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Title stata.com didregress — Difference-in-differences ...

Difference-in-differences estimationDescriptionQuick startMenuSyntaxOptionsRemarks and examplesStored resultsMethods and formulasAcknowledgmentReferencesAlso seeDescriptiondidregressestimates the average treatment effect on the treated (ATET) from observational data bydifference-in-differences (DID) or difference-in- Difference-in-differences (DDD). TheATETof a binaryor continuous treatment on a continuous outcome is estimated by fitting a linear model with time andgroup fixed effects. TheDIDandDDDestimation performed bydidregresscan be applied to datacomprising repeated cross-sections in which different groups of individuals are observed at each theATET from observational data byDIDorDDDfor panel data. TheATETof a binary or continuous treatment on a continuous outcome is estimated by fitting a linearmodel with time and panel fixed startDIDestimate of theATET oftreat1on outcomey1modeled using covariatesx1andx2, andgrpvar1andtvarfixed effects, with the treatment occurring at thegrpvar1andtvarlevelsdidregress (y1 x1 x2) (treat1), group(grpvar1) time(tvar)As above, but compute wild cluster bootstrapp-values and confidence intervals withgrpvar1as theclustering variabledidregress (y1 x1 x2) (treat1), group(grpvar1) time(tvar) ///wildbootstrapAggregate

tvar must be a binary variable indicating observations subject to treatment or a continuous variable ... display of omitted variables and base and empty cells, and ... that are bias-corrected cluster robust using the degrees-of-freedom adjustment proposed byBell and McCaffrey(2002) (hc2), and that use bootstrap sampling done at the group level ...

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