Supporting Parallel Trends (The Effect, Videos on Causality, Ep 54)

Please visit www.theeffectbook.net to read The Effect online for free, or find links to purchase a physical copy or ebook.
The Effect is a book about research design and causal inference. How can we use data to learn about the world? How can we answer questions about whether X causes Y even if we can't run a randomized experiment? The book covers these things and plenty more. These videos are meant to accompany the book, although they can also be viewed on their own.
This video relates to material found in Chapter 18 of the book.
A version of this video without background music can be found here: • Supporting Parallel Tr...
Parallel trends is a key assumption in doing a difference-in-differences analysis. How can we use data to check whether that assumption is plausible and can be trusted? This video goes through a few different ways.

[@specfunctor]

Thanks for this great content!

[@siddharthkaushal5194]

great video, thank you! :)

[@samarth1906]

Great video! Just had a question as to why we're only adding the group fixed effects when testing the parallel trends assumption and not year fixed effects as well, thanks!

[@NickHuntingtonKlein]

You could add them (and if you imagined some sort of nonlinear shared trend combined with linear nonshared trends it might be a good idea) but in general in this test we want the time trend to show up in the time trend coefficients rather htan being absorbed by the time fixed effects.

[@samarth1906]

@@NickHuntingtonKlein Thanks! Could we also further relax parallel trends when testing for it by including covariates that vary across groups and time?

[@NickHuntingtonKlein]

@@samarth1906 Yes but be very careful how you do it, see my recent Substack post nickchk.substack.com/p/controls-in-difference-in-differences