row">Weighted count (thousands)</th>
|
|
<td>22,020</td>
|
|
<td>21,210</td>
|
|
<td>21,210</td>
|
|
<td>21,210</td>
|
|
</tr>
|
|
<tr>
|
|
<td> </td>
|
|
<th colspan="4" class="panel" scope="rowgroup">Women</th>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row">Social Security</th>
|
|
<td>93.8</td>
|
|
<td>87.0</td>
|
|
<td>90.2</td>
|
|
<td>90.2</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row">Asset income</th>
|
|
<td>51.7</td>
|
|
<td>66.6</td>
|
|
<td>66.6</td>
|
|
<td>67.5</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row">Pensions <sup>b</sup></th>
|
|
<td>58.1</td>
|
|
<td>46.2</td>
|
|
<td>46.2</td>
|
|
<td>68.8</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row">Earnings</th>
|
|
<td>30.5</td>
|
|
<td>37.8</td>
|
|
<td>42.0</td>
|
|
<td>42.0</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row">Veterans' benefits</th>
|
|
<td>8.2</td>
|
|
<td>4.1</td>
|
|
<td>4.1</td>
|
|
<td>4.1</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row">Cash public assistance</th>
|
|
<td>9.4</td>
|
|
<td>5.1</td>
|
|
<td>6.8</td>
|
|
<td>6.8</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row">Other <sup>c</sup></th>
|
|
<td>6.7</td>
|
|
<td>12.7</td>
|
|
<td>12.7</td>
|
|
<td>12.7</td>
|
|
</tr>
|
|
<tr class="shaded topPad1">
|
|
<th class="stub0" scope="row">Weighted count (thousands)</th>
|
|
<td>28,132</td>
|
|
<td>26,340</td>
|
|
<td>26,340</td>
|
|
<td>26,340</td>
|
|
</tr>
|
|
</tbody>
|
|
<tfoot>
|
|
<tr>
|
|
<td class="firstNote" colspan="5">SOURCE: Authors' calculations based on <abbr class="spell">HRS</abbr> (wave 13, 2016), 2016 <abbr class="spell">CPS</abbr> <abbr class="spell">ASEC</abbr>, and administrative data from <abbr class="spell">SSA</abbr> and <abbr class="spell">IRS</abbr>. Income questions ask respondent about income received in the previous calendar year (2015).</td>
|
|
</tr>
|
|
<tr>
|
|
<td class="note" colspan="5">a. Approved for release by the Census Bureau's Disclosure Review Board (<abbr class="spell">CBDRB</abbr>-<abbr class="spell">FY</abbr>20-018).</td>
|
|
</tr>
|
|
<tr>
|
|
<td class="note" colspan="5">b. Includes <abbr class="spell">IRA</abbr> withdrawals.</td>
|
|
</tr>
|
|
<tr>
|
|
<td class="lastNote" colspan="5">c. Excludes veterans' benefits.</td>
|
|
</tr>
|
|
</tfoot>
|
|
</table>
|
|
</div>
|
|
<p>In addition to the wide variance in the prevalence of retirement income from pensions and <abbr class="spell">IRA</abbr>s shown in Table 4, some other differences across the four files are worth noting. For instance, the differences in prevalence of Social Security and earnings across the three <abbr class="spell">CPS</abbr> files is relatively small. This reiterates the earlier assertion that the <abbr class="spell">CPS</abbr> <abbr class="spell">PUF</abbr> does reasonably well in measuring Social Security benefits and earnings. Furthermore, note that while there are no major differences across <abbr class="spell">CPS</abbr> files, the <abbr class="spell">HRS</abbr> shows a somewhat higher proportion of aged persons receiving income from Social Security, but a lower proportion with family income from earnings. Lastly, the breakdowns by sex show that the similarities and differences across the four files are more or less consistent.</p>
|
|
<h3>Reliance on Social Security</h3>
|
|
<p>In Table 5, we present Social Security reliance statistics for each of the four files. The sample in Table 5 is restricted to persons in Social Security beneficiary families (that is, at least one family member, respondent or other, is a beneficiary).<sup><a href="#mn18" id="mt18">18</a></sup> The first reliance threshold encompasses individuals for whom family Social Security income comprises 50 percent or more of total family income. The other two reliance thresholds are 75 percent or more and 90 percent or more. We estimate the proportions of aged persons whose ratio of Social Security income to total family income exceed those thresholds. Comparing the two public-use files, we see that the <abbr class="spell">CPS</abbr> <abbr class="spell">PUF</abbr> produces slightly higher reliance figures than the <abbr class="spell">HRS</abbr> <abbr class="spell">PUF</abbr> across the board. For example, the proportion of all persons aged 65 or older relying on Social Security for 50 percent or more of their family income is 49.8 percent in the <abbr class="spell">HRS</abbr> <abbr class="spell">PUF</abbr> compared with 52.5 percent in the <abbr class="spell">CPS</abbr> <abbr class="spell">PUF</abbr>. Similarly, the proportions at the other end of the spectrum (90 percent or more of family income from Social Security) range from 21.2 percent in the <abbr class="spell">HRS</abbr> <abbr class="spell">PUF</abbr> to 25.6 percent in the <abbr class="spell">CPS</abbr> <abbr class="spell">PUF</abbr>. This difference could arise because the <abbr class="spell">HRS</abbr> asks respondents for the net amount of Social Security benefits and thus excludes the Medicare Part B and/or Part D premiums that are deducted from the benefits, whereas the <abbr class="spell">CPS</abbr> asks for the gross Social Security benefit amount, including the Medicare premium (see Dushi, Iams, and Trenkamp 2017).<sup><a href="#mn19" id="mt19">19</a></sup></p>
|
|
<div class="table" id="table5">
|
|
<table>
|
|
<caption><span class="tableNumber">Table 5. </span>Percentages of individuals aged 65 or older for whom Social Security represents a selected proportion of family income, by sex: Measurements from four alternative data files, 2015</caption>
|
|
<colgroup span="1" style="width:14em"></colgroup>
|
|
<colgroup span="2" style="width:8em"></colgroup>
|
|
<colgroup span="2" style="width:8em"></colgroup>
|
|
<thead>
|
|
<tr>
|
|
<th rowspan="2" class="stubHeading" scope="colgroup">Social Security as a proportion of family income</th>
|
|
<th colspan="2" class="spanner" scope="colgroup">Survey data (unmatched)</th>
|
|
<th colspan="2" class="spanner" scope="colgroup">Survey data matched with administrative records <sup>a</sup></th>
|
|
</tr>
|
|
<tr>
|
|
<th scope="col"><abbr class="spell">HRS</abbr> PUF</th>
|
|
<th scope="col"><abbr class="spell">CPS</abbr> PUF</th>
|
|
<th scope="col"><abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr></th>
|
|
<th scope="col"><abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr>+<abbr class="spell">IRS</abbr></th>
|
|
</tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr>
|
|
<td> </td>
|
|
<th colspan="4" class="panel" scope="rowgroup">All</th>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row">50% or more</th>
|
|
<td>49.8</td>
|
|
<td>52.5</td>
|
|
<td>51.1</td>
|
|
<td>39.9</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row">75% or more</th>
|
|
<td>30.5</td>
|
|
<td>33.6</td>
|
|
<td>32.1</td>
|
|
<td>21.2</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row">90% or more</th>
|
|
<td>21.2</td>
|
|
<td>25.6</td>
|
|
<td>23.8</td>
|
|
<td>13.8</td>
|
|
</tr>
|
|
<tr class="shaded topPad1">
|
|
<th class="stub0" scope="row">Weighted count (thousands)</th>
|
|
<td>46,687</td>
|
|
<td>40,520</td>
|
|
<td>42,250</td>
|
|
<td>42,250</td>
|
|
</tr>
|
|
<tr>
|
|
<td> </td>
|
|
<th colspan="4" class="panel" scope="rowgroup">Men</th>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row">50% or more</th>
|
|
<td>44.6</td>
|
|
<td>49.0</td>
|
|
<td>47.9</td>
|
|
<td>37.3</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row">75% or more</th>
|
|
<td>25.8</td>
|
|
<td>30.1</td>
|
|
<td>29.0</td>
|
|
<td>18.6</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row">90% or more</th>
|
|
<td>17.6</td>
|
|
<td>22.5</td>
|
|
<td>21.1</td>
|
|
<td>12.1</td>
|
|
</tr>
|
|
<tr class="shaded topPad1">
|
|
<th class="stub0" scope="row">Weighted count (thousands)</th>
|
|
<td>20,295</td>
|
|
<td>17,800</td>
|
|
<td>18,650</td>
|
|
<td>18,650</td>
|
|
</tr>
|
|
<tr>
|
|
<td> </td>
|
|
<th colspan="4" class="panel" scope="rowgroup">Women</th>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row">50% or more</th>
|
|
<td>53.9</td>
|
|
<td>55.2</td>
|
|
<td>53.7</td>
|
|
<td>42.0</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row">75% or more</th>
|
|
<td>34.1</td>
|
|
<td>36.4</td>
|
|
<td>34.6</td>
|
|
<td>23.3</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row">90% or more</th>
|
|
<td>23.9</td>
|
|
<td>28.0</td>
|
|
<td>25.9</td>
|
|
<td>15.1</td>
|
|
</tr>
|
|
<tr class="shaded topPad1">
|
|
<th class="stub0" scope="row">Weighted count (thousands)</th>
|
|
<td>26,392</td>
|
|
<td>22,720</td>
|
|
<td>23,600</td>
|
|
<td>23,600</td>
|
|
</tr>
|
|
</tbody>
|
|
<tfoot>
