Prospect theory in multiple price list experiments: further insights on behaviour in the loss domain

• Published in: Theory and decision Vol. 94; no. 4; pp. 593 - 636
• Main Authors: Bocquého, Géraldine, Jacob, Julien, Brunette, Marielle
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.05.2023; Springer Nature B.V; Springer Verlag
• Subjects: Behavior; Behavioral/Experimental Economics; Context; Curvature; Domains; Economic Theory/Quantitative Economics/Mathematical Methods; Economics; Economics and Finance; Elicitation; Expected utility; Experiments; Finance; Game Theory; Insurance; Laboratories; Management; Operations Research/Decision Theory; Parameters; Preferences; Probability; Prospect theory; Quantitative Finance; Social and Behav. Sciences; Statistics for Business; Value; Weighting; Weighting functions; Tanaka–Camerer–Nguyen method; Behavioural economics; Reflected behaviour; Risk preferences; Reflection effect; Interval elicitation; Tanaka-Camerer-Nguyen method
• ISSN: 0040-5833; 1573-7187
• DOI: 10.1007/s11238-022-09902-y

In the theoretical description of prospect theory, distinct sets of parameters can control the curvature of the value function and the shape of the probability weighting function. There is one for the gain domain and one for the loss domain. However, in most estimations, behaviour over losses is assumed to perfectly reflect behaviour over gains, through a unique set of parameters. We examine the consequences of relaxing this simplifying assumption in the context of Tanaka et al.’s (Am Econ Rev 100(1):557–571, 2010) risk-elicitation procedure based on multiple price lists. We show that subjects’ behaviour for gains is mostly reflected for losses at the aggregate and individual levels, and is consistent with the distinctive prospect theory fourfold pattern. Reflection is only partial as the mean curvature of the value function is slightly less convex for losses than it is concave for gains. These results are robust to a high-stake context. However, we demonstrate that assuming reflection can have huge consequences on loss-aversion measures. Incidentally, we also highlight the existence of a strong, negative and persistent pure loss-frame effect on elicited loss aversion. We recommend that future practitioners and modellers are particularly cautious about the loss-aversion values they obtain or use because these are especially sensitive to parametric assumptions and framing.