Counterfactuals and Causal Inference

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Sprache: Englisch

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Beschreibung

In this second edition of Counterfactuals and Causal Inference, completely revised and expanded, the essential features of the counterfactual approach to observational data analysis are presented with examples from the social, demographic, and health sciences. Alternative estimation techniques are first introduced using both the potential outcome model and causal graphs; after which, conditioning techniques, such as matching and regression, are presented from a potential outcomes perspective. For research scenarios in which important determinants of causal exposure are unobserved, alternative techniques, such as instrumental variable estimators, longitudinal methods, and estimation via causal mechanisms, are then presented. The importance of causal effect heterogeneity is stressed throughout the book, and the need for deep causal explanation via mechanisms is discussed.

Über den Autor

Stephen L. Morgan is the Bloomberg Distinguished Professor of Sociology and Education at Johns Hopkins University. He was previously the Jan Rock Zubrow '77 Professor in the Social Sciences and the director of the Center for the Study of Inequality at Cornell University. His current areas of interest include social stratification, the sociology of education, and quantitative methodology. He has published On the Edge of Commitment: Educational Attainment and Race in the United States (2005) and, as editor, the Handbook of Causal Analysis for Social Research (2013).

Inhaltsverzeichnis

Part I. Causality and Empirical Research in the Social Sciences: 1. Introduction; Part II. Counterfactuals, Potential Outcomes, and Causal Graphs: 2. Counterfactuals and the potential-outcome model; 3. Causal graphs; Part III. Estimating Causal Effects by Conditioning on Observed Variables to Block Backdoor Paths: 4. Models of causal exposure and identification criteria for conditioning estimators; 5. Matching estimators of causal effects; 6. Regression estimators of causal effects; 7. Weighted regression estimators of causal effects; Part IV. Estimating Causal Effects When Backdoor Conditioning Is Ineffective: 8. Self-selection, heterogeneity, and causal graphs; 9. Instrumental-variable estimators of causal effects; 10. Mechanisms and causal explanation; 11. Repeated observations and the estimation of causal effects; Part V. Estimation When Causal Effects Are Not Point Identified by Observables: 12. Distributional assumptions, set identification, and sensitivity analysis; Part VI. Conclusions: 13. Counterfactuals and the future of empirical research in observational social science.

Erscheinungsjahr:	2016
Genre:	Importe , Soziologie
Rubrik:	Wissenschaften
Medium:	Taschenbuch
Inhalt:	Kartoniert / Broschiert
ISBN-13:	9781107694163
ISBN-10:	1107694167
Sprache:	Englisch
Einband:	Kartoniert / Broschiert
Autor:	Morgan, Stephen L. Winship, Christopher
Auflage:	2nd edition
Hersteller:	Cambridge University Pr.
Verantwortliche Person für die EU:	Libri GmbH, Europaallee 1, D-36244 Bad Hersfeld, gpsr@libri.de
Abbildungen:	30 tables
Maße:	254 x 178 x 28 mm
Von/Mit:	Stephen L. Morgan (u. a.)
Erscheinungsdatum:	01.02.2016
Gewicht:	0,974 kg