
doi: 10.2139/ssrn.2071105
handle: 10419/150357
Summary: We develop a minimum distance estimator for dynamic games of incomplete information. We take a two-step approach, following \textit{V. J. Hotz} and \textit{R. A. Miller} [Rev. Econ. Stud. 60, No. 3, 497--529 (1993; Zbl 0788.90007)], based on the pseudo-model that does not solve the dynamic equilibrium so as to circumvent the potential indeterminacy issues associated with multiple equilibria. The class of games estimable by our methodology includes the familiar discrete unordered action games as well as games where players' actions are monotone (discrete, continuous, or mixed) in the their private values. We also provide conditions for the existence of pure strategy Markov perfect equilibria in monotone action games under increasing differences condition.
Dynamic games, ddc:330, Markov processes: estimation; hidden Markov models, Markov perfect equilibrium, semiparametric estimation with nonsmooth objective functions, dynamic games
Dynamic games, ddc:330, Markov processes: estimation; hidden Markov models, Markov perfect equilibrium, semiparametric estimation with nonsmooth objective functions, dynamic games
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