Statistics MCQs, Data Analysis, Stat Software
Lecture notes about Heteroscedasticity, its consequences, detection, and remedy. Hetero or Heteroscedasticity is a violation of the OLS assumption of consistent variance.
To perform the Breusch-Pagan test for the detection of heteroscedasticity, use the data from the following file Table_11.3. Step 1: The estimated regression is $\hat{Y}_i = 9.2903 + 0.6378X_i$ Step 2: The residuals obtained from this regression are: $\hat{u}_i$ $\hat{u}_i^2$ $p_i$ -5.31307 28.22873 0.358665 -8.06876 65.10494 0.827201 6.49801 42.22407 0.536485 …
One important assumption of Regression is that the variance of the Error Term is constant across observations. If the error has a constant variance, then the errors are called homoscedastic, otherwise heteroscedastic. In the case of heteroscedastic errors (non-constant variance), the standard estimation methods become inefficient. Typically, to assess the …
To detect the presence of heteroscedasticity using the Park Glejser test, consider the following data. Year 1992 1993 1994 1995 1996 1997 1998 Yt 37 48 45 36 25 55 63 Xt 4.5 6.5 3.5 3 2.5 8.5 7.5 The step-by-step procedure for conducting the Park Glejser test: Step 1: …
The post is about “Heteroscedasticity Consistent Standard Errors and Variances. $\sigma_i^2$ are rarely known. However, there is a way of obtaining consistent estimates of variances and covariances of OLS estimators even if there is heteroscedasticity. White’s Heteroscedasticity Consistent Standard Errors and Variances White’s heteroscedasticity-corrected standard errors are known as robust …