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We propose and test a new method for eliciting curvature-controlled discount rates that are invariant to the form of the utility function. Our method uses a single elicitation task and has the advantage of obtaining individual discount rates without knowledge of risk attitude or parametric assumptions about the form of the utility function. We compare our method to the Andersen et al. (2008) double elicitation technique in which the utility function and discount rate are jointly estimated. We use a laboratory experiment to perform a within-subjects comparison of discount rates from these two methods and find consistent results, which is reassuring given the wide range of estimates in the literature. In addition, the estimated discount rates in our study are “plausibly low” in contrast to the vast majority of discount rate studies. Our results are robust to relaxing the expected utility assumption of linearity in the probabilities, as we find little evidence of probability weighting in our data. In a second experiment, we find that discount rates are not sensitive to the length of the horizon, but are sensitive to the length of the front-end delay, suggesting present bias. We estimate average discount rates to be 12.2 percent in the first experiment and 11.3 percent in the second experiment when the front-end delay is at least two weeks


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