Heterogeneity in Risky Choice Behavior in a Broad Population

Abstract

We analyse risk preferences using an experiment with real incentives in a representative sample of 1,422 Dutch respondents. Our econometric model incorporates four structural parameters that vary with observed and unobserved characteristics: Utility curvature, loss aversion, preferences towards the timing of uncertainty resolution, and the propensity to choose randomly rather than on the basis of preferences. We find that all four parameters contribute to explaining choice behaviour. The structural parameters are significantly associated with socio-economic variables, but it is essential to incorporate unobserved heterogeneity in each of them to match the rich variety of choice patterns in the data. JEL: C90, D81

Entrepreneurs Under Uncertainty: An Economic Experiment in China

“…Both groups exhibit a certain degree of risk aversion in the R1 task, because a risk-neutral subject should switch at decision 5 and a risk lover at an earlier decision. This result is consistent with studies of risk aversion in other groups (for college students, see Holt and Laury 2002; for the general population, see Harrison et al 2007a, von Gaudecker et al 2011. Contrary to what many would expect, the entrepreneurs are not 19 In a study of the multiple price list method, Andersen et al (2006) detected that responding to a given task in a list might effect how the subject responded in later tasks.…”

“…There is also a tendency that the entrepreneurs' distribution of switching points has a slightly lower variance. A KolmogorovSmirnov test rejects equality of distributions at the 22 Based on previous studies there is no evidence that income has a substantial impact on the subjects' risk-taking behavior (see Donkers et al 2001, Harrison et al 2007a, von Gaudecker et al 2011 * Statistically significant at the 10% level; * * statistically significant at the 5% level; * * * statistically significant at the 1% level.…”

Deciding for Others Reduces Loss Aversion

“…12 In the regressions, we control for gender, age, education, cognitive ability and cognitive reflection in all specifications since these have shown to be important determinants of risky behavior in previous studies (e.g., Dohmen et al 2010; 14 2013a). 13 We confirm previous studies showing that females are more risk and loss averse and that age, education, are closely linked to noisy decision making (Dave et al 2010;Gaudecker et al 2011). In particular, we corroborate the main results of Andersson et al (2013a) on that measures of cognitive ability is not related to the curvature of utility function but is strongly related to the noise parameter.…”

Like cognitive function, decision making across the life span shows profound age-related changes

“…It is far from clear that poor decision making by elders necessarily reflects some kind of cognitive impairment. It may well be that healthy older adults make "bad" decisions because their preferences or choice efficiencies are different from those of their younger peers (16)(17)(18)(19)(20).…”