The psychometric and empirical properties of measures of risk preferences

By J. Beauchamp, David Cesarini, Magnus Johannesson. Journal of Risk and Uncertainty, 2017

128 citations recorded by the source corpus.

We examine the psychometric and empirical properties of some commonly used survey-based measures of risk preferences in a population-based sample of 11,000 twins. Using a model that provides a general framework for making inferences about the component of measured risk attitudes that is not due to measurement error, we show that measurement-error adjustment leads to substantially larger estimates of the predictive power of risk attitudes, of the size of the gender gap, and of the magnitude of the sibling correlation. Risk attitudes are predictive of investment decisions, entrepreneurship, and drinking and smoking behaviors; are robustly associated with cognitive ability and personality; and our estimates are often larger than those in the literature. Our results highlight the importance of adjusting for measurement error across a wide range of empirical settings.

Subfields: Applied Psychology, General Decision Sciences, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/3370a767c65d69609a6ac1cc60a43f829bac4f96

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Applied Psychology

1. Erik Snowberg
2. Leeat Yariv
3. B. Gillen

In General Decision Sciences

1. Erik Snowberg
2. Leeat Yariv
3. B. Gillen

In Sociology and Political Science

1. Erik Snowberg
2. Leeat Yariv
3. B. Gillen

Citations in the corpus

• Experimenting with Measurement Error: Techniques with Applications to the Caltech Cohort Study (2019, background): “The closest paper to ours in that literature is Beauchamp, Cesarini, and Johannesson (2015), which considers measurement error in survey-based risk elicitations.”