Neale Mahoney

Premiums in insurance markets frequently do not reflect individual differences in costs, either because consumers have private information or because prices are not risk-rated. This creates inefficiencies when consumers self-select into plans. We study this problem in health insurance markets. We develop a simple model and estimate it using data on small employers. In this setting, the welfare loss compared to the feasible risk-rated benchmark is around 2-11% of coverage costs. Three-quarters of this is due to restrictions on risk-rating employee contributions; the rest is due to inefficient contribution choices. Despite the inefficiency, we find substantial benefits from plan choice.

This paper examines the interaction between health insurance and the implicit insurance that people have because they can file (or threaten to file) for bankruptcy. With a simple model that captures key institutional features, I demonstrate that the financial risk from medical shocks is capped by the assets that could be seized in bankruptcy. For households with modest seizable assets, this implicit “bankruptcy insurance” can crowd out conventional health insurance. I test these predictions using variation in the state laws that specify the type and level of assets that can be seized in bankruptcy. Because of the differing laws, people who have the same assets and receive the same medical care face different losses in bankruptcy. Exploiting the variation in seizable assets that is orthogonal to wealth and other household characteristics, I show that households with fewer seizable assets are more likely to be uninsured. This finding is consistent with another: uninsured households with fewer seizable assets end up making lower out-of-pocket medical payments. The estimates suggest that if the laws of the least debtor-friendly state of Delaware were applied nationally, 15.2 percent of the uninsured would buy health insurance. Achieving the same increase in coverage would require a premium subsidy of approximately 41.1 percent. To shed light on puzzles in the literature and examine policy counterfactuals, I calibrate a utility-based, micro-simulation model of insurance choice. Among other things, simulations show that “bankruptcy insurance” explains the low take-up of high-deductible health insurance.

Many organizations fund their spending out of a fixed budget that expires at year's end. Faced with uncertainty over future spending demands, these organizations have an incentive to build a buffer stock of funds over the front end of the budget cycle. When demand does not materialize, they then rush to spend these funds on lower quality projects at the end of the year. We test these predictions using data on procurement spending by the U.S. federal government. Using data on all federal contracts from 2004 through 2009, we document that spending spikes in all major federal agencies during the 52nd week of the year as the agencies rush to exhaust expiring budget authority. Spending in the last week of the year is 4.9 times higher than the rest-of-the-year weekly average. We examine the relative quality of year-end spending using a newly available dataset that tracks the quality of $130 billion in information technology (I.T.) projects made by federal agencies. Consistent with the model, average project quality falls at the end of the year. Quality scores in the last week of the year are 2.2 to 5.6 times more likely to be below the central value. To explore the impact of allowing agencies to roll unused spending over into subsequent fiscal years, we study the I.T. contracts of an agency with special authority to roll over unused funding. We show that there is only a small end-of-year I.T. spending spike in this agency and that the one major I.T. contract this agency issued in the 52nd week of the year has a quality rating that is well above average.