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Non-Monotone Comparative Statics in Games of Incomplete Information

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Abstract

This paper analyses comparative statics for two classes of n-player games of incomplete information with continuous action spaces. The two classes are defined by differences in the payoff and behaviour of the weakest type: the lowest value bidder or highest cost firm. We show that in "weakly competitive games", including all-pay auctions and some oligopoly models, weak types will respond to a stochastically higher distribution of types by playing less aggressively. In "strongly competitive" games, all types play more aggressively. Furthermore, we show that a decrease in dispersion of types, in the sense of a refinement of second order stochastic dominance, although also associated with an increase in competitiveness, may in addition result in less aggressive play by strong types in both strongly and weakly competitive games.

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  • Ed Hopkins & Tatiana Kornienko, 2004. "Non-Monotone Comparative Statics in Games of Incomplete Information," Edinburgh School of Economics Discussion Paper Series 122, Edinburgh School of Economics, University of Edinburgh.
    • Handle: RePEc:edn:esedps:122
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    Cited by:

    1. Ed Hopkins & Tatiana Kornienko, 2006. "Which Inequality? The Inequality of Resources Versus the Inequality of Rewards," Levine's Bibliography 784828000000000621, UCLA Department of Economics.

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    More about this item

    Keywords

    monotone likelihood ratio; monotone probability ratio; conditional stochastic dominance; generalized Lorenz order; comparative statics; games of incomplete information; first price auctions;
    All these keywords.

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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