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John A List, Sally Sadoff, Mathis Wagner

Cited by*: 2 Downloads*: 33

Experimental economics represents a strong growth industry. In the past several decades the method has expanded beyond intellectual curiosity, now meriting consideration alongside the other more traditional empirical approaches used in economics. Accompanying this growth is an influx of new experimenters who are in need of straightforward direction to make their designs more powerful. This study provides several simple rules of thumb that researchers can apply to improve the efficiency of their experimental designs. We buttress these points by including empirical examples from the literature.

Jonathan E Alevy, Michael S Haigh, John A List

Cited by*: 21 Downloads*: 24

Previous empirical studies of information cascades use either naturally occurring data or laboratory experiments with student subjects. We combine attractive elements from each of these lines of research by observing market professionals from the Chicago Board of Trade (CBOT) in a controlled environment. As a baseline, we compare their behavior to student choices in similar treatments. We further examine whether, and to what extent, cascade formation is influenced by both private signal strength and the quality of previous public signals, as well as decision heuristics that differ from Bayesian rationality. Analysis of over 1,500 individual decisions suggests that CBOT professionals are better able to discern the quality of public signals than their student counterparts. This leads to much different cascade formation. Further, while the behavior of students is consistent with the notion that losses loom larger than gains, market professionals are unaffected by the domain of earnings. These results are important in both a positive and normative sense.

Glenn W Harrison, John A List, Charles Towe

Cited by*: 1 Downloads*: 29

Does individual behavior in a laboratory setting provide a reliable indicator of behavior in a naturally occurring setting? We consider this general methodological question in the context of eliciting risk attitudes. The controls that are typically employed in laboratory settings, such as the use of abstract lotteries, could lead subjects to employ behavioral rules that differ from the ones they employ in the field. Because it is field behavior that we are interested in understanding, those controls might be a confound in themselves if they result in differences in behavior. We find that the use of artificial monetary prizes provides a reliable measure of risk attitudes when the natural counterpart outcome has minimal uncertainty, but that it can provide an unreliable measure when the natural counterpart outcome has background risk. Behavior tended to be moderately risk averse when artificial monetary prizes were used or when there was minimal uncertainty in the natural nonmonetary outcome, but subjects drawn from the same population were much more risk averse when their attitudes were elicited using the natural nonmonetary outcome that had some background risk. These results are consistent with conventional expected utility theory for the effects of background risk on attitudes to risk.

John A List, Paramita Sinha, Michael H Taylor

Cited by*: 33 Downloads*: 116

Critics of stated preference methods argue that hypothetical bias precludes survey techniques from providing reliable economic values for non-market goods and services, rendering estimation of the total economic benefits of public programs fruitless. This paper explores a relatively new methodology to obtain the total value of non-market goods and services-choice experiments-which conveniently provide information on the purchase decision as well as the characteristic value vector. The empirical work revolves around examining behavior in two very different field settings. In the first field study, we explore hypothetical bias in the purchase decision by eliciting contributions for a threshold public good in an actual capital campaign. To extend the analysis a level deeper, in a second field experiment we examine both the purchase decision and the marginal value vector via inspection of consumption decisions in an actual marketplace. In support of the new valuation design, both field experiments provide some evidence that hypothetical choice experiments combined with ""cheap talk"" can yield credible estimates of the purchase decision. Furthermore, we find no evidence of hypothetical bias when estimating marginal attribute values. Yet, we do find that the ""cheap talk"" component might induce internal inconsistency of subjects' preferences in the choice experiment.

Steffen Andersen, Alec Brandon, Uri Gneezy, John A List

Cited by*: 6 Downloads*: 51

Perhaps the most powerful form of framing arises through reference dependence, wherein choices are made recognizing the starting point or a goal. In labor economics, for example, a form of reference dependence, income targeting, has been argued to represent a serious challenge to traditional economic models. We design a field experiment linked tightly to three popular economic models of labor supply-two behavioral variants and one simple neoclassical model--to deepen our understanding of the positive implications of our major theories. Consistent with neoclassical theory and reference--dependent preferences with endogenous reference points, workers (vendors in open air markets) supply more hours when presented with an expected transitory increase in hourly wages. In contrast with the prediction of behavioral models, however, when vendors earn an unexpected windfall early in the day, their labor supply does not respond. A key feature of our market in terms of parsing the theories is that vendors do not post prices rather they haggle with customers. In this way, our data also speak to the possibility of reference-dependent preferences over other dimensions. Our investigation again yields results that are in line with neoclassical theory, as bargaining patterns are unaffected by the unexpected windfall.

