Fit a wage model with fixed effects — model

Fits a linear wage model based on a set of predictors and fixed effects.

Usage

model_wage(
  data,
  outcome_var = "gross_salary_lcu",
  predictor_vars = c("contract_type", "occupation_native", "educat7", "whours",
    "paygrade"),
  fixed_effects_vars = c("personnel_id", "est_id", "ref_date")
)

Arguments

data: A data frame containing the outcome, predictor, and fixed effects columns.
outcome_var: Character. Name of the outcome column. Default "gross_salary_lcu".
predictor_vars: A character vector. Names of predictor columns. Default c("contract_type", "occupation_native", "educat7", "whours", "paygrade").
fixed_effects_vars: Character vector, or NULL to fit without fixed effects. Names of fixed effects columns. Default c("personnel_id", "est_id", "ref_date").

Value

A fixest model object, as returned by fixest::feols().

Details

outcome_var and fixed_effects_vars are required to be present in data. predictor_vars are covariates and are dropped with a warning rather than failing the whole call; if none remain, the model is fit with an intercept-only right-hand side (1).