SAVING MOTIVES AFTER RETIREMENT - DESCRIPTION (provided by applicant): Most analyses of the elderly's saving behavior use versions of the life cycle model that cannot replicate two key facts in the data: first, some households keep large amounts of assets even when very old; and second, people with high lifetime income save at a higher rate than those with low lifetime income. The objective of this project is to construct a richer version of the life cycle model that can reconcile both of these observations, estimate the parameters of the model from the Assets and Health Dynamics of the Oldest Old (AHEAD) dataset, and use the model to evaluate policy reforms such as abolishing the estate tax or changing Social Security benefits. Within this proposed model, several savings motives coexist: households save both to self-insure against uncertain longevity and medical expenses, and to leave bequests. The model contains several other important features. Uncertain rates of return affect both expected and realized asset accumulation. The model accounts for social insurance programs such as Supplemental Security Income and Medicaid. Poor and rich people have different life expectancies, and household survival dynamics are explicitly modeled. The model's parameters will be estimated from the AHEAD dataset, using the method of simulated moments. The model will be required to match separate age-asset profiles at different levels of lifetime income, forcing it to replicate observed differences between high and low-income households. Once the model has been estimated, it will be used to assess empirically the relative importance of its competing features, and to perform a variety of policy experiments. Project Narrative: The goal of this project is to construct and estimate a rich model of post- retirement saving that better describes the saving patterns of the elderly. Within our proposed model, elderly households would face uncertain longevity and out-of-pocket medical expenses, but would also receive financial protection from social insurance programs such as Medicaid. Modeling all of these features will allow us to study how medical concerns affect the saving of the elderly, and to analyze the savings impact of various medical policy proposals.