|
|
<tr>
|
|
<td class="firstNote" colspan="5">SOURCE: Authors' calculations based on <abbr class="spell">HRS</abbr> (wave 13, 2016), 2016 <abbr class="spell">CPS</abbr> <abbr class="spell">ASEC</abbr>, and administrative data from <abbr class="spell">SSA</abbr> and <abbr class="spell">IRS</abbr>. Income questions ask respondent about income received in the previous calendar year (2015).</td>
|
|
</tr>
|
|
<tr>
|
|
<td class="lastNote" colspan="5">a. Approved for release by the Census Bureau's Disclosure Review Board (<abbr class="spell">CBDRB</abbr>-<abbr class="spell">FY</abbr>20-018).</td>
|
|
</tr>
|
|
</tfoot>
|
|
</table>
|
|
</div>
|
|
<p>Expanding the comparisons to include the <abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr> file reveals similar patterns. The three files yield relatively similar results, with only slight differences between them. For example, the proportions of persons aged 65 or older who rely on Social Security for 75 percent or more of their total family income are 30.5 percent, 33.6 percent, and 32.1 percent, respectively, in the <abbr class="spell">HRS</abbr> <abbr class="spell">PUF</abbr>, <abbr class="spell">CPS</abbr> <abbr class="spell">PUF</abbr>, and <abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr> files. The highest value (from the <abbr class="spell">CPS</abbr> <abbr class="spell">PUF</abbr>) and the lowest (from the <abbr class="spell">HRS</abbr> <abbr class="spell">PUF</abbr>) vary by only 3.1 percentage points.</p>
|
|
<p>Shifting attention to the <abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr>+<abbr class="spell">IRS</abbr> columns of Table 5 shows lower apparent reliance on Social Security when incorporating the <abbr class="spell">IRS</abbr> administrative data. The proportion of persons aged 65 or older who rely on Social Security for 90 percent or more of their family income is 25.6 percent in the <abbr class="spell">CPS</abbr> <abbr class="spell">PUF</abbr>. The proportion is only slightly lower (23.8 percent, a 1.8 percentage point difference) in the <abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr> file. This is not surprising, as the income sources replaced in the <abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr> file (earnings, Social Security, and <abbr class="spell">SSI</abbr>) are relatively accurate in the <abbr class="spell">CPS</abbr> <abbr class="spell">PUF</abbr>; and in the case of <abbr class="spell">SSI</abbr>, the prevalence is low. However, that proportion is substantially lower—13.8 percent—in the <abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr>+<abbr class="spell">IRS</abbr> file. The marginal difference between the <abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr> file (23.8 percent) and the <abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr>+<abbr class="spell">IRS</abbr> file (13.8 percent) is 10 percentage points, which is attributable to a correction in retirement income from the <abbr class="spell">IRS</abbr> administrative data. The same pattern is evident for individuals who rely on Social Security for at least 75 percent or at least 50 percent of family income, and for both men and women across all three reliance-threshold categories.</p>
|
|
<h3>Poverty Rates</h3>
|
|
<p>As with the other metrics, there are clear differences in poverty rates resulting from the additional retirement income captured by incorporating the <abbr class="spell">IRS</abbr> administrative data, which the public-use <abbr class="spell">CPS</abbr> data miss. Table 6 shows that the poverty rate for all persons aged 65 or older is 7.1 percent in the <abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr>+<abbr class="spell">IRS</abbr> file, compared with 8.7 percent in the <abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr> file and 8.8 percent in the <abbr class="spell">CPS</abbr> <abbr class="spell">PUF</abbr>. Interestingly, the result in the <abbr class="spell">HRS</abbr> <abbr class="spell">PUF</abbr> tracks that of the <abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr>+<abbr class="spell">IRS</abbr> file closely, with a slightly lower poverty rate of 6.6 percent.<sup><a href="#mn20" id="mt20">20</a>,<a href="#mn21" id="mt21">21</a></sup></p>
|
|
<div class="table" id="table6">
|
|
<table>
|
|
<caption><span class="tableNumber">Table 6. </span>Percentages of individuals aged 65 or older in or near poverty, by sex, race/ethnicity, and marital status: Measurements from four alternative data files, 2015</caption>
|
|
<colgroup span="1" style="width:14em"></colgroup>
|
|
<colgroup span="4" style="width:8em"></colgroup>
|
|
<thead>
|
|
<tr>
|
|
<th rowspan="2" class="stubHeading" id="c1">Characteristic</th>
|
|
<th colspan="2" class="spanner" id="c2">Survey data (unmatched)</th>
|
|
<th colspan="2" class="spanner" id="c3">Survey data matched with administrative records <sup>a</sup></th>
|
|
</tr>
|
|
<tr>
|
|
<th id="c4" headers="c2"><abbr class="spell">HRS</abbr> PUF</th>
|
|
<th id="c5" headers="c2"><abbr class="spell">CPS</abbr> PUF</th>
|
|
<th id="c6" headers="c3"><abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr></th>
|
|
<th id="c7" headers="c3"><abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr>+<abbr class="spell">IRS</abbr></th>
|
|
</tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr>
|
|
<td> </td>
|
|
<th colspan="4" class="panel" id="r1">In poverty</th>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub2" id="r2" headers="r1 c1">All</th>
|
|
<td headers="r1 r2 c2 c4">6.6</td>
|
|
<td headers="r1 r2 c2 c5">8.8</td>
|
|
<td headers="r1 r2 c3 c6">8.7</td>
|
|
<td headers="r1 r2 c3 c7">7.1</td>
|
|
</tr>
|
|
<tr class="topPad1">
|
|
<th class="stub0" id="r3" headers="r1 c1">Sex</th>
|
|
<td colspan="4"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r4" headers="r1 r3 c1">Men</th>
|
|
<td headers="r1 r3 r4 c2 c4">4.4</td>
|
|
<td headers="r1 r3 r4 c2 c5">7.0</td>
|
|
<td headers="r1 r3 r4 c3 c6">6.9</td>
|
|
<td headers="r1 r3 r4 c3 c7">5.6</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r5" headers="r1 r3 c1">Women</th>
|
|
<td headers="r1 r3 r5 c2 c4">8.4</td>
|
|
<td headers="r1 r3 r5 c2 c5">10.3</td>
|
|
<td headers="r1 r3 r5 c3 c6">10.2</td>
|
|
<td headers="r1 r3 r5 c3 c7">8.3</td>
|
|
</tr>
|
|
<tr class="topPad1">
|
|
<th class="stub0" id="r6" headers="r1 c1">Race/ethnicity</th>
|
|
<td colspan="4"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r7" headers="r1 r6 c1">Non-Hispanic white <sup>b</sup></th>
|
|
<td headers="r1 r6 r7 c2 c4">3.5</td>
|
|
<td headers="r1 r6 r7 c2 c5">7.5</td>
|
|
<td headers="r1 r6 r7 c3 c6">7.5</td>
|
|
<td headers="r1 r6 r7 c3 c7">6.0</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r8" headers="r1 r6 c1">Non-Hispanic black <sup>c</sup></th>
|
|
<td headers="r1 r6 r8 c2 c4">20.6</td>
|
|
<td headers="r1 r6 r8 c2 c5">18.4</td>
|
|
<td headers="r1 r6 r8 c3 c6">16.0</td>
|
|
<td headers="r1 r6 r8 c3 c7">12.9</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r9" headers="r1 r6 c1">Non-Hispanic other <sup>d</sup></th>
|
|
<td headers="r1 r6 r9 c2 c4">8.6</td>
|
|
<td headers="r1 r6 r9 c2 c5">11.8</td>
|
|
<td headers="r1 r6 r9 c3 c6">14.3</td>
|
|
<td headers="r1 r6 r9 c3 c7">13.6</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r10" headers="r1 r6 c1">Hispanic (any race)</th>
|
|
<td headers="r1 r6 r10 c2 c4">22.0</td>
|
|
<td headers="r1 r6 r10 c2 c5">17.5</td>
|
|
<td headers="r1 r6 r10 c3 c6">18.0</td>
|
|
<td headers="r1 r6 r10 c3 c7">16.5</td>
|
|
</tr>
|
|
<tr class="topPad1">
|
|
<th class="stub0" id="r11" headers="r1 c1">Marital status</th>
|
|
<td colspan="4"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r12" headers="r1 r11 c1">Married</th>
|
|
<td headers="r1 r11 r12 c2 c4">2.9</td>
|
|
<td headers="r1 r11 r12 c2 c5">4.4</td>
|
|
<td headers="r1 r11 r12 c3 c6">4.1</td>
|
|
<td headers="r1 r11 r12 c3 c7">3.0</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r13" headers="r1 r11 c1">Nonmarried</th>
|
|
<td headers="r1 r11 r13 c2 c4">12.1</td>
|
|
<td headers="r1 r11 r13 c2 c5">14.6</td>
|
|
<td headers="r1 r11 r13 c3 c6">14.7</td>
|
|
<td headers="r1 r11 r13 c3 c7">12.4</td>
|
|
</tr>
|
|
<tr>
|
|
<td> </td>
|
|
<th colspan="4" class="panel" id="r14">In or near poverty</th>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub2" id="r15" headers="r14 c1">All</th>
|
|
<td headers="r14 r15 c2 c4">10.6</td>
|
|
<td headers="r14 r15 c2 c5">13.8</td>
|
|
<td headers="r14 r15 c3 c6">13.8</td>
|
|
<td headers="r14 r15 c3 c7">11.1</td>
|
|
</tr>
|
|
<tr class="topPad1">
|
|
<th class="stub0" id="r16" headers="r14 c1">Sex</th>
