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

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.