Mixing Methodologies in Comparative Research
Dr Stefan Kühner
Senior Lecturer in Social Policy,
Department of Social Policy and Social Work, University of York, UK
Advances in international macro-level data consolidation offer an enticing opportunity to revisit contested conclusions in comparative research. Building on a summary of the rationale for mixed methods research designs and different varieties of mixed methods, this workshop will explore the ways in which pooled time-series cross-section (TSCS) regression specifications can sensibly be combined with fuzzy set analysis to identify typical and deviant cases in medium and large-N comparative research. More specifically, using the empirical example of recent debates on the effect of inequality and redistribution on economic growth spells in Asia, the workshop will demonstrate the strengths of ‘mixing it up’ rather than focussing on epistemological and ontological divisions between these two research techniques.
By the end of the workshop, students will be able to:
- Differentiate varieties of mixed methods approaches,
- Appreciate why mixed methods research has increasingly been regarded as the ‘gold standard’ in comparative research,
- Understand the strengths of pooled time-series cross-section (TSCS) regression specifications and fuzzy set analysis, respectively, and
- Learn how these two research techniques can be combined to design a mixed methods comparative research project.