cv.treat option/error AND comparison to gsynth

[pbritteon]

Hi Yiqing. Thanks for referring me to the fect package earlier. It looks like another great resource!

I have two questions about the fect and gsynth packages...

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The first is about an error message that I get when running the ife model using the fect package on a balanced panel of 10 treatment units (all treated in the same month), 150+ control units, 108 time points (60 pre, 48 post)...

The code that I run is...

out.ife <- fect(ddays_social ~ D_gm, data = data, method = "ife", index = c("id","time"), force = "two-way", CV = TRUE, r = c(0, 5), se = TRUE, nboots = 100, parallel = TRUE, seed = 1234)

The error reads...
Error in cv.sample(II, D, rm.count, cv.nobs, cv.treat, cv.donut) :
Too few observations are valid for cross-validation. Try setting the option cv.treat to FALSE.

What does the cv.treat option specify? When I specify cv.treat = FALSE the model runs but I am not sure what this is doing and why I need to specify the option.

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Secondly, I have tried running the same model using the gsynth command...

out.gsynth <- gsynth(ddays_social ~ D_gm, data = data, index = c("id","time"), EM = TRUE, force = "two-way", CV = TRUE, r = c(0, 5), se = TRUE, inference = "parametric", nboots = 100, parallel =TRUE, seed = 1234)

The gsynth model identifies 2 factors from the cross-validation process.

In comparison, the fect ife model above (with cv.treat = FALSE) identifies 3 factors from the cross-validation process.

Do you know why the two packages identify a different number of factors in this scenario? All I can think of is that it is to do with the cv.treat option as discussed above... but I am probably missing something.

P.S. The models estimate the same results when fixing the number of factors (e.g. specifying CV = FALSE and r=c(2) )

[xuyiqing]

Could you email Ziyi and CC me. That may be easier.

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On Wed, May 26, 2021 at 9:08 AM pbritteon ***@***.***> wrote: Hi Yiqing. Thanks for referring me to the fect package earlier. It looks like another great resource! I have two questions about the fect and gsynth packages... xxxxxxxxxxxxxxxxxxxxxxxx The first is about an error message that I get when running the ife model using the fect package on a balanced panel of 10 treatment units (all treated in the same month), 150+ control units, 108 time points (60 pre, 48 post)... The code that I run is... out.ife <- fect(ddays_social ~ D_gm, data = data, method = "ife", index = c("id","time"), force = "two-way", CV = TRUE, r = c(0, 5), se = TRUE, nboots = 100, parallel = TRUE, seed = 1234) The error reads... Error in cv.sample(II, D, rm.count, cv.nobs, cv.treat, cv.donut) : Too few observations are valid for cross-validation. Try setting the option cv.treat to FALSE. What does the cv.treat option specify? When I specify cv.treat = FALSE the model runs but I am not sure what this is doing and why I need to specify the option. xxxxxxxxxxxxxxxxxxxxxxx Secondly, I have tried running the same model using the gsynth command... out.gsynth <- gsynth(ddays_social ~ D_gm, data = data, index = c("id","time"), EM = TRUE, force = "two-way", CV = TRUE, r = c(0, 5), se = TRUE, inference = "parametric", nboots = 100, parallel =TRUE, seed = 1234) The gsynth model identifies 2 factors from the cross-validation process. In comparison, the fect ife model above (with cv.treat = FALSE) identifies 3 factors from the cross-validation process. Do you know why the two packages identify a different number of factors in this scenario? All I can think of is that it is to do with the cv.treat option as discussed above... but I am probably missing something. P.S. The models estimate the same results when fixing the number of factors (e.g. specifying CV = FALSE and r=c(2) ) — You are receiving this because you are subscribed to this thread. Reply to this email directly, view it on GitHub <#19>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AB2PKGDERFDADF4G4464WITTPUMGBANCNFSM45SMNZCA> .

[pbritteon]

Thanks Yiqing. Will do