Incentivizing behavior, a core principle of economic experiments, is currently under scrutiny due to a series of papers that find little to no difference in choices made under real or hypothetical incentives. We experimentally assess the effectiveness of hypothetical incentives to induce participants’ real effort – an integral aspect of reliable experimental data. We find that although linking behavior to hypothetical incentives generates modest additional effort compared to no reference to such incentives, hypothetical incentives fall substantially short of real ones, even when their nominal value is radically inflated. To understand the mechanism behind these effects, we systematically vary base pay and piece-rate magnitudes across incentive conditions and structurally estimate a model of costly effort. Although higher base pay increases effort both by increasing non-pecuniary motivation and by enhancing responsiveness to hypothetical incentives, incentive-compatible real payments are far more cost-effective.

Screening decisions—choosing a costly action that reveals information about an unknown quality—can be crucial in various situations, such as hiring workers or designing policies. Choosing whether to screen can be difficult because it requires recognizing and trading off the benefits of information with the costs of getting it. We investigate whether people recognize when the benefits of screening dominate its costs and what causes them to choose otherwise. Our online experiment simulates a hiring scenario with an initial trial task. Participants can first reveal candidates’ quality at a small cost and then choose which candidate to hire. Most participants choose the dominated task that does not reveal the candidates’ quality, and this mistake persists even with experience and feedback. We show that this insufficient screening is driven by failures to anticipate inference and plan the full strategy.

We study how large language model (LLM) based recommendations affect evaluations of uncertainty. We elicit certainty equivalents for (i) lotteries that share the same reduced-form winning probability but vary in cognitive demands because they are compound, and (ii) an Ellsberg-style ambiguous lottery. Across all lottery types, valuations from participants who receive LLM-based recommendations before each valuation exhibit second-order stochastic dominance relative to valuations from participants who do not. Hence, LLM-based recommendations leave mean valuations unchanged but compress the distribution, reducing the incidence of extreme valuations. Consistent with this pattern, LLM-based recommendations reduce the intensity of risk, complexity, and ambiguity aversion, while leaving the fraction of participants classified as averse unchanged.

Teamwork is prevalent in many forms of production, but individual contributions to team output are often ambiguous. We use a large-scale online experiment with an interactive team task to investigate gender differences in claiming credit for contributions to teamwork with misaligned incentives: Team members have an incentive to exaggerate their contribution, but this harms the other team member. In this setting, we observe that men claim to have contributed more than equally contributing women. Using two further between-subject treatments, we find no evidence that gender differences in altruism or in overconfidence explain the observed gender claim-gap. Further, the gender gap is present only among high contributors, and we show that the gap is particularly pronounced for large claims, which has potentially important consequences for gender equity in labour market outcomes.

This paper examines how prosocial motivations shape lying behavior in a strategic setting. Two players each privately choose a color in their mind, then draw a color at random, and report whether the two colors match. Both players receive a high payoff if at least one reports a match, so a single lie secures the payoff for both, making lies strategic substitutes. I develop a theoretical model in which individuals bear a psychological cost of lying but experience a lower cost when their lie increases their partner’s payoff. The model predicts that individuals are less likely to lie when they can rely on their partner to do so, and more likely to lie when their dishonesty benefits their partner. I test these predictions in an online experiment with four treatments that separately vary the opportunity to rely on the partner’s lie and the presence of a benefit to the partner. In this setting, prosocial motives outweigh lying aversion: participants lie more when their dishonesty benefits their partner, and they do not lie less when they can leave the lie to their partner. Lying increases only when a participant’s report is pivotal to the partner’s payoff, indicating that prosocial preferences reduce the net cost of lying when dishonesty is instrumental in generating benefits for others.

An individual reports subjective beliefs over continuous events using a proper scoring rule, such as the Quadratic Scoring Rule. Under mild additional assumptions, it is known that these reports reflect latent subjective beliefs if the individual is risk neutral. We demonstrate how to fully recover latent subjective beliefs if the individual is known to distort probabilities into decision weights using Rank Dependent Utility theory, and generalize all results for the complete class of proper scoring rules. As an immediate corollary, we can then exactly recover latent subjective beliefs using Expected Utility Theory. Using Bayesian econometric methods, we demonstrate how to recover belief distributions for individuals, and illustrate these results by recovering belief distributions about the “competitiveness” of individuals and the addictiveness of smoking. These results significantly widen the domain of applicability of proper scoring rules for eliciting latent subjective belief distributions.

We examine willingness to donate to climate activism and test whether brief informational infographics affect donations and climate attitudes. Participants completed baseline measures of climate literacy and attitudes before random assignment in a 2 × 2 design with (i) varying information about a climate activism organization and (ii) protest versus neutral imagery. They then made an incentive-compatible allocation of up to $30 between themselves and the organization and completed a post-treatment survey. Donations were high overall, with many full-endowment donations. Organizational information reduced donations, while protest imagery attenuated this effect and increased climate concern, which was positively associated with giving.

