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Huge Popularity of Regression Discontinuity
-
Scott Cunningham
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Kapitel in diesem Buch
- Frontmatter i
- Contents vii
- Acknowledgments ix
-
Introduction
- Introductory Note 1
- What Is Causal Inference? 3
- Do Not Confuse Correlation with Causality 6
- OptimizationMakes Everything Endogenous 8
- Example: Identifying Price Elasticity of Demand 10
- Conclusion 14
- Probability and Regression Review 16
-
Directed Acyclic Graphs
- Introduction 96
- Introduction to DAG Notation 97
-
Potential Outcomes Causal Model
- Introduction 119
- Physical Randomization 123
- Randomization Inference 148
- Conclusion 174
-
Matching and Subclassification
- Subclassification 175
- Exact Matching 191
- Approximate Matching 198
-
Regression Discontinuity
- Huge Popularity of Regression Discontinuity 241
- Estimation Using an RDD 252
- Challenges to Identification 282
- Replicating a Popular Design: The Close Election 289
- Regression Kink Design 312
- Conclusion 313
-
Instrumental Variables
- History of Instrumental Variables: Father and Son 315
- Intuition of Instrumental Variables 319
- Homogeneous Treatment Effects 323
- Parental Methamphetamine Abuse and Foster Care 329
- The Problem of Weak Instruments 337
- Heterogeneous Treatment Effects 346
- Applications 352
- Popular IV Designs 359
- Conclusion 384
-
Panel Data
- DAG Example 386
- Estimation 388
- Data Exercise: Survey of Adult Service Providers 396
- Conclusion 405
-
Difference-in-Differences
- John Snow’s Cholera Hypothesis 406
- Estimation 411
- Inference 423
- Providing Evidence for Parallel Trends Through Event Studies and Parallel Leads 425
- The Importance of Placebos in DD 433
- Twoway Fixed Effects with Differential Timing 461
- Conclusion 509
-
Synthetic Control
- Introducing the Comparative Case Study 511
- Prison Construction and Black Male Incarceration 525
- Conclusion 540
- Bibliography 541
- Permissions 555
- Index 561
Kapitel in diesem Buch
- Frontmatter i
- Contents vii
- Acknowledgments ix
-
Introduction
- Introductory Note 1
- What Is Causal Inference? 3
- Do Not Confuse Correlation with Causality 6
- OptimizationMakes Everything Endogenous 8
- Example: Identifying Price Elasticity of Demand 10
- Conclusion 14
- Probability and Regression Review 16
-
Directed Acyclic Graphs
- Introduction 96
- Introduction to DAG Notation 97
-
Potential Outcomes Causal Model
- Introduction 119
- Physical Randomization 123
- Randomization Inference 148
- Conclusion 174
-
Matching and Subclassification
- Subclassification 175
- Exact Matching 191
- Approximate Matching 198
-
Regression Discontinuity
- Huge Popularity of Regression Discontinuity 241
- Estimation Using an RDD 252
- Challenges to Identification 282
- Replicating a Popular Design: The Close Election 289
- Regression Kink Design 312
- Conclusion 313
-
Instrumental Variables
- History of Instrumental Variables: Father and Son 315
- Intuition of Instrumental Variables 319
- Homogeneous Treatment Effects 323
- Parental Methamphetamine Abuse and Foster Care 329
- The Problem of Weak Instruments 337
- Heterogeneous Treatment Effects 346
- Applications 352
- Popular IV Designs 359
- Conclusion 384
-
Panel Data
- DAG Example 386
- Estimation 388
- Data Exercise: Survey of Adult Service Providers 396
- Conclusion 405
-
Difference-in-Differences
- John Snow’s Cholera Hypothesis 406
- Estimation 411
- Inference 423
- Providing Evidence for Parallel Trends Through Event Studies and Parallel Leads 425
- The Importance of Placebos in DD 433
- Twoway Fixed Effects with Differential Timing 461
- Conclusion 509
-
Synthetic Control
- Introducing the Comparative Case Study 511
- Prison Construction and Black Male Incarceration 525
- Conclusion 540
- Bibliography 541
- Permissions 555
- Index 561