Targeting Policy-Compliers with Machine Learning: An Application to a Tax Rebate Programme in Italy
38 Pages Posted: 8 Dec 2017
Date Written: December 5, 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.
Keywords: machine learning, prediction, programme evaluation, fiscal stimulus
JEL Classification: C5, H3
Suggested Citation: Suggested Citation