Control, Exogeneity, and Directness: Understanding and Designing Quasi- and Natural Experiments

2024/09/12 by Dahlia K. Remler, Gregg G. Van Ryzin · 1 voice
Mathematics · Economics, Econometrics and Finance · #Advanced Causal Inference Techniques #Health Systems, Economic Evaluations, Quality of Life #Economic and Environmental Valuation

paper · doi:10.1177/10982140241265708

openalex publication_date 2024/09/12 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/07

Abstract

This article reviews the origins and use of the terms quasi-experiment and natural experiment. It demonstrates how the terms conflate whether variation in the independent variable of interest falls short of random with whether researchers find, rather than intervene to create, that variation. Using the lens of assignment—the process driving variation in the independent variable—we distinguish three dimensions: control of assignment by the researcher, rather than by a policy process or naturally occurring event; exogeneity of the assignment process; and directness of the link between assignment and the independent variable. These dimensions generate a typology of causal study designs that we illustrate with examples from the social and health sciences. Our framework can assist researchers and practitioners from diverse disciplines to better understand and communicate with one another and, importantly, to recognize opportunities in real-world settings to find or create variation that can be leveraged for valid impact estimates.

Citations

• Causal Inference Using Potential Outcomes
• Estimating causal effects of treatments in randomized and nonrandomized studies.
• The C-Word: Scientific Euphemisms Do Not Improve Causal Inference From Observational Data
• Causal Inference
• Efficacy and Safety of the mRNA-1273 SARS-CoV-2 Vaccine
• Constructing a Control Group Using Multivariate Matched Sampling Methods That Incorporate the Propensity Score

Discussions

• Published in this month's issue of the American Journal of Evaluation, this article by me and Dahlia Remler presents a framework and typology for making sense of the complex and often confusing terrai [bsky, 2 points, 0 comments]

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