Papers - John A List

James Andreoni, Amalia Di Girolamo, John A List, Claire Mackevicius, Anya Samek

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We conduct experiments eliciting risk preferences with over 1,400 children and adolescents aged 3-15 years old. We complement our data with an assessment of cognitive and executive function skills. First, we find that adolescent girls display significantly greater risk aversion than adolescent boys. This pattern is not observed among young children, suggesting that the risk gap in risk preferences emerges in early adolescence. Second, we find that at all ages in our study, cognitive skills (specifically math ability) are positively associated with risk taking. Executive functions among children, and soft skills among adolescents, are negatively associated with risk taking. Third, we find that greater risk-tolerance is associated with higher likelihood of disciplinary referrals, which provides evidence that our task is equipped to measure a relevant behavioral outcome. For academics, our research provides a deeper understanding of the developmental origins of risk preferences and highlights the important role of cognitive and executive function skills to better understand the association between risk preferences and cognitive abilities over the studied age range.

John A List, Zacharias Maniadis, Fabio Tufano

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The sciences are in an era o fan alleged "credibility crisis'. In this study, we discuss the reproducibility of empirical results, focusing on economics research. By combining theory and empirical evidence, we discuss the import of replication studies, and whether they improve our confidence in novel findings. The theory sheds light on the importance of replications, even when replications are subject to bias. We then present a pilot meta-study of replication in experimental economics, a subfield serving as a positive benchmark for investigating the credibility of economics. Our meta-study highlights certain difficulties when applying meta-research (Ioannidis et al., 2015) and systematizing the economics literature.

John A List

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No abstract available

Andreas Leibbrandt, John A List

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Labor force composition and the allocation of talent remain of vital import to modern economies. For their part, governments and companies around the globe have implemented equal employment opportunity (EEO) regulations to influence labor market flows. Even though such regulations are pervasive, surprisingly little is known about their impacts. We use a natural field experiment conducted across 10 U.S. cities to investigate if EEO statements in job advertisements affect the first step in the employment process, application rates. Making use of data from nearly 2,500 job seekers, we find considerable policy effects, but in an unexpected direction: the presence of an EEO statement dampens rather than encourages racial minorities willingness to apply for jobs. Importantly, the effects are particularly pronounced for educated job seekers and in cities with white majority populations. Complementary survey evidence suggests the underlying mechanism at work is "tokenism", revealing that EEO statements backfire because racial minorities avoid environments in which they are perceived as regulatory, or symbolic, hires rather than being hired on their own merits. Beyond their practical and theoretical importance, our results highlight how field experiments can significantly improve policy making. In this case, if one goal of EEO regulations is to enhance the pool of minority applicants, then it is not working.

John A List

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Last year I put together a summary of data from my field experiments website that pertained to framed field experiments. Several people have asked if I have an update. In this document I update all figures and numbers to show the details for 2020. I also include the description from the 2019 paper below.

Kentaro Asai, Seda Ertac, Ali Hortacsu, John A List, Howard Nusbaum, Lester Tong, Karen Ye

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People often demand a greater price when selling goods that they own than they would pay to purchase the same goods- a well-known economic bias called the endowment effect. The endowment effect has been found to be muted among experienced traders, but little is known about how trading experience reduces the endowment effect. We show that when selling, experienced traders exhibit lower right anterior insula activity, but no differences in nucleus accumbens or orbitofrontal activation, compared with inexperienced traders. Furthermore, insula activation mediates the effect of experience on the endowment effect. Similar results are obtained for inexperienced traders who are incentivized to gain trading experience. This finding indicates that frequent trading likely mitigates the endowment effect indirectly by modifying negative affective responses in the context of selling.

Yan Chen, Peter Cramton, John A List, Axel Ockenfels

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We review past research and discuss future directions on how the vibrant research areas of market design and behavioral economics have influenced and will continue to impact the science and practice of management in both the private and public sectors. Using examples from various auction markets, reputation and feedback systems in online markets, matching markets in education, and labor markets, we demonstrate that combining market design theory, behavioral insights, and experimental methods can lead to fruitful implementation of superior market designs in practice.

