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on Experimental Economics |
| By: | Tomu Hirata; Undral Byambadalai; Tatsushi Oka; Shota Yasui; Shingo Uto |
| Abstract: | We propose a novel multi-task neural network approach for estimating distributional treatment effects (DTE) in randomized experiments. While DTE provides more granular insights into the experiment outcomes over conventional methods focusing on the Average Treatment Effect (ATE), estimating it with regression adjustment methods presents significant challenges. Specifically, precision in the distribution tails suffers due to data imbalance, and computational inefficiencies arise from the need to solve numerous regression problems, particularly in large-scale datasets commonly encountered in industry. To address these limitations, our method leverages multi-task neural networks to estimate conditional outcome distributions while incorporating monotonic shape constraints and multi-threshold label learning to enhance accuracy. To demonstrate the practical effectiveness of our proposed method, we apply our method to both simulated and real-world datasets, including a randomized field experiment aimed at reducing water consumption in the US and a large-scale A/B test from a leading streaming platform in Japan. The experimental results consistently demonstrate superior performance across various datasets, establishing our method as a robust and practical solution for modern causal inference applications requiring a detailed understanding of treatment effect heterogeneity. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2507.07738 |
| By: | Choudhury, Prithwiraj; Khanna, Tarun; Makridis, Christos A.; Schirmann, Kyle |
| Keywords: | hybrid work; remote work; work-from-home; field experiment; productivity; employee engagement |
| JEL: | J23 J24 O10 O33 |
| Date: | 2025–02–09 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:128764 |
| By: | Margarita Leib; Nils K\"obis; Ivan Soraperra |
| Abstract: | People increasingly rely on AI-advice when making decisions. At times, such advice can promote selfish behavior. When individuals abide by selfishness-promoting AI advice, how are they perceived and punished? To study this question, we build on theories from social psychology and combine machine-behavior and behavioral economic approaches. In a pre-registered, financially-incentivized experiment, evaluators could punish real decision-makers who (i) received AI, human, or no advice. The advice (ii) encouraged selfish or prosocial behavior, and decision-makers (iii) behaved selfishly or, in a control condition, behaved prosocially. Evaluators further assigned responsibility to decision-makers and their advisors. Results revealed that (i) prosocial behavior was punished very little, whereas selfish behavior was punished much more. Focusing on selfish behavior, (ii) compared to receiving no advice, selfish behavior was penalized more harshly after prosocial advice and more leniently after selfish advice. Lastly, (iii) whereas selfish decision-makers were seen as more responsible when they followed AI compared to human advice, punishment between the two advice sources did not vary. Overall, behavior and advice content shape punishment, whereas the advice source does not. |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2507.19487 |
| By: | Andreas Kotsadam; Mette Løvgren |
| Abstract: | Using data from over 24, 000 respondents in the Norwegian Crime Victimization Survey, we conducted a double list experiment to measure domestic violence (DV). Both list experiments revealed a statistically significant decrease in reporting when including a sensitive DV item. This clear violation of the “no design effects” assumption is not only explained by floor effects. One possibility is that the results indicate a "fleeing" behavior whereby respondents try to avoid association with DV. Combined with the inherent power limitations of list experiments in many contexts, these results underscore the need for caution in employing list experiments to measure DV, even in large samples. |
| Keywords: | domestic violence, list experiment, Norway |
| JEL: | J16 K14 I14 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_12028 |
| By: | Alexander Egberts (Max Planck Institute for Research on Collective Goods, Bonn); Christoph Engel (Max Planck Institute for Research on Collective Goods, Bonn); Joshua Fairfield (Max Planck Institute for Research on Collective Goods, Bonn) |
| Abstract: | Many social ills can be modelled as a public bad. In such scenarios, private benefit is often immediate while the public damage takes some time to materialize. In this experiment, we investigate the behavioral effects caused by such delays in the realization of collective harm. By manipulating the weight with which the damages caused by group contributions are carried over to the next round, we alter the number of periods required for the social damage to fully unfold. We keep constant the economic consequences of contributions between treatments (by introducing a multiplier for the damage) and between periods (by deducting all unrealized harm at the end of the game) to avoid multiple equilibria. In a second treatment dimension, we isolate the cognitive challenges of this experiment by replacing human group-members with “computerized players†which perfectly copy each subject’s previous behavior. We find that participants’ behavior is less cooperative over time when harm is deferred into the future. Our results also suggest that the driving mechanism behind this effect is not insufficient anticipation, but the lack of having experienced the negative consequences of the public damage. |
| Keywords: | public bad; dynamically developing social harm; cognitive and motivational challenge; experiment |
| JEL: | C91 D62 D91 H41 K24 K32 |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:mpg:wpaper:2024_16 |
| By: | Johannes Gessner; Andreas Gerster; Michael Kramm |
| Abstract: | There is growing evidence that households often forgo profitable energy efficiency retrofits, partly due to inattention and imperfect information about their economic benefits. We conduct an incentivized survey experiment to evaluate both the effecƟveness and the welfare implicaƟons of a widely used policy tool aimed at addressing this issue: providing information from an energy efficiency audit. In our incentivized experiment, participants in the treatment group receive personalized information about the potential cost savings from retrofitting their heating systems, while those in the control group do not receive such information. Our results show that providing this information does not increase the average willingness to pay for a retrofit. |
