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Targeting with machine learning: An application to a tax rebate program in Italy

Author

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  • Andini, Monica
  • Ciani, Emanuele
  • de Blasio, Guido
  • D'Ignazio, Alessio
  • Salvestrini, Viola

Abstract

This paper shows how machine learning (ML) methods can be used to improve the effectiveness of public schemes and inform policy decisions. Focusing on a massive tax rebate scheme introduced in Italy in 2014, it shows that the effectiveness of the program would have significantly increased if the beneficiaries had been selected according to a transparent and easily interpretable ML algorithm. Then, some issues in estimating and using ML for the actual implementation of public policies, such as transparency and accountability, are critically discussed.

Suggested Citation

  • Andini, Monica & Ciani, Emanuele & de Blasio, Guido & D'Ignazio, Alessio & Salvestrini, Viola, 2018. "Targeting with machine learning: An application to a tax rebate program in Italy," Journal of Economic Behavior & Organization, Elsevier, vol. 156(C), pages 86-102.
    • Handle: RePEc:eee:jeborg:v:156:y:2018:i:c:p:86-102
    DOI: 10.1016/j.jebo.2018.09.010
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    References listed on IDEAS

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    More about this item

    Keywords

    Machine learning; Prediction; Program evaluation; Fiscal stimulus;
    All these keywords.

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • H3 - Public Economics - - Fiscal Policies and Behavior of Economic Agents

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