Optimal Rules for Patent Races

41 Pages Posted: 30 Mar 2011

See all articles by Kenneth L. Judd

Kenneth L. Judd

Stanford University - The Hoover Institution on War, Revolution and Peace; Center for Robust Decisionmaking on Climate & Energy Policy (RDCEP); National Bureau of Economic Research (NBER)

Karl Schmedders

University of Zurich

Sevin Yeltekin

Tepper School of Business, Carnegie Mellon University

Date Written: November 1, 2011

Abstract

There are two important rules to patent races: minimal accomplishment necessary to receive the patent and the allocation of the innovation benefits. We study the optimal combination of these rules. A planner, who cannot distinguish between competing firms in a multistage innovation race, chooses the patent rules by maximizing either consumer or social surplus. We show that efficiency cost of prizes is a key consideration. Races are undesirable only when efficiency costs are low, firms are similar, and social surplus is maximized. Otherwise, the optimal policy involves a race of nontrivial duration to spur innovation and filter out inferior innovators.

Keywords: Patent Race, Patent Policy, Stochastic Dynamic Games, Markov-perfect Equilibria

JEL Classification: C61, C63, C73, L43, L50

Suggested Citation

Judd, Kenneth L. and Schmedders, Karl and Yeltekin, Sevin, Optimal Rules for Patent Races (November 1, 2011). Available at SSRN: https://ssrn.com/abstract=1797891 or http://dx.doi.org/10.2139/ssrn.1797891

Kenneth L. Judd

Stanford University - The Hoover Institution on War, Revolution and Peace ( email )

Stanford, CA 94305-6010
United States

Center for Robust Decisionmaking on Climate & Energy Policy (RDCEP) ( email )

5735 S. Ellis Street
Chicago, IL 60637
United States

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Karl Schmedders

University of Zurich ( email )

Moussonstrasse 15
Zürich, CH-8044
Switzerland
+41 (0)44 634 3770 (Phone)

Sevin Yeltekin (Contact Author)

Tepper School of Business, Carnegie Mellon University ( email )

Pittsburgh, PA 15213-3890
United States

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