Recombinant Estimation for Normal-Form Games, with Applications to Auctions and Bargaining

In empirical analysis of economic games, researchers frequently wish to estimate quantities describing group outcomes, such as the expected revenue in an auction or the mean allocative efficiency in a market experiment. For such applications, we propose an improved statistical estimation technique called "recombinant estimation." The technique takes observations of the complete strategy of each player and recombines them to compute all the possible group outcomes which could have resulted from different matches of players. We calculate the improvement in efficiency of the recombinant estimator relative to the standard estimator, and show how to estimate standard errors for the recombinant estimator for use in hypothesis testing. We present an application to a two-player sealed-bid auction and a two-player ultimatum bargaining game. In these applications, the improved efficiency of our estimator is equivalent to an increase of between 40% and 200% in the sample size. We discuss how to design game experiments in order to be able to take full advantage of recombinant estimation. Finally, we discuss practical computational issues, showing how one can avoid combinatorial explosions of computing time while still yielding significantly improved efficiency of estimation.

Economics, Psychology, and Social Dynamics of Consumer Bidding in Auctions

With increasing numbers of consumers in auction marketplaces, we highlight some recent approaches that bring additional economic, social, and psychological factors to bear on existing economic theory to better understand and explain consumers' behavior in auctions. We also highlight specific research streams that could contribute towards enriching existing economic models of bidding behavior in emerging market mechanisms.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47034/1/11002_2005_Article_5901.pd

Magic on the Internet--experimental tests of auction theory

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Economics, 1996.Includes bibliographical references.by David H.L. Reiley.Ph.D

Recombinant Estimation for Normal-Form Games, with Applications to Auctions and Bargaining

In empirical studies of simultaneous-move games, such as sealed-bid auctions, researchers frequently wish to estimate quantities which depend on interactions between the strategies of different players. Examples include the expected revenues of an auction, or the mean allocative efficiency in a market experiment. For such applications, we present an improved statistical estimator based on "recombinant estimation": recombining the strategies of individual players to compute what the outcomes would have been if players had been matched in different groups. We calculate the improvement in efficiency of the recombinant estimator relative to the standard estimator, and show how to estimate standard errors for the recombinant estimator. We present an application to a two-player sealed-bid auction and a two-player ultimatum bargaining game. In these applications, the improved efficiency of our estimator is equivalent to an increase of between 40% and 200% in the sample size, and we expect even larger improvements for games with three or more players. We discuss how to design experiments in order to be able to take full advantage of recombinant estimation. Finally, we discuss practical computational issues, showing how one can avoid combinatorial explosions of computing time while still yielding significantly improved efficiency of estimation.Simultaneous-move games, experimental statistics