The limiting power of autocorrelation tests in regression models with linear restrictions

Alan T.K. Wan (), Guohua Zou and Anurag Narayan Banerjee ()

Discussion Paper Series In Economics And Econometrics from University of Southampton, Economics Division, School of Social Sciences

Abstract: It 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.

New Economics Papers: this item is included in nep-ecm and nep-ets
Date: 2004-01-01
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Persistent link: http://EconPapers.repec.org/RePEc:stn:sotoec:0405

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