Estimating risky behavior with multiple-item risk measures: An empirical examination

We compare seven established risk elicitation methods and investigate how they robustly explain eleven kinds of risky behavior with 760 individuals. Risk measures are positively correlated; however, their performance in explaining behavior is heterogeneous and, therefore, difficult to assess ex ante. To close this knowledge gap, greater diversification across risk measures is helpful. We do, indeed, find that performance increases considerably if single-item risk measures are combined to form multiple-item risk measures. They tend to improve results the more single-item measures they contain and if these single-item risk measures have different framings. Interestingly, survey items perform as well as incentivized experimental items in explaining risky behavior.