Experiments in economics usually provide subjects with starting capital to be used in the experiment. This practice could affect decisions as there is no risk of loss. This phenomenon is known as the house-money effect. In a repeated public goods game, we test for house-money effects by paying subjects in advance an amount they could lose in the experiment. We do not find evidence of a house-money effect over time.

Players often fail to coordinate on the efficient equilibrium in laboratory weak-link coordination games. In this paper, we investigate whether such coordination failures can be mitigated by increasing the number of rounds or altering per-period stakes. We find that neither time horizon nor stakes affect equilibrium selection. In contrast to previous findings, players are not more likely to play above the previous period’s minimum choice when the horizon is longer or per-period stakes lower. We also investigate which socio-demographic factors and behavioral traits correlate most strongly with play both in the first round and in subsequent rounds. Cognitive ability as measured by a cognitive reflection test stands out as the characteristic that is most strongly associated with efficient coordination.

The expanding literature on lying has exclusively considered lying behavior within a one-dimensional context. While this has been an important first step, many real-world contexts involve the possibility of simultaneously lying in more than one dimension (e.g., reporting one’s income and expenses in a tax declaration). We experimentally investigate individual lying behavior in one- and two-dimensional contexts to understand how the multi-dimensionality of a decision affects lying behavior. Our paper provides the first evidence regarding the pure effect of dimensionality on lying behavior. Using a two-dimensional die-roll task, we show that participants distribute lies unevenly across dimensions, which results in greater over-reporting of the lower-outcome die.

We introduce stochastic loss into a gift exchange game to study how information on intentions affects reciprocity. In one treatment, the respondent observes the amount received and whether a loss occurred, so both the consequential outcome and the sender’s original intention are known. In the other two treatments, information about whether a loss occurred is hidden, and the respondent is only informed of the amount received (outcome) or the amount initially sent (intention). Using both regression-based approaches and non-parametric tests, we find greater reciprocity in the two treatments that reveal intentions. These differences arise even in a simple one-shot setting without reputational benefits and are economically meaningful; they are similar in magnitude to the difference attributable to a full point reduction in the amount received. Our findings show the impact of the information environment on reciprocity in settings with uncertainty and suggest that transparency is important to reciprocity.

Misreporting—a form of lying—is common in online labor and remote work settings. We execute an experiment on Amazon MTurk to determine how ex-ante honesty oaths and worker beliefs impact lying behavior across a range of plausible and implausible lies. Using a novel quantile-style exposition of the types of lies reported, we find that oaths elicit more truthful behavior, reducing both small, plausible lies and large, implausible ones. Shirking is reduced under oath. Worker expectations of group reporting are positively related to individual reporting of plausible lies.

Building on a partner-switching mechanism, we experimentally test two theories that posit different reasons why promises breed trust and cooperation. The expectation-based explanation (EBE) operates via belief-dependent guilt aversion, while the commitment-based explanation (CBE) suggests that promises offer commitment power via a (belief-independent) preference to keep one’s word. Previous research performed a similar test, which we argue should be interpreted as concerning informal agreements rather than (unilateral) promises.

The current publication system in economics has encouraged the inflation of positive results in empirical papers. Registered Reports, also called Pre-Results Reviews, are a new submission format for empirical work that takes pre-registration one step further. In Registered Reports, researchers write their papers before running the study and commit to a detailed data collection process and analysis plan. After a first-stage review, a journal can give an In-Principle-Acceptance guaranteeing that the paper will be published if the authors carry out their data collection and analysis as pre-specified. We here propose a practical guide to Registered Reports for empirical economists. We illustrate the major problems that Registered Reports address (p-hacking, HARKing, forking, and publication bias), and present practical guidelines on how to write and review Registered Reports (e.g., the data-analysis plan, power analysis, and correction for multiple-hypothesis testing), with R and STATA codes. We provide specific examples for experimental economics, and show how research design can be improved to maximize statistical power. Last, we discuss some tools that authors, editors, and referees can use to evaluate Registered Reports (checklist, study-design table, and quality assessment).

Janssen et al. (Exp Econ 14:547–566, 2014) studied an asymmetric, finitely repeated common-pool resource dilemma with free-form communication in which subjects made decisions about investments in an infrastructure, and about extraction from a resource made available by this infrastructure. They found that infrastructure provision and joint payoffs converged to high levels because structurally advantaged head-enders tend to behave fairly by restricting themselves voluntarily at the extraction stage, and structurally disadvantaged “tail-enders” reciprocate by investing. This paper reports a fully independent, pre-registered, double-blind replication attempt conducted in a different lab, that also supplies elevated statistical power and adheres to the highest principles of scientific transparency and openness. We find that the key results of Janssen et al. not only re-appear qualitatively but are quantitatively and statistically strengthened. The conclusions drawn from the results are therefore robust, and the basic design can be confidently used for follow-up research.

This technical note briefly explains the structure of the z-Tree dataset and presents ztree2stata, a data converting tool for researchers who conduct economic experiments using z-Tree and analyze the data with Stata.

This article surveys the rapidly growing literature that examined the influence of Covid-19 on preferences. Based on 33 studies, the article examines how the pandemic impacted altruism, cooperation, trust, inequity aversion, risk-taking, and patience/time discounting. Even though the survey suggests the effect of the pandemic on preferences is heterogeneous, some noticeable patterns can be observed in the literature. First, in the case of incentivized preference elicitation, there is weak evidence that the pandemic positively influenced altruism and had no significant impact on time preferences or patience. Second, many studies that used balanced panel data and incentivized preference elicitation mechanisms do not find a significant effect of the pandemic on preferences. Last, studies that used unincentivized methods to elicit preferences show relatively higher variability in results when compared to the studies that used incentivized methods for preference elicitation. The organized synthesis and several noticeable patterns can help future research focusing on preference stability during Covid-19 and other unfavorable events.