|
|
<td colspan="4"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r17" headers="r14 r16 c1">Men</th>
|
|
<td headers="r14 r16 r17 c2 c4">8.0</td>
|
|
<td headers="r14 r16 r17 c2 c5">10.6</td>
|
|
<td headers="r14 r16 r17 c3 c6">10.8</td>
|
|
<td headers="r14 r16 r17 c3 c7">8.8</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r18" headers="r14 r16 c1">Women</th>
|
|
<td headers="r14 r16 r18 c2 c4">12.8</td>
|
|
<td headers="r14 r16 r18 c2 c5">16.4</td>
|
|
<td headers="r14 r16 r18 c3 c6">16.3</td>
|
|
<td headers="r14 r16 r18 c3 c7">12.9</td>
|
|
</tr>
|
|
<tr class="topPad1">
|
|
<th class="stub0" id="r19" headers="r14 c1">Race/ethnicity</th>
|
|
<td colspan="4"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r20" headers="r14 r19 c1">Non-Hispanic white <sup>b</sup></th>
|
|
<td headers="r14 r19 r20 c2 c4">6.5</td>
|
|
<td headers="r14 r19 r20 c2 c5">12.1</td>
|
|
<td headers="r14 r19 r20 c3 c6">12.2</td>
|
|
<td headers="r14 r19 r20 c3 c7">9.5</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r21" headers="r14 r19 c1">Non-Hispanic black <sup>c</sup></th>
|
|
<td headers="r14 r19 r21 c2 c4">29.8</td>
|
|
<td headers="r14 r19 r21 c2 c5">26.1</td>
|
|
<td headers="r14 r19 r21 c3 c6">23.9</td>
|
|
<td headers="r14 r19 r21 c3 c7">19.5</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r22" headers="r14 r19 c1">Non-Hispanic other <sup>d</sup></th>
|
|
<td headers="r14 r19 r22 c2 c4">10.6</td>
|
|
<td headers="r14 r19 r22 c2 c5">17.3</td>
|
|
<td headers="r14 r19 r22 c3 c6">20.1</td>
|
|
<td headers="r14 r19 r22 c3 c7">19.3</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r23" headers="r14 r19 c1">Hispanic (any race)</th>
|
|
<td headers="r14 r19 r23 c2 c4">31.4</td>
|
|
<td headers="r14 r19 r23 c2 c5">25.7</td>
|
|
<td headers="r14 r19 r23 c3 c6">26.4</td>
|
|
<td headers="r14 r19 r23 c3 c7">24.2</td>
|
|
</tr>
|
|
<tr class="topPad1">
|
|
<th class="stub0" id="r24" headers="r14 c1">Marital status</th>
|
|
<td colspan="4"></td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r25" headers="r14 r24 c1">Married</th>
|
|
<td headers="r14 r24 r25 c2 c4">4.8</td>
|
|
<td headers="r14 r24 r25 c2 c5">6.9</td>
|
|
<td headers="r14 r24 r25 c3 c6">6.5</td>
|
|
<td headers="r14 r24 r25 c3 c7">4.8</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub1" id="r26" headers="r14 r24 c1">Nonmarried</th>
|
|
<td headers="r14 r24 r26 c2 c4">19.2</td>
|
|
<td headers="r14 r24 r26 c2 c5">22.7</td>
|
|
<td headers="r14 r24 r26 c3 c6">23.3</td>
|
|
<td headers="r14 r24 r26 c3 c7">19.2</td>
|
|
</tr>
|
|
<tr class="shaded topPad1">
|
|
<th class="stub0" id="r27" headers="c1">Weighted count (thousands)</th>
|
|
<td headers="r27 c2 c4">50,152</td>
|
|
<td headers="r27 c2 c5">47,550</td>
|
|
<td headers="r27 c3 c6">47,550</td>
|
|
<td headers="r27 c3 c7">47,550</td>
|
|
</tr>
|
|
</tbody>
|
|
<tfoot>
|
|
<tr>
|
|
<td class="firstNote" colspan="5">SOURCE: Authors' calculations based on <abbr class="spell">HRS</abbr> (wave 13, 2016), 2016 <abbr class="spell">CPS</abbr> <abbr class="spell">ASEC</abbr>, and administrative data from <abbr class="spell">SSA</abbr> and <abbr class="spell">IRS</abbr>.</td>
|
|
</tr>
|
|
<tr>
|
|
<td class="note" colspan="5">NOTES: "In poverty" = with income at or below 100% of the federal poverty guideline; "in or near poverty" = with income at or below 125% of the federal poverty guideline.
|
|
<div class="newNote">Poverty measures are based on family income (in 2015 dollars) and 2015 Census Bureau poverty thresholds corresponding to family size and composition.</div>
|
|
<div class="newNote">Estimates are weighted using survey weights.</div>
|
|
</td>
|
|
</tr>
|
|
<tr>
|
|
<td class="note" colspan="5">a. Approved for release by the Census Bureau's Disclosure Review Board (<abbr class="spell">CBDRB</abbr>-<abbr class="spell">FY</abbr>20-018).</td>
|
|
</tr>
|
|
<tr>
|
|
<td class="note" colspan="5">b. Identified in <abbr class="spell">CPS</abbr> as "white alone."</td>
|
|
</tr>
|
|
<tr>
|
|
<td class="note" colspan="5">c. Identified in <abbr class="spell">CPS</abbr> as "black alone."</td>
|
|
</tr>
|
|
<tr>
|
|
<td class="lastNote" colspan="5">d. Identified in <abbr class="spell">CPS</abbr> as "Asian alone."</td>
|
|
</tr>
|
|
</tfoot>
|
|
</table>
|
|
</div>
|
|
<p>A closer look at the three <abbr class="spell">CPS</abbr> files shows that poverty rates of the <abbr class="spell">CPS</abbr> <abbr class="spell">PUF</abbr> and <abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr> files track each other closely for most race/ethnicity categories (Table 6) and age groups (Table 7). Expanding the comparison to include the <abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr>+<abbr class="spell">IRS</abbr> file, Tables 6 and 7 show poverty rates that are lower than those in the other two <abbr class="spell">CPS</abbr> files for nearly all race/ethnicity categories and age groups. The only exception is the Asian (“non-Hispanic other”) race/ethnicity category, for which the poverty rate is 11.8 percent in the <abbr class="spell">CPS</abbr> <abbr class="spell">PUF</abbr>, 14.3 percent in the <abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr> file, and 13.6 percent in the <abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr>+<abbr class="spell">IRS</abbr> file.</p>
|
|
<div class="table" id="table7">
|
|
<table>
|
|
<caption><span class="tableNumber">Table 7. </span>Percentages of individuals aged 65 or older in or near poverty, by age group: Measurements from four alternative data files, 2015</caption>
|
|
<colgroup span="1" style="width:14em"></colgroup>
|
|
<colgroup span="2" style="width:8em"></colgroup>
|
|
<colgroup span="2" style="width:8em"></colgroup>
|
|
<thead>
|
|
<tr>
|
|
<th rowspan="2" class="stubHeading" scope="colgroup">Age group</th>
|
|
<th colspan="2" class="spanner" scope="colgroup">Survey data (unmatched)</th>
|
|
<th colspan="2" class="spanner" scope="colgroup">Survey data matched with administrative records <sup>a</sup></th>
|
|
</tr>
|
|
<tr>
|
|
<th scope="col"><abbr class="spell">HRS</abbr> PUF</th>
|
|
<th scope="col"><abbr class="spell">CPS</abbr> PUF</th>
|
|
<th scope="col"><abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr></th>
|
|
<th scope="col"><abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr>+<abbr class="spell">IRS</abbr></th>
|
|
</tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr>
|
|
<td> </td>
|
|
<th colspan="4" class="panel" scope="rowgroup">In poverty</th>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row"><span class="nobr">65–69</span></th>
|
|
<td>6.9</td>
|
|
<td>8.1</td>
|
|
<td>8.1</td>
|
|
<td>6.8</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row"><span class="nobr">70–74</span></th>
|
|
<td>5.0</td>
|
|
<td>7.8</td>
|
|
<td>7.0</td>
|
|
<td>5.9</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row"><span class="nobr">75–79</span></th>
|
|
<td>6.2</td>
|
|
<td>8.2</td>
|
|
<td>8.7</td>
|
|
<td>7.3</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row">80 or older</th>
|
|
<td>8.3</td>
|
|
<td>11.4</td>
|
|
<td>11.3</td>
|
|
<td>8.5</td>
|
|
</tr>
|
|
<tr>
|
|
<td> </td>
|
|
<th colspan="4" class="panel" scope="rowgroup">In or near poverty</th>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row"><span class="nobr">65–69</span></th>
|
|
<td>10.6</td>
|
|
<td>11.9</td>
|
|
<td>12.0</td>
|
|
<td>10.1</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row"><span class="nobr">70–74</span></th>
|
|
<td>9.0</td>
|
|
<td>12.1</td>
|
|
<td>11.6</td>
|
|
<td>9.7</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row"><span class="nobr">75–79</span></th>
|
|
<td>10.2</td>
|
|
<td>13.6</td>
|
|
<td>13.8</td>
|
|
<td>10.8</td>
|
|
</tr>
|
|
<tr>
|
|
<th class="stub0" scope="row">80 or older</th>
|
|
<td>13.0</td>
|
|
<td>18.5</td>
|
|
<td>18.9</td>
|
|
<td>14.1</td>
|
|
</tr>
|
|
<tr class="shaded topPad1">
|
|
<th class="stub0" scope="rowgroup">Weighted count (thousands)</th>
|
|
<td>50,152</td>
|
|
<td>47,550</td>
|
|
<td>47,550</td>
|
|
<td>47,550</td>
|
|
</tr>
|
|
</tbody>
|
|
<tfoot>
|
|
<tr>
|
|
<td class="firstNote" colspan="5">SOURCE: Authors' calculations based on <abbr class="spell">HRS</abbr> (wave 13, 2016), 2016 <abbr class="spell">CPS</abbr> <abbr class="spell">ASEC</abbr>, and administrative data from <abbr class="spell">SSA</abbr> and <abbr class="spell">IRS</abbr>.</td>
|
|
</tr>
|
|
<tr>
|
|
<td class="note" colspan="5">NOTES: "In poverty" = with income at or below 100% of the federal poverty guideline; "in or near poverty" = with income at or below 125% of the federal poverty guideline.
