Loss Aversion Under Prospect Theory: A Parameter-Free Measurement

By Mohammed Abdellaoui, Han Bleichrodt, Corina Paraschiv. Management Sciences, 2007

816 citations recorded by the source corpus.

Agrowing body of qualitative evidence shows that loss aversion, a phenomenon formalized in prospect theory, can explain a variety of field and experimental data. Quantifications of loss aversion are, however, hindered by the absence of a general preference-based method to elicit the utility for gains and losses simultaneously. This paper proposes such a method and uses it to measure loss aversion in an experimental study without making any parametric assumptions. Thus, it is the first to obtain a parameter-free elicitation of prospect theory's utility function on the whole domain. Our method also provides an efficient way to elicit utility midpoints, which are important in axiomatizations of utility. Several definitions of loss aversion have been put forward in the literature. According to most definitions we find strong evidence of loss aversion, at both the aggregate and the individual level. The degree of loss aversion varies with the definition used, which underlines the need for a commonly accepted definition of loss aversion.

Subfields: Economics and Econometrics, General Decision Sciences, Safety Research

View Paper: https://www.semanticscholar.org/paper/a9bcd0e9e824b82c974124d6f6e3542ec4b17a00

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Citations in the corpus

Why bad feelings predict good behaviours: The role of positive and negative anticipated emotions on consumer ethical decision making (2019, background): “According to loss aversion theory, individuals are more sensitive to losses than to commensurate gains (Abdellaoui et al., 2007; Brenner et al., 2007; Camerer, 2005), and therefore, in the context of the current study, appeared more sensitive to potential negative future emotions than to potential…”
A genuine foundation for prospect theory (2012, background): “Further, there exist different definition of loss aversion in the literature (for an overview see Abdellaoui, Bleichrodt, and Paraschiv 2007), and behavioral foundations of these definitions of loss aversion are often missing or they have model-dependent implications (Schmidt and Zank 2005, 2008).”
Risk Aversion in the Laboratory (2008, positive): “Abdellaoui, Bleichrodt, and Paraschiv (2007b) extend the TO method to elicit measures of loss aversion.”
Title: the Neural Representation of Subjective Value under Risk and Ambiguity 1 2 (2009, background): “Taking these 105 results together it seems that the same area, the OFC, is involved in the 106 processing of both risk and ambiguity, and that it has a role in signaling how 107 much is unknown, showing higher activation when less is known.”
Modeling uncertainty in multi-criteria decision analysis (2012, background): “[138,3] and more risk proneness for losses [3] than utility functions obtained with the gamble-tradeoff method, potentially as a result of certainty effects [138].”
Understanding customers' repeat purchase intentions in B2C e‐commerce: the roles of utilitarian value, hedonic value and perceived risk (2014, background): “In fact, Abdellaoui et al. (2007) suggest that losses are twice as powerful, psychologically, as gains.”
A tractable method to measure utility and loss aversion under prospect theory (2008, methodology): “In particular, Abdellaoui, Bleichrodt, and Paraschiv (2007) observed that the power function fitted their data very well.”
Measuring Loss Aversion under Ambiguity: A Method to Make Prospect Theory Completely Observable (2016, methodology): “Abdellaoui et al. (2007) was the first to propose a method for measuring loss aversion that did not have to impose simplifying assumptions about utility or probability weighting.”