4
$\begingroup$

Over 60 years ago Durbin and Watson suggested a testing procedure for assessing autocorrelation in regression relationships.The test is known to not work in the presence of lagged dependent variables, in which case Breusch-Godfrey test from the late 1970s applies. Any other known situations where the Durbin-Watson test should not be used?

$\endgroup$
  • $\begingroup$ Section 12.2 Testing for Serial Correlation of Wooldridge's Introductory Econometrics has a good discussion and has an implicit answer to the question: eco.uc3m.es/~jgonzalo/teaching/EconometriaII/… this is close to what I could tick as the accepted answer. Anyone willing to summarize? $\endgroup$ – Hibernating Feb 8 '14 at 3:24
2
$\begingroup$

The Durbin Watson test or dwtest is useful for checking the presence of first-order autocorrelation only. However, your time series might have higher-order autocorrelations as well. In that case Breusch-Godfrey test is used.

A similar argument holds true when you are working on a regression problem that doesn't involve a time series. In that case we can apply the same test to check the correlation in residuals.

| cite | improve this answer | |
$\endgroup$
  • $\begingroup$ lmtest::dwtest and car::durbinWatsonTest are particular implementations of the test that has been generalized to apply for lags of any order. For example, in JBES, April 1987, Vol. 5, No. 2 you may find this: "Following Vinod (1973), the Durbin-Watson(DW) test for autocorrelation at lag k is defined by..." $\endgroup$ – Hibernating Feb 8 '14 at 1:26

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.