John List

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 individuals 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.

Social scientists have increasingly turned to the experimental method to understand human behaviour. One critical issue that makes solving social problems difficult is scaling up the idea from a small group to a larger group in more diverse situations. The urgency of scaling policies impacts us every day, whether it is protecting the health and safety of a community or enhancing the opportunities of future generations. Yet, a common result is that, when we scale up ideas, most experience a ‘voltage drop’—that is, on scaling, the cost–benefit profile depreciates considerably. Here I argue that, to reduce voltage drops, we must optimally generate policy-based evidence. Optimality requires answering two crucial questions: what information should be generated and in what sequence. The economics underlying the science of scaling provides insights into these questions, which are in some cases at odds with …

In 2019 I put together a summary of data from my field experiments website that pertained to framed field experiments (see List 2024). Several people have asked me if I have an update. In this document I update all figures and numbers to show the details for 2023. I also include the description from the 2019 paper below.

In 2019, I put together a summary of data from my field experiments website that pertained to artefactual 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 the year 2023. I also include the description from the 2019 paper below. The definition of artefactual field experiments comes originally from Harrison and List (2004) and is advanced in List (2024).

Businesses, governments, and individuals have dealt with bringing ideas to scale, sometimes successfully, but all too often unsuccessfully. Scaling is at the core of my book The Voltage Effect (List, ) In both the book and this paper, I aim to elucidate what I have learned from using economics to understand the world. I begin this paper by discussing the meaning of the NABE Adam Smith Award. The rest of the papertalk proceeds first by describing the origins of my work on scaling and The Voltage Effect. Scaling has long been considered an art, but there was clearly a need for a scientific understanding. Following the origins, is an overview of some of the key takeaways from The Voltage Effect (List, ): identifying ideas with the potential to scale and the tools to take ideas to scale.

A Course in Experimental Economics John A. List Page 1 A Course in Experimental Economics John A. List Page 2 IF YOU WANT TO CITE OR GIVE ATTRIBUTION TO THIS SLIDE DECK, PLEASE CITE THE FORTHCOMING BOOK: List, John A. “A Course in Experimental Economics,” University of Chicago Press, forthcoming. Page 3 Some Tips for “Start-Ups” to do Better Field Experiments and Getting Your Work Published JA List U. Chicago, ANU, & NBER Page 4 Some Tips for Doing Better Field Experiments and Getting Your Work Published Page 5 Some Tips for “Start-Ups” to do Better Field Experiments and Getting Your Work Published JA List U. Chicago, ANU, & NBER SR Goal: Induce you to go into your AFE slides and your working papers and make changes to improve the work LR Goal: Induce you to change the way you design, examine, interpret, and/or write-up your future studies Human Capital Goals: …

While behavioral non-price interventions (“nudges”) have grown from academic curiosity to a bona fide policy tool, their relative economic efficiency remains under-researched. We develop a unified framework to estimate welfare effects of both nudges and taxes. We showcase our approach by creating a database of more than 300 carefully hand-coded point estimates of nonprice and price interventions in the markets for cigarettes, influenza vaccinations, and household energy. While nudges are effective in changing behavior in all three markets, they are not necessarily the most efficient policy. We find that nudges are more efficient in the market for cigarettes, while taxes are more efficient in the energy market. For influenza vaccinations, optimal subsidies likely outperform nudges. Importantly, two key factors govern the difference in results across markets: i) an elasticity-weighted standard deviation of the behavioral bias, and ii) the magnitude of the average externality. Nudges dominate taxes whenever i) exceeds ii). Combining nudges and taxes does not always provide quantitatively significant improvements to implementing one policy tool alone.

In this paper, we provide a suite of tools for empirical market design, including optimal nonlinear pricing in intensive-margin consumer demand, as well as a broad class of related adverseselection models. Despite significant data limitations, we are able to derive informative bounds on demand under counterfactual price changes. These bounds arise because empirically plausible DGPs must respect the Law of Demand and the observed shift (s) in aggregate demand resulting from a known exogenous price change (s). These bounds facilitate robust policy prescriptions using rich, internal data sources similar to those available in many real-world applications. Our partial identification approach enables viable nonlinear pricing design while achieving robustness against worst-case deviations from baseline model assumptions. As a side benefit, our identification results also provide useful, novel insights into optimal experimental design for pricing RCTs.

This paper uses a natural field experiment to examine the effectiveness of deterrence messages on tax compliance in the Dominican Republic. In collaboration with the tax authority, we sent messages to 56,310 firms that collectively paid $700 million in the year before the experiment. Our field experiment complements a tax enforcement reform in the Dominican Republic a year before our intervention. Sharing information about prison sentences or the public disclosure of evasion arising from the tax enforcement reform increases tax revenue by $184 million (0.22% of GDP). Using a unique sample that covers the entire firm size distribution, we show that the largest firms, that pay 84% of all corporate income taxes and typically have been excluded from this type of intervention, are highly responsive to our information treatments.

Devices and methods for providing real-time feedback of conversational attributes are provided. An audio signal comprising speech is received. The audio signal is divided into a plurality of sequential windows. A plurality of features is extracted from each sequential window of the audio signal. Each plurality of features is sequentially provided to a trained classifier and a speech attribute of the corresponding window of the audio signal is received therefrom. After receiving each speech attribute, and based upon that speech attribute and speech attributes of prior windows, a conversational attribute is generated. A user-perceivable output indicative of the conversational attribute is provided.

In 2019, 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 2022. I also include the description from the 2019 paper below.

