z-Tree (Zurich Toolbox for Ready-made Economic Experiments) is a software for developing and conducting economic experiments. The software is stable and allows programming almost any kind of experiments in a short time. In this article, I present the guiding principles behind the software design, its features, and its limitations.

Over the last 25 years, more than a hundred dictator game experiments have been published. This meta study summarises the evidence. Exploiting the fact that most experiments had to fix parameters they did not intend to test, in multiple regression the meta study is able to assess the effect of single manipulations, controlling for a host of alternative explanatory factors. The resulting rich dataset also provides a testbed for comparing alternative specifications of the statistical model for analysing dictator game data. It shows how Tobit models (assuming that dictators would even want to take money) and hurdle models (assuming that the decision to give a positive amount is separate from the choice of amount, conditional on giving) provide additional insights.

Online labor markets have great potential as platforms for conducting experiments. They provide immediate access to a large and diverse subject pool, and allow researchers to control the experimental context. Online experiments, we show, can be just as valid—both internally and externally—as laboratory and field experiments, while often requiring far less money and time to design and conduct. To demonstrate their value, we use an online labor market to replicate three classic experiments. The first finds quantitative agreement between levels of cooperation in a prisoner's dilemma played online and in the physical laboratory. The second shows— consistent with behavior in the traditional laboratory—that online subjects respond to priming by altering their choices. The third demonstrates that when an identical decision is framed differently, individuals reverse their choice, thus replicating a famed Tversky-Kahneman result. Then we conduct a field experiment showing that workers have upward-sloping labor supply curves. Finally, we analyze the challenges to online experiments, proposing methods to cope with the unique threats to validity in an online setting, and examining the conceptual issues surrounding the external validity of online results. We conclude by presenting our views on the potential role that online experiments can play within the social sciences, and then recommend software development priorities and best practices.

I survey the literature post Ledyard (Handbook of Experimental Economics, ed. by J. Kagel, A. Roth, Chap. 2, Princeton, Princeton University Press, 1995) on three related issues in linear public goods experiments: (1) conditional cooperation; (2) the role of costly monetary punishments in sustaining cooperation and (3) the sustenance of cooperation via means other than such punishments. Many participants in laboratory public goods experiments are “conditional cooperators” whose contributions to the public good are positively correlated with their beliefs about the average group contribution. Conditional cooperators are often able to sustain high contributions to the public good through costly monetary punishment of free-riders but also by other mechanisms such as expressions of disapproval, advice giving and assortative matching.

Experimenter demand effects refer to changes in behavior by experimental subjects due to cues about what constitutes appropriate behavior. We argue that they can either be social or purely cognitive, and that, when they may exist, it crucially matters how they relate to the true experimental objectives. They are usually a potential problem only when they are positively correlated with the true experimental objectives’ predictions, and we identify techniques such as non-deceptive obfuscation to minimize this correlation. We discuss the persuasiveness or otherwise of defenses that can be used against demand effects criticisms when such correlation remains an issue.

We conducted the first randomized controlled field experiment of an Internet reputation mechanism. A high-reputation, established eBay dealer sold matched pairs of lots— batches of vintage postcards—under his regular identity and under new seller identities (also operated by him). As predicted, the established identity fared better. The difference in buyers’ willingness-to-pay was 8.1% of the selling price. A subsidiary experiment followed the same format, but compared sales by relatively new sellers with and without negative feedback. Surprisingly, one or two negative feedbacks for our new sellers did not affect buyers’ willingness-to-pay.

This paper reports the findings of a meta-analysis of 37 papers with 75 results from ultimatum game experiments. We find that on average the proposer offers 40% of the pie to the responder. This share is smaller for larger pie sizes and larger when a strategy method is used or when subjects are inexperienced. On average 16% of the offers is rejected. The rejection rate is lower for larger pie sizes and for larger shares offered. Responders are less willing to accept an offer when the strategy method is employed. As the results come from different countries, meta-analysis provides an alternative way to investigate whether bargaining behavior in ultimatum games differs across countries. We find differences in behavior of responders (and not of proposers) across geographical regions. With one exception, these differences cannot be attributed to various cultural traits on which for instance the cultural classifications of Hofstede (1991) and Inglehart (2000) are based.

In this paper, we present a first survey of the literature regarding whether the strategy method, in which a responder makes conditional decisions for each possible information set, leads to different experimental results than does the more standard direct-response method, in which the responder learns the action of the first mover and then chooses a response. Of the twenty-nine existing comparisons, sixteen find no difference, while four do find differences, and nine comparisons find mixed evidence. We also find some indications about the underlying determinants of when the two methods lead to different responses. For example, it appears that levels of punishment are substantially lower with the strategy method. In addition, it also appears that difference across these elicitation methods are more likely when people make fewer contingent choices. Finally, in no case do we find that a treatment effect found with the strategy method is not observed with the direct-response method.

