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Individual classification of strong risk attitudes: An application across lottery types and age groups

Overview of attention for article published in Psychonomic Bulletin & Review, January 2017
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Title
Individual classification of strong risk attitudes: An application across lottery types and age groups
Published in
Psychonomic Bulletin & Review, January 2017
DOI 10.3758/s13423-016-1212-5
Pubmed ID
Authors

David Kellen, Rui Mata, Clintin P. Davis-Stober

Abstract

Empirical evaluations of risk attitudes often rely on a weak definition of risk that concerns preferences towards risky and riskless options (e.g., a lottery vs. a sure outcome). A large body of work has shown that individuals tend to be weak risk averse in choice contexts involving risky and riskless gains but weak risk seeking in contexts involving losses, a phenomenon known as the reflection effect. Recent attempts to evaluate age differences in risk attitudes have relied on this weak definition, testing whether the reflection effect increases or diminishes as we grow older. The present work argues that weak risk attitudes have limited generalizability and proposes the use of a strong definition of risk that is concerned with preferences towards options with the same expected value but different degrees of risk (i.e., outcome variance). A reanalysis of previously-published data and the results from a new study show that only a minority of individuals manifests the reflection effect under a strong definition of risk, and that, when facing certain lottery-pair types, older adults appear to be more risk seeking than younger adults.

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The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 28 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 6 21%
Student > Master 5 18%
Professor 3 11%
Student > Ph. D. Student 2 7%
Researcher 2 7%
Other 3 11%
Unknown 7 25%
Readers by discipline Count As %
Psychology 12 43%
Economics, Econometrics and Finance 1 4%
Business, Management and Accounting 1 4%
Decision Sciences 1 4%
Social Sciences 1 4%
Other 3 11%
Unknown 9 32%