Person:

Lewis, Gregory

We develop a decentralized Bayesian model of college admissions with two ranked colleges, heterogeneous students and two realistic match frictions: students find it costly to apply to college, and college evaluations of their applications are uncertain. Students thus face a portfolio choice problem in their application decision, while colleges choose admissions standards that act like market-clearing prices. Enrollment at each college is affected by the standards at the other college through student portfolio reallocation. In equilibrium, student-college sorting may fail: weaker students sometimes apply more aggressively, and the weaker college might impose higher standards. Applying our framework, we analyze affirmative action, showing how it induces minority applicants to construct their application portfolios as if they were majority students of higher caliber.

Since Akerlof (1970), economists have understood the adverse selection problem that information asymmetries can create in used goods markets. The remarkable growth in online auctions of used goods, where buyers generally purchase sight unseen, therefore poses a puzzle. I argue that part of the solution is that sellers voluntarily disclose their private information to buyers through photos, text and graphics on the auction webpage. In so doing they define a precise contract between buyer and seller — to deliver the car shown — and this helps protect the buyer from adverse selection. Extending previous theoretical work by Jovanovic (1982), I model the impact of contractible disclosure and changes in disclosure costs on performance and adverse selection on online auction platforms. To test this theory, I examine data from eBay Motors. I find first that sellers selectively disclose information; second that this reduces information asymmetry; and finally that disclosure costs impact both the level of disclosure and the prices obtained by sellers, and consequently incentives for seller participation.

In public sector procurement, social welfare often depends on the time taken to complete the contract. A leading example is highway construction, where slow completion times inflict a negative externality on commuters. Recently, highway departments have introduced innovative contracting methods that give contractors explicit time incentives. We characterize equilibrium bidding and efficient design of these contracts. We then gather a unique data set of highway repair projects awarded by the Minnesota Department of Transportation that includes both innovative and standard contracts. Descriptive analysis shows that for both contract types, contractors respond to the incentives as the theory predicts, both at the bidding stage and after the contract is awarded. Next we build a structural econometric model that endogenizes project completion times, and perform counterfactual policy analysis. Our estimates suggest that switching from standard contracts to designs with socially efficient time incentives would increase welfare by over 19% of the contract value; or in terms of the 2009 Mn/DOT budget, $290 million. We conclude that large improvements in social welfare are possible through the use of improved contract design.

We develop the first Bayesian model of decentralized college admissions, with heterogeneous students, costly portfolio applications, and noisy college evaluations. Students face a nontrivial portfolio choice, and colleges choose admissions standards that act like market-clearing prices. We derive the two college model equilibrium, deriving a “law of demand”. Surprisingly, the worse college might impose higher standards, and weaker students sometimes apply more aggressively. The lesser college impacts its rival through student portfolio reallocation. Also, the weaker college counters affirmative action at its rival with a discriminatory admissions policy, and may poach students from its rival using early admissions.