Fiala, L. & Husovec, M. (2022) Using Experimental Evidence to Improve Delegated Enforcement. International Review of Law & Economics. Vol. 71. 106079.

Abstract: Digital content today is governed by online providers like Facebook or YouTube. Increasingly, these providers are expected to enforce the law by removing illegal content, such as copyright infringement or hate speech. Typically, once they are notified of its existence, they have to assess it and, if infringing, remove it. Otherwise, they face liability. This system of content moderation is a form of delegation of the state's tasks to private parties. In literature, it is empirically established that some schemes of delegated enforcement can trigger substantial false positives, mostly due to over-compliance by providers and under-assertion of rights by affected content creators. This results in a phenomenon known as over-blocking: collateral removal of lawful content. We conduct a laboratory experiment to test a possible solution to this issue, as proposed by Husovec (2016). Our results show that an external dispute resolution mechanism subject to a particular fee structure can significantly reduce over-compliance by providers and improve the accuracy of their decisions, largely thanks to the content creators taking initiative. It does so by re-calibrating the typical asymmetry of incentives under the delegated enforcement schemes. The principles behind the solution have the potential to improve also other schemes of delegated enforcement where providers have weak incentives to properly execute delegated tasks in the public interest.

PDF: Here. (published open access)

z-tree code: Here.

Data & code: Here.

In media:

• Frontier Economics: `To Delete or Not to Delete’ (link)

Impact:

• The EU Advocate General cited our paper as evidence of over-blocking in one of the pending cases before the Court of Justice of the European Union concerning the constitutionality of EU law (C-401/19).
• The European Commission adopted the paper's mechanism after a workshop with my co-author Martin in its Digital Services Act proposal (a major piece of EU legislation that will regulate online digital services like Facebook, YouTube and Twitter). DSA’s Article 18 foresees an out-of-court dispute resolution mechanism whose costs are to be borne by the platforms in case they lose, as proposed by the paper.

Fiala, L., Humphries, J. E., Joensen, J. S., Karna, U., List, J. A., & Veramendi, G. F. (2022) How Early Adolescent Skills and Preferences Shape Economics Education Choices. AEA Papers & Proceedings. Vol. 122. 609-613.

Abstract: Leveraging data from Sweden and Chicago, we study the educational pipeline for STEM and economics majors to better understand the determinants of the gender gap, and when these determinants arise. We present three findings. First, females are less likely to select STEM courses in high school, despite equal or better preparation. Second, there are important gender differences in preferences and beliefs, even conditional on ability. Third, early differences in preferences and beliefs explain more of the gaps in high school sorting than other candidate variables. High school sorting then explains a large portion of the gender difference in college majors.

PDF: Here.

Online appendix: Here.

Data & code: (coming soon)

Fiala, L. & Suetens, S. (2017) Transparency and cooperation in repeated dilemma games: a meta study. Experimental Economics. Vol. 20(4). 755-771.

Abstract: We use data from experiments on finitely repeated dilemma games with fixed matching to investigate the effect of different types of information on cooperation. The data come from 71 studies using the voluntary contributions paradigm, covering 122 data points, and from 18 studies on decision-making in oligopoly, covering another 50 data points. We find similar effects in the two sets of experimental games. We find that transparency about what everyone in a group earns reduces contributions to the public good, as well as the degree of collusion in oligopoly markets. In contrast, transparency about choices tends to lead to an increase in contributions and collusion, although the size of this effect varies somewhat between the two settings. Our results are potentially useful for policy making, because they provide guidance on the type of information to target in order to stimulate or limit cooperation.

Data & code: Download here or access at Dataverse.

PDF: Download here.

Fiala, L. & Noussair, C. (2017) Charitable Giving, Emotions, and the Default Effect. Economic Inquiry. Vol. 55(4). 1792–1812.

Abstract: We report an experiment to study the effect of defaults on charitable giving. In three different treatments, participants face varying default levels of donation. In three other treatments that are paired with the first three, they receive the same defaults, but are informed that defaults are thought to have an effect on their donation decisions. The emotional state of all individuals is monitored throughout the sessions using Facereading software, and some participants are required to report their emotional state after the donation decision. We find that the default level has no effect on donations, and informing individuals of the possible impact of defaults also has no effect. The decision to donate is independent of prior emotional state, unless specific subgroups of participants are considered. Donors experience a negative change in the valence of their emotional state subsequent to donating, when valence is measured with Facereading software. This contrasts with the selfreport data, in which donating correlates with a more positive reported subsequent emotional state.

