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External Validity and Generalizability in Program Evaluation: Embracing Complexity

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  • Anne Revillard

Abstract

This introduction to the second special issue of Evaluation review on external validity and generalizability opens a dialogue between different ways to think about generalizability in program evaluation. It argues that generalizability in impact evaluation fundamentally is about inferring some form of causality at a level broader than the specific circumstances of the initial study or studies from which these inferences are drawn. The question, then, is about how one apprehends causality: in other words, what is being generalized and how ? The first special issue mainly relied on a counterfactual conception of causality, embodied by experimental and quasi-experimental methods, that aimed at impact measurement . The articles in this volume, drawing on mixed methods, also mobilize generative and configurational causal inferences to provide further levers of generalizability, focusing on how the impact is produced. The introduction insists on the specific input of qualitative methods in this respect, as theorized by grounded theory.

Suggested Citation

  • Anne Revillard, 2026. "External Validity and Generalizability in Program Evaluation: Embracing Complexity," Evaluation Review, , vol. 50(2), pages 183-199, April.
    • Handle: RePEc:sae:evarev:v:50:y:2026:i:2:p:183-199
    DOI: 10.1177/0193841X251380908
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    References listed on IDEAS

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    1. Woolcock, Michael, 2013. "Using Case Studies to Explore the External Validity of 'Complex' Development Interventions," Working Paper Series rwp13-048, Harvard University, John F. Kennedy School of Government.
    2. Woolcock, Michael, 2013. "Using Case Studies to Explore the External Validity of 'Complex' Development Interventions," Working Paper Series rwp13-048, Harvard University, John F. Kennedy School of Government.
    3. Danielle V. Handel & Eric A. Hanushek, 2024. "Contexts of Convenience: Generalizing from Published Evaluations of School Finance Policies," Evaluation Review, , vol. 48(3), pages 461-494, June.
    4. Tom Ling, 2024. "Transferability of Lessons From Program Evaluations: Iron Laws, Hiding Hands and the Evidence Ecosystem," Evaluation Review, , vol. 48(3), pages 410-426, June.
    5. Douglas J. Besharov, 2024. "Program Evaluation’s Path to Greater Policy Relevance: Learning From Rossi’s Iron Laws," Evaluation Review, , vol. 48(3), pages 403-409, June.
    6. Burt S. Barnow & Sanjay K. Pandey & Qian “Eric†Luo, 2024. "How Mixed-Methods Research Can Improve the Policy Relevance of Impact Evaluations," Evaluation Review, , vol. 48(3), pages 495-514, June.
    7. Rebecca Maynard, 2024. "Improving the Usefulness and Use of Meta-Analysis to Inform Policy and Practice," Evaluation Review, , vol. 48(3), pages 515-543, June.
    8. Julia H. Littell, 2024. "The Logic of Generalization From Systematic Reviews and Meta-Analyses of Impact Evaluations," Evaluation Review, , vol. 48(3), pages 427-460, June.
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