I am very confused about the output of my regressions.
- First of all, I am not even sure if I could divide my sample as I did, meaning that by subsampling as I did the variable ESG score is both criteria for the division as well as an explanatory variable.
- Then, I am not sure about the best way to interpret the coefficients and their probabilities. For example, the variable "Size", "Blockholding", "Forecast bias" and "Forecast dispersion" are not significant in the regression that includes the Full Sample neither in the subsample that only includes observations with low ESG scores. Nevertheless, those variables become statistically significant in the subsample containing the observations with a high ESG score. How can I interpret those results? Do they even have interpretation possible?
Note: I already have performed the Hausman test to check if the fixed-effects model was the most appropriate method, which it seems to be. But, I did not test yet for endogeneity concerns.
- So, this confusing output may be related to endogeneity ? Or, it may be a sign that my data lacks of some quality?
In any case, thank you for your attention and for any help you can offer!