Elderly Poverty and Supplemental Security Income, 2002–2005

by Joyce Nicholas and Michael Wiseman
Social Security Bulletin, Vol. 70 No. 2, 2010

The Supplemental Security Income (SSI) program is the nation's safety net for the aged, blind, and disabled. SSI receipt is often not reported by individuals interviewed in the Current Population Survey (CPS), the statistical base for the Census Bureau's annual estimates of poverty rates. In an earlier article, we explored the effect on estimated poverty rates in 2002 of adjusting CPS income reports using administrative data on earnings and benefits from the SSI and Old-Age, Survivors, and Disability Insurance programs. We assessed poverty using both the official standard and a "relative" standard based on half of median pretax, posttransfer income. This article extends that work through 2005. We find that including administrative data presents challenges, but under the methodology we adopt, such adjustments lower estimated official poverty overall and increase estimated poverty rates for elderly SSI recipients. Relative poverty rates are much higher than official poverty rates. By any of the applied standards and procedures for income adjustment, poverty changed little over the 2002–2005 interval.


Joyce Nicholas is a social science research analyst in the Office of Program Development and Research within the Office of Retirement and Disability Policy, Social Security Administration (Joyce.Nicholas@ssa.gov). Michael Wiseman is a professor at the George Washington Institute of Public Policy, George Washington University (wisemanm@gwu.edu).

Acknowledgments: The authors are grateful to SSA colleagues Glenn Springstead, Jim Sears, Tom Rush, Tom Hale, Will Jimenez, Mary McKay, Bobbie Gower, and Sheila Thompson for their helpful contributions.

The findings and conclusions presented in the Bulletin are those of the authors and do not necessarily represent the views of the Social Security Administration.

Introduction

Selected Abbreviations
ASEC Annual Social and Economic Supplement
CPS Current Population Survey
DER Detailed Earnings Record
FBR federal benefit rate
NRC National Research Council
OASDI Old-Age, Survivors, and Disability Insurance
PHUS Payment History Update System
SER Summary Earnings Record
SSA Social Security Administration
SSI Supplemental Security Income
SSN Social Security number
SSR Supplemental Security Record

The Supplemental Security Income (SSI) program acts as a safety net by providing a minimum level of income to the aged, blind, and disabled. As of December 2008, approximately 7.5 million persons received SSI, of which 2 million (27 percent) were aged 65 or older (SSA 2009). This group of recipients is about 5 percent of America's senior citizens. Thus, SSI for the elderly is not a major factor in the social assistance landscape. Nevertheless, it does establish an income floor, and it offers an institutional framework for caring for older people who for some reason reach later life with few resources. Given recent economic developments, it is possible that SSI enrollment may grow. Thus, continuing review of SSI outcomes is valuable.

The success of programs like SSI in ensuring minimum incomes for Americans can be measured in various ways. Typically, leaders and researchers have evaluated persons' economic standing using the official Census poverty standard and data from the Current Population Survey's (CPS's) Annual Social and Economic Supplement (ASEC). The official poverty standard is commonly described as "absolute" because it is based on a family budget established in the 1960s and is fixed in real terms (Fisher 1992). In recent decades, the prevalence of poverty among elderly Americans as measured by the official standard has declined substantially. From 1966 through 2006, the poverty rate for persons aged 65 or older fell from 28.5 percent to 9.4 percent. In 1966, the elderly poverty rate exceeded that of adults aged 18–65 by 18 percentage points. By 1993, parity with the poverty rate of other adults was achieved; since that year, the elderly poverty rate has generally been over a percentage-point lower than that registered for adults of "working age" (DeNavas-Walt, Proctor, and Smith 2007, 50). However, it is difficult to trace the connection between SSI and poverty because receipt of SSI is substantially underreported in the CPS. For example, the estimated number of SSI recipients in 2002 derived from the CPS is about 30 percent lower than the count obtained from administrative data (Nicholas and Wiseman 2009, Table 8).

In a recent article, we addressed the underreporting issue by merging CPS/ASEC survey data for 2002 with administrative data on earnings and benefits from the SSI and Old-Age, Survivors, and Disability Insurance (OASDI) programs (Nicholas and Wiseman 2009). We encountered two major problems in this effort. First, for various reasons only about three-quarters of persons surveyed for the CPS could be matched to Social Security administrative records. Second, in a significant number of cases, income sources and amounts reported in the CPS do not match administrative records, although often the differences are slight. We developed two alternatives to address these problems. For the problem of the unmatched records, we experimented both with simply leaving unmatched observations in the data set and relying on income as reported in the CPS and with using only the matched observations, but reweighting them using a propensity score technique. For the problem of the difference between administrative data on incomes and amounts reported in the survey, we developed estimates based on alternative "restrictive" and "inclusive" assumptions about which source to use. After addressing these methodological issues, we used our adjusted data to recalculate the prevalence of poverty using the official poverty standard and to investigate the prevalence of poverty using an alternative, "relative" standard.

Our data adjustments had appreciable effects on the estimates for calendar year (CY) 2002. We managed to reduce the weighted CPS undercount of elderly SSI recipients from 42 percent to 5 percent. Adjustment of income with administrative data reduced the national absolute poverty rate by 0.3–2.8 percentage points, depending on the procedure for incorporating unmatched observations and application of the restrictive or inclusive income adjustment procedures. The effect on estimated poverty rates for elderly SSI recipients was sizable. Adjustment of income with administrative data reduced the estimated aggregate poverty rate for elderly SSI recipients by 7.4–9.4 percentage points, again depending on the method adopted for incorporating unmatched observations and whether the restrictive or inclusive income adjustments were applied.

In addition to poverty estimates that are based on the official standard, we experimented with a relative poverty standard that identifies people as poor if their gross income adjusted for family size is less than half the national median. (We employ the same income measure for both absolute and relative poverty calculations.) This common relative poverty threshold yields a much higher aggregate poverty rate than is registered using the official standard—22 percent versus 12 percent before adjustment of income using administrative data. This difference persists in virtually the same magnitude after adjustment with administrative data because such adjustment generally shifts the entire distribution of income, not just the lower tail. However, for SSI recipients, adjustment does lower poverty rates, but those rates remain at very high levels—from 75.1 percent without adjustment to 70–72 percent, again depending on the choice between using restrictive or inclusive income adjustments.

When this study began, the 2003 CPS/ASEC was the latest public-use file for which matched administrative data were available. Since that time, comparable studies have been completed within the Social Security Administration (SSA) for the 2004, 2005, and 2006 CPS/ASEC data, allowing replication of our methodology for CYs 2003–2005. This article reports the results of our 2002–2005 analysis and outlines opportunities for additional research.

SSI Background

The SSI program provides a basic monthly national income guarantee, called the federal benefit rate (FBR), to persons aged 65 or older, blind individuals, and qualified children and adults with disabilities. The FBR is adjusted annually for inflation and stays constant in real terms. In 2002, the baseline year for this study, the FBR was $545 per month for a single individual and $817 for a couple (the 2009 amounts were $674 and $1,011, respectively). SSI is a program that provides a minimum level of income for needy aged, blind, or disabled individuals and acts as a safety net for those who have little or no Social Security or other income and limited resources (SSA 2009). To be eligible for SSI, applicants must pass financial tests involving certain assets and net ("countable") income and a medical test if disabled and nonelderly. Once eligibility is established, the SSI payment is the FBR minus the recipient's countable income and/or any "in-kind support and maintenance" received from others. In all states but two, the federal SSI payment is augmented for at least some SSI recipients by a state supplement (SSA 2008).

Because SSI eligibility is not determined by total household or even family income, a substantial number of recipients living with persons other than their spouse are not poor, although by official standards, anyone living solely on the FBR is considered to be poor. In 2002, the official poverty standard was $9,359 for a nonelderly single person ($8,628 if aged 65 or older) and $12,047 for a nonelderly couple ($10,874 if the "householder" was aged 65 or older). The annualized FBR—$6,450 per year for a single individual and $9,804 for a couple—was therefore even less than the poverty standard applicable to elderly persons. Despite this shortfall, it is possible for SSI payments to lift some persons out of poverty when considered in combination with the income of other family members. For others, SSI at least reduces the gap between income and the poverty standard, especially in states with substantial supplements.

The Data

We use CPS/ASEC data in conjunction with various Social Security administrative files to examine trends from CYs 2002 through 2005.1 Our administrative data provide information about a person's wages and salaries, self-employment, OASDI, and SSI income. We rely on the CPS for information about all other categories of income.

The Current Population Survey

The CPS is a monthly household survey conducted by the Census Bureau. This survey is the main source of employment information about the civilian noninstitutionalized American population. The CPS provides household, family, and person-level data about employment, unemployment, earnings, hours of work, and other indicators. Additional data are collected in the ASEC for CPS households on various family characteristics plus income received in the previous year. For poverty calculations we follow Census Bureau practice and exclude a small number of children living in households with no relatives because no income data are collected for such persons.

To protect confidentiality, income data in the CPS are subject to top- and bottom-coding. When reported amounts exceed certain thresholds, the actual amounts reported are replaced (top-coded) with average reported amounts for the same item for all surveyed persons with above-threshold amounts and identical (on certain dimensions) demographic characteristics. Bottom-coding occurs for losses from farm and nonfarm self-employment income. When persons are known to have received certain types of income but amounts are not reported, the Census Bureau imputes the missing amount using "hot-deck" methods. In this procedure, missing values are imputed using the amounts reported for sample observations with identical (on certain dimensions) demographic characteristics. It is possible for top- or bottom-coded amounts to be used in such imputations, depending on the data processing sequence.

Social Security Administrative Files

The administrative files we employ from SSA include records of individual earnings in employment covered by the OASDI program as well as SSI payments and OASDI benefits. The data sources for earnings are the Summary Earnings Record (SER) and the Detailed Earnings Record (DER), the Payment History Update System (PHUS) for OASDI, and the Supplemental Security Record (SSR) for SSI.

Summary Earnings Record. Data herein are an extract from SSA's Master Earnings File (MEF). A primary MEF record is created when a person receives a Social Security number (SSN); thus, every person in the CPS/ASEC for whom an SSN match was successfully accomplished will have an SER. The SER is the first administrative file examined when assessing the extent of the CPS/administrative match.

