Stability and change in risk-taking propensity across the adult life span.

Abstract

Can risk-taking propensity be thought of as a trait that captures individual differences across domains, measures, and time? Studying stability in risk-taking propensities across the lifespan can help to answer such questions by uncovering parallel, or divergent, trajectories across domains and measures. We contribute to this effort by using data from respondents aged 18 to 85 in the German Socio-Economic Panel Study (SOEP) and by examining (1) differential stability, (2) mean-level differences, and (3) individual-level changes in self-reported general (N = 44,076) and domain-specific (N =11,903) risk-taking propensities across adulthood. In addition, we investigate (4) the correspondence between cross-sectional trajectories of self-report and behavioral measures of social (trust game; N = 646) and nonsocial (monetary gamble; N = 433) risk taking. The results suggest that risk-taking propensity can be understood as a trait with moderate stability. Results show reliable mean-level differences across the lifespan, with risk-taking propensities typically decreasing with age, although significant variation emerges across domains and individuals. Interestingly, the mean-level trajectory for behavioral measures of social and nonsocial risk taking was similar to those obtained from self-reported risk, despite small correlations between task behavior and self-reports. Individual-level analyses suggest a link between changes in risk-taking propensities both across domains and in relation to changes in some of the Big Five personality traits. Overall, these results raise important questions concerning the role of common processes or events that shape the lifespan development of risk-taking across domains as well as other major personality facets.

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

“…Second, another possibility is that age differences were driven by a "peanuts effect" (Prelec & Loewenstein, 1991), according to which a greater relative prevalence of risk-seeking preferences among older adults is expected given that they are typically wealthier than younger adults (especially college students), making the payoffs more consequential to the latter group than to the former. This explanation seems implausible given previous failures to find a link between income/wealth and risk-taking propensity or age differences thereof (see Josef et al 2016). Moreover, it is unclear how such wealth effects could simultaneously lead to increases in risk aversion when riskless options are involved (Best & Charness, 2015).…”

The psychometric and empirical properties of measures of risk preferences

“…Indeed, it has been shown that personal experiences and time-varying attributes can affect risk attitudes and risk taking (e.g., Malmendier and Nagel 2011;Sahm 2012). We do not attempt such a decomposition of m t here, in part because previous work has shown that changes in observables can explain only a small share of the transitory variation in measured preferences (Andersen et al 2008;Josef et al 2016;Meier and Sprenger 2010;Sahm 2012), and in part because only about a year elapsed on average between the first and the second measurements. Also, though previous work (e.g., Choi et al 2014;Dave et al 2010;von Gaudecker et al 2011) has shown the consistency or variance of decision-making under uncertainty is related to socio-economic characteristics, we do not model m t as dependent on covariates, as this would add a significant layer of complexity to the model and estimation and is not of direct relevance for the objectives of this paper.…”

Experimental and Self‐reported Measures of Risk Taking and Digit Ratio (2d:4d): Evidence From a Large, Systematic Study

“…Nonetheless, a direct systematic comparison of the RP task with the Holt and Laury (, ) test within a representative sample of the U.K. population finds a positive and statistically significant correlation between the two measures of risk aversion (Galizzi et al., ). Our second measure is a self‐reported measure for general RA on a 10‐point Likert scale developed by Dohmen et al. (), which has been introduced in large representative surveys (Josef et al., ; Galizzi et al., ), and it has been extensively used in other studies with neurobiological measures (Cesarini et al., ; Zethraeus et al., ). This procedure also has drawbacks.…”