Acknowledgments: The authors thank Rob Gesumaria for excellent programming assistance and Dean Leimer for many helpful comments over the course of this study. The authors also thank Lee Cohen, Linda Del Bene, Howard Iams, Joyce Manchester, and especially Mike Leonesio for constructive comments and Pat Cole for table preparation. An earlier version of this paper was presented at the 2004 International Association for Research in Income and Wealth General Conference in Cork, Ireland, August
Working papers in this series are preliminary materials circulated for review and comment. The findings and conclusions expressed in them are the authors' and do not necessarily represent the views of the Social Security Administration.
Social Security benefits are the major source of income and wealth for retirees. In 2002, 66 percent of aged beneficiaries (those aged 65 or older) received at least half of their income from Social Security benefits. For 22 percent of aged beneficiaries, Social Security was their only source of income. These benefits are especially important for low earners, widows, and certain other groups of retirees. Moreover, benefits are now almost universal. The proportion of the aged population receiving Social Security benefits rose from 69 percent in 1962 to 90 percent in 2002.
A number of recent studies attempt to examine the adequacy of retirement resources for people approaching retirement. For example, a widely cited 2001 study by Edward Wolff concludes that the Social Security wealth (adjusted for inflation) of people aged 47 to 64 declined from 1983 to 1998. Wolff's result is unexpected, because real Social Security benefits for newly retired workers are structured to grow in line with average wages in the economy. Greater longevity also increases the lifetime value of Social Security benefits, although the scheduled increase in the age of eligibility for full retirement benefits dampens this effect. Wolff, however, did not have access to the earnings histories of the people in the survey used for his analysis. He therefore based his estimates of Social Security benefits and wealth on only a single year of individual earnings, from which he estimated lifetime earnings.
This paper uses better, more comprehensive information to examine Social Security benefits as a retirement resource for individuals recently reaching retirement and those who can expect to retire in the near future. Specifically, it looks at people turning age 61 in 1988 through 2007 (those born from 1927 to 1946), because 62 is the age of first eligibility for Social Security retirement benefits. In contrast to Wolff's analysis, this analysis is based primarily on actual data on lifetime earnings, which yield estimates of Social Security benefits that are much more accurate than those generally available.
The data for this analysis come from the Social Security Administration's project for Modeling Income in the Near Term (MINT). The MINT data files include the Social Security Administration's administrative records on earnings and benefits matched to survey responses from the Census Bureau's Survey of Income and Program Participation. Because of the extensive scope of the data set, this analysis requires considerably less use of imputations and projections than did most previous studies. Imputations and projections that were required were done by MINT modelers using sophisticated analytical methods. The results suggest that Social Security wealth increased considerably faster than estimated by Wolff.
This paper analyzes several different measures of Social Security benefits and examines how they have changed from one cohort to another. Among its findings are the following:
Social Security benefits are the major source of income and wealth for retirees. In 2002, 66 percent of aged beneficiaries (65 or older) received at least half of their income from these benefits, and for 22 percent these benefits were the only source of income (Social Security Administration 2004). These benefits are especially important for low earners and for certain population subgroups, such as widows. Moreover, benefits are now almost universal. The proportion of the aged population receiving Social Security benefits rose from 69 percent in 1962 to 90 percent in 2002.
This paper analyzes Social Security benefits as a retirement resource for today's near-retirees and for earlier cohorts of near-retirees. The near-retirees in this study are people who reach age 61 during the 1988–2007 period. One reason for selecting these birth-year cohorts is that these individuals are not likely to be markedly affected by possible future cuts in benefits; and we choose age 61 because 62 is the age of first eligibility for Social Security retired-worker and spouse benefits. We examine how the average values of several benefit measures (Social Security wealth, annualized benefit payout, and earnings replacement rates) have changed from earlier cohorts to today's near-retiree cohort. We examine how within a cohort these benefit measures differ among sex, marital status, and earnings quintile subgroups and how these measures have changed over time. We look at some reasons for these changes and differences and discuss the effects of earnings, marital behavior, longevity, and Social Security program provisions on these Social Security benefit measures. Our findings can help efforts to understand the economic well-being of the aged and develop proposals to improve the Social Security program.
Other studies have examined the retirement resources of near-retirees (see, for example, Wolff 2001; Engen, Gale, and Uccello 2000; Bernheim 1993; and Congressional Budget Office 1993). A number of these studies focused on other types of retirement resources, such as private pension and private asset wealth. Those that include Social Security estimates generally are plagued by serious data problems, especially inaccurate estimates of Social Security benefits over the period of benefit receipt.1 Benefit estimates based on inaccurate earnings estimates are commonly used to evaluate this component of total retirement wealth. Wolff (2001), for example, estimated lifetime earnings based on a single year of earnings, which in turn were used to calculate the Social Security retirement wealth of near-retirees. He found that the mean real Social Security wealth of people aged
This paper provides an in-depth examination of Social Security benefits for a specific group of the retiree population, namely recent near-retirees and those who can expect to retire in the very near future. We compute a variety of benefit measures that have not been used in previous studies. We rely primarily on actual earnings history data to examine Social Security benefits as a retirement resource for near-retirees. The use of observed earnings histories allows us to capture the large variation in these histories, unlike methods that estimate earnings histories based on a single earnings equation. The study uses data from the Social Security Administration's project for Modeling Income in the Near Term (MINT). The MINT data files include Social Security Administration (SSA) administrative earnings and benefit history records exact-matched to the 1990–1993 panels of the Survey of Income and Program Participation. Because of the extensive content of this data set, we are able to use fewer imputations and projections than have a number of other studies of the subject. Any imputations and projections that were required were done by MINT modelers using sophisticated methods. Thus, this paper attempts to produce more accurate measures of Social Security benefits by using improved data. Our results suggest that Social Security wealth increased considerably faster than was shown by Wolff.
Modeling Income in the Near Term (MINT) is a large-scale effort that has been under way since the late 1990s. Much of the developmental work was done for the Social Security Administration by analysts at the Urban Institute, RAND Corporation, and Brookings Institution. The starting sample is from the 1990, 1991, 1992, and 1993 panels of the Survey of Income and Program Participation (SIPP). In this survey of the noninstitutionalized population, interviews were conducted once every 4 months for
As part of the MINT project, SSA administrative records were exact-matched to SIPP data for sample members born during the 1926–1965 period. These administrative records include earnings history, benefit history, and death information through 1999. Exact matches were made for about 92 percent of these persons, and administrative records were imputed by MINT modelers for the remaining 8 percent. For years after the time range of the administrative and survey data, the MINT model projects dates of death, institutionalizations, marital histories, earnings histories, and benefit histories. In addition, individuals are projected to enter the sample by means of immigration. These projections were designed to be generally consistent with the intermediate assumptions of the 2002 Old-Age, Survivors, and Disability Insurance (OASDI) Trustees Report (Board of Trustees 2002). Additional information about MINT imputations and projections is given in Appendix A. For a detailed description of the MINT3 data, see Toder and others (2002).
This study uses MINT3 data files created in April 2003. That data set has notable strengths. First, longitudinal administrative data are available through 1999. Thus, earnings history data are available through age 53 for the youngest birth cohort analyzed (those born in 1946) and through age 72 for the oldest birth cohort (born in 1927). Benefit record information is available for the great majority of members of the eight oldest single-year cohorts (born 1927–1934) and for many members of the next three single-year cohorts (born 1935–1937). Second, the combined SIPP panels provide a large sample. Each of the single-year birth cohorts is represented by a sample of more than 1,000 persons. Studies of retirement resources of near-retirees typically use much smaller samples.
This section discusses the empirical constructs of the study: the definition of cohorts of near-retirees and the benefit measures (Social Security wealth, annualized payout, and earnings replacement rates).
The unit of analysis is the person and not some larger unit, such as a marital unit or family. In studies that use longitudinal data, the person is often the unit of analysis. The composition of the larger units changes over time. For example, the marital status of most persons changes one or more times during their adult lifetime.
The paper looks at 20 single-year cohorts, that is, those persons reaching age 61 in the 20 years from 1988 through 2007. Each single-year cohort consists of all persons who reach age 61 during that year and are members of the noninstitutionalized population at the end of that year, that is, at the beginning of the year most of them can first receive Social Security retirement benefits.
To facilitate the presentation of results and to avoid small sample sizes for certain sex and marital status subgroups, such as widowers, we combine these 20 single-year cohorts into four groups of five single-year cohorts each. Throughout this paper, the term cohort refers to these
The MINT population excludes persons reaching age 61 in 1988–1992 who were not eligible for SIPP interviews because after reaching age 61 they died, were institutionalized, or left the country before the first SIPP interviews in 1990–1993. This attrition affects the size and composition of the 1988 cohort but does not affect the other three cohorts. Without appropriate correction for attrition bias, the benefit and earnings measures (median Social Security wealth and so on) for the 1988 cohort are not totally comparable with those of the latter three cohorts. This attrition is relatively small. We attempt to remove the effects of this attrition on the benefit and earnings measures for the 1988 cohort by using attrition factors and thus making these measures comparable with those for the other three cohorts. We compute attrition factors using data from the 1993 cohort of near-retirees. For a description and discussion of our attrition correction method, see Appendix B.
Our benefit concept is shared benefits. For each year a person is married, the person's shared benefit equals half the benefits received by the couple. It is our view that shared benefit is superior to individual benefit as a measure of the income support the person receives from the OASDI program. The individual benefits of husband and wife often are quite different. However, most married couples share their incomes. For each year a person is not married, the person's shared benefit equals the benefits received by the person.2
Our benefit measures, such as Social Security wealth, include benefits received in the years after the year the person reaches age 61. Our measures include benefits paid from the Old-Age and Survivors (OASI) and Disability Insurance (DI) trust funds, to a worker, spouse, divorced spouse, surviving spouse, or surviving divorced spouse.
