Efficient Coding and Risky Choice

82 Pages Posted: 5 Nov 2018 Last revised: 7 Aug 2020

See all articles by Cary Frydman

Cary Frydman

University of Southern California - Marshall School of Business

Lawrence J. Jin

California Institute of Technology

Date Written: August 7, 2020

Abstract

We experimentally test a theory of risky choice in which the perception of a lottery payoff is noisy due to information processing constraints in the brain. We model perception using the principle of efficient coding, which implies that perception is most accurate for those payoffs that occur most frequently. Across two pre-registered laboratory experiments, we manipulate the distribution from which payoffs in the choice set are drawn. In our first experiment, we find that risk taking is more sensitive to payoffs that are presented more frequently. In a follow-up task, we incentivize subjects to classify which of two symbolic numbers is larger. Subjects exhibit higher accuracy and faster response times for numbers they have observed more frequently. In our second experiment, we manipulate the payoff distribution so that efficient coding induces the decision maker’s perceived value function to switch from concave to convex. We find that demand for risk is significantly higher when efficient coding induces a convex value function. Together, our experimental results suggest that risk taking depends systematically on the payoff distribution to which the decision maker's perceptual system has recently adapted. More broadly, we provide novel evidence of the importance of imprecise and efficient coding in economic decision-making.

Keywords: efficient coding, perception, risky choice, neuroeconomics

JEL Classification: G02, G41, D81, D87

Suggested Citation

Frydman, Cary and Jin, Lawrence J., Efficient Coding and Risky Choice (August 7, 2020). Available at SSRN: https://ssrn.com/abstract=3270773 or http://dx.doi.org/10.2139/ssrn.3270773

Cary Frydman

University of Southern California - Marshall School of Business ( email )

701 Exposition Blvd
Los Angeles, CA 90089
United States

Lawrence J. Jin (Contact Author)

California Institute of Technology ( email )

1200 E. California Blvd.
MC 228-77
Pasadena, CA 91125
United States
626-395-4558 (Phone)

HOME PAGE: http://www.hss.caltech.edu/content/lawrence-jin

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