Testing out the new tidysynth package on Cunningham (2021, chap 10.)

mixtape-tidysynth.R

# Libraries ---------------------------------------------------------------

library(tidysynth)
library(haven)


# Data --------------------------------------------------------------------

texas = read_dta('https://raw.github.com/scunning1975/mixtape/master/texas.dta')


# Set & run the SC --------------------------------------------------------

texas_synth =
	texas %>%
	## Initialize the synthetic control object
	synthetic_control(
		outcome = bmprison, # outcome
		unit = state, # unit index in the panel data
		time = year, # time index in the panel data
		i_unit = 'Texas', # unit where the intervention occurred
		i_time = 1994, # time period when the intervention occurred
		generate_placebos = TRUE # generate placebo synthetic controls (for inference)
		) %>%
	## Generate the aggregate predictors used to fit the weights...
	generate_predictor(
		time_window = 1988,	
		bmprison = mean(bmprison, na.rm = T)
		) %>%
	## 1990 vars 
	generate_predictor(
		time_window = 1990,
		alcohol = mean(alcohol, na.rm=T),
		perc1519 = mean(perc1519, na.rm=T)) %>%
	## 1990 - 1991 vars
	generate_predictor(
		time_window = 1990:1991,
		aidscapita = mean(aidscapita, na.rm = T)
		) %>%
	## 1990:1992 vars
	generate_predictor(
		time_window = 1990:1992,
		black = mean(black, na.rm = T)
		) %>%
	## Generate the fitted weights for the synthetic control
	generate_weights(
		optimization_window = 1985:1993 ## time to use in the optimization task
		) %>%
	# Generate the synthetic control
	generate_control()


# Plots -------------------------------------------------------------------

## Fig. 10.9
plot_trends(texas_synth)

## Fig. 10.10
plot_differences(texas_synth)

## Donor weights
plot_weights(texas_synth)

## Fig 10.12
plot_placebos(texas_synth)