Detailed Earnings Record. These data are an extract from the MEF, which includes data on total earnings from all sources—wages, salaries, and income from self-employment that are subject to Federal Insurance Contributions Act (FICA) and/or Self-Employment Contributions Act (SECA) taxation. DER coverage extends to all earnings reported by employers on workers' W-2 forms, and amounts are not capped.2 These data include deferred wages such as contributions to 401(k) retirement plans.3 Because individuals do not make SECA contributions if they lose money in self-employment, only positive self-employment earnings are reported in the DER. Our data are aggregated across all employers for each individual and include earnings from wages, salaries, and self-employment, in addition to deferred income.4

Payment History Update System. These data record OASDI (Social Security) benefits when paid. PHUS data include both total benefit and the amount of benefit subtracted for Medicare Part B premiums. A key feature of the PHUS is that monthly amounts recorded here represent actual payments, not entitlement. Hence if a person begins entitlement for a Social Security benefit in November 2004, but does not actually receive a check for the amount until February 2005, the payment will be recorded for 2005. This corresponds to income received as reported in the CPS/ASEC.5

Supplemental Security Record. Data herein provide the information that is needed to calculate and distribute SSI payments. SSA typically creates an SSR record when an individual files an SSI application. Each person's record includes eligibility and payment information as well as income information about ineligible spouses and parents that is pertinent to establishing and maintaining the individual's eligibility. SSR payments are recorded as disbursed. The SSR includes state SSI supplements if federally administered (that is, if SSA makes the payment on the state's behalf). Payments made by state-administered SSI supplement programs are not included in the SSR. For the most part, state supplements are small, and some of the largest (from California, Massachusetts, and New York, for example) are federally administered (SSA 2008, 7). However, benefits in Alaska, Connecticut, Wisconsin, Minnesota, and a few other states are substantial and are administered by the state. By far the largest state-administered SSI supplement is Alaska's. In 2002, that state added $362 to the FBR for singles and $528 to the FBR for couples living independently (SSA 2008, 13).

The Match

The common element among original CPS/ASEC and administrative files is a Social Security number. CPS interviewers request SSNs for all persons aged 15 or older in each household in the address-based CPS household sample. Interviewees are not required to provide these data, but most do, or at least permit the Census Bureau to search Social Security's administrative files for their SSN using name, birth date, and address. SSNs for persons younger than age 15 are all obtained by searching administrative data. Once collected, the CPS data are extensively reviewed and reorganized, missing values are imputed, and potentially identifiable outlier income values are top- or bottom-coded. Upon completion of these adjustments, the Census Bureau produces a public-use data set. CPS public-use data sets do not include respondents' SSNs, but do contain unique household sequence and, within households, person identifiers. These identifiers relate to file structure only and convey no information useful for determining the actual identity of CPS respondents.

Upon release of the public-use CPS data, the Census Bureau provides a special encrypted file to SSA. This "cross-walk" file specifies the SSN for each person in the CPS for whom an SSN has been reported, identified by the household sequence number and person identifier. Only one person at SSA has access to the cross-walk file, who then uses the SSNs to construct SER, DER, PHUS, and SSR files for each person with a corresponding household sequence number and person identifier. Only the CPS identifiers are retained and used to link persons' CPS and administrative records.

Unweighted match rates for CPS person observations and Social Security administrative data are given in Table 1. The key match is for the SER. Primarily because of diminishing respondent willingness to provide SSNs, the match rate declined from the 2003 to the 2005 CPS/ASEC interviews (pertaining to CYs 2002 through 2004). However, the match rate increases substantially for the March 2006 interview. Beginning with the 2006 CPS/ASEC, the Census Bureau altered its policy for collecting SSNs. Rather than asking respondents for their SSNs and for an affirmative agreement for use of such information for data matching, the new protocol requires that respondents not wanting such matches to occur to notify the Census Bureau through that agency's Web site or to use a special mailed response. If no such instruction is received from respondents, SSA uses both the SSN and other information (name, address, age, and sex) that are provided to establish correct SSNs for data matching. As the table indicates, substituting an "opt-out" option for the former "opt-in" procedure for SSN reporting had a major effect.

Table 1. CPS and Social Security administrative data match rates, 2002–2005
Data 2002 2003 2004 2005
Number Percent Number Percent Number Percent Number Percent
CPS/ASEC 215,860 100.0 212,717 100.0 210,152 100.0 207,987 100.0
Matched with records in the—
SER 165,039 76.5 150,721 70.9 145,948 69.4 183,317 88.1
DER 113,138 52.4 104,255 49.0 97,537 46.4 132,469 63.7
PHUS 37,587 17.4 35,277 16.6 32,712 15.6 44,264 21.3
SSR 11,880 5.5 11,963 5.6 11,227 5.3 13,957 6.7
SOURCE: Authors' calculations using the CPS/ASEC public-use data set matched to Social Security administrative records.

Match rates for earnings (the DER), OASDI benefits (the PHUS), and SSI (the SSR) are lower than for the SER because not everyone for whom a match was achieved in a particular year had earnings or received SSI payments or OASDI benefits. Note that the DER, PHUS, and SSR match groups are subsets of the SER counts.

The Merge

We turn now to procedures for merging the CPS data with administrative records. "Adjusted data" is the term used for any CPS-reported values that have been replaced with administrative data. We discuss income adjustment first and then describe creation of a reweighted sample subset based on persons for whom we have a successful SER match. The outcome is three CPS samples for each year. "Baseline" samples are comprised of the same CPS/ASEC data applied by the Census Bureau to calculate official poverty estimates for any given year. (The terms baseline, official, and unadjusted refer to the same sample.) "Intermediate" samples involve CPS income adjustments that have only been applied to CPS observations with matching SER records. The "final" samples are restricted to individuals living in families with at least one person with a successful SER match and are reweighted to adjust for variation across families in the likelihood the match criterion is met.

Income-Adjustment Strategy

The baseline for our calculations is income as reported in the unadjusted public-use CPS/ASEC data. We distinguish between restrictive and inclusive assumptions at each step of our adjustment process. For a summary of the procedural protocol, see Nicholas and Wiseman (2009, Table A-1). In general, the restrictive assumption set gives credence to administrative data when both administrative and CPS reports are available, and the inclusive assumption set gives credence to CPS income reports when such reports are not imputed and exceed amounts recorded in our administrative sources.

Our income-adjustment procedure incorporates three important choices. First, when comparing CPS data with income reported in the DER, we generally work with total earnings—the sum of wages, salaries, and self-employment income—rather than distinguish between wages and salaries and income from self-employment. Second, we use reported earnings from the DER, but accept CPS earnings reports in the absence of DER amounts or in cases of loss from self-employment. Third, we rely solely on administrative sources for income from OASDI and SSI. The CPS collects data on 17 types of income, from alimony and veterans' benefits to wages and salaries. Our adjustments involve only earnings, OASDI benefits, and SSI payments. For all other sources the CPS amounts, including imputations and top-coded values, are retained.

The reasons for the earnings strategy are discussed in detail in our previous article. For OASDI and SSI, we rely on administrative data for both our restrictive and inclusive income adjustments. Incorporating OASDI and SSI administrative data is complicated by evidence that CPS respondents sometimes confuse SSI payments with OASDI benefits. In the previous article, we argue that this underreporting is due in part to misidentification of SSI payments as Social Security benefits. If such confusion does in fact exist, we should expect to see and actually do see greater reported OASDI benefits in the CPS among known SSI recipients who fail to report SSI than is the case for individuals who correctly report SSI receipt (Nicholas and Wiseman 2009, Table 4). Given the misreporting problem, we focus our income adjustment on the combined OASDI and SSI benefit. Our calculations also include an adjustment for state-administered SSI supplements (SSA 2004).

The Consequences of Adjustment

Table 2 reports the outcome of our CPS income adjustments, differentiating observations by their CPS/SER match status and whether their earnings were changed, their combined OASDI/SSI total was changed, or whether both earnings and OASDI were adjusted. We are interested here in the prevalence of adjustments within the sample, so the data are unweighted. The table has two panels: one incorporating the restrictive income adjustments and the other incorporating the inclusive income adjustments. We have tabulated here only income changes, without respect to whether the CPS-reported numbers were increased or decreased. (Our previous article provides greater detail for 2002.)

Table 2. Incidence of SSI, OASDI, and earnings adjustments: Percent of CPS/SER matched sample subset, 2002–2005
Adjustment category 2002 2003 2004 2005
Using restrictive income adjustment
Change in earnings 50.4 48.4 48.0 53.4
Change in combined SSI and OASDI total 13.1 14.1 14.0 16.0
Both 60.5 59.4 58.9 65.7
Using inclusive income adjustment
Change in earnings 29.5 26.4 27.7 30.6
Change in combined SSI and OASDI total 13.1 14.1 14.0 16.0
Both 40.6 38.4 39.7 44.2
Total CPS sample 215,860 212,717 210,152 207,987
Total CPS sample with SER match 165,040 150,721 145,948 183,317
Percent of total CPS sample 76.5 70.9 69.4 88.1
SOURCE: Authors' calculations using the CPS/ASEC public-use data set matched to Social Security administrative records.

The following four findings should be noted:

  1. Income adjustments are made for only CPS observations with an SER match. The bottom row of Table 2 indicates that the proportion of affected observations ranges from a low of 69.4 percent in the 2005 CPS/ASEC (2004 reference year) to a high of 88.1 percent in the following year.
  2. Income adjustments are common. This finding is to some extent misleading because any difference between what is in the CPS and what we gain from administrative data is recorded. Moreover, in considering the large number of cases with no changes for both earnings and the sum of OASDI and SSI benefits, it is important to recall that many of these cases receive neither, so zero matches with zero.
  3. The 2006 Census data linkage policy change not only increased the 2005 CPS/SER match rate, but also the proportion of CPS earnings and SSI/OASDI totals that our procedures adjust. This outcome might be attributed to a higher incidence of imputations among those observations added on the basis of the new Census "opt-out" procedure. Our adjustment procedure generally substitutes administrative data for imputations under both the restrictive and inclusive income protocols.
  4. Adjustments in earnings are generally less prevalent under the inclusive adjustment procedure. This outcome is a consequence of accepting survey earnings reports by the inclusive procedure if reported amounts exceed administrative data and are not imputed. The restrictive procedure substitutes DER data in most of these cases, and each substitution counts as an adjustment. The obvious question is whether the size and distribution of these adjustments have significant effects on our perception of poverty for the elderly and for individuals and families in general.

We began with the CPS baseline samples. Applying the income adjustments to persons with an SER match creates for each year a second, intermediate data set, which is somewhat of an amalgam because at least 24 percent of observations in each year lack an SER match. For this group it is necessary to rely solely on income as reported in the CPS.

