R/5-0-0data_acces.R

In rdlearn: Safe Policy Learning under Regression Discontinuity Design with Multiple Cutoffs

#' ACCES Program
#'
#' A dataset comprising 8245 applicants to the ACCES Program across 23 different
#' departments in Colombia, including eligibility for the ACCES Program,
#' position score of the SABER 11, cutoff of each department, and the name of
#' each department.
#'
#' @format A data frame with 8245 rows and 4 columns: \describe{
#'   \item{elig}{eligibility for the ACCES Program.
#'   1: eligible; 0: not eligible}
#'   \item{saber11}{position scores of the SABER 11.
#'   We multiply the position score by -1 so that the values of the running variable
#'   above a cutoff lead to the program eligibility.}
#'   \item{cutoff}{cutoffs of each department.}
#'   \item{department}{the names of each department.}}
#' @references Melguizo, T., F. Sanchez, and T. Velasco (2016). Credit for
#'   low-income students and access to and academic performance in higher
#'   education in colombia: A regression discontinuity approach. World
#'   development 80, 61-77.
"acces"