Long-term or perpetual licenses give their owners incentives to invest in and maintain the common value of public resources, but may impede reallocation of resources to innovative entrants. Short-term licenses improve allocative efficiency at the cost of investment incentives. We propose depreciating licenses, a system that navigates the allocative-investment tradeoff more efficiently. Licensees annually announce valuations at which they commit to sell their licenses, and pay a percent of these valuations as license fees. Depreciating licenses induce high and time-stationary investment incentives. The self-assessed license fee encourages value revelation and improves allocative efficiency. The only tuning parameter, the depreciation rate, can be chosen appropriately by targeting the observed probability of license turnover.
A Mechanism Design Approach to Identification and Estimation, with Brad Larsen, May 2017.
This paper provides a new, nonparametric identification and estimation approach for a variety of incomplete information games, both static and dynamic. The approach relies on the Revelation Principle, exploiting the incentive compatibility of the direct revelation mechanism corresponding to the underlying and unspecified game, rather than attempting to solve for or specify the extensive form or equilibrium strategies of the game directly. We illustrate the approach using simulated and actual data from bargaining settings.
Implementability, Walrasian Equilibria, and Efficient Matchings, with Piotr Dworczak, Economics Letters, 2017, 153 pp. 57–60.