  We consider a general difference-in-differences model in which the treatment
variable of interest may be non-binary and its value may change in each period.
It is generally difficult to estimate treatment parameters defined with the
potential outcome given the entire path of treatment adoption, because each
treatment path may be experienced by only a small number of observations. We
propose an alternative approach using the concept of effective treatment, which
summarizes the treatment path into an empirically tractable low-dimensional
variable, and develop doubly robust identification, estimation, and inference
methods. We also provide a companion R software package.
