Incorporating Insurance Rate Estimates and Differential Mortality into Net Marginal Social Security Tax Rate Calculations
Brian S. Armour and M. Melinda Pitts
Working Paper 2002-29
This paper extends the literature on net marginal tax rates created by the Social Security program by including variations in both the probability of being eligible to receive benefits and income-related life expectancy. The previous literature has found that women incur a lower net marginal tax rate because they have longer life expectancies. The results presented in this paper indicate that including variations in eligibility for benefits partially reverses this result by increasing net marginal Social Security tax rates for older women. In addition, the existing literature has shown that low-income households pay lower net marginal tax rates because the benefit formula is progressive. Including variations in life expectancy reduces, but does not eliminate, this result. This implies that differential mortality increases the net marginal Social Security tax rates incurred by low-income households. These results are important from a policy standpoint given the gender differences in poverty among the population over age sixty-five and the current debate on the future of the Social Security system.
JEL classification: H2, J26, I30
Keywords: Social Security, poverty, tax rates
The authors gratefully acknowledge Jim Alm, Robert Clark, and Rosemary Cunningham. They also thank seminar participants at Agnes Scott College for helpful comments. The views expressed here are the authors’ and not necessarily those of the Federal Reserve Bank of Atlanta or the Federal Reserve System. Any remaining errors are the authors’ responsibility.
Please address questions regarding content to Brian S. Armour, Kerr L.White Institute, 315 W. Ponce de Leon Avenue, Suite 321, Decatur, Georgia 30030, firstname.lastname@example.org, or M. Melinda Pitts, Research Department, Federal Reserve Bank of Atlanta, 1000 Peachtree Street, N.E., Atlanta, Georgia 30309-4470, 404-498-7009, email@example.com.