I am trying to regress a dynamic binary fixed-effects model of the form

\[ y_{it} = \alpha_i + y_{it-1}*z_{it-1} + X_{it}+u_{it} \]

I am using a short balanced panel of 8 periods and about 8000 individuals with very minor attrition over the years. y_it is a binary response variable and z_it is a treatment. My theoretical model suggests a variable state-dependance for y_it based on the treatment variable z_it, and hence I want to interact the two terms in my regression. Given the binary dependent variable and the dynamic nature of the model, I am trying to estimate it using the Conditional Maximum Likelihood methods by Bartolucci and Nigro (2010) The authors have recently released a stata and R module called "cquad" that can estimate these types of models. The structure of the cquad code is very simple and, for the non-interacted version of my model, goes like this
The code automatically adds the lagged dependent variable and estimates the model. It has no options to manually add the lagged dependent variable and hence an option for me to interact it with some other variable. I was hoping if someone could help me with this.

Thanks Soumya

\[ y_{it} = \alpha_i + y_{it-1}*z_{it-1} + X_{it}+u_{it} \]

I am using a short balanced panel of 8 periods and about 8000 individuals with very minor attrition over the years. y_it is a binary response variable and z_it is a treatment. My theoretical model suggests a variable state-dependance for y_it based on the treatment variable z_it, and hence I want to interact the two terms in my regression. Given the binary dependent variable and the dynamic nature of the model, I am trying to estimate it using the Conditional Maximum Likelihood methods by Bartolucci and Nigro (2010) The authors have recently released a stata and R module called "cquad" that can estimate these types of models. The structure of the cquad code is very simple and, for the non-interacted version of my model, goes like this

Code:

xi: cquadbasic y_it id z_[it-1] X_it

Thanks Soumya

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