The Final Sample

Our objective in constructing our third, final sample is to create a data set for which the administrative match is near "universal." However, because poverty is assessed on the basis of family income, universal is somewhat ambiguous. Three alternatives were considered. One was to limit consideration only to singles living alone who were matched to the SER and to families in which every member was matched. A second, less rigorous, alternative was to limit consideration to persons who were themselves matched even if every person in their family was not. The third was to restrict the sample to singles living alone who were matched as well as any person living in a family in which at least one family member was matched. We chose the third alternative, in part because a majority of unmatched persons who ended up being included under this strategy appeared unlikely to have income. The effect of the most rigorous "every family member matched" approach and the second "every person matched" approach would be to reduce the final unweighted samples on average by about 35 percent and 24 percent, respectively.

For population inference, the original CPS weights still work for CPS observations without matching SER records because all original CPS observations are used for our intermediate analyses. However, this is not true for the final sample, which excludes unmatched observations. Before generating our final estimates, we must adjust the person weights of our CPS restricted sample members.

The absence of a CPS/SER match can be treated as a problem in unit nonresponse—as if failure to provide an SSN that could be matched to the SER is equivalent to refusing to cooperate with the survey at all (Lehtonen and Pahkinen 2004, 115). Adjusting data for nonresponse then requires specifying, to some extent, the circumstances that affect the likelihood of cooperation (Groves and Couper 1998). The simplest assumption is that such outcomes are a random phenomenon, and each sampling unit shares a common probability of responding. The response rate for the survey then provides an estimate of this common probability, and population totals for various features of interest could be obtained by multiplying the analysis weights for respondents by a nonresponse adjustment factor. However, even the simplest tabulation indicates that the match rate is not independent of demographic characteristics. Hence without adjustment, the subset of observations for which matches are achieved cannot be used to make inference about the U.S. population as a whole.

We address this problem by reweighting our matched sample in a manner that reflects the varying propensity across interview units to provide SSNs or the information required for SSA to obtain them. Both poverty and income distribution statistics are based on families and single individuals. Given that absolute poverty assessment involves considering the income of all family members, it would be convenient if every family member had a CPS/SER match. In practice, there are families who have members without a CPS/SER match, and this issue presents a choice of what sample to use in generating population estimates. We choose to generate our final estimates from CPS observations who live in families in which someone in the family is matched, but not necessarily the observations themselves because this selection criteria is the least restrictive. For each year's data, we compute the parameters of a logistic regression for the log odds of being matched in this sense for each of the persons in the CPS sample (Folsom 1991; Iannacchione 1999). We estimate separate functions for persons who are either younger than age 18, aged 18–64, or aged 65 or older (Nicholas and Wiseman 2009, Appendix C-2). We use this function to calculate i and an adjusted weight for each individual observation. These calculations produce a third or final sample made up of unrelated individuals with an SER match and persons in families with at least one member with an SER match, each with a propensity-adjusted weight and both restrictive and inclusive income estimates.

It should be emphasized that these estimates are not only experimental, but we have not attempted to estimate variances for the sample estimates. Because of confidentiality issues, the design information necessary to estimate variances for sample statistics from the CPS is not publicly released, and the variance estimation methodology provided by the Census Bureau is not applicable to the final sample we construct because of the additional reweighting step applied (Census Bureau and Bureau of Labor Statistics 2002; Valliant 2004).

The Results: Absolute Poverty

We turn now to the results, treating 2002 (that is, the income data from the 2003 CPS/ASEC) as the baseline of this study. The same data presentation employed in our previous article for 2002 is used here, and results for 2003–2005 are given in Table A-1.

Poverty in 2002

We begin by examining the consequence of CPS income and weight adjustments on poverty rate estimates using the same poverty thresholds applied in Census Bureau publications. As already noted, for 2002 a single, nonelderly adult living alone was considered poor if his or her gross cash income after transfers but before taxes for the year fell below $9,359; for a family of four with two children, the reference amount is $18,244 (Proctor and Dalaker 2003, 4). The standard increases with family size and varies with composition. Elderly persons living alone or with spouses are assumed to require about 10 percent less income than do nonelderly persons in the same circumstance.

Poverty rates by age group for CY 2002 are reported in Table 3. The table is divided into two parts: (1) results for the total U.S. population as covered by official poverty statistics and (2) results for the SSI recipient population. For both groups, we present results (a) using the same baseline CPS/ASEC data applied for official estimates published by the Census Bureau, (b) based on an intermediate CPS/ASEC data that only involve income adjustments, and (c) from a final sample involving a CPS/administrative matched data set limited to observations with matching SER records as well as CPS income- and weight- adjusted records. Within each estimate group, we present results for children aged 17 or younger, adults aged 18–64, and for those aged 65 or older.

Table 3. Poverty rates across age and SSI recipient groups before and after adjustment using Social Security administrative data: Total U.S. population and SSI recipient population, 2002
Age group Estimated population Restrictive Inclusive Data summary
Number
living below poverty a
Percent living below poverty Number living below poverty Percent living below poverty Person records Income Weights
1(a): U.S. population; estimates based on unadjusted CPS income data b
0–17 72,695,775 12,127,725 16.7 12,127,725 16.7 215,860 Unadjusted Unadjusted
18–64 178,387,747 18,859,737 10.6 18,859,737 10.6
65 or older 34,233,824 3,576,169 10.4 3,576,169 10.4
Total 285,317,346 34,563,631 12.1 34,563,631 12.1
1(b): U.S. population; estimates based on adjusted CPS income data c
0–17 72,695,775 11,942,960 16.4 9,684,218 13.3 215,860 Adjusted Unadjusted
18–64 178,387,747 18,702,806 10.5 15,030,345 8.4
65 or older 34,233,824 3,111,542 9.1 3,043,279 8.9
Total 285,317,346 33,757,308 11.8 27,757,842 9.7
1(c): U.S. population with income adjustment, sample restriction, and reweighting d
0–17 72,451,591 11,832,495 16.3 9,453,838 13.0 185,284 Adjusted with sample restriction Adjusted
18–64 172,660,884 18,192,264 10.5 13,616,602 7.9
65 or older 33,001,207 2,768,217 8.4 2,677,064 8.1
Total 278,113,682 32,792,976 11.8 25,747,504 9.3
2(a): SSI recipient population; estimates based on unadjusted CPS income data e
0–17 364,804 132,151 36.2 132,151 36.2 3,635 Unadjusted Unadjusted
18–64 3,595,948 1,577,196 43.9 1,577,196 43.9
65 or older 1,192,268 572,868 48.0 572,868 48.0
Total 5,153,020 2,282,215 44.3 2,282,215 44.3
2(b): SSI recipient population; estimates based on adjusted CPS income data f
0–17 830,116 219,764 26.5 181,242 21.8 4,381 Adjusted Unadjusted
18–64 3,809,850 1,609,734 42.3 1,557,189 40.9
65 or older 1,695,088 688,697 40.6 668,344 39.4
Total 6,335,054 2,518,195 39.8 2,406,775 38.0
2(c): SSI recipient population with income adjustment, sample restriction, and reweighting g
0–17 862,176 228,729 26.5 187,873 21.8 3,707 Adjusted with sample restriction Adjusted
18–64 3,880,146 1,729,553 44.6 1,666,596 43.0
65 or older 1,956,997 781,043 39.9 754,997 38.6
Total 6,699,319 2,739,325 40.9 2,609,466 39.0
SOURCE: Authors' calculations using 2003 CPS/ASEC public-use data matched to Social Security administrative records.
NOTE: Weight adjustments are based on person-level records differentiated by age group.
a. Persons are identified as "poor" if their CPS total family income record is less than their corresponding CPS family poverty standard record. Family income records may include top-coded components. These totals differ slightly from official reports, which are based on actual reported income without top-coding.
b. Figures have been generated from the entire 2003 CPS/ASEC sample of 215,860 persons used by the Census Bureau to estimate poverty rates.
c. Income adjustments made using administrative data on SSI, OASDI, and earnings receipt, following decision rules as presented in text and Nicholas and Wiseman (2009).
d. Estimates derived from a reduced 2003 CPS/ASEC poverty sample of 185,284 persons who have at least one family member with matching CPS/SER records. Figures are based on the adjustment of CPS income records using administrative data following decision rules discussed in text and presented in detail in Nicholas and Wiseman (2009). Weights have been adjusted by propensity estimates derived from a regression model involving person-level records.
e. Persons identified as SSI recipients if they have a positive CPS SSI record.
f. Income adjustments made using administrative data on SSI, OASDI, and earnings receipt, following decision rules presented in text. SSI status based on adjusted data.
g. Estimates derived from a reduced 2003 CPS/ASEC poverty sample of 185,284 persons who have at least one family member with matching CPS/SER records. Figures are based on the adjustment of CPS income records using administrative data following decision rules presented in text. Weights have been adjusted by propensity estimates derived from a regression model involving person-level records; see text and Nicholas and Wiseman (2009) for methodology; propensity model estimates are available from the authors upon request. Persons are identified as SSI recipients if they have a positive SSR SSI record.

Tabulations in panels 1(a) and 2(a), in Table 3, are based on the same CPS data used by the Census Bureau to generate official poverty estimates. (Our estimates differ slightly from figures published by the Census Bureau because it uses data without top-codes, and we use the public-use sample, which is top-coded.) The official estimates appear for reference for both the restrictive and inclusive computations. We are particularly interested in poverty rates among the elderly and SSI recipients. National poverty rates for working-age and elderly populations in 2002 were 10.6 percent and 10.4 percent, respectively. As anticipated, poverty rates for SSI recipients in all age groups are much higher than rates estimated for the age groups in the U.S. population as a whole.

Tabulations in panels 1(b) and 2(b) report the results of applying our restrictive and inclusive income-adjustment protocols. At this stage of our research, the entire CPS sample is retained, and CPS data are used for all persons for whom a CPS/SER match was not achieved, so the total sample size does not change from that recorded for the CPS. Looking first at the data for all persons, the effect of incorporating administrative data is sensitive to the assumption set. The restrictive income adjustment decreases the estimated aggregate poverty rate from 12.1 percent to 11.8 percent; the estimated rates for all three age groups decline, with the greatest change for the elderly. The inclusive income adjustment produces a much larger reduction in poverty rates for all groups, most notably among the nonelderly. Both adjustments produce lower SSI poverty rates. The effect is most dramatic for persons aged 17 or younger. Under the restrictive income estimate procedure, the poverty rate for elderly SSI recipients is 40.6 percent, more than 7 percentage-points less than the unadjusted CPS estimate. Using our inclusive income-adjustment procedure, the estimate is 39.4 percent, 8.6 percentage-points less than the unadjusted CPS estimate. The unweighted SSI recipient count (the number in the "person records" column under the data summary section of the table) goes up by over a fifth, from 3,635 to 4,381 when administrative data are employed. This outcome is another manifestation of underreporting of SSI in the CPS.

