On the Stochasticity of Ultimatum Games

Abstract

Brenner and Vriend (2006) argued (experimentally and theoretically) that one should not expect proposers in ultimatum games to learn to converge to the subgame perfect Nash equilibrium offer, as finding the optimal offer is a hard learning problem for (boundedly-rational) proposers. In this paper we show that providing the proposers with given (fixed) acceptance probabilities (essentially eliminating the learning task) leads to somewhat lower offers, but still substantially above the monetary payoff-maximizing offer. By using a Risk Attitude test and a Probability Matching test, we show experimentally that the proposers’ attitude with respect to risk, as well as their ability to interpret and deal with probabilities may matter when it comes to making UG offers. Thus, we argue that the lack of convergence to the minimum offers in ultimatum games may be related to the inherent stochasticity of typical UG experiments, highlighting a possible cause of such deviations that seems a complementary explanation to existing ones.