The strategy frequency estimation method (Dal Bó and Fréchette in Am Econ Rev 101(1):411-429, 2011; Fudenberg in Am Econ Rev 102(2):720-749, 2012) allows us to estimate the fraction of subjects playing each of a list of strategies in an infinitely repeated game. Currently, this method assumes that subjects tremble with the same probability. This paper extends this method, so that subjects’ trembles can be heterogeneous. Out of 60 ex ante plausible specifications, the selected model uses the six strategies described in Dal Bó and Fréchette (2018), and allows the distribution of trembles to vary by strategy.

We systematically investigate prisoner’s dilemma and dictator games with valence framing. We find that give versus take frames influence subjects’ behavior and beliefs in the prisoner’s dilemma games but not in the dictator games. We conclude that valence framing has a stronger impact on behavior in strategic interactions, i.e., in the prisoner’s dilemma game, than in allocation tasks without strategic interaction, i.e., in the dictator game.

We join a growing body of literature suggesting that the languages people speak influence their decision-making. We tested whether dropping the first-person pronoun “I” affects pro-social behavior in a dictator game-like setting. To this end, we conducted an online randomized, incentivized experiment with a socially representative sample of 2000 Japanese respondents. We provide compelling causal evidence that pronoun dropping reduces pro-sociality. Given that our results provide little empirical support for previous research findings linking first-person pronoun use and lower pro-sociality, we prescribe caution in using languages as a proxy for culture in several cross-country empirical studies in economics.

In this paper, motivated by aspects of preregistration plans we discuss issues that we believe have important implications for how experiments are designed. To make possible valid inferences about the effects of a treatment in question, we first illustrate how economic theories can help allocate subjects across treatments in a manner that boosts statistical power. Using data from two laboratory experiments where subject behavior deviated sharply from theory, we show that the ex-post subject allocation to maximize statistical power is closer to these ex-ante calculations relative to traditional designs that balances the number of subjects across treatments. Finally, we call for increased attention to (i) the appropriate levels of the type I and type II errors for power calculations, and (ii) how experimenters consider balance in part by properly handling over-subscription to sessions.

The hypothesis that intuition promotes cooperation has attracted considerable attention. Although key results in this literature have failed to replicate in pre-registered studies, recent meta-analyses report an overall effect of intuition on cooperation. We address the question with a meta-analysis of 82 cooperation experiments, spanning four different types of intuition manipulations—time pressure, cognitive load, depletion, and induction—including 29,315 participants in total. We obtain a positive overall effect of intuition on cooperation, though substantially weaker than that reported in prior meta-analyses, and between studies the effect exhibits a high degree of systematic variation. We find that this overall effect depends exclusively on the inclusion of six experiments featuring emotion-induction manipulations, which prompt participants to rely on emotion over reason when making allocation decisions. Upon excluding from the total data set experiments featuring this class of manipulations, between-study variation in the meta-analysis is reduced substantially—and we observed no statistically discernable effect of intuition on cooperation. Overall, we fail to obtain compelling evidence for the intuitive cooperation hypothesis.

We provide the first, in experimental economics, consistent estimates of a dynamic learning model with a continuous outcome. The econometric approach we propose can be used in many experimental studies including auctions, bargaining with transfers, and gift exchange experiments. We focus on affiliated private value auctions, where subjects are generally assumed to converge to the rule-of-thumb bidding, but our general approach is applicable to many other settings. Our IV estimates suggest that subjects become significantly less aggressive over time; specifically, they decrease their bids in proportion to the previous period’s signal minus bid. However, the inconsistent OLS and FE estimators imply that subjects become significantly more aggressive over time—they raise their bids in proportion to the previous period’s signal minus bid. Our instruments are randomly generated by the experiment, and pass popular weak instrument tests.

This paper empirically compares the use of straightforward verses more complex methods to estimate public goods game data. Five different estimation methods were compared holding the dependent and explanatory variables constant. The models were evaluated using a large out-of-sample cross-country public goods game data set. The ordered probit and tobit random-effects models yielded lower p values compared to more straightforward models: ordinary least squares, fixed and random effects. However, the more complex models also had a greater predictive bias. The straightforward models performed better than expected. Despite their limitations, they produced unbiased predictions for both the in-sample and out-of-sample data.

