The psychometric and empirical properties of measures of risk preferences

Beauchamp, Jonathan P.; Cesarini, David; Johannesson, Magnus

doi:10.1007/s11166-017-9261-3

Cited by 102 publications

(56 citation statements)

References 79 publications

(96 reference statements)

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“…While this design removes the uncertainty associated with measuring time preferences, it potentially reduces the weight of each decision given that choices are hypothetical. 5 Finally, our Anchoring task is based on the Wheel-of-Fortune task introduced in Tversky and Kahneman (1974), where a randomly generated number was found to influence subjects' answers to an independent question. We created an abstract version of the task to allow for scalability in a repeated setting.…”

Section: Methodsmentioning

confidence: 99%

The effect of cognitive load on economic decision making: A survey and new experiments

Deck

Jahedi

2015

European Economic Review

222

144

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Psychologists and economists have examined the effect of cognitive load in a variety of situations from risk taking to snack choice. We review previous experiments that have directly manipulated cognitive load and summarize their findings. We report the results of two new experiments where participants engage in a digit-memorization task while simultaneously performing a variety of economic tasks including: (1) choices involving risk, (2) choices involving intertemporal substitution, (3) choices with anchoring effects, (4) choices over healthy and unhealthy snacks, and (5) math problems. We find that higher cognitive load reduces numeracy as measured by performance in math problems. Moreover, within-subject analysis indicates that cognitive load leads to more risk-averse behavior, more impatience over money, and (nominally) more likelihood to anchor. We do not find any evidence that cognitive load increases impatience over consumption goods or unhealthy snack choices. Exploiting the panel nature of our data set, we find that those individuals who are most sensitive to cognitive load, as measured by a large drop in their own math performance across 1-and 8-digit memorization treatments, are driving much of the effect. * The authors wish to thank

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Section: Methodsmentioning

confidence: 99%

The effect of cognitive load on economic decision making: A survey and new experiments

Deck

Jahedi

2015

European Economic Review

222

144

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“…von Gaudecker et al (2011), using both hypothetical and incentivized measures on a Dutch sample (using the CentER internet panel), find that women on average are less risktaking than men (1422 participants). 8 Beauchamp et al (2017) use a random sample (approximately 11,000 individuals) of the Swedish twin population (the sample of twins is similar to the general population on some selected characteristics). Also using the nonincentivized risk measure mentioned above, they find that male twins on average are more risktaking than female twins (only looking at same-sex twins).…”

Section: Introductionmentioning

confidence: 99%

Gender, risk preferences and willingness to compete in a random sample of the Swedish population✰

Boschini

Dreber

Essen

et al. 2019

Journal of Behavioral and Experimental Economics

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Experimental results from student or other non-representative convenience samples often suggest that men, on average, are more risk-taking and competitive than women. Here we explore whether these gender preference gaps also exist in a simple random sample of the Swedish adult population. Our design comprises four different treatments to systematically explore how the experimental context may impact gender gaps; a baseline treatment, a treatment where participants are primed with their own gender, and a treatment where the participants know the gender of their counterpart (man or woman). We look at willingness to compete in two domains: a math task and a verbal task. We find no gender differences in risk preferences or in willingness to compete in the verbal task in this random sample. There is some support for men being more competitive than women in the math task, in particular in the pooled sample. The effect size is however considerably smaller than what is typically found. We further find no consistent impact of treatment on (the absence of) the gender gap in preferences.

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“…Based on literature concerning general rather than health-specific risk attitude, individuals with a higher education are expected to be more risk seeking (Donkers et al, 2001;Schurer, 2015). Following literature in which health behaviour is associated with risk attitude (Anderson & Mellor, 2008;Beauchamp et al, 2017;Dieteren et al, 2020;Dohmen et al, 2011;Weber et al, 2002), it is expected that HRAS-13 scores are positively associated with unhealthy behaviours (i.e. smoking, poor nutrition, excessive drinking and limited physical exercise) of respondents.…”

Section: Validitymentioning

confidence: 99%

Psychometric evaluation of the Health-Risk Attitude Scale (HRAS-13): assessing the reliability, dimensionality and validity in the general population and a patient population

Huls

Osch

Brouwer

et al. 2020

Psychology & Health

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Objectives: The aim of this study was to assess the reliability, dimensionality and validity of the self-report questionnaire Health-Risk Attitude Scale (HRAS-13) in a sample of the general population and a patient population. Methods: Sample 1 (n ¼ 930) was recruited from the general population aged 18-65 years in the Netherlands. Sample 2 (n ¼ 486) was recruited from the population of knee and hip osteoarthritis patients aged 45 and over, also from the Netherlands. Reliability was assessed using Cronbach's alpha, average inter-item correlation and item-total correlations. Dimensionality was examined using confirmatory factor analysis (CFA), principal component analysis (PCA) and bifactor analysis. Validity was assessed by performing known-group analysis using ANOVA tests. Results: Cronbach's alphas of the HRAS-13 were 0.73 in sample 1 and 0.69 in sample 2. Reliability and dimensionality analyses differed slightly between the samples, and suggest that a short version of the HRAS may capture a general component of health-risk attitude. Validity assessment of known groups showed that the HRAS-13 and a likely HRAS-6 distinguished between subgroups of respondents based on most of the assessed characteristics, but not all. Discussion: These findings are a preliminary indication that the HRAS-13 is a promising multidimensional instrument for measuring health-risk attitude. However, further research in various samples on decisions where health risks play a role is warranted to confirm the dimensionality of the HRAS-13 and the items to be retained in a full or a shorter version.

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The psychometric and empirical properties of measures of risk preferences

Cited by 102 publications

References 79 publications

The effect of cognitive load on economic decision making: A survey and new experiments

The effect of cognitive load on economic decision making: A survey and new experiments

Gender, risk preferences and willingness to compete in a random sample of the Swedish population✰

Psychometric evaluation of the Health-Risk Attitude Scale (HRAS-13): assessing the reliability, dimensionality and validity in the general population and a patient population

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