Social Security Bulletin, Vol. 69, No. 1
Earnings sharing is an alternate method of calculating Social Security retirement benefits whereby earnings are assumed to be shared by married couples. This article presents a microsimulation analysis to estimate the impact of three earnings sharing proposals on the aged population of married, divorced, and widowed men and women in 2030. The impact of earnings sharing differs by marital status and sex, as measured by the percentage change in benefits and by the percentage of beneficiaries with increased and reduced benefits.
This article examines the distribution of Social Security benefits among recent cohorts of near-retirees, by (1) race and ethnicity, (2) nativity, and (3) disability status. Actual earnings history data help produce more accurate measures of benefits. The authors find that substantial differences in earnings levels and/or mortality levels among these subgroups interact with Social Security program provisions to produce sizable differences in values of benefit measures, such as Social Security wealth and earnings replacement rates.
Provided here are the absolute and relative poverty status of 2002 elderly Supplemental Security Income (SSI) recipients. Official poverty estimates are generated from the Current Population Survey's Annual Social and Economic Supplement (CPS/ASEC). The poverty study presented here differs from previous studies in that it is based on CPS/ASEC income and weight records conditionally adjusted by matching Social Security administrative data. This effort improves the coverage of SSI receipt and the accuracy of SSI estimates. The adjusted CPS/administrative matched data reveal lower 2002 poverty rates among elderly persons (with and without SSI payments) than those generated from the unadjusted CPS/ASEC data.
This article discusses the advantages and limitations of using administrative data for research, examines how linking administrative data to survey results can be used to evaluate and improve survey design, and discusses research studies and SSA statistical products and services that are based on administrative data.