Real-effort experiments are frequently used when examining a response to incentives. For a real-effort task to be well suited for such an exercise its measurable output must be sufficiently elastic over the incentives considered. The popular slider task in Gill and Prowse (Am Econ Rev 102(1):469–503, 2012) has been characterized as satisfying this requirement, and the task is increasingly used to investigate the response to incentives. However, a between-subject examination of the slider task’s response to incentives has not been conducted. We provide such an examination with three different piece-rate incentives: half a cent, two cents, and eight cents per slider completed. We find only a small increase in performance: despite a 1500 % increase in the incentives, output only increases by 5 %. With such an inelastic response we caution that for typical experimental sample sizes and incentives the slider task is unlikely to demonstrate a meaningful and statistically significant performance response.

In oligopoly, imitating the most successful competitor yields very competitive outcomes. This theoretical prediction has been confirmed experimentally by a number of studies. A recent paper by Friedman et al. (J Econ Theory 155:185–205, 2015) qualifies those results in an interesting way: While they replicate the very competitive results for the first 25–50 periods, they show that when using a much longer time horizon of 1200 periods, results slowly turn to more and more collusive outcomes. We replicate their result for duopolies. However, with 4 firms, none of our oligopolies becomes permanently collusive. Instead, the average quantity always stays above the Cournot–Nash equilibrium quantity. Thus, it seems that “four remain many” even with 1200 periods.

In an experiment, we first elicit the distributional preferences of subjects and then let them bid for a lottery, either in a Becker–DeGroot–Marschak (BDM) mechanism or a Vickrey auction (VA). The standard theory predicts that altruistic subjects underbid in the VA—compared to the BDM—while spiteful subjects overbid in the VA. The data do not confirm those predictions. While we observe aggregate underbidding in the VA, the result is not driven by the choices of altruistic subjects.

We examine a variant of ultimatum bargaining in which principals may delegate their proposal decision to agents hired from a competitive market. Contrary to several prior studies, we find that when principals must use agents, the resulting proposals are significantly higher than when principals make proposals themselves. In reconciling our results with prior findings, we conclude that both the rejection power afforded to responders and the structure of principal-agent contracts can play significant roles in the nature of outcomes under delegated bargaining.

This paper investigates how process data like response time and click position relates to economic decisions. We use a social value orientation experiment, which can be considered as a prototypical multi-attribute decision problem. We find that in the social value orientation task more individualistic subjects have shorter response times than prosocial subjects. Individualistic subjects click more often on their own payoffs than on the others’ payoffs, and they click more often on their own payoffs than prosocial subjects. Moreover, the response time information and the click position information are complementary in explaining subjects’ preferences. These results show that response times and click positions can be used as indicators of people’s preferences.

We exhibit a mechanism by which two parties leverage their social relationship to ratchet up the rents they collect from a third party residual claimant. Specifically, in a laboratory environment, we study a novel three-person insider game in which ‘insiders’ decide how to distribute profits among themselves and an ‘outsider’ who is the residual claimant. We find that the distribution of payments is largely determined by an informal quid pro quo among the two decision makers at the expense of the outsider. We then manipulate pay transparency and the competition to keep interaction partners, thereby improving the strategic position of one insider. Pay transparency increases the profit share that goes to rent seekers. In addition, rent extraction from the third party persists when competition for interaction partners is introduced. As a result, we find that payments both affect and reflect the influence of social relationships.

This study investigates whether individuals engage in prosocial behavior when it requires an investment of their time, but not money. In a laboratory experiment with rigorous anonymity arrangements, senders receive their payoff at the beginning. They may then engage in a tedious task to increase the earnings of exogenously disadvantaged recipients who otherwise receive no earnings. We find that senders are willing to sacrifice time to benefit recipients. Whether or not the recipient is present in the laboratory during the working time does not alter this decision. However, in a treatment variation some senders also display antisocial behavior.

Most economic experiments designed to test theories carefully choose specific games. This paper reports on an experimental design to evaluate how well the minimax hypothesis describes behavior across a population of games. Past studies suggest that the hypothesis is more accurate the closer the equilibrium is to equal probability play of all actions, but many differences between the designs makes direct comparison impossible. We examine the minimax hypothesis by randomly sampling constant sum games with two players and two actions with a unique equilibrium in mixed strategies. Only varying the games, we find behavior is more consistent with minimax play the closer the mixed strategy equilibrium is to equal probability play of each action. The results are robust over all iterations as well as early and final play. Experimental designs in which the game is a variable allow some conclusions to be drawn that cannot be drawn from more conventional experimental designs.

Betrayal aversion has been operationalized as the evidence that subjects demand a higher risk premium to take social risks compared to natural risks. This evidence has been first shown by Bohnet and Zeckhauser (J Econ Behav 98:294–310, 2004) using an adaptation of the Becker–DeGroot–Marschak mechanism (BDM, Becker et al. Behav Sci 9:226–232, 1964). We compare their implementation of the BDM mechanism with a new version designed to facilitate subjects’ comprehension. We find that, although the two versions produce different distributions of values, the size of betrayal aversion, measured as an average treatment difference between social and natural risk settings, is not different across the two versions. We further show that our implementation is preferable to use in practice as it reduces substantially subjects’ mistakes and the likelihood of noisy valuations.

We report on the results of an experiment with a statistical choice task involving the toss of a fair coin. In our experiment, participants had to decide whether they were willing to pay a price to switch from betting on the future performance of one player to betting on that of another player. The switch was from a player who had been previously less successful in betting on five coin flips to another one who had been more successful in the same task. We conducted a treatment with the Becker–DeGroot–Marschak mechanism and one in which participants were faced with a fixed price. In both cases, participants exhibit a strong bias towards placing their bets on players with a good guessing history in the coin toss task. Participants’ behaviour is compatible with prescriptive luck beliefs, that is, the idea that luck is a somehow deterministic and personal attribute.

In this article, we highlight how simulation methods can be used to analyze power of economic experiments. We provide the powerBBK package programmed for experimental economists, that can be used to perform simulations in STATA. Power can be simulated using a single command line for various statistical tests (nonparametric and parametric), estimation methods (linear, binary, and censored regression models), treatment variables (binary, continuous, time-invariant or time varying), sample sizes, experimental periods, and other design features (within or between-subjects design). The package can be used to predict minimum sample sizes required to reach a user-specific level of power, to maximize power of a design given the researcher supplied a budget constraint, or to compute power to detect a user-specified treatment order effect in within-subjects designs. The package can also be used to compute the probability of sign errors—the probability of rejecting the null hypothesis in the wrong direction as well as the share of rejections pointing in the wrong direction. The powerBBK package is provided as an .ado file along with a help file, both of which can be downloaded here (http://www.bbktools.org).

A number of recent papers have looked at framing effects in linear public good games. In this comment, I argue that, within this literature, the distinction between give-take and positive–negative framing effects has become blurred, and that this is a barrier towards understanding the experimental evidence on framing effects. To make these points, I first illustrate that frames can differ along both an externality and choice dimension. I then argue that the existing evidence is consistent with a strong positive–negative framing effect but no give-take framing effect on average contributions.

This paper specifies the panel data experimental design condition under which ordinary least squares, fixed effects, and random effects estimators yield identical estimates of treatment effects. This condition is relevant to the large body of laboratory experimental research that generates panel data. Although the point estimates and the true standard errors of the estimated average treatment effects are identical across the three estimators, the estimated standard errors differ. A standard F test as well as asymptotic reasoning guide the choice of which estimated standard errors are the appropriate ones to use for statistical inference.