Many economic, political and social environments can be described as contests in which agents exert costly effort while competing over the distribution of a scarce resource. These environments have been studied using Tullock contests, all-pay auctions and rank-order tournaments. This survey provides a comprehensive review of experimental research on these three canonical contests. First, we review studies investigating the basic structure of contests, including the number of players and prizes, spillovers and externalities, heterogeneity, risk and incomplete information. Second, we discuss dynamic contests and multi-battle contests. Then we review studies examining sabotage, feedback, bias, collusion, alliances, group contests and gender, as well as field experiments. Finally, we discuss applications of contests and suggest directions for future research.

Experimental dictator games have been used to explore unselfish behaviour. Evidence is presented here, however, that subjects’ generosity can be reversed by allowing them to take a partner's money. Dictator game giving therefore does not reveal concern for consequences to others existing independently of the environment, as posited in rational choice theory. It may instead be an artefact of experimentation. Alternatively, evaluations of options depend on the composition of the choice set. Implications of these possibilities are explored for experimental methodology and charitable donations respectively. The data favour the artefact interpretation, suggesting that demand characteristics of experimental protocols merit investigation, and that economic analysis should not exclude context-specific social norms.

Objective: To use meta-analysis techniques to assess the impact of various factors on the extent of cooperation in standard linear public goods experiments using the voluntary contributions mechanism.

Data Sources: Potentially relevant experiments were identified through searches of EconLit, the Internet Documents in Economics Access Service (IDEAS), and a survey article.

Review Methods: A total of 349 potentially relevant studies were identified. Of these, 27 (representing a total of 711 groups of participants) met the inclusion criteria. Data were abstracted from these studies using a standardized protocol. Results were analyzed using weighted ordinary least squares. Average group efficiency was the dependent variable.

Results: The marginal per capita return, communication, constant group composition over the session (“partners”), positive framing, and the use of children as subjects had a positive and significant effect (p < 0.05) on the average level of contribution to the public good. Heterogeneous endowments to subjects, experienced participants, and soliciting subjects’ beliefs regarding other participants’ behaviour prior to the start of the session/period had a negative and significant effect. A number of other factors were not identified as significant.

Conclusion: The meta-analysis results parallel several key findings from previous literature reviews. In addition, they offer parameter estimates and an analysis of significance based on the totality of the available research evidence. More consistent reporting of the results of experiments would greatly improve the ability to conduct this type of research.

We examine the properties of a popular method for eliciting choices and values from experimental subjects, the multiple price list format. The main advantage of this format is that it is relatively transparent to subjects and provides simple incentives for truthful revelation. The main disadvantages are that it only elicits interval responses, and could be susceptible to framing effects. We consider extensions to address and evaluate these concerns. We conclude that although there are framing effects, they can be controlled for with a design that allows for them. We also find that the elicitation of risk attitudes is sensitive to procedures, subject pools, and the format of the multiple price list table, but that the qualitative findings that participants are generally risk averse is robust. The elicitation of discount rates appear less sensitive to details of the experimental design.

What motivates people to trust and be trustworthy? Is trust solely “calculative,” based on the expectation of trustworthiness, and trustworthiness only reciprocity? Employing a within-subject design, we run investment and dictator game experiments in Russia, South Africa and the United States. Additionally, we measured risk preferences and expectations of return. Expectations of return account for most of the variance in trust, but unconditional kindness also matters. Variance in trustworthiness is mainly accounted for by unconditional kindness, while reciprocity plays a comparatively small role. There exists some heterogeneity in motivation but people behave surprisingly similarly in the three countries studied.

Controlled laboratory conditions using monetary incentives have been utilized in previous studies that examine individual discount rates, and researchers have found several apparently robust anomalies. We conjecture that subject behavior in these experiments may be affected by (uncontrolled) factors other than discount rates. We address some experimental design issues and report a new series of experiments designed to elicit individual discount rates. Our primary treatments include: (i) informing subjects of the annual and effective interest rates associated with alternative payment streams, and (ii) informing subjects of current market interest rates. We also test for the effect of real (vs. hypothetical) payments and for the effect of delaying both payment options (vs. offering an immediate payment option). The statistical analysis uses censored data techniques to account for the interactions between field and lab incentives. Each of the information treatments appears to reduce revealed discount rates. When both types of information are provided, annual rates in the interval of 15%—17.5% are revealed, whereas rates of 20%-25% are revealed in the control session. Each of the treatments also lowers the residual variance of subject responses.

