We know that this regression suffers from autocorrelation.
Once again let us return to our wages-productivity regression (12.5.1). Therefore, if a sample is reasonably large, one should use the Newey-West procedure to correct OLS standard errors not only in situations of autocorrelation only but also in cases of heteroscedasticity, for the HAC method can handle both, unlike the White method, which was designed specifically for heteroscedasticity. But in large samples we now have a method that produces autocorrelation-corrected standard errors so that we do not have to worry about the EGLS transformations discussed in the previous chapter. But it is important to point out that the Newey-West procedure is strictly speaking valid in large samples and may not be appropriate in small samples. We will not present the mathematics behind the Newey-West procedure, for it is involved.45 But most modern computer packages now calculate the Newey-West standard errors.
The corrected standard errors are known as HAC (heteroscedasticity- and autocorrelation-consistent) standard errors or simply as Newey-West standard errors. Instead of using the FGLS methods discussed in the previous section, we can still use OLS but correct the standard errors for autocorrelation by a procedure developed by Newey and West.44 This is an extension of White's heteroscedasticity-consistent standard errors that we discussed in the previous chapter.
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