Social Security Wealth. For each person with benefits, we compute Social Security wealth—the present value of shared benefits evaluated as of January 1 of the year the person reaches age 62. Real Social Security wealth (SSW) is expressed in prices as of January 1, 2002. Our annual discount rate series consists of the rates of return on OASI trust fund assets. Projected
Annualized SSW Payout. For each person with benefits, we compute an annualized SSW payout (ANNPAYOUT), which is equal to the constant real annual payment over all of the person's potential benefit years that has a present value equal to the person's SSW. As with SSW, ANNPAYOUT is expressed in prices as of January 1, 2002. Potential benefit years consist of all years from the year the person reaches age 62 through the last year before the year of death.3 After 1999, the year of death is that projected by the MINT model.
ANNPAYOUT, which has not been used in previous studies, is a useful measure of the average annual support provided by Social Security over the years after age 61.4 ANNPAYOUT is less affected by increases over cohorts or differences within cohorts in longevity than is the SSW measure.5
Earnings Replacement Rates. There are a number of possible replacement rate measures. For example, replacement rates have been defined as the percentage of average earnings for the last few years before benefit receipt that are replaced by benefits. Our replacement rates measure the extent to which average career earnings are replaced by benefits. One reason for selecting average career earnings for the replacement rate measures is that one goal of the Social Security program is to provide benefits that replace a portion of average career earnings. For each person with some shared earnings, we calculate two earnings replacement rates—one for average wage-indexed shared taxable earnings
Taxable earnings (wages and self-employment income) are those below the legislated taxable maximum (the maximum amount of annual earnings included in the calculation of benefits). For each year since 1981, the legislated taxable maximum has been indexed by SSA's average annual wage series; therefore, since 1983 the ratio of the legislated taxable maximum to the average annual wage has been roughly constant at about 2.3 to 2.5. The ratio was 2.3 to 2.4 during 1983–1989 and 2.4 to 2.5 during the 1990s. Before 1983, this ratio was always below 2.3 and varied substantially. The ratio was 1.0 to 1.7 during 1951–1978 and 2.0 to 2.2 during 1979–1982.6
Less-censored earnings for a worker are those from employment covered by Social Security that are estimated to be below a hypothetical taxable maximum that for each year was set at about 2.45 times the average annual wage. For years before 1990, the MINT model projects less-censored earnings in excess of the legislated taxable maximum.7 Less-censored earnings are superior to taxable earnings in approximating relative changes in total earnings over cohorts or differences in total earnings within cohorts among socioeconomic subgroups.
We compute average taxable wage-indexed earnings as follows. For each person, shared taxable earnings for each year of the computation period (defined below) are indexed, using the average wage series, to wage levels as of the beginning of the year the person reaches age 62. The indexed earnings are then averaged over the person's computation period. Finally, this average is expressed in prices prevailing as of January 1, 2002, to get a measure of average wage-indexed shared taxable earnings,
A person's
All of our results are for Social Security program participants, that is, near-retirees with some shared earnings (with positive
Average SSW increases as we move from earlier to later near-retiree cohorts; the medians and means exhibit similar patterns (Table 1). The percentage increase in median SSW from the 1993 cohort to the 1998 cohort (20 percent) is larger than the increases for 1988–1993 (16 percent) and 1998–2003 (12 percent). The growth of average
Measure | Cohort a | Percentage change | |||||||
---|---|---|---|---|---|---|---|---|---|
1988 | 1993 | 1998 | 2003 | 1988– 1993 |
1993– 1998 |
1998– 2003 |
1993– 2003 |
1988– 2003 |
|
Social Security wealth (SSW, dollars) | |||||||||
Median | 105,624 | 122,258 | 147,003 | 164,961 | 16 | 20 | 12 | 35 | 56 |
Mean | 108,352 | 125,588 | 153,307 | 173,296 | 16 | 22 | 13 | 38 | 60 |
Annualized payout (ANNPAYOUT, dollars) | |||||||||
Median | 5,580 | 6,338 | 7,487 | 8,292 | 14 | 18 | 11 | 31 | 49 |
Mean | 5,382 | 6,079 | 7,189 | 7,952 | 13 | 18 | 11 | 31 | 48 |
Median replacement rate (percent) | |||||||||
Taxable earnings |
32.6 | 33.9 | 32.2 | 31.0 | 4 | -5 | -4 | -9 | -5 |
Less-censored earnings |
28.8 | 30.6 | 30.0 | 29.5 | 6 | -2 | -2 | -4 | 2 |
Average wage-indexed earnings (dollars) | |||||||||
Taxable |
|||||||||
Median | 16,836 | 18,454 | 22,915 | 26,198 | 10 | 24 | 14 | 42 | 56 |
Mean | 16,460 | 18,309 | 22,995 | 26,770 | 11 | 26 | 16 | 46 | 63 |
Less-censored |
|||||||||
Median | 19,093 | 20,276 | 24,437 | 27,237 | 6 | 21 | 11 | 34 | 43 |
Mean | 18,917 | 20,354 | 24,775 | 28,061 | 8 | 22 | 13 | 38 | 48 |
Mean potential benefit years | 21.23 | 21.47 | 21.97 | 22.34 | 1.13 | 2.33 | 1.68 | 4.05 | 5.23 |
SOURCE: Authors' calculations using data from Modeling Income in the Near Term (MINT3). | |||||||||
NOTE: Money amounts are in January 1, 2002, dollars. | |||||||||
a. Persons aged |
There are very few studies with which we can compare these results. Wolff (2001) provided estimates of Social Security wealth for the soon-to-retire.11 He reported that over the period 1983–1998, mean real Social Security wealth declined among the soon-to-retire older U.S. households (
We provide a brief comparison of our results for mean Social Security wealth with those obtained by Wolff for roughly comparable age groups and roughly comparable periods. Our results indicate that between 1988 and 1998, mean real Social Security wealth increased by 39 percent for those aged
We do not find any evidence of declining average real Social Security wealth in our results that span the period 1988–2003. Instead, successive cohorts of near-retirees receive higher average real amounts than previous cohorts. For our cohorts aged
Average real annualized payout also increases as we move from earlier to later near-retiree cohorts; the medians and means for annualized payouts exhibit similar patterns (Table 1). The relative 1993–1998 increase in median ANNPAYOUT (18 percent) is larger than the increases for 1988–1993 (14 percent) and 1998–2003 (11 percent). Notice that the relative increases in average ANNPAYOUT are slightly smaller than the corresponding increases in average SSW. This difference is due to small increases in average potential benefit years (all years from age 62 through the year before death); the increases in mean potential benefit years are 1.0 percent for 1988–1993, 2.3 percent for 1993–1998, and 1.7 percent for 1998–2003. These increases in potential benefit years are the actual and projected increases in life expectancy.
Recall that
As we move from earlier to later near-retiree cohorts, the median taxable earnings replacement rate first increases (by 4 percent for 1988–1993) and then decreases (by 5 percent for 1993–1998 and by 4 percent for 1998–2003).13 We discuss three causes of the 1993–2003 declines in median
Phased Increase in Full Retirement Age. A key cause of the 1993–2003 declines in
Larger Intercohort Percentage Increases in
Interaction Between Growth of Women's Labor Market Activity and the Benefit Formula. This interaction may also account for part of the 1993–2003 decrease in
Difference in Wage-Indexing. A person's retired-worker benefits are based on that person's average indexed monthly earnings. In the computation of AIME, the person's earnings are wage-indexed to the level of the SSA average annual wage prevailing for the calendar year in which the person attains age 60.17 Taxable earnings,
As we move from earlier to later near-retiree cohorts, the median less-censored earnings replacement rate also first increases (by 6 percent for 1988–1993) and then decreases (by 2 percent for 1993–1998 and for 1998–2003). Notice that the relative decreases in median
We now turn to results for sex and marital status subgroups. Marital status is as of the beginning of the year the person reaches age 62. Table 2 briefly describes several characteristics of each cohort of near-retirees. Educational attainment levels have steadily risen from earlier to later near-retiree cohorts. In the 2003 cohort, 28 percent of near-retirees are college graduates compared with only 17 percent just 15 years earlier. The percentage of people who identified themselves as white decreased slightly, the percentage identifying themselves as Hispanic rose, and the percentage of foreign-born individuals among near-retirees increased markedly. The 2003 cohort has the largest share of divorced individuals, and the mean number of marriages entered during one's lifetime has risen slightly.
Characteristic | 1988 | 1993 | 1998 | 2003 |
---|---|---|---|---|
Male (percent) | 46.74 | 48.20 | 47.65 | 48.43 |
Education (percent) | ||||
Dropout | 28.48 | 24.71 | 18.59 | 14.92 |
High school graduate | 54.64 | 56.03 | 59.95 | 57.58 |
College graduate | 16.87 | 19.27 | 21.46 | 27.50 |
Number of grades completed (mean) | 12.03 | 12.32 | 12.75 | 13.21 |
Race (percent) | ||||
White | 88.05 | 86.60 | 86.95 | 85.56 |
Black | 8.98 | 9.95 | 9.62 | 10.09 |
Native American | 0.60 | 0.71 | 0.70 | 0.56 |
Asian | 2.36 | 2.73 | 2.72 | 3.79 |
Hispanic (percent) | 5.77 | 6.72 | 6.77 | 7.51 |
Foreign born (percent) | 7.96 | 9.92 | 10.35 | 11.57 |
Marital status at age 62 (percent) | ||||
Never married | 4.08 | 4.23 | 4.32 | 5.10 |
Women | 1.62 | 2.06 | 2.22 | 2.72 |
Men | 2.46 | 2.17 | 2.10 | 2.38 |
Married | 74.50 | 74.46 | 73.24 | 71.35 |
Women | 35.39 | 34.60 | 34.78 | 33.52 |
Men | 39.11 | 39.86 | 38.46 | 37.83 |
Widowed | 12.36 | 10.06 | 7.83 | 7.55 |
Woman | 10.42 | 8.61 | 6.63 | 5.99 |
Men | 1.94 | 1.45 | 1.20 | 1.56 |
Divorced | 9.06 | 11.26 | 14.61 | 16.00 |
Woman | 5.64 | 6.54 | 8.72 | 9.34 |
Men | 3.43 | 4.72 | 5.89 | 6.66 |
Number of marriages (mean) | 1.29 | 1.35 | 1.39 | 1.42 |
Sample size (unweighted) | 6,602 a | 6,584 | 7,524 | 9,562 |
Total number of near-retirees (weighted) | 10,372,401 | 10,032,734 | 11,114,759 | 13,910,898 |
SOURCE: Authors' calculations using data from Modeling Income in the Near Term (MINT3). | ||||
a. Not corrected for attrition. |
For each marital status subgroup, SSW is greater for women than men (Table 3a). For each of the not-married subgroups, SSW is greater for women because on average they have a longer period of benefit receipt. For the married subgroup, SSW is greater for women for two reasons: (1) their longer period of benefit receipt and (2) our use of a shared concept of wealth rather than an individual concept.19 Women in every cohort and every marital status subgroup have considerably more years of benefit receipt than men. For example, for married or divorced women, the median number of years of benefit receipt is 26, compared with only 17 for married men and 14 for divorced men in the 2003 cohort. The never-married receive the lowest SSW in each gender group, and the ever-married have roughly similar amounts.
