Abstract
Simple functional forms for utility require restrictive structural assumptions that are often contrary to observed behavior. Even so, they are widely used in applied economic research. I address this issue using a two-part adaptive experimental design to compare the predictions of a popular parametric model of decision making under risk to those of non-parametric bounds on indifference curves. Interpreting the latter as an approximate upper bound, I find the parametric model sacrifices very little in terms of predictive success. This suggests that, despite their restrictiveness, simple functional forms may nevertheless be useful representations of preferences over risky alternatives.
Risk-Adaptive Experimental Design for High-Consequence Systems: LDRD Final Report.
