Dear All:

I am writing to ask for a Difference-in-Difference question.

Usually in a standard DiD setting (as in Jeff Wooldridge's online lecture notes), there is a control group (in period 1 and period 2) and treatment group (becomes treated in period 2). The assumption one needs to check is the parallel "pre-trend" in the outcome variables.

However, in the setting of policy expansion, there is a treated group and control group in period 1, and the treated group remain treated in period 2 while the control group becomes treated in period 2. My idea of evaluating a policy expansion is to use a "reversed DiD". That means, we will need to check the parallel "post-trend" assumption instead. In addition, we will have to assume that the policy does not have a "time-accumulative" effect on the outcome variables.

Does my idea sound reasonable? Is this the way how people use DiD in evaluating policy expansion or is it just my own imagination?

I look forward to hearing from you! Thank you!

Best,
Long