bacon function

Goodman-Bacon Decomposition

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)

Arguments

• 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)

Returns

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.

Examples

# 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")