#Set working directory (edit following command) #setwd("/.../Panagopoulos_PB_2010/") #Load data library(foreign) library(AER) library(gmodels) library(lmtest) library(sandwich) library(sem) data <- read.dta("Panagopoulos_PB_2010_ReplicationDataset_dta.dta", convert.factors=F) ######### #Table 2# ######### #Column 1: (Turnout) CrossTable(data$four_weeks, data$vtr_gen05, prop.c=F, prop.t=F, prop.chisq=F, digits=4) CrossTable(data$two_weeks, data$vtr_gen05, prop.c=F, prop.t=F, prop.chisq=F, digits=4) CrossTable(data$two_weeks, data$vtr_gen05, prop.c=F, prop.t=F, prop.chisq=F, digits=4) #Column 2: (ITT) out.1.1 <- lm(vtr_gen05 ~ four_weeks + two_weeks + three_days, data=data) coeftest(out.1.1, vcov=vcovHC(out.1.1, type="HC1")) #Column 3: (Contact Rate) out.1.2 <- lm(treated ~ four_weeks + two_weeks + three_days, data=data) coeftest(out.1.2, vcov=vcovHC(out.1., type="HC1")) #Column 4 (TOT) #The following models do not include Robust Standard errors, only slightly changing the standard errors from those reported in the model. out.1.3 <- tsls(vtr_gen05 ~ treated, ~ four_weeks, data=data[data$four_weeks==1 | data$control==1,]) summary(out.1.3) out.1.4 <- tsls(vtr_gen05 ~ treated, ~ two_weeks, data=data[data$two_weeks==1 | data$control==1,]) summary(out.1.4) out.1.5 <- tsls(vtr_gen05 ~ treated, ~ three_days, data=data[data$three_days==1 | data$control==1,]) summary(out.1.5) ######### #TABLE 3# ######### #Create treatment variable data$treatment[data$control==0] <- 1 data$treatment[data$control==1] <- 0 #Column 1 out.2.1 <- tsls(vtr_gen05 ~ treated, ~ treatment, data=data) summary(out.2.1) #Column 2 out.2.2 <- tsls(vtr_gen05 ~ treated, ~ four_weeks + two_weeks + three_days, data=data) summary(out.2.2) out.2.3 <- tsls(vtr_gen05 ~ contacted_4weeks + contacted_2weeks + contacted_3days, ~ four_weeks + two_weeks + three_days, data=data) summary(out.2.3) out.2.4 <- tsls(vtr_gen05 ~ contacted_4weeks + contacted_2weeks + contacted_3days + democrat + republican + unenrolled + other_party + age + age_squared + vtr_gen01 + vtr_gen03, ~ four_weeks + two_weeks + three_days + democrat + republican + unenrolled + other_party + age + age_squared + vtr_gen01 + vtr_gen03, data=data[data$use==1,]) summary(out.2.4) ######### #TABLE 4# ######### data$high <- 0 data$high[data$vote_prop>.68] <- 1 out.3.1 <- tsls(vtr_gen05 ~ contacted_4weeks + contacted_2weeks + contacted_3days + democrat + republican + unenrolled + other_party + age + age_squared + vtr_gen01 + vtr_gen03, ~ four_weeks + two_weeks + three_days + democrat + republican + unenrolled + other_party + age + age_squared + vtr_gen01 + vtr_gen03, data=data[data$use==1,], subset=data$high==1) summary(out.3.1) out.3.2 <- tsls(vtr_gen05 ~ contacted_4weeks + contacted_2weeks + contacted_3days + democrat + republican + unenrolled + other_party + age + age_squared + vtr_gen01 + vtr_gen03, ~ four_weeks + two_weeks + three_days + democrat + republican + unenrolled + other_party + age + age_squared + vtr_gen01 + vtr_gen03, data=data[data$use==1,], subset=data$high==0) summary(out.3.2)