Optimal Patent Policy with Recurrent Innovators

Hugo Hopenhayn, Department of Economics, UCLA, and Matthew Mitchell, Rotman School of Management, University of Toronto

10/25/2011
(Original Publish Date: 9/1/2011)

We characterize the solution to the problem facing a planner who must allocate preferential treatment across two terms who can use preferential treatment to make profits, and in turn are encouraged to innovate by the provision of preferential treatment. The planner, because he can allocate preference to a single firm for multiple innovations at any point in time, backloads rewards, giving the firm with the preponderance of the promise a preference that corresponds to a patent offering complete exclusion. We show that the promised duration of preference evolves in a region that is determined by the optimal promises in a static version of the model, which corresponds to a classic static patent problem of Arrow and Nordhaus. When there are no static distortions, so that the optimal static patent lasts forever, the optimal policy we study leads to monopoly, in the sense that one firm is excluded even though it is getting useful ideas. We show that these basic results hold even if the planner is forced to use a restricted set of polices where preference is always granted immediately for any innovation that is implemented.