Recombinant estimation for normal-form games, with applications to auctions and bargaining

When analyzing economic games, researchers frequently estimate quantities describing group outcomes, such as the expected revenue in an auction. For such applications, we propose an improved statistical estimation technique called “recombinant estimation.” The technique takes observations of players' strategies and recombines them to compute all possible group outcomes that could have resulted from different player combinations. In applications to an auction and a bargaining game, the improved efficiency of our estimator is equivalent to increasing the sample size between 25 and 200%. We discuss how to design experiments in order to utilize recombinant estimation. We also discuss practical computational issues, and provide software for computing estimates and standard errors.