The empirical implications of rank in Bimatrix games
Pages 55 - 72
Abstract
We study the structural complexity of bimatrix games, formalized via rank, from an empirical perspective. We consider a setting where we have data on player behavior in diverse strategic situations, but where we do not observe the relevant payoff functions. We prove that high complexity (high rank) has empirical consequences when arbitrary data is considered. Additionally, we prove that, in more restrictive classes of data (termed laminar), any observation is rationalizable using a low-rank game: specifically a zero-sum game. Hence complexity as a structural property of a game is not always testable. Finally, we prove a general result connecting the structure of the feasible data sets with the highest rank that may be needed to rationalize a set of observations.
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Published In
June 2013
924 pages
ISBN:9781450319621
DOI:10.1145/2492002
- General Chair:
- Michael Kearns,
- Program Chairs:
- Preston McAfee,
- Éva Tardos
Copyright © 2013 ACM.
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Published: 16 June 2013
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