The personal experience of events such as financial crises and natural disasters can alter economic preferences. We administered a repeated cross-sectional preference survey during the early stages of the COVID-19 outbreak, collecting three bi-weekly samples from participants recruited through Amazon Mechanical Turk. The survey elicits economic preferences, self-reported fear of the pandemic, and beliefs about economic and health consequences. Preferences varied over time and across regions, and self-reported fear of the pandemic explains this variation. These findings suggest caution about the generalizability of some types of experimental work during times of heightened fear.

For the trust game, recent models of belief-dependent motivations make opposite predictions regarding the correlation between back transfers and second-order beliefs of the trustor: while reciprocity models predict a negative correlation, guilt-aversion models predict a positive one. This paper tests the hypothesis that the inconclusive results in the previous studies investigating the reaction of trustees to their beliefs are due to the fact that reciprocity and guilt aversion are behaviorally relevant for different subgroups and that their impact cancels out in the aggregate. We find little evidence in support of this hypothesis and conclude that type heterogeneity is unlikely to explain previous results.

We conduct an experiment on an online game, exploring the effect on gameplay behavior of voluntary commitment devices that allow players to limit their gameplay. Approximately 25% of players use the devices. Median and 75th percentile device users use devices approximately 60 and 100% of the time, respectively. Players who chose to use the device were those who had previously played longer and more frequently than those who chose not to use the device. Offering the commitment devices decreased session length and session frequency by 2.8 and 6.1%, respectively, while increasing weeks of play by 5.5%. Our results are consistent with some players having self-identified self-control problems, leading to longer and more frequent play than they would prefer, and to demand for commitment, and also with commitment devices creating a more rewarding experience, leading to longer-lasting involvement with the game. Our results suggest incentivizing or requiring commitment devices in computer games.

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).

Since Holt and Laury (Am Econ Rev 92(5):1644–1655, 2002), the multiple price list (MPL) procedure has widely been used to elicit individual risk preferences. We assess the impact of varying list order and spacing, and of presentation via text or graphs. Relative to the original MPL baseline, some non-linear transformations of lottery prices systematically increase elicited risk aversion, while some graphical displays tend to reduce it.

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.

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.

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 study the effects on performance of incentives framed as gains or losses, as well as the effort channels through which individuals increase performance. We also explore potential spill-over effects on a non-incentivised activity. Subjects participated in a medically framed real-effort task under one of the three contracts, varying the type of performance incentive received: (1) no incentive; (2) incentive framed as a gain; or (3) incentive framed as a loss. We find that performance improved similarly with incentives framed as losses or gains. However, individuals increase performance differently under the two frames: potential losses increase participants’ performance through a greater attention (fewer mistakes), while bonuses increase the time spent on the rewarded activity. There is no spill-over effect, either negative or positive, on the non-incentivised activity. We discuss the meaning and implications of our results for the design of performance contracts.

The famous linguistic-savings hypothesis states that languages that grammatically separate the future from the present (like English) causally induce less future-oriented behavior than languages in which speakers can refer to the future using present tense (like German or Chinese). Chen et al., European Economic Review 120 (2019) experimentally investigate the effect of using future-oriented language on incentivized intertemporal choices and find no support for the hypothesis. We replicate Chen et al., European Economic Review 120 (2019)’s study in the German-speaking context. In our experiment with 332 subjects, we randomly refer to future payments using present or future tense and find no causal effect of language on intertemporal choice. Given the importance of replications for confidence in scientific findings, our results provide corroborating evidence that the linguistic-savings hypothesis is not empirically tenable. Eventually, the results provide a methodological contribution to the conduct of experiments.

I show how using response times as a proxy for effort can address a long-standing issue of how to separate the effect of cognitive ability on performance from the effect of motivation. My method is based on a dynamic stochastic model of optimal effort choice in which ability and motivation are the structural parameters. I show how to estimate these parameters from the data on outcomes and response times in a cognitive task. In a laboratory experiment, I find that performance on a digit-symbol test is a noisy and biased measure of cognitive ability. Ranking subjects by their performance leads to an incorrect ranking by their ability in a substantial number of cases. These results suggest that interpreting performance on a cognitive task as ability may be misleading.

Garbarino et al. (J Econ Sci Assoc. https://doi.org/10.1007/s40881-018-0055-4, 2018) describe a new method to calculate the probability distribution of the proportion of lies told in “coin flip” style experiments. I show that their estimates and confidence intervals are flawed. I demonstrate two better ways to estimate the probability distribution of what we really care about—the proportion of liars—and I provide R software to do this.

Recruitment of representative and generalizable adult samples is a major challenge for researchers conducting economic field experiments. Limited access to representative samples or the high cost of obtaining them often leads to the recruitment of non-representative convenience samples. This research compares the findings from two field experiments involving 860 adults: one from a non-representative in-person convenience sample and one from a representative online counterpart. We find no meaningful differences in the key behaviors of interest between the two samples. These findings contribute to a growing body of literature demonstrating that non-representative convenience samples can be sufficient in certain contexts.

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.

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.

$\mu$Cap is a software package (citeware) for economic experiments enabling experimenters to analyze emotional states of subjects using z-Tree and FaceReader™. $\mu$Cap is able to create videos of subjects on client computers based on stimuli shown on screen and restrict recording material to relevant time frames. Another feature of $\mu$Cap is the creation of time stamps in csv format at prespecified screens (or at prespecified points in time) during the experiment, measured on the client computer. The software makes it possible to import these markers into FaceReader™ easily. $\mu$Cap is the first program that significantly simplifies the process of connecting z-Tree and FaceReader™ with the additional benefit of extremely high precision. This paper describes the usage, underlying principles as well as advantages and limitations of $\mu$Cap. Furthermore, we give a brief outlook of how $\mu$Cap can be beneficial in other contexts.

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.

Access to information via social media is one of the biggest differentiators of public health crises today. During the early stages of the Covid-19 outbreak in January 2020, we conducted an experiment in Wuhan, China to assess the impact of viral social media content on pro-social and trust behaviours and preferences towards risk taking with known and unknown probabilities. Prior to the experiment, participants viewed one of two videos that had been widely and anonymously shared on Chinese social media: a central government leader visiting a local hospital and supermarket, or health care volunteers transiting to Wuhan. In a control condition, participants watched a Neutral video, unrelated to the crisis. Viewing one of the leadership or volunteer videos leads to higher levels of pro-sociality and lesser willingness to take risks in an ambiguous situation relative to the control condition. The leadership video, however, induces lower levels of trust. We provide evidence from two post-experiment surveys that the video’s impact on pro-sociality is modulated by influencing the viewer’s affective emotional state.