Semiparametric Estimation of a Dynamic Game of Incomplete Information / Patrick Bajari, Han Hong.

Format:

Book

Author/Creator:

Bajari, Patrick.

Contributor:

National Bureau of Economic Research.

Hong, Han.

Series:

Technical Working Paper Series (National Bureau of Economic Research) no. t0320.

NBER technical working paper series no. t0320

Language:

English

Physical Description:

1 online resource: illustrations (black and white);

Place of Publication:

Cambridge, Mass. National Bureau of Economic Research 2006.

Summary:

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' 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.

Notes:

Print version record

February 2006.