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  "Description": "Implements the Path-Integrated Difference-in-Differences\n('PI-DiD') framework of Salavi (2026), which treats the\ntreatment effect as a trajectory tau(t) = c1(t) - c0(t) and\nintegrates the baseline-differenced gap over a post-treatment\nwindow to obtain a cumulative causal effect and a\npath-integrated average treatment effect on the treated,\ntogether with cluster-robust standard errors, confidence\nintervals, diagnostic plots, and the pre-treatment\nparallel-trends, grid-density, and anticipation-robustness\nchecks of section 5 of the companion paper. This approach\navoids the endpoint-subtraction bias that arises whenever a\ntransitory policy's effect has fully decayed by the evaluation\ndate, in which case the conventional static\ndifference-in-differences estimate can be zero even though the\ncumulative benefit delivered to treated units was strictly\npositive. Formerly distributed as a Stata package under the\nnames 'pidid' and 'pididplot'.",
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