Tabulations in panels 1(c) and 2(c) report the results of applying CPS income adjustments, reweighting the observations' CPS person weights using propensity scores, and restricting the sample to persons living in families with at least one member with matching individual CPS and SER records. The combined effect of our CPS income and weight adjustments (panel 1(c)) is a modest additional decrease in estimated aggregate poverty rates under the restricted convention when compared with estimates based only on adjusting the CPS income data for respondents who could be matched to SSA records. When the inclusive adjustment is employed, estimated poverty rates fall further. The effect varies among SSI recipients; child and nonelderly adult SSI poverty estimates are greater, and elderly rates are less than those estimated without sample restriction and reweighting (Table 3, panels 1(b) and 2(b)).

What drives the difference between the final restrictive and inclusive income estimates? Our previous article indicates that the most sizable difference between our two sets of final estimates is that for earnings and self-employment income, the restricted calculations rely on the DER, that is, earnings reported by employers. The inclusive alternative takes CPS reports when the amounts reported in the survey exceed what appears in matching administrative records. Therefore, inclusive income estimates are larger than those that are restrictive. For the elderly, earnings are less important (although they count because poverty is estimated on the basis of total family income, not just the income of the elderly themselves), but correcting for SSI underreporting has a noticeable impact. Aside from imputations for state-administered SSI supplements, the same correction is applied in both the restrictive and inclusive procedures, and the consequence in both cases is an 8–9 percentage-point reduction in estimated poverty, particularly among elderly SSI recipients. This alteration comes about principally because of the effect on prevalence of SSI receipt, not amounts reported.

Changes in Poverty, 2002–2005

CPS adjustment with administrative data produces poverty estimates for 2002–2005 that differ from official ones generated from unadjusted CPS data. Charts 1 and 2 focus on the differences between unadjusted CPS baseline estimates (reported in panels 1(a) and 2(a) of Table 3) and our final restrictive and inclusive estimates based on adjusted CPS/administrative matched data (reported in panels 1(c) and 2(c) of Table 3). (A complete version of Table 3 is presented for each reference year in Table A-1.)

Chart 1 illustrates absolute poverty rates estimated for the entire national and elderly populations. The basic relationships between baseline and final estimates change marginally in later years. For the U.S. population as a whole, poverty estimates based on our restrictive final data are slightly below those generated from unadjusted CPS data, and estimates based on CPS inclusive final data are lower. The noted restrictive and inclusive income adjustments produce the same outcomes for the elderly from one reference year to another by reducing their absolute poverty estimates by approximately 1–2 percentage points.

Chart 1.
Poverty rates for the entire national and elderly populations before and after inclusion of administrative data, 2002–2005
Line chart linked to data in table format.
SOURCE: Authors' calculations using the CPS/ASEC public-use data set matched to Social Security administrative records.

Chart 2 plots baseline and final estimates for elderly SSI recipients. This chart is based on poverty estimates appearing in panels 2(a) and 2(c) of Table 3. For 2002, the chart shows that incorporating CPS elements with administrative data produces a sizable reduction in estimated poverty rates for elderly SSI recipients. In contrast, for 2003–2005, adjusted estimates for the elderly are greater, regardless of the income adjustment applied.

Chart 2.
Poverty rates for elderly SSI recipients before and after inclusion of administrative data, 2002–2005
Line chart linked to data in table format.
SOURCE: Authors' calculations using the CPS/ASEC public-use data set merged with Social Security administrative records.

The relationship between our baseline and final poverty estimates for elderly SSI recipients differs substantially from the corresponding national estimates. For both the total U.S. population and all elderly persons, our restrictive and inclusive final estimates of the poverty rate for the 2002–2005 period are consistently below the baseline official estimates. For elderly SSI recipients, however, this is true for 2002 (as reported in our previous article), but not for the 2003–2005 period.

What is going on in Chart 2 is unclear, but it is possible to say more about what is driving the change between the outcome for 2002 and for subsequent years. Recall that in moving from baseline to final estimates in each year, the sample base changes. The baseline includes only observations for people who report SSI receipt in the CPS. The sample base for the final estimates includes only observations for people in families matched to Social Security administrative records (using our match criteria) for the year. Persons who report SSI receipt and for whom matches to the SSR SSI records are found are included in both the baseline and final samples. The baseline poverty rates for this group are quite high, ranging from 44–50 percent over the 4 sample years. The final rates are only slightly changed with adjustment of family earnings, family income from other sources including SSI, and reweighting. Poverty rates adjusted for actual SSI receipt among persons who did not report SSI receipt in the 2002 CPS, but in fact were SSI recipients, were substantially lower than rates for those who reported SSI receipt, but for whom no administrative match was obtained. For the final poverty estimates, persons not meeting our CPS/SER match criteria were deleted from the sample of elderly SSI recipients, and persons known from administrative records to be recipients but who did not report so in the CPS were added and counted as SSI recipients. The observations in the resulting subsample were reweighted to reflect the sample adjustments. The result is a lower overall poverty rate than what is obtained from the baseline sample (Chart 2).

For subsequent years, things change. Persons who did not report SSI receipt to the CPS but in fact were SSI recipients have poverty rates higher than estimated for persons in this category in 2002. In 2003 and 2004, these higher rates are similar to those for the persons reporting SSI, but for whom no administrative confirmation is available. The effects of adjustment on the family income of those who did report receiving SSI are larger and result in substantial reduction in average estimated family income. The combination of changes causes the final samples to have a higher overall poverty rate that exceeds the baseline estimates. Because of the procedural change for collection of SSNs, discussed earlier, the match rate for the 2005 data is much higher, and the proportion of the elderly persons reporting SSI receipt that is verified with administrative data increases. Nevertheless, the final poverty estimates are similar to those for 2003 and 2004. In sum, to our knowledge the difference between the 2002 and 2003–2005 samples cannot be related to some change in the way the CPS collects SSI data or other administrative factors, so the outcome remains an anomaly.

SSI Population Estimates

CPS income and weight adjustments substantially increase the sample-based estimates of the total population of SSI recipients. Estimates of the total SSI recipient population by age group for the original and modified CPS samples for each year are given in Table 4. The first bank in column (1) specifies the sum of sample weights for persons for whom the unadjusted 2003 CPS/ASEC reports receipt of SSI in 2002. The second column indicates intermediate estimates generated from the same CPS sample used for official poverty estimates, but matched to administrative sources and involving adjustment to only CPS income records. The third column gives our final estimates of the number of recipients calculated on the basis of our restricted CPS/administrative-matched sample with CPS income and weight adjustments. Column (4) shows the average monthly SSI caseload for 2002, indicated by SSA's 1 percent SSR sample. Column (5) gives, from the same 1 percent SSR sample, an estimate of the number of persons in the CPS sample universe who had income from SSI in 2002.

Table 4. Estimated SSI population compared with Social Security administrative data count (including Medicaid institution adjustment), 2002–2005
Age group
(at time of CPS/ASEC)
Total SSI recipients estimated from— Average monthly recipient caseload from administrative data Total SSI recipients in CPS/ASEC universe estimated from administrative data a Ratio, CPS/ASEC unadjusted reweighted sample population estimate to administrative recipient count Ratio, CPS/ASEC restricted/ reweighted sample population estimate to administrative recipient count
CPS/ASEC CPS/ASEC using adjusted income data CPS/ASEC using restricted/ reweighted sample and adjusted income data
(1) (2) (3) (4) (5) (6) (7)
2002
0–17 364,804 830,116 862,176 897,771 1,024,500 0.356 0.842
18–64 3,595,948 3,809,850 3,880,146 3,862,587 4,308,000 0.835 0.901
65 or older 1,192,268 1,695,088 1,956,997 1,998,249 2,064,200 0.578 0.948
Total 5,153,020 6,335,054 6,699,319 6,758,608 7,396,700 0.697 0.906
2003
0–17 364,478 866,916 902,579 936,516 1,051,400 0.347 0.858
18–64 3,783,005 3,903,433 4,132,750 3,932,819 4,379,600 0.864 0.944
65 or older 1,225,478 1,690,810 1,994,570 1,996,932 2,070,500 0.592 0.963
Total 5,372,961 6,461,159 7,029,899 6,866,267 7,501,500 0.716 0.937
2004
0–17 408,915 901,805 957,402 981,877 1,098,500 0.372 0.872
18–64 4,036,944 4,136,748 4,158,826 4,007,361 4,443,700 0.908 0.936
65 or older 1,117,640 1,620,585 1,832,597 1,993,369 2,058,900 0.543 0.890
Total 5,563,499 6,659,138 6,948,825 6,982,606 7,601,100 0.732 0.914
2005
0–17 379,909 951,558 997,049 1,027,372 1,120,200 0.339 0.890
18–64 3,900,117 4,115,297 4,493,624 4,069,369 4,506,400 0.865 0.997
65 or older 1,176,402 1,825,269 1,878,685 1,992,673 2,047,500 0.575 0.918
Total 5,456,428 6,892,124 7,369,358 7,089,414 7,674,100 0.711 0.960
SOURCE: Authors' calculations using the noted year CPS/ASEC universe and Social Security 1 percent SSR beneficiary samples. SSI population in 2002 estimated using 2003 CPS/ASEC universe matched to Social Security administrative records; 2003 population estimated using 2004 survey data matched to administrative records; 2004 population estimated using 2005 survey data matched to administrative records; and 2005 population estimated using 2006 survey data matched to administrative records.
a. Estimated number of persons ever receiving SSI in a given year who were alive and in indicated age group at the time of the CPS March Supplement interview of the following year. This estimate is reduced by the approximate number of persons who live in communal facilities, but includes homeless persons not counted in the CPS/ASEC.

Relative Poverty

We turn now from absolute to relative poverty assessment. Reliance on absolute poverty measures, especially measures as old as the official U.S. standard, is controversial. In our previous article, we considered the consequences of evaluating poverty on a relative basis, using the common Organisation for Economic Co-operation and Development standard of 50 percent of median income before taxes (Förster and Mira d'Ercole 2005). We convert family income into "individual equivalents" using an equivalence scale suggested by a recent National Research Council (NRC) review of recommendations for poverty standard reform.6 Because of data limitations, we conduct this analysis using the same "pretax, posttransfer" income measure as that employed in official statistics. Ideally we would include income benefits such as food stamps, earned income credit, and housing subsidies, but we could not do so. This issue is discussed further in our conclusions.

