Pedro H.C. Sant'Anna "Difference-in-Differences with Multiple Time Periods"

DiD Reading Group Meeting #3 from May 14, 2021 (taylorjwright.github.io/did-r....
Pedro H.C. Sant'Anna presents his paper "Difference-in-Differences with Multiple Time Periods" (with Brantly Callaway) (pedrohcgs.github.io/files/Cal....
Slides can be found here: pedrohcgs.github.io/files/Cal...
Example code using did in R:

[@wenjieli8514]

Extremely useful! It is such a pleasure to enjoy those viedos. Thanks a lot for the work.

[@cheriseregier4729]

This was such a helpful video; Pedro is so clear!

[@cheriseregier4729]

Two quick questions: 1. If I am filtering my sample population to better capture the target demographic of the policy that I am evaluating, is this considered conditioning the parallel trends assumption on a set of pre-treatment covariates? 2. I am a bit confused about post-treatment parallel trends. If one of my treatment groups is negatively impacted by the policy, whereas the rest are positively impacted, is this a volition of this assumption?

[@hwei9502]

Thank you for uploading this great video!

[@taylorwright3880]

Thanks for watching, glad you found it useful!

[@begumozdemiroluk865]

Thank you for this helpful video!

[@petraszepesi106]

Hello, thank you for the video. I've been trying to replicate this methodology but I'm having issues with defining the gvar and get an error message when I run the code. I currently have a dummy for that variable, indicating when a treatment was implemented. Instead of having a value of 1 or 0 for when the treatment was implemented, how should my variable be coded in my dataset? I would really appreciate any advice! Thank you so much!

[@gesteira_pedro]

Hi Petra, hope you solved your issue. If not, the group variable is an id for assign each entry to a group, it isn't a dummy. For example: Say i have 100 entries, each entry is a individual. The first 50 represents the group that's treated in 2004. The last 50 represents the group that's treated in 2005. In this case, we would have two groups: group 1, all the entries that's treated in 2004 and group 2, all the entries that's treated in 2005. Hope it could help you or anyone with the same issue.

[@robinkim5685]

How does he have ATT on g-1 time period when g-1 is the base period that he compares to?

[@mafe3006]

This is extremely useful. Do you have the link for the example code using did in R?

[@taylorwright3880]

It's been a little while since I looked at it, but I believe the code I had used can be found here: github.com/taylorjwright/did_reading_group/blob/main/callaway_santanna/callaway_santanna_castle.R You can also see some examples from Pedro and Brant in their vignette: bcallaway11.github.io/did/articles/did-basics.html#other-features-of-the-did-package

[@mafe3006]

@@taylorwright3880 Thank you so much! your answer was so fast! :)

[@JasmineAllyson]

@@taylorwright3880 Hi, the code doesn't work at line 76-80. The error is Error in pre_process_did(yname = yname, tname = tname, idname = idname, : data[, tname] must be numeric

[@taylorwright3880]

@@JasmineAllyson Thanks for letting me know, I'll look into that and see what's going on!

[@sgeorg80]

👍

[@JMRG2992]

Thank you for this. However, I must appoint that the estimator does fail when we have a common year for the treatment intervention for all treated units. Secondly, the explanation of how to define gvar is really poor in both the code and the video

[@stephenclark9917]

Thanks for this presentation - it complements well your paper. I have one question, does the 'not yet treated' group include cases that are 'never treated'? Also, a slight typo on slide 20, missing a '['.

[@dr.kingschultz]

AS far as I can tell you should dived them up and yes they can be part of the group

[@annh2022]

hey @Taylor Wirght, where can we find the example code? it dissapeared from the video description

[@user-iw7cf3os8v]

What is a propensity score... I am lost from there