Nonstationary dynamic models with finite dependence

• 成果类型: Article
• 署名作者: Arcidiacono, Peter; Miller, Robert A.
• 署名单位: Duke University; National Bureau of Economic Research; Carnegie Mellon University
• 刊物名称: QUANTITATIVE ECONOMICS
• ISSN/ISSBN: 1759-7323
• DOI: 10.3982/QE626
• 发表日期: 2019
• 页码: 853-890
• 关键词: Dynamic discrete choice; finite dependence; conditional choice probabilities; C33; C35

摘要

The estimation of nonstationary dynamic discrete choice models typically requires making assumptions far beyond the length of the data. We extend the class of dynamic discrete choice models that require only a few-period-ahead conditional choice probabilities, and develop algorithms to calculate the finite dependence paths. We do this both in single agent and games settings, resulting in expressions for the value functions that allow for much weaker assumptions regarding the time horizon and the transitions of the state variables beyond the sample period.