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Semiparametric estimation of Markov decision processeswith continuous state space

Linton, Oliver and Srisuma, Sorawoot (2010) Semiparametric estimation of Markov decision processeswith continuous state space. Econometrics (EM/2010/550). Suntory and Toyota International Centres for Economics and Related Disciplines, London, UK.

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We propose a general two-step estimation method for the structural parameters of popular semiparametric Markovian discrete choice models that include a class of Markovian Games and allow for continuous observable state space. The estimation procedure is simple as it directly generalizes the computationally attractive methodology of Pesendorfer and Schmidt-Dengler (2008) that assumed finite observable states. This extension is non-trivial as the value functions, to be estimated nonparametrically in the first stage, are defined recursively in a non-linear functional equation. Utilizing structural assumptions, we show how to consistently estimate the infinite dimensional parameters as the solution to some type II integral equations, the solving of which is a well-posed problem. We provide sufficient set of primitives to obtain root-T consistent estimators for the finite dimensional structural parameters and the distribution theory for the value functions in a time series framework.

Item Type: Monograph (Report)
Official URL:
Additional Information: © 2010 The Authors
Divisions: STICERD
Subjects: H Social Sciences > HB Economic Theory
Date Deposited: 23 Jul 2014 15:41
Last Modified: 08 Oct 2021 23:18
Funders: Erythrocyte sedimentation rate (ESR)

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