Using data for couples to project the distributional effects of changes in Social Security policy.
Under Social Security program rules, the aged receive Social Security benefits either as retired workers, spouses, divorced spouses, or widow(er)s. Retired-worker benefits are paid to workers who have 40 quarters of coverage over their lives. Auxiliary benefits are paid to spouses, divorced spouses, and widow(er)s of retired workers. Spouse benefits are computed using the earnings history of the current spouse for individuals who are married when they apply for benefits. Divorced spouse and widow(er) benefits are computed using the earnings history of the ex-spouse or deceased spouse with the highest PIA. A large number of retired women are entitled to auxiliary benefits. Some women receive only auxiliary benefits, while the majority of women have their retired-worker benefit supplemented by auxiliary benefits. Because the level of Social Security benefits can reflect the relative lifetime earnings of both spouses, as a couple, using individual data to estimate Social Security benefits will tend to underestimate actual benefits, particularly for women. However, detailed data for couples are often difficult to obtain. There is currently no known single data source that includes both marital and earnings history information. As a result, many researchers resort to estimating Social Security benefits using individual data or aggregate data, such as the average earnings of men and women. The Social Security Administration's Office of Research, Evaluation, and Statistics, with substantial assistance from the Brookings Institution, the Urban Institute, and the RAND Corporation, is developing a model that overcomes this problem by using the marital and earnings histories of both marital partners to estimate Social Security benefits. The Modeling Income in the Near Term (MINT) model projects retirement income (Social Security benefits, pension income, asset income, and earnings of working beneficiaries) from 1997 through 2031 for current and future Social Security beneficiaries using a unique data source--the Survey of Income and Program Participation (SIPP)--matched to Social Security Administration records. Using MINT data, this article establishes the importance of using data for couples rather than individuals by examining the impact of changing Social Security benefits to reflect 40 years of lifetime earnings rather than the 35 years required under current law. We compare the effect of this policy change on married women by estimating their benefits with data for couples and with individual data. Results indicate that: Using individual data overestimates the projected reduction in retirement benefits brought about by the policy change and makes the effects on women look more severe than they actually are. Because older birth cohorts are more likely than younger cohorts to receive auxiliary benefits based on their husbands' average lifetime earnings, the bias created by using individual data is projected to be much larger for older cohorts than for younger cohorts. This article emphasizes the importance of using data for couples to estimate Social Security benefits, particularly for women. Although our focus is on married women, using data for couples is just as important for calculating the retirement benefits of divorced and widowed individuals. For individuals who are divorced or widowed at retirement, their Social Security benefits are based on their own earnings history, as well as the earnings histories of each of their previous spouses.
Butrica
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BA
Iams
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HM
Sandell
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D000367:Age Factors; D000368:Aged; D015982:Bias; D015331:Cohort Studies; D003627:Data Interpretation, Statistical; D004243:Divorce / Q000706:statistics & numerical data; D005260:Female; D005544:Forecasting; D006801:Humans; D008297:Male; D008393:Marriage / Q000706:statistics & numerical data*; D018803:Models, Economic; D009936:Organizational Innovation; D016134:Organizational Policy; D015203:Reproducibility of Results; D012179:Retirement / Q000191:economics*; D012737:Sex Factors; D012943:Social Security / Q000458:organization & administration*; D014481:United States; D017805:Widowhood / Q000706:statistics & numerical data