|
|
<div class="newNote">Poverty measures are based on family income (in 2015 dollars) and 2015 Census Bureau poverty thresholds corresponding to family size and composition.</div>
|
|
<div class="newNote">Estimates are weighted using survey weights.</div>
|
|
</td>
|
|
</tr>
|
|
<tr>
|
|
<td class="lastNote" colspan="5">a. Approved for release by the Census Bureau's Disclosure Review Board (<abbr class="spell">CBDRB</abbr>-<abbr class="spell">FY</abbr>20-018).</td>
|
|
</tr>
|
|
</tfoot>
|
|
</table>
|
|
</div>
|
|
<h2>Summary and Follow-Up Work</h2>
|
|
<p>We have supplemented March 2016 <abbr class="spell">CPS</abbr> data with administrative data from <abbr class="spell">SSA</abbr> and <abbr class="spell">IRS</abbr> and compared the matched data files with the original public-use data to reveal that, despite the redesigned <abbr class="spell">CPS</abbr> questionnaire (first fully implemented in the 2015 survey), underreporting of retirement income continues to be an issue with the public-use data. The analysis presented here confirms earlier research that shows retirement income from sources other than Social Security to be significantly underreported in the <abbr class="spell">CPS</abbr>. While the <abbr class="spell">HRS</abbr> is better than the public-use <abbr class="spell">CPS</abbr> in estimating the income of the aged population, we find that it still produces lower figures than those generated by the <abbr class="spell">CPS</abbr> data supplemented with <abbr class="spell">SSA</abbr> and <abbr class="spell">IRS</abbr> administrative data.</p>
|
|
<p>The <abbr class="spell">CPS</abbr> <abbr class="spell">PUF</abbr> reports Social Security as the primary source of aggregate income among the population aged 65 or older; however, our <abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr>+<abbr class="spell">IRS</abbr> data file reports that pensions (including <abbr class="spell">IRA</abbr> withdrawals) are the largest source of aggregate income. Furthermore, the proportion of persons aged 65 or older relying on Social Security for 90 percent or more of their family income is reported as 25.6 percent in the public-use <abbr class="spell">CPS</abbr> but is 13.8 percent if the <abbr class="spell">CPS</abbr> data are supplemented with the full set of administrative data (<abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr>+<abbr class="spell">IRS</abbr>). For comparison, the <abbr class="spell">HRS</abbr> public-use data report the same statistic as 21.2 percent. Finally, supplementing the <abbr class="spell">CPS</abbr> with <abbr class="spell">SSA</abbr> and <abbr class="spell">IRS</abbr> administrative data resulted in a reduction in the estimated poverty rate among people aged 65 or older from 8.8 percent to 7.1 percent. Meanwhile, the <abbr class="spell">HRS</abbr> produced a somewhat lower poverty rate estimate of 6.6 percent.</p>
|
|
<p>The results presented here provide strong evidence in support of supplementing survey data with administrative data to describe the income of older Americans. Bee and Mitchell (2017) shed light on pervasive underreporting of income from retirement pensions in the <abbr class="spell">CPS</abbr> prior to the questionnaire redesign, and our work confirms that it continues to be an issue. Thus, the <abbr class="spell">CPS</abbr> <abbr class="spell">ASEC</abbr> <abbr class="spell">PUF</abbr> data understate the retirement security and well-being of the aged population. The <abbr class="spell">SSA</abbr> publications <i><a href="/policy/docs/statcomps/income_pop55/index.html">Income of the Population 55 or Older</a></i> and the <i><a href="/policy/docs/chartbooks/income_aged/index.html">Income of the Aged Chartbook</a></i> reach both the media and policymakers. Through 2016, those publications used the <abbr class="spell">CPS</abbr> <abbr class="spell">ASEC</abbr> <abbr class="spell">PUF</abbr>; they have since been suspended, pending analysis of the redesigned <abbr class="spell">CPS</abbr> questionnaire and potential alternative data sources. We find that survey data supplemented with administrative data are needed to ensure that these publications provide the public with reliable information.</p>
|
|
<p>Of course, moving from exclusively public-use data to blended survey and administrative data is not without risks and challenges. Of utmost concern when using administrative data is the avoidance of any disclosure that could potentially lead to the identification of individuals. It is worth noting that <abbr class="spell">SSA</abbr>, the Census Bureau, and <abbr class="spell">IRS</abbr> take the protection of personally identifiable information very seriously. However, the measures necessary to protect administrative data present challenges to the timely release of statistics. For a statistical publication released on a regular basis, this could be an important consideration. In this case, matching the <abbr class="spell">CPS</abbr> with administrative data from <abbr class="spell">SSA</abbr> and <abbr class="spell">IRS</abbr> requires interagency cooperation and lengthy disclosure review processes that would inevitably result in delays.</p>
|
|
<p>In forthcoming work we plan to make several additions and improvements. We will extend the analysis on aggregate income to include total dollar amounts by each income source for each data file. This should add some much-needed context to the current presentation of the distribution of aggregate income by source. Additionally, we plan to include a more detailed look at the population distributions by income level across the four data files. This will include statistics on mean and median income within each income quintile. Lastly, we plan to conduct sensitivity analyses including investigating whether respondents with matched administrative records differ systemically from unmatched respondents, and reweighting the matched <abbr class="spell">CPS</abbr> sample.</p>
|
|
<h2 id="appA">Appendix A: Definitions of Income and Poverty in <abbr class="spell">CPS</abbr></h2>
|
|
<h3 class="bottomPad05">Income</h3>
|
|
<ul>
|
|
<li><b>Earnings</b>: Includes the following…
|
|
<ul>
|
|
<li><b>Wages and salaries</b>: Money wages or salary is defined as total money earnings received for work performed as an employee during the income year. It includes wages, salary, Armed Forces pay, commissions, tips, piece-rate payments, and cash bonuses earned, before deductions are made for taxes, bonds, pensions, union dues, and so forth. Earnings for self-employed persons in incorporated businesses are considered wage and salary.</li>
|
|
<li><b>Self-employment</b>: Income from self-employment is the combined income from farm and nonfarm self-employment. Farm self-employment is net money income (gross receipts minus operating expenses) from the operation of a farm by a person on their own account, as an owner, as a renter, or as a sharecropper. Nonfarm self-employment is net money income (gross receipts minus expenses) from one's own business, professional enterprise, or partnership.</li>
|
|
</ul>
|
|
</li>
|
|
<li><b>Asset income</b>: Includes the following…
|
|
<ul>
|
|
<li><b>Interest income</b>: Interest includes payments people receive (or have credited to their accounts) from bonds, treasury notes, <abbr class="spell">IRA</abbr>s, certificates of deposit, interest-bearing savings and checking accounts, and all other investments that pay interest.</li>
|
|
<li><b>Dividends</b>: Dividends include income people receive from stock holdings and mutual fund shares. The <abbr class="spell">CPS</abbr> does not include capital gains from the sale of stock holdings as income.</li>
|
|
<li><b>Rents, royalties, and estates and trusts</b>: Include net income people receive from the rental of a house, store, or other property, receipts from boarders or lodgers, net royalty income, and periodic payments from estate or trust funds.</li>
|
|
</ul>
|
|
</li>
|
|
<li><b>Retirement benefits</b>: is the sum of Social Security benefits and public and private pensions.
