Webinars
Virtual Workshop Schedule 2026
Join our virtual webinar series for periodic methodological webinars on field experiments! Stay updated by registering with the community.
Experimental Economics: Theory and Practice
Abstract: Experimental economics has become a central tool for understanding human decisions, motivations, and outcomes, offering researchers a powerful way to identify causal effects in both laboratory and real-world settings. Drawing on more than three decades of experience designing and conducting experiments, John A. List discusses the ideas behind his new book, Experimental Economics: Theory and Practice. The book provides a practical framework for developing, implementing, and interpreting economic experiments, covering topics from experimental design and execution to administrative and ethical considerations. Combining methodological guidance with lessons from field and laboratory research, List highlights what researchers can learn from both successful experiments and the challenges that arise along the way.
Advantages and Limitations of Small-Sample Evidence in Developing Economies
Abstract: Policymakers often test expensive new programs on relatively small samples. Formally incorporating informative Bayesian priors into impact evaluation offers the promise to learn more from these experiments. We evaluate a Colombian program for 200 firms which aimed to increase exporting. Priors were elicited from academics, policymakers, and firms. Contrary to these priors, frequentist estimation cannot reject null effects in 2019, and finds some negative impacts in 2020. For binary outcomes like whether firms export, frequentist estimates are relatively precise, and Bayesian posterior intervals update to overlap almost completely with standard confidence intervals. For outcomes like increasing export variety, where the priors align with the data, the value of these priors is seen in posterior intervals that are considerably narrower than the confidence intervals. Finally, for noisy outcomes like export value, posterior intervals show almost no updating from priors, highlighting how uninformative the data are about such outcomes. Future policy experiments could use these posteriors as priors in a Bayesian or empirical Bayesian analysis.