Regression Discontinuity Designs
Overview
1
Continuity Assumption
1.1
Simulate Continuity Assumption
1.2
Simulate the discontinuity
1.3
Nonlinear data generation process
2
Sharp RDD
2.1
Replicate Lee, Moretti, and Butler (2004)
2.1.1
Theory
2.1.2
Potential roll-calling voting records outcomes
2.1.3
Replicate
2.2
Different functional forms of RDD
2.2.1
Treatment with no running variable
2.2.2
Recentered running variable and treatment
2.2.3
Interaction between treatment and running variable
2.2.4
Quadratic interaction between treatment and running variable
2.2.5
Local regression: 5 points from cutoff with OLS
3
Visualize Global and Local Regressions
3.1
Install
cmogram
3.2
Global Regression with Quadratic Fit
3.3
Local Regression with Quadratic Fit
3.4
Global Regression with Linear Fit
3.5
Local Regression with Linear Fit
3.6
Global Regression with Lowess Fit
4
Kernel-weighted local polynomial regression
5
RDRobust
6
McCrary Density Test
References
Published with bookdown
Regression Discontinuity Design
Regression Discontinuity Design
Samuel Rowe adapted from Cunningham (2022)
2026-03-21
Overview
Topics:
Continuity Assumption
Sharp Regression Discontinuity Design
Global and Local Regressions
Kernel-Weighted Regressions
RDRobust
McCrary Density Test