Despite substantial evidence for the effectiveness of monetary incentives, some experiments have shown that high-powered incentives might lead to lower performance than lesser incentives. This study explores whether firms have means to counter these potential negative effects. Building on a standard experimental design identifying the drawbacks of large-stake rewards, it shows that when workers either self-select into the task or have prior practice, high-powered incentives lead to higher average performance than a smaller reward. This effect is driven mainly by selection and practice increasing the share of workers who respond positively to high-powered incentives. These results suggest that firms have natural instruments to deal with the potential adverse effects of high-powered incentives.

A growing number of studies use “real” effort designs for laboratory experiments where subjects complete an actual task to exert effort rather than using a stylized effort design where subjects simply choose an effort level from a predefined set. The commonly argued reason for real effort is that it makes the results more generalizable and field relevant. We investigate the nature of modeling effort provision by first trying to provide a clear theoretical understanding of the nature of effort costs. We then empirically examine claims about the differences between real effort and stylized effort. A key to our examination is ensuring that we compare the two modes of effort provision keeping effort costs constant, which is a point overlooked in many past examinations. In our data, when controlling for effort costs, we find no differences in behavior between real and stylized effort. Given the importance of effort costs and the lack of a generally accepted way to include them in real effort designs, we provide a simple add-on that any researcher can use with their real effort experiments to incorporate a theoretically appropriate and controlled cost of effort even in a real effort setting. We also discuss ways to better approach modeling effort costs in experiments, whether one is conducting real or stylized designs, to improve inference on research questions.

Using public goods games in a laboratory setting, we study team-level production, where two teams compete for the resources of a common-member who can benefit from and provide effort in both teams. Intrinsically, the common-member faces divided loyalties. We examine such competition in a setting in which the common-member has productive abilities equal to that of the other team members (dedicated-members), and in two settings where he/she has greater relative potential. When effort (contributions) by the common-member have greater productivity (coupled with higher opportunity costs to contribute) in providing the public good relative to that of dedicated-members, we find team performance is not significantly increased. On the other hand, when the common-member has a greater endowment, sufficient to match the absolute contributions of team members in both teams, there is a significant increase in team performance. The evidence suggests that a norm of reciprocity by dedicated-members based on absolute contributions of the common-member better explains behavior than a norm based on the value added of the common-member's contributions. This behavior, along with fairness norms elicited in a survey, suggests that on average dedicated members do not sufficiently incorporate the common-members' higher opportunity costs in the treatment where his/her productivity is increased. This setting provides an important illustration of where the behavioral response to the type of inequality matters, leading to differences in team efficiency.

I experimentally investigate whether there is a gender difference in advice giving in a gender-neutral task with varying difficulty in which the incentives of the sender and the receiver are perfectly aligned. I find that women are more reluctant to give advice compared to men for difficult questions. The gender difference in advice giving cannot be explained by gender differences in performance. Self-confidence explains some of the gender gap, but not all. The gender gap disappears if advice becomes enforceable. Introducing a model of guilt and responsibility, I discuss possible underlying mechanisms that are consistent with the findings.

We introduce price freeze options into a model of sequential search. The model's predictions are tested in a laboratory experiment. The experiment varies (1) whether freezing is possible or not, (2) the cost of freezing, and (3) the time horizon. Overall, the observed treatment effects are consistent with the predictions of our model. Assuming that individuals experience regret, fail to ignore sunk search costs, misperceive the number of periods remaining, or are risk-averse, does not improve upon the performance of the model. Our results support the use of the assumption of optimal search behavior in theoretical and empirical studies.

This paper reports a series of experiments designed to evaluate how the advertised participation payment impacts participation rates in laboratory experiments. Our initial goal was to generate variation in the participation rate as a means to control for selection bias when evaluating treatment effects in common laboratory experiments. Initially, we varied the advertised participation payment to 1734 people from $\mathrm{\$}5$ to $\mathrm{\$}15$ using standard email recruitment procedures, but found no statistical evidence this impacted the participation rate. A second study increased the advertised payment up to $\mathrm{\$}100$. Here, we find marginally significant statistical evidence that the advertised participation payment affects the participation rate when payments are large. To combat skepticism of our results, we also conducted a third study in which verbal offers were made. Here, we found no statistically significant increase in participation rates when the participation payment increased from $\mathrm{\$}5$ to $\mathrm{\$}10$. Finally, we conducted an experiment similar to the first one at a separate university. We found no statistically significant increase in participation rates when the participation payment increased from $\mathrm{\$}7$ to $\mathrm{\$}15$. The combined results from our four experiments suggest moderate variation in the advertised participation payment from standard levels has little impact on participation rates in typical laboratory experiments. Rather, generating useful variation in participation rates likely requires much larger participation payments and/or larger potential subject pools than are common in laboratory experiments.

Pledges are ubiquitous in charitable giving, but they are often reneged upon. To investigate whether adding the phrase “I swear” to pledge language can reduce pledge reneging, we conduct a series of experiments in the context of online fundraising. We find that including “I swear” at the beginning of the pledge language significantly increases immediate giving and pledge fulfillment, with more individuals switching from pledging to giving immediately. We also observe individual heterogeneity in moral identity: Our findings are present among individuals with low moral identity, but not among those with high moral identity. Our paper presents a simple and no-cost strategy for increasing the effectiveness of pledges in online fundraising.

Disappointment aversion has been suggested as an explanation for non-truthful rankings in strategy-proof school-choice matching mechanisms. We test this hypothesis using a novel experimental design that eliminates important alternative causes of non-truthful rankings. The design uses a simple contingent choice task with only two possible outcomes. Between two treatments, we manipulate the possibility for disappointment aversion to have an effect on ranking. We find a small and statistically marginally significant treatment effect in the direction predicted by disappointment aversion. We therefore conclude that disappointment aversion is a minor contributor to non-truthful rankings in strategy-proof school-choice matching mechanisms.

We investigate the role of visual attention in risky choice in a rich experimental dataset that includes eye-tracking data. We first show that attention is not reducible to individual and contextual variables, which explain only 20% of attentional variation. We then decompose attentional variation into individual average attention and trial-wise deviations of attention to capture different cognitive processes. Individual average attention varies by individual, and can proxy for individual preferences or goals (as in models of “rational inattention” or goal-directed attention). Trial-wise deviations of attention vary within subjects and depend on contextual factors (as in models of “salience” or stimulus-driven attention). We find that both types of attention predict behavior: average individual attention patterns are correlated with individual levels of loss aversion and capture part of this individual heterogeneity. Adding trial-wise deviations of attention further improves model fit. Our results show that a decomposition of attention into individual average attention and trial-wise deviations of attention can capture separable cognitive components of decision making and provides a useful tool for economists and researchers from related fields interested in decision-making and attention.