I explore fundamental behavioral aspects of several market design environments in a variety of projects using both theoretical models and laboratory experiments. I show that human tendencies can drastically shift potential outcomes away from those which would result if individuals were fully 'rational' and unbiased in decision problems similar to those found frequently in the field. I explore two common classes of centralized matching mechanisms--Deferred Acceptance and Priority--which have wildly different success rates in practice despite both being open to manipulation by agents who have incomplete information about the other participants in the match. For this reason, theory predicts both mechanisms in equilibrium will yield match outcomes which are unstable, meaning some agents will desire to renegotiate with one another after receiving their match assignments, and thus reduce participants' confidence in using the match. I provide laboratory evidence that out-of-equilibrium truth telling by agents is substantially more frequent in the Deferred Acceptance environment and thus Deferred Acceptance matches will generally be more stable in practice than matches using a Priority mechanism. This may explain why Deferred Acceptance mechanisms appear to be more viable in the field. I also explore two different models of decentralized two-sided matching environments where establishing scarce signaling methods can improve market outcomes. In a laboratory experiment, I show that allowing potential receiving job offers to send a single signal to their favorite potential employer before job offers are made increases overall match rates in the market, but is potentially damaging to the firms making offers when compared to the market without such a signal. Then, in a theoretical model where pre-offer communication takes the form of an interview process where workers have natural limits on the number of interviews in which they can participate, I show that in many cases firms can benefit themselves and the market as a whole by voluntarily restricting the number of interviews they offer to participate in. While not traditionally thought of as market design problems, voting mechanisms are fundamentally goods allocation problems as well and have many of the same issues as traditional markets do. I explore the effects of voter bias on outcomes in an otherwise standard voting model and find that even slight external pressure on individuals in a committee tasked with coming to a collective decision can destroy the ability of that committee to arrive at the correct result, even when individuals have good information about the best decision to make. Furthermore, the quality of the decision made by such a committee can actually degrade as the committee size increases, in contrast with the canonical Condorcet Jury Theorem which predicts that a committee's ability to choose the right outcome increases quickly as more members are added.

Two-sided matching provides a model of search processes such as those between firms and workers in labor markets or between buyers and sellers in auctions. This book gives a comprehensive account of recent results concerning the game-theoretic analysis of two-sided matching. The focus of the book is on the stability of outcomes, on the incentives that different rules of organization give to agents, and on the constraints that these incentives impose on the ways such markets can be organized. The results for this wide range of related models and matching situations help clarify which conclusions depend on particular modeling assumptions and market conditions, and which are robust over a wide range of conditions. 'This book chronicles one of the outstanding success stories of the theory of games, a story in which the authors have played a major role: the theory and practice of matching markets ... The authors are to be warmly congratulated for this fine piece of work, which is quite unique in the game-theoretic literature.' From the Foreword by Robert Aumann

This dissertation has four chapters. The first three chapters examine health insurance markets in the U.S., focusing in particular on contexts where there are important interactions between health insurance plans. The fourth chapter is on the U.S. budget, examining the implications of annual budget cycles on the quantity and quality of end-of-year spending. Chapter 1, entitled "Bankruptcy as Implicit Health Insurance" 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, 16.3 percent of the uninsured would buy health insurance. Achieving the same increase in coverage would require a premium subsidy of approximately 44.0 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. Chapter 2, entitled "Pricing and Welfare in Health Plan Choice", is coauthored with M. Kate Bundorf and Jonathan Levin. The starting point for the paper is the simple observation that when insurance premiums do not reflect individual differences in expected costs, consumers may choose plans inefficiently. We study this problem in health insurance markets, a setting in which prices often do not incorporate observable differences in expected costs. 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, the benefits from plan choice relative to each of the single-plan options are substantial. Chapter 3, entitled "The Private Coverage and Public Costs: Identifying the Effect of Private Supplemental Insurance on Medicare Spending, " is coauthored with Marika Cabral. While most elderly Americans have health insurance coverage through Medicare, traditional Medicare policies leave individuals exposed to significant financial risk. Private supplemental insurance to "fill the gaps" of Medicare, known as Medigap, is very popular. In this Chapter, we estimate the impact of this supplemental insurance on total medical spending using an instrumental variables strategy that leverages discontinuities in Medigap premiums at state boundaries. Our estimates suggest that Medigap increases medical spending by 57 percent--or about 40 percent more than previous estimates. Back-of-the-envelope calculations indicate that a 20 percent tax on premiums would generate combined revenue and savings of 6.2 percent of baseline costs; a Pigovian tax that fully accounts for the fiscal externality would yield savings of 18.1 percent. Chapter 4, entitled "Do Expiring Budgets Lead to Wasteful Year-End Spending? Evidence from Federal Procurement, " is coauthored with Jeffrey Liebman. 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.