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Abadie’s semiparametric difference-in-differences estimator


  • Kenneth Houngbedji

    () (Paris School of Economics)


The difference-in-differences estimator measures the effect of a treatment or policy intervention by comparing change over time of the outcome variable across treatment groups. To interpret the estimate as a causal effect, this strategy requires that, in the absence of the treatment, the outcome variable followed the same trend in treated and untreated groups. This assumption may be im- plausible if selection for treatment is correlated with characteristics that affect the dynamic of the outcome variable. In this article, I describe the command asdid, which implements the semiparametric difference-in-differences (SDID) estimator of Abadie (2005, Review of Economic Studies 72: 1–19). The SDID is a reweigh- ing technique that addresses the imbalance of characteristics between treated and untreated groups. Hence, it makes the parallel trend assumption more credible. In addition, the SDID estimator allows the use of covariates to describe how the average effect of the treatment varies for different groups of the treated population.

Suggested Citation

  • Kenneth Houngbedji, 2016. "Abadie’s semiparametric difference-in-differences estimator," Stata Journal, StataCorp LP, vol. 16(2), pages 482-490, June.
  • Handle: RePEc:tsj:stataj:y:16:y:2016:i:2:p:482-490

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    Cited by:

    1. Cecilia Navarra, 2017. "Contracts between smallholders and private firms in Mozambique and their implications on food security," WIDER Working Paper Series 197, World Institute for Development Economic Research (UNU-WIDER).


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