install.packages("bacondecomp")

library(devtools)
install_github("evanjflack/bacondecomp")

library(bacondecomp)
#> Loading required package: fixest
#> fixest 0.9.0, BREAKING changes! (Permanently remove this message with fixest_startup_msg(FALSE).) 
#> - In i():
#>     + the first two arguments have been swapped! Now it's i(factor_var, continuous_var) for interactions. 
#>     + argument 'drop' has been removed (put everything in 'ref' now).
#> - In feglm(): 
#>     + the default family becomes 'gaussian' to be in line with glm(). Hence, for Poisson estimations, please use fepois() instead.
df_bacon <- bacon(incearn_ln ~ reform_math,
                  data = bacondecomp::math_reform,
                  id_var = "state",
                  time_var = "class")
                  
# All 2x2 Comparisons
head(df_bacon)
#>    treated untreated    estimate      weight                     type
#> 2     1987      1985  0.04575585 0.031655309 Later vs Earlier Treated
#> 4     1986      1985  0.11390411 0.001978457 Later vs Earlier Treated
#> 5     1984      1985  0.12012908 0.001978457 Earlier vs Later Treated
#> 6     1985      1987  0.01021379 0.039569136 Earlier vs Later Treated
#> 9     1986      1987 -0.09374495 0.005440756 Earlier vs Later Treated
#> 10    1984      1987  0.09784857 0.013354583 Earlier vs Later Treated
# Summary of Early vs. Later, Later vs. Earlier, and Treated vs. Untreated
bacon_summary(df_bacon)
#>                       type  weight  avg_est
#> 1 Earlier vs Later Treated 0.06353  0.02868
#> 2 Later vs Earlier Treated 0.05265  0.03375
#> 3     Treated vs Untreated 0.88382 -0.00129

library(ggplot2)

ggplot(df_bacon) +
  aes(x = weight, y = estimate, shape = factor(type)) +
  geom_point() +
  geom_hline(yintercept = 0) + 
  theme_minimal() +
  labs(x = "Weight", y = "Estimate", shape = "Type")