Rounding is a common phenomenon when subjects provide an answer to an open-ended question, both in experimental tasks and in survey responses. From a statistical perspective, rounding implies that the measured variable is a coarsened version of the underlying continuous target variable. Since the coarsening process is non-random, inference from rounded data is generally biased. Despite the potentially severe consequences of rounding, little is known about its causes. In this paper, we focus on subjects’ uncertainty about the target variable as one potential cause for rounding behavior. We present a novel experimental method that induces uncertainty in a controlled way, thus providing causal evidence for the effect of subjects’ uncertainty on the extent of rounding. Then, we specify and estimate a mixture model that relates uncertainty and rounding. The results suggest that an increase in the exogenous level of uncertainty translates into higher variance of the subjects’ beliefs, which in turn results in more rounding.

Several papers have documented that when subjects play with standard laboratory “endowments” they make less self-interested choices than when they use money they have either earned through a laboratory task or brought from outside the lab. In the context of a charitable giving experiment we decompose this into two common artifacts of the laboratory: the intangibility of money (or experimental currency units) promised on a computer screen relative to cash in hand, and the distinct treatment of random “windfall” gains relative to earned money. While both effects are found to be significant in non-parametric tests, the former effect, which has been neglected in previous studies, has a stronger impact on total donations, while the latter effect has a greater impact on the probability of donating. These results have clear implications for experimental design, and also suggest that the availability of more abstract payment methods may increase other-regarding behavior in the field.

We report the results of experiments that test for behavioral differences between volunteer subjects recruited in the usual way and pseudo-volunteer subjects in experiments conducted during class time. In a series of dictator games, we find that psuedo-volunteers are more generous on average than their volunteer counterparts, and that non-monetary factors such as religious or altruistic preferences have a greater effect on the giving behavior of pseudo-volunteers.

Are decisions in economics experiments distorted because the money subjects risk comes from the experimenter rather than their own pockets? There is some evidence that people receiving small, one time “windfall gains” have a higher marginal propensity to consume them, and when doing so, exhibit greater risk-seeking behaviour. This has been found in individual decision making experiments when anticipated wealth effects have been controlled, and labelled the “house money effect.” In public good experiments, house money effects could be driving the high levels of voluntary contributions commonly observed. This possibility is tested by comparing VCM contribution rates when subjects supply their own endowments with those when endowments are provided, while holding constant the distribution of promised earnings. No evidence of house money effects is found, suggesting that use of “free” initial money endowments does not distort subsequent contributions in VCM environments.

Belief-elicitation experiments usually reward accuracy of stated beliefs in addition to payments for other decisions. But this allows risk-averse subjects to hedge with their stated beliefs against adverse outcomes of the other decisions. So can we trust the existing belief-elicitation results? And can we avoid potential hedging confounds? We propose an experimental design that theoretically eliminates hedging opportunities. Using this design, we test for the empirical relevance of hedging effects in the lab. Our results suggest that hedging confounds are not a major problem unless hedging opportunities are very prominent. If hedging opportunities are transparent, and incentives to hedge are strong, many subjects do spot hedging opportunities and respond to them. The bias can go beyond players actually hedging themselves, because some expect others to hedge and best respond to this.

In experimental economics there is a norm against using deception. But precisely what constitutes deception is unclear. While there is a consensus view that providing false information is not permitted, there are also “gray areas” with respect to practices that omit information or are misleading without an explicit lie being told. In this paper, we report the results of a large survey among experimental economists and students concerning various specific gray areas. We find that there is substantial heterogeneity across respondent choices. The data indicate a perception that costs and benefits matter, so that such practices might in fact be appropriate when the topic is important and there is no other way to gather data. Compared to researchers, students have different attitudes about some of the methods in the specific scenarios that we ask about. Few students express awareness of the no-deception policy at their schools. We also briefly discuss some potential alternatives to “gray-area” deception, primarily based on suggestions offered by respondents.

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.

Belief elicitation is an important methodological issue for experimental economists. There are two generic questions: 1) Do incentives increase belief accuracy? 2) Are there interaction effects of beliefs and decisions? We investigate these questions in the case of finitely repeated public goods experiments. We find that belief accuracy is significantly higher when beliefs are incentivized. The relationship between contributions and beliefs is slightly steeper under incentives. However, we find that incentivized beliefs tend to lead to higher contribution levels than either non-incentivized beliefs or no beliefs at all. We discuss the implications of our results for the design of public good experiments.

We report the results of a novel protocol for running online experiments using a combination of an online experimental platform in parallel with web-conferencing software in two formats—with and without subject webcams—to improve subjects’ attention and engagement. We compare the results between our online sessions with the offline (lab) sessions of the same experiment. We find that both online formats lead to comparable subject characteristics and performance as the offline (lab) experiment. However, the webcam-on protocol has less noisy data, and hence better statistical power, than the protocol without a webcam. The webcam-on protocol can detect reasonable effect sizes with a comparable sample size as in the offline (lab) protocol.