Review of Economic Studies Vol. 61 No. 4 1994
Automatic Lag Selection in Covariance Matrix Estimation
Abstract
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.
- DOI
- 10.2307/2297912
- Volume
- 61
- Issue
- 4
- Pages
- 631-653
- Language
- en
- Sources
- bibtex:phds-export.bib openalex crossref