TY  - JOUR
AU  - Bajari,Patrick
AU  - Hong,Han
TI  - Semiparametric Estimation of a Dynamic Game of Incomplete Information
JF  - National Bureau of Economic Research Technical Working Paper Series
VL  - No. 320
PY  - 2006
Y2  - February 2006
UR  - http://www.nber.org/papers/t0320
L1  - http://www.nber.org/papers/t0320.pdf
N1  - Author contact info:
Patrick Bajari
Professor of Economics
University of Minnesota
4-101 Hanson Hall
1925 4th Street South
Minneapolis, MN 55455
Tel: 612/625-8369
Fax: 612/624-0209
E-Mail: bajari@econ.umn.edu

Han Hong
Landau Economics Building
579 Serra Mall
Stanford, CA 94305
E-Mail: doubleh@stanford.edu
AB  - 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.
ER  -