Includes bibliographical references (pages 291-316) and index.
Part I. Counterfactual Causality and Empirical Research in the Social Sciences -- 1. Introduction -- 2. The counterfactual model; Part II. Estimating Causal Effects by Conditioning -- 3. Causal graphs, identification, and models of causal exposure -- 4. Matching estimators of causal effects -- 5. Regression estimators of causal effects -- Part III. Estimating Causal Effects When Simple Conditioning is Ineffective -- 6. Identification in the absence of a complete model of causal exposure -- 7. Natural experiments and instrumental variables -- 8. Mechanisms and causal explanation -- 9. Repeated observations and the estimation of causal effects -- Part IV. Conclusions -- 10. Counterfactual causality and future empirical research in the social sciences.
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"In this book, the counterfactual model of causality for observational data analysis is presented, and methods for causal effect estimation are demonstrated using examples from sociology, political science, and economics."--Jacket.