Investors' risk attitude and risky behavior: a Bayesian approach with imperfect information

In a choice model of risky assets the role of risk aversion is analyzed. The measure of risk preference comes from a direct subjective survey question and it is considered as an imperfect information about the true risk attitude of investors. Misclassification between the true and the observed risk aversion is explicitly taken into account in the empirical model. A Data Augmentation approach, a Bayesian procedure for incomplete-data problems, is applied on data from the 2006 Survey of Household Income and Wealth by the Bank of Italy. Results indicate that when misclassification of investors is taken into account model estimates show the good performance of the subjective question when used as a control in a portfolio choice models. Moreover risk aversion emerges as a strong predictor of the probability to hold risky assets. The analysis also shows that probability of misclassification decreases as latent risk aversion increases, that means that more risk tolerant investors tend to be classified erroneously more often than less risk tolerant investors.