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A good complementary reading if you already purchased the causation bible, Causality: Models, Reasoning and Inference, by Pearl. This one was published by Cambridge University press in 2007, and was recommended by a few of our readers.

Title: Counterfactuals and Causal Inference

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.

  • Causal inference from a counterfactual perspective
  • Techniques for the estimation of causal effects
  • Examples from sociology, political science, and economics

Table of content:

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.


  • Stephen L. MorganCornell 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 WinshipHarvard University, Massachusetts. 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.

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