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Nonparametric synthetic control method for program evaluation: model and Stata implementation

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  • Giovanni Cerulli

    (Research Institute on Sustainable Economic Growth, Rome)

Abstract

Building on the paper by Abadie and Gardeazabal (2003) and Abadie, Diamond, and Hainmueller (2010), I extend the Synthetic Control Method for program evaluation to the case of a nonparametric identification of the synthetic (or counterfactual) time pattern of the treated unit (for instance: a country, region, city, etc.). I discuss the advantages of this method over the one provided by previous authors and apply them to the same example of Abadie, Diamond, and Hainmueller (2010), i.e. the study of the effects of Proposition 99, a large-scale tobacco control program that California implemented in 1988. I will also show the use of the Stata command synth provided by Abadie, Diamond, and Hainmueller (2014) and that of npsynth for nonparametric synthetic control method I implemented in Stata. Given that many policy interventions and events of interest in social sciences take place at an aggregate level (countries, regions, cities, etc.) and affect a small number of aggregate units, the potential applicability of synthetic control methods to comparative case studies is very large, especially in situations where traditional regression methods are not appropriate.

Suggested Citation

  • Giovanni Cerulli, 2017. "Nonparametric synthetic control method for program evaluation: model and Stata implementation," United Kingdom Stata Users' Group Meetings 2017 02, Stata Users Group.
  • Handle: RePEc:boc:usug17:02
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