Sex | Total | Never married |
Married | Widowed | Divorced |
---|---|---|---|---|---|
1988 | |||||
All participants | 105,624 | 70,101 | 105,077 | 125,149 | 91,966 |
Women | 120,660 | 78,347 | 123,792 | 128,049 | 107,271 |
Men | 87,018 | 73,288 | 92,312 | 107,626 | 75,255 |
1993 | |||||
All participants | 122,258 | 80,195 | 122,107 | 134,931 | 123,063 |
Women | 146,224 | 95,595 | 149,838 | 142,041 | 147,314 |
Men | 99,454 | 60,214 | 101,214 | 112,293 | 96,411 |
1998 | |||||
All participants | 147,003 | 115,961 | 145,385 | 167,753 | 153,148 |
Women | 175,531 | 127,556 | 177,171 | 177,615 | 177,847 |
Men | 121,767 | 108,973 | 121,625 | 129,375 | 121,798 |
2003 | |||||
All participants | 164,961 | 119,263 | 163,742 | 188,613 | 171,960 |
Women | 195,822 | 133,549 | 196,891 | 203,534 | 198,649 |
Men | 136,700 | 105,137 | 137,700 | 152,987 | 137,421 |
SOURCE: Authors' calculations using data from Modeling Income in the Near Term (MINT3). |
For each sex and marital status subgroup, median SSW is greater for the 2003 cohort than for the 1988 cohort. The relative change in the amount of SSW between the 1988 cohort and the 2003 cohort is similar for men and women, increasing by 57 percent and 62 percent. The patterns of relative increase are somewhat different among marital status subgroups.
The ANNPAYOUT amounts given in Table 3b show that not-married women receive smaller amounts than not-married men across the four cohorts. ANNPAYOUT spreads SSW over potential benefit years. Because median potential benefit years are greater for women than men, the ratio of female to male median amounts is considerably lower for ANNPAYOUT than for SSW. For the never-married, the ratio of women's ANNPAYOUT to men's is less than one because women have lower taxable earnings. For the divorced, the reason that women's ANNPAYOUT is less than men's is probably that these divorced women typically have lower earnings and these divorced men have higher earnings than their ex-spouses. Thus divorced men tend to receive higher benefits based on their own higher earnings, and divorced women tend to receive lower benefits (divorced spouse benefits or worker benefits based on their own lower earnings). For the married, median ANNPAYOUT is slightly larger for women than for men.
Sex | Total | Never married |
Married | Widowed | Divorced |
---|---|---|---|---|---|
1988 | |||||
All participants | 5,580 | 5,183 | 5,533 | 6,228 | 5,411 |
Women | 5,646 | 4,841 | 5,645 | 6,087 | 4,919 |
Men | 5,513 | 5,663 | 5,428 | 6,918 | 6,570 |
1993 | |||||
All participants | 6,338 | 4,837 | 6,281 | 6,948 | 6,564 |
Women | 6,425 | 4,614 | 6,476 | 6,854 | 6,049 |
Men | 6,232 | 5,019 | 6,116 | 7,568 | 7,526 |
1998 | |||||
All participants | 7,487 | 6,755 | 7,414 | 8,130 | 7,808 |
Women | 7,520 | 5,769 | 7,567 | 7,955 | 7,256 |
Men | 7,446 | 7,792 | 7,265 | 9,406 | 8,926 |
2003 | |||||
All participants | 8,292 | 6,964 | 8,231 | 8,761 | 8,771 |
Women | 8,316 | 6,625 | 8,396 | 8,663 | 8,137 |
Men | 8,249 | 7,254 | 8,074 | 9,521 | 10,039 |
SOURCE: Authors' calculations using data from Modeling Income in the Near Term (MINT3). |
In each of the four cohorts, never-married women receive the lowest ANNPAYOUT amounts, and women in other groups receive somewhat similar amounts. Among men, the widowed and divorced have substantially larger ANNPAYOUT amounts than men in the other two subgroups. Taxable earnings
For each sex and marital status subgroup, median real annualized payout is greater for the 2003 cohort than for the 1988 cohort. Overall, men's ANNPAYOUT amounts go up by 50 percent between the 1988 and 2003 cohorts, compared with 47 percent for women. For each marital status subgroup, the increases are rather similar for men and women.
Overall,
Sex | Total | Never married |
Married | Widowed | Divorced |
---|---|---|---|---|---|
1988 | |||||
All participants | 32.6 | 30.4 | 31.6 | 45.2 | 35.2 |
Women | 35.6 | 28.9 | 34.0 | 47.0 | 33.5 |
Men | 30.1 | 32.8 | 29.7 | 38.1 | 39.3 |
1993 | |||||
All participants | 33.9 | 35.9 | 32.7 | 46.5 | 36.2 |
Women | 37.0 | 34.9 | 35.5 | 47.8 | 35.2 |
Men | 31.1 | 36.7 | 30.2 | 39.3 | 37.8 |
1998 | |||||
All participants | 32.2 | 31.3 | 31.2 | 42.9 | 34.6 |
Women | 34.2 | 30.5 | 33.4 | 43.1 | 34.0 |
Men | 29.9 | 31.9 | 29.0 | 41.0 | 35.4 |
2003 | |||||
All participants | 31.0 | 31.4 | 29.9 | 42.5 | 33.0 |
Women | 32.9 | 30.0 | 32.0 | 43.6 | 32.0 |
Men | 29.0 | 32.6 | 28.1 | 38.8 | 34.2 |
SOURCE: Authors' calculations using data from Modeling Income in the Near Term (MINT3). |
For seven of the eight subgroups,
Values for
Sex | Total | Never married |
Married | Widowed | Divorced |
---|---|---|---|---|---|
1988 | |||||
All participants | 28.8 | 28.6 | 27.4 | 40.8 | 32.2 |
Women | 31.4 | 26.8 | 29.5 | 41.6 | 31.0 |
Men | 26.4 | 29.7 | 25.6 | 36.0 | 35.7 |
1993 | |||||
All participants | 30.6 | 32.6 | 29.1 | 42.7 | 34.1 |
Women | 33.7 | 30.5 | 31.8 | 44.3 | 33.0 |
Men | 28.1 | 33.9 | 27.3 | 36.9 | 35.6 |
1998 | |||||
All participants | 30.0 | 30.2 | 28.9 | 39.8 | 32.6 |
Women | 32.2 | 30.3 | 31.2 | 40.5 | 32.4 |
Men | 28.0 | 30.1 | 27.1 | 37.7 | 33.1 |
2003 | |||||
All participants | 29.5 | 29.3 | 28.4 | 41.2 | 32.1 |
Women | 31.3 | 29.2 | 30.3 | 41.7 | 31.0 |
Men | 27.6 | 29.8 | 26.7 | 37.9 | 33.1 |
SOURCE: Authors' calculations using data from Modeling Income in the Near Term (MINT3). |
Three measures that help explain the findings for the four benefit measures (SSW, ANNPAYOUT,
Sex | Total | Never married |
Married | Widowed | Divorced |
---|---|---|---|---|---|
1988 | |||||
All participants | 16,836 | 15,235 | 17,697 | 13,216 | 14,214 |
Women | 15,323 | 14,141 | 16,562 | 12,894 | 13,157 |
Men | 18,629 | 15,392 | 18,937 | 16,411 | 16,817 |
1993 | |||||
All participants | 18,454 | 11,581 | 19,431 | 14,226 | 16,960 |
Women | 16,831 | 10,219 | 18,144 | 13,463 | 16,012 |
Men | 20,065 | 14,032 | 20,460 | 19,631 | 18,858 |
1998 | |||||
All participants | 22,915 | 18,461 | 23,745 | 18,666 | 21,589 |
Women | 21,349 | 13,836 | 22,560 | 17,818 | 19,907 |
Men | 24,859 | 22,910 | 24,936 | 22,853 | 24,858 |
2003 | |||||
All participants | 26,198 | 18,375 | 27,473 | 19,787 | 25,164 |
Women | 24,207 | 16,595 | 25,977 | 18,395 | 23,407 |
Men | 28,681 | 21,517 | 29,228 | 24,574 | 28,005 |
SOURCE: Authors' calculations using data from Modeling Income in the Near Term (MINT3). |
Sex | Total | Never married |
Married | Widowed | Divorced |
---|---|---|---|---|---|
1988 | |||||
All participants | 19,093 | 16,625 | 20,204 | 15,044 | 15,324 |
Women | 17,552 | 14,984 | 19,029 | 14,404 | 14,092 |
Men | 21,003 | 15,861 | 21,365 | 18,111 | 17,659 |
1993 | |||||
All participants | 20,276 | 12,566 | 21,580 | 15,084 | 18,577 |
Women | 18,593 | 10,998 | 20,351 | 14,334 | 17,427 |
Men | 22,143 | 15,758 | 22,557 | 21,727 | 20,134 |
1998 | |||||
All participants | 24,437 | 18,739 | 25,452 | 19,649 | 23,029 |
Women | 22,834 | 13,836 | 24,130 | 18,930 | 20,852 |
Men | 26,363 | 23,282 | 26,577 | 23,897 | 25,976 |
2003 | |||||
All participants | 27,237 | 19,373 | 28,736 | 20,823 | 25,825 |
Women | 25,283 | 16,839 | 27,036 | 19,077 | 24,408 |
Men | 29,714 | 22,365 | 30,386 | 25,070 | 29,234 |
SOURCE: Authors' calculations using data from Modeling Income in the Near Term (MINT3). |
Sex | Total | Never married |
Married | Widowed | Divorced |
---|---|---|---|---|---|
1988 | |||||
All participants | 22 | 19 | 22 | 23 | 18 |
Women | 24 | 24 | 25 | 23 | 22 |
Men | 17 | 16 | 19 | 18 | 13 |
1993 | |||||
All participants | 22 | 18 | 22 | 23 | 20 |
Women | 25 | 27 | 26 | 24 | 25 |
Men | 17 | 14 | 18 | 14 | 15 |
1998 | |||||
All participants | 22 | 20 | 22 | 24 | 22 |
Women | 26 | 24 | 26 | 25 | 26 |
Men | 18 | 18 | 18 | 14 | 15 |
2003 | |||||
All participants | 22 | 19 | 22 | 24 | 22 |
Women | 27 | 24 | 26 | 26 | 28 |
Men | 18 | 15 | 19 | 19 | 16 |
SOURCE: Authors' calculations using data from Modeling Income in the Near Term (MINT3). |
Information for the four cohorts by quintiles of less-censored earnings is shown in Table 4 and Charts 1 and 2.