Uri Gneezy, Andreas Leibbrandt, John A List

Cited by*: 1 Downloads*: 9

The functioning and well-being of any society and organization critically hinges on norms of cooperation that regulate social activities. Empirical evidence on how such norms emerge and in which environments they thrive remains a clear void in the literature. To provide an initial set of insights, we overlay a set of field experiments in a natural setting. Our approach is to compare behavior in Brazilian fishermen societies that differ along one major dimension: the workplace organization. In one society (located by the sea) fishermen are forced to work in groups whereas in the adjacent society (located on a lake) fishing is inherently an individual activity. We report sharp evidence that the sea fishermen trust and cooperate more and have greater ability to coordinate group actions than their lake fishermen counterparts. These findings are consistent with the argument that people internalize social norms that emerge from specific needs and support the idea that socio-ecological factors play a decisive role in the proliferation of pro-social behaviors.

Daniel Houser, John A List, Anya Samek

Cited by*: 0 Downloads*: 32

Young children have long been known to act selfishly and gradually appear to become more generous across middle childhood. While this apparent change has been well documented, the underlying mechanisms supporting this remain unclear. The current study examined the role of early theory of mind and executive functioning in facilitating sharing in a large sample (N = 98) of preschoolers. Results reveal a curious relation between early false-belief understanding and sharing behavior. Contrary to many commonsense notions and predominant theories, competence in this ability is actually related to less sharing. Thus, the relation between developing theory of mind and sharing may not be as straightforward as it seems in preschool age children. It is precisely the children who can engage in theory of mind that decide to share less with others.

Jeffrey A Flory, Andreas Leibbrandt, John A List

Cited by*: 12 Downloads*: 3

Recently an important line of research using laboratory experiments has provided a new potential reason for why we observe gender imbalances in labor markets: men are more competitively inclined than women. Whether, and to what extent, such preferences yield differences in naturally-occurring labor market outcomes remains an open issue. We address this question by exploring job-entry decisions in a natural field experiment where we randomized nearly 7,000 interested job-seekers into different compensation regimes. By varying the role that individual competition plays in setting the wage, we are able to explore whether competition, by itself, can cause differential job entry. The data highlight the power of the compensation regime in that women disproportionately shy away from competitive work settings. Yet, there are important factors that attenuate the gender differences, including whether the job is performed in teams, whether the job task is female-oriented, and the local labor market.

Erwin Bulte, John A List, Qin Tu

Cited by*: 0 Downloads*: 32

A vibrant literature has emerged that explores the economic implications of the sex ratio (the ratio of men to women in the population), including changes in fertility rates, educational outcomes, labor supply, and household purchases. Previous empirical efforts, however, have paid less attention to the underlying channel via which changes in the sex ratio affect economic decisions. This study combines evidence from a field experiment and a survey to document that the sex ratio importantly influences female bargaining power: as the sex ratio increases, female bargaining power increases.

Erwin Bulte, John A List, Mark Strazicich

Cited by*: 17 Downloads*: 2

Recent empirical work suggests that (i) incomes are converging through time, and (ii) income and pollution levels are linked. This paper weds these two literatures by examining the spatial and temporal distribution of pollution. After establishing that theoretical predictions about whether pollution will converge are critically linked to certain structural parameters, we explore pollution convergence using state-level data on two important pollutants-nitrogen oxides and sulfur oxides-from 1929 to 1999. We find stronger evidence of converging emission rates during the federal pollution control years (1970-1999) than during the local control years (1929-1969). These results suggest that income convergence alone may not be sufficient to induce convergence of pollutant emissions.

