Causal inference : the mixtape /
por Scott Cunningham. --
- New Haven, EUA : Yale University Press, 2021.
- 572 p. : il.
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 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 Prision Construction and Black Male Incarceration Conclusion Bibliography Permissions Index
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Ciências Sociais - Métodos Estatísticos Inferência Causal Técnicas de Modelagem