The Income Distribution in 2002

Again, we use 2002 and our previous analysis as an anchor. The results appear in the two parts of Table 5: part 1—based on the restrictive adjustment protocol, and part 2—based on the inclusive alternative. Both parts of the table show results for unadjusted CPS data, the sample that combines adjusted data for matched households with CPS data alone for the unmatched, and a third sample of matched CPS data reweighted to adjust for nonresponse. Looking first at part 1, the table identifies the points of demarcation for various deciles of the income distribution for each of the three samples and then the proportion of all observations that fall within the corresponding interval (to save space, deciles 30 and 40 and deciles 70 and 80 are combined). By definition, for each sample, 10 percent of all people fall within each decile. What is of interest here is the location of the median, the corresponding poverty standard, and the proportion of the elderly and elderly SSI recipients who fall below this standard. The median is quite similar across the three samples, causing the relative poverty standard to vary by less than $100. For the estimates in panel (c) the standard is $12,764. This is the amount for a single individual; the NRC equivalence scale says that for a family of two adults and two children, this should be increased by a factor of (2 + .5 * 2)0.7 = 2.16, that is, to $27,540. As noted in our earlier article, the relative poverty standard assesses a larger proportion of the population to be in poverty (22 percent versus the 12.1 percent reported in Table 3). In contrast to the results for absolute poverty rates, the poverty rate for the elderly now exceeds that for the population as a whole, and the poverty rate for elderly SSI recipients rises to 70.7 percent for the adjusted and reweighted sample.

Table 5. The effect of merging CPS and Social Security administrative data on the estimated national income distribution using restrictive and inclusive income-adjusted protocols, 2002
National income distribution Percentiles Data summary
10 20 40 50 60 80 90 Top decile 50 percent of the median Person records Income Weights
Part 1: Restrictive 2002—
(a) using unadjusted income percentiles for all people a
Upper bound ($) 7,462 12,000 20,862 25,712 31,350 47,696 64,793 . . . 12,856 215,860 Unadjusted Unadjusted
Distribution (%)                    
All people 10.0 10.0 20.0 10.0 10.0 20.0 10.0 10.0 22.0 215,860
Elderly b 7.8 16.1 29.1 11.9 9.2 13.3 6.0 6.7 27.5 20,384
Elderly SSI c 32.9 39.0 14.8 5.0 3.6 2.9 1.0 0.8 75.1 778
(b) using adjusted income percentiles for all people (unadjusted weights) d
Upper bound ($) 7,579 12,134 20,856 25,662 31,284 48,302 66,451 . . . 12,831 215,860 Adjusted Unadjusted
Distribution (%)                    
All people 10.0 10.0 20.0 10.0 10.0 20.0 10.0 10.0 21.7 215,860
Elderly 7.2 15.2 29.1 12.2 9.7 14.1 6.1 6.4 25.2 20,384
Elderly SSI e 35.4 33.4 12.4 5.6 5.0 5.7 1.2 1.4 70.0 1,081
(c) using adjusted income percentiles for all people (adjusted weights) f
Upper bound ($) 7,624 12,109 20,726 25,527 31,086 47,903 66,343 . . . 12,764 185,284 Adjusted with sample restriction Adjusted
Distribution (%)                    
All people 10.0 10.0 20.0 10.0 10.0 20.0 10.0 10.0 21.6 185,284
Elderly b 6.8 14.9 28.5 12.2 10.0 14.9 6.4 6.4 24.0 14,564
Elderly SSI g 35.2 34.2 11.5 5.8 4.8 5.7 1.4 1.5 70.7 906
Part 2: Inclusive 2002—
(a) using unadjusted income percentiles for all people a
Upper bound ($) 7,462 12,000 20,862 25,712 31,350 47,696 64,793 . . . 12,856 215,860 Unadjusted Unadjusted
Distribution (%)                    
All people 10.0 10.0 20.0 10.0 10.0 20.0 10.0 10.0 22.0 215,860
Elderly b 7.8 16.1 29.1 11.9 9.2 13.3 6.0 6.7 27.5 20,384
Elderly SSI c 32.9 39.0 14.8 5.0 3.6 2.9 1.0 0.8 75.1 778
(b) using adjusted income percentiles for all people (unadjusted weights) d
Upper bound ($) 8,708 13,585 23,095 28,325 34,441 52,321 72,435 . . . 14,163 215,860 Adjusted Unadjusted
Distribution (%)                    
All people 10.0 10.0 20.0 10.0 10.0 20.0 10.0 10.0 21.3 215,860
Elderly 10.1 17.6 28.7 10.8 8.5 12.7 5.8 5.8 29.6 20,384
Elderly SSI e 42.3 27.4 13.2 4.2 5.1 5.1 1.4 1.4 70.7 1,081
(c) using adjusted income percentiles for all people (adjusted weights) f
Upper bound ($) 9,000 13,896 23,444 28,718 34,843 52,919 73,743 . . . 14,359 185,284 Adjusted with sample restriction Adjusted
Distribution (%)                    
All people 10.0 10.0 20.0 10.0 10.0 20.0 10.0 10.0 21.0 185,284
Elderly b 10.0 17.3 28.3 10.7 8.6 13.2 5.9 5.9 29.0 14,564
Elderly SSI g 46.7 23.9 12.4 3.7 5.2 5.3 1.5 1.4 71.7 906
SOURCE: Authors' calculations using 2003 CPS/ASEC data matched to Social Security administrative records and the NRC equivalence scale.
NOTE: . . . = data not applicable.
a. Figures involve unadjusted CPS income data and weights as well as the entire 2003 CPS/ASEC poverty sample of 215,860 persons.
b. Persons with a CPS-reported age of 65 or older.
c. Persons with a positive CPS SSI record.
d. Estimates are based on adjusted CPS income records, unadjusted weights, and involve the entire 2003 CPS/ASEC poverty sample.
e. Persons are identified as SSI recipients if either they have no matching CPS/SER records and a positive CPS SSI record or matching CPS/SER records and a positive SSR SSI record.
f. Figures involve adjusted CPS income data and weights and a reduced 2003 CPS/ASEC poverty sample.
g. Persons are identified as SSI recipients if they have a positive SSR SSI record.

The same calculations using the inclusive version of the data set are shown in part 2 of Table 5. The inclusive income estimates increase estimated median income and thereby increase the poverty standard. However, the estimated poverty rates do not change much at all. We do find that a larger fraction of elderly SSI recipients are estimated to fall in the lowest decile of the income distribution. On the other side of the distribution, between 8.2 percent (inclusive) and 8.6 percent (restrictive) of elderly SSI recipients live in families with total incomes that place their members in the upper 20 percent of the income distribution.

Changes in the Income Distribution, 2002–2005

Both parts of Table 5 are replicated for 2003–2005 in Table A-2. Our text discussion is based on an extract of that data and focuses on comparison of baseline estimates with the final estimates developed with the restricted/reweighted data set and the restrictive and inclusive income-adjustment protocols. We begin with changes in median income over time and the resulting changes in the poverty standard. The standard for all 4 years of our data set is reported in Table 6. To facilitate comparison, we have adjusted the data to 2002 prices using the Consumer Price Index.

Table 6. Relative poverty standard values, by estimate group, 2002–2005 (in 2002 dollars)
Estimate group 2002 2003 2004 2005
Baseline 12,856 12,844 12,766 12,852
Final restrictive 12,764 12,669 12,604 12,852
Final inclusive 14,359 14,104 14,051 14,702
SOURCE: Authors' calculations using CPS/ASEC public-use data matched to Social Security administrative records.

Income distributions change slowly, so we do not expect much change over a 4-year interval. By and large, the restrictive income-adjustment procedure produces a relative poverty standard slightly lower than what is computed using the baseline, unadjusted data; the inclusive measure moves the estimated income distribution to the right and raises the standard. Perhaps the most interesting feature is the general decline in the relative standard from 2002–2004, followed by an increase in 2005. Recall that the federal SSI payment for a single individual is indexed for price changes. Annualized, the 2002 monthly individual FBR amounted to $6,540 per year, or nearly 45 percent of the 2002 "final inclusive" relative standard ($14,350).

Medians capture only one feature of the income distribution. Dispersion is relevant as well, especially in the context of relative poverty assessment. Table 7 reports the 90/10 and 80/20 decile cutoff ratios for the total population for each of the 4 years under study. The 90/10 ratio is equal to the ratio of the demarcation point for the 90th decile in the income distribution to the demarcation for the 10th decile. The 80/20 ratio is defined in a similar manner, but obviously does not reach as far out on the tails of the distribution.

Table 7. Comparison of national income dispersion ratios, by estimate group, 2002–2005
Estimate group 2002 2003 2004 2005
National 90/10 ratios
Baseline 8.63 9.11 9.16 9.22
Final restrictive 8.70 8.72 8.93 9.28
Final inclusive 8.19 8.44 8.51 8.63
National 80/20 ratios
Baseline 3.97 4.09 4.02 4.01
Final restrictive 3.96 3.96 4.01 4.09
Final inclusive 3.81 3.86 3.88 3.88
SOURCE: Authors' calculations using CPS/ASEC public-use data matched to Social Security administrative records.

Four things stand out in these results.

  1. Adjustment with administrative data generally reduces estimated dispersion of the income distribution.
  2. Estimates based solely on the inclusive income-adjustment protocol generally produce the lowest dispersion.
  3. Dispersion as measured by the 90/10 ratio grew over this period, regardless of the income-adjustment protocol followed.
  4. Most changes in the distribution of income occur among those belonging to the bottom and top quintiles of the national income distribution. The estimated change in the 90/10 ratio is larger than the estimated change in the 80/20 ratio.

Finally, relative poverty rates for each of the 4 years under study for all persons—the elderly and the subset of the elderly who are SSI recipients—are given in Table 8. Basically, no trends are evident in the general income distribution. The baseline shows some decline for the elderly and for elderly SSI recipients. This is consistent with trends in the official poverty rate shown in Chart 2. However, the adjusted data show little change. As with the data for the official poverty rate, results after adjustment using administrative data provide little evidence of improvement in the prevalence of poverty among elderly SSI recipients using either poverty standard.

Table 8. Relative poverty rates, by estimate group, 2002–2005 (in percent)
Estimate group 2002 2003 2004 2005
U.S. population
Baseline 22.0 22.4 22.2 22.2
Final restrictive 21.6 21.8 21.9 22.1
Final inclusive 21.0 21.4 21.4 21.3
Elderly population
Baseline 27.5 27.7 26.4 26.1
Final restrictive 24.0 23.6 21.9 23.2
Final inclusive 29.0 28.2 26.7 28.8
Elderly SSI recipient population
Baseline 75.1 73.3 67.3 71.5
Final restrictive 70.7 73.9 69.8 71.3
Final inclusive 71.7 74.7 70.8 72.2
SOURCE: Authors' calculations using CPS/ASEC public-use data set matched to Social Security administrative records.

