Mariacristina De Nardi

We use k-means clustering, a machine learning technique, and Health and Retirement Study data to identify health types during middle and old age.

Medicaid is a government programme that also provides health insurance to the elderly who have few assets and either low income or catastrophic health care expenses. We ask how the Medicaid rules map into the reality of Medicaid recipiency, and we ask what other observable characteristics are important to determine who ends up on Medicaid.

The authors use detailed health care data for the period 2009–11 from nine countries to measure the composition and magnitude of medical spending in the three years before death.

Who receives medicaid in old age? Rules and reality

We use data from the Medicare Current Beneficiary Survey (MCBS) to document the medical spending of Americans aged 65 and older.

The old age provisions of the Medicaid program were designed to insure retirees against medical expenses. We estimate a structural model of savings and medical spending and use it to compute the distribution of lifetime Medicaid transfers and Medicaid valuations across currently single retirees.

More work is needed to distinguish precautionary saving motives from other motives, such as the desire to leave bequests. In this paper, progress toward disentangling these motivations has been made by matching other features of the data, such as public and private insurance choices.

This paper constructs a rich model of saving for retired single people.

We find that the differences in life expectancy related to observable factors such as income, gender, and health have large effects on savings.