We collect individual participant data from 70 papers that use laboratory experiments to examine individual tax evasion behavior (or “Tax Evasion Games”), in order to use meta-analysis to estimate the impacts of different public policy, experimental design and individual level variables on tax evasion choices. Our results show that standard enforcement variables like audits (including audit rules) and fines perform differently on the extensive and intensive margins. We find that other fiscal variables like a flat tax system, tax rates, and tax amnesties have unambiguous negative impacts on tax compliance, and that specific features of the experimental setting, such as how subjects are directed to report income, or whether taxes are redistributed to the participants or to a real life public good, have significant impacts on tax compliance. Our results also indicate that the demographic characteristics of the subjects (e.g., gender, experimental income, occupation, risk attitude) affect compliance.

We provide a novel but intuitive explanation for expected utility violations found in the Allais paradox: individuals are commonly averse to receiving nothing. We call this phenomenon the zero effect. Our laboratory experiments show support for the zero effect. By contrast, the evidence for the certainty effect is weak to nonexistent.

Bayesian optimal experiments that maximize the information gained from collected data are critical to efficiently identify behavioral models. We extend a seminal method for designing Bayesian optimal experiments by introducing two computational improvements that make the procedure tractable: (1) a search algorithm from artificial intelligence that efficiently explores the space of possible design parameters, and (2) a sampling procedure which evaluates each design parameter combination more efficiently. We apply our procedure to a game of imperfect information to evaluate and quantify the computational improvements. We then collect data across five different experimental designs to compare the ability of the optimal experimental design to discriminate among competing behavioral models against the experimental designs chosen by a “wisdom of experts” prediction experiment. We find that data from the experiment suggested by the optimal design approach requires significantly less data to distinguish behavioral models (i.e., test hypotheses) than data from the experiment suggested by experts. Substantively, we find that reinforcement learning best explains human decision-making in the imperfect information game and that behavior is not adequately described by the Bayesian Nash equilibrium. Our procedure is general and computationally efficient and can be applied to dynamically optimize online experiments.

Preferences over social ranks have emerged as potential drivers of weaker than expected support for redistributive interventions among those closest to the bottom of the income distribution. We compare preferences for alterations of the income distribution affecting the decision maker’s social rank, but not their income, and compare them with similar alterations leaving both rank and income unchanged. Our study fails to find evidence of last-place aversion in a replication of Kuziemko et al. (Q J Econ 129(1):105–149, 2014). However, using a modified design that holds ranks fixed across rounds we find support for both a discontinuously greater disutility from occupying the last as opposed to higher ranks, thus affecting only those closest to the bottom of the distribution, and for a general dislike of rank reversals affecting most ranks. We discuss implications for policy design in both public finance and management science.

An experiment is designed to shed light on how deception works. The experiment involves a twenty period sender/receiver game in which period 5 has more weight than other periods. In each period, the informed sender communicates about the realized state, the receiver then reports a belief about the state before being informed whether the sender lied. Throughout the interaction, a receiver is matched with the same sender who is either malevolent with an objective opposed to the receiver or benevolent always telling the truth. The main findings are: (1) in several variants (differing in the weight of the key period and the share of benevolent senders), the deceptive tactic in which malevolent senders tell the truth up to the key period and then lie at the key period is used roughly 25% of the time, (2) the deceptive tactic brings higher expected payoff than other observed strategies, and (3) a majority of receivers do not show cautiousness at the key period when no lie was made before. These observations do not match the predictions of the Sequential Equilibrium and can be organized using the analogy-based sequential equilibrium (ABSE) in which three quarters of subjects reason coarsely.

This paper studies how social ties interact with bribery and corruption. In the laboratory, subjects are in triads where two ‘performers’ individually complete an objective real-effort task and an evaluator designates one of them as the winner of a monetary prize. In one treatment dimension, we vary whether performers can bribe the evaluator—where any bribe made is non-refundable, irrespective of the evaluator’s decision. A second treatment dimension varies the induced social ties between the evaluator and the performers. The experimental evidence suggests that both bribes and social ties may corrupt evaluators’ decisions. Bribes decrease the importance of performance in the decision. The effect of social ties is asymmetric. While performers’ bribes vary only little with their ties to the evaluator, evaluators exhibit favoritism based on social ties when bribes are not possible. This ‘social-tie-based’ corruption is, however, replaced by bribe-based corruption when bribes are possible. We argue that these results have concrete consequences for possible anti-corruption policies.

