Structuring the Calibration of Qualitative Data as Sets for Qualitative Comparative Analysis (QCA)

Working Paper

27 Pages Posted: 6 May 2011 Last revised: 29 May 2011

See all articles by Johanna Speer

Johanna Speer

Humboldt University Berlin

Xavier Basurto

Duke Marine Lab, Nicholas School of the Environment

Date Written: October 1, 2010

Abstract

Most studies that apply fuzzy-set Qualitative Comparative Analysis (fsQCA) rely on macro-level data, but there is an increasing number of studies that rely on units of analysis at the micro level, i.e., municipalities, communities, local associations, programs within protected areas or departments within firms. For such studies qualitative interview data are often the primary source of information. Yet, so far no procedure is available describing how to calibrate interview data to fuzzy-sets. We propose a technique to do so, and illustrate it using examples from the study of Guatemalan local governments. By spelling out the details of this important analytic step we aim at contributing to the growing literature on best practice in fsQCA.

Keywords: Qualitative Comparative Analysis (QCA), qualitative data, fuzzy sets, calibration, intermediate n study, best practice

Suggested Citation

Speer, Johanna and Basurto, Xavier, Structuring the Calibration of Qualitative Data as Sets for Qualitative Comparative Analysis (QCA) (October 1, 2010). Working Paper, Available at SSRN: https://ssrn.com/abstract=1831606 or http://dx.doi.org/10.2139/ssrn.1831606

Xavier Basurto

Duke Marine Lab, Nicholas School of the Environment ( email )

135 Duke Marine Lab Road
Beaufort, NC 28516-9721
United States

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
239
Abstract Views
1,350
rank
181,960
PlumX Metrics