Recently, empirical industrial organization economists have proposed estimators for dynamic games of incomplete information. In these models, agents choose from a finite number actions and maximize expected discounted utility in a Markov perfect equilibrium. Previous econometric methods estimate the probability distribution of agents%u2019 actions in a first stage. In a second step, a finite vector of parameters of the period return function are estimated. In this paper, we develop semiparametric estimators for dynamic games allowing for continuous state variables and a nonparametric first stage. The estimates of the structural parameters are T1/2 consistent (where T is the sample size) and asymptotically normal even though the first stage is estimated nonparametrically. We also propose sufficient conditions for identification of the model.
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Paper provided by National Bureau of Economic Research, Inc in its series NBER Technical Working Papers with number
0320.
Length: Date of creation: Feb 2006 Date of revision: Handle: RePEc:nbr:nberte:0320
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Find related papers by JEL classification: L0 - Industrial Organization - - General L5 - Industrial Organization - - Regulation and Industrial Policy C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General
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