Perpetual licenses incent owners to invest in the common value of public resources, but impede efficient reallocation of resources to higher-valued entrants. Short-term licenses improve allocative efficiency but discourage investment. We propose a depreciating license that improves on this tradeoff. Licensees periodically announce valuations at which they commit to sell their licenses, and pay a percent of these valuations as license fees. Depreciating licenses produce time-stationary investment incentives while encouraging truthful value revelation that improves allocative efficiency. The only tuning parameter, the depreciation rate, can be chosen appropriately by targeting the observed equilibrium frequency of license turnover.
A Mechanism Design Approach to Identification and Estimation, with Brad Larsen, December 2017.
This paper presents a two-step identification argument for a large class of quasilinear utility trading games, imputing agents' values using revealed preference based on their choices from a convex menu of expected outcomes available in equilibrium. This generalizes many existing two-step approaches in the auctions literature. We propose nonparametric value estimation procedures based on our identification results for general trading games. In simulations, our procedures are competitive with existing estimation procedures for first-price auction settings. We derive a approach based on proxy variables to analyze settings in which actions are incompletely observed, and show that our procedures can be combined with tools for handling unobserved heterogeneity and non-independent types from the auctions literature. We apply our results to analyze efficiency and surplus division in the complex game played at wholesale used-car auctions, that of a secret reserve price auction followed by post-auction bargaining.
Implementability, Walrasian Equilibria, and Efficient Matchings, with Piotr Dworczak, Economics Letters, 2017, 153 pp. 57–60.