Hi,
I am using difference in difference method with the help of logit model. I have read this paper " Interaction term in logit and probit models" by Churnog Ai and Edward C. Nortan. In that paper they described that interaction effect requires computing Cross derivative and Cross difference. I have gone through this paper as well " The treatment effect, the cross difference, and the interaction term in nonlinear" by Patrick A. Phuani (2012). In which he described that in the case of non Linear difference in difference the treatment effect i.e the parameter of interest, is not a simple cross difference , but a difference between cross differences: it is the cross difference of the conditional expectation of the observed outcome minus the cross difference of the conditional expectation of the potential outcome without treatment and this difference in cross differences simplifies to the incremental effect of the coefficient of the interaction term. so that treatment effect has the same sign as the coefficient of the interaction effect.
I am using a two year paneI data (2004-05=0 and 2011-12 = 1). time variable is a discrete variable having value 1 and 0. mgnregadmy is dummy variable (treatment group = 1 and control group= 0) used the following command to compute DID in the case of Logit Model.
I have a doubt that, Is the treatment effect is measured by the interaction variable (mgnregadmy*time) or is it measured by the pairwise comparison of average marginal effect? if it is measured by the pairwise comparison of average marginal effect, then how can it be difference in difference estimator because DID includes the double differences. In this case is pairwise comparison of average marginal effect show the cross difference between two cross differences?
I am using difference in difference method with the help of logit model. I have read this paper " Interaction term in logit and probit models" by Churnog Ai and Edward C. Nortan. In that paper they described that interaction effect requires computing Cross derivative and Cross difference. I have gone through this paper as well " The treatment effect, the cross difference, and the interaction term in nonlinear" by Patrick A. Phuani (2012). In which he described that in the case of non Linear difference in difference the treatment effect i.e the parameter of interest, is not a simple cross difference , but a difference between cross differences: it is the cross difference of the conditional expectation of the observed outcome minus the cross difference of the conditional expectation of the potential outcome without treatment and this difference in cross differences simplifies to the incremental effect of the coefficient of the interaction term. so that treatment effect has the same sign as the coefficient of the interaction effect.
I am using a two year paneI data (2004-05=0 and 2011-12 = 1). time variable is a discrete variable having value 1 and 0. mgnregadmy is dummy variable (treatment group = 1 and control group= 0) used the following command to compute DID in the case of Logit Model.
Code:
logit Loan20 i.mgnregadmy##i. time RO5 ca2 ca3 education1 NPERSONS COPC, vce(robust)
Code:
margins mgnregadmy, dydx (time) pwcompare
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