R/eba_impairments_2016.R

In Martin-Summer-1090/syslosseval: Provide data and functions to support the analysis in Systemic Loss Evaluation

#' Impairment data of 51 European banks which took part in the EBA stress test
#' 2016.
#'
#' A dataset containing the impairment data of 51 European banks who took part
#' in the EBA stress test 2016. The data are compiled from a raw data set. The
#' script of compiling the data from the raw data can be inspected by editing
#' the file make_balance_sheet_data.R in the raw-data folder of the syslosseval
#' package source code.
#'
#' @format A data frame with 15480 rows and 8 variables:
#' \describe{
#'   \item{LEI_code}{LEI_code, legal entity identifyer of a bank. chr.}
#'   \item{Country_code}{Country_code, ISO-code of the country where the bank is
#'   domiciled, chr.}
#'   \item{Bank_name}{Bank_name, Name of the bank, chr.}
#'   \item{Period}{Period, Reporting period of the data given as 201612 (31.
#'   December 2015). There are three impairment periods in total. num}
#'   \item{Scenario}{Scenario, reports whether it is the baseline or the stress
#'   scenario, chr}
#'   \item{Country}{Country, Country to which the bank is exposed.
#'   This is either a ISO code like AT, DE etc. or it is called Total if it is
#'   the overall exposure aggregated across all countries, or there are special
#'   abbreviations which are further explained in the EBA metadata in the
#'   raw-data folder. They are not relevant for our analysis and not described
#'   further here. chr}
#'   \item{Exposure}{Asset class according to the IRB
#'   classification scheme. chr}
#'   \item{Impairment_rate}{Impairment_rate, the
#'   Impairment rate in percentage according to the EBA 2016 stress test. num} }
#' @source
#'   \url{https://eba.europa.eu/risk-analysis-and-data/eu-wide-stress-testing/2016}
"eba_impairments_2016"