| Keywords: | information provision, nudge, welfare, heterogeneity, incentivized survey experiment, energy efficiency |
| JEL: | C93 D83 Q41 Q48 |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:bon:boncrc:crctr224_2025_696 |
| By: | Lorenz Goette; Zhi Hao Lim |
| Abstract: | This paper studies the potential for behavioral interventions aimed at promoting resource conservation within one domain to induce spillovers in another. Through a large-scale natural field experiment involving around 2, 000 residents, we assess the direct and spillover effects of real-time feedback and social comparisons on water and energy consumption. Three interventions were implemented: two targeting shower use and one targeting air-conditioning use. We document a significant reduction in shower use attributable to both water-saving interventions, but no direct effects on air-conditioning use from the energy-saving intervention. For spillovers, we precisely estimated null effects on air-conditioning use arising from the water-saving interventions, and vice versa. |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2508.04371 |
| By: | Shan, Xiaoyue (National University of Singapore); Zölitz, Ulf (University of Zurich); Backes-Gellner, Uschi (University of Zurich) |
| Abstract: | We study the impact of online instruction with a field experiment that randomly assigns 1, 344 university students to different proportions of online and in-person lectures in multiple introductory courses. Increased online instruction leaves men’s exam performance unaffected but significantly lowers women’s performance, particularly in math-intensive courses. Online instruction also reduces women’s longer-run performance and increases their study dropout. Exploring mechanisms, we find that women exposed to more online lectures report greater difficulty in connecting with peers, less engaging instructors, and lower course satisfaction. Our findings suggest that shifting toward more online instruction may disproportionally harm women. |
| Keywords: | gender disparities, field experiment, Online instruction |
| JEL: | J16 I23 C93 |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18011 |
| By: | Pugatch, Todd (University at Buffalo, SUNY); Schroeder, Elizabeth (Oregon State University) |
| Abstract: | Randomized controlled trials (RCTs) have become an essential tool for economists. The credibility revolution in empirical economics emphasizes research designs that identify casual effects, and random assignment of treatment is seen as the gold standard. Implementation can, however, be a challenge in many applications. The field of economic education is in a unique position to learn from RCTs, given the ability to test interventions in the classroom or at educational institutions. We discuss what is needed to run an RCT effectively in an educational setting, drawing from the experimental literature on topics such as student success in higher education and diversity in undergraduate economics. We additionally outline quasi-experimental approaches that can be used when treatment cannot be randomized. |
| Keywords: | economics of education, randomized controlled trial, higher education |
| JEL: | I21 I23 |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18018 |
| By: | Filipe R. Campante; Ruben Durante; Felix Hagemeister; Ananya Sen |
| Abstract: | We study how AI-generated misinformation affects demand for trustworthy news, using data from a field experiment by a major German outlet, Süddeutsche Zeitung (SZ). Readers were randomly assigned to a treatment highlighting the challenge of distinguishing real from AI-generated images. The treatment raised concern with misinformation (0.3 s.d.) and reduced trust in news (0.1 s.d.), including SZ. Importantly, it affected post-survey browsing behavior: daily visits to SZ digital content rose by 2.5% in the immediate aftermath of the treatment. Moreover, we find that subscriber retention increased by 1.1% after five months, corresponding to about a one-third drop in attrition rate. Results are consistent with a model where the relative value of trustworthy news sources increases with the prevalence of misinformation, which may thus boost engagement with those sources even while lowering trust in news content. |
| JEL: | D12 L82 L86 |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34100 |
| By: | Agyeah, George; Samad, Zeeshan; Drujano-Ochoa, Dario |
| Abstract: | This study replicates and extends the analysis of belief elicitation methods conducted by Danz et al. (2022). The original paper scrutinizes the binarized scoring rule (BSR) method and its effectiveness in incentivizing truthful reporting. Using data from the original controlled laboratory experiments conducted at the Pittsburgh Experimental Economics Laboratory (PEEL), this replication investigates the impact of varying levels of information about incentives on belief reporting accuracy. The findings of the replication confirm systematic biases in belief reporting, particularly a center-bias effect, challenging the behavioral incentive compatibility of the BSR method. Robustness checks further confirm the generalizability of these results across different settings and belief elicitation tasks. These findings underscore the need for improved methodologies that ensure both theoretical and behavioral incentive compatibility in belief elicitation. |
| Keywords: | Replication, Data Analysis, Belief Elicitation, Incentive Effects |
| JEL: | C91 D83 D91 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:i4rdps:255 |
| By: | Igor Asanov (University of Kassel, Germany); Maria Mavlikeeva (University of Kassel, INCHER, Germany) |
