Control, Exogeneity, and Directness
Understanding and Designing Quasi- and Natural Experiments
Bibliographic Data
| ID | 6414828 |
|---|---|
| Authors | Dahlia K Remler (0000-0002-9661-2460, Baruch College), Gregg G Van Ryzin (0000-0003-4107-5319, Rutgers, the State University of New Jersey) |
| Year | 2024 |
| Volume | 46 |
| Issue | 1 |
| Pages | 62-89 |
| Publication date | 2024-09-12 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | American Journal of Evaluation (JOURNAL) |
| Journal identifiers | ISSN: 1098-2140 • E-ISSN: 1557-0878 |
| Publisher | SAGE Publishing (PUBLISHER • US) |
| DOI | 10.1177/10982140241265708 |
| OpenAlex | W4402546169 |
| Language | EN |
| Citations received | 3 |
| References cited | 70 |
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
Argument (complex analysis · Conflation · Control (management · Econometrics · Economics · Endogeneity · Epistemology · Machine learning · Management science · Natural (archaeology · Natural experiment · Process (computing · Random assignment · Sociology · Statistics · Typology · Variable (mathematics · Variation (astronomy · Advanced Causal Inference Techniques · Computer Science · Economic and Environmental Valuation · Health Systems, Economic Evaluations, Quality of Life · Mathematics · Artificial Intelligence
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| Unique citing works | 3 |
|---|---|
| Citations per year | 3 |
| Citation span | 2026 - 2026 (1) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 2 |