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Selecting Cases for Intensive Analysis

Author

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  • John Gerring
  • Lee Cojocaru

Abstract

This study revisits the task of case selection in case study research, proposing a new typology of strategies that is explicit, disaggregated, and relatively comprehensive. A secondary goal is to explore the prospects for case selection by algorithm , aka ex ante , automatic , quantitative , systematic , or model-based case selection. We lay out a suggested protocol and then discuss its viability. Our conclusion is that it is a valuable tool in certain circumstances, but should probably not determine the final choice of cases unless the chosen sample is medium-sized. Our third goal is to discuss the viability of medium-n samples for case study research, an approach closely linked to algorithmic case selection and occasionally practiced by case study researchers. We argue that medium- n samples occupy an unstable methodological position, lacking the advantages of efficiency promised by traditional, small- n case studies but also lacking the advantages of representativeness promised by large- n samples.

Suggested Citation

  • John Gerring & Lee Cojocaru, 2016. "Selecting Cases for Intensive Analysis," Sociological Methods & Research, , vol. 45(3), pages 392-423, August.
    • Handle: RePEc:sae:somere:v:45:y:2016:i:3:p:392-423
    DOI: 10.1177/0049124116631692
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    References listed on IDEAS

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    1. Fairfield, Tasha, 2013. "Going Where the Money Is: Strategies for Taxing Economic Elites in Unequal Democracies," World Development, Elsevier, vol. 47(C), pages 42-57.
    2. Dunning,Thad, 2012. "Natural Experiments in the Social Sciences," Cambridge Books, Cambridge University Press, number 9781107698000, November.
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    1. Eugene Danso, 2019. "Anatomy of the Privatization of State-Owned Enterprises (SOEs) in Ghana: Implication for Policy and Accountability," Journal of Public Administration and Governance, Macrothink Institute, vol. 9(4), pages 181-199, December.

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