Abstract

This paper shows how to recover behavioral biases from revealed preference rankings implied by choices. The approach is sufficiently flexible to account for many well-documented behavioral biases in the literature. I apply the model to workhorse datasets in the literature on choice under risk and scanner consumer choices. I show that accounting for simple behavioral biases such as inattention and salience thinking suffices to explain most violations of rationality. Finally, I demonstrate that well-known regularities, such as the correlates of risk aversion, might in fact be confounded by simple behavioral biases. Overall, this research delineates a robust method for extracting behavioral biases from choice data, thereby not only enhancing our understanding of consumer decision-making but also offering a fresh lens through which to explore the contours of rationality in human behavior.

Reference

Avner Seror (Aix-Marseille University), “Semi-Parametric Approach to Behavioral Biases”, IAST General Seminar, Toulouse: IAST, September 26, 2023, 12:00–13:00, room Auditorium 3 (Ground floor - TSE Building).