Our Best Chance to Make Real Change? Scalable Ideas with Private Partners Page 1 Our Best Chance to Make Real Change? Scalable Ideas with Private Partners John A. List @Econ_4_Everyone U. Chicago & NBER Page 2 Our Best Chance to Make Real Change? Scalable Ideas with Private Partners John A. List @Econ_4_Everyone U. Chicago & NBER A. Taking Flight: An Example of a Private Partnership B. Does that Idea Scale? What is the Science Behind that Claim? C. A Glimpse Behind the Curtain: A Little Can Go a Long Way With a Big Footprint Page 3 A. TAKING FLIGHT 3 Page 4 High-skilled workers at Virgin Atlantic Why did Virgin Atlantic care about this? Jet Fuel Cost Page 5 High-skilled workers at Virgin Atlantic Why did Virgin Atlantic care about this? Jet Fuel Cost Page 6 High-skilled workers at Virgin Atlantic Why did Virgin Atlantic care about this? Jet Fuel Cost Page 7 High-skilled workers at …

This paper provides a framework for testing multiple null hypotheses simultaneously using experimental data in which simple random sampling is used to assign treatment status to units. Using general results from the multiple testing literature, we develop under weak assumptions a procedure that (i) asymptotically controls the familywise error rate—the probability of one or more false rejections—and (ii) is asymptotically balanced in that the marginal probability of rejecting any true null hypothesis is approximately equal in large samples. Our procedure improves upon classical methods by incorporating information about the joint dependence structure of the test statistics when determining which null hypotheses to reject, leading to gains in power. An important point of departure from prior work is that we exploit observed, baseline covariates to obtain further gains in power. The precise way in which we incorporate …

In modern economies, when debt and trust issues arise, a partial forgiveness policy is often the solution to induce payment and increase disclosure. For their part, governments around the globe continue to use tax amnesties as a strategy to allow debtors to make amends for past misdeeds in exchange for partial debt forgiveness. While ubiquitous, much remains unknown about the basic facts of how well amnesties work, for whom, and why. We present a simple theoretical construct that provides both economic clarity into tax amnesties as well as insights into the necessary behavioral parameters that one must estimate to understand the consequences of tax amnesties. We partner with the Dominican Republic Tax Authorities to design a natural field experiment that is linked to the theory to estimate key causal mechanisms. Empirical results from our field experiment, which covers 125,452 taxpayers who collectively owe $5.2 billion (5.5% of GDP) in known debt, highlight the import of deterrence laws, beliefs about future amnesties, and tax morale for debt payment and increased disclosure. Importantly, we find large short run effects: our most effective treatment (deterrence) increased payments of known debt by 25% and hidden debt by 48%. Further, we find no evidence of our intervention backfiring on subsequent tax payments.

Uber’s experiment with five-dollar discount coupons with select passengers in Seattle appeared a win-win. The passengers rode more, the drivers made more, and the company profited. When Uber scaled this initiative, the results were the opposite. Demand scaled, outstripping supply. Scarcity caused resentment in overworked drivers. Wait times and prices increased, and then demand fell.Historically, economists such as David Ricardo and Karl Marx recognized labor’s value. Ricardo believed that labor should determine the price of goods, a calculation which became mathematically complex after the industrial revolution. Marx had other ideas for labor. Though labor and capital haven’t always seen eye-to-eye, there’s one distinction between them which Uber didn’t appreciate-humans don’t scale well. Scale–the geometric growth of ideas, institutions, businesses, policies–is often constrained by labor supply.

Have you ever noticed that some concepts seem outstanding initially but eventually fail? Many promising ideas have the potential to be expanded, but why are the outcomes not as expected? Consider the factors that distinguish successful expandable concepts from unsuccessful ones. This is what this book helps to accomplish.‘The Voltage Effect’by John A. List is a book written based on the several roles professor List has had in the past including a professor at the University of Chicago; consultant and chief economist at Uber and Lyft–both renowned companies; as well as his toles as advisor at a government agency. This book is divided into two parts: the first part (comprised of five chapters) delved into the factors that determine the extent to which a particular concept can be expanded; the second part (made of four chapters) covers specific matters that effectively discuss the process of dissemination of …

The “voltage effect” is defined as the tendency for a program’s efficacy to change when it is scaled up, which in most cases results in the absolute size of a program’s treatment effects to diminish when the program is scaled. Understanding the scaling problem and taking steps to diminish voltage drops are important because if left unaddressed, the scaling problem can weaken the public’s faith in science, and it can lead to a misallocation of public resources. There exists a growing literature illustrating the prevalence of the scaling problem, explaining its causes, and proposing countermeasures. This paper adds to the literature by providing a simple model of the scaling problem that is consistent with rational expectations by the key stakeholders. Our model highlights that asymmetric information is a key contributor to the voltage effect.

The fractal nature of giving to charitable causes in the U.S. suggests that the literature that focuses on modal donors potentially misses a key piece of the puzzle to understanding overall giving patterns. Using a natural field experiment with more than 5500 high-capacity donors, we make a small step in this direction by reporting suggestive evidence across several features of our data. For example, we find that “warm-list” donors are more likely to donate, that gift matching increases donations, and that the price of giving is directionally in line with the Law of Demand. Unlike typical small donors, donors on the warm list respond while those on the cold list do not, and often with a longer time lag, a phenomenon that could be explained through social norming.

This study explores the role of neighborhoods on human capital formation at an early age. We do so by estimating the spillover effects of an early childhood intervention on the educational attainment of a large sample of disadvantaged children in the United States. We document large spillover effects on the cognitive skills of children living near treated children, which amount to approximately 40\% of the direct treatment effects. Interestingly, these spillover effects are localized and decrease with the spatial distance to treated neighbors. We do not find evidence of spillover effects on non-cognitive skills. Perhaps our most novel insight is the underlying mechanisms at work: the spillover effect on cognitive scores is very localized and seems to operate through the child's social network, mostly between treated kids. We do not find evidence that parents' or children's social networks are effective for non-cognitive skills. Overall, our results reveal the importance of public programs and neighborhoods on human capital formation at an early age, highlighting that human capital accumulation is fundamentally a social activity.

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. 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.

