Counterfactuals and Casual Inference : Method and Principles for Social Research

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 a butterfly ballot in some Florida counties in the 2000 presidential election cost Al Gore votes? Simple cause-and-effect questions such as these are the motivation for much empirical work in the social sciences. 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.

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.