CFA Level 2 Exam 2025 – 400 Free Practice Questions to Pass the Test

The Breusch-Godfrey test is specifically designed to detect serial autocorrelation in the residuals of a regression model. Autocorrelation occurs when the residuals are correlated across different time periods, which can violate the ordinary least squares (OLS) assumption that residuals should be independent of one another. If this assumption is violated, it can lead to inefficient estimates and invalid statistical inferences.

This test provides a way to formally assess whether residuals from a regression analysis exhibit this undesirable property. By identifying serial autocorrelation, the test helps to ensure the validity of the regression analysis and its results, particularly in time series data. Addressing any detected autocorrelation is crucial for ensuring that the model's predictions and inferences about relationships among variables are reliable.

Understanding that the other options focus on different aspects of regression analysis elaborates why they do not apply here. Although multicollinearity impacts the estimates of coefficients, it does not directly relate to this test's purpose. The goodness-of-fit pertains to how well the model explains the variance, which is not the main concern of the Breusch-Godfrey test. Finally, the stability of regression coefficients over time is assessed through other methods, such as Chow tests, rather than through the Breusch-God