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Project
Essays on Applied Machine Learning
The thesis deals with innovative machine learning techniques and it is composed of four papers. The first two papers provide an extension of causal inference frameworks to a machine learning scenario while the last two papers are direct applications of the predictive power of machine learning. The four papers provide applications in the field of public economics.
Date:4 Mar 2019 → 8 Jul 2020
Keywords:Machine learning, Causal inference, Targeted policies, Public economics, Quantitative social sciences
Disciplines:Machine learning and decision making, Public economics, Econometric and statistical methods and methodology
Project type:PhD project