POOR (WO)MAN'S BOOTSTRAP

• 成果类型: Article
• 署名作者: Honore, Bo E.; Hu, Luojia
• 署名单位: Princeton University; Federal Reserve System - USA; Federal Reserve Bank - Chicago
• 刊物名称: ECONOMETRICA
• ISSN/ISSBN: 0012-9682
• DOI: 10.3982/ECTA13465
• 发表日期: 2017
• 页码: 1277-1301
• 关键词: MOMENTS ESTIMATORS; generalized-method; TRADING PARTNERS; models; DYNAMICS; volumes

摘要

The bootstrap is a convenient tool for calculating standard errors of the parameter estimates of complicated econometric models. Unfortunately, the fact that these models are complicated often makes the bootstrap extremely slow or even practically infeasible. This paper proposes an alternative to the bootstrap that relies only on the estimation of one-dimensional parameters. We introduce the idea in the context of M and GMM estimators. A modification of the approach can be used to estimate the variance of two-step estimators.