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

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

Journal of Economic Behavior & Organization, 2018, vol. 156, issue C, 86-102

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.

Keywords: Machine learning; Prediction; Program evaluation; Fiscal stimulus (search for similar items in EconPapers)
JEL-codes: C5 H3 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (41)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jeborg:v:156:y:2018:i:c:p:86-102

DOI: 10.1016/j.jebo.2018.09.010

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