This article investigates the use of standard econometric models for quantal choice to study equilibria of extensive form games. Players make choices based on a quantal-choice model and assume other players do so as well. We define an agent quantal response equilibrium (AQRE), which applies QRE to the agent normal form of an extensive form game and imposes a statistical version of sequential rationality. We also define a parametric specification, called logit-AQRE, in which quantal-choice probabilities are given by logit response functions. AQRE makes predictions that contradict the invariance principle in systematic ways. We show that these predictions match up with some experimental findings by Schotter et al. (1994) about the play of games that differ only with respect to inessential transformations of the extensive form. The logit-AQRE also implies a unique selection from the set of sequential equilibria in generic extensive form games. We examine data from signaling game experiments by Banks et al. (1994) and Brandts and Holt(1993). We find that the logit-AQRE selection applied to these games succeeds in predicting patterns of behavior observed in these experiments, even when our prediction conflicts with more standard equilibrium refinements, such as the intuitive criterion. We also reexamine data from the McKelvey and Palfrey (1992) centipede experiment and find that the AQRE model can account for behavior that had previously been explained in terms of altruistic behavior.

This paper provides a comparative-statics analysis of punishment in public-good experiments. We vary the effectiveness of punishment, that is, the factor by which punishment reduces the punished player's income. The data show that contributions increase monotonically in punishment effectiveness. High effectiveness leads to near complete cooperation and welfare improvements. Below a certain threshold, however, punishment cannot prevent the decay of cooperation. In these cases, punishment opportunities reduce welfare. The results suggest that the experimenter's choice of the punishment effectiveness is of great importance for the experimental outcome.

Laboratory experiments are an important methodology in economics, especially in the field of behavioral economics. However, it is still debated to what extent results from laboratory experiments are informative about behavior in field settings. One highly important question about the external validity of experiments is whether the same individuals act in experiments as they would in the field. This paper presents evidence on how individuals behave in donation experiments and how the same individuals behave in a naturally occurring decision situation on charitable giving. While we find evidence that pro-social behavior is more accentuated in the lab, the data show that pro-social behavior in experiments is correlated with behavior in the field.

Choice behavior is typically evaluated by assuming that the data is generated by one latent decision-making process or another. What if there are two (or more) latent decision-making processes generating the observed choices? Some choices might then be better characterized as being generated by one process, and other choices by the other process. A finite mixture model can be used to estimate the parameters of each decision process while simultaneously estimating the probability that each process applies to the sample. We consider the canonical case of lottery choices in a laboratory experiment and assume that the data is generated by expected utility theory and prospect theory decision rules. We jointly estimate the parameters of each theory as well as the fraction of choices characterized by each. The methodology provides the wedding invitation, and the data consummates the ceremony followed by a decent funeral for the representative agent model that assumes only one type of decision process. The evidence suggests support for each theory, and goes further to identify under what demographic domains one can expect to see one theory perform better than the other. We therefore propose a reconciliation of the debate over two of the dominant theories of choice under risk, at least for the tasks and samples we consider. The methodology is broadly applicable to a range of debates over competing theories generated by experimental and non-experimental data.

The analysis of data from experiments in economics routinely involves testing multiple null hypotheses simultaneously. These different null hypotheses arise naturally in this setting for at least three different reasons: when there are multiple outcomes of interest and it is desired to determine on which of these outcomes a treatment has an effect; when the effect of a treatment may be heterogeneous in that it varies across subgroups defined by observed characteristics and it is desired to determine for which of these subgroups a treatment has an effect; and finally when there are multiple treatments of interest and it is desired to determine which treatments have an effect relative to either the control or relative to each of the other treatments. In this paper, we provide a bootstrap-based procedure for testing these null hypotheses simultaneously using experimental data in which simple random sampling is used to assign treatment status to units. Using the general results in Romano and Wolf (Ann Stat 38:598–633, 2010), we show under weak assumptions that our procedure (1) asymptotically controls the familywise error rate—the probability of one or more false rejections—and (2) is asymptotically balanced in that the marginal probability of rejecting any true null hypothesis is approximately equal in large samples. Importantly, by incorporating information about dependence ignored in classical multiple testing procedures, such as the Bonferroni and Holm corrections, our procedure has much greater ability to detect truly false null hypotheses. In the presence of multiple treatments, we additionally show how to exploit logical restrictions across null hypotheses to further improve power. We illustrate our methodology by revisiting the study by Karlan and List (Am Econ Rev 97(5):1774–1793, 2007) of why people give to charitable causes.

Online labor markets provide new opportunities for behavioral research, but conducting economic experiments online raises important methodological challenges. This particularly holds for interactive designs. In this paper, we provide a methodological discussion of the similarities and differences between interactive experiments conducted in the laboratory and online. To this end, we conduct a repeated public goods experiment with and without punishment using samples from the laboratory and the online platform Amazon Mechanical Turk. We chose to replicate this experiment because it is long and logistically complex. It therefore provides a good case study for discussing the methodological and practical challenges of online interactive experimentation. We find that basic behavioral patterns of cooperation and punishment in the laboratory are replicable online. The most important challenge of online interactive experiments is participant dropout. We discuss measures for reducing dropout and show that, for our case study, dropouts are exogenous to the experiment. We conclude that data quality for interactive experiments via the Internet is adequate and reliable, making online interactive experimentation a potentially valuable complement to laboratory studies.