Can We Infer Inter-Individual Differences in Risk-Taking From Behavioral Tasks?

Abstract

Investigating the bases of inter-individual differences in risk-taking is necessary to refine our cognitive and neural models of decision-making and to ultimately counter risky behaviors in real-life policy settings. However, recent evidence suggests that behavioral tasks fare poorly compared to standard questionnaires to measure individual differences in risk-taking. Crucially, using model-based measures of risk taking does not seem to improve reliability. Here, we put forward two possible - not mutually exclusive - explanations for these results and suggest future avenues of research to improve the assessment of inter-individual differences in risk-taking by combining repeated online testing and mechanistic computational models.

Keywords: behavioral economics; behavioral phenotype; correlational psychology; inter-individual variability; risk-taking.

FIGURE 1

The figure schematizes how low consistency of behavioral measures of risk may arise from the multi-layer model. At the top, we represent the different factors that influence the probability to express a given behavioral phenotype at a given time point in addition to random error. We consider a simplified case in which only two phenotypes are possible: red (risk seeking) and blue (risk aversion). The different layers change at different time constants (as exemplified by the gray triangle on the right). At a given time point (t) the momentary risk attitude is the weighted sum of the different layers of influence plus random error. A given subject is tested in two experimental sessions (ES1, and ES2) with two behavioral tasks supposed to measure the same behavioral phenotype (T1 and T2). The multi-layer model may explain why behavioral measures are not consistent between-tasks and between-sessions.