Case Studies and Causal Inference

A discussion of the case study method which develops an integrative framework for causal inference in small-n research. This framework is applied to research design tasks such as case selection and process tracing. The book presents the basics, state-of-the-art and arguments for improving the case study method and empirical small-n research.

Auteur
INGO ROHLFING is Assistant Professor for Comparative Social Research at the Cologne Graduate School in Management, Economics and Social Sciences, University of Cologne, Germany. His research is centred on party politics and social science methodology and he has published in journals such as Comparative Political Studies and West European Politics.

Contenu
Introduction Case, Case Study, and Causality: Core Concepts and Fundamentals Types of Case Study and Case Selection Forms and Problems of Comparisons Enhancing Causal Inference in Comparisons Process Tracing: Theory, Temporality, and Method From Evidence to Inference: Uses of Sources and Counterfactuals Frequentist and Bayesian Causal Inference in Tests of Hypotheses External Validity: Challenges and Strategies Conclusion: Guided by Theory, Moving Forward Step by Step