Expected utility theory and prospect theory: one wedding and a decent funeral

By Glenn W. Harrison, E Elisabet Rutström. 2009

451 citations recorded by the source corpus.

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

View Paper: https://www.semanticscholar.org/paper/abd9a95b88242080911e2876fd452749509e2b67

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

In General Decision Sciences

In Safety Research

Citations in the corpus

Hierarchical Bayesian parameter estimation for cumulative prospect theory (2011, methodology): “Below we will illustrate how single-subject maximum likelihood, one of themost popular estimation methods for CPT (e.g. Harrison & Rutström, 2009; Harless & Camerer, 1994; Stott, 2006), can produce extreme, implausible point estimates for parameters estimated with high uncertainty.”
A penny for your thoughts: a survey of methods for eliciting beliefs (2014, unknown): “There is a wealth of experimental evidence related to the ﬁrst point, with many decision theories proposed and tested (see, for example, Harrison and Rutstr¨om (2009)).”
Stochastically more risk averse: A contextual theory of stochastic discrete choice under risk (2011, methodology): “Graphs illustrate this using MPS pairs from Hey’s (2001) four- outcome design (these are common, e.g. Hey and Orme 1994 and Harrison and Rutström 2005).”
Mixture models of choice under risk (2011, methodology): “We emphasise that we are by no means the first to use such a solution in such a context – a very useful reference is Harrison and Rutstrom (2009), which includes a discussion of the previous use of mixture models in economics 3 .”
Expected utility or prospect theory maximisers? Assessing farmers' risk behaviour from field-experiment data (2014, methodology): “14 According to Harrison and List’s (2004) terminology, our experiment belongs to the class of artefactual field experiments (non-standard population, but abstract framing).”
Risk and Rationality: Uncovering Heterogeneity in Probability Distortion (2009, background): “Related work by Harrison and colleagues (Andersen, Harrison, and Rutström (2006), Harrison, Humphrey, and Verschoor (2010), Harrison and Rutström (2009)) applies finite mixture models as well, but differs from our approach.”
Time to Change What to Sow: Risk Preferences and Technology Adoption Decisions of Cotton Farmers in China (2013, background): “5 Several studies, such as Benjamin, Brown, and Shapiro (2006), Harrison and Rutström (2009), and List (2003), have shown that some subjects would behave more in line with EU theory than PT.”
NEUROECONOMICS: A CRITICAL RECONSIDERATION (2008, methodology): “It also lends itself to formalization in certain structured settings (e.g. Andersen et al. 2008a) and more generally using mixture specifications defined over multiple latent decision-making processes (e.g. Harrison and Rutström 2005; Andersen et al. 2007).”