Data & code: Download here.

Link to PDF: Here.

Impact:

• Top 20 most downloaded paper in the Economic Inquiry in 2017-2018 (certificate, details)

Schaerer, M., du Plessis, C., Nguyen, M. H. B., van Aert, R. C. M., Tiohkin, L., Lakens, D., (5 others plus 185-author consortium including Fiala, L.), Uhlmann, E. L. (2023) On the Trajectory of Discrimination: A Meta-analysis and Forecasting Survey Capturing 44 Years of Field Experiments on Gender and Hiring Decisions. Organizational Behavior and Human Decision Processes. Vol. 179. 104280.

Abstract: A preregistered meta-analysis, including 244 effect sizes from 85 field audits and 361,645 individual job applications, tested for gender bias in hiring practices in female-stereotypical and gender-balanced as well as male-stereotypical jobs from 1976 to 2020. A “red team” of independent experts was recruited to increase the rigor and robustness of our meta-analytic approach. A forecasting survey further examined whether laypeople (n = 499 nationally representative adults) and scientists (n = 312) could predict the results. Forecasters correctly anticipated reductions in discrimination against female candidates over time. However, both scientists and laypeople overestimated the continuation of bias against female candidates. Instead, selection bias in favor of male over female candidates was eliminated and, if anything, slightly reversed in sign starting in 2009 for mixed-gender and male-stereotypical jobs in our sample. Forecasters further failed to anticipate that discrimination against male candidates for stereotypically female jobs would remain stable across the decades.

PDF: Here.

Pre-registration, data, code: Here and here.

Huber, C., Dreber, A., Huber, J., Johannesson, M., Kirchler, M., Weitzel, U., (88 others including Fiala, L.), Holzmeister, F. (2023) Competition and Moral Behavior: A Meta-analysis of Forty-five Crowd-sourced Experimental Designs. PNAS. Vol. 120(23). 2215572120.

Abstract: Does competition affect moral behavior? This fundamental question has been debated among leading scholars for centuries, and more recently, it has been tested in experimental studies yielding a body of rather inconclusive empirical evidence. A potential source of ambivalent empirical results on the same hypothesis is design heterogeneity—variation in true effect sizes across various reasonable experimental research protocols. To provide further evidence on whether competition affects moral behavior and to examine whether the generalizability of a single experimental study is jeopardized by design heterogeneity, we invited independent research teams to contribute experimental designs to a crowd-sourced project. In a large-scale online data collection, 18,123 experimental participants were randomly allocated to 45 randomly selected experimental designs out of 95 submitted designs. We find a small adverse effect of competition on moral behavior in a meta-analysis of the pooled data. The crowd-sourced design of our study allows for a clean identification and estimation of the variation in effect sizes above and beyond what could be expected due to sampling variance. We find substantial design heterogeneity—estimated to be about 1.6 times as large as the average standard error of effect size estimates of the 45 research designs—indicating that the informativeness and generalizability of results based on a single experimental design are limited. Drawing strong conclusions about the underlying hypotheses in the presence of substantive design heterogeneity requires moving toward much larger data collections on various experimental designs testing the same hypothesis.

PDF: Here. (published open access)

Data & code: Here.

Brodeur, A. et al. (2024) : Mass Reproducibility and Replicability: A New Hope

Abstract: This study pushes our understanding of research reliability by reproducing and replicating claims from 110 papers in leading economic and political science journals. The analysis involves computational reproducibility checks and robustness assessments. It reveals several patterns. First, we uncover a high rate of fully computationally reproducible results (over 85%). Second, excluding minor issues like missing packages or broken pathways, we uncover coding errors for about 25% of studies, with some studies containing multiple errors. Third, we test the robustness of the results to 5,511 re-analyses. We find a robustness reproducibility of about 70%. Robustness reproducibility rates are relatively higher for re-analyses that introduce new data and lower for re-analyses that change the sample or the definition of the dependent variable. Fourth, 52% of re-analysis effect size estimates are smaller than the original published estimates and the average statistical significance of a re-analysis is 77% of the original. Lastly, we rely on six teams of researchers working independently to answer eight additional research questions on the determinants of robustness reproducibility. Most teams find a negative relationship between replicators’ experience and reproducibility, while finding no relationship between reproducibility and the provision of intermediate or even raw data combined with the necessary cleaning codes.

