The Comparative Advantages of fsQCA and Regression Analysis for Moderately Large-N Analyses

This article contributes to the literature on comparative methods in the social sciences by assessing the strengths and weaknesses of regression analysis and fuzzy-set qualitative comparative analysis (fsQCA) for studies with a moderately large-n (between approximately 50 and 100). Moderately large-...

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Bibliographic Details
Published in:Sociological methods & research 2012-02, Vol.41 (1), p.168-198
Main Author: Vis, Barbara
Format: Article
Language:English
Subjects:
Comparative advantage
Comparative Analysis
Epistemology
Expenditures
Government Spending
Labour market
Methodology
Qualitative research
Regression analysis
Research methods
Social Science Research
Social sciences
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Summary:This article contributes to the literature on comparative methods in the social sciences by assessing the strengths and weaknesses of regression analysis and fuzzy-set qualitative comparative analysis (fsQCA) for studies with a moderately large-n (between approximately 50 and 100). Moderately large-n studies are interesting in this respect since they allow for regression analysis as well as fsQCA analysis. These two approaches have a different epistemological foundation and thereby answer different, yet related, research questions. To illustrate the comparison of fsQCA and regression analysis empirically, I use a recent data set (n = 53) that includes data on the conditions under which governments in Western democracies increase their spending on active labor market policies (ALMPs). This comparison demonstrates that while each approach has merits and demerits, fsQCA leads to a fuller understanding of the conditions under which the outcome occurs.
ISSN:0049-1241
1552-8294
DOI:10.1177/0049124112442142