Back in January of this year I provided some data on all field experiments that were published on a website that I started nearly 20 years ago. Back then, I was trying to provide a service in the spirit of what Charlie Holt did for laboratory experiments. Charlie’s site compelled me to create my own bibliographical site http://www. fieldexperiments. com, which lists publications and discussion papers in experimental economics that make use of the" field" in some manner. The site remains quite active, with an open source that allows scholars to post their own work, and to download hundreds of field experimental papers.In my own work I have reserved the term" field experiment" for those cases where I observed subjects in their naturally occurring environments (see, e, g., Czibor et al.(2019; List, 2002, 2004, 2006). I explicitly, therefore, discriminated between explorations in this environment and laboratory studies that used non-standard subject pools (see, eg, Andersen et al.(2018) or Cappelen et al.(2022)). In a JEL paper (Harrison and List, 2004), such important differences are accounted for via qualifiers.

EconPapers: How Can We Make Experimental Research Results More Reliable and Replicable? EconPapers Economics at your fingertips EconPapers Home About EconPapers Working Papers Journal Articles Books and Chapters Software Components Authors JEL codes New Economics Papers Advanced Search EconPapers FAQ Archive maintainers FAQ Cookies at EconPapers Format for printing The RePEc blog The RePEc plagiarism page How Can We Make Experimental Research Results More Reliable and Replicable? John List Artefactual Field Experiments from The Field Experiments Website Abstract: ASSA 2023 presentation Date: 2023 References: Add references at CitEc Citations: Track citations by RSS feed Downloads: (external link) http://s3.amazonaws.com/fieldexperiments-papers2/papers/00780.pdf Related works: This item may be available elsewhere in EconPapers: Search for items with the …

We conduct a field experiment across three diverse school districts to structurally identify student motivation and estimate productivity parameters in a model of adolescent human capital development. By observing exogenous variation in study time, homework task completion, and test results, we can identify individual and demographic variations in motivation and study time effectiveness. Struggling students typically do not lack motivation but rather have difficulties converting study time into completed assignments and proficiency improvements. The study also shows that attending a higher-performing school is associated with both higher productivity and higher motivation relative to peers with similar observables in lower-performing schools. Counterfactual analyses provide a suite of policies to reduce racial performance gaps and suggest that school quality differences account for a substantial share of the racial differences in test scores.

We found that minority drivers are 24–33 percent more likely to receive a speeding ticket when traveling at the same speed at the same time and in the same location as white drivers.

Whether, and to what extent, behavioral anomalies uncovered in the lab can extend to natural environments by explaining decision making in the field remains of first order importance in economics and finance. We explore this in the context of myopic loss aversion (MLA). We use artefactual field experiments to elicit the extent of MLA exhibited by retail investors in constructed laboratory markets and link it to a proprietary, individual-level dataset of their private investment accounts. We find that MLA is associated with lower equity market investment levels and lower market beta of portfolios. The MLA effect is stronger for investors who are less experienced, who update themselves frequently about the market and who make changes to their portfolio frequently. Additional evidence shows that MLA investors react negatively to short term losses in their portfolio, and their investments also perform more poorly in the stock market.

Recent theoretical work shows that the better-than-average effect, where a majority believes their ability to be better than average, can be perfectly consistent with Bayesian updating. However, later experiments that account for this theoretical advance still find behavior consistent with overconfidence. The literature notes that overoptimism can be caused by either overconfidence (optimism about performance), wishful thinking (optimism about outcomes), or both. To test whether the better-than-average effect might be explained by wishful thinking instead of overconfidence, we conduct an experiment that is similar to those used in the overconfidence literature, but removes performance as a potential channel. We find evidence that wishful thinking might explain overconfidence only among the most optimistic subjects and that conservatism is possibly more of a worry; if unaccounted for, overconfidence might be …

"Putting Economic Research into Practice at Businesses (to Inform Science and Major Social Challenges)" Slides from ASSA NABE

In the past several decades, the experimental method has lent deep insights into economics. One 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 and provide a comprehensive summary of experimental methods used with children. 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 …

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 preprocessing, data cleaning, and other analytical tasks while helping reviewers and replicators investigate studies. Each of these tasks improves the probability of reporting accurate findings.

I am pleased to present the inaugural issue of the Journal of Political Economy Microeconomics (JPE Micro). JPE Micro, which is published by the University of Chicago Press and is closely tied to the Journal of Political Economy (JPE), is intended to serve as a forum for high-quality theoretical and empirical research in microeconomics. More specifically, the journal strives to publish high-quality theoretical, empirical, and econometric research papers and replication studies that address issues of relevance to microeconomics. JPE Micro interprets microeconomics in the broadest possible sense, which means including issues related to how individuals, households, firms, and governments make choices and how those choices affect prices, the allocation of resources, and the well-being of people. JPE Micro welcomes submissions in all areas of microeconomics including, but not limited to, industrial organization and …

In this study, we first present a large natural field experiment that tested messages aimed at increasing tax compliance. We find that the main drivers of changes in compliance are messages describing the monitoring and enforcement behavior of the tax collector. A second natural field experiment built on the results of the first experiment to further investigate what kinds of costs resulting from tax collector oversight are salient to taxpayers. Specific time and cognitive incentives did not significantly increase payment rates, whereas stating non-specific costs of inaction did. Additional analyses suggest the increase in compliance is likely due to a'fill in the blank’effect in which taxpayers assume the consequence is a fine. Interestingly, specifically stating maximum fine or jailtime consequences have the largest effect in a laboratory setting but only if the consequences are interpreted as realistic. Overall, our study reinforces that tax authorities can use short messages to increase tax compliance; the estimated accelerated revenue from the two field studies amounts to£ 9.9 m.