Quintile | 1988 | 1993 | 1998 | 2003 |
---|---|---|---|---|
Social Security wealth (SSW, in dollars) | ||||
Bottom | 47,538 | 57,888 | 69,173 | 76,649 |
Second | 95,893 | 109,787 | 130,169 | 146,100 |
Third | 110,430 | 137,730 | 161,425 | 186,338 |
Fourth | 131,188 | 152,326 | 193,914 | 215,300 |
Top | 146,868 | 170,219 | 220,816 | 251,363 |
Annualized payout (ANNPAYOUT, in dollars) | ||||
Bottom | 2,897 | 3,552 | 4,226 | 4,382 |
Second | 4,824 | 5,561 | 6,508 | 7,066 |
Third | 5,655 | 6,429 | 7,640 | 8,448 |
Fourth | 6,283 | 7,004 | 8,340 | 9,437 |
Top | 6,703 | 7,697 | 9,266 | 10,646 |
Taxable earnings replacement rate |
||||
Bottom | 57.7 | 60.5 | 58.0 | 56.8 |
Second | 40.5 | 42.5 | 39.4 | 39.6 |
Third | 33.1 | 34.8 | 33.0 | 32.0 |
Fourth | 29.4 | 29.9 | 28.4 | 27.0 |
Top | 25.0 | 25.3 | 23.9 | 22.7 |
Less-censored earnings replacement rate |
||||
Bottom | 55.4 | 57.3 | 54.4 | 52.8 |
Second | 37.7 | 40.1 | 37.4 | 38.1 |
Third | 29.9 | 31.9 | 31.2 | 30.6 |
Fourth | 25.2 | 26.9 | 26.3 | 26.0 |
Top | 20.8 | 22.0 | 21.9 | 21.6 |
Taxable earnings |
||||
Bottom | 4,940 | 5,852 | 7,113 | 7,342 |
Second | 11,863 | 13,161 | 16,579 | 17,821 |
Third | 17,077 | 18,693 | 23,087 | 26,381 |
Fourth | 21,440 | 23,594 | 29,408 | 34,832 |
Top | 26,733 | 29,931 | 37,982 | 46,258 |
Less-censored earnings |
||||
Bottom | 5,114 | 6,091 | 7,711 | 7,923 |
Second | 12,953 | 14,008 | 17,321 | 18,512 |
Third | 19,111 | 20,282 | 24,465 | 27,241 |
Fourth | 24,685 | 26,121 | 31,619 | 36,332 |
Top | 31,599 | 33,975 | 41,062 | 48,299 |
Potential benefit years | ||||
Bottom | 20 | 19 | 20 | 21 |
Second | 21 | 21 | 21 | 21 |
Third | 22 | 23 | 22 | 23 |
Fourth | 21 | 22 | 24 | 23 |
Top | 23 | 23 | 24 | 24 |
SOURCE: Authors' calculations using data from Modeling Income in the Near Term (MINT3). | ||||
NOTE: Money amounts are in January 1, 2002, dollars. |
As expected, the median annualized payout increases markedly as we move to higher earnings quintiles (Chart 1). For the 2003 cohort, for example, the top quintile's ANNPAYOUT is about 2.4 times that of the bottom quintile.
For each less-censored earnings quintile, median annualized payout increases as we move from earlier to later cohorts. Each quintile has about the same 1993–1998 relative increase in ANNPAYOUT (from 17 percent to 20 percent). In addition, each of the top four quintiles has about the same 1988–1993 relative ANNPAYOUT increase (from 11 percent to 15 percent). However, the 1998–2003 relative increases rise consistently from the lowest to the highest quintile (from 4 percent to 15 percent). The pattern of differences in 1998–2003 earnings growth by quintiles is the main cause of the pattern of differences in ANNPAYOUT growth by quintiles. The 1998–2003 relative increases in median taxable earnings and in median less-censored earnings rise consistently from the lowest to the highest quintile (from 3 percent to between 18 percent and 22 percent).
Again as expected, the median less-censored earnings replacement rate
For each quintile,
We looked at two additional benefit measures; size-adjusted measures and measures for the population not receiving Disability Insurance benefits.
All the results presented and discussed in the previous sections are for shared benefits (and shared earnings). For each year, the person's shared benefit equals the per capita benefit of the unit (married couple or unmarried person) to which the person belongs.
The results presented briefly here and in some detail in Appendix D are for size-adjusted benefits (and size-adjusted earnings). The general view in the economic literature is that there are considerable economies of scale with respect to unit size in the production of economic well-being. Thus, a given per capita or shared benefit contributes more to the economic well-being of a married person than to that of an unmarried person. The adjustment of benefits for differences in unit size attempts to achieve a situation in which a given size-adjusted benefit contributes the same to the well-being of a married person as to that of an unmarried person. The adjusted benefit measures (ANNPAYOUT and SSW) are cardinal measures of the number of utility units contributed by Social Security benefits to the economic well-being of a person.20
We adjust benefits and earnings for differences in unit size using an equivalence scale implicit in the official U.S. poverty thresholds. Our equivalence scale is for two types of units—unmarried persons and married couples. The equivalence scale values are 1.00 and 1.26 for these two types of units. This equivalence scale incorporates considerable economies of scale. For each year a person is married, the person's adjusted benefit equals the couple's benefit divided by 1.26. For each year a person is not married, the person's adjusted benefit equals the person's benefit. This equivalence scale is also used to compute size-adjusted earnings.
An important effect of size adjustment is to very substantially increase SSW and ANNPAYOUT of the married subgroups relative to those of the other sex and marital status subgroups. Size adjustment increases median ANNPAYOUT of married men and married women by about 55 percent and 40 percent. The increases for the six not-married subgroups are much smaller (1 percent and 11 percent).21 The effects on median SSW are similar. The percentage increases in SSW and ANNPAYOUT are larger for married men than for married women because these men spend a larger proportion of their benefit receipt years married than do these women, primarily because about three-fourths of women outlive their husbands.
The main effect of size adjustment on replacement rates is to decrease the replacement rates of the widowed and divorced relative to those of the never-married and married. For the 2003 cohort, for example, size adjustment decreases the median less-censored replacement rate of the widowed and divorced by 29 percent and 19 percent. The changes are quite small for the never-married and married (+6 percent and −2 percent). The effects of size adjustment on replacement rates result from effects on both the numerator and denominator of these rates. For the widowed and divorced, size adjustment produces small percentage changes in the numerator (ANNPAYOUT) but quite sizable percentage increases in the denominator
Size adjustment also reduces somewhat the measured progressivity of
The results for shared benefits and earnings presented and discussed in previous sections are for all Social Security program participants. Some of these near-retiree participants received Disability Insurance benefits, and some had spouses who received them. It is useful to look at results for just the near-retirees who did not receive DI benefits and did not have spouses who received such benefits, referred to here as
This paper has analyzed the Social Security benefits of near-retirees—people turning age 61 in years 1988 through 2007. It has examined Social Security wealth, annualized benefit payouts, and replacement rates for average career earnings for all program participants, sex and marital status subgroups, and career earnings quintile subgroups.
A few of the paper's key results are as follows:
The analysis of the Social Security benefits of near-retirees could be extended in various ways. We plan to extend our analysis to cover additional subgroups including racial and ethnic subgroups and benefit-type subgroups (retired workers, spouses, and so on). There is considerable interest in how various racial and ethnic subgroups fare under Social Security. The analysis of benefit-type subgroups should not only provide useful information about these subgroups but should also help us better understand our results for sex and marital status subgroups.
One could also extend the analysis to cover younger cohorts. This extension could quantify the effects of the second round of scheduled increases in the full retirement age on replacement rates and other benefit measures. Note, however, that younger cohorts could be markedly affected by possible future changes in benefit law provisions. Although our paper's replacement rates measure the extent to which average career earnings are replaced by benefits, one could examine late-life earnings replacement rates, that is, replacement rates that measure the extent to which earnings for the last few years before benefit receipt are replaced by benefits.
This appendix gives some additional information about how the MINT3 model completes the historical data via imputations and how it makes projections beyond the time range of the historical information.
The MINT3 model imputes missing administrative records and estimates less-censored earnings.
