Estimating Parametric Loss Aversion with Prospect Theory: Recognising and Dealing with Size Dependence

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.