Pseudo-likelihood estimation and bootstrap inference for structural discrete Markov decision models
Abstract
This paper analyzes the higher-order properties of the estimators based on the nested pseudo-likelihood (NPL) algorithm and the practical implementation of such estimators for parametric discrete Markov decision models. We derive the rate at which the NPL algorithm converges to the MLE and provide a theoretical explanation for the simulation results in Aguirregabiria and Mira [Aguirregabiria, V., Mira, P., 2002. Swapping the nested fixed point algorithm: A class of estimators for discrete Markov decision models. Econometrica 70, 1519-1543], in which iterating the NPL algorithm improves the accuracy of the estimator. We then propose a new NPL algorithm that can achieve quadratic convergence without fully solving the fixed point problem in every iteration and apply our estimation procedure to a finite mixture model. We also develop one-step NPL bootstrap procedures for discrete Markov decision models. The Monte Carlo simulation evidence based on a machine replacement model of Rust [Rust, J., 1987. Optimal replacement of GMC bus engines: An empirical model of Harold Zurcher. Econometrica 55, 999-1033] shows that the proposed one-step bootstrap test statistics and confidence intervals improve upon the first order asymptotics even with a relatively small number of iterations.Download Info
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Bibliographic Info
Article provided by Elsevier in its journal Journal of Econometrics.
Volume (Year): 146 (2008)
Issue (Month): 1 (September)
Pages: 92-106
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Handle: RePEc:eee:econom:v:146:y:2008:i:1:p:92-106
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Web page: http://www.elsevier.com/locate/jeconom
For corrections or technical questions regarding this item, or to correct its listing, contact: (Jeroen Loos).
Related research
Keywords: Edgeworth expansion Finite mixture k-step bootstrap Maximum pseudo-likelihood estimators Nested fixed point algorithm Newton-Raphson method Policy iteration;References
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Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.Cited by:
- Aguirregabiria, Victor & Nevo, Aviv, 2010.
"Recent developments in empirical IO: dynamic demand and dynamic games,"
MPRA Paper
27814, University Library of Munich, Germany.
- Victor Aguirregabiria & Victor Aguirregabiria & Aviv Nevo & Aviv Nevo, 2010. "Recent Developments in Empirical IO: Dynamic Demand and Dynamic Games," Working Papers tecipa-419, University of Toronto, Department of Economics.
- Vadim Marmer & Taisuke Otsu, 2009.
"Optimal Comparison of Misspecified Moment Restriction Models under a Chosen Measure of Fit,"
Cowles Foundation Discussion Papers
1724, Cowles Foundation for Research in Economics, Yale University, revised Jul 2011.
- Marmer, Vadim & Otsu, Taisuke, 2008. "Optimal Comparison of Misspecified Moment Restriction Models under a Chosen Measure of Fit," Micro Theory Working Papers vadim_marmer-2008-13, Microeconomics.ca Website, revised 25 Jul 2011.
- Hiroyuki Kasahara & Katsumi Shimotsu, 2008.
"Sequential Estimation of Structural Models with a Fixed Point Constraint,"
CESifo Working Paper Series
2507, CESifo Group Munich.
- Kasahara, Hiroyuki & Shimotsu, Katsumi, 2009. "Sequential Estimation of Structural Models with a Fixed Point Constraint," Discussion Papers 2009-18, Graduate School of Economics, Hitotsubashi University.
- Hiroyuki Kasahara & Katsumi Shimotsu, 2008. "Sequential Estimation of Structural Models with a Fixed Point Constraint," Working Papers 1192, Queen's University, Department of Economics.
- Aguirregabiria, Victor, 2009. "Estimation of Dynamic Discrete Games Using the Nested Pseudo Likelihood Algorithm: Code and Application," MPRA Paper 17329, University Library of Munich, Germany.
- Aguirregabiria, Victor & Ho, Chun-Yu, 2009.
"A Dynamic Oligopoly Game of the US Airline Industry: Estimation and Policy Experiments,"
MPRA Paper
16739, University Library of Munich, Germany.
- Victor Aguirregabiria & Chun-Yu Ho, 2008. "A Dynamic Oligopoly Game of the US Airline Industry: Estimation and Policy Experiments," Working Papers tecipa-337, University of Toronto, Department of Economics.
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