[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

st: Re: Newey-West robust errors

From   Kit Baum <>
To   Bruno Schroder <>
Subject   st: Re: Newey-West robust errors
Date   Sat, 21 Feb 2009 09:50:44 -0500


It is the case that if the only departure from iid errors is positive AR(1), the OLS standard errors will be downward biased relative to the correct standard errors. But in the presence of heteroskedasticity and autocorrelation, all we know is that the OLS standard errors are biased and inconsistent. They could be higher or lower than the HAC standard errors. A serious issue, though, is that tests for non-iid errors are sensitive to the maintained hypothesis that the model is specified properly. Residuals will be correlated, for instance, if an important variable is omitted from the model (in your case, y(-2)?) So consider those test results as a possible signal of misspecification. Use the RESET test (estat ovtest) and see what it says.

Best wishes

Kit Baum, Boston College Economics and DIW Berlin
An Introduction to Modern Econometrics Using Stata:

On Feb 20, 2009, at 22:28 , Bruno Schroder wrote:

Dear Professor Baum,
I`m an undergraduate student majoring in economics and have visited your awsome webpage recently searching for an answer. Is it possible that after correcting for autocorrelation in residuals the new standard errors get smaller than the usual OLS ones? It`s all about because I have running a regression of "y on y(-1) plus controls" (annual data) and through OLS many of the parameters are not statistical significant. Then, I`ve run tests for heteroskedasticity and autocorrelation, always rejecting the null. So I do not need to correct for these "problems", actually. But when I use HAC Standard Errors, those parameters become significant. Is there any problem?
I appreciate your comments.
Best regards,
Bruno Schroder

*   For searches and help try:

© Copyright 1996–2022 StataCorp LLC   |   Terms of use   |   Privacy   |   Contact us   |   What's new   |   Site index