The Performance of Robust Modification of Breusch-Godfrey Test in the Presence of Outliers

Autocorrelation problem causes unduly effects on the variance of ordinary least squares (ols) estimates. hence, it is very essential to detect the autocorrelation problem so that appropriate remedial measures can be taken. the breusch-godfrey (bg) test is the most popular and commonly used test for the detection of autocorrelation. since this test is based on the ols estimates, which are not robust, it is easily affected by outliers. in this paper, we propose a robust breusch-godfrey (mbg) test which is not easily affected by outliers. the results of the study indicate that the mbg test is more powerful than the bg test in the detection of autocorrelation problem.