Measuring utility is at the heart of microeconomics and has important applications in many areas of economics. Here we present a new experimental method to elicit utility functions and associated measures of (higher order) risk preferences. The method we propose builds on a non-parametric estimation technique called P-spline regression in order to obtain continuous and differentiable estimations of utility functions from any mapping of experimental income to utility levels. Using this method we can compute well-known theoretically derived measures of the intensities of risk aversion, prudence and temperance. An accompanying laboratory and online experiment validates our method: We find significant relations to other methods, and more favorable characteristics such as test-retest-reliability for our method.
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