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John A List, Anya Samek, Dana L Suskind

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Behavioral economics and field experiments within the social sciences have advanced well beyond academic curiosum. Governments around the globe as well as the most powerful firms in modern economies employ staffs of behavioralists and experimentalists to advance and test best practices. In this study, we combine behavioral economics with field experiments to reimagine a new model of early childhood education. Our approach has three distinct features. First, by focusing public policy dollars on prevention rather than remediation, we call for much earlier educational programs than currently conceived. Second, our approach has parents at the center of the education production function rather than at its periphery. Third, we advocate attacking the macro education problem using a public health methodology, rather than focusing on piecemeal advances.

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

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

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

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

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

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

Snigdha Gupta, John A List, Lauren Supplee, Dana L Suskind

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Failed to Scale: Embracing the Challenge of Scaling in Early Childhood

Snigdha Gupta, Maggie C. Kane, John A List, Liz Sablich, Lauren Supplee, Dana L Suskind

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Recommendations for Mitigating Threats to Scaling

John A List, Julie Pernaudet, Dana L Suskind

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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.

Robert T Ammerman, Anne K Duggan, John A List, Lauren Supplee, Dana L Suskind

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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 United States is early childhood home visiting. While there is a 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 case study of the relevance of the economic model and open science in developing and scaling evidence-based home visiting. The case study considers how the traditional approach for testing interventions has influenced home visiting's evolution to date and how open science practices could have supported efforts to maintain impacts while scaling home visiting. It concludes by considering how open science can accelerate the refinement and scaling of home visiting interventions going forward, through accelerated translation of research into policy and practice.

John A List, Dana L Suskind

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Op-ed