TD_BREUSCH_GODFREY Function | Teradata Vantage - TD_BREUSCH_GODFREY - Teradata Vantage

TD_BREUSCH_GODFREY checks for the presence of serial correlation among the residual and error terms after running a regression associated with a fitted model. With respect to regression models, it is expected that there is no serial correlation among the error terms.

The Breusch-Godfrey test is used to determine if there is evidence of autocorrelation in the residuals of a model. Autocorrelation is correlation between the errors or residuals of a regression model, which means that the errors in the model are not independent. In other words, the value of an error at a given point in time is related to the values of the errors at earlier points in time.

TD_BREUSCH_GODFREY tests the null hypothesis that there is no autocorrelation in the residuals against the hypothesis that there is autocorrelation. The test is performed by regressing the residuals on their lagged values up to a certain number of lags, and then performing a chi-squared test on the residuals of the regression.

TD_BREUSCH_GODFREY is used in time-series analysis and econometrics, where it is important to ensure that the assumptions of the regression model are met. If autocorrelation is present in the residuals of a regression model, the standard errors of the estimates of the regression coefficients may be biased, leading to incorrect inference and predictions. Using TD_BREUSCH_GODFREY, researchers can identify potential problems with their regression model and correct them.