Modeling SSI financial eligibility and simulating the effect of policy options.

Abstract

This article simulates eligibility for Supplemental Security Income (SSI) among the elderly, analyzes factors affecting participation, and looks at the potential effects of various options to modify financial eligibility standards for the federal SSI program. We find that in the estimated noninstitutional elderly population of 30.2 million in the United States in 1991, approximately 2 million individuals aged 65 or older were eligible for SSI (a 6.6 percent rate of eligibility). Our overall estimate of the rate of participation among eligible elderly is approximately 63 percent, suggesting that more than a third of those who are eligible do not participate in the program. The results of our analysis of factors affecting participation among the eligible elderly show that expected SSI benefits and a number of demographic and socioeconomic variables are associated with the probability of participation. We also simulate the effects of various policy options on the poverty rate, poverty gap, annual program cost, the number of participants, and the average estimated benefits among participants. The simulations consider the potential effects of five policy alternatives: Increase the general income exclusion (GIE) from $20 to $80. Increase the earned income exclusion (EIE) from $65 to $260. Increase the federal benefit rate (FBR) by $50 for individuals and $75 for couples and eliminate the GIE. Increase the asset threshold to $3,000 for individuals and $4,500 for couples. Increase the asset threshold to $6,000 for individuals and $9,000 for couples. Using 1991 microdata from the Survey of Income and Program Participation (SIPP) matched to Social Security Administration administrative records and making adjustments reflecting aggregate program statistics, we present the results of our simulations for December 1999. The results show substantial variation in the simulated effects of the five policy alternatives along the various outcome dimensions considered. The simulated effects on the poverty gap of the elderly population range from a 7.9 percent reduction ("Increase the GIE from $20 to $80") to a 0.1 percent reduction ("Increase the EIE from $65 to $260"). All simulated interventions are expected to increase the rate of SSI participation among the elderly from a high of 20.3 percent ("Increase the GIE from $20 to $80") to a low of 0.5 percent ("Increase the EIE from $65 to $260"). We also find that the interventions that have greater estimated effects in terms of increased participation and reduced poverty tend to cost more. At the high end, we estimate that increasing the GIE from $20 to $80 could raise annual federal SSI cash benefit outlays by about 46 percent, compared with only 0.9 percent for increasing the EIE from $65 to $260. Similar to the EIE intervention, raising the resource thresholds by 50 percent would reduce the overall poverty gap of the elderly by only 0.2 percent, would increase SSI participation only modestly (by 1.3 percent), but would entail slightly higher program costs (by 1.4 percent). Increasing the asset threshold by 200 percent would have higher estimated effects on all three outcomes, but it would still be associated with relatively low increases in both costs and benefits. Finally, the simulated effects on the three key outcomes of increasing the FBR by $50 for individuals and $75 for couples, combined with eliminating the GIE, are relatively large but are clearly less substantial than increasing the GIE from $20 to $80. This work relies on data from the SIPP matched to administrative data on federal SSI benefits that provide a more accurate picture of SSI participation than has been feasible for previous studies. We simulate eligibility for federal SSI benefits by applying the program rules to detailed information on the characteristics of individuals and couples based on the rich array of demographic and socioeconomic data in the SIPP, particularly the comprehensive information SIPP provides on assets and monthly income. A probit model is estimated to analyze factors affecting participation among the eligible elderly. Finally, we conduct the policy simulations using altered program rules represented by the policy alternatives and predicted participation probabilities to estimate outcomes under simulated program rules. We compare those simulated outcomes to observed outcomes under current program rules. The results of our simulations are conditional on the characteristics of participants and eligibles in 1991, but they also reflect aggregate adjustments capturing substantial changes in overall participation and program benefit levels between 1991 and 1999.

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