Identifying robust correlates of risk preference

A systematic approach using specification curve analysis

Datos Bibliográficos

ID6207544
AutoresRenato Frey (0000-0002-3190-3523, University of Basel, autor de correspondencia), David Richter (0000-0003-2811-8652, German Institute for Economic Research), Jürgen Schupp (0000-0001-5273-643X, German Institute for Economic Research), Ralph Hertwig (0000-0002-9908-9556, German Institute for Economic Research), Rui Mata (0000-0002-1679-906X, University of Basel)
Año2021
Volumen120
Número2
Páginas538-557
Fecha de publicación2021-02-01
Peer ReviewedSí
Open AccessNo
TipoARTICLE
RevistaJournal of Personality and Social Psychology (JOURNAL)
Identificadores de la revistaISSN: 0022-3514 • E-ISSN: 1939-1315
EditorialAmerican Psychological Association (APA) (PUBLISHER)
DOI10.1037/pspp0000287
PMID32118465
OpenAlexW3005755974
IdiomaEN
Citas recibidas23
Referencias citadas44

916), and by adopting an exhaustive modeling approach-specification curve analysis. Our analyses of 6 candidate correlates (household income, sex, age, fluid intelligence, crystallized intelligence, years of education) suggest that sex and age have robust and consistent associations with risk preference, whereas the other candidate correlates show weaker and more (domain-) specific associations (except for crystallized intelligence, for which there were no robust associations). The results further demonstrate the important role of construct operationalization when assessing people's risk preferences: Self-reported propensity measures picked up various associations with the proposed correlates, but (incentivized) behavioral measures largely failed to do so. In short, the associations between the 6 candidate correlates and risk preference depend mostly on how risk preference is measured, rather than whether and which control variables are included in the model specifications. The present findings inform several theories that have suggested candidate correlates of risk preference, and illustrate how personality research may profit from exhaustive modeling techniques to improve theory and measurement of essential constructs. (PsycInfo Database Record (c) 2021 APA, all rights reserved)

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