Probability Weighting Functions

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Nonlinear neurobiological probability weighting functions for aversive outcomes

While mainstream economic models assume that individuals treat probabilities objectively, many people tend to overestimate the likelihood of improbable events and underestimate the likelihood of probable events. However, a biological account for why probabilities would be treated this way does not yet exist. While undergoing fMRI, we presented individuals with a series of lotteries, defined by ...

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Discriminating Among Probability Weighting Functions Using Adaptive Design Optimization.

Probability weighting functions relate objective probabilities and their subjective weights, and play a central role in modeling choices under risk within cumulative prospect theory. While several different parametric forms have been proposed, their qualitative similarities make it challenging to discriminate among them empirically. In this paper, we use both simulation and choice experiments t...

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Second-best Probability Weighting∗

Non-linear probability weighting is an integral part of descriptive theories of choice under risk such as prospect theory. But why do these objective errors in information processing exist? Should we try to help individuals overcome their mistake of overweighting small and underweighting large probabilities? In this paper, we argue that probability weighting can be seen as a compensation for pr...

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Inverse probability weighting.

Statistical analysis usually treats all observations as equally important. In some circumstances, however, it is appropriate to vary the weight given to different observations. Well known examples are in meta-analysis, where the inverse variance (precision) weight given to each contributing study varies, and in the analysis of clustered data. Differential weighting is also used when different p...

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ژورنال

عنوان ژورنال: SSRN Electronic Journal

سال: 2015

ISSN: 1556-5068

DOI: 10.2139/ssrn.2675133