Missing Administrative Records. Administrative records are imputed using a hot-deck procedure for the 8 percent of persons with no exact match. Age, sex, marital status, race, education, and earnings from the Survey of Income and Program Participation are among the variables used in the hot-decking. In addition, administrative records are imputed for the former spouses of SIPP sample members using a hot-deck procedure. The administrative records contain information on mortality, disability, benefit history, and earnings history.
Less-Censored Earnings. For the 1951–1977 period, the administrative earnings records (Summary Earnings Records) contain information on the quarter in which a person's earnings reached the legislated taxable maximum. This information, along with wage information from several Current Population Surveys (CPS), is used to impute earnings that are above the 1951–1977 legislated taxable maximums but do not exceed the less-censored taxable maximums.
For the 1978–1989 period, the Summary Earnings Records do not contain information on the quarter in which an individual's earnings reached the legislated taxable maximums. For this period, CPS wage information is used to impute earnings that are above the legislated taxable maximums but do not exceed the less-censored taxable maximums.
Because of the order of the processes in the MINT3 projection model, there is minimal interaction between demographic and economic events. Death is determined first for all persons, then marital dynamics, and then earnings.
Mortality. Mortality before age 65 is projected using a hot-deck procedure that selects older workers' earnings to splice to the end of incomplete earnings records of younger workers. This splicing procedure gives projections of mortality and disability as well as projections of earnings. Age, sex, and education are among the variables used in this splicing procedure. Mortality before age 65 is adjusted to match the mortality assumptions in the 2002 Trustees Report.
Mortality after age 65 is projected using a regression model that includes age, sex, marital status, education, and race among its predictor variables. Post-age 65 mortality rates are slightly lower than those assumed in the Trustees Report.
Marital Dynamics. Changes in marital status are projected using hazard models that include age, sex, marital history, education, race, and ethnicity among their predictor variables.
Demographic characteristics (age, race and ethnicity, education, disability history, and so on) of each projected spouse were imputed based on the characteristics of the sample person. Then a hot-deck imputation procedure was used to impute earnings and other variables to the projected spouses; age, marital history, education, and race and ethnicity are among the variables used in the hot-decking.
Earnings. For nondisabled workers, earnings after age 50 are projected using a series of regression equations. Age, sex, and education are predictors in all of the regressions. Marital status, race and ethnicity, earnings, health, and spouse characteristics are predictor variables in some of the regressions.
Earnings of disabled workers are projected using the hot-deck splicing procedure described above in the discussion of mortality.
Benefit Acceptance Dates. Several regression equations are used to project benefit entitlement dates. The predictor variables include age, sex, marital status, education, race and ethnicity, earnings, and spouse characteristics.
Immigration. Persons are projected to enter the MINT sample by means of immigration in the years after the end of the SIPP interview. A hot-deck imputation procedure is used to select postinterview immigrants from a donor pool of immigrants from the SIPP sample. The imputation is done so as to approximate estimated control totals of immigrants by time period, sex, age at immigration, and source region. The records of the selected donors are then updated to the year of projected immigration.
The paper looks at 20 single-year cohorts, that is, persons reaching age 61 in the 20 years from 1988 through 2007. Each single-year cohort consists of all persons who reach age 61 during that year and are members of the noninstitutionalized population at the end of that year. In our tables, we combine these single-year cohorts into four groups of five single-year cohorts each: 1988–1992 (1988 cohort or cohort 1), 1993–1997 (1993 cohort or cohort 2), 1998–2002 (1998 cohort or cohort 3), and 2003–2007 (2003 cohort or cohort 4).
The initial MINT sample is from the 1990–1993 panels of the Survey of Income and Program Participation. The SIPP panels are samples of the U.S. noninstitutionalized population. The first interviews of the 1990, 1991, 1992, and 1993 panels took place early in those years. The MINT data file includes only persons who were interviewed in the SIPP in those years or were projected to immigrate to the United States after 1993.23 The MINT data file contains actual or projected information on the dates of death, institutionalization, and emigration of these persons.
The MINT population excludes persons reaching age 61 in 1988–1992 who were not eligible for SIPP interviews because after reaching age 61 they left the U.S. noninstitutionalized population because they died, were institutionalized, or emigrated before the first SIPP interviews in 1990–1993. This attrition affects the size and composition of cohort 1, but does not affect the other three cohorts. Without appropriate corrections for attrition bias, the benefit and earnings measures (mean SSW, median ANNPAYOUT, and so on) for cohort 1 are not totally comparable with those of the other three cohorts.
We attempt to remove the effects of this attrition on the benefit and earnings measures for cohort 1 by using attrition factors and thus making the measures comparable with the measures for the other three cohorts. We compute attrition factors using data for the cohort 2 of near-retirees.
First, we determine which persons are hypothetical attriters. If the SIPP interviews had started 5 years later, that is, in 1995–1998 instead of in 1990–1993, some of the members of cohort 2 would have died, entered institutions, or emigrated before the start of the hypothetical interviews; these are the hypothetical attriters. About 1.6 percent of cohort 2 is lost via hypothetical attrition, overwhelmingly because they died.
Next, for each benefit or earnings measure (Mi), we determine an attrition factor for all participants and for each sex and marital status subgroup and for each quintile group as follows:
In effect, we assume that the relative effect of actual attrition on Mi,1 is the same as the relative effect of hypothetical attrition on Mi,2. This assumption ignores the fact that mortality was slightly higher for cohort 1 than for cohort 2.
The corrected measures for all participants should be very reliable. The cohort 1 and cohort 2 samples are large, and the loss from hypothetical attrition is only 1.6 percent. For the shared measures shown in Table 1 in the text, the adjustment factors are between 0.985 and 1.000. For median SSW the factor is 0.986. For ANNPAYOUT,
The corrected measures for quintiles shown in Table 4 and Charts 1 and 2 in the main body of this paper should also be quite reliable. The quintile samples are large. The adjustment factors are 0.970–0.993 for median shared SSW. For the other five shared measures, the factors for medians are 0.989–1.000. For Mi,2,f, quintiles are determined for the full population; for Mi,2,p, quintiles are determined for the population after hypothetical attrition.
The attrition corrections for some of the sex and marital status subgroups in Tables
To examine how intercohort growth in
Average
Participant characteristics |
Cohort a | Percentage change | |||||||
---|---|---|---|---|---|---|---|---|---|
1988 | 1993 | 1998 | 2003 | 1988– 1993 |
1993– 1998 |
1998– 2003 |
1993– 2003 |
1988– 2003 |
|
Average relative shared less-censored earnings |
|||||||||
All participants | |||||||||
Median | 0.675 | 0.696 | 0.730 | 0.754 | 3 | 5 | 3 | 8 | 12 |
Mean | 0.667 | 0.696 | 0.740 | 0.775 | 4 | 6 | 5 | 11 | 16 |
At ages |
|||||||||
Median | 0.553 | 0.575 | 0.647 | 0.675 | 4 | 13 | 4 | 17 | 22 |
Mean | 0.550 | 0.571 | 0.634 | 0.661 | 4 | 10 | 4 | 15 | 20 |
At ages |
|||||||||
Median | 0.733 | 0.782 | 0.841 | 0.844 | 7 | 8 | 0 | 15 | 15 |
Mean | 0.703 | 0.755 | 0.811 | 0.846 | 7 | 7 | 4 | 15 | 20 |
At ages |
|||||||||
Median | 0.810 | 0.816 | 0.828 | 0.876 | 1 | 1 | 6 | 2 | 8 |
Mean | 0.781 | 0.814 | 0.848 | 0.897 | 4 | 4 | 6 | 9 | 15 |
At ages |
|||||||||
Median | 0.566 | 0.576 | 0.607 | 0.619 | 2 | 5 | 2 | 7 | 9 |
Mean | 0.636 | 0.650 | 0.680 | 0.716 | 2 | 5 | 5 | 7 | 13 |
Average relative individual less-censored earnings |
|||||||||
All participants | |||||||||
Median | 0.482 | 0.530 | 0.591 | 0.637 | 10 | 12 | 8 | 23 | 32 |
Mean | 0.663 | 0.694 | 0.735 | 0.778 | 5 | 6 | 6 | 11 | 17 |
Participants with positive earnings | |||||||||
Median | 0.513 | 0.553 | 0.609 | 0.648 | 8 | 10 | 6 | 19 | 26 |
Mean | 0.684 | 0.711 | 0.748 | 0.785 | 4 | 5 | 5 | 9 | 15 |
SOURCE: Authors' calculations using data from Modeling Income in the Near Term (MINT3). | |||||||||
a. Persons aged |
Is the growth of shared less-censored earnings relative to the SSA average annual wage confined to certain stages of the work life? To address this question, we created average relative earnings measures for four stages of the work life—ages
All four of these additional measures of relative earnings increase as we move from earlier to later cohorts of near-retirees. The 1988–1998 intercohort increase for median
Do average individual less-censored earnings also grow at a faster percentage rate than the SSA average annual wage? To address this question, we created an additional average relative earnings measure
Table
Average
Average
Most of the results presented and discussed in the main text are for shared benefits and shared earnings. For each year a person is married, the person's shared benefit equals the couple's benefits divided by 2; for each year a person is not married, the person's shared benefit equals the person's benefit. That is, the person's shared benefit equals the per capita benefit of the unit (married couple or unmarried person) to which the person belongs.
The results presented and discussed here are for size-adjusted benefits and size-adjusted earnings. The general view in the economics literature is that there are considerable economies of scale with respect to unit size in the production of economic well-being. Thus, a given per capita or shared benefit contributes much more to the economic well-being of a married person than to that of an unmarried person. The adjustment of benefits for differences in unit size attempts to achieve a situation in which a given size-adjusted benefit contributes the same to the well-being of a married person as to that of an unmarried person. The adjusted benefit measures—annualized payout (ANNPAYOUT) and Social Security wealth (SSW) are cardinal measures of the number of utility units contributed by Social Security benefits to a person's economic well-being.29
Various equivalence scales have been used to adjust unit incomes for differences in unit size.30 We adjust benefits using an equivalence scale implicit in the official U.S. poverty thresholds (Proctor and Dalaker 2003). Our equivalence scale is for two types of units—unmarried persons and married couples. We use the equivalence scale derived from the poverty thresholds for unrelated individuals aged 65 or older and two-person units with householder aged 65 or older and with no related child under age 18. The equivalence scale values are 1.00 and 1.26 for these two types of units.31 Thus, the equivalence scale incorporates large economies of scale.