|
|
<ul>
|
|
<li><b>Social Security</b>: Social Security includes retired-worker benefits, dependents' or survivor benefits, and disability benefits made by <abbr class="spell">SSA</abbr> prior to deductions for medical insurance and railroad retirement insurance checks from the <abbr>U.S.</abbr> Government. Medicare reimbursements are not included.</li>
|
|
<li><b>Pensions</b>: Includes the following…
|
|
<ul>
|
|
<li><b>Employer pensions</b>: Employer pensions include pensions from Railroad Retirement, government employee pensions, and private pensions and annuities.</li>
|
|
<li><b>Government employee pensions</b>: Government employee pensions include payments from federal government (civil service), military, and state or local governments.</li>
|
|
<li><b>Private pensions and annuities</b>: Private pensions and annuities include payments from companies or unions, annuities or <span class="nobr">paid-up</span> insurance policies, <abbr class="spell">IRA</abbr>s, Keogh, or <span class="nobr">401(k)</span> payments.</li>
|
|
</ul>
|
|
</li>
|
|
</ul>
|
|
</li>
|
|
<li><b>Cash public assistance</b>: Includes the following…
|
|
<ul>
|
|
<li><b>Supplemental Security Income</b>: Includes federal, state, and local welfare agency payments to low-income people who are 65 years old or older, or people of any age who are blind or disabled.</li>
|
|
<li><b>Other public assistance</b>: Includes cash public assistance payments low-income people receive, such as Aid to Families with Dependent Children (<abbr class="spell">AFDC</abbr>, <abbr class="spell">ADC</abbr>), temporary assistance to needy families (<abbr title="TAN F">TANF</abbr>), general assistance, and emergency assistance.</li>
|
|
</ul>
|
|
</li>
|
|
<li><b>Other income</b>: is total income minus earnings, Social Security, pensions, asset income, and cash public assistance; included are unemployment and workers' compensation, veterans' payments, and personal contributions.
|
|
<ul>
|
|
<li><b>Unemployment compensation</b>: Includes payments the respondent received from government unemployment agencies or private companies during periods of unemployment and any strike benefits the respondent received from union funds.</li>
|
|
<li><b>Workers' compensation</b>: Includes payments people receive periodically from public or private insurance companies for injuries received at work.</li>
|
|
<li><b>Veterans' payments</b>: Include payments disabled members of the armed forces or survivors of deceased veterans receive periodically from the Department of Veterans Affairs for education and on-the-job training, and means-tested assistance to veterans.</li>
|
|
<li><b>Personal contributions</b>: Include child support, alimony, and financial assistance from friends and relatives.</li>
|
|
</ul>
|
|
</li>
|
|
</ul>
|
|
<p class="noindent">For additional details on income definitions in the <abbr class="spell">CPS</abbr> <abbr class="spell">ASEC</abbr>, see Census Bureau (2020, <span class="nobr">7.3–7.5).</span></p>
|
|
<h3>Poverty Rate</h3>
|
|
<p>Following the Office of Management and Budget's (<abbr class="spell">OMB</abbr>'s) Directive 14, the Census Bureau uses a set of money income thresholds that vary by family size and composition to detect who is poor. If a family's total income is less than that family's threshold, then that family, and every individual in it, is considered poor. The poverty thresholds do not vary geographically, but they are updated annually for inflation with the Consumer Price Index (<abbr class="spell">CPI</abbr>). The official poverty definition counts money income before taxes and excludes capital gains and noncash benefits (such as public housing, Medicaid, and Supplemental Nutrition Assistance Program benefits).</p>
|
|
<p>Poverty statistics are based on a definition developed by <abbr class="spell">SSA</abbr>'s Mollie Orshansky in 1964 and revised in 1969 and 1981 by interagency committees. This definition was established as the official definition of poverty for statistical use in all Executive departments in 1969 (in Bureau of the Budget Circular <abbr title="Number">No.</abbr> <span class="nobr">A-46)</span> and was reconfirmed in <abbr class="spell">OMB</abbr> Statistical Policy Directive <abbr title="Number">No.</abbr> 14. For further details, see the section, “Changes in the Definition of Poverty,” in Census Bureau (1982).</p>
|
|
<p>The poverty thresholds are increased each year by the same percentage as the annual average <abbr class="spell">CPI</abbr>.</p>
|
|
<h2 id="appB">Appendix B: Definitions of <abbr class="spell">HRS</abbr> Income Variables and Poverty Rate</h2>
|
|
<h3>Earnings (individual-level variable)</h3>
|
|
<p>For each <abbr class="spell">HRS</abbr> respondent, total survey-reported earnings is the sum of reported wages, self-employment income, and business and farm income. For couples, the spouse's earnings, defined in the same way, are included. In the <abbr>RAND</abbr>-<abbr class="spell">HRS</abbr> file, self-employment income and household business and farm income are included in household capital income. Therefore, to be consistent with <abbr class="spell">CPS</abbr>, we subtract self-employment income and household business and farm income from the capital income category and add them to the earnings category.</p>
|
|
<h3>Social Security Benefits (individual-level variable)</h3>
|
|
<p>For each respondent, the self-reported amount of Social Security benefits is defined as the sum of retired-worker benefits, dependent or survivor benefits, and disability benefits. For married couples, the spouse's Social Security benefits (if any), defined the same way, are included. Thus, the household's total Social Security benefits variable is the sum of benefits received by both respondent and spouse.</p>
|
|
<h3>Asset Income (household-level variable)</h3>
|
|
<p>Asset income in the <abbr class="spell">HRS</abbr> is the household capital income, which aggregates several other variables reported in the survey. It includes business or farm income, self-employment earnings, business income, gross rent, dividend and interest income, trust funds and royalties, and other asset income. To be consistent with <abbr class="spell">CPS</abbr> definition, as noted above, we subtract business or farm income and self-employment earnings from the asset income variable, and include them instead in the earnings category. For couples, the amount for this variable is divided by two and assigned to the total income for each spouse.</p>
|
|
<h3>Cash Public Assistance (individual-level variable)</h3>
|
|
<p>In the <abbr>RAND</abbr>-<abbr class="spell">HRS</abbr> public data, income from public programs is an aggregate variable called government transfers, which is the sum of self-reported amounts of veterans' benefits, welfare, and food stamps. For this study, to make our “cash public assistance” variable (<a href="#table4">Table 4</a>) consistent with the <abbr class="spell">CPS</abbr> data, we subtract the amount of veterans' benefits and add the amount of self-reported <abbr class="spell">SSI</abbr> payments received. The <abbr class="spell">HRS</abbr> government transfer variable and its components are available separately for each respondent and for the spouse of a married respondent. We create a household-level variable, which is equal to either the respondent's amount (if not married) or the sum of respondent's and spouse's amounts (if married).</p>
|
|
<h3>Other Income (household-level variable)</h3>
|
|
<p>In the <abbr class="spell">HRS</abbr> data, “other income” includes alimony; lump sums from insurance, pensions, and inheritances; and income from miscellaneous other sources. By contrast, in the <abbr class="spell">CPS</abbr> data, the variable “other income” includes unemployment and workers compensation, veterans' benefits, personal contributions (such as child support, alimony, and financial assistance), and income from miscellaneous other sources. To make the <abbr class="spell">HRS</abbr> and <abbr class="spell">CPS</abbr> variables consistent, we define “other income” as the combined household amounts of veterans' benefits; unemployment and workers compensation; alimony; lump sums from insurance, pension, and inheritance; and income from miscellaneous other sources.</p>
|
|
<h3>Pension Income (individual-level variable)</h3>
|
|
<p>In the <abbr class="spell">HRS</abbr>, the pension income variable includes self-reported regular income received from all pensions and annuities; if the respondent is married, the spouse's pension income is similarly defined. While the <abbr class="spell">HRS</abbr> question asks about different types of pension (such as, veterans' benefits, retirement or other pensions, annuities, <abbr class="spell">IRA</abbr> distributions, stocks and bonds, and other), this pension income variable is created by <abbr>RAND</abbr> and does not include veterans' benefits.<sup><a href="#mn22" id="mt22">22</a></sup> The pension income variable also omits withdrawals or distributions from <abbr class="spell">IRA</abbr> accounts. However, a separate variable is available in the <abbr>RAND</abbr>-<abbr class="spell">HRS</abbr> data file and is called “<abbr class="spell">IRA</abbr> withdrawals in the last calendar year.” Hence, we create a household-level variable, which is the sum of <abbr class="spell">IRA</abbr> withdrawals and income from pensions and annuities received by the respondent and, if married, also by the spouse. We recognize that this derived variable may not exactly track the pension income in the <abbr class="spell">CPS</abbr> <abbr class="spell">PUF</abbr>, but it may more closely compare with the pension income variable in the <abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr>+<abbr class="spell">IRS</abbr> file (which includes <abbr class="spell">IRA</abbr> withdrawals).</p>
|
|
<h3>Total Household Income (respondent and spouse only)</h3>
|
|