We design and conduct a real-effort experiment to jointly estimate present bias and sophistication across effort and monetary domains. Unlike prior work (e.g.,Augenblick and Rabin, 2019; Fedyk, 2024), we do not assume that these parameters are identical across domains. We explain and empirically demonstrate how assuming identical sophistication across money and effort domains can bias the estimates of key parameters. In our online experiment, participants chose to (predicted to) complete 14% (10%) fewer tasks on the same day than on a future day, leading to an estimated present bias ($\beta_e$) over effort of 0.70–0.79, and an estimated sophistication ($\widehat{\beta}_e$) of 0.80–0.88. For money, aggregate present bias ($\beta_m$) is near zero, but there is substantial heterogeneity, with roughly equal numbers of participants exhibiting present bias and future bias. At the individual level, roughly three quarters of all participants correctly anticipate the direction of their bias in both domains, even if not its full magnitude.

We build an experiment to uncover the bandit-like nature of consumer behavior usually masked by the product and time aggregation of consumption data. Subjects make repeated choices between musical styles (either all familiar or unfamiliar), and post-choice satisfaction is observed. We estimate Bayesian bandit models of learning taste by consuming with satiation. Our best model features decreasing random exploration, with openness being associated with higher exploration. Early exploration is more intensive in the unfamiliar treatment and persists throughout the experiment in both treatments. Overall, subjects make choices that deviate from their best prediction 61.5% of the time in the unfamiliar treatment versus 44.7% in the familiar treatment. Our model offers a rational interpretation of random utility in discrete consumer choices which does not rest on perception and/or decision errors.

We experimentally investigate preferences for clumping-versus-separating information in the gain and the loss domains, and also preferences for timing. Our design is motivated by the idea that information preferences may depend on reference points. Subjects participate in two monetary lotteries and choose how to receive the outcome information. For half of the subjects, the lotteries are framed as two gain lotteries; for the other half, as two loss lotteries. Based on Thaler (1985) one can expect that people want to learn the outcomes of the gain lotteries separately and the outcomes of the loss lotteries clumped together (cf. hedonic editing hypothesis). On the other hand, a different reference dependent model by Koszegi and Rabin (2009) relies on expectations-based reference points, and predicts that subjects should prefer clumped information irrespective of the frame.

The results of our experiment show a preference for separating information about gains, and no preference for clumping or separating information about losses. Regarding timing, we find a weak overall preference for receiving information sooner. These findings provide new insights into information preferences. We conclude by discussing policy implications, as well as our additional contributions to related literature.

This study investigates how in-game virtual currencies influence consumer spending behaviour. In an incentivized randomized controlled trial with 753 UK participants, we estimate the willingness-to-pay (WTP) for loot boxes represented as risky and ambiguous lotteries. We test the effects of virtual currencies, money illusion, and cognitive-demanding (non-intuitive) exchange rates, three practices commonly used to sell loot boxes. Our results show that WTP is significantly higher when transactions are conducted in virtual currencies with a 1:1 exchange rate compared to British pounds, contributing to the debate on the neutrality of virtual currencies and experimental currency units. Moreover, participants in our study are affected by money illusion distortions, regardless of the exchange rate’s intuitiveness. However, we find no evidence that non-intuitive exchange rates affect participants’ WTP compared to intuitive exchange rates of comparable size. These findings highlight the behavioural distortions induced by common monetization practices in games and provide empirical support for the European Commission’s call for stricter regulation of virtual currencies in digital environments.

We experimentally investigate whether lying is more likely when the addressees are individuals or groups of individuals, and in the latter case how the probability of lying depends on the group size and the magnitude of the negative externality inflicted by the lie. We employ an observed cheating game, where an individual can reveal or misreport a privately observed number. A misreport can be monetarily beneficial for the liar but imposes a monetary loss on addressees. The privately observed number is also known to the experimenter, who, therefore, can study both whether there is truth or misreporting and, in the latter case, the extent of misreporting. Treatments vary the loss for group members compared to the loss for an individual addressee. We find that groups are never lied to more than individual addressees. When considering how much to deviate from the truth, liars are sensitive to a decreasing loss at the individual level but do not care for an increasing loss at the group level. Groups of different sizes are treated similarly. Social image concerns may explain the results.

The Multiple Price List (MPL) and Switching Multiple Price List (sMPL) provide a useful framework for estimating preference parameters, most usually risk aversion, from a sample of experimental subjects or survey respondents. In this paper, we consider designs in which more than one sMPL is presented to each subject, allowing more than one preference parameter to be estimated simultanously, and we propose a consistent estimator in this setting – the Multivariate Heterogeneous Preference (MHP) estimator. Focusing on the bivariate case of two sMPLs and two preference parameters, we demonstrate that non-standard econometric techniques, namely Monte Carlo integration with importance sampling, are required to implement the MHP estimator. Via a Monte Carlo exercise, we show that our estimator has good finite-sample properties. Finally, we apply the MHP estimator to a real data set and compare the estimates to those obtained using an inconsistent estimator applied in previous studies.