For each year a person is married, the person's adjusted benefit equals the couple's benefits divided by 1.26.32 For each year a person is not married, the person's adjusted benefit equals the person's benefit. This equivalence scale is also used to compute size-adjusted earnings. The size-adjusted benefit measures (Social Security wealth, annualized payout, and earnings replacement rates) differ from the shared benefit measures discussed in the main body of this paper only because they use adjusted annual benefits and earnings rather than shared annual benefits and earnings.
We will show that the most important effect of size adjustment is to very substantially increase Social Security wealth and annualized payouts of the married subgroups relative to those of the other marital status subgroups.
Social Security Wealth and Annualized Payout. The intercohort percentage increases in average adjusted SSW are the same as or slightly smaller than those for average shared SSW (Tables 1 and
Measure | Cohort a | Percentage change | |||||||
---|---|---|---|---|---|---|---|---|---|
1988 | 1993 | 1998 | 2003 | 1988– 1993 |
1993– 1998 |
1998– 2003 |
1993– 2003 |
1988– 2003 |
|
Social Security wealth (SSW, dollars) | |||||||||
Median | 142,660 | 165,441 | 198,953 | 219,459 | 16 | 20 | 10 | 33 | 54 |
Mean | 145,462 | 168,614 | 204,664 | 230,932 | 16 | 21 | 13 | 37 | 59 |
Annualized payout (ANNPAYOUT, dollars) | |||||||||
Median | 7,588 | 8,595 | 10,109 | 11,113 | 13 | 18 | 10 | 29 | 46 |
Mean | 7,331 | 8,291 | 9,740 | 10,744 | 13 | 17 | 10 | 30 | 47 |
Median replacement rate (percent) | |||||||||
Taxable earnings |
30.4 | 31.6 | 30.1 | 29.0 | 4 | -5 | -4 | -8 | -5 |
Less-censored earnings |
26.6 | 28.4 | 28.0 | 27.6 | 7 | -1 | -1 | -3 | 4 |
Average wage-indexed earnings (dollars) | |||||||||
Taxable |
|||||||||
Median | 25,318 | 27,310 | 33,637 | 38,094 | 8 | 23 | 13 | 39 | 50 |
Mean | 24,426 | 27,017 | 33,711 | 38,695 | 11 | 25 | 15 | 43 | 58 |
Less-censored |
|||||||||
Median | 28,521 | 30,109 | 36,384 | 40,610 | 6 | 21 | 12 | 35 | 42 |
Mean | 28,162 | 30,190 | 35,843 | 39,500 | 7 | 19 | 10 | 31 | 40 |
Median potential benefit years | 21 | 21 | 22 | 22 | 1 | 2 | 2 | 4 | 5 |
SOURCE: Authors' calculations using data from Modeling Income in the Near Term (MINT3). | |||||||||
NOTE: Money amounts are in January 1, 2002, dollars. | |||||||||
a. Persons aged |
Replacement Rates for Taxable and Less-Censored Earnings. The intercohort percentage changes in median adjusted
The intercohort decreases in median adjusted
Information for the four cohorts by sex and marital status subgroups is shown in Tables
Social Security Wealth. The main effect of size adjustment is to increase median SSW of the married relative to that of the other marital status subgroups. For the three youngest cohorts, size adjustment increases SSW of married women by 42 percent to 46 percent and SSW of married men by 52 percent to 53 percent (Table
Sex | Total | Never married |
Married | Widowed | Divorced |
---|---|---|---|---|---|
1988 | |||||
All participants | 1.35 | 1.03 | 1.49 | 0.99 | 1.05 |
Women | 1.20 | 1.03 | 1.44 | 1.01 | 1.01 |
Men | 1.49 | 0.96 | 1.52 | 1.07 | 1.00 |
1993 | |||||
All participants | 1.35 | 1.02 | 1.50 | 1.01 | 1.07 |
Women | 1.27 | 1.00 | 1.42 | 1.00 | 1.02 |
Men | 1.44 | 1.04 | 1.52 | 1.11 | 1.07 |
1998 | |||||
All participants | 1.35 | 1.01 | 1.49 | 1.04 | 1.02 |
Women | 1.27 | 1.00 | 1.45 | 1.02 | 1.02 |
Men | 1.44 | 1.02 | 1.52 | 1.22 | 1.04 |
2003 | |||||
All participants | 1.33 | 1.01 | 1.49 | 1.05 | 1.04 |
Women | 1.25 | 1.00 | 1.43 | 1.00 | 1.01 |
Men | 1.42 | 1.00 | 1.53 | 1.11 | 1.05 |
SOURCE: Authors' calculations using data from Modeling Income in the Near Term (MINT3). |
For a person who is married in all of their benefit receipt years, size adjustment increases SSW by 58.73 percent.33 The percentage increases are larger for married men than for married women because these men spend a larger proportion of their benefit receipt years married than do these women. This is primarily because about three-fourths of women outlive their husbands. The increases in SSW of the not-married are due to their marriages that begin after the start of the year they reach age 62.
For shared SSW, we find that in each gender group the ever-married have roughly similar amounts of median SSW. For size-adjusted SSW, we get a rather different result: in each gender group, the married have substantially higher SSW than do the widowed and divorced.
The other results for size-adjusted SSW are similar to those for shared SSW (see Findings by Sex and Marital Status in the main body of the paper).
Annualized Payout. The main effect of size adjustment is to increase median ANNPAYOUT of the married relative to those of the other marital status subgroups (Table
Sex | Total | Never married |
Married | Widowed | Divorced |
---|---|---|---|---|---|
1988 | |||||
All participants | 1.36 | 1.00 | 1.48 | 1.02 | 1.01 |
Women | 1.26 | 1.00 | 1.40 | 1.01 | 1.01 |
Men | 1.49 | 1.01 | 1.55 | 1.04 | 1.08 |
1993 | |||||
All participants | 1.36 | 1.01 | 1.48 | 1.02 | 1.03 |
Women | 1.25 | 1.00 | 1.40 | 1.01 | 1.01 |
Men | 1.47 | 1.11 | 1.55 | 1.08 | 1.07 |
1998 | |||||
All participants | 1.35 | 1.03 | 1.47 | 1.03 | 1.05 |
Women | 1.25 | 1.00 | 1.40 | 1.01 | 1.02 |
Men | 1.46 | 1.03 | 1.54 | 1.11 | 1.06 |
2003 | |||||
All participants | 1.34 | 1.01 | 1.48 | 1.05 | 1.02 |
Women | 1.26 | 1.03 | 1.41 | 1.03 | 1.01 |
Men | 1.43 | 1.02 | 1.54 | 1.07 | 1.04 |
SOURCE: Authors' calculations using data from Modeling Income in the Near Term (MINT3). |
For shared ANNPAYOUT, we get the following results:
For size-adjusted ANNPAYOUT, we get the following, rather different results:
The other results for size-adjusted ANNPAYOUT are generally similar to those for shared ANNPAYOUT (see Findings by Sex and Marital Status in the main body of the paper).
