HOW RELIABLE ARE LOCAL PROJECTION ESTIMATORS OF IMPULSE RESPONSES?

• 成果类型: Article
• 署名作者: Kilian, Lutz; Kim, Yun Jung
• 署名单位: University of Michigan System; University of Michigan
• 刊物名称: REVIEW OF ECONOMICS AND STATISTICS
• ISSN/ISSBN: 0034-6535
• DOI: 10.1162/REST_a_00143
• 发表日期: 2011-11
• 页码: 1460-1466
• 关键词: confidence-intervals; Bootstrap Inference; autoregressions

摘要

We compare the finite-sample performance of impulse response confidence intervals based on local projections (LPs) and vector autoregressive (VAR) models in linear stationary settings. We find that in small samples, the asymptotic LP interval often is less accurate than the bias-adjusted bootstrap VAR interval, notwithstanding its excessive average length. Although the asymptotic LP interval has adequate coverage in sufficiently large samples, its average length still far exceeds that of bias-adjusted bootstrap VAR intervals with comparable accuracy. Bootstrap LP intervals (with or without bias correction) and asymptotic VAR intervals are shorter on average, but they often lack coverage accuracy in finite samples.