The limiting power of autocorrelation tests in regression models with linear restrictions
AbstractIt is well known that the Durbin-Watson and several other tests for first-order autocorrelation have limiting power of either zero or one in a linear regression model without an intercept, and tend to a constant lying strictly between these values when an intercept term is present. This paper considers the limiting power of these tests in models with restricted coefficients. Surprisingly, it is found that with linear restrictions on the coefficients, the limiting power can still drop to zero even with the inclusion of an intercept in the regression. It is also shown that for regressions with valid restrictions, these test statistics have algebraic forms equivalent to the corresponding statistics in the unrestricted model.
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Bibliographic InfoPaper provided by Economics Division, School of Social Sciences, University of Southampton in its series Discussion Paper Series In Economics And Econometrics with number 0405.
Date of creation: 01 Jan 2004
Date of revision:
This paper has been announced in the following NEP Reports:
- NEP-ALL-2005-10-29 (All new papers)
- NEP-ECM-2005-10-29 (Econometrics)
- NEP-ETS-2005-10-29 (Econometric Time Series)
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