Taxable Earnings Replacement Rate. The main effect of size adjustment is to decrease
Sex | Total | Never married |
Married | Widowed | Divorced |
---|---|---|---|---|---|
1988 | |||||
All participants | 0.93 | 1.03 | 0.97 | 0.69 | 0.81 |
Women | 0.87 | 1.00 | 0.93 | 0.68 | 0.76 |
Men | 0.99 | 1.02 | 1.00 | 0.80 | 0.79 |
1993 | |||||
All participants | 0.93 | 1.03 | 0.97 | 0.72 | 0.80 |
Women | 0.88 | 1.00 | 0.93 | 0.71 | 0.77 |
Men | 0.99 | 1.02 | 1.01 | 0.80 | 0.83 |
1998 | |||||
All participants | 0.93 | 1.03 | 0.97 | 0.73 | 0.80 |
Women | 0.89 | 1.00 | 0.93 | 0.72 | 0.80 |
Men | 0.99 | 1.04 | 1.02 | 0.81 | 0.81 |
2003 | |||||
All participants | 0.94 | 1.04 | 0.97 | 0.77 | 0.81 |
Women | 0.89 | 1.06 | 0.93 | 0.72 | 0.81 |
Men | 0.99 | 1.02 | 1.01 | 0.78 | 0.83 |
SOURCE: Authors' calculations using data from Modeling Income in the Near Term (MINT3). |
The effects of size adjustment on
For shared
For size-adjusted
The intercohort changes in size-adjusted
Less-Censored Earnings Replacement Rate. The effects of size adjustment on
Sex | Total | Never married |
Married | Widowed | Divorced |
---|---|---|---|---|---|
1988 | |||||
All participants | 0.92 | 1.02 | 0.96 | 0.69 | 0.81 |
Women | 0.86 | 1.00 | 0.93 | 0.69 | 0.78 |
Men | 0.99 | 1.03 | 1.00 | 0.78 | 0.82 |
1993 | |||||
All participants | 0.93 | 1.04 | 0.97 | 0.72 | 0.79 |
Women | 0.86 | 1.00 | 0.92 | 0.70 | 0.78 |
Men | 0.99 | 1.04 | 1.01 | 0.79 | 0.83 |
1998 | |||||
All participants | 0.93 | 1.01 | 0.98 | 0.72 | 0.80 |
Women | 0.88 | 1.00 | 0.92 | 0.71 | 0.78 |
Men | 0.99 | 1.04 | 1.02 | 0.76 | 0.82 |
2003 | |||||
All participants | 0.94 | 1.06 | 0.98 | 0.71 | 0.81 |
Women | 0.89 | 1.03 | 0.94 | 0.71 | 0.80 |
Men | 0.99 | 1.09 | 1.02 | 0.74 | 0.82 |
SOURCE: Authors' calculations using data from Modeling Income in the Near Term (MINT3). |
For shared
For size-adjusted
The intercohort changes in size-adjusted
Related Measures. Two measures that help explain the findings for the four benefit measures (SSW, ANNPAYOUT,
Sex | Total | Never married |
Married | Widowed | Divorced |
---|---|---|---|---|---|
1988 | |||||
All participants | 1.50 | 1.00 | 1.54 | 1.46 | 1.32 |
Women | 1.50 | 1.00 | 1.56 | 1.49 | 1.33 |
Men | 1.49 | 1.00 | 1.52 | 1.38 | 1.33 |
1993 | |||||
All participants | 1.48 | 1.00 | 1.54 | 1.41 | 1.30 |
Women | 1.49 | 1.00 | 1.55 | 1.42 | 1.31 |
Men | 1.49 | 1.00 | 1.52 | 1.36 | 1.39 |
1998 | |||||
All participants | 1.47 | 1.00 | 1.53 | 1.43 | 1.32 |
Women | 1.47 | 1.00 | 1.55 | 1.45 | 1.34 |
Men | 1.46 | 1.00 | 1.52 | 1.47 | 1.28 |
2003 | |||||
All participants | 1.45 | 1.00 | 1.53 | 1.40 | 1.27 |
Women | 1.45 | 1.00 | 1.54 | 1.46 | 1.31 |
Men | 1.45 | 1.00 | 1.51 | 1.39 | 1.29 |
SOURCE: Authors' calculations using data from Modeling Income in the Near Term (MINT3). |
Sex | Total | Never married |
Married | Widowed | Divorced |
---|---|---|---|---|---|
1988 | |||||
All participants | 1.49 | 1.00 | 1.54 | 1.46 | 1.37 |
Women | 1.49 | 1.00 | 1.57 | 1.50 | 1.34 |
Men | 1.48 | 1.00 | 1.53 | 1.44 | 1.37 |
1993 | |||||
All participants | 1.49 | 1.00 | 1.54 | 1.44 | 1.30 |
Women | 1.48 | 1.00 | 1.56 | 1.44 | 1.33 |
Men | 1.48 | 1.00 | 1.53 | 1.41 | 1.32 |
1998 | |||||
All participants | 1.47 | 1.00 | 1.53 | 1.44 | 1.30 |
Women | 1.46 | 1.00 | 1.56 | 1.45 | 1.36 |
Men | 1.47 | 1.00 | 1.51 | 1.50 | 1.31 |
2003 | |||||
All participants | 1.45 | 1.00 | 1.53 | 1.39 | 1.29 |
Women | 1.45 | 1.00 | 1.55 | 1.45 | 1.30 |
Men | 1.46 | 1.00 | 1.51 | 1.42 | 1.26 |
SOURCE: Authors' calculations using data from Modeling Income in the Near Term (MINT3). |
Information for the four cohorts by quintiles of size-adjusted less-censored earnings
Quintile | 1988 | 1993 | 1998 | 2003 |
---|---|---|---|---|
Social Security wealth (SSW) | ||||
Bottom | 1.31 | 1.33 | 1.27 | 1.28 |
Second | 1.28 | 1.32 | 1.31 | 1.35 |
Third | 1.44 | 1.31 | 1.34 | 1.32 |
Fourth | 1.46 | 1.44 | 1.37 | 1.39 |
Top | 1.43 | 1.46 | 1.42 | 1.40 |
Annualized payout (ANNPAYOUT) | ||||
Bottom | 1.27 | 1.31 | 1.27 | 1.25 |
Second | 1.33 | 1.31 | 1.33 | 1.30 |
Third | 1.37 | 1.42 | 1.37 | 1.36 |
Fourth | 1.42 | 1.43 | 1.42 | 1.40 |
Top | 1.45 | 1.42 | 1.42 | 1.41 |
Taxable earnings replacement rate |
||||
Bottom | 0.90 | 0.89 | 0.90 | 0.91 |
Second | 0.90 | 0.89 | 0.92 | 0.92 |
Third | 0.93 | 0.93 | 0.93 | 0.93 |
Fourth | 0.94 | 0.95 | 0.95 | 0.96 |
Top | 0.98 | 0.97 | 0.97 | 0.97 |
Less-censored earnings replacement rate |
||||
Bottom | 0.89 | 0.90 | 0.90 | 0.94 |
Second | 0.90 | 0.89 | 0.92 | 0.92 |
Third | 0.92 | 0.92 | 0.94 | 0.94 |
Fourth | 0.95 | 0.95 | 0.96 | 0.95 |
Top | 0.97 | 0.97 | 0.97 | 0.97 |
Taxable earnings |
||||
Bottom | 1.43 | 1.44 | 1.44 | 1.36 |
Second | 1.49 | 1.45 | 1.45 | 1.44 |
Third | 1.50 | 1.49 | 1.47 | 1.46 |
Fourth | 1.52 | 1.50 | 1.48 | 1.47 |
Top | 1.47 | 1.48 | 1.48 | 1.45 |
Less-censored earnings |
||||
Bottom | 1.43 | 1.44 | 1.42 | 1.40 |
Second | 1.45 | 1.45 | 1.46 | 1.43 |
Third | 1.49 | 1.49 | 1.47 | 1.45 |
Fourth | 1.51 | 1.50 | 1.48 | 1.47 |
Top | 1.50 | 1.49 | 1.48 | 1.45 |
SOURCE: Authors' calculations using data from Modeling Income in the Near Term (MINT3). | ||||
NOTE: Numerators of ratios are by size-adjusted quintiles; denominators are by shared quintiles. |
The percentage increases in ANNPAYOUT due to size adjustment generally rise as we move from lower to higher quintiles. Size adjustment widens somewhat the relative spread between lower and higher quintiles. For the 2003 cohort, size adjustment increases the ratio of top-quintile ANNPAYOUT to bottom-quintile ANNPAYOUT from 2.43 to 2.86.
The results for shared ANNPAYOUT (see Findings by Earnings Quintiles in the main body of the paper) generally hold for size-adjusted ANNPAYOUT.
Size adjustment reduces median
The results for shared
The findings presented and discussed in the main text are for all Social Security program participants. Social Security program participants are persons with some shared earnings. Some of these participants received Disability Insurance (DI) benefits or had spouses who received them. It is useful to look at results for just the population not receiving DI benefits (referred to here as
The results presented and discussed here are for the
For the later three cohorts, the exclusion of DIB persons increases average SSW by 2 percent to 5 percent (Tables 1 and
Measure | Cohort a | Percentage change | |||||||
---|---|---|---|---|---|---|---|---|---|
1988 | 1993 | 1998 | 2003 | 1988– 1993 |
1993– 1998 |
1998– 2003 |
1993– 2003 |
1988– 2003 |
|
Social Security wealth (SSW, dollars) | |||||||||
Median | 105,944 | 125,932 | 154,305 | 169,430 | 19 | 23 | 10 | 35 | 60 |
Mean | 108,114 | 127,993 | 157,966 | 177,168 | 18 | 23 | 12 | 38 | 64 |
Annualized payout (ANNPAYOUT, dollars) | |||||||||
Median | 5,445 | 6,203 | 7,383 | 8,218 | 14 | 19 | 11 | 32 | 51 |
Mean | 5,159 | 5,868 | 7,001 | 7,816 | 14 | 19 | 12 | 33 | 52 |
Median replacement rate (percent) | |||||||||
Taxable earnings |
31.0 | 32.1 | 30.6 | 29.7 | 4 | -5 | -3 | -7 | -4 |
Less-censored earnings |
27.1 | 28.7 | 28.4 | 28.2 | 6 | -1 | -1 | -2 | 4 |
Average wage-indexed earnings (dollars) | |||||||||
Taxable |
|||||||||
Median | 17,435 | 19,240 | 23,988 | 27,413 | 10 | 25 | 14 | 42 | 57 |
Mean | 16,865 | 18,836 | 23,679 | 27,580 | 12 | 26 | 16 | 46 | 64 |
Less-censored |
|||||||||
Median | 19,772 | 21,247 | 25,690 | 28,585 | 7 | 21 | 11 | 35 | 45 |
Mean | 19,409 | 21,005 | 25,563 | 28,950 | 8 | 22 | 13 | 38 | 49 |