<p>In the <abbr class="spell">HRS</abbr>, total household income is calculated as the sum of the respondent's and the spouse's earnings, pensions and annuities, <abbr class="spell">SSI</abbr> payments, Social Security disability and retirement benefits, unemployment and workers compensation, other government transfers, household capital income, and other income. This is the variable we use in Tables <span class="nobr"><a href="#table3">3</a>–<a href="#table5">5</a>.</span> For estimating the poverty rate in Tables <a href="#table6">6</a> and <a href="#table7">7</a>, we use the family income variable created by <abbr>RAND</abbr> for calculating poverty rate (see below). The difference between total household income and family income is that the latter includes the amount deducted from Social Security benefits for Medicare Part B and/or Part D premiums and it excludes noncash benefits (such as food stamps) and capital gains and losses. Therefore, it is likely that using the latter measure may result in a lower poverty rate than using the total household income measure. However, it is also worth noting that only 22 percent of the <abbr class="spell">HRS</abbr> sample aged 65 or older live in a family with three or more members (<a href="#table1">Table 1</a>).</p>
|
|
<h3>Poverty Rate</h3>
|
|
<p>According to the <abbr>RAND</abbr> <abbr class="spell">HRS</abbr> data documentation, <abbr class="spell">HRS</abbr> poverty measures follow the methods and definitions that the Census Bureau applies to <abbr class="spell">CPS</abbr> data to derive the national poverty rate. The poverty threshold that applies to an <abbr class="spell">HRS</abbr> family is determined by using poverty threshold levels defined annually by the Census Bureau for each family composition type. The two key variables for applying these methods to <abbr class="spell">HRS</abbr> families are income and family composition.</p>
|
|
<p>Family composition is determined by the number of resident family members, the number of those aged under 18, and the age of the head of household in one- or two-member households. People living in institutions, such as nursing homes and college dormitories, are not included when counting resident family members.</p>
|
|
<p>Family income includes before-tax incomes from earnings, unemployment insurance, and worker's compensation; <abbr class="spell">SSI</abbr>, public assistance, and veterans' benefits; Social Security income before deductions;<sup><a href="#mn23" id="mt23">23</a></sup> pension and retirement income; interest, dividends, rents, royalties, and income from estates and trusts; education assistance; alimony and child support; assistance from outside the household; other sources; and income of all resident family members. Income does not include noncash benefits such as Supplemental Nutrition Assistance Program benefits (food stamps) and capital gains and losses.</p>
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<p>Education assistance and other sources are assumed to have been reported as “other income” in the <abbr class="spell">HRS</abbr>, but it is likely that at least some assistance from outside the household may not be included in any of the <abbr class="spell">HRS</abbr> income categories. The <abbr class="spell">HRS</abbr> total household income—less food stamps, and including Medicare Part B and/or Part D premiums deducted from Social Security—would seem to be close to the Census definition of income, with the exception of income from resident family members besides the respondent and spouse. Survey questions ask about the income of resident family members, including the earnings of each and the total <span class="nobr">non-job</span> income of them all. With these questions, the income of all resident family members can be estimated, but is not included in total household income. More specifically, total household income, for poverty calculation purposes, is equal to:</p>
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<blockquote>(Total household income – food stamps)</blockquote>
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<blockquote>+ (Medicare Part B and/or Part D premiums in instances when the respondent had deducted these amounts from reported Social Security benefits)</blockquote>
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<blockquote>+ (income of <span class="nobr">non-core</span> resident family members)</blockquote>
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<blockquote>– (income of any core <abbr class="spell">HRS</abbr> nursing home residents, including earnings, pensions, Social Security, <abbr class="spell">SSI</abbr>, unemployment and workers compensation, and government transfer income)</blockquote>
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<p>Family composition is defined based on household members reported at the time of the interview. Then, after the income and poverty threshold are determined as described above, the <abbr class="spell">HRS</abbr> family income is compared with the appropriate poverty threshold for the last calendar year. If household income for the last calendar year is below the poverty threshold then the household is defined as being in poverty.<sup><a href="#mn24" id="mt24">24</a></sup></p>
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<p>Another variable available in the <abbr>RAND</abbr> <abbr class="spell">HRS</abbr> file is the ratio of household income to the poverty threshold. We use this variable to construct the poverty measures used in this study. If the ratio of household income to the poverty threshold is equal to or less than 1 (at or below 100 percent of the poverty threshold) then the respondent is defined as being in poverty. If the ratio of household income to the poverty threshold is equal to or less than 1.25 (at or below 125 percent of the poverty threshold) then the respondent is defined as being in or near poverty. </p>
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<div id="notes">
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<h2>Notes</h2>
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<p> <a href="#mt1" id="mn1">1</a> Although <abbr class="spell">ORES</abbr> had previously published occasional <abbr class="spell">CPS</abbr>-based statistics on income of the aged population, biennial publication began in 1976.</p>
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<p> <a href="#mt2" id="mn2">2</a> Every year, the Census Bureau fields the <abbr class="spell">CPS</abbr> <abbr class="spell">ASEC</abbr> in February and releases its results in March. Users have traditionally used the <abbr class="spell">CPS</abbr> <abbr class="spell">ASEC</abbr> and March <abbr class="spell">CPS</abbr> nomenclature interchangeably. Hereafter in this paper, we use “<abbr class="spell">CPS</abbr> <abbr class="spell">ASEC</abbr>” and “March <abbr class="spell">CPS</abbr>” (or simply “<abbr class="spell">CPS</abbr>”) interchangeably.</p>
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<p> <a href="#mt3" id="mn3">3</a> Chen, Munnell, and Sanzenbacher compared the <abbr class="spell">CPS</abbr> with the Survey of Consumer Finances (<abbr class="spell">SCF</abbr>), the <abbr class="spell">HRS</abbr>, the Survey of Income and Program Participation (<abbr>SIPP</abbr>), and the Panel Study of Income Dynamics (<abbr class="spell">PSID</abbr>). When comparing aggregate retirement income (other than Social Security) from <abbr class="spell">SOI</abbr> data with the survey results, they found that the <abbr class="spell">SCF</abbr>, <abbr class="spell">HRS</abbr>, <abbr>SIPP</abbr>, and <abbr class="spell">PSID</abbr> accounted for 99 percent, 94 percent, 97 percent, and 85 percent of retirement income, respectively. However, they found that the <abbr class="spell">CPS</abbr> accounted for only about 47 percent of the aggregate non–Social Security retirement income based on the <abbr class="spell">SOI</abbr> data. </p>
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<p> <a href="#mt4" id="mn4">4</a> In the tables and throughout this paper we will refer to the <abbr class="spell">HRS</abbr> public data as <abbr class="spell">HRS</abbr> <abbr class="spell">PUF</abbr> for brevity and consistency with <abbr class="spell">CPS</abbr> <abbr class="spell">PUF</abbr>. </p>
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<p> <a href="#mt5" id="mn5">5</a> The results presented in this paper were approved for release by the Census Bureau's Disclosure Review Board (<abbr class="spell">CBDRB</abbr>-<abbr class="spell">FY</abbr>20-018). This paper is released to inform interested parties of ongoing research and to encourage discussion of work in progress. The views expressed on statistical issues are those of the authors and not necessarily those of the Census Bureau or the <abbr class="spell">IRS</abbr>.</p>
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<p> <a href="#mt6" id="mn6">6</a> A family is a group of two or more people (one of whom is the householder) related by birth, marriage, or adoption and residing together; all such people (including related subfamily members) are considered members of one family. For persons aged 65 or older, we assign the total value of family income at each unit of observation. This value will simply be one's own personal income in the case of single persons aged 65 or older living alone. For others this value will likely be the combined income of the householder and a spouse. In some cases, it will be the combined income of the person aged 65 or older and any related subfamily members (spouse, child, other) living in the household.</p>