PDF: here

Fiala, L. (2022) Statistical Role Models.

Abstact: I study whether the reason why role models change people’s behavior is because they communicate that a person of a specific identity has been able to succeed. I use an online experiment to isolate the effect of providing such information about past successful participants (‘statistical role models’) on subjects’ decision to enter a risky, yet relatively high-paying math task, and their subsequent performance on the task. I set my study in the context of gender stereotypes regarding mathematical ability, systematically manipulate the salience of stereotypes associated with the task, and test the mechanisms that drive participation and performance in these settings. I find that while the information and stereotype treatments successfully manipulate beliefs about aggregate gender success rates, this does not affect any of the measures associated with individual task choice or success (self-confidence, math ability, and effort), leaving both outcomes of interest unaffected.

PDF: (coming soon)

Pre-registration: Pre-test and main experiment.

In media:

• Innovation Growth Lab blog

Fiala, L. (2022) Can You Fight Fake News with Reason?

Abstract: I study the introduction of a compulsory argumentation and debate program into high school curricula. I measure the impact of the program on critical thinking, and specifically on the students' ability to recognize a fake article and pinpoint parts that require fact-checking.

PDF: (coming soon)

In media:

• Die Welt: So wollen Top-Ökonomen die Welt verbessern. (link)
• Lindau Nobel Laureate Meetings 2017: The Press Talk. (info, German version, English version, photo) Photo credit to Julia Nimke/Lindau Nobel Laureate Meetings

Awards:

• Young Researcher ASFEE 2019 Prize for the best experimental poster (2019)

Fiala, L., Joensen, J. S., List, J. A., Pagnotta, F., & Uchida, H. (2024) Peers and the Evolution of Skills during Adolescence.

Abstract: (being revised)

Dasgupta, S., Fiala, L. & Mol, J. M. (2024) For the ‘Greater Good’: Please Choose A.

Abstract: How do people trade off individual versus group welfare in the face of uncertainty regarding private benefits of different actions? We propose a partial information revelation (‘recommendation’) policy designed to maximize group welfare, and we show its theoretical robustness to well-documented behavioral deviations from the risk neutral, Bayesian, and self-interested benchmark. In a large-scale online experiment with 2600 subjects, we then show that this policy fails to improve upon a full information benchmark even when individual and group objectives are aligned, as the recommended course of action is not followed often enough. In a setting where individual and group interests clash, the recommendation is followed less often, largely by subjects who misunderstand the policy. This provides suggestive evidence in favor of simplicity in information design in multi-agent strategic settings.

Pre-registration: link

PDF: here

Fiala, L., Fleisje, E. M. & Reiremo, T. A. (2023) Replication: Reshaping Adolescents' Gender Attitudes: Evidence from a School-Based Experiment in India.

Abstract: Dhar et al. (2022) examine the effect of a gender attitude change program in secondary schools in India. In their preferred specification, the authors show that the program made the students report more gender-egalitarian attitudes by 0.18 of a standard deviation, and shifted self-reported behaviors to be more aligned with gender-progressive norms by 0.20 standard deviations (both significant at 1% level). In contrast, they found no effect on girls’ aspirations, as these were already high before the intervention. The effects did not attenuate between the first end-line (right after the programme was completed) and the second (two years later). To put the paper’s results in perspective, we first comment on the authors’ deviations from their pre-registration and pre-analysis plans, provide detailed power calculations, and add multiple-hypothesis-testing-adjusted standard errors. Second, we show that the paper’s results are perfectly reproducible. Third, we show that the results are robust to excluding control variables, and alternative ways of constructing indices and dealing with non-response.

PDF: here

Fiala, L. & de Haan, T. Back in Our Day: Are Math Exams Getting Easier?

Dalton, P., Fiala, L., van der Heijden, E. & van Soest, D. The Impact of Mentoring on Students' Performance. Evidence from a Randomized Evaluation.