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Autoempleo y Machine Learning: Una aplicación para España

Gutierrez-Lythgoe, Antonio (2023): Autoempleo y Machine Learning: Una aplicación para España.

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Abstract

Research in the field of Artificial Intelligence has made considerable progress in recent years, demonstrating its effectiveness in predicting and classifying discrete decisions. However, these advances have been relatively underutilized in economic research due to the lack of links with economic theories that explain the decision-making process of agents. In this paper, we propose a microeconomic framework for decision trees, a machine learning technique, to establish a more solid connection with economic theory and encourage its application in the field of discrete choice. To do so, we rely on data from the 2019 EU-SILC for Spain. Through comparison with a conventional multinomial logit model, we demonstrate the usefulness of this economic perspective for studying the sociodemographic factors associated with self-employment in Spain. The results suggest that incorporating economic foundations can significantly improve the accuracy of predictions and the ability to draw individual sociodemographic profiles for self-employment.

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