NATIONAL BESTSELLER• A leading economist answers one of today’s trickiest questions: Why do some great ideas make it big while others fail to take off?“Brilliant, practical, and grounded in the very latest research, this is by far the best book I’ve ever read on the how and why of scaling.”—Angela Duckworth, CEO of Character Lab and New York Times bestselling author of Grit LONGLISTED FOR THE PORCHLIGHT BUSINESS BOOK AWARD “Scale” has become a favored buzzword in the startup world. But scale isn't just about accumulating more users or capturing more market share. It's about whether an idea that takes hold in a small group can do the same in a much larger one—whether you’re growing a small business, rolling out a diversity and inclusion program, or delivering billions of doses of a vaccine. Translating an idea into widespread impact, says University of Chicago economist John A. List, depends on one thing only: whether it can achieve “high voltage”—the ability to be replicated at scale. In The Voltage Effect, List explains that scalable ideas share a common set of attributes, while any number of attributes can doom an unscalable idea. Drawing on his original research, as well as fascinating examples from the realms of business, policymaking, education, and public health, he identifies five measurable vital signs that a scalable idea must possess, and offers proven strategies for avoiding voltage drops and engineering voltage gains. You’ll learn:• How celebrity chef Jamie Oliver expanded his restaurant empire by focusing on scalable “ingredients”(until it collapsed because talent doesn’t scale)• Why the failure to detect false …

Parental investments shape children's educational specializations. Using a longitudinal study, we find that parents invest more in daughters than sons at ages three through five. We find that early parental investment can explain persistently higher English scores for girls than boys four to six years later. However, there is no gender gap in math. Parental investments at ages three through five appear to contribute to girls' advantage in English but have little impact on math. Our results suggest that parental investments at early ages contributes to girls' comparative advantage in English.

We conduct experiments with 720 children ages 9–11 to evaluate the relationship of time and risk preferences with health. Children who are more patient report consuming fewer unhealthy calories and spending less time on sedentary activities such as video games. Children who are more risk seeking report engaging in more exercise and more screen time. However, time and risk preferences are not predictive of body mass index (BMI). Moreover, some of the negative health behaviors, such as screen time, are associated with lower – rather than higher – BMI.

In organizations, teams are ubiquitous. “Weakest Link” and “Best Shot” are incentive schemes that tie a group member’s compensation to the output of their group’s least and most productive member, respectively. In this paper, we test the impact of these incentive schemes by conducting two pilot RCTs (one in-person, one online), which included more than 250 graduate students in a graduate math class. Students were placed in study groups of three or four students, and then groups were randomized to either control, Weakest Link, or Best Shot incentives. We find evidence that such incentive approaches can affect test scores, both in-person and online.

We use a theory of apologies to design 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 and apologies that promise to do better. For firms, caveat venditor should be the rule when considering apologies.

Soon after I was dispatched to discuss the important work of John Siegfried and David Colander (2022), I asked 30 people to define critical thinking. I received 25 different answers. When I asked those same 30 people if critical thinking (CT) is important in life, I received 1 answer: YES! Using my own CT skills, I then reasoned that in the area of CT skill formation, we seem to agree that what we do not homogeneously define is nevertheless important in life. In this spirit, CT is akin to creativity, great intuition, and deep insights, meaningful characteristics of scholars that we might find difficult to define precisely, but we know them when we see them; and we very much appreciate them. In my own experiences in both the classroom and my travels, I have come to define the key aspects of CT as individual skills that facilitate logical and informed decisions. I have observed the import of such skills in nearly every walk of life …

We combine a field experiment with structural estimation to study skill formation during adolescence. We randomize adolescents from low-income communities to distinct low-cost classroom interventions for 10-11 weeks. We find that the interventions improve skills, particularly executive function skills. We estimate skill production functions separately for each treatment group to document the inter-relationship between skills and uncover underlying mechanisms driving treatment effects. Our interventions impact the technology of skill formation-ie, the way in which students produce future skills from initial skills and investments they make outside of school. Effective interventions make skills more malleable by increasing the marginal product of investments on skills. We find important heterogeneity in mechanisms by initial skills, and show how predicted program impacts on high school graduation depend on (i) the persistence of the change in technology,(ii) how early the program starts, and (iii) the relative importance of executive function and cognitive skills in determining high school graduation.

The goal of creating evidence-based programs is to scale them at sufficient breadth to support population-level improvements in critical outcomes. However, this promise is challenging to fulfill. One of the biggest issues for the field is the reduction in effect sizes seen when a program is taken to scale. This paper discusses an economic perspective that identifies the underlying incentives in the research process that lead to scale up problems and to deliver potential solutions to strengthen outcomes at scale. The principles of open science are well aligned with this goal. One prevention program that has begun to scale across the USA is early childhood home visiting. While there is substantial impact research on home visiting, overall average effect size is .10 and a recent national randomized trial found attenuated effect sizes in programs implemented under real-world conditions. The paper concludes with a …

In a field experiment, we provide financial incentives to teachers framed either as gains, received at the end of the year, or as losses, in which teachers receive up-front bonuses that must be paid back if their students do not improve sufficiently. Pooling two waves of the experiment, loss-framed incentives improve math achievement by an estimated 0.124 standard deviations (σ), with large effects in the first wave and no effects in the second wave. Effects for gain-framed incentives are smaller and not statistically significant, approximately 0.051σ. We find suggestive evidence that the effects on teacher value added persist posttreatment. (JEL C93, I21, I28, J32, J45)

Recent models and empirical work on network formation emphasize the importance of propinquity in producing strong interpersonal connections. Yet, one might wonder how deep such insights run, as thus far empirical results rely on survey and lab-based evidence. In this study, we examine propinquity in a high-stakes setting of talent allocation: the Major League Baseball (MLB) Draft from 2000-2019 (30,000 players were drafted from a player pool of more than a million potential draftees). Our findings can be summarized in four parts. First, propinquity is alive and well in our setting, and spans even the latter years of our sample, when higher-level statistical exercises have become the norm rather than the exception. Second, the measured effect size is consequential, as MLB clubs pay a significant opportunity cost in terms of inferior talent acquired due to propinquity bias: for example, their draft picks are 38% less likely to ever play a MLB game relative to players drafted without propinquity bias. Third, those players who benefit from propinquity bias fare better both in terms of the timing of their draft picks and their initial financial contract, conditional on draft order. Finally, the effect is found to be the most pronounced in later rounds of the draft, where the Scouting Director has the greatest latitude.

