We document the growth in higher education costs and tuition over the past 50 years. To explain these trends, we develop a general equilibrium model with skill- and sector-biased technical change. Finding the model’s parameters through a combination of estimation and calibration, we show that it can explain the rise in college costs between 1961 and 2009, along with the increase in college attainment and the change in the relative earnings of college graduates. The model predicts that if college costs had ceased to grow after 1961, enrollment in 2010 would have been 3%–6% higher.

This paper provides an empirical analysis of the effects of employer-provided health insurance, Medicare, and Social Security on retirement behavior. Using data from the Health and Retirement Study, we estimate a dynamic programming model of retirement that accounts for both saving and uncertain medical expenses. Our results suggest that Medicare is important for understanding retirement behavior, and that uncertainty and saving are both important for understanding the labor supply responses to Medicare. Half the value placed by a typical worker on his employer-provided health insurance is the value of reduced medical expense risk. Raising the Medicare eligibility age from 65 to 67 leads individuals to work an additional 0.074 years over ages 60–69. In comparison, eliminating 2 years worth of Social Security benefits increases years of work by 0.076 years.

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.

Using a rich panel of owner-operated New York dairy farms, we provide new evidence on entrepreneurial behavior. We formulate a dynamic model of farms facing uninsured risks and financial constraints. Farmers derive nonpecuniary benefits from operating their businesses. We estimate the model via simulated minimum distance, matching both production and financial data. We find that financial factors and nonpecuniary benefits are of first-order importance. Collateral constraints and liquidity restrictions inhibit borrowing and the accumulation of capital, especially among high-productivity firms seeking to expand. The nonpecuniary benefits to farming are large and keep small, low-productivity farms in business. Although farmers are risk averse, eliminating uninsured production risk has only modest effects on capital and output.

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. Compensating variation calculations indicate that current retirees value Medicaid insurance at more than its actuarial cost, but that most would value an expansion of the current Medicaid program at less than its cost. These findings suggest that for current single retirees, the Medicaid program may be of the approximately right size.

Rich people, women, and healthy people live much longer than their poor, male, and sick counterparts. Two extremes, taken from our analysis of single people in the Assets and Health Dynamics of the Oldest Old (AHEAD) dataset, illustrate this point: an unhealthy 70-year-old male at the twentieth percentile of the permanent income distribution expects to live only 6 more years, that is, to age 76. In contrast, a healthy 70-year-old woman at the eightieth percentile of the permanent income distribution expects to live 16 more years, thus making it to age 86.] Such significant differences in life expectancy could, all else equal, lead to significant differ ences in saving behavior. A related observation is that people with high permanent incomes keep large amounts of assets until very late in life. Table 1, also based on the

We estimate a model of savings for retired couples and singles who face longevity and medical expense risks and in which couples can leave bequests both when the first spouse dies and when the last spouse dies. We show that saving motives vary by marital status, permanent income, and age. We find that most households save more for medical expenses than for bequests but that richer households and couples, who hold most of the wealth, save more for bequests. As a result, bequest motives are a key determinant of aggregate retirement wealth.