First release.
gmm_staggered(), replacing the earlier
gmm_staggered_I(), gmm_staggered_II() and gmm_staggered_III(). The
covariance model is chosen with weighting, one of "pooled_toeplitz",
"cohort_toeplitz" or "unrestricted" (GMM-T, GMM-HT and GMM-U in the
paper).did package convention: yname, tname,
idname, gname.never_treated = NULL detects a never-treated group automatically,
replacing has_nt = FALSE.staggered_gmm with print, summary,
coef, vcov and confint methods.gmm_j_test(): the serial-correlation robust over-identification test
of parallel trends and no anticipation, in full-set and local-pre-window
forms.CW (treated-observation weighting,
as used throughout the paper) and EW (cohort-equal weighting).NA with
identified = FALSE, never as an estimated zero, and are excluded from
the parameter vector so that partial identification no longer disables the
efficient weighting for every other cell.max_iter now defaults to 100: the
iteration can converge linearly at a slow rate, and sim_panel under
weighting = "cohort_toeplitz" needs 86 steps.weighting = "unrestricted", because the returned estimates are then the
identity-weighted seed rather than a GMM estimate under the requested
weighting. The warning reports how many independent moment directions the
estimated weight supported, against the number of effects to identify.
Merely failing to converge after a weighted step did run continues not to
warn under "unrestricted", where it is routine.beck_banks documentation now records its CC BY 4.0 licence and the
thirteen always-treated states it contains.