Dear All,

I have a panel data for about 200 companies over 15 years and assume the following regression model:

dv= f(v1, v2, v1*v2)

where v2 is industry dummy (0 or 1); therefore, if I run the model with fixed effect model (xtreg dv v1 v2 v1*v2, fe) , v2 is omitted due to its time-constant nature. And I know in this case I can remove the v2 (industry dummy) in the model as the firm dummy takes care of the industry effect. But the thing is I'm interested in not only the interaction term of v1*v2, but also the coefficient on the v2, i.e., how different is my dependent variable between the industries.

If I run this analysis using a 'reg' command along with firm dummies, i.e., reg dv v1 v2 v1*v2 i.company, this produces results on the v2 (industry dummies), but I was wondering this approach is okay because there is a perfect multicollinearity between the v2 and i.company.

Does anyone have advice/suggestion in terms of the model specification or alternatives that I can take?

Thank you in advance!

I have a panel data for about 200 companies over 15 years and assume the following regression model:

dv= f(v1, v2, v1*v2)

where v2 is industry dummy (0 or 1); therefore, if I run the model with fixed effect model (xtreg dv v1 v2 v1*v2, fe) , v2 is omitted due to its time-constant nature. And I know in this case I can remove the v2 (industry dummy) in the model as the firm dummy takes care of the industry effect. But the thing is I'm interested in not only the interaction term of v1*v2, but also the coefficient on the v2, i.e., how different is my dependent variable between the industries.

If I run this analysis using a 'reg' command along with firm dummies, i.e., reg dv v1 v2 v1*v2 i.company, this produces results on the v2 (industry dummies), but I was wondering this approach is okay because there is a perfect multicollinearity between the v2 and i.company.

Does anyone have advice/suggestion in terms of the model specification or alternatives that I can take?

Thank you in advance!

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