I am running a Diff-in-Diff analysis about the triggering of a policy that once triggered bans a certain action for 6 months.
I have run the analysis considering only pre and post period, including in the post-period also the observations that are after the 6-month period, that is, when the ban was actually released.
Now I want to run a robustness check and I want to consider the fact that after the 6-month period the ban is gone.
How can I do this?
I thought I could simply change my EVENT vector, which had a dummy equal $0$ for pre-treatment and $1$ for post-treatment. Could I just change this and do:
$0$ for pre-treatment, $1$ for post-treatment, $0$ for released-treatment.
It seems wrong to me. isn't it? should I then change also the treatment vector?
Best Answer
The choice depends on whether you expect a lingering effect in the released-from-treatment period. This expectation can come from theory or domain expertise.
If that is sensible in your setting, then you should have two separate post dummies and two treated-post interactions. The two interaction coefficients will allow the effect to vary in the two post-treatment regimes.
The coding scheme you propose would be suitable if you expect the effect to go away immediately (like a light switch being turned off).