Strong convergence and dynamic economic models

Robert L. Bray

doi:10.3982/QE833

Strong convergence and dynamic economic models

Robert L. Bray^*

^*Corresponding author for this work

Managerial Economics, Decision Sciences and Operations

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

Abstract

Morton and Wecker (1977) stated that the value iteration algorithm solves a dynamic program's policy function faster than its value function when the limiting Markov chain is ergodic. I show that their proof is incomplete, and provide a new proof of this classic result. I use this result to accelerate the estimation of Markov decision processes and the solution of Markov perfect equilibria.

Original language	English (US)
Pages (from-to)	43-65
Number of pages	23
Journal	Quantitative Economics
Volume	10
Issue number	1
DOIs	https://doi.org/10.3982/QE833
State	Published - Jan 2019

Keywords

C01
C13
C15
C61
C63
C65
Markov decision process
Markov perfect equilibrium
dynamic discrete choice
nested fixed point
nested pseudo-likelihood
relative value iteration
strong convergence

ASJC Scopus subject areas

Economics and Econometrics

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Cite this

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abstract = "Morton and Wecker (1977) stated that the value iteration algorithm solves a dynamic program's policy function faster than its value function when the limiting Markov chain is ergodic. I show that their proof is incomplete, and provide a new proof of this classic result. I use this result to accelerate the estimation of Markov decision processes and the solution of Markov perfect equilibria.",

keywords = "C01, C13, C15, C61, C63, C65, Markov decision process, Markov perfect equilibrium, dynamic discrete choice, nested fixed point, nested pseudo-likelihood, relative value iteration, strong convergence",

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note = "Publisher Copyright: Copyright {\textcopyright} 2019 The Author.",

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AB - Morton and Wecker (1977) stated that the value iteration algorithm solves a dynamic program's policy function faster than its value function when the limiting Markov chain is ergodic. I show that their proof is incomplete, and provide a new proof of this classic result. I use this result to accelerate the estimation of Markov decision processes and the solution of Markov perfect equilibria.

KW - C01

KW - C13

KW - C15

KW - C61

KW - C63

KW - C65

KW - Markov decision process

KW - Markov perfect equilibrium

KW - dynamic discrete choice

KW - nested fixed point

KW - nested pseudo-likelihood

KW - relative value iteration

KW - strong convergence

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JO - Quantitative Economics

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IS - 1

ER -

Strong convergence and dynamic economic models

Abstract

Keywords

ASJC Scopus subject areas

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