This paper uses a field experiment and structural model to estimate the eff ects of prices and social norms on the decision to adopt a new household technology. Reduced form estimates show that while prices aff ect behavior along both the extensive and intensive margins, social norms only impact the extensive margin decision. Structural estimates uncover a negative correlation between behavioral parameters of our model: curiosity and social pressure. This points to important heterogeneity in the welfare eff ects of our intervention: whereas some consumers are “curious” and welcome the opportunity to learn about and purchase the new technology, others have no interest in learning about the technology and are made worse o↵ by the social pressure of the ask. Policy simulations highlight a complementary relationship between psychological and economic instruments; the subsidy required to achieve any level of adoption is lower when combined with the provision of normative statements.

In 2019, I put together a summary of data from my field experiments website that pertained to artefactual 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 2021. I also include the description from the 2019 paper below.

In 2019 I put together a summary of data from my field experiments website that pertained to framed 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 2021. I also include the description from the 2019 paper below.

GEOGRAPHY MARCH 2019 Page 1 SY 37 1 PTO Reg. No. : ..................................... SY 37 Name : ......................................... Time : 2 Hours Cool-off time : 15 Minutes Part – III GEOGRAPHY Maximum : 60 Scores (Map Accompanied) General Instructions to Candidates : • There is a ‘Cool-off time’ of 15 minutes in addition to the writing time. • Use the ‘Cool-off time’ to get familiar with questions and to plan your answers. • Read questions carefully before answering. • Read the instructions carefully. • Calculations, figures and graphs should be shown in the answer sheet itself. • Malayalam version of the questions is also provided. • Give equations wherever necessary. • Electronic devices except non-programmable calculators are not allowed in the Examination Hall.   •    15  ‘  ’ . • ‘  ’ …

This study investigates how to use regression adjustment to reduce variance in experimental data. We show that the estimators recommended in the literature satisfy an orthogonality property with respect to the parameters of the adjustment. This observation greatly simplifies the derivation of the asymptotic variance of these estimators and allows us to solve for the efficient regression adjustment in a large class of adjustments. Our efficiency results generalize a number of previous results known in the literature. We then discuss how this efficient regression adjustment can be feasibly implemented. We show the practical relevance of our theory in two ways. First, we use our efficiency results to improve common practices currently employed in field experiments. Second, we show how our theory allows researchers to robustly incorporate machine learning techniques into their experimental estimators to minimize variance.

These are the slides from John A. List's keynote at the 2022 AFE conference.

We design three field experiments to estimate how workers' social preferences toward their employer motivates their work effort. We vary the pay rates offered to workers, the return to the employer, and employer generosity demonstrated via unexpected gifts. Workers exert effort even without private incentives, but their effort is insensitive to the return to the employer. This is consistent with “warm glow” but not pure altruism. The gifts have no effect on productivity, but engender extra work. This difference is explained partly by the finding that extra work is much more responsive to incentives than is productivity. (JEL C93, J24, J28, J33, M52)

In-person tutoring programs can have large impacts on K-12 student achievement, but high program costs and limited local supply of tutors have hampered scale-up. Online tutoring provided by volunteers can potentially reach more students in need. We implemented a randomized pilot program of online tutoring that paired college volunteers with middle school students. We estimate consistently positive but statistically insignificant effects on student achievement, 0.07 standard deviations for math and 0.04 standard deviations for reading. While our estimated effects are smaller than those for many higher-dosage in-person programs, they are from a significantly lower-cost program delivered within the challenging context of the COVID-19 pandemic.

Perché alcune grandi idee si realizzano mentre altre non riescono a decollare? Se non esiste un modo per prevedere con assoluta certezza che un’idea avrà successo, la storia recente ha dimostrato che alla base di ogni progresso sociale e tecnologico c’è sempre il concetto di «scalabilità»: che si tratti di una scoperta in ambito medico, di un programma politico o di un’innovazione tecnologica, un progetto deve poter crescere ed essere replicabile in maniera sostenibile su larga scala. Tradurre un’idea in un successo dipende quindi sostanzialmente dal fatto che tale idea sia in grado di garantire un «alto voltaggio», la possibilità cioè di essere replicabile con la giusta energia e in diversi luoghi. Dalla contaminazione tra le teorie della behavioral economics e la sua lunga esperienza sul campo come consulente di società internazionali, List mette a punto una vera e propria scienza dello scaling e, analizzando vari casi del mondo del business, della politica, della scuola o della salute pubblica, ne identifica i fattori chiave.

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 approach provides key insights into the total effect of civilian race on outcomes of interest and highlights the methodological import of combining high-frequency data and machine learning to evaluate critical social issues.∗ Researchers Alec Brandon and Justin Holz, with support from the Lyft economics team, which was run by John List and included Pradhi Aggarwal, Ariel Goldszmidt, Ian Muir, Gregory Sun, and Thomas Yu, directed the empirical analyses in this paper. All analyses conducted by the economics team were solely for purposes of this paper and the results were shared with the researchers to form the basis of the conclusions discussed herein. These conclusions are those of the authors in their individual capacities and any errors are their own.

