Counterfactuals and Causal Inference

Methods and Principles for Social Research

Nonfiction, Social & Cultural Studies, Social Science, Methodology, Reference & Language, Reference
Cover of the book Counterfactuals and Causal Inference by Stephen L. Morgan, Christopher Winship, Cambridge University Press
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Author: Stephen L. Morgan, Christopher Winship ISBN: 9781139234924
Publisher: Cambridge University Press Publication: July 30, 2007
Imprint: Cambridge University Press Language: English
Author: Stephen L. Morgan, Christopher Winship
ISBN: 9781139234924
Publisher: Cambridge University Press
Publication: July 30, 2007
Imprint: Cambridge University Press
Language: English

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.

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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.

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