Estimating parametric loss aversion with prospect theory: recognising and dealing with size dependenceBalcombe, K., Bardsley, N., Dadzie, S. and Fraser, I. (2019) Estimating parametric loss aversion with prospect theory: recognising and dealing with size dependence. Journal of Economic Behavior & Organization, 162. pp. 106-119. ISSN 0167-2681
It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.1016/j.jebo.2019.04.017 Abstract/SummaryParametric 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 and 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.
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