Papers - John A List

Uri Gneezy, Kenneth Leonard, John A List

Cited by*: 243 Downloads*: 41

This study uses a controlled experiment to explore whether there are gender differences in selecting into competitive environments across two distinct societies: the Maasai in Tanzania and the Khasi in India. One unique aspect of these societies is that the Maasai represent a textbook example of a patriarchal society whereas the Khasi are matrilineal. Similar to the extant evidence drawn from experiments executed in Western cultures, Maasai men opt to compete at roughly twice the rate as Maasai women. Interestingly, this result is reversed amongst the Khasi, where women choose the competitive environment more often than Khasi men, and even choose to compete weakly more often than Maasai men. We view these results as potentially providing insights into the underpinnings of the factors hypothesized to be determinants of the observed gender differences in selecting into competitive environments.

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.

Gary Charness, Brian Jabarian, John A List

Cited by*: None Downloads*: None

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.

Chien-Yu Lai, John A List, Anya Samek

Cited by*: None Downloads*: None

The National School Lunch Program (NSLP) is a federal food assistance program that serves over 30 million children in the United States annually. Yet the impact of NSLP on nutritional intake may be limited because children frequently do not choose the healthier offerings or waste large portions of their meal. In this article, we study whether we can improve the impact of the NSLP on child food choice through low-cost nudges. We conduct a field experiment in a school lunchroom with 2500 children, evaluating the impact of informational prompts on milk choice and consumption over two weeks. We find that the prompts alone increase the proportion of children choosing and consuming the healthier white milk relative to sugar-sweetened chocolate milk from 20% in the control group to 30% in the treatment groups. Adding health or taste messaging to the prompt does not seem to make a difference. We survey students and find that most prompts affect perceived healthfulness of the milk, but not perceived taste. Finally, we find that the prompts are nearly as effective as a small nonmonetary incentive.

John A List, Anya Samek, Michael K Price

Cited by*: 0 Downloads*: 2

No abstract available

Iwan Barankay, Magnus Johannesson, John A List, Richard Friberg, Matti Liski, Kjetil Storesletten

Cited by*: 1 Downloads*: 1

No abstract available

John A List, Robert D Metcalfe, Michael K Price, Florian Rundhammer

Cited by*: 0 Downloads*: 51

The literature has shown the power of social norms to promote residential energy conservation, particularly among high usage users. This study uses a natural field experiment with nearly 200,000 US households to explore whether a financial rewards program can complement such approaches. We observe strong impacts of financial rewards, particularly amongst low-usage and low-variance households, customers who typically are less responsive to normative messaging. Our data thus suggest important policy complementarities between behavioral and financial incentives: whereas non-pecuniary interventions disproportionally affect intense users, financial incentives are able to affect substantially low-user, "sticky households."

John A List

Cited by*: 12 Downloads*: 4

Previous studies of income distribution have found evidence indicating that incomes across U.S. regions have converged, supporting the prediction of the neoclassical growth model. A potential shortcoming in these studies is that only one measure of well-being is considered a measure of wealth linked to incomes or production. This paper examines whether income convergence was accompanied by air pollutant emission convergence. Results from unit root tests provide some evidence that indicators of environmental quality have converged across U.S. regions during the 1929-1994 period.

Pradhi Aggarwal, Alec Brandon, Ariel Goldszmidt, Justin Holz, John A List, Ian Muir, Gregory Sun, Thomas Yu

Cited by*: None Downloads*: None

Prior research finds that, conditional on an encounter, minority civilians are more likely to be punished by police than white civilians. An open question is whether the actual encounter is related to race. Using high-frequency location data of rideshare drivers operating on the Lyft platform in Florida, we estimate the effect of driver race on traffic stops and fines for speeding. Estimates obtained across traditional and machine learning approaches show that, relative to a white driver traveling the same speed, minorities are 24 to 33 percent more likely to be stopped for speeding and pay 23 to 34 percent more in fines. We find no evidence that these estimates can be explained by racial differences in accident and re-offense rates. Our study provides key insights into the total effect of civilian race on outcomes of interest and highlights the potential value of private sector data to help inform major social challenges.

Steven D Levitt, John A List

Cited by*: 38 Downloads*: 65

No abstract available

John A List

Cited by*: 4 Downloads*: 46

No abstract available

Vic Adamowicz, Jonathan E Alevy, John A List

Cited by*: 0 Downloads*: 10

Psychological insights have made inroads within most major areas of study in economics. One area where less advance has been made is environmental and resource economics. In this study, we examine the implications of preference reversals over evaluation modes, in which stated economic values critically depend on whether the good is valued jointly with others or in isolation. The question arises because two commonly used methods for eliciting stated preferences differ in that one presents objects together and another presents objects to be evaluated in isolation. Beyond showing an example of the import of behavioral economics, our empirical evidence sheds new light on the factors associated with insensitivity of valuations to the scope of the good

Dean S Karlan, John A List

Cited by*: 0 Downloads*: 29

We conducted two matching grant experiments with an international development charity. The primary experiment finds that a matching grant from the Bill and Melinda Gates Foundation raises more funds than a matching grant from an anonymous donor. The effect persists, and is strongest for donors who previously gave to other poverty-oriented charities. Combining these insights with survey results, we conclude that our matching gift primarily works through a quality signal mechanism. Overall, the results help to clarify why people give to charity, what models help to describe those motivations, and how practitioners can leverage economics to increase their fundraising potential.

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

Cited by*: None Downloads*: None

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.

John A List

Cited by*: None Downloads*: None

ASSA 2023 presentation

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

Cited by*: None Downloads*: None

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.

John A List, Daniel M Sturm

Cited by*: 3 Downloads*: 1

In this paper we explore to what extent secondary policy issues are influenced by electoral incentives. We develop a political agency model in which a politician decides on both a frontline policy issue, such as the level of public spending, and a secondary policy issue, such as environmental policy. The model shows under which conditions the incumbent finds it worthwhile to manipulate the secondary policy to attract additional votes to his platform. We test the predictions of the model using state-level panel data on Gubernatorial environmental policy choices over the years 1960-2000. In contrast to the popular view that choices on secondary policy instruments are largely determined by lobbying, we find strong effects of electoral incentives on environmental policy.

John A List, Ragan Petrie, Anya Samek

Cited by*: None Downloads*: None

In the past several decades the experimental method has lent deep insights into economics. One surprising area that has contributed is the experimental study of children, where advances as varied as the evolution of human behaviors that shape markets and institutions to how early life influences shape later life outcomes have been explored. We first develop a framework for economic preference measurement that provides a lens into how to interpret data from experiments with children. Next, we survey work that provides general empirical insights within our framework. Finally, we provide 10 tips for pulling off experiments with children, including factors such as taking into account child competencies, causal identification, and logistical issues related to recruitment and implementation. We envision the experimental study of children as a high growth research area in the coming decades as social scientists begin to more fully appreciate that children are active participants in markets who (might) respond predictably to economic incentives.

John A List

Cited by*: None Downloads*: None

This review summarizes results of field experiments examining individual behaviors across several market settings from - open-air markets to rideshare markets to tax-compliance markets - where people sort themselves into market roles wherein they make consequential decisions. Using three distinct examples from my own research on the endowment effect, left-digit bias, and omission bias, I showcase how field experiments can help researchers understand mediators, heterogeneity, and causal moderation involved in judgment biases in the field. In this manner, the review highlights that economic field experiments can serve an invaluable intellectual role alongside traditional laboratory research.

Omar Al-Ubaydli, John A List

Cited by*: None Downloads*: None

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.