Robust autocorrelation testing in multiple linear regression
It is very essential to detect the autocorrelation problem due to its responsibility for ruining the important properties of Ordinary Least Squares (OLS) estimates. The Breusch-Godfrey test is the most commonly used method for autocorrelation detection. However, not many statistics practitioners awa...
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| Main Authors: | , |
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| Format: | Article |
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2023
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| Institution: | Universiti Tenaga Nasional |
| Summary: | It is very essential to detect the autocorrelation problem due to its responsibility for ruining the important properties of Ordinary Least Squares (OLS) estimates. The Breusch-Godfrey test is the most commonly used method for autocorrelation detection. However, not many statistics practitioners aware that this test is easily affected by high leverage points. In this paper, we proposed a new robust Breusch-Godfrey test which is resistant to the high leverage points. The results of the study signify that the robustified Breusch-Godfrey test is very powerful in the detection of autocorrelation problem with and without the presence of high leverage points. |
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