The Rich Domain of Uncertainty: Source Functions and Their Experimental Implementation

By Mohammed Abdellaoui, Lætitia Placido, Aurélien Baillon, Peter P. Wakker. 2011

559 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Economics and Econometrics, General Decision Sciences

View Paper: https://www.semanticscholar.org/paper/f319317300e5a2e88e76901f4fb5b3c9e277532e

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Citations in the corpus

Rankings and Risk-Taking in the Finance Industry (2018, unknown): “In the first task we measured risk-attitudes in a standard choice list setting (Bruhin et al., 2010; Abdellaoui et al., 2011).”
Risk aversion and religion (2012, unknown): “In a study of risk attitudes, the procedure leverages incentives, and avoids the potential problem of relatively linear utility for small payoffs (see Abdellaoui et al. (2010) and references therein). Abdellaoui et al. (2010) argue that random selection leads to”
Common components of risk and uncertainty attitudes across contexts and domains: evidence from 30 countries (2015, methodology): “This design closely follows the procedures introduced and tested by Abdellaoui et al. (2011). In addition to the incentivized tasks, subjects were asked a series of questions on their self-declared risk attitudes.”
Prospect Theory and the Brain (2009, background): “For a discussion of how source preferences can be incorporated into the two-stage model see Fox and Tversky (1998); for a more detailed account of “source functions” in a prospect theory framework see Abdellaoui et al. (2011a).”
Estimating Ambiguity Aversion in a Portfolio Choice Experiment (2009, background): “Abdellaoui et al. (2011) capture attitudes to ambiguity by fitting source functions.”
Aggregating imprecise or conflicting beliefs: An experimental investigation using modern ambiguity theories (2012, unknown): “Formal difference with the source method of Abdellaoui et al. (2011) In Abdellaoui et al.’s (2011) source method, sources refer to different algebras, i.e. different collections of subsets (events) of the state space.”
Measuring Loss Aversion under Ambiguity: A Method to Make Prospect Theory Completely Observable (2016, unknown): “Abdellaoui et al. (2011) and Vieider et al. (2013) measured utility under risk and under ambiguity for small stakes and under parametric assumptions about utility.”
Asset pricing and ambiguity: Empirical evidence (2018, unknown): “These findings support Hypotheses 2 and 3, and are consistent with the findings of previous behavioral studies; see, for example, Mangelsdorff and Weber (1994), Abdellaoui et al. (2005), and Du and Budescu (2005). However, unlike these studies, in our model investors’ preferences for ambiguity are c”
Measuring Ambiguity Attitudes for All (Natural) Events (2018, methodology): “Abdellaoui et al. (2011) measured similar indexes as ours but had to use complex measurements and data fittings, requiring measurements of subjective probabilities, utilities, and event weights. As regards the treatment of unknown beliefs, Gallant, Jahan-Parvar, & Liu (2015) and Brenner & Izhakian (”
Higher Order Risk Attitudes, Demographics, and Financial Decisions (2011, background): “In a study of risk attitudes, the procedure leverages incentives, and avoids the potential problem of relatively linear utility for small payoffs (see Abdellaoui et al. (2011) and references therein). Abdellaoui et al. (2011) argue that random selection leads to”
Information Gaps: A Theory of Preferences Regarding the Presence and Absence of Information (2018, methodology): “Although existing models (e.g., Abdellaoui et al., 2011) can accommodate these phenomena, they do not specifically predict them.”