Matching Estimators of Causal Effects: Prospects and Pitfalls in Theory and Practice

As the counterfactual model of causality has increased in popularity, sociologists have returned to matching as a research methodology. In this article, advances over the past two decades in matching estimators are explained, and the practical limitations of matching techniques are emphasized. The a...

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Bibliographic Details
Published in:Sociological methods & research 2006-08, Vol.35 (1), p.3-60
Main Authors: Morgan, Stephen L., Harding, David J.
Format: Article
Language:English
Subjects:
Causality
Data analysis
Estimating techniques
Estimation
History, theory and methodology
Mathematical methods
Methodological Problems
Methodology
Methodology (Data Analysis)
Methodology (Data Collection)
Quantitative analysis
Research Methodology
Research methods
Sociological Research
Sociology
Theory Practice Relationship
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Summary:As the counterfactual model of causality has increased in popularity, sociologists have returned to matching as a research methodology. In this article, advances over the past two decades in matching estimators are explained, and the practical limitations of matching techniques are emphasized. The authors introduce matching methods by focusing first on ideal scenarios in which stratification and weighting procedures warrant causal inference. Then, they discuss how matching is often undertaken in practice, offering an overview of the most prominent data analysis routines. With four hypothetical examples, they demonstrate how the assumptions behind matching estimators often break down in practice. Even so, the authors argue that matching techniques can be used effectively to strengthen the prosecution of causal questions in sociology.
ISSN:0049-1241
1552-8294
DOI:10.1177/0049124106289164