| Abstract: | We conduct a large-scale experiment in the labor market using more than 8, 000 fictitious resumes to uncover the demand-side mechanisms behind the wage penalty for the self-employed. We find that self-employed individuals, compared to wage earners, are subject to adverse treatment across different occupations. This adverse treatment is concentrated in the lower-skilled, non-managerial market. This differential treatment, conditional on managerial skills, also holds for different occupational levels and increases with the length of self-employment experience. The results suggest that self-employment leads to the development of generalist skills (useful for managerial roles) at the cost of specialist skills. |
| Keywords: | Self-employment, Field experiment, Skills mismatch, Wage penalty, Managerial skills, Specialist skills |
| Date: | 2025–04–16 |
| URL: | https://d.repec.org/n?u=RePEc:mar:magkse:202513 |
| By: | Notte, Vincent; De Bundel, Florian; de Pierpont de Burnot, Charles |
| Abstract: | This study replicated the research by Bellemare et al. (2023a) to evaluate the transparency and robustness of their findings. We found that computational reproducibility was achieved with ease due to the precise and clear coding provided in their article, and no errors were detected. However, the scope of the publicly available dataset is somewhat restricted, containing only a limited number of variables, which constrains the extent of possible sensitivity analyses. It is unfortunate that the complete set of variables related to the experiments seems to not been made available. We conducted two basic robustness checks, both of which confirmed the validity of the authors' conclusions. |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:i4rdps:257 |
| By: | Pawe{\l} Niszczota; Tomasz Grzegorczyk; Alexander Pastukhov |
| Abstract: | Machines driven by large language models (LLMs) have the potential to augment humans across various tasks, a development with profound implications for business settings where effective communication, collaboration, and stakeholder trust are paramount. To explore how interacting with an LLM instead of a human might shift cooperative behavior in such settings, we used the Prisoner's Dilemma game -- a surrogate of several real-world managerial and economic scenarios. In Experiment 1 (N=100), participants engaged in a thirty-round repeated game against a human, a classic bot, and an LLM (GPT, in real-time). In Experiment 2 (N=192), participants played a one-shot game against a human or an LLM, with half of them allowed to communicate with their opponent, enabling LLMs to leverage a key advantage over older-generation machines. Cooperation rates with LLMs -- while lower by approximately 10-15 percentage points compared to interactions with human opponents -- were nonetheless high. This finding was particularly notable in Experiment 2, where the psychological cost of selfish behavior was reduced. Although allowing communication about cooperation did not close the human-machine behavioral gap, it increased the likelihood of cooperation with both humans and LLMs equally (by 88%), which is particularly surprising for LLMs given their non-human nature and the assumption that people might be less receptive to cooperating with machines compared to human counterparts. Additionally, cooperation with LLMs was higher following prior interaction with humans, suggesting a spillover effect in cooperative behavior. Our findings validate the (careful) use of LLMs by businesses in settings that have a cooperative component. |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2507.18639 |
| By: | Natalia Montinari; Matteo Ploner; Veronica Rattini |
| Abstract: | Immigration has shaped many nations, posing the challenge of integrating immigrants into society. While economists often focus on immigrants' economic outcomes compared to natives (such as education, labor market success, and health) social interactions between immigrants and natives are equally crucial. These interactions, from everyday exchanges to teamwork, often lack enforceable contracts and require cooperation to avoid conflicts and achieve efficient outcomes. However, socioeconomic, ethnic, and cultural differences can hinder cooperation. Thus, evaluating integration should also consider its impact on fostering cooperation across diverse groups. This paper studies how priming different identity dimensions affects cooperation between immigrant and native youth. Immigrant identity includes both ethnic ties to their country of origin and connections to the host country. We test whether cooperation improves by making salient a specific identity: Common identity (shared society), Multicultural identity (ethnic group within society), or Neutral identity. In a lab in the field experiment with over 390 adolescents, participants were randomly assigned to one of these priming conditions and played a Public Good Game. Results show that immigrants are 13 percent more cooperative than natives at baseline. Natives increase cooperation by about 3 percentage points when their multicultural identity is primed, closing the initial gap with immigrant peers. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2507.02511 |
| By: | Jörg Papenkordt (Paderborn University); Axel-Cyrille Ngonga Ngomo (Paderborn University); Kirsten Thommes (Paderborn University) |
| Abstract: | Advances in AI and our limited human capabilities have made AI decision-making opaque to humans. One prerequisite for enhancing the transparency of AI recommendations is improving AI explainability as humans need to be enabled to take responsibility for their actions even with AI support. Our study aims to tackle this issue by investigating two basic approaches to explainability: We evaluate numerical explanations, such as certainty measures, against verbal explanations, such as those provided by LLM as explanatory agents. Specifically, we examine whether verbal or numerical (or both) explanations in tasks of high uncertainty lure users into false beliefs or, on the contrary, promote appropriate reliance. Drawing on an experiment with 441 participants, we explore the dynamics of non-expert users' interactions with AI under varying explanatory conditions. Results show that explanations significantly improve reliance and decision accuracy. Numerical explanations aid in identifying uncertainties and errors, but the users' reliance on the advice falls far behind the given numerical certainty. Verbal explanations foster higher reliance while increasing the risk of over-reliance. Combining both explanation types enhances reliance but further amplifies blind trust in AI. |
