bacon {bacondecomp} | R Documentation |
bacon() is a function that performs the Goodman-Bacon decomposition for differences-in-differences with variation in treatment timing (with or without time-varying covariates).
bacon(formula, data, id_var, time_var, quietly = F)
formula |
an object of class "formula": a symbolic representation of the model to be fitted. Must be of the form y ~ D + controls, where y is the outcome variable, D is the binary treatment indicator, and 'controls' can be any additional control variables. Do not include the fixed effects in the formula. If using '.' notation must be of the form y ~ D + . - FE1 - FE2 |
data |
a data.frame containing the variables in the model. |
id_var |
character, the name of id variable for units. |
time_var |
character, the name of time variable. |
quietly |
logical, default = FALSE, if set to TRUE then bacon() does not print the summary of estimates/weights by type (e.g. Treated vs Untreated) |
If control variables are included in the formula, then an object of class "list" with three elements:
Omega |
a number between 0 and 1, the weight of the within timing group coefficient |
beta_hat_w |
a number, the within timing group coefficient |
two_by_twos |
a data.frame with the covariate adjusted 2x2 estimates and weights |
If not control variables are included then only the two_by_twos data.frame is returned.
# Castle Doctrine (Uncontrolled) df_bacon <- bacon(l_homicide ~ post, data = bacondecomp::castle, id_var = "state", time_var = "year") # Castle Doctrine (Controlled) ret_bacon <- bacon(l_homicide ~ post + l_pop + l_income, data = bacondecomp::castle, id_var = "state", time_var = "year")