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I did a Panel data regression with 4,000 U.S. firms of 12 different industries over a period of 20 years. I also included several control variables and controlled for the year and industry effects. While I am happy with the results, I want to dive into the results per industry. Therefore, I ran the regression per industry. Now I am doubting whether I need to control for Industry effects again.

Could someone help me with this?

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Let us say there are 10 industries indexed by $j=1,\dotsc,10$. From what I understand/imagine, after an initial linear regression with industry and year fixed effects, you made 10 additional regressions where you restricted the regression to each industry. Basically, your industry fixed-effect is absorbed by the constant, so this is not a worry.

Yet, a better design is to make only one additional regression where your variable of interest is interacted with all the industry dummies (and you still have the industry dummies).

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  • $\begingroup$ Thank you for your answer! I do get your point. So you suggest that I need to manually compute the industry fixed effect by including 10 industry dummies. What I a proper way to do this? The current formula is: Y = ß1 + ß2Climate Change + Control variables + Fixed effects + e. Can I simply add 10 dummies, e.g. for agriculture, which will have a value of 1 for all agricultural firms and so on? $\endgroup$ – Julian Dec 21 '19 at 20:04
  • $\begingroup$ Let us call C your variable of interest, and D_j your 10 industry dummies. I suggest that you add the following variables: C * D_j. They enable to see the specific impact of C for each industry. One gets: $Y=\beta_0 + \beta_1 C + \sum \beta_j C*D_j + \beta cov + fixed effects$ $\endgroup$ – Alex. C-L - Reinstate Monica Dec 23 '19 at 6:39
  • $\begingroup$ I get it! Thank you! $\endgroup$ – Julian Dec 23 '19 at 13:17

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