Evidence of Increasing Differential Mortality: A Comparison of the HRS and SIPP

Bosworth, Barry; Zhang, Kan; House, Hovey; Ave, Commonwealth

doi:10.2139/ssrn.2625792

Cited by 7 publications

(11 citation statements)

References 14 publications

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“…Contrasting rich versus poor cohorts reveals that, as expected, wealth (panel a), and health (panel c) depletion is faster for poor agents, such that low-wealth individuals enter 24 the depletion, and accelerating regions more rapidly (panel d). Moreover, exposure to death risk is higher for the poor (panel e), consistent with stylized facts (Bosworth et al, 2016;Bosworth and Zhang, 2015), except at very old age where attrition effects imply that only the very healthy poor agents remain alive, and the rich and poor exposures to mortality are converging. Put differently, our simulations indicate that agents entering the last period of life optimally select a short expected lifespan, and allocations that are consistent with optimal closing down, i.e.…”

Section: Simulation Analysissupporting

confidence: 79%

“…It follows that unless very wealthy, and very unhealthy, the bulk of the population would be located in the health and wealth depletion regions. Besides being consistent with expectations regarding agents near the end of life, the results also rationalize better longevity for the rich (Bosworth et 22 al., 2016;Bosworth and Zhang, 2015). Indeed, very rich and sick agents who are not in in the health depletion region will select expected increase in the health capital as long as their wealth maintains them out of the D H region.…”

Section: Induced Parametersmentioning

confidence: 99%

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Closing down the shop: Optimal health and wealth dynamics near the end of life

2019

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The observed health decline near the end of life coincides with less curative (e.g. hospital stay, doctor visits), and more comfort (e.g. nursing home) care, which accelerate both the fall in wealth, and the timing of death. We investigate whether these dynamics jointly result from a closing down the shop decision i.e. a depletion of the health stock is optimally selected (and eventually accelerated), leading to states characterized by indifference between life, and death. Towards that aim, we expand, structurally estimate, and simulate a life cycle model of financial, and health expenses with endogenous mortality exposure (Hugonnier et al., 2013).Under economically plausible, and statistically verified conditions, we find that, unless sufficiently rich and healthy, agents will optimally select expected depletion of their health capital, and associated increase in death likelihood. Moreover, we identify a wealth and health locus below which agents accelerate their health depletion. Importantly, wealth is also expected to decline for all, such that all surviving agents eventually enter the closing down phase.JEL classification: D91, D14, I12 1 optimality of these joint end-of-life health and wealth dynamics. More precisely, we look at conditions under which health, and wealth depletion is optimally selected to fall towards a region associated with very high mortality risk, and indifference between life and death. Put differently, agents optimally choose to let go, i.e. to close down the shop. The conditions under which they do are associated with lower wealth, such that richer individuals delay the health depletion. However, we show that under reasonable assumptions, wealth depletion is also optimally selected, such that agents eventually enter the closing-down phase. We further identify threshold effects whereby the depletion of the health capital is initially slowed down, before being accelerated.This paper has two main contributions: theoretical and empirical. First, we build upon a rich life cycle model developed in Hugonnier, Pelgrin and St-Amour (2013) in order to identify optimal depletion, and acceleration. This model encompasses a health investment setup with endogenous exposure to death risk, and exogenous sickness shocks that further depreciate the health capital. In addition to investing in their health, agents can buy actuarially fair insurance against health shocks, and save in risky, and risk-less assets. Agents also earn income, part of which is fixed (e.g. social security), and part which is health-dependent, reflecting their physical ability to work. Finally, preferences are characterized by subsistence consumption, as well as by generalized attitudes towards the various sources of risk (mortality, morbidity, and financial), and towards intertemporal substitution. Importantly, they also guarantee strict ex-ante preference for life, so that agents have no proclivity for death over life.We rely on the closed-form solutions of that model in order to characterize the optimal dynamics for health, and ...

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Section: Simulation Analysissupporting

confidence: 79%

Section: Induced Parametersmentioning

confidence: 99%

Closing down the shop: Optimal health and wealth dynamics near the end of life

2019

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“…The third type of policy option attempts to mitigate changes in differential mortality by SES. This option builds on the idea that solely adjusting benefits to average life expectancy would not account for the fact that persons with high SES have exhibited the largest longevity gains (Bosworth & Zhang, 2015). As noted, greater life expectancy associates with characteristics of higher SES, and research shows that SES differentials in life expectancy of retirees have been increasing since World War II.…”