Central banks are increasingly communicating their economic outlook in an effort to manage the public and financial market participants’ expectations. We provide original causal evidence that the information communicated and the assumptions underlying a central bank’s projection can matter for expectation formation and aggregate stability. Using a between-subject design, we systematically vary the central bank’s projected forecasts in an experimental macroeconomy where subjects are incentivized to forecast the output gap and inflation. Without projections, subjects exhibit a wide range of heuristics, with the modal heuristic involving a significant backward-looking component. Ex-Ante Rational dual projections of the output gap and inflation significantly reduce the number of subjects’ using backward-looking heuristics and nudge expectations in the direction of the rational expectations equilibrium. Ex-Ante Rational interest rate projections are cognitively challenging to employ and have limited effects on the distribution of heuristics. Adaptive dual projections generate unintended inflation volatility by inducing boundedly-rational forecasters to employ the projection and model-consistent forecasters to utilize the projection as a proxy for aggregate expectations. All projections reduce output gap disagreement but increase inflation disagreement. Central bank credibility is significantly diminished when the central bank makes larger forecast errors when communicating a relatively more complex projection. Our findings suggest that inflation-targeting central banks should strategically ignore agents’ irrationalities when constructing their projections and communicate easy-to-process information.

We report experimental evidence showing a positive effect of redistribution on economic efficiency via the self-enforcement of property rights, and identify which status groups benefit more and which less. We model an economy in which wealth is produced if players voluntarily comply with the—efficient but inequitable—prevailing social order. We vary exogenously whether redistribution is feasible, and how it is organized. We find that redistribution benefits all status groups as property disputes recede. It is most effective when transfers are not discretionary but instead imposed by some exogenous administration. In the absence of coercive means to enforce property rights, it is the higher status groups, not the lower status groups, who benefit from redistribution being compulsory rather than voluntary.

Although volunteers are a critical resource for non-profit organizations, little is known about how best to motivate them to work. A non-profit organization asked episodic volunteers to produce handmade greeting cards to sell at a fundraising event. By running a natural field experiment, we study the effect of motivating these volunteers through (a) the opportunity to vote on how the money that was raised would be spent and (b) the prospect of individual performance feedback. We find an economically and statistically significant positive effect of both tools on the quantity of work done, while the quality is mostly unaffected. Moreover, we observe significant gender differences in responsiveness to the treatments. While the prospect for feedback is more motivating to men, women respond more strongly to the opportunity to decide how the money would be spent. Empowerment seems to be a simple way to increase engagement for people with low enjoyment.

This paper experimentally investigates the effect of introducing unavailable alternatives and irrelevant information regarding the alternatives on the optimality of decisions in choice problems. We find that the presence of unavailable alternatives and irrelevant information generates suboptimal decisions with the interaction between the two amplifying this effect. Irrelevant information in any dimension increases the time costs of decisions. We also identify a “preference for simplicity” beyond the desire to make optimal decisions or minimize time spent on a decision problem.

When it comes to experiments with multiple-round decisions under risk, the current payoff mechanisms are incentive compatible with either outcome weighting theories or probability weighting theories, but not both. In this paper, I introduce a new payoff mechanism, the Accumulative Best Choice (“ABC”) mechanism that is incentive compatible for all rational risk preferences. I also identify three necessary and sufficient conditions for a payoff mechanism to be incentive compatible for all models of decision under risk with complete and transitive preferences. I show that ABC is the unique incentive compatible mechanism for rational risk preferences in a multiple-task setting. In addition, I test empirical validity of the ABC mechanism in the lab. The results from both a choice pattern experiment and a preference (structural) estimation experiment show that individual choices under the ABC mechanism are statistically not different from those observed with the one-round task experimental design. The ABC mechanism supports unbiased elicitation of both outcome and probability transformations as well as testing alternative decision models that do or do not include the independence axiom.

While distance learning has become widespread, causal estimates regarding returns to effort in technology-assisted learning environments are scarce due to high attrition rates and endogeneity of effort. In this paper, I manipulate effort by randomly assigning students different numbers of lessons in a popular online language learning platform. Using administrative data from the platform and the instrumental variables strategy, I find that completing 9 Duolingo lessons, which corresponds to approximately 60 minutes of studying, leads to a 0.057–0.095 standard deviation increase in test scores. Comparisons to the literature and back-of-the-envelope calculations suggest that distance learning can be as effective as in-person learning for college students for an introductory language course.