Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Abstract This paper constructs a rich model of saving for retired single people. Our framework allows for bequest motives and heterogeneity in medical expenses and life expectancies. We estimate the model using AHEAD data and the method of simulated moments. The data show that out-of-pocket medical expenses rise quickly with both age and permanent income. For many elderly people the risk of living long and requiring expensive medical care is a more important driver of old age saving than the desire to leave bequests. Social insurance programs such as Medicaid rationalize the low asset holdings of the poorest. These government programs, however, also benefit the rich because they insure them against their worst nightmares about their * An older and less complete version of this paper was previously circulated under the title "Differential Mortality, Uncertain Medical Expenses, and the Saving of Elderly Singles". We thank for helpful comments and suggestions Terms of use: Documents in EconStor may

Using data from the Health and Retirement Survey and the Assets and Health Dynamics of the Oldest Old survey, we estimate the stochastic process that determines both the distribution and dynamics of health care costs. We find that the data generating process for log health costs is well represented as the sum of a white noise process and a highly persistent AR(1) process. We also find that the innovations to this process can be modelled with a normal distribution that has been adjusted to capture the risk of catastrophic health care costs. Simulating this model, we find that in any given year 0.1% of households receive a health cost shock with a present value of at least $125,000.

A popular way to account for unobserved heterogeneity is to assume that the data are drawn from a finite mixture distribution. A barrier to using finite mixture models is that parameters that could previously be estimated in stages must now be estimated jointly: using mixture distributions destroys any additive separability of the log-likelihood function. We show, however, that an extension of the EM algorithm reintroduces additive separability, thus allowing one to estimate parameters sequentially during each maximization step. In establishing this result, we develop a broad class of estimators for mixture models. Returning to the likelihood problem, we show that, relative to full information maximum likelihood, our sequential estimator can generate large computational savings with little loss of efficiency.

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Abstract This paper constructs a rich model of saving for retired single people. Our framework allows for bequest motives and heterogeneity in medical expenses and life expectancies. We estimate the model using AHEAD data and the method of simulated moments. The data show that out-of-pocket medical expenses rise quickly with both age and permanent income. For many elderly people the risk of living long and requiring expensive medical care is a more important driver of old age saving than the desire to leave bequests. Social insurance programs such as Medicaid rationalize the low asset holdings of the poorest. These government programs, however, also benefit the rich because they insure them against their worst nightmares about their * An older and less complete version of this paper was previously circulated under the title "Differential Mortality, Uncertain Medical Expenses, and the Saving of Elderly Singles". We thank for helpful comments and suggestions Terms of use: Documents in EconStor may

The program was funded through a grant from the Social Security Administration (SSA). Each grant awarded was up to $25,000. In addition to submitting a paper, successful applicants also present their results to SSA in Washington, DC.

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People have heterogenous life expectancies: women live longer than men, rich people live longer than poor people, and healthy people live longer than sick people. People are also subject to heterogenous out-of-pocket medical expense risk. We construct a rich structural model of saving behavior for retired single households that accounts for this heterogeneity, and we estimate the model using AHEAD data and the method of simulated moments. We find that the risk of living long and facing high medical expenses goes a long way toward explaining the elderly's savings decisions. Specifically, medical expenses that rise quickly with both age and permanent income can explain why the elderly singles, and especially the richest ones, run down their assets so slowly. We also find that social insurance has a big impact on the elderly's savings.

Many elderly households benefit from Medicaid, a means-tested, public health insurance program. Despite the increasing importance of Medicaid in the presence of an aging population and rising medical costs, very little is known about how Medicaid payments are distributed among the elderly and how the elderly value these payments. Which elderly households receive Medicaid transfers? How redistributive are these transfers and the taxes needed to finance them? What is the insurance value of these transfers? Is Medicaid of about the right size? How much would people lose if it were cut? These are important questions to answer before reforming the programs currently in place. In this paper we seek to fill this gap.We focus on single retirees, who comprise about 50 percent of people aged 70 or older and 70 percent of households aged 70 or older. We document new facts on Medicaid recipiency in the Assets and Health Dynamics Among the Oldest Old (AHEAD) data and show that, while the recipiency rate in the bottom income quintile is around 70 percent throughout retirement, the recipiency rate of higher-income