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

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.

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Publication Details

Journal
American Journal of Evaluation
Published
2024-09-12
DOI
https://doi.org/10.1177/10982140241265708
Citations
4
Primary Topic
Advanced Causal Inference Techniques
Type
article
Field-Weighted Citation Impact
2.84
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article

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

Gregg G. Van Ryzin, Dahlia K. Remler
4 citations
American Journal of Evaluation
Advanced Causal Inference Techniques
2.84
article

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

Gregg G. Van Ryzin, Dahlia K. Remler
article en
4 citations

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.

American Journal of EvaluationVol. 46(1)
Rutgers, The State University of New Jersey (US), Baruch College (US), City University of New York (US), Rutgers Sexual and Reproductive Health and Rights (NL)
Openalex Percentile: Top 9%
Advanced Causal Inference Techniques
2.84
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