I was working on a simple multi period diff -in diff . I have a policy implemented at the state level so the diff in diff is clustered by state.
Yst = a + B1Xst+ B2 (Treats) + B3(Postt) + B4Year + B5(Post * Treat) + est
I found no statistically significant effect and one of my explanations was that the treatment group was too small, and that the treatment effect is too small to be detected at the state level with proper precision. Power analysis by simulation (varying the size of the treatment group) seems the best way to back up my claim. I've learned on my own about simulation and am near the point of writing my data generating process, but have a few concerns:
1) Is there a package that would make this easy?
2) Can I use runiform() for treat / post? Do I have to make treatment correlated with X (I would think not since this is taken care of by the treat group dummy)?
2) How can I ensure that my post treatment variable is conditional on being in the treatment group?
4) Is there literature on this type of simulation?
Best Regards,
Esteban Fernandez
Yst = a + B1Xst+ B2 (Treats) + B3(Postt) + B4Year + B5(Post * Treat) + est
I found no statistically significant effect and one of my explanations was that the treatment group was too small, and that the treatment effect is too small to be detected at the state level with proper precision. Power analysis by simulation (varying the size of the treatment group) seems the best way to back up my claim. I've learned on my own about simulation and am near the point of writing my data generating process, but have a few concerns:
1) Is there a package that would make this easy?
2) Can I use runiform() for treat / post? Do I have to make treatment correlated with X (I would think not since this is taken care of by the treat group dummy)?
2) How can I ensure that my post treatment variable is conditional on being in the treatment group?
4) Is there literature on this type of simulation?
Best Regards,
Esteban Fernandez