| Keywords: | explainable AI, artificial intelligence, human-computer interaction |
| JEL: | C83 D81 C88 O33 |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:pdn:dispap:147 |
| By: | Ben Weidmann; Yixian Xu; David J. Deming |
| Abstract: | We show that the ability to lead groups of humans is predicted by leadership skill with Artificially Intelligent agents. In a large pre-registered lab experiment, human leaders worked with AI agents to solve problems. Their performance on this 'AI leadership test' was strongly correlated with their causal impact on human teams, which we estimate by repeatedly randomly assigning leaders to groups of human followers and measuring team performance. Successful leaders of both humans and AI agents ask more questions and engage in more conversational turn-taking; they score higher on measures of social intelligence, fluid intelligence, and decision-making skill, but do not differ in gender, age, ethnicity or education. Our findings indicate that AI agents can be effective proxies for human participants in social experiments, which greatly simplifies the measurement of leadership and teamwork skills. |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2508.02966 |
| By: | Robin Musolff; Florian Zimmermann |
| Abstract: | Mental models help people navigate complex environments. This paper studies how people deal with model uncertainty. In an experiment, participants estimate a company’s value, facing uncertainty about which one of two models correctly determines its true value. Using a between-subjects design, we vary the degree of model complexity. Results show that in high-complexity conditions people fully neglect model uncertainty in their actions. However, their beliefs continue to reflect model uncertainty. This disconnect between beliefs and actions suggests that complexity leads to biased decision-making, while beliefs remain more nuanced. Furthermore, we show that complexity, via full uncertainty neglect, leads to higher confidence in the optimality of own actions. |
| Keywords: | mental models, geliefs, attention, confidence, representations |
| JEL: | D01 D83 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_12041 |
| By: | Daniel Engler (University of Kassel, Institute of Economics); Marvin Gleue (University of Kassel, Institute of Economics); Gunnar Gutsche (University of Kassel, Institute of Economics); Sophia Möller (University of Kassel, Institute of Economics); Andreas Ziegler (University of Kassel, Institute of Economics) |
| Abstract: | Legal norms can have a direct effect on individual behavior through their legal enforcement. However, according to the ‘expressive function of law, ’ they can also have indirect effects on individual behavior by shaping related social norms. Since evidence for this expressive function is scarce, we consider a new law on corporate due diligence for the protection of human rights and the environment (i.e. the German Supply Chain Act) and empirically examine its indirect effects on individual sustainable purchasing behavior, as indicated by the willingness to pay (WTP) for sustainable socks, where sustainability is ensured by the certification with a label of the Fair Wear Foundation. The empirical analysis is based on data from a pre-registered and incentivized experiment implemented in a representative survey of 1, 017 citizens in Germany. Before making socks purchasing decisions and the elicitation of related personal injunctive and perceived social norms, the respondents were randomly assigned to either a control group or a treatment group that received information about the German Supply Chain Act. We examine average treatment effects and, based on a causal mediation analysis, the mediating role of related personal injunctive and perceived social norms on individual sustainable purchasing behavior. A manipulation check shows that the treatment information has a significantly positive effect on individual knowledge about the objectives of the German Supply Chain Act. However, the treatment information has no significant effect on the WTP for sustainable socks with the Fair Wear Foundation label or on related norms. Although our mediation analysis reveals that personal injunctive and perceived social norms are significantly positively correlated with this WTP, our experimental analysis does not provide any evidence for the expressive function of law in the case of the German Supply Chain Act and individual sustainable purchasing behavior. |
| Keywords: | Legal norms, personal injunctive norm, perceived social norms, German Supply Chain Act, individual sustainable purchasing behavior |
| JEL: | D91 K38 Q58 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:mar:magkse:202510 |
| By: | John Zhuang Liu (University of Hongkong); Christoph Engel (Max Planck Institute for Research on Collective Goods, Bonn); Yun-chien Chang (Cornell Law School) |
| Abstract: | A real-world puzzle has eluded the attention of scholars and policymakers. Using unique data sets covering more than 8 million civil lawsuits in mainland China, Taiwan, and Japan, we observe that parties are often pro se even when high amounts of money are at stake. One (partial) explanation could be a “tipping point effect”: parties are more inclined to be represented by an attorney if they expect the case to be a close call – and less inclined if they believe the odds of winning to be very high or very low. We support the tipping point effect in survey experiments framed as litigation. If the otherwise identical experiment is an unframed lottery, the effect disappears. Based on this evidence, we argue that the effect results from the combination of two behavioral effects: reference point dependence, and competitive spirit. |
| Keywords: | pro se, attorney representation, reference point dependence, the near miss effect, anticipated regret, framing, competitive spirit |
| JEL: | C91 D86 D91 K41 |
| Date: | 2025–01 |
| URL: | https://d.repec.org/n?u=RePEc:mpg:wpaper:2025_01 |
| By: | Dang, Justin; Maeder, Nicolas; Mao, Chenyu; Yoo, Kwanjai |
