One-shot interaction and repeated interaction often co-exist in the real world. We study possible behavioral effects of this co-existence in a principal-agent setting, in which a principal simultaneously employs a permanent and a temporary agent. Our experimental results indicate that there is...

In the experimental scenario several agents repeatedly invest in n (n = 2) state-speciïfic assets. The evolutionarily stable and equilibrium (Blume and Easley, 1992) portfolio for this situation requires to distribute funds according to the constant probabilities of the various states. The...

Unlike previous attempts to implement cooperation in a prisoners' dilemma game with an infinite horizon in the laboratory, we focus on extended prisoners' dilemma games in which a second (pure strategy) equilibrium allows for voluntary cooperation in all but the last round. Our four main...

Bidding challenges learning theories since experiences for the same bid vary stochastically: the same choice can result in a gain or a loss. In such an environment the question arises how the nearly universally documented phenomenon of loss aversion affects the adaptive dynamics. We analyze the...

We study behavior in experimental beauty contests with, first, boundary and interior equilibria, and, second, homogeneous and heterogenous types of players. We find quicker and better convergence to the game-theoretic equilibrium with interior equilibria and homogeneous players.

In the article suggests the integral methods for estimation of population’s living standards in Northwest Federal District subjects. It allows to determine indexes which require additional stimulation in order to improve overall condition of the issue under investigation. According to...

We study the impact of advice or observation on the depth of reasoning in an experimental beauty-contest game. Both sources of information trigger faster convergence to the equilibrium. Yet, we find that subjects who receive naiuml;ve advice outperform uninformed subjects permanently, whereas...