Include covariates on which parallel trends should not condition? #178
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valentinyverse
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I would like to know if I can include covariates on which parallel trends are not conditioned.
My setting has no anticipation periods, only one group is treated and therefore I have only one time of treatment implementation, and I have an unbalanced panel. I use the function
att_gt
to estimate the effect of a policy change (from tracked classes to comprehensive classes) in a region on binary individual outcome variables (e.g. school dropout) and I condition the parallel trends assumption on several binary individual time-invariant covariates (e.g. female, nationality, own ability).Now I want to include another covariate (share of students with high ability in class) on which I don't want the parallel trends to be conditioned on. Further I'd like to get the estimate back for this continuous variable.
I am really unsure, if this even makes sense in this framework. The covariate has only one value per individual, hence is time-invariant.
The model I estimate is:
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