Finite State Dynamic Games with Asymmetric Information: A Computational Framework
AbstractWe present a simple algorithm for computing an intuitive notion of MPE for ?nite state dynamic games with asymmetric information. The algorithm does not require; storage and updating of posterior distributions, explicit integration over possible future states to deter- mine continuation values, or storage and updating of information at all possible points in the state space. It is also easy to program. To il- lustrate we compute the MPE of a collusive industry in which ?rms do not know each other?s cost positions. Costs evolve with the (privately observed) outcomes of their investment decisions. Costly meetings are called when a ?rm perceives that its relative cost position has improved. The meetings reveal information and realign pro?ts accod- ingly. We show that parameters determining information ?ows can e¤ect market structure and through market structure, producer and consumer surplus.
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Bibliographic InfoPaper provided by Harvard - Institute of Economic Research in its series Harvard Institute of Economic Research Working Papers with number 2041.
Date of creation: 2004
Date of revision:
Other versions of this item:
- Ariel Pakes & Chaim Fershtman, 2004. "Finite State Dynamic Games with Asymmetric Information: A Computational Framework," 2004 Meeting Papers 41, Society for Economic Dynamics.
- L1 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
- C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
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- Susan Athey & Kyle Bagwell, 2004.
"Collusion with Persistent Cost Shocks,"
122247000000000334, UCLA Department of Economics.
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