The president laid out his plan for easing the financial strain on middle-and working-class people who want to give their children the best possible future. One of the levers Biden hopes to pull is to make pre-k for three-and four-year-olds free. As the co-directors of the University of Chicago’s Center for Early Learning+ Public Health, we applaud him. But to make this plan and others like it a success, he’ll need more than just political dexterity to push policies through the House and Senate. He’ll need the latest science on how to scale government programs.To many Americans, free pre-k might seem like a no-brainer policy for a country with so many overworked, underpaid parents. But critics point out that the benefits of similar initiatives in the past have not always been evenly distributed demographically. In a few prior cases, some children showed more developmental gains than others; one such pre-k program in …

In this study, we first present a large field experiment to investigate the nature of costs resulting from tax collector oversight that are salient to taxpayers. Messages pertaining to specific time and cognitive incentives do not significantly increase payment rates, whereas stating non-specific costs of inaction does. Further analysis suggests the increase in compliance is likely due to rational taxpayers' filling in the blank’-an effect in which taxpayers likely assume the consequence is an average-sized fine when subject to uncertain enforcement actions. Specifically stating maximum fine or jailtime consequences have the largest effect in a laboratory setting but only if the consequences are interpreted as realistic. Overall, our study reinforces that tax authorities can use short messages to increase tax compliance. Moreover, our results may be useful to regulators that cannot commit to punishments ex-ante as our study shows tax messages need not necessarily be detailed and specific; the estimated accelerated revenue from the field study amounts to£ 5.16 m.

Leveraging data from Sweden and Chicago, we study the educational pipeline for science, technology, engineering, and mathematics (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.

Smart-home technologies have been heralded as an important way to increase energy conservation. While in vitro engineering estimates provide broad optimism, little has been done to explore whether such estimates scale beyond the lab. We estimate the causal impact of smart thermostats on energy use via two novel framed field experiments in which a random subset of treated households have a smart thermostat installed in their home. Examining 18 months of associated high-frequency data on household energy consumption, yielding more than 16 million hourly electricity and daily natural gas observations, we find little evidence that smart thermostats have a statistically or economically significant effect on energy use. We explore potential mechanisms using almost four million observations of system events including human interactions with their smart thermostat. Results indicate that user behavior dampens energy savings and explains the discrepancy between estimates from engineering models, which assume a perfectly compliant subject, and actual households, who are occupied by users acting in accord with behavioral economists’ conjectures. In this manner, our data document a keen threat to the scalability of new user-based technologies.

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 approach provides key insights into the total effect of civilian race on outcomes of interest and highlights the methodological import of combining high-frequency data and machine learning to evaluate critical social issues.

Socioeconomic gaps in child development open up early, with associated disparities in parental investments in children. Understanding the drivers of these disparities is key to designing effective policies. We first show that parental beliefs about the impact of early parental investments differ across socioeconomic status (SES), with parents of higher SES being more likely to believe that parental investments impact child development. We then use two randomized controlled trials to explore the mutability of such beliefs and their link to parental investments and child development, our three primary outcomes. In the first trial (NCT02812017 on clinicaltrials.gov), parents in the treatment group were asked to watch a short educational video during four well-child visits with their pediatrician while in the second trial (NCT03076268), parents in the treatment group received twelve home visits with feedback based on their …

In 2019, I put together a summary of data from my field experiments website that pertained to artefactual 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 2021. I also include the description from the 2019 paper below.

Evidence-based policy making has become the poster child of any politician—who wouldn’t want to claim that they are making their decisions based on the analysis of data? In this way, the one feature of political decision making that certainly should span the political aisle is evidence-based policy. Yet, what “evi dence-based” means is left to the imagination. In the US, the meaning began to take form in the early 2000s when the George W. Bush administration pushed for empirical research to have a greater impact on policy making. What resulted was a quiet new crusade called implementation science (see, eg, Cheng et al., 2017; Gottfredson et al., 2015; Kilbourne et al., 2007; Supplee & Metz, 2015; Supplee & Meyer, 2015). Its mandate is very simple: to evaluate the performance of programs when they are scaled up in the real world. This is where our work enters. In a series of studies motivated by digging into the …

Whether, and to what extent, behavioral anomalies uncovered in the lab manifest themselves in the field remains of first order importance in finance and economics. We begin by examining behavior of retail traders/investors making investment decisions in constructed laboratory markets. Our results show that the behaviors of the traders are consistent with myopic loss aversion. We combine the lab results with a unique individual-level matched dataset on daily stock market transactions and portfolio positions over a two year period. We find that lab behaviors help to predict, but do not fully capture, the essential real-world trading analogs of retail traders.

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.

We thank the responders for their thoughtful and quite constructive reactions to our manuscript. Their insights and comments are incredibly useful since they span broad disciplines that have each lent insights into the scalability of public policies and the importance of the scale-up effect. In particular, we believe that their complementing thoughts can aid the special issue readers to synthesize the

In recent years, citizens and law makers have become increasingly enthusiastic about adopting evidence-based policies and programs. Social scientists have delivered evidence of countless interventions that positively impact people’s lives. And yet, most programs, when expanded, have not delivered the dra matic societal impacts promised.This is especially true in the field of early childhood. Research suggests that high-quality early childhood programs (those serving children from birth through age 5) have the potential to reduce the inequities that plague our nation and rob too many children of opportunity—and that they can deliver a 13% return on investment in the process. Despite the research and evidence, however, few programs have followed through and delivered on this promise. In order to reap the individual and economic benefits of early childhood programs, researchers and practitioners must figure …

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.

We partnered with Alaska’s Pick.Click.Give. programme to implement a statewide natural field experiment with 540,000 Alaskans designed to examine two of the main motivations for charitable giving: concerns for the benefits to self (impure altruism or ‘warm glow’) or concerns for the benefits to others (pure altruism). Our empirical results highlight the relative importance of appeals to self: individuals who received such an appeal were 6.6% more likely to give and gave 23% more than counterparts in the control group. Yet, a message that instead appealed to recipient benefits (motivated by altruism) had no statistically significant effect on average donations relative to the control group. We also find evidence of long-run effects of warm-glow appeals in the subsequent year. Our results have import for theoreticians and empiricists interested in modelling charitable giving as well as practitioners and policymakers.