| Abstract: | This report replicates the study by Belot et al. (2022), which investigates how posted wages affect labor supply through a field experiment using a job platform with varying wage postings. The paper's main finding is that a higher wage increases job seekers' interest in a vacancy, a result at odds with the same variables' inverse relationship in the paper's observational data. This report assesses the computational and robustness reproducibility of the referenced paper's results. Testing various empirical specifications and datasets, we find that all findings are, in fact, reproducible. Most importantly, the elasticity of a job posting's saves/views with respect to its posted wage is consistently positive and statistically significant across all of our specifications and datasets. |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:i4rdps:253 |
| By: | Gallegos, Sebastian |
| Abstract: | Bellemare et al. (2023b) examine discrimination against individuals with physical disabilities in the labor market in Quebec, Canada. Their findings indicate that callbacks from potential employers decrease by 25 percentage points if physical disability is (randomly) revealed. Callbacks increase by 10 percentage points if there is a video resume (randomly) sent to potential employers. In this document, we first conduct a computational reproduction using the replication package. Then, we test the robustness of the findings to the inclusion of different covariates, selecting them with a Double Selection Lasso approach. We complement the analysis estimating heterogeneous treatment effects using Causal Forests, which allow us to uncover data-driven subgroups and test their responses to the treatment. We find that Bellemare et al. (2023b)'s estimates are stable across these robustness checks. |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:i4rdps:256 |
| By: | Michael Keinprecht (Department of Economics, WU Vienna University of Economics and Business) |
| Abstract: | The growing inequalities around the world are becoming increasingly alarming making redistribution more relevant than ever. One reason why people may oppose redistribution is third party loss aversion. In a pre-registered online experiment with a within-subjects design, I show that redistribution decisions by third parties are affected by loss aversion. Overall, spectators are 7%-points less likely to redistribute from a status quo to an alternative if the alternative entails a loss for one person, even if inequality aversion, maximin preferences and efficiency concerns favor the alternative. This effect is stronger the higher the loss is compared to the gain and the higher the individual loss aversion of the spectator. The key contribution of the paper is to disentangle third party loss aversion from pure status quo bias, rank reversal aversion and other distributional preferences in multiple loss scenarios and to link it to individual loss aversion. |
| Keywords: | Third party loss aversion, loss aversion, redistribution, spectators, fairness |
| JEL: | D91 D63 |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:wiw:wiwwuw:wuwp382 |
| By: | Dan Anderberg; Rachel Cassidy; Anaya Dam; Melissa Hidrobo; Jessica Leight; Karlijn Morsink |
| Abstract: | One in three women globally experiences intimate partner violence (IPV), yet little is known about how such trauma affects economic decision-making. We provide causal evidence that IPV influences women's time preferences - a key parameter in models of savings, investment, and labor supply. We combine two empirical strategies using four distinct datasets. First, in two randomized recall experiments in Ethiopia, we randomly assigned women to recall specific acts of abuse before eliciting their intertemporal choices. Women with IPV experiences prompted to recall IPV display significantly greater impatience than otherwise similar women who are not prompted. Second, we exploit exogenous reductions in IPV generated by two randomized interventions - one involving cash transfers, the other psychotherapy - and use treatment assignment as an instrument for IPV exposure. Women who experience reduced IPV as a result of treatment exhibit more patient time preferences. Together, these results provide consistent, novel causal evidence that exposure to IPV induces individuals to discount the future more heavily. This evidence suggests a psychological channel through which violence can perpetuate economic disadvantage and constrain women's ability to take actions - such as saving, investing, or exiting abusive relationships - that require planning over time. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2507.10416 |
| By: | Peter Haan; Chen Sun; Felix Weinhardt; Georg Weizsäcker |
| Abstract: | Different methods of eliciting long-run expectations yield data that predict economic choices differently well. We ask members of a wide population sample to make a 10-year investment decision and to forecast stock market returns in one of two formats: they either predict the average of annual growth rates over the next 10 years, or they predict the total, cumulative growth that occurs over the 10-year period. Results show that total 10-year forecasts are more pessimistic than average annual forecasts, but they better predict experimental portfolio choices and real-world stock market participation. |
| Keywords: | Household finance, long-run predictions, survey experiments |
| JEL: | D01 D14 D84 D9 |
| Date: | 2025–07–28 |
| URL: | https://d.repec.org/n?u=RePEc:bdp:dpaper:0070 |
| By: | Gabriel Bayle (GATE Lyon Saint-Étienne - Groupe d'Analyse et de Théorie Economique Lyon - Saint-Etienne - UL2 - Université Lumière - Lyon 2 - UJM - Université Jean Monnet - Saint-Étienne - EM - EMLyon Business School - CNRS - Centre National de la Recherche Scientifique); Marc Willinger (CEE-M - Centre d'Economie de l'Environnement - Montpellier - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - Institut Agro Montpellier - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement - UM - Université de Montpellier) |
