Dear researchers,
I am using the generalized DID model “Two way-fixed effect”. I have more than two groups and more than two periods. The period of my study is from 2000 to 2019. There is an event has been happened in 2005. And, I am applying the unbalance data for a set of firms across the years.

The main is to examine the effect of the event on the dependent variable.

The code is
Code:
Xtreg Depv Firm_Age firm_size Event Fim_age*Event Firm_size*Event i.year, fe cluster (COMPANY)
Where:
Event: dummy variable coded one in the year of adoption and for all subsequent years, and zero otherwise.

All the independent variables are continuous variables and time-varying variables.

The thing is I need to assess the endogeneity issue in the above-mentioned regression. I have resorted to the literature, and I have found that the lagged dependent variable technique has been used to assess the endogeneity. However, I have found that Paul Allison has mentioned that using the lagged dependent variable in the mixed model usually leads to severe bias. Here is the link:
https://statisticalhorizons.com/lagg...dent-variables

However, I have used it and I have got different results from those that I have got in the above-regression.

Thus, is there any method that you can recommend assessing the endogeneity for the DID?

Many thanks in advance.