A very common assumption of DiD is parallel pre-trend satisfaction. And when we subsample, we need to make sure the parallel trend assumption of the subsample also need to be statistically satisfied. One way to circumvent it is to use DDD (Difference-in-Differences-in-Differences).

For example, the setting is to examine the impact of anti-corruption laws on firms' asset growth in a staggered setting (laws being implemented differently among countries). Afterward, I want to examine the difference between the impact of laws on asset growth in developed and developing countries. If I subsample, I need to test the parallel trend of the developed and developing group- separately. However, if I use DDD, it would be easier that I just need to add the interaction into the regression. But I am wondering whether I need to test any further parallel trend assumption here ? I tested the parallel assumption already for my whole sample.