I currently using a random effects model for my panel data and my regression is as follows: Beta(t) = constant + Env Score(t-1) + Controls(t) + i.Industry + error

  1. The main independent variable Env.Score is lagged. When i calculate the Pearson correlation in my descriptive statistics, should I include the lagged version of the ENV Score as it is in the regression or just the ENV Score variable without being lagged?
  2. When I perform the random effects model, the first industry and the first year are ommited from my regression results. But this industry is my main one from my data, is there a way that I can still calculate the effect of the first industry and the first year on Beta?
  • $\begingroup$ Industry is a categorical variable and the first industry is the "reference level". See for example here, here, here... Since the first year is omitted as well, we know that you treat year as a categorical variable as well -- is that your intention? Also it's not clear what the random effects are in your regression. $\endgroup$
    – dipetkov
    Jun 7, 2022 at 0:14


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