Practical Methods for Estimation of Dynamic Discrete Choice Models

被引：62

作者：

Arcidiacono, Peter ^{[1
]}

Ellickson, Paul B. ^{[2
]}

机构：

[1] Duke Univ, Dept Econ, Durham, NC 27708 USA

[2] Univ Rochester, Simon Sch Business Adm, Rochester, NY 14627 USA

来源：

ANNUAL REVIEW OF ECONOMICS, VOL 3 | 2011年 / 3卷

关键词：

dynamic structural models; unobserved heterogeneity; conditional choice probabilities; STRUCTURAL MODELS; EM ALGORITHM; GAMES; HETEROGENEITY; LABOR; DISTRIBUTIONS; SIMULATION; LIKELIHOOD; FERTILITY; DECISIONS;

D O I：

10.1146/annurev-economics-111809-125038

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

Many discrete decisions are made with an eye toward how they will affect future outcomes. Formulating and estimating the underlying models that generate these decisions is difficult. Conditional choice probability (CCP) estimators often provide simpler ways to estimate dynamic discrete choice problems. Recent work shows how to frame dynamic discrete choice problems in a way that is conducive to CCP estimation and demonstrates that CCP estimators call be adapted to handle rich patterns of unobserved state variables.

引用

页码：363 / 394

页数：32

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