Matilde Giaccherini, David H Herberich, David Jimenez-Gomez, John A List, Giovanni Ponti, Michael K Price

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This paper uses a field experiment to estimate the effects of prices and social norms on the decision to adopt and efficient technology. We find that prices and social norms influence the adoption and decision along different margins: while prices operate on both the extensive and intensive margins, social norms operate mostly through the extensive margin. This has both positive and normative implications, and suggests that economics and psychology may be strong complements in the diffusion process. To complement the reduced form results, we estimate a structural model that points to important household heterogeneity: whereas some consumers welcome the opportunity to purchase and learn about the new technology, for others the inconvenience and social pressure of the ask results in negative welfare. As a whole, our findings highlight that the design of optimal technological diffusion policies will require multiple instruments and a recognition of household heterogeneity.

Omar Al-Ubaydli, John A List, Dana L Suskind

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Policymakers are increasingly turning to insights gained from the experimental method as a means of informing public policies. Whether-and to what extent-insights from a research study scale to the level of the broader public is, in many situations, based on blind faith. This scale-up problem can lead to a vast waste of resources, a missed opportunity to improve people's lives, and a diminution in the public's trust in the scientific method's ability to contribute to policymaking. This study provides a theoretical lens to deepen our understanding of the science of how to use science. Through a simple model, we highlight three elements of the scale-up problem: (1) when does evidence become actionable (appropriate statistical inference); (2) properties of the population; and (3) properties of the situation. We argue that until these three areas are fully understood and recognized by researchers and policymakers, the threats to scalability will render any scaling exercise as particularly vulnerable. In this way, our work represents a challenge to empiricists to estimate the nature and extent of how important the various threats to scalability are in practice, and to implement those in their original research.

Omar Al-Ubaydli, John A List, Claire Mackevicius, Min Sok Lee, Dana L Suskind

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Policymakers are increasingly turning to insights gained from the experimental method as a means to inform large scale public policies. Critics view this increased usage as premature, pointing to the fact that many experimentally-tested programs fail to deliver their promise at scale. Under this view, the experimental approach drives too much public policy. Yet, if policymakers could be more confident that the original research findings would be delivered at scale, even the staunchest critics would carve out a larger role for experiments to inform policy. Leveraging the economic framework of Al-Ubaydli et al. (2019), we put forward 12 simple proposals, spanning researchers, policymakers, funders, and stakeholders, which together tackle the most vexing scalability threats. The framework highlights that only after we deepen our understanding of the scale up problem will we be on solid ground to argue that scientific experiments should hold a more prominent place in the policymaker's quiver.

Amanda Chuan, John A List, Anya Samek

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Research has shown that giving disadvantaged families financial incentives to invest in their children could decrease socioeconomic inequality by enhancing human capital formation. Yet, within the household how are such gains achieved? We use a field experiment to investigate how parents allocate time when they receive financial incentives. We find that incentives increase investment in the target child. But, parents achieve these gains by substituting away from time spent with the child's sibling(s). An unintended consequence is that intrahousehold inequality increases and aggregate gains from the program are overstated when focusing only on target children.

John A List

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While empirical economics has made important strides over the past half century, there is a recent attack that threatens the foundations of the empirical approach in economics: external validity. Certain dogmatic arguments are not new, yet in some circles the generalizability question is beyond dispute, rendering empirical work as a passive enterprise based on frivolity. Such arguments serve to caution even the staunchest empirical advocates from even starting an empirical inquiry in a novel setting. In its simplest form, questions of external validity revolve around whether the results of the received study can be generalized to different people, situations, stimuli, and time periods. This study clarifies and places the external validity crisis into perspective by taking a unique glimpse into the grandest of trials: The External Validity Trial. A key outcome of the proceedings is an Author Onus Probandi, which outlines four key areas that every study should report to address external validity. Such an evaluative approach properly rewards empirical advances and justly recognizes inherent empirical limitations.

Bharat Chandar, Uri Gneezy, John A List, Ian Muir

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Even though social preferences affect nearly every facet of life, there exist many open questions on the economics of social preferences in markets. We leverage a unique opportunity to generate a large data set to inform the who's, what's, where's, and when's of social preferences through the lens of a nationwide tipping field experiment on the Uber platform. Our field experiment generates data from more than 40 million trips, allowing an exploration of social preferences in the ride sharing market using bid data. Combining experimental and natural variation in the data, we are able to establish tipping facts as well as provide insights into the underlying motives for tipping. Interestingly, even though tips are made privately, and without external social benefits or pressure, more than 15% of trips are tipped. Yet, nearly 60% of people never tip, and only 1% of people always tip. Overall, the demand-side explains much more of the observed tipping variation than the supply-side.

