R Econ Visual Library

# Install and load packages ---------------
packages <- c(
  "tidyverse",
  "haven",
  "rdd",
  "splines"
)

# Change to install = TRUE to install the required packages
pacman::p_load(packages, character.only = TRUE, install = FALSE)

# Load an example dataset ---------------
data <- read_dta("https://github.com/worldbank/r-econ-visual-library/raw/master/Library/Data/RDD_data.dta")
data <- data %>%
  mutate(treatment = (pmt_score >= cutoff))

bw_seq = seq(0.5, 6, 0.5)
rdd_mat = matrix(0, length(bw_seq), 3)
for (i in seq_along(bw_seq)){
  rdd_tmp <- RDestimate(
    tmt_status ~ pmt_score, data = data, 
    cutpoint = mean(data$cutoff), bw = bw_seq[i]
    )
  rdd_tmp <- summary(rdd_tmp)$coefficients["LATE",]
  rdd_mat[i, 1] <- bw_seq[i]
  rdd_mat[i, 2] <- rdd_tmp["Estimate"]
  rdd_mat[i, 3] <- rdd_tmp["Std. Error"]
}

rdd_df <- as_tibble(rdd_mat)
colnames(rdd_df) <- c("bw", "coef", "se")

ggplot(rdd_df, aes(x = bw, y = coef)) +
  geom_point()  + 
  geom_linerange(aes(ymin = coef - 1.96 * se, ymax = coef + 1.96 * se)) +
  xlab("Bandwidth") +
  ylab("Regression coefficients & 95% CI") +
  theme_classic() +
  theme(
    axis.text = element_text(size = 12),
    axis.title = element_text(size = 14)
  )