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We design experiments to jointly elicit risk and time preferences for the adult Danish population. We find that joint elicitation results in estimates of discount rates that are dramatically lower than those found in previous studies. Estimation of latent time preferences requires that one specify a theoretical structure to understand risk and time choices,(More)
(2002) develop an experimental design to determine the risk attitude of an individual. They use their observations to argue that increased incentives appear to change risk attitudes, leading to greater risk aversion. Popular utility functions that do not allow for such effects are therefore misspecified. Building on this finding, they estimate a flexible(More)
We elicit measures of individual discount rates from a representative sample of the Danish population and test two substantive hypotheses. The first hypothesis is that smokers have higher individual discount rates than non-smokers. The second hypothesis is that smokers are more likely to have time inconsistent preferences than non-smokers, where time(More)
Measures of risk attitudes derived from experiments are often questioned because they are based on small stakes bets and do not account for the extent to which the decision-maker integrates the prizes of the experimental tasks with personal wealth. We exploit the existence of detailed information on individual wealth of experimental subjects in Denmark, and(More)
Keywords: Virtual reality Field experiments Laboratory experiments Risk perception Subjective beliefs Wildfires Environmental policy a b s t r a c t We develop the concept of virtual experiments and consider their application to environmental policy. A virtual experiment combines insights from virtual reality in computer science, naturalistic(More)
This paper asks a simple methodological question about belief elicitation: Does asking subjects about their beliefs during a repeated game change the way subjects play the game? In particular, we ask if belief elicitation changes behavior in the direction of belief based learning models, away from reinforcement learning models. Based on a carefully designed(More)