| Abstract: | The minimum approval mechanism (MAM) was introduced by Masuda et al. ( 2014) as a mechanism aimed at mitigating free riding in the social dilemma context of a public good game. The MAM is a two-stage mechanism which theoretically achieves the socially optimum level of public good provision, according to various equilibrium concepts (e.g., backward elimination of weakly dominated strategies, level-k, or minimax regret). We study the robustness of this mechanism to the introduction of endowment heterogeneity. We explore, theoretically and experimentally, how endowment inequalities affect the effectiveness of the MAM at improving the level of provision. We find that the mechanism is still Pareto-improving under endowment heterogeneity, but that its efficiency diminishes as inequality is increased. Our experimental findings indicate a significant weakening of the mechanism under endowment inequalities, surpassing our theoretical predictions. A close examination of individual behaviors reveals a significant drop in contributions compared to the uniform case, prompted by even minor inequalities. Intriguingly, our findings challenge conventional assumptions by showing that inequality aversion drives contributions in a public good game with endowment disparities only under certain assumptions. We explore the impact of beliefs about the contributions of advantaged players as potential motivations through guilt aversion and Kantian preferences. |
| Keywords: | approval mechanism, inequalities, inequality aversion, public goods |
| Date: | 2025–07–20 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05173769 |
| By: | Gagnon, Nickolas; Nosenzo, Daniele |
| Abstract: | We reconsider discrimination preferences through moral lenses and conduct experiments to systematically investigate these preferences using representative UK samples. Specifically, we evaluate the distribution of individual preferences for and against taste-and statistical-based discrimination across three domains—ethnicity, gender, and LGBTQ+ status. Using over 60, 000 anonymous decisions affecting how workers are paid from more than 3, 500 individuals, we document that most individuals prefer to engage in at least one type of discrimination, that there is substantial heterogeneity in preferences, and that the existence of multiple preferences changes our understanding of why individuals engage or not in discrimination. Among others, we examine how preferences relate across domains, map them onto socio-demographic characteristics, politics, support for policies, and gender wage gaps, and study underlying redistributive principles and effects of wage transparency. |
| Keywords: | Ethnicity, Gender, LGBTQ+, Moral principles, Experiment, Discrimination |
| JEL: | D63 D90 J23 J31 J71 J78 K31 M52 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:esprep:323979 |
| By: | Christoph Engel (Max Planck Institute for Research on Collective Goods, Bonn) |
| Abstract: | In an experiment on the large language model GPT-4o, a supplier always makes a higher profit if it replaces uniform contract terms with a set of terms between which the custom-er may choose. The extra profit results from price discrimination. There is a first order and a second order effect. The first order effect results from heterogeneous willingness to pay for a more protective term. The second order effect results from the possibility that con-tract choice is a signal for general willingness to pay for the traded commodity. In the ex-periment, the effect is bigger if the least protective version is labelled as the default, and more protective terms as an “upgrade†. The effect is smaller if, conversely, the most pro-tective version is labelled as the default and less protective (and cheaper) versions as an opportunity for “savings†. The effect is also bigger if the supplier only sets the price after it knows which version of the contract the consumer chooses. The profit increasing effect of giving the consumer a choice is strong. There is no piece of demographic information that has a stronger effect. Most pieces of demographic information (which the supplier might, for instance, learn through cookie data) have a significantly smaller effect on profit. If the supplier combines cookie information about demographic markers with contract choice, it always makes an extra profit. |
| Keywords: | forced choice of contract clause; price discrimination; large language model; experiment |
| JEL: | C91 D01 D02 D12 D42 D91 K12 |
| Date: | 2024–12 |
| URL: | https://d.repec.org/n?u=RePEc:mpg:wpaper:2024_19 |
| By: | Christoph Engel (Max Planck Institute for Research on Collective Goods, Bonn); Jasmin Golder (University of Heidelberg); Rima-Maria Rahal (Max Planck Institute for Research on Collective Goods and University of Heidelberg) |
| Abstract: | Defendants should be judged on the merits of the case, not on prejudice, rumors, or evidence obtained through questionable methods. This is why criminal law of procedure regulates which information can be introduced in a trial. Two types of prohibited evidence are the criminal history of the defendant (the defendant shall not be considered more likely guilty since he had earlier been convicted for another crime), and information harvested from an unauthorized wiretap. In a series of online vignette experiments involving 1432 US participants, we show that character evidence never makes it significantly more likely that the defendant is judged guilty, whereas wiretap evidence has a strong effect. Various interventions aimed at debiasing the adjudicator have an effect, but this effect is insufficient to neutralize the bias. |
| Keywords: | criminal procedure, character evidence, wiretap, bias, debiasing |
| JEL: | C91 D02 D84 D91 K14 K41 K42 |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:mpg:wpaper:2024_17 |
| By: | Matthew A. Tarduno; Reed Walker |
| Abstract: | This paper explores whether misperceptions about air pollution contribute to environmental inequality in the United States. We use a two-part survey experiment to elicit respondents' beliefs about local air quality and pollution's effects on life expectancy. We document how misperception differs across demographic groups and then how this misperception affects willingness to pay (WTP) for cleaner air. Since misperception or beliefs may be correlated with other unobservable determinants of WTP, we randomly show selected participants customized information about their actual air pollution. This allows us to trace out how experimentally induced changes in beliefs affect WTP for air quality. Our results suggest significant misperceptions about air pollution in the US. Respondents, on average, overestimate both their air pollution exposure and its impact on life expectancy. Beliefs about relative air pollution are not systematically biased but are noisy. Despite some differences in misperceptions between Black and White respondents, counterfactual exercises do not suggest that rectifying these misperceptions would meaningfully close the observed gap in WTP and/or pollution exposure. |
