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

被引：34

作者：

Andini, Monica ^{[1
]}

Ciani, Emanuele ^{[1
,2
]}

de Blasio, Guido ^{[1
]}

D'Ignazio, Alessio ^{[1
]}

Salvestrini, Viola ^{[3
]}

机构：

[1] Bank Italy, Struct Econ Anal Directorate, Via Nazl 91, I-00184 Rome, Italy

[2] Univ Modena & Reggio Emilia, Ctr Anal Publ Policies, Viale Berengario 51, I-41121 Modena, Italy

[3] London Sch Econ & Polit Sci, Dept Econ, Houghton St, London WC2A 2AE, England

来源：

JOURNAL OF ECONOMIC BEHAVIOR & ORGANIZATION | 2018年 / 156卷

关键词：

Machine learning; Prediction; Program evaluation; Fiscal stimulus; POLICY;

D O I：

10.1016/j.jebo.2018.09.010

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

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. (C) 2018 Elsevier B.V. All rights reserved.

引用

页码：86 / 102

页数：17

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