Question

The difference-in-differences (DID) estimator is one of the most popular tools for applied research in economics to evaluate the effects of public interventions and other treatments of interest on some relevant outcome variables. The conventional DID estimator requires that, in the absence of the treatment, the average outcomes for the treated and control groups would have followed parallel paths over time. Can you think of a situation where this assumption would not necessarily hold?  Why is the “parallel trend” assumption so important?

Answer 1

Answer) Difference in difference method is used to mimick the experiment condition and further use it to observe the differential impact between the treatment and the control group. This assumption of difference in difference methodology falls flat in the case of :

1. Omitted variable bias
2. Both the direction and magnitude of regression coefficient changes after a significant amount of time.

The assumption of parallel trend line is vital as it helps to consolidate the assumption of differential impact between the controlled group and a treatment group. For instance, to check the efficiency of a drug to control Blood pressure. The actual dose is given to a certain group and other group is given just a placebo.