| JEL: | H4 Q5 |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34116 |
| By: | Nicolas L. Bottan; Ricardo Perez-Truglia; Hitoshi Shigeoka; Katsunori Yamada |
| Abstract: | Preferences for status are typically attributed to two distinct channels: self-image, in which individuals derive utility from being richer than others, and social-image, in which individuals value being seen as richer by others. While both channels are believed to be at play, little is known about their relative importance. We address this gap using a hypothetical discrete choice experiment. Our findings indicate that self-image is at most 19.3% as important as social-image. Additionally, we document substantial heterogeneity in the strength of these preferences across individuals and domains. |
| JEL: | C9 Z13 |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34094 |
| By: | Blaufus, Kay; Maiterth, Ralf; Milde, Michael; Sureth, Caren |
| Abstract: | We examine behavioral frictions in entrepreneurs' tax planning when choosing between corporate and partnership taxation under a check-the-box rule. Using German tax return data, we show that only a small fraction of entrepreneurs opt for corporate taxation, despite substantial potential tax savings. A pre-registered incentivized online experiment demonstrates that complexity aversion, status quo bias, and misperception about the corporate tax burden-arising from the interaction of corporate and deferred dividend taxation-help explain the preference for partnership taxation. We further find that these behavioral frictions heighten liquidity risk under the corporate system, particularly in the face of unexpected cash flow needs. Finally, a survey of German tax advisors indicates that tax advice only partially mitigates these frictions. Some advisors misperceive the benefits of corporate taxation, while others anticipate client biases and therefore refrain from recommending the corporate tax system. |
| Keywords: | Check-the-box, Legal Form, Tax Complexity, Tax Misperception, Behavioral Taxation, Tax Advice |
| JEL: | H25 D91 D22 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:arqudp:323941 |
| By: | Francesca Cibrario; Ron Cohen; Emanuele Dri; Christian Mattia; Or Samimi Golan; Tamuz Danzig; Giacomo Ranieri; Hanan Rosemarin; Davide Corbelletto; Amir Naveh; Bartolomeo Montrucchio |
| Abstract: | We present a comprehensive quantum algorithm tailored for pricing autocallable options, offering a full implementation and experimental validation. Our experiments include simulations conducted on high-performance computing (HPC) hardware, along with an empirical analysis of convergence to the classically estimated value. Our key innovation is an improved integration-based exponential amplitude loading technique that reduces circuit depth compared to state-of-the-art approaches. A detailed complexity analysis in a relevant setting shows an approximately 50x reduction in T-depth for the payoff component relative to previous methods. These contributions represent a step toward more efficient quantum approaches to pricing complex financial derivatives. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2507.19039 |
| By: | Barone, Guglielmo (University of Bologna); Loviglio, Annalisa (University of Bologna); Tommasi, Denni (University of Bologna) |
| Abstract: | Digital skills are increasingly essential for full participation in modern life. Yet many low-income families face a dual digital divide: limited access to technology and limited ability to use it effectively. These gaps can undermine adults' ability to support their children's education, restrict access to public services, and reduce their own employability. Despite growing policy attention, rigorous evidence on how to close these gaps—especially among disadvantaged adults in high-income countries—remains scarce. We evaluate the impact of a comprehensive digital inclusion program in Turin, Italy, targeting 859 low-income families with school-aged children. Participants were randomly assigned to a control group or one of two treatment arms, each combining a free tablet with internet access and digital literacy training of different durations. One year later, treated participants reported large improvements in daily technology use and digital skills, as measured by the "Digital Skills Indicator 2.0" (DSI) developed by Eurostat. Parents also became more confident in guiding their children's online activities, more engaged in digital parenting, and more likely to access public services digitally. We find no effects on employment or job search behavior, but treated participants expressed greater optimism about future training prospects. The effects are statistically similar across the two training intensities, suggesting that (i) once basic barriers are removed, digital engagement can become self-sustaining, and/or (ii) that the returns to digital training are strongly diminishing. Mediation analysis confirms that digital skills — not just access — are key drivers of broader behavioral and economic outcomes. Sequential effects are particularly strong in the domains of social inclusion and parenting. The findings underscore the importance of addressing both financial and learning constraints and suggest that bundled interventions can foster inclusive digital participation. |
| Keywords: | digital divide, digital literacy, low-income families, labor market outcomes, digital parenting |
| JEL: | I24 J24 O33 C93 |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18032 |
| By: | Sandra Walzenbach; Thomas Hinz |