Section: Methodsmentioning

confidence: 99%

“…Further, declining old-age mortality in the United States has not been uniform. Growing evidence suggests that mortality risks by SES have been widening over time, measured by income, education, and occupation (Bosworth & Burke, 2014 ; Bosworth & Zhang, 2015; Bound, Geronimus, Rodriguez, & Waidmann, 2014; Cristia, 2009; Goldman & Orszag, 2014; Masters, Hummer, & Powers, 2012; Montez, Hummer, Hayward, Woo, & Rogers, 2011; Olshansky et al, 2012; Preston, Stokes, Mehta, & Cao, 2014; Waldron, 2007, 2013). This leads to the policy concern that changing differentials in old-age mortality are making the Social Security system increasingly less generous to low-income individuals on a lifetime basis (Goldman & Orszag, 2014).…”

Section: Literature Reviewmentioning

confidence: 99%

The Distributional Impact of Social Security Policy Options

et al. 2016

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Using microsimulation, we estimate the effects of three policy proposals that would alter Social Security's eligibility rules or benefit structure to reflect changes in women's labor force activity, marital patterns, and differential mortality among the aged. First, we estimate a set of options related to the duration of marriage required to receive divorced spouse and survivor benefits. Second, we estimate the effects of an earnings sharing proposal with survivor benefits, in which benefits are based entirely on earned benefits with spouses sharing their earnings during years of marriage. Third, we estimate the effects of adjusting benefits to reflect the increasing differential life expectancy by lifetime earnings. The results advance our understanding of the distributional effects of these alternative policy options on projected benefits and retirement income, including poverty and supplemental poverty status, of divorced and widowed women aged 60 or older in 2030.

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“…However, official demographic projections usually do not provide any disaggregation by socioeconomic sub-groups, and this aspect represents a major drawback in the context of ageing and retirement planning for two main reasons. First, health status and life expectancy have a strong socioeconomic gradient (Dowd et al, 2011;Mackenbach & Valverde, 2018;Majer, Nusselder, Mackenbach, & Kunst, 2011;Office for National Statistics, 2012;Stringhini et al, 2017), even in old age (Enroth, Raitanen, Hervonen, & Jylhä, 2013;Hoffmann, 2008Hoffmann, , 2011Zarulli, Domantas, & Jdanov, 2012), the future evolution of which is highly debated (Bosworth & Zhang, 2015;Currie & Schwandt, 2016). The transparency and soundness of the hypotheses that support any population projection would increase considerably if they were disaggregated by socioeconomic sub-groups.…”

Section: Introductionmentioning

confidence: 99%

Disaggregation of official demographic projections in sub-groups by education level: the neglected “composition effect” in the future path of life expectancy

Ginebri

Lallo

2021

Genus

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We developed an innovative method to break down official population forecasts by educational level. The mortality rates of the high education group and low education group were projected using an iterative procedure, whose starting point was the life tables by education level for Italy, based on the year 2012. We provide a set of different scenarios on the convergence/divergence of the mortality differential between the high and low education groups. In each scenario, the demographic size and the life expectancy of the two sub-groups were projected annually over the period 2018–2065. We compared the life expectancy paths in the whole population and in the sub-groups. We found that in all of our projections, population life expectancy converges to the life expectancy of the high education group. We call this feature of our outcomes the “composition effect”, and we show how highly persistent it is, even in scenarios where the mortality differential between social groups is assumed to decrease over time. In a midway scenario, where the mortality differential is assumed to follow an intermediate path between complete disappearance in year 2065 and stability at the 2012 level, and in all the scenarios with a milder convergence hypothesis, our “composition effect” prevails over the effect of convergence for men and women. For instance, assuming stability in the mortality differential, we estimated a life expectancy increase at age 65 of 2.9 and 2.6 years for men, and 3.2 and 3.1 for women, in the low and high education groups, respectively, over the whole projection period. Over the same period, Italian official projections estimate an increase of 3.7 years in life expectancy at age 65 for the whole population. Our results have relevant implications for retirement and ageing policies, in particular for those European countries that have linked statutory retirement age to variations in population life expectancies. In all the scenarios where the composition effect is not offset by a strong convergence of mortality differentials, we show that the statutory retirement age increases faster than the group-specific life expectancies, and this finding implies that the expected time spent in retirement will shrink for the whole population. This potential future outcome seems to be an unintended consequence of the indexation rule.

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Evidence of Increasing Differential Mortality: A Comparison of the HRS and SIPP

Cited by 7 publications

References 14 publications

Closing down the shop: Optimal health and wealth dynamics near the end of life

Closing down the shop: Optimal health and wealth dynamics near the end of life

The Distributional Impact of Social Security Policy Options

Disaggregation of official demographic projections in sub-groups by education level: the neglected “composition effect” in the future path of life expectancy

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