The FOSSR project, funded by Italy’s National Recovery and Resilience Plan (PNRR), is hosting an online seminar dedicated to the Policy Learning Platform (PLP), an innovative tool designed to learn optimal policies from data. The event will take place on February 19, 2025, from 3:00 PM to 5:00 PM CET, and will be held entirely online.
The PLP, implemented through the Optimal Policy Learning (OPL) set of algorithms, enables users to define treatment assignment rules that maximize overall welfare by estimating policy effects on beneficiaries. This online seminar will explore three key approaches to empirical welfare maximization: threshold-based, linear-combination, and decision-tree, demonstrating their applications across three platforms: Stata, R, and Python.
Speakers and presentations
- Giovanni Cerulli (IRCrES-CNR) will present the OPL package for Stata, highlighting its functionalities for policy evaluation.
- Federico Brogi (ISTAT) will introduce the R implementation of OPL, focusing on its benefits for social science research and policy assessment.
- Fabrizio De Fausti (ISTAT) will explore the use of OPL in Python, demonstrating the potential of machine learning algorithms in policy analysis.
The invited discussants, Marco Ventura (Sapienza University of Rome) and Barbara Guardabascio (Università di Perugia), will provide insights into the practical applications of PLP in public policy.
This online seminar is part of FOSSR’s training program for the Italian scientific community, aiming to promote open science methodologies and advanced tools for reliable data analysis and policy research.
Registration is required to participate. More details are available on the devoted page: https://www.fossr.eu/eventi/the-fossr-plp-a-tutorial/.
*image credits: Mihail Ribkin on Unsplash