A Small-Sample Correction for Testing for gth-Order Serial Correlation with Artificial Regressions

David Belsley

Computational Economics, 1997, vol. 10, issue 3, 197-229

Abstract: Monte Carlo experiments establish that the usual 't-statistic' used for testing for first-order dial correlation with artificial regressions is far from being distributed as a Student's t in small samples. Rather, it is badly biased in both mean and variance and results in grossly misleading tests of hypotheses when treated as a Student's t. (Similar distortions plague the familiar Durbin-Watson statistic.) Simply computed corrections for the mean and variance are derived, however, which are shown to lead to a transformed statistic producing acceptable tests. The test procedure is detailed and exemplar code provided. Citation Copyright 1997 by Kluwer Academic Publishers.

Date: 1997
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Working Paper: A Small-Sample Correction for Testing for gth-Order Serial Correlation with Artificial Regressions (1996)
Working Paper: A Small-Sample Correction for Testing for gth-Order Serial Correlation with Artificial Regressions
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