We develop an extension of the familiar linear mixed logit model to allow for the direct estimation of parametric non-linear functions defined over structural parameters. Classic applications include the estimation of coefficients of utility functions to characterize risk attitudes and discounting functions to characterize impatience. There are several unexpected benefits of this extension, apart from the ability to directly estimate structural parameters of theoretical interest.

Evidence of risk aversion in laboratory settings over small stakes leads to a priori implausible levels of risk aversion over large stakes under certain assumptions. One core assumption in statements of this calibration puzzle is that small-stakes risk aversion is observed over all levels of wealth, or over a â sufficiently largeâ range of wealth. Although this assumption is viewed as self-evident from the vast experimental literature showing risk aversion over laboratory stakes, it actually requires that lab wealth be varied (...) for a given subject as one evaluates the risk attitudes of the subject. We consider evidence from a simple design that tests this assumption, and find that the assumption is strikingly rejected for a large sample of subjects from a population of college students. We conclude that the implausible predictions that flow from these assumptions do not apply to one specialized population widely used to study economic behavior in laboratory experiments. (shrink)

To understand how small business entrepreneurs respond to government policy one has to know their risk and time preferences. Are they risk averse, or have high discount rates, such that they are hard to motivate? We have conducted a set of field experiments in Denmark that will allow a direct characterization of small business entrepreneurs in terms of these traits. We build on experimental tasks that are well established in the literature. The results do not suggest that small business entrepreneurs (...) are more or less risk averse than the general population under the assumption of Expected Utility Theory. However, we generally find an S-shaped probability weighting function for both small business entrepreneurs and non-entrepreneurs, with entrepreneurs being more optimistic about the chance of occurrence for the best outcome in lotteries with real monetary outcomes. The results also point to a significant difference in individual discount rates between entrepreneurs and non-entrepreneurs: entrepreneurs are willing to wait longer for certain rewards than the general population. (shrink)

We question the behavioral premise underlying Ainslie's claims about hyperbolic discounting theory. The alleged evidence for humans can be easily explained as an artefact of experimental procedures that do not control for the credibility of payment over different time horizons. In appropriately controlled and financially motivated settings, human behavior is consistent with conventional exponential preferences.