From a description of DiD method of Borusyak,2020 , I saw that
pretrends(integer): if some value k>0 is specified, the command will performs a test for parallel trends, by a separate regression on nontreated observations only: of the outcome on the dummies for 1,...,k periods before treatment, in addition to all the FE and controls. The coefficients are reported as pre1,...,prek. The Wald statistic, pvalue, and degrees-of-freedom as reported in e(pre_chi2), e(pre_p), and e(pre_df) resp.
- Use a reasonable number of pre-trends, do not use all of the available ones unless you have a really large never-treated group. With too many pre-trend coefficients, the power of the joint test will be lower.
I am wondering how to explain the bold sentence. In another word, why joint null test has less power when there are more coefficients involve?