Estimating parametric loss aversion with prospect theory: Recognising and dealing with size dependence

B-Tier
Journal: Journal of Economic Behavior and Organization
Year: 2019
Volume: 162
Issue: C
Pages: 106-119

Score contribution per author:

0.503 = (α=2.01 / 4 authors) × 1.0x B-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

Parameteric identification of loss aversion requires either the imposition of rotational symmetry on the utility function or a point dependent normalization condition. In this paper, we propose a new approach in which point dependence is reduced by integration over normalization points. To illustrate our approach, we consider a sample of Ghanaian farmers’ risk preferences over the gain, loss and mixed domains. Using Bayesian econometric methods, we find support for Prospect Theory albeit with substantial behavioral variation across individuals plus mild overweighting of losses compared to gains. We also show that the majority of respondents are mildly loss averse especially as the size of the payoffs increase.

Technical Details

RePEc Handle
repec:eee:jeborg:v:162:y:2019:i:c:p:106-119
Journal Field
Theory
Author Count
4
Added to Database
2026-01-24