Towards a typology of risk preference: Four risk profiles describe two-thirds of individuals in a large sample of the U.S. population

Renato Frey, Shannon M. Duncan, Elke U. Weber

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

It has been a longstanding goal of the behavioral sciences to measure and model people’s risk preferences. In this article, we adopt a novel theoretical perspective of doing so and test to what extent specific types of individuals share similar risk profiles (i.e., configurations of multidimensional risk preferences). To this end, we analyzed data of a U.S. sample (N = 3,123) in a comprehensive and rigorous way, resulting in a twofold contribution. First, based on data from the Domain-Specific Risk-Taking scale (DOSPERT) and using a cross-validation procedure, we established a multidimensional trait space including general and domain-specific dimensions of risk preference. Second, we employed model-based cluster analyses in this multidimensional trait space, finding that 66% of participants can be described well with four basic risk profiles. In sum, the typological perspective proposed in this article has important implications for current theories of risk preference and the measurement of individual differences therein.

Original languageEnglish (US)
Pages (from-to)1-17
Number of pages17
JournalJournal of Risk and Uncertainty
Volume66
Issue number1
DOIs
StatePublished - Feb 2023

All Science Journal Classification (ASJC) codes

  • Accounting
  • Finance
  • Economics and Econometrics

Keywords

  • Bayesian latent profile analyses
  • DOSPERT
  • Psychometric modeling
  • Risk preference

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