Advances in Econometrics, volume 38
Regression Discontinuity Designs: Theory and Applications
Editors: Matias D. Cattaneo (University of Michigan) and Juan Carlos Escanciano (Indiana University)

Published version: Advances in Econometrics, Emerald Group Publishing Limited.

Introduction: Regression Discontinuity Designs.

The following papers are part of this volume:
  1. Bartalotti, Otavio, and Quentin Brummet: Regression Discontinuity Designs with Clustered Data.
  2. Bartalotti, Otavio, Gray Calhoun, and Yang He: Bootstrap Confidence Intervals for Sharp Regression Discontinuity Designs.
  3. Card, David, David Lee, Zhuan Pei, and Andrea Weber: Regression Kink Design: Theory and Practice.
  4. Cerulli, Giovanni, Yingying Dong, Arthur Lewbel, and Alexander Poulsen: Testing Stability of Regression Discontinuity Models.
  5. Frandsen, Brigham: Party Bias in Union Representation Elections: Testing for Manipulation in the Regression Discontinuity Design When the Running Variable is Discrete.
  6. Galiani, Sebastian, Patrick McEwan, and Brian Quistorff: External and Internal Validity of a Geographic Quasi-experiment Embedded in a Cluster-randomized Experiment.
  7. Jales, Hugo, and Zhengfei Yu: Identification and Estimation using a Density Discontinuity Approach.
  8. Keele, Luke, Scott Lorch, Molly Passarella, Dylan Small, and Rocio Titiunik: An Overview of Geographically Discontinuous Treatment Assignments With an Application to Children’s Health Insurance.
  9. McCrary, Justin, and David Lee: The Deterrence Effect of Prison: Dynamic Theory and Evidence.
  10. Pei, Zhuan, and Yi Shen: The Devil is in the Tails: Regression Discontinuity Design with Measurement Error in the Assignment Variable.
  11. Sekhon, Jasjeet, and Rocio Titiunik: On Interpreting the Regression Discontinuity Design as a Local Experiment.
  12. Tang, Yang, Thomas Cook, Yasemin Kisbu-Sakarya, Heinrich Hock, and Hanley Chiang: The Comparative Regression Discontinuity (CRD) Design: An Overview and Demonstration of its Performance Relative to Basic RD and the Randomized Experiment.