Bharat Chandar, Ali Hortacsu, John A List, Ian Muir, Jeffrey M Wooldridge

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Field experiments conducted with the village, city, state, region, or even country as the unit of randomization are becoming commonplace in the social sciences. While convenient, subsequent data analysis may be complicated by the constraint on the number of clusters in treatment and control. Through a battery of Monte Carlo simulations, we examine best practices for estimating unit-level treatment effects in cluster-randomized field experiments, particularly in settings that generate short panel data. In most settings we consider, unit-level estimation with unit fixed effects and cluster-level estimation weighted by the number of units per cluster tend to be robust to potentially problematic features in the data while giving greater statistical power. Using insights from our analysis, we evaluate the effect of a unique field experiment: a nationwide tipping field experiment across markets on the Uber app. Beyond the import of showing how tipping affects aggregate outcomes, we provide several insights on aspects of generating and analyzing cluster-randomized experimental data when there are constraints on the number of experimental units in treatment and control.

John A List

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Last year I put together a summary of data from my field experiments website that pertained to natural field experiments. Several people have asked me if I have an update. In this document I update all figures and numbers to show the details for 2020. I also include the description from the 2019 paper below.

Basil Halperin, Benjamin Ho, John A List, Ian Muir

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We use a theory of apologies to analyze a nationwide field experiment involving 1.5 million Uber ridesharing consumers who experienced late rides. Several insights emerge. First, apologies are not a panacea: the efficacy of an apology and whether it may backfire depend on how the apology is made. Second, across treatments, money speaks louder than words - the best form of apology is to include a coupon for a future trip. Third, in some cases sending an apology is worse than sending nothing at all, particularly for repeated apologies. For firms, caveat venditor should be the rule when considering apologies.

Avner Ben-Ner, John A List, Louis Putterman, Anya Samek

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An active area of research within the social sciences concerns the underlying motivation for sharing resources and engaging in other pro-social actions. In this paper we ask: do parents model social preference behavior to children, and do children emulate this behavior? We develop a theoretical framework to examine this question, and conduct an experiment with 147 3 to 5 year old children and their parents, using dictator games to measure generosity. We find (1) evidence of parental teaching/modeling in the case of fathers and in that of parents of relatively generous children, and (2) an emulation effect such that children who initially share less than half of their endowment subsequently share more the more they see a parent or other adult share. We find little correlation between baseline sharing of children and the parents, with the possible exception of the oldest children.

Omar Al-Ubaydli, John A List

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Natural field experiments investigating key labour market phenomena such as unemployment have only been used since the early 2000s. This paper reviews the literature and draws three primary conclusions that deepen our understanding of unemployment. First, the inability to monitor workers perfectly in many occupations complicates the hiring decision in a way that contributes to unemployment. Second, the inability to determine a worker's attributes precisely at the time of hiring leads to discrimination on the basis of factors such as race, gender, age and ethnicity. This can lead to systematically high and persistent levels of unemployment for groups that face discrimination. Third, the importance of social and personal dynamics in the workplace can lead to short-term unemployment. Much of the knowledge necessary for these conclusions could only be obtained using natural field experiments due to their ability to combine randomized control with an absence of experimenter demand effects.

Eszter Czibor, David Jimenez-Gomez, John A List

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What was once broadly viewed as an impossibility - learning from experimental data in economics - has now become commonplace. Governmental bodies, think tanks, and corporations around the world employ teams of experimental researchers to answer their most pressing questions. For their part, in the past two decades academics have begun to more actively partner with organizations to generate data via field experimentation. While this revolution in evidence-based approaches has served to deepen the economic science, recently a credibility crisis has caused even the most ardent experimental proponents to pause. This study takes a step back from the burgeoning experimental literature and introduces 12 actions that might help to alleviate this credibility crisis and raise experimental economics to an even higher level. In this way, we view our "12 action wish list" as discussion points to enrich the field.

Lenka Fiala, John Eric Humphries, Juanna S Joensen, Uditi Karna, John A List, Gregory Veramendi

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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.