Don't hate the player, hate the game: Uncovering the foundations of cheating in contests

Contests are meant to attract the best performers and incentivize high effort, however, they may also attract cheaters who try to win via illicit means which crowds out the best performers. We use a laboratory experiment to explore the role of self-selection in contests with a possibility of lying in a real effort task. Contrary to common wisdom, we do not find evidence that contests disproportionately attract intrinsic cheaters. However, we find that contests fail at selecting the best performers, as no difference is observed in the actual or perceived ability of those who selected into the contest versus those who selected into a comparable noncompetitive pay scheme

The optimal allocation of prizes in tournaments of heterogeneous agents

Tournaments are widely used in organizations, explicitly or implicitly, to reward the best-performing employees, e.g., through promotion or bonuses, and to punish the worst-performing employees, e.g., through firing or unfavorable job assignments. We use a principal-agent model to compare the efficiency of two tournament incentive schemes, reward tournament and punishment tournament, which, respectively, reward the best performer and punish the worst performer. We show that while the two schemes are equivalent when agents are symmetric in their ability, the equivalence is broken in the presence of heterogeneity. Specifically, punishment tournaments lead to higher profits of the firm. The reason is that low-ability agents are discouraged less in punishment tournaments than in reward tournaments, and hence can be compensated less to meet their participation constraints. Hence, our results predict that firms using punishment tournament contracts will perform better

Biased contests for symmetric players

In a biased contest, one of the players has an advantage in the winner determination process. We characterize a novel class of biased contest success functions pertaining to such contests and provide necessary and sufficient conditions for zero bias to be a critical point of arbitrary objectives satisfying certain symmetry restrictions. We, however, challenge the common wisdom that unbiased contests are always optimal when contestants are symmetric ex ante or even ex post. We show that contests with arbitrary favorites, i.e., biased contests of symmetric players, can be optimal in terms of various objectives such as expected aggregate effort, the probability to reveal the stronger player as the winner or expected effort of the winner

Biased contests for symmetric players

In a biased contest, one of the players has an advantage in the winner determination process. We characterize a novel class of biased contest success functions pertaining to such contests and provide necessary and sufficient conditions for zero bias to be a critical point of arbitrary objectives satisfying certain symmetry restrictions. We, however, challenge the common wisdom that unbiased contests are always optimal when contestants are symmetric ex ante or even ex post. We show that contests with arbitrary favorites, i.e., biased contests of symmetric players, can be optimal in terms of various objectives such as expected aggregate effort, the probability to reveal the stronger player as the winner or expected effort of the winner

Strive to be first or avoid being last: An experiment on relative performance incentives.

Managers often use tournaments which motivate workers to compete for the top, compete to avoid the bottom, or both. In this paper we compare the effectiveness and efficiency of the corresponding incentive schemes. To do so, we utilize optimal contracts in a principal-agent setting, using a Lazear-Rosen type model that predicts equal effort and efficiency levels for the three mechanisms with the appropriate distribution of prizes. We test the model's predictions in a laboratory experiment and find that a mechanism which incorporates both competition for the top and away from the bottom produces the highest effort from agents, especially in contests of a relatively larger size. Avoiding being last is shown to produce the lowest variance of effort, be more effective and, in larger contests, more efficient than competing for the top. Finally, we show that behavior in all mechanisms is consistent with basic directional and reinforcement learning

Strive to be first and avoid being last: An experiment on relative performance incentives

Managers often use tournament incentive schemes which motivate workers to compete for the top, compete to avoid the bottom, or both. In this paper we test the effectiveness and efficiency of these incentive schemes. To do so, we utilize optimal contracts in a principal-agent setting, using a Lazear-Rosen type model that predicts equal effort and efficiency levels for three tournament incentive schemes: reward tournaments, punishment tournaments, and tournaments combining reward and punishment. We test the model s predictions in a laboratory experiment and find that the combination of reward and punishment produces the highest effort from agents, especially in contests of a relatively larger size. Punishment is shown to be more effective and, in larger contests, more efficient than rewards, and it is also the mechanism with the lowest variance of effort. Finally, we show that behavior in all mechanisms is consistent with a model of basic directional and reinforcement learning

Corrupt Police

MacroeconomicsPERC Professor Danila Serra, along with Klaus Abbink and Dmitry Ryvkin employ laboratory experiments to examine the effects of corrupt law enforcement on crime within a society. The authors embed corruption in a social dilemma setting where citizens simultaneously choose whether to obey the law or to break the law and impose a negative externality on others. Police officers observe citizens’ behavior and decide whether to impose �nes on law-breakers or, in treatments with corruption, extort bribes from any citizen. In the �rst study, findings show that the presence of police substantially reduces crime, as compared to a baseline setting without police. This is true also when police officers are corrupt. This result is driven by corrupt police officers using bribes in a targeted manner as a substitute for official �nes to punish law-breakers. In the second study, the authors test the effectiveness of two reward mechanisms aimed at reducing police corruption, both of which are based on society-wide police performance measures and not on the observation/monitoring of individual officers. Results show that both mechanisms make bribery more targeted toward law-breakers, and one of them leads to a moderate reduction in crim

Fatigue in dynamic tournaments

Employee overwork and fatigue are a concern of managers in many organizations, as they may increase health and safety risks and decrease productivity. The problem is especially severe in competitive environments where compensation and promotions are awarded, explicitly or implicitly, on the basis of relative performance. In this paper, we propose a theory for, and study experimentally, the phenomenon of fatigue in dynamic contests aimed to mimic such settings. Theoretically, we find that if managers wish to avoid overwork, for example due to its negative impact on productivity, they should let their employees compete for promotion longer, with multiple intermediate performance evaluation stages. Experimentally, we find that subjects react strongly to changes in the environment related to fatigue and follow the comparative statics of equilibrium predictions. At the same time, within a given environment subjects behave as if they are unaware of the deteriorating effect of fatigue on their competitiveness. The results suggest that nonspecific information on consequences of fatigue is more effective than targeted information on how fatigue affects an employee’s chances of winning the competition.overwork, fatigue, dynamic contest, experiment