An effective agreement must eliminate subsidies for fuel (7), distant-water and destructive fishing fleets (4, 5), and illegal and unregulated vessels in line with the aims of Sustainable Development Goal 14.6 (8). To ensure accountability, it should also support low-income countries’ efforts to meet their commitments and transition to sustainable management. Finally, the agreement should require transparent data documentation and enforcement measures (9). We call on the heads of state of the High Level Panel for a Sustainable Ocean Economy, the Comprehensive and Progressive Agreement for Trans-Pacific Partnership, and the United States–Mexico–Canada Agreement—who have already committed to eliminating harmful subsidies (10–12)—as well as other trade blocs and individual countries, to declare their support now for an agreement that enshrines these recommendations. WTO members must harness …

Al-Ubaydli et al. provide a far-reaching, insightful and directly actionable analysis of how social-behavioral research may exert more influence over the development and implementation of public policy. Their paper offers a sophisticated understanding of the ‘scale-up effect’, or factors that influence the extent to which positive experimental effects replicate as an intervention is implemented more broadly. Using economic principles, models and analyses, they offer 12 proposals for improving the process of scaling up effective and policy-relevant interventions. The current paper outlines how their proposals share a number of complementary features with behavioral psychology and applied behavior analysis. This response considers three possible points of intersection: (1) perspectives on the importance and challenges of studying and controlling our own behavior; (2) approaches to determining the social value of …

Incomplete contracts are the rule rather than the exception, and any incentive scheme faces the risk of improving performance on incented aspects of a task at the detriment of performance on non-incented aspects. Recent research documents the effect of loss-framed versus gain-framed incentives on incentivized behavior, but how do such incentives affect overall performance? We explore potential trade-offs by conducting field experiments in an artificial “workplace”. We explore two types of incentive spillovers: those contemporaneous to the incented task and those subsequent to the incented task. We report three main results. First, consonant with the extant literature, a loss aversion incentive induces greater effort on the incented task. Second, offsetting this productivity gain, we find that the quality of work decreases if quality is not specified in the incentive contract. Third, we find no evidence of harmful spillover …

A growing body of research indicates that high-performing early childhood interventions and care and education programs have strong program-or center/school-wide structures in place that enable them to continually build the capacity and competency of their staff to implement evidence-based models and practices effectively and with benefits to children and families (Bryk et al., 2010; Dennis & O’Connor, 2013; Ehrlich et al., 2019; National Academies of Sciences, Engineering, and Medicine, 2020; Pacchiano et al., 2019; Sandstrom et al., 2020; Whalen et al., 2016). Successful scaling of early childhood innovations and comprehensive models of early care and education requires helping providers actively attend to administration quality, including building knowledge of the innovation, monitoring adherence, and shaping and guiding skillful and effective implementation by their practitioners; how ever, building and …

The growth of the “gig” economy generates worker flexibility that, some have speculated, will favour women. We explore this by examining labour supply choices and earnings among more than a million rideshare drivers on Uber in the U.S. We document a roughly 7% gender earnings gap amongst drivers. We show that this gap can be entirely attributed to three factors: experience on the platform (learning-by-doing), preferences and constraints over where to work (driven largely by where drivers live and, to a lesser extent, safety), and preferences for driving speed. We do not find that men and women are differentially affected by a taste for specific hours, a return to within-week work intensity, or customer discrimination. Our results suggest that, in a “gig” economy setting with no gender discrimination and highly flexible labour markets, women’s relatively high opportunity cost of non-paid-work time and gender …

Socioeconomic inequalities in child development crystallize at early stages, with associated disparities in parental investment in children. A key to understanding the data patterns is to document the sources underlying the observed inequalities. We first show that there are dramatic differences in parental beliefs across socioeconomic backgrounds (SES), with parents of higher SES being more likely to believe that parental investments impact child development. We then use two field experiments targeted to low-SES families to explore the mutability of such beliefs and their link to parental investments. In both cases, we find that parental beliefs about child development are malleable. The less intensive version of the program based on educational videos changes parental beliefs, but fails to lastingly increase parental investments and child outcomes. By contrast, in the more intensive version of our program combining home visits and feedback, the augmented beliefs are associated with enriched parent-child interactions and improved vocabulary, math, and social-emotional skills for the children. Together, these results suggest that changing parental beliefs can be an important pathway to raising parental investments and reducing socioeconomic gaps in children’s skills, but that simple informational policies may not be sufficient.

This paper uses a natural field experiment to connect corporate social responsibility (CSR) to an important but often neglected behavior: employee misconduct and shirking. Through employing more than 1,500 workers, we find that our use of CSR increases employee misbehavior—24% more employees act detrimentally toward our firm by shirking on their primary job duties when we introduce CSR. Observed data patterns across the treatments are consonant with a model of “moral licensing,” whereby the “doing good” nature of CSR induces workers to misbehave on another dimension that is harmful to the firm.This paper was accepted by Yan Chen, decision analysis.

How do prices adjust when markets are in disequilibrium? This paper investigates this question by comparing two models of price dynamics: the classic excess supply model developed by Leon Walras, and the excess rent model developed by Vernon Smith. Past investigations exploring how prices adjust rely upon naturally-occurring variation in the treatment variable (prevailing price) as opposed to experimental control via randomization. We explore price dynamics using laboratory experiments wherein we control the assignment mechanism of the key treatment variable. Across two distinct market institutions, double oral auctions and decentralized bilateral bargaining, our results provide strong support for Smith’s excess rent model as the driver of price adjustments.

EconPapers: Recommendations for Mitigating Threats to Scaling EconPapers Economics at your fingertips EconPapers Home About EconPapers Working Papers Journal Articles Books and Chapters Software Components Authors JEL codes New Economics Papers Advanced Search EconPapers FAQ Archive maintainers FAQ Cookies at EconPapers Format for printing The RePEc blog The RePEc plagiarism page Recommendations for Mitigating Threats to Scaling Snigdha Gupta, Maggie Kane, John List, Liz Sablich, Lauren Supplee and Dana Suskind Artefactual Field Experiments from The Field Experiments Website Abstract: Recommendations for Mitigating Threats to Scaling Date: 2021 References: Add references at CitEc Citations: Track citations by RSS feed Downloads: (external link) http://s3.amazonaws.com/fieldexperiments-papers2/papers/00735.pdf Related works: This item may be available elsewhere …

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. This paper was accepted by David Simchi-Levi, Special Section of Management Science: 65th Anniversary.