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<p> <a href="#mt7" id="mn7">7</a> We used the same <abbr class="spell">SSA</abbr> and <abbr class="spell">IRS</abbr> data files that Bee and Mitchell used. We matched the administrative data files to the <abbr class="spell">CPS</abbr> using the Personal Identification Key (<abbr class="spell">PIK</abbr>). The Census Bureau uses the <abbr class="spell">PIK</abbr> to link administrative records with survey data. For the 2016 <abbr class="spell">CPS</abbr> (2015 income reference year), about 90 percent of respondents aged 65 or older were assigned a <abbr class="spell">PIK</abbr>, and therefore could be matched to administrative data. Bee and Mitchell (2017) limited their sample to survey respondents assigned a <abbr class="spell">PIK</abbr> and then reweighted the sample. For simplicity, we have opted to keep the full sample of <abbr class="spell">CPS</abbr> respondents aged 65 or older and to use the survey weights. After testing a number of ways to tabulate our statistics, we decided not to exclude those survey respondents without a <abbr class="spell">PIK</abbr> and not to reweight the sample. The 90 percent match rate is high enough that any differences were negligible.</p>
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<p> <a href="#mt8" id="mn8">8</a> The <abbr class="spell">HRS</abbr> survey is conducted by the University of Michigan with support from National Institute on Aging and <abbr class="spell">SSA</abbr>. The raw data files are available at the <abbr class="spell">HRS</abbr> website, but compiling even a subset of the extensive amount of the available <abbr class="spell">HRS</abbr> data would require a prohibitive amount of a user's time. To make the <abbr class="spell">HRS</abbr> data easier and more accessible for users, <abbr>RAND</abbr> Corporation—through a subcontract from <abbr class="spell">HRS</abbr>—compiles, maintains and updates a user-friendly data file, which contains a subset of data with variables that are most widely used by the research community. </p>
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<p> <a href="#mt9" id="mn9">9</a> The <abbr>RAND</abbr> documentation data file states that: “We assume that educational assistance and other sources would have been reported as 'other income' in the <abbr class="spell">HRS</abbr>, but it is likely that at least some assistance from outside the household may not be included in any of the <abbr class="spell">HRS</abbr> income categories. The <abbr class="spell">HRS</abbr> total household income, e.g., as calculated in <abbr class="spell">H6ITOT</abbr> on the <abbr>RAND</abbr> <abbr class="spell">HRS</abbr> Longitudinal File, less food stamps, and including Medicare Part B and/or Part D premiums deducted from Social Security, would seem to be close to the Census definition of income, with the exception of income from resident family members besides the Respondent and spouse. … Questions ask about the income of resident family members, including the earnings of each and total <span class="nobr">non-job</span> income of them all. With these questions, we can estimate income of all resident family members, which is not included in <abbr class="spell">HwITOT</abbr>” (Bugliari and others 2020, 33).</p>
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<p><a href="#mt10" id="mn10">10</a> Note that different income measures in the <abbr>RAND</abbr> <abbr class="spell">HRS</abbr> file are reported separately for respondents and spouses (if married), and overall for the household. In general, with the exception of other income, the household variables are simply the sum of the respondent and spouse income. Hence, while we use the “household” reference to be consistent with terminology used in the <abbr>RAND</abbr> <abbr class="spell">HRS</abbr> file, we believe that the income variables in <abbr class="spell">HRS</abbr> are closer to the family income, particularly for respondents who live alone or with only a spouse/partner. For the estimations in this paper, we use the total household income measure (<abbr class="spell">H13ITOT</abbr>), which as noted in the previous footnote does not include income of other family members, unless reported in other income. To the extent that incomes of other resident family members are not reported, our measure of household income may likely underestimate family income among respondents with resident family members (other than spouse). However, given the age group for our study, it is plausible that it may not be a major issue, since only 22 percent of the <abbr class="spell">HRS</abbr> sample aged 65 or older live in a family with 3 or more members. In future updates to this paper, we will try to quantify the extent and magnitude of income from other resident members, and determine whether it may affect results.</p>
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<p><a href="#mt11" id="mn11">11</a> Since its inception in 1992, the <abbr class="spell">HRS</abbr> has asked respondents to provide consent to link the survey information with data from <abbr class="spell">IRS</abbr>'s earnings and <abbr class="spell">SSA</abbr>'s benefits records. Until the 2004 wave, the consent form was retrospective, meaning that the records could be matched for all years prior to the consent year. Thus, for someone who consented in 2004, the record would be matched up to the year 2003. In the 2006 wave, the form was changed to allow prospective consent, with which records could be matched up to the year 2030. In addition, in 2006, the <abbr class="spell">HRS</abbr> introduced face-to-face (<abbr class="spell">FTF</abbr>) interviews for half of the sample, with the <abbr class="spell">FTF</abbr> interview samples to rotate in subsequent waves. The rationale was that <abbr class="spell">FTF</abbr> interviews would lead to increased consent rates and respondents who provided consent would not be asked again. As a result of <abbr class="spell">FTF</abbr> interviews, the <abbr class="spell">HRS</abbr> match rate increased to <span class="nobr">65–75</span> percent. However, in 2012, the consent form changed again, and instead of prospective consent to match earnings and benefits records up to 2030, the match was allowed for up to 6 years after the consent year for <abbr class="spell">IRS</abbr> earnings records and up to 12 years for <abbr class="spell">SSA</abbr> benefits records. This new shorter-term prospective match would apply even to those respondents who consented prior to 2012 and consequently all survey respondents would need to be asked again for new consents every 6 to 8 years. Hence, in 2016, half of the sample of any age without a valid consent were asked to provide a consent. Expectedly, these changes affected the consent rate for the overall sample and particularly for the sample aged 65 or older.</p>
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<p><a href="#mt12" id="mn12">12</a> Those results are available on request from the authors.</p>
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<p><a href="#mt13" id="mn13">13</a> For additional detail on the <abbr class="spell">IRS</abbr> data extracts, see Bee and Mitchell (2017).</p>
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<p><a href="#mt14" id="mn14">14</a> For each income source, we use survey weights to aggregate the income for the total for <abbr>U.S.</abbr> population. Then, we calculate each source's share of the total income.</p>
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<p><a href="#mt15" id="mn15">15</a> Note that <abbr class="spell">CPS</abbr> <abbr class="spell">PUF</abbr> and <abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr> files use pension income as reported in the survey, whereas <abbr class="spell">CPS</abbr>+<abbr class="spell">SSA</abbr>+<abbr class="spell">IRS</abbr> replaces the survey-reported pension income with data from <abbr class="spell">IRS</abbr> records.</p>
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<p><a href="#mt16" id="mn16">16</a> See <a href="#appA">Appendices</a> for <abbr class="spell">CPS</abbr> and <abbr class="spell">HRS</abbr> definitions of the “other income” category.</p>
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<p><a href="#mt17" id="mn17">17</a> See <a href="#appB">Appendix B</a> for the definitions of household (family) income in <abbr class="spell">HRS</abbr>. </p>
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<p><a href="#mt18" id="mn18">18</a> Note that in the <abbr class="spell">HRS</abbr>, the family income measures include only the income received from the respondents (if single, widowed, divorced, or separated) and from the spouse or partner income (if coupled). Hence, the Social Security beneficiary can be either the respondent, or the spouse, or both.</p>
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<p><a href="#mt19" id="mn19">19</a> The reliance rates may also be higher in the <abbr class="spell">CPS</abbr> than the <abbr class="spell">HRS</abbr> because the <abbr class="spell">CPS</abbr> defines family income as including income of family members in addition to the spouse, increasing the reported amount of family income received from Social Security. In future updates, we will provide estimates of mean and median Social Security income at the respondent and family level for both the <abbr class="spell">HRS</abbr> and <abbr class="spell">CPS</abbr> samples.</p>
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<p><a href="#mt20" id="mn20">20</a> It is worth emphasizing that the different poverty rates in the <abbr class="spell">HRS</abbr> and the <abbr class="spell">CPS</abbr> may be due to several reasons that affect family income and consequently poverty rate. First, as <a href="#table1">Table 1</a> shows, <abbr class="spell">HRS</abbr> respondents are more likely than <abbr class="spell">CPS</abbr> respondents to live in a family with three or more members and are more likely to be Social Security beneficiaries. Second, <abbr class="spell">HRS</abbr> respondents are more likely to be in families with income of $50,000 or more (45.7 percent versus 44.7 percent; see <a href="#table3">Table 3</a>). Both of these factors would plausibly lead to higher total family income and lower poverty rates in the <abbr class="spell">HRS</abbr>. Third, the total family income variable in the <abbr>RAND</abbr>-<abbr class="spell">HRS</abbr> data file does not include the income of other residing family members, although only 22 percent of <abbr class="spell">HRS</abbr> respondents aged 65 or older live in a family with three or more members and are affected by this exclusion. Lastly, the family income measure in Table 3 does not include Medicare Part B and/or Part D premiums deducted from Social Security benefits, whereas these amounts are included in the family income variable used for calculating poverty rate in Tables <a href="#table6">6</a> and <a href="#table7">7</a>. The addition of Medicare premiums would lead to higher income and thus an upward shift in income distribution and a lower poverty rate. See <a href="#appB">Appendix B</a> for a detailed discussion of the <abbr class="spell">HRS</abbr> total income and poverty measures.</p>
