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st: Difference in difference and non-linear regression model


From   Thomas Werner <thomas.werner@unibw.de>
To   statalist@hsphsun2.harvard.edu
Subject   st: Difference in difference and non-linear regression model
Date   Wed, 14 Nov 2012 17:26:18 +0100

Dear Statalisters

I want to see if a statutory minimum wage had any effect on the probability of price increases respectively decreases after its implementation.

The dataset I use contains among others monthly firm-level price (Y) state of business (S) and demand data (D) of business surveys. Most of the variables have three categories, whereby the answers are coded as 1 ("increased"), 0 ("not changed") and -1 ("decreased"). The independent variables are recoded as binary variables but there are also continuous control variables like capacity utilization.

I have to run a stereotyped ordered logit model because the parallel regression assumption of the ordered logit model is violated.
Actually I want to run a diff-in-diff model like this:

slogit = treat + post + treat*post + lag_price + D_increase + D_decrease + S_increase + S_decrease + material_price + ... + error

But I don’t know how to compute the marginal effect of the interaction term (treat*post) because the inteff command doesn’t work as a result of the trichotomic shape of the dependent variable and the margins command isn’t a viable alternative.

As far as I can see the interaction effect should be equal to the difference of cross differences
Is there a way to compute these effect with stata?

Best
Thomas Werner

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