Conclusions

In this article, we have applied the experimental procedures developed in our earlier study of the incomes of elderly SSI recipients in 2002 as well as 3 subsequent years of data. In general, the results for 2003–2005 are consistent with 2002. Even given the incomplete match between CPS and administrative records, we have produced an adjusted data set that yields estimates of the prevalence of SSI receipt that are much closer to administrative totals than can be achieved using the standard CPS data set. Unlike what might be inferred from unadjusted CPS data, we see no evidence of significant decline in poverty rates among the elderly or among elderly SSI recipients over this interval.

Several features of this analysis deserve more attention. The difference between our restrictive and inclusive estimates is quite broad generally because of reliance on administrative data alone for the restrictive estimates. For a significant number of persons with an SER match, earnings reported in the CPS are substantially greater than what is recorded in the DER. On balance, the reduction in incorporated earnings for this group under the restrictive protocol almost offsets the addition to income made for those without CPS earnings, but with a DER report. Clearly more thought needs to be given to alternatives for using administrative data, and the sensitivity of the outcomes to procedural variation deserves more thorough investigation. Beyond sensitivity to definition, some investigation of confidence intervals for the many point estimates we have tabulated is essential.

There are noticeable differences between results for 2004 and 2005. The 2005 data are the first collected following the procedural change in obtaining CPS respondent consent for data matching. It is possible that the observed changes are the product of differences between those persons who prior to 2005 would not have been matched and those who would have been captured in the sample had procedures gone unchanged. Of course it is impossible to identify just who would and who would not have consented under the Census Bureau's opt-in interviewer policy. But it would be possible to use the match propensity models estimated for prior years to identify those observations in 2005 that would have been least likely in previous years to have been matched to Social Security administrative data and to use propensity scores to reduce the 2005 sample to a rate consistent with earlier years. The analysis could then be replicated with an eye toward consequences for income distribution estimates obtained using the procedural change adopted with the 2006 CPS/ASEC.

Recently, various groups have shown renewed interest in the recommendations of the NRC for reform of the poverty standard. In March, the Census Bureau announced plans for a "supplemental poverty measure" (SPM) "broadly based" on the NRC recommendations, to be first published in the fall of 2011 (Census Bureau 2010). As the name suggests, at least initially, the new measure will not replace the current poverty standard, but rather provide a broader perspective on both the resources and needs of families and individuals. The Census Bureau's Web site now includes an ingenious table generator for experimenting with alternative equivalence scales and poverty standards, including relative measures based on position in the income distribution. However, aside from differences in top- and bottom-coding, the generator, like the Census Bureau's other experimental analyses, relies on reported amounts of income from sources such as SSI, OASDI, and Temporary Assistance for Needy Families (TANF). A major part of the reform agenda and the modifications incorporated in the SPM involves addition to measures of income from sources such as Supplemental Nutrition Assistance Program (SNAP, formerly the Food Stamp Program) benefits and payments from the Earned Income Tax Credit, which are not now included. Underreporting will need to be addressed as well, possibly through more systematic incorporation of administrative data. Our experience suggests that incorporating administrative data is important, but not easy.

