Macartan Humphreys is Director of the Institutions and Political Inequality group at the WZB Berlin, and honorary professor in social sciences at Humboldt University and Trinity College Dublin. His research focuses on post-conflict development, ethnic politics, and democratic decision-making. He has been President of the APSA Experimental Political Science section and Executive Director of the Evidence on Governance and Politics network, and has taught summer schools in experimental methods and empirical implications of theoretical models.
Alan M. Jacobs is Professor of Political Science at the University of British Columbia, conducting research on comparative political economy in democratic settings. He has been President of the APSA's Qualitative and Multi-Method Research section, winner of the section's Mid-Career Achievement Award, and a regular instructor at the Institute for Qualitative and Multi-Method Research.
They will teach the workshop Causal Models for Qualitative and Mixed Methods Research, taking place in Cologne from 27 to 28 January 2026.
How did you become interested in your subject?
Macartan & Alan: We have been interested in both quantitative and qualitative methods in our own work, as well as in theory and causal inference. Alan's early substantive work involved the systematic use of qualitative tools, while Macartan‘s employed predominantly on quantitative methods. As we began to discuss how one might mix these approaches, we were struck by how difficult conversations seemed to be across different analytic traditions in our discipline – how qualitative and quantitative tools were often treated as fundamentally divergent and incommensurable. Yet we were convinced that scholars in different traditions often shared similar goals: to understand similar phenomena, to connect theory with evidence, and to explore causal relationships.
Our hunch was that if scholars pursue the same inferential targets using different methods, then it must be possible to combine the insights from each toward a set of common goals.
What lessons can participants draw from your GESIS course?
Macartan & Alan:
We hope that participants will get a lot out of our course. First and foremost, we want them to come away with an understanding of how to create causal models and then use them for both process tracing and mixed-methods research that combines the intensive study of a small number of cases with the extensive analysis of many cases. Along the way, we hope that students will gain a deeper appreciation of Bayesianism.
Lastly, we hope that students will get an initial foothold on how they can apply these ideas to their own projects, thus getting a leg up in developing their own theories and empirical strategies.
What do you enjoy most about being a social scientist?
Macartan:
Start to work on an important question when you only have a foggy glimpse of what an answer might look like – and then seeing an answer come into focus, whether gradually or all at once.
We thank Macartan & Alan for their insights and look forward to their upcoming course in January.
