Counterfactuals and Causal Inference

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Counterfactuals and Causal Inference

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 by Stephen L Morgan

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.
"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 formallyThe 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
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.
SKU Unavailable
ISBN 13 9780521671934
ISBN 10 0521671930
Title Counterfactuals and Causal Inference
Author Stephen L Morgan
Series Analytical Methods For Social Research
Condition Unavailable
Binding Type Paperback
Publisher Cambridge University Press
Year published 2007-07-30
Number of pages 328
Cover note Book picture is for illustrative purposes only, actual binding, cover or edition may vary.
Note Unavailable