Standard incentive theory models provide a rich framework for studying informational problems but assume that contracts can be perfectly enforced. This paper studies the design of self-enforced relational contracts. I show that optimal contracts often can take a simple stationary form, but that self-enforcement restricts promised compensation and affects incentive provision. With hidden information, it may be optimal for an agent to supply the same inefficient effort regardless of cost conditions. With moral hazard, optimal contracts involve just two levels of compensation. This is true even if performance measures are subjective, in which case optimal contracts terminate following poor performance.

The combinatorial clock auction has become popular for large-scale spectrum awards and other uses, replacing more traditional ascending or clock auctions. We describe some surprising properties of the auction, including a wide range of ex post equilibria with demand expansion, demand reduction, and predation. Our results obtain in a standard homogeneous good setting where bidders have well-behaved linear demand curves, and suggest some practical difficulties with dynamic implementations of the Vickrey auction. (JEL D44, D47, H82, L13)

We develop a model in which firms set impersonal salary levels before matching with workers. Wages fall relative to any competitive equilibrium while profits rise almost as much, implying little inefficiency. Furthermore, the best firms gain the most from the system while wages become compressed. In light of our results, we discuss the performance of alternative institutions and the recent antitrust case against the National Resident Matching Program.

We describe a two-step algorithm for estimating dynamic games under the assumption that behavior is consistent with Markov perfect equilibrium. In the first step, the policy functions and the law of motion for the state variables are estimated. In the second step, the remaining structural parameters are estimated using the optimality conditions for equilibrium. The second step estimator is a simple simulated minimum distance estimator. The algorithm applies to a broad class of models, including industry competition models with both discrete and continuous controls such as the Ericson and Pakes (1995) model. We test the algorithm on a class of dynamic discrete choice models with normally distributed errors and a class of dynamic oligopoly models similar to that of Pakes and McGuire (1994).

We compare the costs and benefits of profit-sharing partnerships relative to the corporate form of organization. We show that organizing as a partnership can be desirable in human-capital intensive industries where product quality is hard to observe. The theory explains the relative scarcity of partnerships outside of professional service industries such as law, accounting, medicine, investment banking, architecture, advertising, and consulting. It also sheds light on features of partnerships such as up-or-out promotion systems, the use of non-compete clauses, motives for profit sharing as well as recent trends in professional service industries

Early admissions are widely used by selective colleges and universities. We identify some basic facts about early admissions policies, including the admissions advantage enjoyed by early applicants and patterns in application behavior, and propose a game-theoretic model that matches these facts. The key feature of the model is that colleges want to admit students who are enthusiastic about attending, and early admissions programs give students an opportunity to signal this enthusiasm. (JEL C78, I23)

The past decade has seen the explosive emergence of online advertising as a major source of revenue for Internet publishers. Analyses of this phenomenon are mostly conducted in the sway of Google’s hugely successful search advertising program. In the early days of the Internet, before Google, virtually all advertising revenues were related to simple display ads. Yet by 2008 search advertising accounted for over $10.5 billion of the $23.4 billion in total online advertising, and pundits were forecasting continued growth at rates of 12 % per year over the next five years.1 Internet advertising markets have broken sharply from the advertising markets for traditional media. In the older media, every consumer that received a particular magazine, listened to a particular radio program, or watched a particular TV show would read, hear or see the same advertisement. An advertiser that wanted to reach an audience with particular characteristics could do so only within narrow limits. For example, a beer company might advertise on televised football games and a maker of fashion clothing might advertise in women's magazines. Although publications do some tailoring of their offerings, as when a newspaper has different local editions, audience mix is nevertheless

We study entry and bidding patterns in sealed bid and open auctions with heterogeneous bidders. Using data from U.S. Forest Service timber auctions, we document a set of systematic effects of auction format: sealed bid auctions attract more small bidders, shift the allocation towards these bidders, and can also generate higher revenue. We show that a private value auction model with endogenous participation can account for these qualitative effects of auction format. We estimate the model's parameters and show that it can explain the quantitative effects as well. Finally, we use the model to provide an assessment of bidder competitiveness, which has important consequences for auction choice.

This paper analyzes the role of private information in U.S. Forest Service timber auctions. In these auctions, firms bid a per unit price for each timber species. Total bids are computed by multiplying these prices by Forest Service volume estimates, but payments depend on actual volumes harvested. We develop an equilibrium theory for these auctions. We then relate (ex post) data about volume to (ex ante) bids. We show that bidders have private information about volumes of species and use it as predicted by theory. Differences in bidder estimates appear to affect the allocation of tracts, but competition limits information rents.

We analyze subprime consumer lending and the role played by down payment requirements in screening high-risk borrowers and limiting defaults. To do this, we develop an empirical model of the demand for financed purchases that incorporates both adverse selection and repayment incentives. We estimate the model using detailed transaction-level data on subprime auto loans. We show how different elements of loan contracts affect the quality of the borrower pool and subsequent loan performance. We also evaluate the returns to credit scoring that allows sellers to customize financing terms to individual applicants. Our approach shows how standard econometric tools for analyzing demand and supply under imperfect competition extend to settings in which firms care about the identity of their customers and their postpurchase behavior.