Quantitative Approaches to Intersectionality: New Methodological Directions and Implications for Policy Analysis

  • Joshua K. DubrowEmail author
  • Corina Ilinca
Part of the The Politics of Intersectionality book series (POLI)


Intersectionality is a way to approach the collection and use of information and explain data patterns. This chapter discusses several major methodological challenges in the application of quantitative methods to intersectionality: (a) measurement of identity with cross-national survey data, (b) accounting for power structures, and (c) the small n problem. It also discusses several solutions: structural equation modelling, survey data harmonization, big data, and mixed methods. The authors argue that factorial analysis within structural equation modelling invites new possibilities to measure intersections. Survey data harmonization, at a large enough scale, turns into big data with a sufficient number of cases to construct and analyse nuanced intersectional groups. The mixed method approach uses both quantitative data to generalize across populations and qualitative approaches to delve deep into social and political processes that can reveal and explain power structures.



Some of this research was presented in sessions of the Fritz Thyssen Foundation conference, “Measuring Women’s Political Empowerment across the Globe: Strategies, Challenges and Future Research,” 2015, in Cologne, Germany; the European Conference on Politics and Gender (ECPG) conference 2015 at Uppsala University, Sweden; and the DomEQUAL Venice Symposium #3, “The Challenges of Intersectionality,” 2018, at Ca’ Foscari University, Venice, Italy. We thank the organizers and participants of those sessions and we also thank Irina Tomescu-Dubrow and Paula Tufis for their comments. This chapter is funded, in part, by a grant from Poland’s National Science Centre for “Political Voice and Economic Inequality across Nations and Time” (2016/23/B/HS6/03916).


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Copyright information

© The Author(s) 2019

Authors and Affiliations

  1. 1.Polish Academy of SciencesWarsawPoland
  2. 2.University of BucharestBucharestRomania

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