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Counterfactuals and Causal Inference Stephen L. Morgan (Cornell University, New York)

Counterfactuals and Causal Inference By Stephen L. Morgan (Cornell University, New York)

Counterfactuals and Causal Inference by Stephen L. Morgan (Cornell University, New York)


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Summary

In this book, the essential features of the counterfactual model of causality for observational data analysis are presented with examples from sociology, political science, and economics. The importance of causal effect heterogeneity is stressed throughout the book and the need for deep causal explanation via mechanisms is discussed.

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Counterfactuals and Causal Inference Summary

Counterfactuals and Causal Inference: Methods and Principles for Social Research by Stephen L. Morgan (Cornell University, New York)

Did mandatory busing programs in the 1970s increase the school achievement of disadvantaged minority youth? Does obtaining a college degree increase an individual's labor market earnings? Did the use of the butterfly ballot in some Florida counties in the 2000 presidential election cost Al Gore votes? If so, was the number of miscast votes sufficiently large to have altered the election outcome? At their core, these types of questions are simple cause-and-effect questions. Simple cause-and-effect questions are the motivation for much empirical work in the social sciences. This book presents a model and set of methods for causal effect estimation that social scientists can use to address causal questions such as these. The essential features of the counterfactual model of causality for observational data analysis are presented with examples from sociology, political science, and economics.

Counterfactuals and Causal Inference Reviews

This book is the first representative of a growing surge of interest among social scientists and economists to reclaim their professions from the tyrany of regression analysis and address cause-effect relationships squarely and formally. The book is unique in recognizing the equivalence between the counterfactual and graphical approaches to causal analysis and shows readers how to best utilize the distinct features of each. An indispensible reading for every forward-looking student of quantitative social science. -Judea Pearl University of California, Los Angeles
...Morgan and Winship have written an important, wide-ranging, careful, and original introduction to the modern literature on causal inference in nonexperimental social research. Canadian Journal of Sociology

About Stephen L. Morgan (Cornell University, New York)

Stephen L. Morgan is Associate Professor of Sociology and the current Director of the Center for the Study of Inequality at Cornell University. His previous publications include On the Edge of Commitment: Educational Attainment and Race in the United States (2005). Christopher Winship is Diker-Tishman Professor of Sociology at Harvard University. For the past twelve years he has served as editor of Sociological Methods and Research. He has published widely in a variety of journals and edited volumes.

Table of Contents

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.

Additional information

CIN0521671930G
9780521671934
0521671930
Counterfactuals and Causal Inference: Methods and Principles for Social Research by Stephen L. Morgan (Cornell University, New York)
Used - Good
Paperback
Cambridge University Press
20070730
328
N/A
Book picture is for illustrative purposes only, actual binding, cover or edition may vary.
This is a used book - there is no escaping the fact it has been read by someone else and it will show signs of wear and previous use. Overall we expect it to be in good condition, but if you are not entirely satisfied please get in touch with us

Customer Reviews - Counterfactuals and Causal Inference