CSDID (Bootstrap C.I. vs. Asymptotic normal C.I.)

[Marlene Fiesole]

Hi,

I recently started using the CSDID command with the agg(event) option, namely event aggregation.
I would like to have the usual event plot with the resulting coefficients and the Wild Boostrap Confidence intervals.
I know that an easy way would be to use csdid_plot,but since the command has not many options to personalize the graph (e.g. decide how many leads and lags to include) I decided to opt for the event_plot command. My main issue is that event_plot doesn't graph the wild bootstrap confidence intervals but the default asymptotic normal ones.

Two main questions:
1) Is there an easy way to obtain an event plot with wild boostrap Confidence intervals and decide how many lags/leads to show?
2) If Callaway Sant'Anna 2021 suggest the usage of wild boostrap, when and why should we think to use asymptotic normal confidence intervals that are default in CSDID?

Thanks in advanced for your help!

[FernandoRios]

1. It is better to use csdid to create the attgts and save the rifs then create the event plots with the option window
csdid_stat event, window(#1 #2)
then use csdid plot
2. this are two different things All together
If you are concerned about multiple testing adjustment
then wild bootstrap is better.
other wise asymptotic CI is what other papers do already
f

[Marlene Fiesole]

Hi Fernando,

thanks a lot, this really helps!

I have another question related to csdid_plot.

Opposed to other commands (e.g. event_plot) csdid_plot seems to estimate also the coefficient and confidence intervals for the period before treatment, usually referred to as "reference period" in t = g-1, where g is the time where treatment switched on.

Could it be that actually it is omitting the reference period directly and plotting only the other coefficients? This latter option would make more sense to me.

How should I interpret this?

Once again thanks a lot for your help and time
Marlene

[FernandoRios]

It’s not cadid_plot
you need to estimate the model with long2 option

[Marlene Fiesole]

Thanks a lot!

[Melody Burns]

It’s not cadid_plot
you need to estimate the model with long2 option

If long2 option is not used, how do we interpret the results in the csdid_plot?

[FernandoRios]

the -pre-treatment- are SHORT differences. If even one is Significant, there is a violation of PTA.
For Post-treatment, interpretation is as usual

[Melody Burns]

Thank you!