离散选择动态规划模型的估计

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY Accounts of Chemical Research Pub Date : 2017-12-01 DOI:10.1111/jere.12169

Hiroyuki Kasahara, Katsumi Shimotsu

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引用次数: 5

摘要

本文综述了无限视界离散选择动态规划模型的估计方法，并进行了蒙特卡罗实验。我们考虑了极大似然估计量(MLE)、两步条件选择概率估计量、有限依赖下基于策略迭代映射的序列估计量和基于值迭代映射的序列估计量。我们的仿真结果表明，基于策略迭代和值迭代映射的序列估计器的估计性能在很大程度上与MLE相当，而对于具有中等大小状态空间的模型，它们比MLE获得了100倍的计算增益。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Estimation of Discrete Choice Dynamic Programming Models

This study reviews estimation methods for the infinite horizon discrete choice dynamic programming models and conducts Monte Carlo experiments. We consider: the maximum likelihood estimator (MLE), the two-step conditional choice probabilities estimator, sequential estimators based on policy iterations mapping under finite dependence, and sequential estimators based on value iteration mappings. Our simulation result shows that the estimation performance of the sequential estimators based on policy iterations and value iteration mappings is largely comparable to the MLE, while they achieve substantial computation gains over the MLE by a factor of 100 for a model with a moderately large state space.

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来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.

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