Using a laboratory experiment, we investigate whether a variety of behaviors in repeated games are related to an array of individual characteristics that are popular in economics: risk attitude, time preference, trust, trustworthiness, altruism, strategic skills in one-shot matrix games, compliance with first-order stochastic dominance, ability to plan ahead, and gender. We do find some systematic relationships. A subject’s compliance with first-order stochastic dominance as well as, possibly, patience, gender, and altruism have some systematic effects on her behavior in repeated games. At the level of a pair of subjects who are playing a repeated game, each subject’s gender as well as, possibly, patience and ability to choose an available dominant strategy in a one-shot matrix game systematically affect the frequency of the cooperate–cooperate outcome. However, overall, the number of systematic relationships is surprisingly small.

We use data from experiments on finitely repeated dilemma games with fixed matching to investigate the effect of different types of information on cooperation. The data come from 71 studies using the voluntary contributions paradigm, covering 122 data points, and from 18 studies on decision-making in oligopoly, covering another 50 data points. We find similar effects in the two sets of experimental games. We find that transparency about what everyone in a group earns reduces contributions to the public good, as well as the degree of collusion in oligopoly markets. In contrast, transparency about choices tends to lead to an increase in contributions and collusion, although the size of this effect varies somewhat between the two settings. Our results are potentially useful for policy making, because they provide guidance on the type of information to target in order to stimulate or limit cooperation.

Exogeneous disruptions in labor demand have become more frequent in recent times. The COVID-19 pandemic has resulted in millions of workers being repeatedly laid off and rehired according to local public health conditions. This may be bad news for market efficiency. Typical employment relations—which resemble non-enforceable (implicit) contracts—rely on reciprocity (Brown et al. in Econometrica 72:747–780, 2004), and hence could be harmed when workers’ efforts no longer guarantee reemployment in the next period. In this paper we extend the BFF paradigm to include a per-period probability (0%, 10%, 50%) of publicly observable “shutdown”, where a specific firm cannot contract with any workers for several periods. A Perfect Bayesian Equilibrium exists in which these shutdowns destabilize relationships, but do not harm efficiency. Our experiment shows that, remarkably, market efficiency can be maintained even with very frequent stochastic shutdowns. However, the dynamic of relational contracts changes from one where a worker finds stable employment to one where she juggles multiple employers, laying the burden of maintaining productivity upon workers and worsening worker-side inequality.

We consider multistage bidding models where two types of risky assets (shares) are tradedbetween two agents that have different information on the liquidation prices of tradedassets. These prices are random integer variables that are determined by the initialchance move according to a probability distribution p over thetwo-dimensional integer lattice that is known to both players. Player 1 is informed on theprices of both types of shares, but Player 2 is not. The bids may take any integer values.The model of n-stage bidding is reduced to a zero-sum repeated game withlack of information on one side. We show that, if liquidation prices of shares have finitevariances, then the sequence of values of n-step games is bounded. This makes itreasonable to consider the bidding of unlimited duration that is reduced to the infinitegame G∞(p). We give the solutions for thesegames. Optimal strategies of Player 1 generate random walks of transaction prices. Butunlike the case of one-type assets, the symmetry of these random walks is broken at thefinal stages of the game.

A matrix game is played repeatedly, with the actions taken at each stage determining both a reward paid to Player I and the probability of continuing to the next stage. An infinite history of play determines a sequence (Rn) of such rewards, to which we assign the payoff lim supn (R1 + · ·· + Rn). Using the concept of playable strategies, we slightly generalize the definition of the value of a game. Then we find sufficient conditions for the existence of a value and for the existence of stationary optimal strategies (Theorems 8 and 9). An example shows that the game need not have a value (Example 4).