ON THE COMPARATIVE PERFORMANCE OF MACHINE LEARNING AND ECONOMIC MODELS FOR RISKY DECISION-MAKING

Mateus Hiro Nagata

Abstract: What constitutes the pinnacle of decision under risk models? This paper addresses this question by comparing a range of models, from popular economic models to black-box machine learning algorithms, as well as hybrid approaches in predicting the choice of certainty equivalents of risky prospects. The findings demonstrate that there is a relevant gain in descriptive prowess in using machine learning techniques. However, this indicates heterogeneity in the population rather than inadequacy of the economic models.