Abstract: This paper develops a new empirical model of a multistage R&D contest for a procurement contract and uses it to study the design of the Small Business Innovation Research program in the Department of Defense. Firms' incentives to innovate depend on the cost of research, the intensity of competition, and the rewards from securing the procurement contract. The cost of research, the distributions of project values and delivery costs, and the fraction of the surplus shared by the procurer are nonparametrically identified and can be tractably estimated using data on the procurement contract amount and the R&D expenditures of the firms. Estimates suggest that there is fairly low variation in the values of projects developed by different firms and that most of the variation in the procurement contract is attributable to differences in delivery costs, which are drawn later in the research process. Further, the DOD currently provides high-powered incentives, sharing approximately three-quarters of the surplus from the innovation with the supplier. Increasing the number of competitors in later stages of the contest, lowering the share of the surplus firms receive in procurement, and mandating that firms share intellectual property would all increase total social surplus. However, since the DOD pays for research expenditures but only partially internalizes the gains from improved innovations, many socially beneficial design changes would actually reduce its profits from the contest. Together, these results suggest that at the estimated parameters, the DOD may have an incentive to skew the design of the contest significantly away from the socially optimal one.
Imperfect Public Monitoring with a Fear of Signal Distortion (with Lucas Manuelli and Ludwig Straub), Revise and Resubmit at Journal of Economic Theory
Abstract: This paper proposes a model of signal distortion in a two-player game with imperfect public monitoring. We construct a tractable theoretical framework where each player has the opportunity to distort the true public signal and each player is uncertain about the distortion technologies available to the other player. We show that when players evaluate strategies according to their worst-case guarantees—i.e., are ambiguity averse over certain distributions in the environment—perceived continuation payoffs endogenously lie on a positively sloped line. We then provide examples showing that, counterintuitively, identifying deviators can be harmful in enforcing a strategy profile; moreover, we illustrate how the presence of such signal distortion can sustain cooperation when it is impossible in standard settings. We show that the main result and examples are robust to a number of natural modifications to our setting. Finally, we extend our model to a repeated game where our concept is a natural generalization of strongly symmetric equilibria. In this setting, we prove an anti-folk theorem, showing that payoffs under our equilibrium concept are under general conditions bounded away from efficiency.
Rank-Based Elicitation Schemes for Relative Likelihoods of Events (with Benjamin N. Roth)
Abstract: This paper studies whether rank-based scoring rules, in which agents are asked to order events by their likelihoods, can elicit truthful rankings. Such mechanisms are commonly used in the field since they only require agents to compare probabilities of similar events to each other rather than to numerical probabilities, which may be difficult for agents with low numeracy. We first show that commonly-used rank-based scoring rules need not elicit truthful rankings from agents who are not risk-neutral. We then provide a variation of a rank-based scoring rule that incentivizes agents to rank arbitrary sets of events truthfully, regardless of risk preferences. This scheme can elicit approximate numerical probabilities as well. We provide a simple implementation of this scheme using a series of questions that ask agents about the relative likelihoods of pairs of events. Finally, we conduct numerical experiments that show that this scheme elicits probabilities to high precision using relatively few questions.
Regulating Bidder Participation in Auctions (with James W. Roberts and Andrew Sweeting), RAND Journal of Economics, 45(4), 2014
Abstract: In the standard model of procurement auctions with endogenous and free entry, too many or too few suppliers may enter because their entry decisions are not coordinated. We show how an alternative "entry rights auction" mechanism, where an initial auction is used to allocate rights to participate in a second auction for the contract, may improve efficiency depending on how much information suppliers have about their costs when they decide whether to enter. In an empirical application, using data from highway procurement auctions, we predict that the entry rights auction mechanism would both increase efficiency and reduce procurement costs significantly.
Selective Entry and Auction Design (with Andrew Sweeting), International Journal of Industrial Organization, 43, 2015
Abstract: This article examines how different auction designs perform when entry is endogenous and selective, by which we mean that bidders with higher values are more likely to enter. In a model where potential bidders are symmetric, we show that three alternative designs can significantly outperform the "standard auction with simultaneous and free entry" when entry is selective. When bidders are asymmetric, we show that the level of bid preference that maximizes a seller’s revenues is significantly affected by the degree of selection. We also describe recent empirical and econometric work that shows that the degree of selection can be identified and estimated using standard types of auction data.
Research in Progress
An Empirical Model of Learning and Deterrence in Dynamic Research Contests