Mean potential benefit years | 21.75 | 22.22 | 22.86 | 23.01 | 2 | 3 | 1 | 4 | 6 |
SOURCE: Authors' calculations using data from Modeling Income in the Near Term (MINT3). | |||||||||
NOTE: Money amounts are in January 1, 2002, dollars. | |||||||||
a. Persons aged |
The exclusion of DIB persons decreases average ANNPAYOUT by 1 percent to 4 percent. For the three later cohorts, median ANNPAYOUT of DIB persons is 106 percent to 115 percent of that of
The exclusion of DIB persons decreases replacement rates by 4 percent to 6 percent. Both a decrease in median ANNPAYOUT (1 percent to 2 percent) and an increase in median average career earnings (4 percent to 5 percent) contribute to this decrease in replacement rates. For the three later cohorts, median replacement rates of DIB persons are 143 percent to 155 percent of those of
The effects of excluding DIB persons on the levels of median SSW and ANNPAYOUT are often rather small and do not show a consistent pattern of differences by sex and marital status subgroup (Tables
Sex | Total | Never married |
Married | Widowed | Divorced |
---|---|---|---|---|---|
1988 | |||||
All participants | 1.00 | 1.06 | 1.00 | 1.00 | 1.00 |
Women | 1.00 | 1.02 | 0.99 | 0.98 | 1.01 |
Men | 1.07 | 0.86 | 1.02 | 0.97 | 0.97 |
1993 | |||||
All participants | 1.03 | 1.09 | 1.02 | 1.04 | 1.09 |
Women | 1.01 | 0.95 | 1.00 | 1.00 | 1.02 |
Men | 1.06 | 1.13 | 1.05 | 1.02 | 1.06 |
1998 | |||||
All participants | 1.05 | 1.04 | 1.04 | 1.06 | 1.05 |
Women | 1.04 | 1.00 | 1.03 | 1.02 | 1.06 |
Men | 1.07 | 1.00 | 1.04 | 1.13 | 1.06 |
2003 | |||||
All participants | 1.03 | 1.03 | 1.02 | 1.05 | 1.05 |
Women | 1.03 | 1.04 | 1.03 | 1.02 | 1.03 |
Men | 1.03 | 1.09 | 1.03 | 1.01 | 1.04 |
SOURCE: Authors' calculations using data from Modeling Income in the Near Term (MINT3). |
Sex | Total | Never married |
Married | Widowed | Divorced |
---|---|---|---|---|---|
1988 | |||||
All participants | 0.98 | 0.94 | 0.98 | 0.98 | 0.94 |
Women | 0.97 | 0.99 | 0.98 | 0.99 | 0.97 |
Men | 0.98 | 0.96 | 0.98 | 0.99 | 0.98 |
1993 | |||||
All participants | 0.98 | 0.95 | 0.98 | 0.99 | 0.97 |
Women | 0.99 | 0.94 | 0.99 | 0.98 | 0.98 |
Men | 0.97 | 0.98 | 0.98 | 0.99 | 0.96 |
1998 | |||||
All participants | 0.99 | 0.96 | 0.99 | 0.99 | 0.98 |
Women | 0.99 | 0.96 | 0.99 | 0.99 | 0.99 |
Men | 0.98 | 0.98 | 0.98 | 0.95 | 0.98 |
2003 | |||||
All participants | 0.99 | 0.98 | 0.99 | 0.99 | 0.98 |
Women | 0.99 | 0.96 | 0.99 | 0.98 | 0.99 |
Men | 0.99 | 1.00 | 0.99 | 1.00 | 1.00 |
SOURCE: Authors' calculations using data from Modeling Income in the Near Term (MINT3). |
Sex | Total | Never married |
Married | Widowed | Divorced |
---|---|---|---|---|---|
1988 | |||||
All participants | 0.95 | 0.95 | 0.95 | 0.95 | 0.94 |
Women | 0.94 | 0.94 | 0.94 | 0.96 | 0.98 |
Men | 0.96 | 0.90 | 0.95 | 0.97 | 0.96 |
1993 | |||||
All participants | 0.95 | 0.85 | 0.94 | 0.96 | 0.94 |
Women | 0.94 | 0.85 | 0.95 | 0.97 | 0.96 |
Men | 0.95 | 0.83 | 0.96 | 0.95 | 0.95 |
1998 | |||||
All participants | 0.95 | 0.91 | 0.95 | 0.95 | 0.94 |
Women | 0.96 | 0.90 | 0.96 | 0.96 | 0.96 |
Men | 0.96 | 0.93 | 0.96 | 0.93 | 0.92 |
2003 | |||||
All participants | 0.96 | 0.90 | 0.96 | 0.96 | 0.94 |
Women | 0.96 | 0.92 | 0.96 | 0.96 | 0.94 |
Men | 0.96 | 0.87 | 0.96 | 0.96 | 0.94 |
SOURCE: Authors' calculations using data from Modeling Income in the Near Term (MINT3). |
Sex | Total | Never married |
Married | Widowed | Divorced |
---|---|---|---|---|---|
1988 | |||||
All participants | 0.94 | 0.94 | 0.95 | 0.96 | 0.95 |
Women | 0.94 | 0.94 | 0.93 | 0.97 | 0.97 |
Men | 0.95 | 0.91 | 0.95 | 0.94 | 0.90 |
1993 | |||||
All participants | 0.94 | 0.87 | 0.95 | 0.96 | 0.93 |
Women | 0.94 | 0.92 | 0.94 | 0.95 | 0.95 |
Men | 0.95 | 0.85 | 0.95 | 0.92 | 0.92 |
1998 | |||||
All participants | 0.95 | 0.92 | 0.95 | 0.96 | 0.94 |
Women | 0.95 | 0.88 | 0.95 | 0.96 | 0.95 |
Men | 0.95 | 0.93 | 0.95 | 0.92 | 0.96 |
2003 | |||||
All participants | 0.96 | 0.94 | 0.96 | 0.96 | 0.93 |
Women | 0.96 | 0.92 | 0.96 | 0.97 | 0.93 |
Men | 0.96 | 0.94 | 0.96 | 0.93 | 0.94 |
SOURCE: Authors' calculations using data from Modeling Income in the Near Term (MINT3). |
Sex | Total | Never married |
Married | Widowed | Divorced |
---|---|---|---|---|---|
1988 | |||||
All participants | 1.04 | 1.04 | 1.04 | 1.02 | 1.05 |
Women | 1.04 | 1.05 | 1.04 | 1.00 | 0.99 |
Men | 1.04 | 0.96 | 1.03 | 1.12 | 1.09 |
1993 | |||||
All participants | 1.04 | 1.20 | 1.04 | 1.01 | 1.06 |
Women | 1.04 | 1.03 | 1.04 | 1.00 | 1.01 |
Men | 1.05 | 1.13 | 1.04 | 1.04 | 1.04 |
1998 | |||||
All participants | 1.05 | 1.10 | 1.05 | 1.01 | 1.07 |
Women | 1.05 | 1.10 | 1.05 | 1.01 | 1.04 |
Men | 1.05 | 1.01 | 1.05 | 1.13 | 1.06 |
2003 | |||||
All participants | 1.05 | 1.12 | 1.05 | 1.04 | 1.07 |
Women | 1.05 | 1.05 | 1.04 | 1.05 | 1.04 |
Men | 1.05 | 1.09 | 1.04 | 1.02 | 1.08 |
SOURCE: Authors' calculations using data from Modeling Income in the Near Term (MINT3). |
Sex | Total | Never married |
Married | Widowed | Divorced |
---|---|---|---|---|---|
1988 | |||||
All participants | 1.04 | 0.96 | 1.04 | 1.00 | 1.04 |
Women | 1.03 | 1.10 | 1.04 | 0.99 | 1.04 |
Men | 1.04 | 0.99 | 1.04 | 1.05 | 1.14 |
1993 | |||||
All participants | 1.09 | 1.26 | 1.04 | 1.01 | 1.07 |
Women | 1.10 | 1.00 | 1.04 | 1.01 | 1.10 |
Men | 1.18 | 1.13 | 1.04 | 1.03 | 1.30 |
1998 | |||||
All participants | 1.05 | 1.10 | 1.04 | 1.10 | 1.07 |
Women | 1.05 | 1.10 | 1.06 | 1.01 | 1.07 |
Men | 1.05 | 1.04 | 1.05 | 1.09 | 1.06 |
2003 | |||||
All participants | 1.05 | 1.06 | 1.04 | 1.06 | 1.06 |
Women | 1.05 | 1.03 | 1.05 | 1.08 | 1.05 |
Men | 1.05 | 1.07 | 1.04 | 1.04 | 1.07 |
SOURCE: Authors' calculations using data from Modeling Income in the Near Term (MINT3). |
The exclusion of DIB persons reduces median ANNPAYOUT of the bottom quintiles by 6 percent to 10 percent and ANNPAYOUTs of the next-to-bottom quintiles by 2 percent to 5 percent (Table
Quintile | 1988 | 1993 | 1998 | 2003 |
---|---|---|---|---|
Social Security wealth (SSW) | ||||
Bottom | 0.96 | 0.97 | 1.00 | 1.02 |
Second | 0.99 | 1.02 | 1.03 | 1.03 |
Third | 1.06 | 1.05 | 1.06 | 1.05 |
Fourth | 1.02 | 1.01 | 1.04 | 1.02 |
Top | 1.00 | 1.02 | 1.02 | 1.01 |
Annualized payout (ANNPAYOUT) | ||||
Bottom | 0.90 | 0.92 | 0.92 | 0.94 |
Second | 0.95 | 0.97 | 0.98 | 0.98 |
Third | 0.98 | 0.99 | 0.99 | 1.00 |
Fourth | 0.98 | 0.99 | 1.00 | 1.00 |
Top | 1.00 | 1.00 | 1.00 | 1.00 |
Taxable earnings replacement rate |
||||
Bottom | 0.90 | 0.90 | 0.91 | 0.92 |
Second | 0.92 | 0.93 | 0.94 | 0.93 |
Third | 0.96 | 0.94 | 0.95 | 0.96 |
Fourth | 0.97 | 0.97 | 0.98 | 0.98 |
Top | 0.98 | 0.98 | 0.98 | 0.98 |
Less-censored earnings replacement rate |
||||
Bottom | 0.89 | 0.91 | 0.89 | 0.93 |
Second | 0.92 | 0.92 | 0.95 | 0.93 |
Third | 0.94 | 0.94 | 0.95 | 0.97 |
Fourth | 0.95 | 0.96 | 0.97 | 0.97 |
Top | 0.99 | 0.98 | 0.97 | 0.99 |
Taxable earnings |
||||
Bottom | 0.97 | 0.99 | 0.98 | 1.00 |
Second | 1.04 | 1.04 | 1.04 | 1.05 |
Third | 1.04 | 1.05 | 1.05 | 1.05 |
Fourth | 1.02 | 1.03 | 1.03 | 1.03 |
Top | 1.02 | 1.02 | 1.02 | 1.02 |
Less-censored earnings |
||||
Bottom | 0.99 | 1.00 | 1.00 | 1.02 |
Second | 1.04 | 1.05 | 1.04 | 1.05 |
Third | 1.04 | 1.05 | 1.05 | 1.05 |
Fourth | 1.02 | 1.03 | 1.03 | 1.03 |
Top | 1.02 | 1.02 | 1.02 | 1.02 |
SOURCE: Authors' calculations using data from Modeling Income in the Near Term (MINT3). | ||||
NOTE: Numerators of ratios are by |
The exclusion of DIB persons reduces median