Semiparametric estimation of Markov decision processes with continuous state space

Srisuma, S and Linton, O (2012) Semiparametric estimation of Markov decision processes with continuous state space Journal of Econometrics, 166 (2). pp. 320-341.

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Abstract

We propose a general two-step estimator for a popular Markov discrete choice model that includes a class of Markovian games with continuous observable state space. Our estimation procedure generalizes the computationally attractive methodology of Pesendorfer and Schmidt-Dengler (2008) that assumed finite observable states. This extension is non-trivial as the policy value functions are solutions to some type II integral equations. We show that the inverse problem is well-posed. We provide a set of primitive conditions to ensure root-T consistent estimation for the finite dimensional structural parameters and the distribution theory for the value functions in a time series framework. © 2011 Elsevier B.V. All rights reserved.

Item Type:	Article
Divisions :	Surrey research (other units)
Authors :	Name Email ORCID Srisuma, S s.srisuma@surrey.ac.uk Linton, O
Date :	1 February 2012
DOI :	10.1016/j.jeconom.2011.10.003
Depositing User :	Symplectic Elements
Date Deposited :	16 May 2017 15:27
Last Modified :	24 Jan 2020 14:41
URI:	http://epubs.surrey.ac.uk/id/eprint/819754

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