This Conceptual Design Report describes LUXE (Laser Und XFEL Experiment), an experimental campaign that aims to combine the high-quality and high-energy electron beam of the European XFEL with a powerful laser to explore the uncharted terrain of quantum electrodynamics characterised by both high energy and high intensity. We will reach this hitherto inaccessible regime of quantum physics by analysing high-energy electron-photon and photon-photon interactions in the extreme environment provided by an intense laser focus. The physics background and its relevance are presented in the science case which in turn leads to, and justifies, the ensuing plan for all aspects of the experiment: Our choice of experimental parameters allows (i) field strengths to be probed where the coupling to charges becomes non-perturbative and (ii) a precision to be achieved that permits a detailed comparison of the …

World Patent Information (WPI) is the leading international academic peer reviewed journal in the field of patent information. The journal was launched in 1979 and celebrated its 40th anniversary in 2019. In recognition of this event, the aim of this work is to analyse the main actors, research themes and audiences of WPI. The analyses are based on the Scopus and Web of Science databases and include bibliographic coupling, co-citation and co-occurrence of author keywords. WPI is a boundary-spanning journal with authors from academia, industry and governmental organisations, such as patent authorities. This unique composition provides a prominent platform for knowledge transfer between academia and industry. In addition, WPI facilitates knowledge transfer between academia and industry, with research institutions citing contributions from authors affiliated to industry and patent offices. Furthermore, WPI …

In recent years, citizens and law makers have become increasingly enthusiastic about adopting evidence-based policies and programs. Social scientists have delivered evidence of countless interventions that positively impact people’s lives. And yet, most programs, when expanded, have not delivered the dramatic societal impacts promised.This is especially true in the field of early childhood. Research suggests that highquality early childhood programs (those serving children from birth through age 5) have the potential to reduce the inequities that plague our nation and rob too many children of opportunity—and that they can deliver a 13% return on investment in the process. Despite the research and evidence, however, few programs have followed through and delivered on this promise. In order to reap the individual and economic benefits of early childhood programs, researchers and practitioners must figure out how to take these programs from small-scale experiments and implement them at scale in a way that enables population-level impacts. This book—at its heart an exploration of threats to and facilitators of scaling—uses the lens of early childhood to examine the topic for two key reasons: a) early

Introduction Instruction in implicit bias is becoming prevalent across the spectrum of medical training. Little education exists for preclinical students, and guidance for faculty to facilitate such education is minimal. To address these gaps, we designed and delivered a single session for incoming first-year medical students and developed a facilitator training program. Methods One faculty member delivered a 1-hour, multimedia, interactive lecture to all first-year medical students. Students subsequently met in small groups with trained facilitators. Activities included reflection, guided debriefing, and strategy identification to become aware of when they might be making an assumption causing them to jump to a conclusion about someone. The program evaluation consisted of aggregated student strategies and facilitator feedback during postsession debriefs, both analyzed through thematic analysis. Results We …

The behavioral revolution within economics has been largely driven by psychological insights, with the sister sciences playing a lesser role. This study leverages insights from sociology to explore the role of neighborhoods on human capital formation at an early age. We do so by estimating the spillover effects from a large-scale early childhood intervention on the educational attainment of over 2,000 disadvantaged children in the United States. We document large spillover effects on both treatment and control children who live near treated children. Interestingly, the spillover effects are localized, decreasing with the spatial distance to treated neighbors. Perhaps our most novel insight is the underlying mechanisms at work: the spillover effect on non-cognitive scores operate through the child's social network while parental investment is an important channel through which cognitive spillover effects operate. Overall, our results reveal the importance of public programs and neighborhoods on human capital formation at an early age, highlighting that human capital accumulation is fundamentally a social activity.

We use field experiments with nearly 900 children to investigate how skills developed at ages 3-5 drive later-life outcomes. We find that skills map onto three distinct factors-cognitive skills, executive functions, and economic preferences. Returning to the children up to 7 years later, we find that executive functions, but not cognitive skills, predict the likelihood of receiving disciplinary referrals. Economic preferences have an independent effect: children who displayed impatience at ages 3-5 were more likely to receive disciplinary referrals. Random assignment to a parenting program reduced disciplinary referrals. This effect was not mediated by skills or preferences.

The value of time determines relative prices of goods and services, investments, productivity, economic growth, and measurements of income inequality. Economists in the 1960s began to focus on the value of non-work time, pioneering a deep literature exploring the optimal allocation and value of time. By leveraging key features of these classic time allocation theories, we use a novel approach to estimate the value of time (VOT) via two large-scale natural field experiments with the ridesharing company Lyft. We use random variation in both wait times and prices to estimate a consumer's VOT with a data set of more than 14 million observations across consumers in US cities. We find that the VOT is roughly $19 per hour (or 75%(100%) of the after-tax mean (median) wage rate) and varies predictably with choice circumstances correlated with the opportunity cost of wait time. Our VOT estimate is larger than what is currently used by the US Government, suggesting that society is under-valuing time improvements and subsequently under-investing public resources in time-saving infrastructure projects and technologies.

We offer a unified conceptual, behavioral, and econometric framework for optimal fundraising that deals with both synergies and discrepancies between approaches from Economics, Marketing, Psychology, and Sociology. The purpose is to offer a framework that can bridge differences and open a dialogue between disciplines in order to facilitate optimal fundraising design. The literature is extensive, and our purpose is to offer a brief background and perspective on each of the approaches, provide an integrated framework leading to new insights, and discuss areas of future research.