Arbeitspapier

Nested pseudo-likelihood estimation and bootstrap-based inference for structural discrete Markov decision models

This paper analyzes the higher-order properties of nested pseudo-likelihood (NPL) estimators and their practical implementation for parametric discrete Markov decision models in which the probability distribution is defined as a fixed point. We propose a new NPL estimator that can achieve quadratic convergence without fully solving the fixed point problem in every iteration. We then extend the NPL estimators to develop one-step NPL bootstrap procedures for discrete Markov decision models and provide some Monte Carlo evidence based on a machine replacement model of Rust (1987). The proposed one-step bootstrap test statistics and confidence intervals improve upon the first order asymptotics even with a relatively small number of iterations. Improvements are particularly noticeable when analyzing the dynamic impacts of counterfactual policies.

Sprache
Englisch

Erschienen in
Series: Research Report ; No. 2006-4

Klassifikation
Wirtschaft
Hypothesis Testing: General
Estimation: General
Statistical Simulation Methods: General
Operations Research; Statistical Decision Theory
Computational Techniques; Simulation Modeling
Thema
Edgeworth expansion
k-step bootstrap
maximum pseudo-likelihood estimators
nested fixed point algorithm
Newton-Raphson method
policy iteration

Ereignis
Geistige Schöpfung
(wer)
Kasahara, Hiroyuki
Shimotsu, Katsumi
Ereignis
Veröffentlichung
(wer)
The University of Western Ontario, Department of Economics
(wo)
London (Ontario)
(wann)
2006

Handle
Letzte Aktualisierung
10.03.2025, 11:43 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Kasahara, Hiroyuki
  • Shimotsu, Katsumi
  • The University of Western Ontario, Department of Economics

Entstanden

  • 2006

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