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I'm running an event study and calculate the mean cumulative average return and the mean buy-and-hold abnormal return.

The t-test is straightforward:
t_CAR = (Mean(CAR_it)) / (sigma(CAR_it) / sqrt(n)) ; and

t_BHAR = (Mean(BHAR_it)) / (sigma(BHAR_it) / sqrt(n))

but how many degrees of freedom do I use for the critical t-values?

I would assume its df= number of CAR - 2 ?

(Note that Mean(CAR_it) and Mean(BHAR_it) are the sample averages and sigma(CAR_it) and sigma(BHAR_it) are the cross-sectional sample standard deviatons of abnormal returns for the sample of n firms (Barber/Lyon 1997))

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In R there is a number of built in event study library routines that are very comprehensive, I have really only had a cursory glance at estudy2 libray link here https://cloud.r-project.org/web/packages/estudy2/estudy2.pdf but here is 2 others https://cloud.r-project.org/web/packages/crseEventStudy/crseEventStudy.pdf; and https://cran.r-project.org/web/packages/EventStudy/EventStudy.pdf They are all thorough and comprehensive and estudy2 is not difficult to implement, I have not tried the others.

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  • $\begingroup$ estudy2 is now deprecated on cran as is crseEventStudy, you can only run old packages on old versions of R, or rstudio. $\endgroup$ Apr 14 at 7:44

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