# name: baker_cs.R

# install.packages("haven", dependencies = TRUE)
library(haven)
# install.packages("devtools"); devtools::install_github("bcallaway11/did")
library(ggplot2)
library(did) # Callaway & Sant'Anna

baker <- read_dta("https://github.com/scunning1975/mixtape/raw/master/baker.dta")
# untreated units have effective year of 0
baker$treat_date[is.na(baker$treat_date)] <- 0 

# Estimating the effect on y2 (constant) and y (dynamic treatment)
atts <- att_gt(
  yname = "y", # LHS variable
  tname = "year", # panel time variable
  idname = "id", # firms' panel id variable
  gname = "treat_date", # first treatment period variable
  data = baker, # data
  xformla = NULL, # no covariates
  #xformla = ~ l_police, # with covariates
  est_method = "ipw", # "dr" is doubly robust. "ipw" is inverse probability weighting. "reg" is regression
  control_group = "notyettreated", # set the comparison group which is either "nevertreated" or "notyettreated" 
  bstrap = TRUE, # if TRUE compute bootstrapped SE
  biters = 1000, # number of bootstrap iterations
  print_details = FALSE, # if TRUE, print detailed results
  base_period="universal", # long-differences
  clustervars = "state", # cluster level
  panel = TRUE # whether the data is panel or repeated cross-sectional
) 

# Group-time ATTs
summary(atts)

# Simple ATT
agg_effects <- aggte(atts, type = "simple", balance_e=TRUE)
summary(agg_effects)

# Group Average ATT
agg_effects <- aggte(atts, type = "group", balance_e=TRUE)
summary(agg_effects)

# Plot group-time ATTs
ggdid(atts)

# Event-study
agg_effects_es <- aggte(atts, type = "dynamic")
summary(agg_effects_es)

# Plot event-study coefficients
ggdid(agg_effects_es)