Data from a risky choice experiment are used to estimate a fully parametric stochastic model of risky choice. As is usual with such analyses, Expected Utility Theory is rejected in favour of a form of Rank Dependent Theory. Then an estimate of the risk aversion parameter is deduced for each subject, and this is used to construct a measure of the “closeness to indifference” of each subject in each choice problem. This measure is then used as an explanatory variable in a random effects model of decision time, with other explanatory variables being the complexity of the problem, the financial incentives, and the amount of experience accumulated at the time of performing the task. The most interesting finding is that significantly more effort is allocated to problems in which subjects are close to indifference. This presents us with another reason (in addition to statistical information considerations) why such tasks should play a prominent role in experiments.

The dhreg command implements maximum likelihood estimation of the double-hurdle model for continuously distributed outcomes. The command includes the option to fit a p-tobit model, that is, a model that estimates only an intercept for the hurdle equation. The bootdhreg command (the bootstrap version of dhreg) may be convenient if the data-generating process is more complicated or if heteroskedasticity is suspected. The xtdhreg command is a random-effects version of dhreg applicable to panel data. However, this estimator differs from standard random-effects estimators in the sense that the outcome of the first hurdle applies to the complete set of observations for a given subject instead of applying at the level of individual observations. Command options include estimation of a correlation parameter capturing dependence between the two hurdles.

Spousal correlation in risk attitude is estimated using data from the German Socio-Economic Panel over the period 2004–2009. We apply the bivariate panel ordered probit model to the analysis of the simultaneous determination of the male’s and the female’s risk attitude, using the survey question about general willingness to take risk, provided on a 0–10 Likert-scale. The correlations between both the individual-specific effects of the two partners and the two within-individual errors are separately estimated, and found to be +0.285 and +0.310, respectively. We consider the former to be a key parameter, since its positive sign may be interpreted in terms of positive assortative mating on risk attitude: individuals tend to form partnerships with others having a similar risk attitude. We also find evidence that this correlation increases with years of marriage, suggesting either a form of spousal socialization or a selection process in which marriage breakdown is more likely in poorly matched couples.