This article studies whether people want to control what information on their own past pro-social behavior is revealed to others. Participants are assigned a color that depends on their past pro-social behavior. They can spend money to manipulate the probability with which their color is revealed to another participant. The data show that participants are more likely to reveal colors with more favorable informational content. This pattern is not found in a control treatment in which colors are randomly assigned, thus revealing nothing about past pro-social behavior. Regression analysis confirms these findings, also when controlling for past pro-social behavior. These results complement the existing empirical evidence, confirming that people strategically and, therefore, consciously manipulate their social image.

Accurately estimating risk preferences is of critical importance when evaluating data from many economic experiments or strategic interactions. I use a simulation model to conduct power analyses over two lottery batteries designed to classify individual subjects as being best explained by one of a number of alternative specifications of risk preference models. I propose a case in which there are only two possible alternatives for classification and find that the statistical methods used to classify subjects result in type I and type II errors at rates far beyond traditionally acceptable levels. These results suggest that subjects in experiments must make significantly more choices, or that traditional lottery pair batteries need to be substantially redesigned to make accurate inferences about the risk preference models that characterize a subject’s choices.

Households are frequently subject to income and asset shocks. We performed a lab experiment, inducing losses on a real effort task, after which we measured cognitive performance, loss aversion and cheating behavior. We found that asset losses, but not income losses, act as a cognitive load, by decreasing accuracy and increasing response times. We did not detect any change in dishonesty or loss aversion.

Statistical power is an important detail to consider in the design phase of any experiment. This paper serves as a reference for experimental economists on power calculations. We synthesize many of the questions and issues frequently brought up regarding power calculations and the literature that surrounds that. We provide practical coded examples and tools available for calculating power, and suggest when and how to report power calculations in published studies.

Most large real-world organizations contain multiple smaller groups, such as working groups within firms. However, can this sort of nested groups be used to alleviate coordination failures in the larger group? We report on a multi-player Stag Hunt experiment wherein we hierarchically structure a large group into mutually exclusive small groups. We offer varying incentive payments if efficient coordination is achieved at a large or small group level. The novelty of our design is that we hold the total payment size constant between treatments. In our nested incentive treatment, we reduce the reward for achieving large-group coordination by a small amount and reallocate the same amount to successful small-group coordination. The results reveal that incentive reallocations privileging small groups facilitate efficient large-group coordination in the nested group structure.

The present study investigates the framing effect of tax–transfer systems on work effort decisions. We devised two theoretically equivalent treatments—the redistributive tax treatment and the redistributive transfer treatment—and studied subjects’ work effort choices in a novel public goods experiment. We found that subjects chose higher effort levels when redistribution took place via transfers than via taxes. Interestingly, the treatment effect was more pronounced among those with lower cognitive abilities and those who judged the tax–transfer system to be unfair. The results have the potential to offer insight on the debate about the extent to which taxes or transfers should be actively used for redistribution.

We test whether anchoring affects people’s elicited valuations for a bottle of wine in individual decision-making and in markets. We anchor subjects by asking them if they are willing to sell a bottle of wine for a transparently uninformative random price. We elicit subjects’ Willingness-To-Accept for the bottle before and after the market. Subjects participate in a double auction market either in a small or a large trading group. The variance in subjects’ Willingness-To-Accept shrinks within trading groups. Our evidence supports the idea that markets have the potential to diminish anchoring effects. However, the market is not needed: our anchoring manipulation failed in a large sample. In a concise meta-analysis, we identify the circumstances under which anchoring effects of preferences can be expected.

There is a long-standing unresolved debate in game theory and experimental economics regarding the behavioral equivalence of the direct-response method (hot play) and the strategy method (cold play). Using a unified experimental framework, we compare behavior elicited via both methods in four different Centipede Games that differ in their incentives to take or pass, in the evolution of those incentives over decision nodes, and in the asymmetry of the incentives across the two player roles. Out of the four Centipede Games, we find that both methods yield statistically different behavior in two of them, while in the remaining two we cannot reject the same behavior across the hot and cold methods. Whenever the behavior diverges, hot play consistently makes individuals stop earlier. These findings should shift the question from whether both methods are generically behaviorally equivalent to under which conditions they are (not) and why.

LIONESS Lab is a free web-based platform for interactive online experiments. An intuitive, user-friendly graphical interface enables researchers to develop, test, and share experiments online, with minimal need for programming experience. LIONESS Lab provides solutions for the methodological challenges of interactive online experimentation, including ways to reduce waiting time, form groups on-the-fly, and deal with participant dropout. We highlight key features of the software, and show how it meets the challenges of conducting interactive experiments online.