Appendix

Table A-1. Poverty rates across age and SSI recipient groups before and after adjustment using Social Security administrative data: Total U.S. population and SSI recipient population, 2003–2005
Age group Estimated population Restrictive Inclusive Data summary
Number
living below poverty a
Percent living below poverty Number living below poverty Percent living below poverty Person records Income Weights
2003
1(a): U.S. population; estimates based on unadjusted CPS income data b
0–17 72,999,159 12,862,482 17.6 12,862,482 17.6 212,717 Unadjusted Unadjusted
18–64 180,040,766 19,438,817 10.8 19,438,817 10.8
65 or older 34,659,258 3,552,224 10.2 3,552,224 10.2
Total 287,699,183 35,853,523 12.5 35,853,523 12.5
1(b): U.S. population; estimates based on adjusted CPS income data c
0–17 72,999,159 12,458,869 17.1 10,572,783 14.5 212,717 Adjusted Unadjusted
18–64 180,040,766 19,390,106 10.8 16,021,505 8.9
65 or older 34,659,258 3,281,911 9.5 3,217,534 9.3
Total 287,699,183 35,130,886 12.2 29,811,822 10.4
1(c): U.S. population with income adjustment, sample restriction, and reweighting d
0–17 72,571,990 12,343,900 17.0 10,341,176 14.2 176,378 Adjusted with sample restriction Adjusted
18–64 174,596,837 19,083,414 10.9 14,583,316 8.4
65 or older 33,410,983 2,970,712 8.9 2,877,647 8.6
Total 280,579,810 34,398,026 12.3 27,802,139 9.9
2(a): SSI recipient population; estimates based on unadjusted CPS income data e
0–17 364,478 130,015 35.7 130,015 35.7 3,689 Unadjusted Unadjusted
18–64 3,783,005 1,641,514 43.4 1,641,514 43.4
65 or older 1,225,478 491,079 40.1 491,079 40.1
Total 5,372,961 2,262,608 42.1 2,262,608 42.1
2(b): SSI recipient population; estimates based on adjusted CPS income data f
0–17 866,916 232,028 26.8 214,996 24.8 4,422 Adjusted Unadjusted
18–64 3,903,433 1,670,517 42.8 1,621,520 41.5
65 or older 1,690,810 697,426 41.2 687,139 40.6
Total 6,461,159 2,599,971 40.2 2,523,655 39.1
2(c): SSI recipient population with income adjustment, sample restriction, and reweighting g
0–17 902,579 242,513 26.9 224,514 24.9 3,641 Adjusted with sample restriction Adjusted
18–64 4,132,750 1,847,519 44.7 1,786,457 43.2
65 or older 1,994,570 898,805 45.1 883,584 44.3
Total 7,029,899 2,988,837 42.5 2,894,555 41.2
2004
1(a): U.S. population; estimates based on unadjusted CPS income data h
0–17 73,241,407 13,032,729 17.8 13,032,729 17.8 210,152 Unadjusted Unadjusted
18–64 182,165,671 20,542,896 11.3 20,542,896 11.3
65 or older 35,209,459 3,453,014 9.8 3,453,014 9.8
Total 290,616,537 37,028,639 12.7 37,028,639 12.7
1(b): U.S. population; estimates based on adjusted CPS income data c
0–17 73,241,407 12,841,996 17.5 10,831,290 14.8 210,152 Adjusted Unadjusted
18–64 182,165,671 20,389,278 11.2 17,005,469 9.3
65 or older 35,209,459 3,153,166 9.0 3,089,437 8.8
Total 290,616,537 36,384,440 12.5 30,926,196 10.6
1(c): U.S. population with income adjustment, sample restriction, and reweighting i
0–17 72,780,925 12,673,526 17.4 10,516,356 14.4 171,025 Adjusted with sample restriction Adjusted
18–64 174,149,526 19,695,068 11.3 15,120,123 8.7
65 or older 34,341,153 2,822,185 8.2 2,731,627 8.0
Total 281,271,604 35,190,779 12.5 28,368,106 10.1
2(a): SSI recipient population; estimates based on unadjusted CPS income data e
0–17 408,915 137,954 33.7 137,954 33.7 3,654 Unadjusted Unadjusted
18–64 4,036,944 1,636,391 40.5 1,636,391 40.5
65 or older 1,117,640 487,229 43.6 487,229 43.6
Total 5,563,499 2,261,574 40.7 2,261,574 40.7
2(b): SSI recipient population; estimates based on adjusted CPS income data f
0–17 901,805 288,788 32.0 264,954 29.4 4,371 Adjusted Unadjusted
18–64 4,136,748 1,704,145 41.2 1,642,760 39.7
65 or older 1,620,585 704,398 43.5 685,532 42.3
Total 6,659,138 2,697,331 40.5 2,593,246 38.9
2(c): SSI recipient population with income adjustment, sample restriction, and reweighting j
0–17 957,402 316,299 33.0 290,332 30.3 3,542 Adjusted with sample restriction Adjusted
18–64 4,158,826 1,831,598 44.0 1,750,954 42.1
65 or older 1,832,597 837,655 45.7 811,304 44.3
Total 6,948,825 2,985,552 43.0 2,852,590 41.1
2005
1(a): U.S. population; estimates based on unadjusted CPS income data k
0–17 73,285,108 12,876,738 17.6 12,876,738 17.6 207,987 Unadjusted Unadjusted
18–64 184,344,650 20,445,497 11.1 20,445,497 11.1
65 or older 35,504,791 3,603,363 10.1 3,603,363 10.1
Total 293,134,549 36,925,598 12.6 36,925,598 12.6
1(b): U.S. population; estimates based on adjusted CPS income data c
0–17 73,285,108 12,991,585 17.7 10,181,026 13.9 207,987 Adjusted Unadjusted
18–64 184,344,650 20,435,725 11.1 15,549,429 8.4
65 or older 35,504,791 3,087,589 8.7 3,000,478 8.5
Total 293,134,549 36,514,899 12.5 28,730,933 9.8
1(c): U.S. population with income adjustment, sample restriction, and reweighting l
0–17 73,122,462 12,906,491 17.7 9,962,323 13.6 195,241 Adjusted with sample restriction Adjusted
18–64 187,594,219 20,881,714 11.1 15,301,606 8.2
65 or older 35,489,782 2,986,274 8.4 2,894,087 8.2
Total 296,206,463 36,774,479 12.4 28,158,016 9.5
2(a): SSI recipient population; estimates based on unadjusted CPS income data e
0–17 379,909 163,268 43.0 163,268 43.0 3,578 Unadjusted Unadjusted
18–64 3,900,117 1,663,514 42.7 1,663,514 42.7
65 or older 1,176,402 463,754 39.4 463,754 39.4
Total 5,456,428 2,290,536 42.0 2,290,536 42.0
2(b): SSI recipient population; estimates based on adjusted CPS income data f
0–17 951,558 306,242 32.2 272,135 28.6 4,513 Adjusted Unadjusted
18–64 4,115,297 1,776,404 43.2 1,715,613 41.7
65 or older 1,825,269 804,188 44.1 789,392 43.2
Total 6,892,124 2,886,834 41.9 2,777,140 40.3
2(c): SSI recipient population with income adjustment, sample restriction, and reweighting m
0–17 997,049 326,283 32.7 290,511 29.1 4,298 Adjusted with sample restriction Adjusted
18–64 4,493,624 2,028,375 45.1 1,959,127 43.6
65 or older 1,878,685 850,640 45.3 835,042 44.4
Total 7,369,358 3,205,298 43.5 3,084,680 41.9
SOURCE: For the 2003 panel of the table, authors' calculations using 2004 CPS/ASEC public-use data matched to Social Security administrative records; for 2004, authors' calculations using 2005 survey data matched to administrative records; and for 2005, authors' calculations using 2006 survey data matched to administrative records.
NOTE: Weight adjustments are based on person-level records differentiated by age group.
a. Persons are identified as "poor" if their CPS total family income record is less than their corresponding CPS family poverty standard record. Family income records may include top-coded components. These totals differ slightly from official reports, which are based on actual reported income without top-coding.
b. Figures have been generated from the entire 2004 CPS/ASEC sample of 212,717 persons used by the Census Bureau to estimate poverty rates.
c. Income adjustments made using administrative data on SSI, OASDI, and earnings receipt, following decision rules as presented in text and Nicholas and Wiseman (2009).
d. Estimates derived from a reduced 2004 CPS/ASEC poverty sample of 176,378 persons who have at least one family member with matching CPS/SER records. Figures are based on the adjustment of CPS income records using administrative data following decision rules discussed in text and presented in detail in Nicholas and Wiseman (2009). Weights have been adjusted by propensity estimates derived from a regression model involving person-level records.
e. Persons identified as SSI recipients if they have a positive CPS SSI record.
f. Income adjustments made using administrative data on SSI, OASDI, and earnings receipt, following decision rules presented in text. SSI status based on adjusted data.
g. Estimates derived from a reduced 2004 CPS/ASEC poverty sample of 176,378 persons who have at least one family member with matching CPS/SER records. Figures are based on the adjustment of CPS income records using administrative data following decision rules presented in text. Weights have been adjusted by propensity estimates derived from a regression model involving person-level records; see text and Nicholas and Wiseman (2009) for methodology; propensity model estimates are available from the authors upon request. Persons are identified as SSI beneficiaries if they have a positive SSR SSI record.
h. Figures have been generated from the entire 2005 CPS/ASEC sample of 210,152 persons used by the Census Bureau to estimate poverty rates.
i. Estimates derived from a reduced 2005 CPS/ASEC poverty sample of 171,025 persons who have at least one family member with matching CPS/SER records. Figures are based on the adjustment of CPS income records using administrative data following decision rules discussed in text and presented in detail in Nicholas and Wiseman (2009). Weights have been adjusted by propensity estimates derived from a regression model involving person-level records.
j. Estimates derived from a reduced 2005 CPS/ASEC poverty sample of 171,025 persons who have at least one family member with matching CPS/SER records. Figures are based on the adjustment of CPS income records using administrative data following decision rules presented in text. Weights have been adjusted by propensity estimates derived from a regression model involving person-level records; see text and Nicholas and Wiseman (2009) for methodology; propensity model estimates are available from the authors upon request. Persons are identified as SSI beneficiaries if they have a positive SSR SSI record.
k. Figures have been generated from the entire 2006 CPS/ASEC sample of 207,987 persons used by the Census Bureau to estimate poverty rates.
l. Estimates derived from a reduced 2006 CPS/ASEC poverty sample of 195,241 persons who have at least one family member with matching CPS/SER records. Figures are based on the adjustment of CPS income records using administrative data following decision rules discussed in text and presented in detail in Nicholas and Wiseman (2009). Weights have been adjusted by propensity estimates derived from a regression model involving person-level records.
m. Estimates derived from a reduced 2006 CPS/ASEC poverty sample of 195,241 persons who have at least one family member with matching CPS/SER records. Figures are based on the adjustment of CPS income records using administrative data following decision rules presented in text. Weights have been adjusted by propensity estimates derived from a regression model involving person-level records; see text and Nicholas and Wiseman (2009) for methodology; propensity model estimates are available from the authors upon request. Persons are identified as SSI beneficiaries if they have a positive SSR SSI record.
Table A-2. The effect of merging CPS and Social Security administrative data on the estimated national income distribution using restrictive and inclusive income-adjustment protocols, 2003–2005
National income distribution Percentiles Data summary
10 20 40 50 60 80 90 Top decile 50 percent of the median Person records Income Weights
Restrictive 2003—
(a) using unadjusted income percentiles for all people a
Upper bound ($2002) 7,252 11,826 20,568 25,687 31,377 48,166 66,090 . . . 12,844   Unadjusted Unadjusted
Upper bound ($2003) 7,416 12,094 21,035 26,270 32,089 49,258 67,589 . . . 13,135 212,717
Distribution (%)                    
All people 10.0 10.0 20.0 10.0 10.0 20.0 10.0 10.0 22.4 212,717
Elderly b 7.2 15.9 29.5 11.3 8.8 14.2 5.9 7.0 27.7 20,369
Elderly SSI c 25.0 44.8 15.6 5.5 2.7 3.9 0.9 1.1 73.3 813
(b) using adjusted income percentiles for all people (unadjusted weights) d
Upper bound ($2002) 7,420 11,914 20,487 25,457 31,004 47,663 65,694 . . . 12,728   Adjusted Unadjusted
Upper bound ($2003) 7,588 12,184 20,952 26,034 31,707 48,744 67,184 . . . 13,017 212,717
Distribution (%)                    
All people 10.0 10.0 20.0 10.0 10.0 20.0 10.0 10.0 22.0 212,717
Elderly 7.3 14.7 29.0 11.3 9.1 15.1 6.2 7.3 25.4 20,369
Elderly SSI e 33.6 36.4 14.2 4.7 3.6 4.5 1.7 1.3 72.5 813
(c) using adjusted income percentiles for all people (adjusted weights) f
Upper bound ($2002) 7,458 11,917 20,471 25,337 30,843 47,213 65,008 . . . 12,669   Adjusted with sample restriction Adjusted
Upper bound ($2003) 7,627 12,187 20,935 25,912 31,543 48,284 66,483 . . . 12,956 176,378
Distribution (%)                    
All people 10.0 10.0 20.0 10.0 10.0 20.0 10.0 10.0 21.8 176,378
Elderly b 7.0 14.0 58.3 11.5 9.4 16.0 6.3 7.6 23.6 13,539
Elderly SSI g 37.3 34.9 13.5 4.3 3.3 4.5 1.2 1.1 73.9 880
Inclusive 2003—
(a) using unadjusted income percentiles for all people a
Upper bound ($2002) 7,252 11,826 20,568 25,687 31,377 48,166 66,090 . . . 12,844   Unadjusted Unadjusted
Upper bound ($2003) 7,416 12,094 21,035 26,270 32,089 49,258 67,589 . . . 13,135 212,717
Distribution (%)                    
All people 10.0 10.0 20.0 10.0 10.0 20.0 10.0 10.0 22.4 212,717
Elderly b 7.2 15.9 29.5 11.3 8.8 14.2 5.9 7.0 27.7 20,369
Elderly SSI c 25.0 44.8 15.6 5.5 2.7 3.9 0.9 1.1 73.3 813
(b) using adjusted income percentiles for all people (unadjusted weights) d
Upper bound ($2002) 8,259 13,117 22,479 27,728 33,730 51,420 70,804 . . . 13,864   Adjusted Unadjusted
Upper bound ($2003) 8,446 13,415 22,989 28,357 34,495 52,586 72,410 . . . 14,179 212,717
Distribution (%)                    
All people 10.0 10.0 20.0 10.0 10.0 20.0 10.0 10.0 21.6 212,717
Elderly 9.4 17.1 28.7 10.2 8.6 13.3 5.9 6.9 29.3 20,369
Elderly SSI e 43.9 28.3 11.9 5.3 2.4 5.9 1.2 1.2 73.2 1,090
(c) using adjusted income percentiles for all people (adjusted weights) f
Upper bound ($2002) 8,562 13,478 22,882 28,208 34,209 52,071 72,252 . . . 14,104   Adjusted with sample restriction Adjusted
Upper bound ($2003) 8,756 13,784 23,401 28,848 34,985 53,252 73,891 . . . 14,424 176,378
Distribution (%)                    
All people 10.0 10.0 20.0 10.0 10.0 20.0 10.0 10.0 21.4 176,378
Elderly b 9.4 16.7 27.8 10.3 9.3 13.5 6.4 6.8 28.2 13,539
Elderly SSI g 48.0 26.0 11.4 5.0 2.7 5.1 0.9 1.0 74.7 880
Restrictive 2004—
(a) using unadjusted income percentiles for all people h
Upper bound ($2002) 7,115 11,854 20,604 25,532 31,040 47,612 65,207 . . . 12,766   Unadjusted Unadjusted
Upper bound ($2004) 7,472 12,448 21,637 26,812 32,596 50,000 68,477 . . . 13,406 210,152
Distribution (%)                    
All people 10.0 10.0 20.0 10.0 10.0 20.0 10.0 10.0 22.2 210,152
Elderly b 7.0 15.6 29.4 11.4 8.8 14.3 6.5 7.0 26.4 20,561
Elderly SSI c 26.2 39.8 18.9 4.1 3.8 3.9 2.2 1.1 67.3 1,030
(b) using adjusted income percentiles for all people (unadjusted weights) i
Upper bound ($2002) 7,307 11,859 20,575 25,415 30,920 47,888 66,087 . . . 12,707   Adjusted Unadjusted
Upper bound ($2004) 7,673 12,454 21,607 26,689 32,470 50,289 69,401 . . . 13,345 210,152
Distribution (%)                    
All people 10.0 10.0 20.0 10.0 10.0 20.0 10.0 10.0 22.1 210,152
Elderly 6.5 14.3 29.8 11.7 9.3 15.3 6.6 6.7 24.1 20,561
Elderly SSI e 34.0 31.7 17.9 4.8 3.5 5.8 1.3 1.1 68.6 1,030
(c) using adjusted income percentiles for all people (adjusted weights) j
Upper bound ($2002) 7,399 11,823 20,468 25,209 30,632 47,453 66,072 . . . 12,604   Adjusted with sample restriction Adjusted
Upper bound ($2004) 7,770 12,416 21,494 26,473 32,168 49,833 69,385 . . . 13,237 171,025
Distribution (%)                    
All people 10.0 10.0 20.0 10.0 10.0 20.0 10.0 10.0 21.9 171,025
Elderly b 6.0 13.3 29.2 11.9 9.9 16.3 6.9 6.7 21.9 13,135
Elderly SSI g 38.7 28.3 17.2 5.0 3.7 5.6 1.0 0.5 69.8 815
Inclusive 2004—
(a) using unadjusted income percentiles for all people h
Upper bound ($2002) 7,115 11,854 20,604 25,532 31,040 47,612 65,207 . . . 12,766   Unadjusted Unadjusted
Upper bound ($2004) 7,472 12,448 21,637 26,812 32,596 50,000 68,477 . . . 13,406 210,152
Distribution (%)                    
All people 10.0 10.0 20.0 10.0 10.0 20.0 10.0 10.0 22.2 210,152
Elderly b 7.0 15.6 29.4 11.4 8.8 14.3 6.5 7.0 26.4 20,561
Elderly SSI c 26.2 39.8 18.9 4.1 3.8 3.9 2.2 1.1 67.3 1,030
(b) using adjusted income percentiles for all people (unadjusted weights) i
Upper bound ($2002) 8,138 13,093 22,508 27,655 33,444 51,268 70,343 . . . 13,828   Adjusted Unadjusted
Upper bound ($2004) 8,546 13,750 23,637 29,042 35,121 53,839 73,870 . . . 14,521 210,152
Distribution (%)                    
All people 10.0 10.0 20.0 10.0 10.0 20.0 10.0 10.0 21.6 210,152
Elderly 8.4 16.7 29.3 10.8 8.3 13.9 6.2 6.5 27.9 20,561
Elderly SSI e 41.6 26.4 15.8 4.2 4.2 5.0 1.9 0.9 69.7 1,030
(c) using adjusted income percentiles for all people (adjusted weights) j
Upper bound ($2002) 8,489 13,429 22,860 28,103 33,861 52,099 72,221 . . . 14,051   Adjusted with sample restriction Adjusted
Upper bound ($2004) 8,915 14,102 24,006 29,512 35,559 54,711 75,842 . . . 14,756 171,025
Distribution (%)                    
All people 10.0 10.0 20.0 10.0 10.0 20.0 10.0 10.0 21.4 171,025
Elderly b 8.4 15.8 28.9 10.8 8.7 14.4 6.4 6.6 26.7 13,135
Elderly SSI g 45.9 23.9 15.4 4.2 3.8 4.9 1.3 0.6 70.8 815
Restrictive 2005—
(a) using unadjusted income percentiles for all people k
Upper bound ($2002) 7,185 11,956 20,781 25,704 31,339 47,884 66,250 . . . 12,852 207,987 Unadjusted Unadjusted
Upper bound ($2005) 7,801 12,981 22,562 27,907 34,025 51,989 71,929 . . . 13,954  
Distribution (%)                    
All people 10.0 10.0 20.0 10.0 10.0 20.0 10.0 10.0 22.2 207,987
Elderly b 7.0 16.0 28.9 11.0 9.3 14.1 6.1 7.6 26.1 20,413
Elderly SSI c 22.9 45.5 17.0 2.4 4.7 3.7 1.8 2.0 71.5 757
(b) using adjusted income percentiles for all people (unadjusted weights) l
Upper bound ($2002) 7,293 11,936 20,735 25,635 31,326 48,800 67,983 . . . 12,818 207,987 Adjusted Unadjusted
Upper bound ($2005) 7,918 12,959 22,513 27,833 34,011 52,983 73,811 . . . 13,917  
Distribution (%)                    
All people 10.0 10.0 20.0 10.0 10.0 20.0 10.0 10.0 22.0 207,987
Elderly 6.2 14.0 29.2 11.8 9.6 15.4 15.4 6.6 23.3 20,413
Elderly SSI e 35.4 33.7 13.6 5.6 4.1 4.3 2.1 1.2 70.7 1,181
(c) using adjusted income percentiles for all people (adjusted weights) m
Upper bound ($2002) 7,334 11,953 20,768 25,705 31,433 48,907 68,038 . . . 12,852 195,241 Adjusted with sample restriction Adjusted
Upper bound ($2005) 7,963 12,978 22,548 27,908 34,128 53,099 73,871 . . . 13,954  
Distribution (%)                    
All people 10.0 10.0 20.0 10.0 10.0 20.0 10.0 10.0 22.1 195,241
Elderly b 6.0 14.0 29.4 11.9 9.7 15.4 6.6 7.1 23.2 19,178
Elderly SSI g 36.7 33.0 13.3 5.8 3.6 4.1 2.2 1.3 71.3 1,128
Inclusive 2005—
(a) using unadjusted income percentiles for all people k
Upper bound ($2002) 7,185 11,956 20,781 25,704 31,339 47,884 66,250 . . . 12,852 207,987 Unadjusted Unadjusted
Upper bound ($2005) 7,801 12,981 22,562 27,907 34,025 51,989 71,929 . . . 13,954  
Distribution (%)                    
All people 10.0 10.0 20.0 10.0 10.0 20.0 10.0 10.0 22.2 207,987
Elderly b 7.0 16.0 28.9 11.0 9.3 14.1 6.1 7.6 26.1 20,413
Elderly SSI c 22.9 45.5 17.0 2.4 4.7 3.7 1.8 2.0 71.5 757
(b) using adjusted income percentiles for all people (unadjusted weights) l
Upper bound ($2002) 8,661 13,816 23,668 29,065 35,344 54,098 75,823 . . . 14,533 207,987 Adjusted Unadjusted
Upper bound ($2005) 9,403 15,000 25,697 31,557 38,374 58,735 82,323 . . . 15,779  
Distribution (%)                    
All people 10.0 10.0 20.0 10.0 10.0 20.0 10.0 10.0 21.4 207,987
Elderly 9.4 16.7 28.6 10.3 8.7 13.3 6.2 6.9 28.3 20,413
Elderly SSI e 46.0 24.5 13.4 5.0 3.9 3.9 1.8 1.6 71.7 1,181
(c) using adjusted income percentiles for all people (adjusted weights) m
Upper bound ($2002) 8,860 14,039 23,976 29,403 35,669 54,422 76,447 . . . 14,702 195,241 Adjusted with sample restriction Adjusted
Upper bound ($2005) 9,620 15,243 26,031 31,924 38,727 59,087 83,000 . . . 15,962  
Distribution (%)                    
All people 10.0 10.0 20.0 10.0 10.0 20.0 10.0 10.0 21.3 195,241
Elderly b 9.6 17.2 28.4 10.2 8.6 13.3 6.0 6.8 28.8 19,178
Elderly SSI g 47.9 23.6 13.1 4.9 3.4 3.6 1.8 1.7 72.2 1,128
SOURCE: For the 2003 panel of the table, authors' calculations using 2004 CPS/ASEC public-use data matched to Social Security administrative records; for 2004, authors' calculations using 2005 survey data matched to administrative records; and for 2005, authors' calculations using 2006 survey data matched to administrative records.
NOTES: . . . = data not applicable. Both the restrictive and inclusive estimates are replicated for 2002 in Table 5 of this article.
a. Figures involve unadjusted CPS income data and weights as well as the entire 2004 CPS/ASEC poverty sample of 212,717 persons.
b. Persons with a CPS-reported age of 65 or older.
c. Persons with a positive CPS record.
d. Estimates are based on adjusted CPS income records, unadjusted weights, and involve the entire 2004 CPS/ASEC poverty sample.
e. Persons are identified as SSI recipients if either they have no matching CPS/SER records and a positive CPS SSI record or matching CPS/SER records and a positive SSR SSI record.
f. Figures involve adjusted CPS income data and weights and a reduced 2004 CPS/ASEC poverty sample.
g. Persons are identified as SSI recipients if they have a positive SSR SSI record.
h. Figures involve unadjusted CPS income data and weights as well as the entire 2005 CPS/ASEC poverty sample of 210,152 persons.
i. Estimates are based on adjusted CPS income records, unadjusted weights, and involve the entire 2005 CPS/ASEC poverty sample.
j. Figures involve adjusted CPS income data and weights and a reduced 2005 CPS/ASEC poverty sample.
k. Figures involve unadjusted CPS income data and weights as well as the entire 2006 CPS/ASEC poverty sample of 207,987 persons.
l. Estimates are based on adjusted CPS income records, unadjusted weights, and involve the entire 2006 CPS/ASEC poverty sample.
m. Figures involve adjusted CPS income data and weights and a reduced 2006 CPS/ASEC poverty sample.

