RCT (version 1.2)

impact_eval: Impact Evaluation of Treatment Effects

Description

Impact Evaluation of Treatment Effects

Usage

impact_eval(
  data,
  endogenous_vars,
  treatment,
  heterogenous_vars,
  fixed_effect_vars = NULL,
  control_vars,
  cluster_var
)

Value

impact_eval() returns a list of regression tables. The names of the list are the same as the endogenous variables. for heterogeneities the names are endogenous_var_heterogenous_var

Arguments

data

A data.frame, tibble or data.table

endogenous_vars

Vector of Y's on which treatment effects will be evaluated

treatment

Variable indicating the treatment status

heterogenous_vars

Vector of variables for which you wish to assess treatment distributions/heterogeneities.

fixed_effect_vars

Vector of variables to add as fixed effects. Default is without fixed effects

control_vars

Vector of variables to control for in the evaluation. Default is without controls

cluster_var

String of cluster variable the standard errors. Default is without clustered std errors

Details

This function carries out the evaluation of treatment effects on endogenous variables. It automatically runs the regressions of all the endogenous_vars supplied & all the combinations of endogenous_vars and heterogenous_vars. Additionally, the function has the option of include fixed_effects, controls and cluster variables for clustered std errors.

Examples

data <- data.frame(y_1 = rnorm(n = 100, mean = 100, sd = 15), 
                  y_2 = rnorm(n = 100, mean = 8, sd = 2), 
                  treat = rep(c(0,1,2,3), each = 25), 
                  heterogenous_var1 = rep(c("X_Q1", "X_Q2", "X_Q3", "X_Q4"), times = 25),
                  cluster_var1 = rep(c(1:5), times = 20), 
                  fixed_effect_var1 = rep(c(1,2), times = 50),
                  control_var1 = rnorm(n = 100, mean = 20, sd = 1))

evaluation<-impact_eval(data = data, 
                       endogenous_vars = c("y_1", "y_2"), 
                       treatment = "treat", 
                       heterogenous_vars = c("heterogenous_var1"), 
                       cluster_var = "cluster_var1", fixed_effect_vars = c("fixed_effect_var1"), 
                       control_vars = c("control_var1"))