| Abstract: | In today’s digital media landscape, individuals must judge the credibility of competing information from an unprecedented range of sources, including established news organizations, political actors, unverified online voices and self-declared experts. Building on a theoretical discussion of how the internet and social media – with its algorithmic curation, its omnipresent misinformation and strategic disinformation – have altered media consumption, this study examines the challenges individuals face in evaluating the credibility of media content. Informed by dual-process theory and the concept of motivated reasoning, we explore the roles of both belief-consistency and established quality cues (namely source expertise and data references) in shaping credibility judgments. We use the Covid-19 pandemic in Germany as a case study of polarization, contrasting an inconspicuous majority with a vocal minority represented by the “Querdenker” protest movement. Heavily relying on social media, this movement mobilized a heterogeneous base of supporters united by deep-rooted mistrust of politics, science, and mainstream media. To investigate these dynamics, we conducted a factorial survey experiment in which a general population sample evaluated the credibility of Covid-19–related media content. The results provide strong evidence of confirmation bias, no detectable effect of quality cues, and remarkably similar evaluation strategies across both groups. |
| Keywords: | public opinion, media perception, polarization, Covid-19, confirmation bias, factorial survey experiment |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:esprep:324165 |
| By: | Senan Hogan-Hennessy |
| Abstract: | Natural experiments are a cornerstone of applied economics, providing settings for estimating causal effects with a compelling argument for treatment randomisation, but give little indication of the mechanisms behind causal effects. Causal Mediation (CM) provides a framework to analyse mechanisms by identifying the average direct and indirect effects (CM effects), yet conventional CM methods require the relevant mediator is as-good-as-randomly assigned. When people choose the mediator based on costs and benefits (whether to visit a doctor, to attend university, etc.), this assumption fails and conventional CM analyses are at risk of bias. I propose a control function strategy that uses instrumental variation in mediator take-up costs, delivering unbiased direct and indirect effects when selection is driven by unobserved gains. The method identifies CM effects via the marginal effect of the mediator, with parametric or semi-parametric estimation that is simple to implement in two stages. Applying these methods to the Oregon Health Insurance Experiment reveals a substantial portion of the Medicaid lottery's effect on self-reported health and happiness flows through increased healthcare usage -- an effect that a conventional CM analysis would mistake. This approach gives applied researchers an alternative method to estimate CM effects when an initial treatment is quasi-randomly assigned, but the mediator is not, as is common in natural experiments. |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2508.05449 |
| By: | Maria A. Cattaneo; Christian Gschwendt; Stefan C. Wolter |
| Abstract: | The global rise in tertiary educational attainment has been attributed to various factors, most commonly higher expected earnings, improved protection against technological change, and prospects for upward social mobility. In a large-scale discrete-choice experiment with nearly 6, 000 adults, we show that when these three factors are held constant, individuals show on average no additional intrinsic willingness to pay (WTP) for a university degree. Individuals are willing to forgo an amount of income roughly equivalent to the total cost of obtaining a university degree - including opportunity and direct costs-when trading off such a degree against basic vocational education. However, we observe significant heterogeneity depending on respondents' own educational attainment, gender and type of tertiary education: individuals with tertiary qualifications and men assign a higher value to higher education and the WTP is higher for university of applied degrees compared to academic university degrees. |
| Keywords: | University, discrete choice experiment, willingness to pay, Switzerland |
| JEL: | I21 I23 I26 |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:iso:educat:0247 |
| By: | Ismaël Rafaï (GREDEG - Groupe de Recherche en Droit, Economie et Gestion - UNS - Université Nice Sophia Antipolis (1965 - 2019) - CNRS - Centre National de la Recherche Scientifique - UniCA - Université Côte d'Azur); Bérengère Davin-Casalena (ORS PACA - Observatoire régional de la santé Provence-Alpes-Côte d'Azur [Marseille]); Dimitri Dubois (CEE-M - Centre d'Economie de l'Environnement - Montpellier - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - Institut Agro Montpellier - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement - UM - Université de Montpellier); Thierry Blayac (CEE-M - Centre d'Economie de l'Environnement - Montpellier - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - Institut Agro Montpellier - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement - UM - Université de Montpellier); Bruno Ventelou (AMSE - Aix-Marseille Sciences Economiques - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique) |
| Abstract: | Recent advances in artificial intelligence (AI) have made it possible to detect neurodegenerative diseases (NDDs) earlier, potentially improving patient outcomes. However, AI-based detection tools remain underutilized. We studied individual valuation for early diagnosis tests for NDDs. We conducted a discrete choice experiment with a representative sample of the French adult population (N = 1017). Participants were asked to choose between early diagnosis tests that differed in terms of: (1) type of test (saliva vs. AI-based tests analysing electronic health records); (2) identity of the person communicating the test results; (3) sensitivity; (4) specificity; and (5) price. We calculated the weights in the decision for each attribute and examined how socio-demographic characteristics influenced them. Respondents revealed a reduced utility value when AI-based testing was involved (valuated at an average of €36.08, CI [€22.13; €50.89]) and when results were communicated by a private company (€95.15, CI [€82.01; €109.82]). We interpret these figures as the shadow price that the public attaches to medical data privacy. Beyond monetization, our representative sample of the French population appears reluctant to adopt AI-powered screening, particularly when performed on large sets of personal data. However, they would be more supportive when medical expertise is associated with the tests. |
| Date: | 2025–07–23 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05189620 |