Notes

1 Alexander, Davern, and Stevenson (2010) report discovery of errors in age- and sex-specific population estimates generated from the 2004–2009 CPS for persons aged 65 or older. These errors are apparently produced by misapplication of disclosure avoidance procedures to the CPS and certain other public-use microdata samples (PUMS). According to the authors (p. 11), the problems arise only in disaggregating the data for the elderly by age and sex and do not apply when the data are "grouped into a single age 65 or older category," which is done in the present analysis.

2 The SER also includes earnings data. However, annual earnings reports in the SER are capped at the FICA/SECA taxable maximum ($84,900 in 2002).

3 Information on retirement plan contributions in the DER corresponds to codes "d" through "h" in box 13 on the W-2 form: 401(k), SiMPLE, 403(b), 408(k) and (6), SEP, 457(b), and 501(c), (18), and (D) plans (Smith, Johnson, and Muller 2004, 8). See Abowd and Stinson (2005, 10) for a more detailed discussion of elements of gross compensation (for example, pretax health insurance premiums paid by the employee) that will not appear in the DER.

4 The data aggregation was performed by SSA's Office of Research, Evaluation, and Statistics following a protocol established by the agency.

5 See Sears and Rupp (2003) for an investigation on the divergence between payment eligibility and payment receipt and the consequence for assessment of errors in OASDI-reporting in the Survey of Income and Program Participation. Koenig (2003) analyzes OASDI/SSI underreporting in the March 1997 CPS, but could use only information on OASDI entitlement, not payments (as in the PHUS) for comparison with CPS reports.

6 See Iceland (2005). Under the three-parameter NRC equivalence scale, to achieve an equivalent standard of living, for every $1 of income for a single individual, a childless couple would require $1.41; single-parent families would need $(A + + P * (C-1))F; and all other families would require $(A + P * C)F, where A is the number of adults in a family and C is the number of children. Following the NRC review of the Census Bureau poverty standard, we assume that = 0.8, P = 0.5, and F = 0.7. The parameter P indicates how children are to be weighted relative to adults: P = 0.5 means that each child beyond the first one requires half the income needed for adults. The parameter allows the first child in a single-parent family to be weighted differently from others. F reflects economies of scale.

References

Abowd, John M., and Martha H. Stinson. 2005. Estimating measurement error in SIPP annual job earnings: A comparison of Census survey and administrative data. Unpublished manuscript, Cornell University. Available at http://courses.cit.cornell.edu/jma7/abowd-stinson-200501.pdf.

Alexander, J. Trent, Michael Davern, and Betsey Stevenson. 2010. Inaccurate age and sex data in the Census PUMS files: Evidence and implications. Working Paper No. 15703. Cambridge, MA: National Bureau of Economic Research.

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