Policy Implications for Sources of Increasing Differential Mortality among the Aged by Socioeconomic Status, by Bosworth, Burtless, and Zhang Hilary Waldron, SSA, Office of Research, Evaluation, and Statistics (ORES) The comments and views presented are those of the author and do not necessarily represent the views of the Social Security Administration.

Summary Important and useful contribution to the literature Results consistent with other empirical studies: widening of differentials, multiple causes of death, differentials remain after controlling for behaviors Overall, unable to explain causes of widening differentials

Policy Application: Progressivity studies; sometimes imply progressivity in the distribution of benefits is a program objective But… “…it is to be expected that some people from higher income groups will come to financial grief and dependence in old age.” Committee on Economic Security “Some redistribution of income undoubtedly is involved in all social security programs. As I see it, however, this is only one of its results, not its principle objective.” - Edwin Witte (1959), Executive Director, 1935 Committee on Economic Security “The fact that OASDI is compulsory has no connection with whether or not it is insurance. The essence of insurance is broad pooling of the risks involved. OASDI, as a social insurance program, provides such pooling.”-Robert Meyers (1993), Chief Actuary for SSA from “Social Security is not a program of forced savings…nor is it a welfare program designed simply to relieve poverty…Social Security has been from its inception a program of wage insurance…Redistribution is not a feature unique to welfare. All group insurance redistributes.”-Nancy Altman (2013)

Empirical caveat to mortality differential studies Mortality studies are looking at average mortality by various SES subgroups Committee on Economic Security is suggesting we should also see differences in mortality risk within SES groups, because all workers are subject to hazards and vicissitudes Variation within SES groups would be consistent with a group insurance design that pools risk broadly

Variation in risk within groups Correlation between age of claiming and risk of death held, even after controlling for lifetime earnings, education, race, and marital status (the earlier the age of claim, the higher the risk of death). Men in the top quartile of earnings distribution claiming at age 62 had higher mortality risk than men with lower earnings claiming later. Future research?: Is there variation in the reliance on Social Security within SES subgroup? Source: Waldron (2004)

Policy Implications—Proposal to index EEA and FRA to increases in average longevity Longevity indexing often proposed as a way to stabilize OASDI financing (FRA increase = benefit reduction) But… Can we estimate the distributional effects of longevity indexing if causes of widening are unknown? – Distributional estimate must include a projection of mortality differentials (we can only fully observe deaths for already retired birth cohorts, i.e. age 85+) – Proposal might index for up to the next 75-years, or beyond – Uncertainty about causes of widening means no theoretical basis for a life expectancy projection by SES and high sensitivity to projection assumptions Which means… – Uncertainty about distributional impacts of longevity indexing proposals for policy makers and the public

Uncertainty about projecting life-expectancy differentials Source: Fig. 3 and 4 are an excerpt of Baker and Rosnick (2010), CEPR 5.1 years difference 10.7 years difference

Can policy proposals be targeted to reflect changing differentials? Examples – Benefit Reductions: Disproportionately reduce benefits for high earners, and/or protect low earners from reductions – Revenue Increases: Raise the OASDI tax max (charge high earners more for increased longevity) Typically proposed as way to adjust for disproportionate earnings growth at upper earnings distribution/eroding OASDI tax base, rather than a response to differential To hit the target, men and women both: – Need same correlation between their own AIME and their SES (but Bosworth, Burtless, Zhang use household earnings) – Need roughly same life expectancy at a given SES level

Can the benefit formula be adjusted to compensate for widening mortality? Example: Introduce new bend point at the unisex median and reduce benefits above the median Benefit reductions would be equivalent to 70% of male and 30% of female earners Source: Waldron 2012, Social Security Bulletin Only 6 percent of men are at or below bottom bend point Almost 50 percent of men are at or above top bend point

Source: Waldron 2013, Social Security Bulletin

Can the tax max be adjusted to reflect widening differentials? OASDI tax max is closer to the longest lived males than the top bend point of the benefit formula, but very few women are at the tax max. – Could indirectly charge married women with high household earnings for their longevity through the tax on their husband’s earnings. – May overcharge unmarried men over the tax max who might have higher mortality risk than some lower earning women, but who have no survivor entitled on their record. – Targeting survivor benefits charges women (98.5% widow(er) benefits paid to women), but reduces longevity insurance for those workers.