Hi all,
I am writing some c++ code to automatically do OLS regression, however, it appears using the Breusch-Pagan and White test that the data is heteroskedastic. Based on this I then weighted the residuals via FGLS outlined in Introductory Econometrics: A Modern Approach (Jeffrey Wooldridge)
The question I have is, once you have obtained a revised regression using FGLS, how do you establish that the errors are homoscedastic and that the FGLS is a better fit? (I believe \(R^{2}\) is not valid under GLS?)
Many thanks,
Hob
I am writing some c++ code to automatically do OLS regression, however, it appears using the Breusch-Pagan and White test that the data is heteroskedastic. Based on this I then weighted the residuals via FGLS outlined in Introductory Econometrics: A Modern Approach (Jeffrey Wooldridge)
The question I have is, once you have obtained a revised regression using FGLS, how do you establish that the errors are homoscedastic and that the FGLS is a better fit? (I believe \(R^{2}\) is not valid under GLS?)
Many thanks,
Hob
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