We experimentally test the predictive success of three stationary concepts in two cyclic duopoly games. The concepts are Nash equilibrium, impulse-balance equilibrium and payoff-sampling equilibrium. In the experiment 11 independent subject groups, consisting out of six participants interacting over 200 rounds, were gathered for each game. The comparison of the three concepts with mixed strategies shows that the order of performance from best to worst is as follows: payoff-sampling equilibrium, impulse-balance equilibrium, and Nash equilibrium. In addition the data exhibit a weak but significant tendency over time in the direction of coordination at a pure strategy equilibrium.

Many experiments have demonstrated the power of norm enforcement— peer monitoring and punishment—to maintain, or even increase, contributions in social dilemma settings, but little is known about the underlying norms that monitors use to make punishment decisions, either within or across groups. Using a large sample of experimental data, we empirically recover the set of norms used most often by monitors and show first that the decision to punish should be modeled separately from the decision of how much to punish. Second, we show that absolute norms often fit the data better than the group average norm often assumed in related work. Third, we find that different norms seem to influence the decisions about punishing violators inside and outside one's own group.

We use laboratory experiments to examine the effect of firm size asymmetry on the emergence of price leadership in a price-setting duopoly with capacity constraints. Independent of the level of size asymmetry, the unique subgame perfect equilibrium of our timing game predicts that the large firm is the price leader. Experimental data show that price leadership by the large firm is frequent, but simultaneous moves are also often observed. Profit outcomes in the previous period affect the subjects’ decisions to announce or wait in a way that hampers convergence to the equilibrium. Furthermore, while both small and large firms display a strong tendency to wait to announce their price when firm size asymmetry is low, they often set prices early when size asymmetry is high. Prices are higher when price setting is sequential rather than simultaneous and when firm size asymmetry is high. Hence, price leadership by either type of firm has an anti-competitive effect that is more pronounced when the size difference between firms is large.

We study the influence of gender and gender pairing on economic decision making in an experimental two-person bargaining game where the other party's gender is known to both actors. We find that (1) gender per se has no significant effect on behavior, whereas (2) gender pairing systematically affects behavior. In particular, we observe much more competition and retaliation and, thus, lower efficiency when the bargaining partners have the same gender than when they have the opposite gender. These findings are consistent with predictions from evolutionary psychology. Implications of our results for real-world organizations are discussed.

A standard method to elicit certainty equivalents is the Becker-DeGroot- Marschak (BDM) procedure. We compare the standard BDM procedure and a BDM procedure with a restricted range of minimum selling prices that an individual can state. We find that elicited prices are systematically affected by the range of feasible minimum selling prices. Expected utility theory cannot explain these results. Nonexpected utility theories can only explain the results if subjects consider compound lotteries generated by the BDM procedure. We present an alternative explanation where subjects sequentially compare the lottery to monetary amounts in order to determine their minimum selling price. The model offers a formal explanation for range effects and for the underweighting of small and the overweighting of large probabilities.

Economic agents often have to make decisions in environments affected by regime switches but expectation formation has hardly been explored in this context. We report about a laboratory experiment whose participants judgmentally forecast three time series subject to regime switches. The participants make forecasts without context knowledge and without support from statistical software. Their forecasts are only based on the previous realizations of the time series. Our interest is the explanation of the average forecasts with a simple model, the bounds & likelihood heuristic. In previous studies it was shown that this model can explain average forecasting behavior very well given stable and stationary time series. We find that the forecasts after a structural break are characterized by a higher variance and less accuracy over several periods. Considering this transition phase in the model, the heuristic performs even slightly better than the Rational Expectations Hypothesis.