CAUSAL INFERENCE: THE MIXTAPE

Causal 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.

 

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
Author: Scott Cunningham
ISBN-13: 978-0-3002-5168-5
©Copyright: 2021

Causal 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.