Recently, there is an emerging line of the study said that the traditional two-way fixed effect(TWFE) is failed in a lot of case because of the heterogeneous effects of laws over time, follow some paper Goodman-Bacon (2019), Chaisemartin, 2020.
Especially, Goodman, 2019 did a great job to decompose the single post-treatment dummy. In his note, he answered the question "Is DD wrong":
Not in general. The DD research design—comparing outcomes for groups whose treatment status changes to groups whose treatment status does not change—still can be a good idea. The DD specification—estimating the coefficient a single post-treatment dummy—is a bad idea when your treatment effects vary over time (get bigger with time since treatment). In this case, just summarize your findings in a different way—event-study or a linear trend-break, for instance.
My question here is, if I expect and argue that the treatment effects get smaller with time since treatment, so whether DD specification now is a bad idea?