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Omar Al-Ubaydli, Faith Fatchen, John A List

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Field experiments are a useful empirical tool that can be deployed in any sub-discipline - including institutional economics - to enhance the sub-discipline's empirical insights. However, we here argue that there exist fundamental barriers to the use of field experiments in understanding the impact of institutions on economic growth. Despite these obstacles, we present some significant scholarly contributions that merit exposition, while also proposing some future methods for using field experiments within institutional economics. While field experiments may be limited in answering questions in institutional economics with macroeconomic outcomes, there is great potential in employing field experiments to answer micro founded questions.

Faith Fatchen, John A. List, Francesca Pagnotta

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In recent years, field experiments have reshaped policy worldwide, but scaling ideas remains a thorny challenge. Perhaps the most important issue facing policymakers today is deciding which ideas to scale. One approach to attenuate this information problem is to augment traditional A/B experimental designs to address questions of scalability from the beginning. List 2024 denotes this approach as “Option C” thinking. Using early education as a case study, we show how AI can overcome a critical barrier in Option C thinking – generating viable options for scaling experimentation. By integrating AI-driven insights, this approach strengthens the link between controlled trials and large-scale implementation, ensuring the production of policy-based evidence for effective decision-making.