In various organizational settings, a team member is given the authority to make an investment decision that influences the value of the jointly produced surplus. We experimentally investigate the effect of asymmetric status, investment decisions, and the outcome of these decisions on bargaining behavior and outcomes. Agents’ initial contributions to the surplus are determined by their relative performances in a real-effort task. Three treatments vary in how the final surplus value is determined. We observe that when low-contributors take a risk, they are punished (rewarded) for failure (success), whereas high-contributors receive a fixed share independent of the outcome. Analysis of bargaining process variables, subjects’ communication during bargaining, and third parties’ normative judgments provides further insights into the possible mechanism behind this observation.

We investigate whether time pressure exacerbates or mitigates bubbles in laboratory experiments. We find that under high time pressure price volatility is lower and market prices are closer to their fundamental value. This is due to participants using simpler adaptive forecasting strategies, instead of the self-reinforcing extrapolative expectations that they use under low time pressure, and which are conducive to the emergence of bubbles. In addition, by substantially increasing the number of decision periods in our experiment, we find that in the long run prices tend to converge to their fundamental value, also in the absence of time pressure.

Large Language Models (LLMs) have the potential to profoundly transform and enrich experimental economic research. We propose a new software framework, “alter_ego”, which makes it easy to design experiments between LLMs and to integrate LLMs into oTree-based experiments with human subjects. Our toolkit is freely available at github.com/mrpg/ego. To illustrate, we run differently framed prisoner’s dilemmas with interacting machines as well as with human-machine interaction. Framing effects in machine-only treatments are strong and similar to those expected from previous human-only experiments, yet less pronounced and qualitatively different if machines interact with human participants.

Theoretical insights dominate the literature examining the incentive compatibility of payment mechanisms. Despite their elegance, theoretical insights are rarely empirically validated. We fill this gap by empirically exploring the effects of frequently used payment mechanisms using a collective sample of over 3000 participants across two experiments. In Experiment 1, we obtained offer prices to sell a card, systematically varying between-subjects the way subjects received payments over repeated rounds, by either paying for all decisions (and various modifications) or just one, as well as making the payments certain, probabilistic, or purely hypothetical. While we find that the magnitude of the induced value and the range of the prices used to draw a random price significantly affect misbidding behavior, neither the payment mechanism nor the certainty of payment affected misbidding. In Experiment 2, we replaced the BDM mechanism with a Second Price-Auction and found similar results, albeit lower rates of misbidding behavior. Overall, our empirical exercise shows that theoretically relevant elements do not produce empirical differences, while design choices that are theoretically irrelevant produce empirical differences. As such, payment mechanism design considerations should carefully consider the choice architecture in addition to incentive compatibility.

Agents frequently engage with multiple principals simultaneously – for example, when borrowing from several banks or peers. In such settings, principals typically possess less information about the agent’s ability or intentions (e.g., to repay a loan) and must rely on trust. This paper presents experimental evidence from trust games framed in a credit market context to examine the role of reciprocity in interactions involving multiple principals (lenders) and a single agent (borrower). Agents were asked to decide whether to act trustworthily and repay, or to default and act selfishly, after receiving the same credit amount from either one or multiple principals. The results show that reciprocity declines when the number of trusting principals increases. A key mechanism appears to be the reduced marginal harm that an agent’s default imposes on each individual principal. Additionally, agents seem less sensitive to the negative consequences of their actions when multiple principals are affected. These findings suggest that interactions involving multiple principals are behaviorally riskier than bilateral ones. The results have implications for the design of incentive structures in multi-principal-agent environments, such as crowdlending platforms.

Across three studies involving more than 5,000 participants, we provide a comprehensive analysis of the effects of incentivizing responses in the Krupka-Weber norm elicitation task. We consider both the potential benefits of incentivization (higher response quality and mitigation of response biases) and its possible drawbacks (distortion of responses in the direction of norm-unrelated focal points and materialistic values). We find no evidence of undesirable effects of incentives. While we report only modest improvements in response quality, we also show that incentives effectively mitigate response biases that arise when participants’ self-serving motivations conflict with accurate responding.

There is existing evidence that many individuals have preferences regarding selection of numbers in lottery games. Lottery data indicate that the percentage of players who choose their numbers, instead of having numbers randomly assigned, varies widely by lottery game. Differences in number selection mechanisms between games and an expected return maximization motive only present for parimutuel games are both reasons that can explain the variation. Differences in the payoff distributions between lottery games could also be contributing to the observed variation, a novel proposition. An experiment is designed to control for differences in number selection mechanisms and remove the expected return maximization motive, to test for the presence of distribution-dependent number preferences. Results indicate that 40% to 50% of subjects may display such preferences. It is therefore possible that distribution-dependent number preferences contribute to the empirical variation in number selection percentages in lottery games.