ESTIMATION OF DYNAMIC DISCRETE CHOICE MODELS BY MAXIMUM LIKELIHOOD AND THE SIMULATED METHOD OF MOMENTS

• 成果类型: Article
• 署名作者: Eisenhauer, Philipp; Heckman, James J.; Mosso, Stefano
• 署名单位: University of Chicago; University of Chicago
• 刊物名称: INTERNATIONAL ECONOMIC REVIEW
• ISSN/ISSBN: 0020-6598
• DOI: 10.1111/iere.12107
• 发表日期: 2015
• 页码: 331-357
• 关键词: statistical properties; borrowing constraints; high-school; uncertainty

摘要

We compare the performance of maximum likelihood (ML) and simulated method of moments (SMM) estimators for dynamic discrete choice models. We construct and estimate a simplified dynamic structural model of education that captures some basic features of educational choices in the United States in the 1980s and early 1990s. We use estimates from our model to simulate a synthetic data set and assess the ability of ML and SMM to recover the model parameters on this sample. We investigate the performance of alternative tuning parameters for SMM.