Panel Data, dummy variables omitted because of collinearity

[Clara Gallego]

Hello Statalist users,

We are using panel data to examine the effect of board gender diversity (variable Nmuj) on environmental performance (variable IndRU) for 6 years (2015-2020). A fixed effects model is estimated using an international sample of listed tourism companies but we are including year, region and activity as dummies and region and activity dummies are omitted because of collinearity. Although, if we estimate a random effects model, only one dummy of each type is omitted to protect us from the dummy trap. What can we do to solve the omission of region and activity dummies in the fixed effects model? In case of not being able to solve it, would it be correct to present this results or are they biased?

Following you can find the commands.

First, we create the dummy variables.

forvalues year=2015/2020 {
gen yr`year'a=year>=`year'
}

forvalues REGIONID=1/5 {
gen reg`REGIONID'a= REGIONID>=`REGIONID'
}

forvalues TRBCACTIVITYID=1/4 {
2. gen act`TRBCACTIVITYID'a= TRBCACTIVITYID>=`TRBCACTIVITYID'
3. }

Then , we specify the model and run the regression (fe – fixed effects and re random effects)

xtset id year
xtreg IndRU yr2015a-yr2020a reg1a-reg5a act1a-act4a Nmuj B_SIZE, fe
xtreg IndRU yr2015a-yr2020a reg1a-reg5a act1a-act4a Nmuj B_SIZE, re

This is the matrix of correlation between the dummies variables, the dependent variable (IndRU) and the independent variables (Nmuj and B_SIZE).

Thank you in advance.
Clara-Gallego.