Update answer for Step 2: CTV2019

CTV2019.R

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+################################################################################
+## The Regression Discontinuity Design -- Re-analysis of Klasnja-Titiunik (2017)
+## Authors: Matias Cattaneo, Rocio Titiunik, Gonzalo Vazquez-Bare
+## Last update: 10-Jun-2019
+################################################################################
+## SOFTWARE WEBSITE: https://sites.google.com/site/rdpackages/
+################################################################################
+## TO INSTALL/DOWNLOAD R PACKAGES/FUNCTIONS:
+## RDROBUST: install.packages('rdrobust')
+## RDDENSITY: install.packages("rddensity",dependencies=TRUE)
+## RDLOCRAND: install.packages('rdlocrand')
+################################################################################
+
+rm(list = ls())
+
+library(rdrobust)
+library(rddensity)
+library(rdlocrand)
+
+
+#################################
+# Read data and define variables 
+#################################
+
+data = read.csv("CTV_2019_Sage.csv")
+
+Y = data$mv_incpartyfor1
+X = data$mv_incparty
+
+covs = data[, c("pibpc", "population", "numpar_candidates_eff", "party_DEM_wonlag1_b1",  "party_PSDB_wonlag1_b1", "party_PT_wonlag1_b1", "party_PMDB_wonlag1_b1")]
+covsnm = c("GDP per capita", "Population", "No. Effective Parties", "DEM Victory t-1",  "PSDB Victory t-1", "PT Victory t-1", "PMDB Victory t-1")
+
+
+#################################
+# Falsification analysis 
+#################################
+
+rddens = rddensity(X)
+summary(rddens)
+rdplotdensity(rddens, X = data$mv_incparty[!is.na(data$mv_incparty)], 
+              xlab = "Incumbent Party's Margin of Victory at t", ylab = "Estimated density")
+
+for(c in 1:ncol(covs)){
+  summary(rdrobust(covs[,c],X))
+  rdplot(covs[,c],X,y.label=covsnm[c],x.label="Incumbent Party's Margin of Victory",
+         x.lim= c(-30,30),binselect = "qsmv")
+}
+
+
+#################################
+# Outcome analysis 
+#################################
+
+# rdplot
+
+rdplot(Y,X)
+
+# Continuity-based approach
+
+rdr = rdrobust(Y,X)
+summary(rdr)
+
+# with covariates
+
+rdrcovs = rdrobust(Y,X,covs=covs)
+summary(rdrcovs)
+
+# Local randomization approach
+
+rdwin = rdwinselect(X,covs,wmin=0.05,wstep=0.01,nwindows=200,seed=765,plot=TRUE)
+w = 0.15
+
+rdrand = rdrandinf(Y,X,wl=-w,wr=w,reps=1000,seed=765)
+

CTV2019.do

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+********************************************************************************
+** The Regression Discontinuity Design -- Re-analysis of Klasnja Titiunik (2017)
+** Authors: Matias D. Cattaneo, Rocio Titiunik and Gonzalo Vazquez-Bare
+** Last update: 10-JUN-2019
+********************************************************************************
+** SOFTWARE WEBSITE: https://sites.google.com/site/rdpackages/
+********************************************************************************
+** TO INSTALL STATA PACKAGES:
+** RDROBUST: net install rdrobust, from(https://sites.google.com/site/rdpackages/rdrobust/stata) replace
+** RDDENSITY: net install rddensity, from(https://sites.google.com/site/rdpackages/rddensity/stata) replace
+** RDLOCRAND: net install rdlocrand, from(https://sites.google.com/site/rdpackages/rdlocrand/stata) replace
+********************************************************************************
+* Score:   mv_incparty (margin of victory of incumbent party at t)
+* Outcome: indicator for victory of incumbent party at t+1 
+* Cutoff:  0
+********************************************************************************
+
+
+********************************************************************************
+** Load Data
+********************************************************************************
+
+use "CTV_2019_Sage.dta", clear
+
+global y mv_incpartyfor1 
+global x mv_incparty
+global covs "pibpc population numpar_candidates_eff party_DEM_wonlag1_b1 party_PSDB_wonlag1_b1 party_PT_wonlag1_b1 party_PMDB_wonlag1_b1"
+
+
+********************************************************************************
+** Falsification analysis
+********************************************************************************
+
+* Density discontinuity test
+
+rddensity $x, plot
+
+* Placebo tests on pre-determined covariates
+
+foreach var of global covs {
+	rdrobust `var' $x
+	qui rdplot `var' $x if abs($x)<=30, graph_options(graphregion(color(white)) ///
+													  xlabel(-30(10)30) ///
+													  ytitle(`var'))
+}
+
+
+********************************************************************************
+* Outcome analysis 
+********************************************************************************
+
+* RD plot 
+
+rdplot $y $x, graph_options(graphregion(color(white)) ///
+							xtitle(Margin of Victory at t) ///
+							ytitle(Margin of Victory at t+1)) 
+
+* Continuity based approach  
+
+rdrobust $y $x 
+
+* with covariates
+
+rdrobust $y $x, covs($covs) 
+
+
+* Local randomization approach 
+
+* Window selector: uncomment to run. Can take a long time.
+
+*rdwinselect $x $covs, wmin(0.05) wstep(0.01) nwindows(200) seed(765) plot graph_options(xtitle(Half window length) ytitle(Minimum p-value across all covariates) graphregion(color(white)))
+
+* Randomization inference
+
+local  w =  0.15
+rdrandinf $y $x, wl(-`w') wr(`w') reps(1000) seed(765)
+
+
+