Dear Statalisters,
I have differences-in-differences setting where I have multiple treatments that occur at different times for different treated units. My main specification is the following one:
Y_it= β_1 Post_it + δi + γt+ u_it where Post_it is the value of treatment for application i at week t, and δi and γt are application and time fixed effect parameters that are estimated.

I use following commands to estimate the above specification:
Code:
xtpqml downloads post timefe*, fe i(app) cluster(app)
and also:
Code:
xtreg ln(downloads + 1) post timefe*, fe vce(cluster app)
However, although the number of observations are the same, results are very different: while I get a positive and significant coefficient (0.464) on the post variable in the first specification, I get a negative and significant coefficient in the second specification (-0,13)

My dependent variable has the mean of 3.53, standard deviation of 16.7. Negative binomial (NB) fits better than Poisson specification, however given that no true fixed-effect estimator has yet been proposed in the NB, I use Poisson.

Which specification I have to use?