Tim Jeppesen, John A List, Daan van Soest

Cited by*: 5 Downloads*: 6

Empirical tests of the relationship between international competitiveness and the severity of environmental regulations are hampered by the lack of pollution abatement cost data for non-U.S. countries. The theory of the firm suggests that environmental stringency can be measured by the difference between a polluting input's shadow price and its market price. We make a first attempt at quantifying such a measure for two industries located in nine European OECD countries. Overall, we provide (i) a new approach to measure cross-country regulatory differences in that we use a theoretically attractive measure of industry-specific private compliance cost, and (ii) empirical estimates that are an attractive tool for researchers and policymakers who are interested in examining how economic activity is influenced by compliance costs.

Junsoo Lee, John A List, Mark Strazicich

Cited by*: 0 Downloads*: 2

In this paper we examine temporal properties of eleven natural resource real price series from 1870-1990 by employing a Lagrangian Multiplier unit root test that allows for two endogenously determined structural breaks with and without a quadratic trend. Contrary to previous research, we find evidence against the unit root hypothesis for all price series. Our findings support characterizing natural resource prices as stationary around deterministic trends with structural breaks. This result is important in both a positive and normative sense. For example, without an appropriate understanding of the dynamics of a time series, empirical verification of theories, forecasting, and proper inference are potentially fruitless. More generally, we show that both pre-testing for unit roots with breaks and allowing for breaks in the forecast model can improve forecast accuracy.

Erwin Bulte, Simon Levin , John A List, Steven Pacala

Cited by*: 1 Downloads*: 2

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Peggy Dwyer , James Gilkeson , John A List

Cited by*: 46 Downloads*: 15

Using data from a national survey of nearly 2000 mutual fund investors, we investigate whether investor gender is related to risk taking as revealed in mutual fund investment decisions. Consonant with the received literature, we find that women exhibit less risk-taking than men in their most recent, largest, and riskiest mutual fund investment decisions. More importantly, we find that the impact of gender on risk taking is significantly weakened when investor knowledge of financial markets and investments is controlled in the regression equation. This result suggests that the greater level of risk aversion among women that is frequently documented in the literature can be substantially, but not completely, explained by knowledge disparities.

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.

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.

John A List, Ian Muir, Devin Pope, Gregory Sun

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Left-digit bias (or 99-cent pricing) has been discussed extensively in economics, psychology, and marketing. Despite this, we show that the rideshare company, Lyft, was not using a 99-cent pricing strategy prior to our study. Based on observational data from over 600 million Lyft sessions followed by a field experiment conducted with 21 million Lyft passengers, we provide evidence of large discontinuities in demand at dollar values. Approximately half of the downward slope of the demand curve occurs discontinuously as the price of a ride drops below a dollar value (e.g. $14.00 to $13.99). If our short run estimates persist in the longer run, we calculate that Lyft could increase its profits by roughly $160M per year by employing a left-digit bias pricing strategy. Our results showcase the robustness of an important behavioral bias for a large, modern company and its persistence in a highly-competitive market.

Gary Charness, Brian Jabarian, John A List

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We investigate the potential for Large Language Models (LLMs) to enhance scientific practice within experimentation by identifying key areas, directions, and implications. First, we discuss how these models can improve experimental design, including improving the elicitation wording, coding experiments, and producing documentation. Second, we discuss the implementation of experiments using LLMs, focusing on enhancing causal inference by creating consistent experiences, improving comprehension of instructions, and monitoring participant engagement in real time. Third, we highlight how LLMs can help analyze experimental data, including pre-processing, data cleaning, and other analytical tasks while helping reviewers and replicators investigate studies. Each of these tasks improves the probability of reporting accurate findings. Finally, we recommend a scientific governance blueprint that manages the potential risks of using LLMs for experimental research while promoting their benefits. This could pave the way for open science opportunities and foster a culture of policy and industry experimentation at scale.

John A List, Lina Ramirez, Julia Seither, Jaime Unda, Beatriz Vallejo

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Misinformation represents a vital threat to the societal fabric of modern economies. While the supply side of the misinformation market has begun to receive increased scrutiny, the demand side has received scant attention. We explore the demand for misinformation through the lens of augmenting critical thinking skills in a field experiment during the 2022 Presidential election in Colombia. Data from roughly 2.000 individual suggest that our treatments enhance critical thinking, causing subjects to more carefully consider the truthfulness of potential misinformation. We furthermore provide evidence that reducing the demand of fake news can deliver on the dual goal of reducing the spread of fake news by encouraging reporting of misinformation.