Machine Learning in the Service of Policy Targeting: The Case of Public Credit Guarantees

83 Pages Posted: 2 Aug 2019 Last revised: 8 Aug 2019

Date Written: February 4, 2019

Abstract

We use Machine Learning (ML) predictive tools to propose a policy-assignment rule designed to increase the effectiveness of public guarantee programs. This rule can be used as a benchmark to improve targeting in order to reach the stated policy goals. Public guarantee schemes should target firms that are both financially constrained and creditworthy, but they often employ naïve assignment rules (mostly based only on the probability of default) that may lead to an inefficient allocation of resources. Examining the case of Italy’s Guarantee Fund, we suggest a benchmark ML-based assignment rule, trained and tested on credit register data. Compared with the current eligibility criteria, the ML-based benchmark leads to a significant improvement in the effectiveness of the Fund in gaining credit access to firms. We discuss the problems in estimating and using these algorithms for the actual implementation of public policies, such as transparency and omitted payoffs.

Keywords: machine learning, program evaluation, loan guarantees

JEL Classification: C5, H81

Suggested Citation

Andini, Monica and Boldrini, Michela and Ciani, Emanuele and de Blasio, Guido and D'Ignazio, Alessio and Paladini, Andrea, Machine Learning in the Service of Policy Targeting: The Case of Public Credit Guarantees (February 4, 2019). Bank of Italy Temi di Discussione (Working Paper) No. 1206, February 2019, Available at SSRN: https://ssrn.com/abstract=3431144 or http://dx.doi.org/10.2139/ssrn.3431144

Monica Andini

Bank of Italy ( email )

Via Nazionale 91
Rome, 00184
Italy

Michela Boldrini

Independent ( email )

Emanuele Ciani (Contact Author)

Bank of Italy ( email )

Via Nazionale 91
Rome, 00184
Italy

Guido De Blasio

Bank of Italy ( email )

Via Nazionale 91
00184 Roma
Italy

Alessio D'Ignazio

Bank of Italy ( email )

Via Nazionale 91
Rome, 00184
Italy

Andrea Paladini

Independent ( email )

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