Causal Inference: The Mixtape |
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Comment from the Stata technical groupCausal Inference: The Mixtape is a book for practitioners. The purpose of the book is to allow researchers to understand causal inference and work with their data to answer relevant questions in the area. It is the emphasis on the use of statistical software that sets Cunningham's book apart. In each chapter, theoretical details are clearly presented, followed by how to apply the theory to answer causal inference problems using statistical software. The examples are accompanied by readily available data and replication code. The book starts with some basic concepts and then moves into the most commonly used causal inference models and estimators. Topics include directed acyclical graphs, potential outcome models, matching and subclassification, regression discontinuity, instrumental variables, difference in differences, and synthetic control. The inclusion and discussion of synthetic control and directed acyclical graphs differentiates this book from others in the literature, which do not cover these topics or do so tangentially. The structure of the book lends itself to teaching a course on causal inference, but at the same time it is a useful reference for any researcher delving into causal inference. |
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Table of contentsView table of contents >> Acknowledgments
Introduction
What is Causal Inference?
Do Not Confuse Correlation with Causality Optimization Makes Everything Endogenous Example: Identifying Price Elasticity of Demand Conclusion Probability and Regression Review
Directed Acyclic Graphs
Introduction to DAG Notation
Potential Outcomes Causal Model
Physical Randomization
Randomization Inference Conclusion Matching and Subclassification
Subclassification
Exact Matching Approximate Matching Regression Discontinuity
Huge Popularity of Regression Discontinuity
Estimation Using an RDD Challenges to Identification Replicating a Popular Design: The Close Election Regression Kink Design Conclusion Instrumental Variables
History of Instrumental Variables: Father and Son
Intuition of Instrumental Variables Homogeneous Treatment Effects Parental Methamphetamine Abuse and Foster Care The Problem of Weak Instruments Heterogeneous Treatment Effects Applications Popular IV Designs Conclusion Panel Data
DAG Example
Estimation Data Exercise: Survey of Adult Service Providers Conclusion Difference-in-Differences
John Snow's Cholera Hypothesis
Estimation Inference Providing Evidence for Parallel Trends Through Event Studies and Parallel Leads The Importance of Placebos in DD Twoway Fixed Effects with Differential Timing Conclusion Synthetic Control
Introducing the Comparative Case Study
Prison Construction and Black Male Incarceration Conclusion
Bibliography
Permissions
Index
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