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<p><a href="#mt21" id="mn21">21</a> Also, as noted above, Czajka and Denmead (2008) found that <abbr class="spell">HRS</abbr>-reported household income in 2002 among people aged 51 or older was <span class="nobr">20–30</span> percent higher than that in the <abbr class="spell">CPS</abbr>, with <abbr class="spell">HRS</abbr> respondents being less likely to live alone than their <abbr class="spell">CPS</abbr> counterparts. This, if still the case in the 2016 wave of the <abbr class="spell">HRS</abbr>, would help explain the poverty rate being lower in the <abbr class="spell">HRS</abbr> than the <abbr class="spell">CPS</abbr>. In future updates of this paper, we will examine whether higher-income families are overrepresented in the <abbr class="spell">HRS</abbr> survey relative to the <abbr class="spell">CPS</abbr>, along with other factors that could contribute to the difference in poverty rates observed in the two surveys.</p>
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<p><a href="#mt22" id="mn22">22</a> It is worth remembering that for the sake of comparability with <abbr class="spell">CPS</abbr>, we subtracted veterans' benefits from the <abbr class="spell">HRS</abbr> government transfers variable and added them to other income.</p>
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<p><a href="#mt23" id="mn23">23</a> Medicare Part B and/or Part D premiums are added if the respondent reports that they were deducted from Social Security payments.</p>
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<p><a href="#mt24" id="mn24">24</a> Note that the terms household income and family income are used interchangeably in the <abbr class="spell">HRS</abbr>. </p>
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</div>
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<div id="references">
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<h2>References</h2>
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<p>Anguelov, Chris E., Howard M. Iams, and Patrick J. Purcell. 2012. “<a href="/policy/docs/ssb/v72n3/v72n3p59.html">Shifting Income Sources of the Aged</a>.” <i>Social Security Bulletin</i> 72(3): <span class="nobr">59–68.</span></p>
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<p>Bee, C. Adam, and Joshua W. Mitchell. 2017. “Do Older Americans Have More Income Than We Think?” <abbr class="spell">SEHSD</abbr> Working Paper <abbr title="Number">No.</abbr> <span class="nobr">2017-39.</span> Washington, <abbr class="spell">DC</abbr>: Census Bureau, Social, Economic, and Housing Statistics Division.</p>
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<p>Bollinger, Christopher R. 1998. “Measurement Error in the Current Population Survey: A Nonparametric Look.” <i>Journal of Labor Economics</i> 16(3): <span class="nobr">576–594.</span></p>
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<p>Bound, John, Charles Brown, and Nancy Mathiowetz. 2001. “Measurement Error in Survey Data.” In <i>Handbook of Econometrics, Volume 5,</i> edited by James J. Heckman and Edward Leamer <span class="nobr">(3705–3843).</span> Amsterdam: Elsevier Science <abbr class="spell">BV</abbr>.</p>
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<p>Bricker, Jesse, and Gary V. Engelhardt. 2007. “Measurement Error in Earnings Data in the Health and Retirement Study.” Working Paper <abbr title="Number">No.</abbr> <span class="nobr">2007-16.</span> Chestnut Hill, <abbr title="Massachusetts">MA</abbr>: Center for Retirement Research at Boston College.</p>
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<p>Bugliari, Della, Joanna Carroll, Orla Hayden, Jessica Hayes, Michael Hurd, Adam Karabatakis, Regan Main, Joyce Marks, Colleen McCullough, Erik Meijer, Michael Moldoff, Philip Pantoja, Susan Rohwedder, and Patricia <abbr title="Saint">St.</abbr> Clair. 2020. <i><abbr>RAND</abbr> <abbr class="spell">HRS</abbr> Longitudinal File 2016 (V2) Documentation.</i> Santa Monica, <abbr title="California">CA</abbr>: <abbr>RAND</abbr> Center for the Study of Aging.</p>
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<p>Census Bureau. 1982. <i>Characteristics of the Population Below the Poverty Level: 1980.</i> Current Population Reports Series <span class="nobr">P-60,</span> <abbr title="Number">No.</abbr> 133. Washington, <abbr class="spell">DC</abbr>: Government Printing Office.</p>
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<p>———. 2020. <i>Current Population Survey 2020 Annual Social and Economic (<abbr class="spell">ASEC</abbr>) Supplement Technical Documentation.</i> Washington, <abbr class="spell">DC</abbr>: Census Bureau. <a href="https://www.census.gov/data/datasets/time-series/demo/cps/cps-asec.html">https://www.census.gov/data/datasets/time-series/demo/cps/cps-asec.html</a>.</p>
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<p>Chen, Anqi, Alicia H. Munnell, and Geoffrey T. Sanzenbacher. 2018. “How Much Income Do Retirees Actually Have? Evaluating the Evidence from Five National Datasets.” Working Paper <abbr title="Number">No.</abbr> <span class="nobr">2018-14.</span> Chestnut Hill, <abbr title="Massachusetts">MA</abbr>: Center for Retirement Research at Boston College.</p>
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<p>Czajka, John L., and Gabrielle Denmead. 2008. <i>Income Data for Policy Analysis: A Comparative Assessment of Eight Surveys. Final Report.</i> Washington, <abbr class="spell">DC</abbr>: Mathematica Policy Research.</p>
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<p>Davies, Paul S., and T. Lynn Fisher. 2009. “<a href="/policy/docs/ssb/v69n2/v69n2p1.html">Measurement Issues Associated with Using Survey Data Matched with Administrative Data from the Social Security Administration</a>.” <i>Social Security Bulletin</i> 69(2): <span class="nobr">1–12.</span></p>
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<p>Dushi, Irena, Howard M. Iams, and Brad Trenkamp. 2017. “<a href="/policy/docs/ssb/v77n2/v77n2p1.html">The Importance of Social Security Benefits to the Income of the Aged Population</a>.” <i>Social Security Bulletin</i> 77(2): <span class="nobr">1–12.</span></p>
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<p>Fisher, T. Lynn. 2008. “<a href="/policy/docs/ssb/v67n2/v67n2p55.html">The Impact of Survey Choice on Measuring the Relative Importance of Social Security Benefits to the Elderly</a>.” <i>Social Security Bulletin</i> 67(2): <span class="nobr">55–64.</span></p>
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<p>Iams, Howard M., and Patrick J. Purcell. 2013. “<a href="/policy/docs/ssb/v73n2/v73n2p77.html">The Impact of Retirement Account Distributions on Measures of Family Income</a>.” <i>Social Security Bulletin</i> 73(2): <span class="nobr">77–84.</span></p>
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<p>Meyer, Bruce D., Wallace K. C. Mok, and James X. Sullivan. 2015. “The Under-Reporting of Transfers in Household Surveys: Its Nature and Consequences.” Chicago, <abbr title="Illinois">IL</abbr>: University of Chicago. <a href="https://harris.uchicago.edu/files/underreporting.pdf">https://harris.uchicago.edu/files/underreporting.pdf</a>.</p>
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<p>Miller, Billie Jean, and Sylvester J. Schieber. 2013. “Employer Plans, <abbr class="spell">IRA</abbr>s, and Retirement Income Provision: Making a Molehill Out of a Mountain.” <i>Insider</i> (October). London: Willis Towers Watson.</p>
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<p>Munnell, Alicia H., and Anqi Chen. 2014. “Do Census Data Understate Retirement Income?” Issue in Brief <abbr title="Number">No.</abbr> <span class="nobr">14-19.</span> Chestnut Hill, <abbr title="Massachusetts">MA</abbr>: Center for Retirement Research at Boston College.</p>
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<p>Pedace, Roberto, and Nancy Bates. 2000. “Using Administrative Records to Assess Earnings Reporting Error in the Survey of Income and Program Participation.” <i>Journal of Economic and Social Measurement</i> <span class="nobr">26(3–4)</span>: <span class="nobr">173–192.</span></p>
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<p>Rodgers, Willard L., Charles Brown, and Greg J. Duncan. 1993. “Errors in Survey Reports of Earnings, Hours Worked, and Hourly Wages.” <i>Journal of the American Statistical Association</i> 88(424): <span class="nobr">1208–1218.</span></p>
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<p>Schieber, Sylvester J. 1995. “Why Do Pension Benefits Seem So Small?” <i>Benefits Quarterly</i> 11(4): <span class="nobr">57–70.</span></p>
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<p>Semega, Jessica L., and Edward Welniak, <abbr title="Junior">Jr.</abbr> 2015. “The Effects of the Changes to the Current Population Survey Annual Social and Economic Supplement on Estimates of Income.” Paper presented at the proceedings of the 2015 Allied Social Science Association Research Conference, Boston, <abbr title="Massachusetts">MA</abbr> (January <span class="nobr">3–5).</span></p>
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<p>Woods, John R. 1996. “<a href="/policy/docs/ssb/v59n3/v59n3p3.pdf">Pension Benefits Among the Aged: Conflicting Measures, Unequal Distributions</a>.” <i>Social Security Bulletin</i> 59(3): <span class="nobr">3–30.</span></p>
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