AUTOMATIC LAG SELECTION IN COVARIANCE-MATRIX ESTIMATION

• 成果类型: Article
• 署名作者: NEWEY, WK; WEST, KD
• 署名单位: University of Wisconsin System; University of Wisconsin Madison
• 刊物名称: REVIEW OF ECONOMIC STUDIES
• ISSN/ISSBN: 0034-6527
• DOI: 10.2307/2297912
• 发表日期: 1994
• 页码: 631-653
• 关键词: Heteroskedasticity

摘要

We propose a nonparametric method for automatically selecting the number of autocovariances to use in computing a heteroskedasticity and autocorrelation consistent covariance matrix. For a given kernel for weighting the autocovariances, we prove that our procedure is asymptotically equivalent to one that is optimal under a mean-squared error loss function. Monte Carlo simulations suggest that our procedure performs tolerably well, although it does result in size distortions.