An Experimental Analysis of Decision Weights in Cumulative Prospect Theory under Uncertainty

Tversky and Kahneman's Cumulative Prospect Theory (CPT) can be seen as one of the leading descriptive theories of decision making under uncertainty. We conducted an experimental study to characterize utility function and decision weights of CPT, employing a two-step procedure based on the trade-off method. As a first step, we elicit the utility function individually for each subject and without relying on specific parametric forms. In the second step, the utility function serves as an input to determine decision weights. Our results confirm concavity of the utility function in the gain domain and bounded subadditivity of decision weights. Furthermore, we find evidence for systematic differences between the decision weights of the gain and loss domains.