We used eye-tracking to measure the dynamic patterns of visual information acquisition in two-player normal-form games. Participants played one-shot games in which either, neither, or only one of the players had a dominant strategy. First, we performed a mixture models cluster analysis to group participants into types according to the pattern of visual information acquisition observed in a single class of games. Then, we predicted agents' choices in different classes of games and observed that patterns of visual information acquisition were game invariant. Our method allowed us to predict whether the decision process would lead to equilibrium choices or not, and to attribute out-of-equilibrium responses to limited cognitive capacities or social motives. Our results suggest the existence of individually heterogeneous-but-stable patterns of visual information acquisition based on subjective levels of strategic sophistication and social preferences

Previous experimental research suggests that individuals apply rules of thumb to a simplified mental model of the “real” decision problem. We claim that this simplification is obtained either by neglecting the other players’ incentives and beliefs or by taking them into consideration only for a subset of game outcomes. We analyze subjects’ eye movements while playing a series of two-person, 3 × 3 one-shot games in normal form. Games within each class differ by a set of descriptive features (i.e., features that can be changed without altering the game equilibrium properties). Data show that subjects on average perform partial or non-strategic analysis of the payoff matrix, often ignoring the opponent´s payoffs and rarely performing the necessary steps to detect dominance. Our analysis of eye-movements supports the hypothesis that subjects use simple decision rules such as “choose the strategy with the highest average payoff” or “choose the strategy leading to an attractive and symmetric outcome” without (optimally) incorporating knowledge on the opponent’s behavior. Lookup patterns resulted being feature and game invariant, heterogeneous across subjects, but stable within subjects. Using a cluster analysis, we find correlations between eye-movements and choices; however, applying the Cognitive Hierarchy model to our data, we show that only some of the subjects present both information search patterns and choices compatible with a specific cognitive level. We also find a series of correlations between strategic behavior and individual characteristics like risk attitude, short-term memory capacity, and mathematical and logical abilities.

We here present both experimental and theoretical results for an Anticipation Game, a two-stage game wherein the standard Dictator Game is played after a matching phase wherein receivers use the past actions of dictators to decide whether to interact with them. The experimental results for three different treatments show that partner choice induces dictators to adjust their donations towards the expectations of the receivers, giving significantly more than expected in the standard Dictator Game. Adding noise to the dictators’ reputation lowers the donations, underlining that their actions are determined by the knowledge provided to receivers. Secondly, we show that the recently proposed stochastic evolutionary model where payoff only weakly drives evolution and individuals can make mistakes requires some adaptations to explain the experimental results. We observe that the model fails in reproducing the heterogeneous strategy distributions. We show here that by explicitly modelling the dictators’ probability of acceptance by receivers and introducing a parameter that reflects the dictators’ capacity to anticipate future gains produces a closer fit to the aforementioned strategy distributions. This new parameter has the important advantage that it explains where the dictators’ generosity comes from, revealing that anticipating future acceptance is the key to success.

Paying on the basis of fee‐for‐service (FFS) is often associated with a risk of overprovision. Policymakers are therefore increasingly looking to other payment schemes to ensure a more efficient delivery of health care. This study tests whether context plays a role for overprovision under FFS. Using a laboratory experiment involving medical students, we test the extent of overprovision under FFS when the subjects face different fee sizes, patient types, and market conditions. We observe that decreasing the fee size has an effect on overprovision under both market conditions. We also observe that patients who are harmed by excess treatment are at little risk of overprovision. Finally, when subjects face resource constraints but still have an incentive to overprovide high‐profit services, they hesitate to do so, implying that the presence of opportunity costs in terms of reduced benefits to other patients protects against overprovision. Thus, this study provides evidence that the risk of overprovision under FFS depends on fee sizes, patients' health profiles, and market conditions.

Many physicians receive a payment for their performance (P4P). This performance is often linked to a health target that triggers a bonus when met. For some patients the target is easily met, while others require a significant amount of care to reach the target (if ever). This study contributes to the literature by providing evidence of how P4P affects allocation of care across patients with low and high responsiveness to treatment compared to a fixed payment, such as capitation and salary, under different degrees of resource constraint. Our evidence is based on a controlled laboratory experiment involving 143 medical students in Denmark in 2019. We find that patients who have the potential to reach the health target, gain care under P4P, whereas patients with no potential to reach it, may receive less care. Redistribution of care between patients under P4P arises when physicians are resource constrained. As many physicians are currently operating under tight resource constraints, policymakers should be careful to avoid unintended inequalities in patients' access to health care when introducing P4P. Risk-adjusting the performance target may potentially solve this issue.