Hello everyone!
I'm doing an analysis of the impact of board composition (different types of diversity, etc) on company performance. As the data is in a panel structure (80 companies over 6 years) I intended to use xtreg.
Unfortunately, I am not very familiar with the generalized least square regression. I assume that as with every other regression type, you have to verify the model. Meaning check for: Multicollinearity, Autocorrelation, Non-linearity and Heteroscedasticity.
Reading through a number of studies, I learnt that for multicollinearity one uses the OLS model for VIFs and uses a correlation matrix as usual. Autocorrelation should be counteracted by the GLS regression, I assume. I did not find anything on non-linearity or heteroscedasticity and thus wanted to ask, if I need to check for these two criteria and how I can do so in Stata.
Thankful for any advice on how I could tackle this issue.
Best regards,
Simon
I'm doing an analysis of the impact of board composition (different types of diversity, etc) on company performance. As the data is in a panel structure (80 companies over 6 years) I intended to use xtreg.
Unfortunately, I am not very familiar with the generalized least square regression. I assume that as with every other regression type, you have to verify the model. Meaning check for: Multicollinearity, Autocorrelation, Non-linearity and Heteroscedasticity.
Reading through a number of studies, I learnt that for multicollinearity one uses the OLS model for VIFs and uses a correlation matrix as usual. Autocorrelation should be counteracted by the GLS regression, I assume. I did not find anything on non-linearity or heteroscedasticity and thus wanted to ask, if I need to check for these two criteria and how I can do so in Stata.
Thankful for any advice on how I could tackle this issue.
Best regards,
Simon
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