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When Natural Experiments Are Neither Natural nor Experiments

Published online by Cambridge University Press:  09 February 2012

JASJEET S. SEKHON  and
ROCÍO TITIUNIK
JASJEET S. SEKHON*
Affiliation:
University of California, Berkeley
ROCÍO TITIUNIK*
Affiliation:
University of Michigan
*
Jasjeet S. Sekhon is Associate Professor, Travers Department of Political Science and Department of Statistics, University of California at Berkeley, 210 Barrows Hall, #1950, Berkeley, CA 94720 (sekhon@berkeley.edu).
Rocío Titiunik is Assistant Professor, Department of Political Science and Faculty Associate, Center for Political Studies, University of Michigan, 426 Thompson Street, Ann Arbor, MI 48104 (titiunik@umich.edu).
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Abstract

Natural experiments help to overcome some of the obstacles researchers face when making causal inferences in the social sciences. However, even when natural interventions are randomly assigned, some of the treatment–control comparisons made available by natural experiments may not be valid. We offer a framework for clarifying the issues involved, which are subtle and often overlooked. We illustrate our framework by examining four different natural experiments used in the literature. In each case, random assignment of the intervention is not sufficient to provide an unbiased estimate of the causal effect. Additional assumptions are required that are problematic. For some examples, we propose alternative research designs that avoid these conceptual difficulties.

Type
Research Article
Information
American Political Science Review , Volume 106 , Issue 1 , February 2012 , pp. 35 - 57
Copyright
Copyright © American Political Science Association 2012

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