Newey, Whitney K.; West, Kenneth D. Automatic lag selection in covariance matrix estimation. (English) Zbl 0815.62063 Rev. Econ. Stud. 61, No. 4, 631-653 (1994). Summary: 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. Cited in 4 ReviewsCited in 180 Documents MSC: 62M10 Time series, auto-correlation, regression, etc. in statistics (GARCH) 62G05 Nonparametric estimation Keywords:time series models; number of autocovariances; heteroskedasticity; autocorrelation consistent covariance matrix; mean-squared error loss; Monte Carlo simulations PDFBibTeX XMLCite \textit{W. K. Newey} and \textit{K. D. West}, Rev. Econ. Stud. 61, No. 4, 631--653 (1994; Zbl 0815.62063) Full Text: DOI Link