05b_compute_synthetic_control_cito.R

# Script to compute synthetic control weights
# i.e., X1, X0, Z1, Z0, and v weights for each school.
# last edited 2024-01-26 by @vankesteren
library(tidyverse)
library(furrr)
plan(multisession)
library(pensynth) # github.com/vankesteren/pensynth

# read the prepared data
synth_mats <- read_rds("processed_data/synth_mats_cito.rds")

# Compute penalized synthetic control
# use Z (pre-intervention outcomes) as cross-validation target to tune lambda
# and equally weigh pre-intervention covariates on a standardized scale
psynth_list <- future_map(
  .x = synth_mats, 
  .f = function(m) {
    try(cv_pensynth(
      X1 = m$X1,
      X0 = m$X0,
      v  = 1,
      Z1 = m$Z1,
      Z0 = m$Z0,
      nlambda = 100
    ))
  }, 
  .progress = TRUE
)
write_rds(psynth_list, "processed_data/psynth_list_cito.rds")

# Showcase: weight path
png("img/weight_path_school_1_cito.png", width = 2400, height = 1800, res = 200)
plot_path(psynth_list[[1]])
dev.off()

png("img/weights_school_11_cito.png", width = 2400, height = 1800, res = 200)
par(mfrow = c(2, 1))
barplot(psynth_list[[1]]$w_path[,1],main = "Unpenalized weights")
barplot(psynth_list[[1]]$w_opt, main = "CV penalized weights")
dev.off()