What did I leave out? Omitted variables in regression and qualitative comparative analysis

Abstract

Social scientists often face a fundamental problem: Did I leave something causally important out of my explanation? How do I diagnose this? Where do I look for solutions to this problem? We build bridges between regression models and qualitative comparative analysis (QCA) by comparing diagnostics and solutions to the problem of omitted variables and conditions. We then discuss various approaches and tackle the theoretical issues around causality which must be addressed before attending to technical fixes. In the conclusions we reflect on the bridges built between the two traditions and draw more general lessons about the logic of social science research.