No. 1158 - Targeting policy-compliers with machine learning: an application to a tax rebate programme in Italy

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by Monica Andini, Emanuele Ciani, Guido de Blasio, Alessio D'Ignazio and Viola Salvestrini December 2017

Machine Learning (ML) can be a powerful tool to inform policy decisions. Those who are treated under a programme might have different propensities to put into practice the behaviour that the policymaker wants to incentivize. ML algorithms can be used to predict the policy-compliers; that is, those who are most likely to behave in the way desired by the policymaker.

When the design of the programme is tailored to target the policy-compliers, the overall effectiveness of the policy is increased. This paper proposes an application of ML targeting that uses the massive tax rebate scheme introduced in Italy in 2014.

Published in 2018 in: Journal of Economic Behavior & Organization, v. 156, pp. 86-102