We combine choice data in the ultimatum game with the expectations of proposers elicited by subjective probability questions to estimate a structural model of decision making under uncertainty. The model, estimated using a large representative sample of subjects from the Dutch population, allows both nonlinear preferences for equity and expectations to vary across socioeconomic groups. Our results indicate that inequity aversion to one's own disadvantage is an increasing and concave function of the payoff difference. We also find considerable heterogeneity in the population. Young and highly educated subjects have lower aversion for inequity than other groups. Moreover, the model that uses subjective data on expectations generates much better in- and out-of-sample predictions than a model which assumes that players have rational expectations. Copyright Copyright 2008 by The Econometric Society.

Centre interuniversitaire sur le risque, les politiques économiques et l'emploi Cahier de recherche/Working Paper 05-04

We experimentally disentangle the effect of information feedback from the effect of investment flexibility on the investment behavior of a myopically loss averse investor. Our findings show that varying the information condition alone suffices to induce behavior that is in line with the hypothesis of Myopic Loss Aversion. JEL Codes: D81,C91Keywords: Myopic loss aversion, information feedback, commitment, investment flexibility. * We would like to thank Jan Potters for providing us with instructions and for helpful comments and suggestions. Financial support from the Center for Economic Research (CentER) is gratefully acknowledged.

We use spline interpolation to approximate the subjective cumulative distribution function of an economic agent over the future realization of a continuous (possibly censored) random variable. The method proposed exploits information collected using a small number of probability questions on expectations and requires a weak prior knowledge of the shape of the underlying distribution. We find that eliciting 4 or 5 points on the cumulative distribution function of an agent is sufficient to accurately approximate a wide variety of underlying distributions. We show that estimated moments of general functions of the random variable can be computed analytically and/or using standard simulation techniques. We illustrate the usefulness of the method by estimating a simple model to asses the impact of expectations on investment decisions in a commonly used trust game. JEL Classification:C81, C10, D39