Extending the difference-in-differences (DID) to settings with many treated units and same intervention time: Model and Stata implementation

Giovanni Cerulli

2019 Stata Conference from Stata Users Group

Abstract: The difference-in-differences (DID) estimator is popular to estimate average treatment effects in causal inference studies. Under the common support assumption, DID overcomes the problem of unobservable selection using panel, time, and/or location fixed effects, and the knowledge of the pre/post intervention times. New developments of DID have been recently proposed: (i) the Synthetic Control Method (SCM) applies when a long pre- and post-intervention time series is available, only one unit is treated, and intervention occurs in a specific time (implemented in Stata via SYNTH by Hainmueller, Abadie, Dimond, 2014); (ii) an extension to binary time varying treatment with many treated units, have been also proposed and implemented in Stata via TVDIFF (Cerulli and Ventura, 2018). However, a command to accommodate a setting with many treated units and same intervention time is still lacking. In this presentation, I propose a potential outcome model to accommodate this latter setting, and provide a Stata implementation via the new Stata routine FTMTDIFF (standing for fixed-time multiple treated DID). I will finally set some guidelines for future DID developments.

Date: 2019-08-02
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Persistent link: https://EconPapers.repec.org/RePEc:boc:scon19:26

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