Description
While existing qualitative, case-study methods deliver specific explanations, quantitative approaches to causal inference emphasize valid inferences at the expense of explanations. In this book, David Waldner presents a hybrid method drawing on both approaches to ensure that explanations are based on validly inferred causes and to avoid making valid inferences that have limited explanatory power. Qualitative Causal Inference and Explanation integrates a qualitative identification strategy based on graph-theoretic analysis into traditional process-tracing methods by introducing three novel methodological concepts: hypothetical interventions, invariant causal mechanisms, and event-history maps. This new approach provides clear and feasible standards for making valid, unit-level causal inferences. The result is a groundbreaking approach to explaining complex social and political phenomena, one that better avoids false positives while providing explanations that satisfy the criteria of explanatory depth, density, relevance, and unification.
Table of Contents
1. Introduction; Part I. Foundations: 2. Causal graphs; 3. Invariant causal mechanisms; 4. Event-history maps; Part II. Qualitative Causal Inference: 5. Inferring causes qualitatively; 6. Evaluating qualitative causal inferences; 7. Comparing methods; Part III. Qualitative Causal Explanations: 8. Causal explanations; 9. Standard explanatory patterns; 10. Looking backward and forward.
