R/meta-documentation.R

In MultiATSM: Multicountry Term Structure of Interest Rates Models

#' Overview of Datasets Included in the MultiATSM Package
#'
#' The package includes several pre-processed datasets used for estimation and replication examples:
#'
#' \describe{
#'   \item{GlobalMacro}{Global macro-financial risk factors, namely global economic activity and global inflation.}
#'   \item{GlobalMacro_covid}{Global macro-financial risk factors, namely the output growth rate from the U.S. and China and the S&P 500 index.}
#'   \item{DomMacro}{Domestic macroeconomic risk factors, namely economic activity and inflation.}
#'   \item{DomMacro_covid}{Domestic macroeconomic risk factors, namely otput growth, inflation, CDS and the COVID-19 reproduction rate}
#'   \item{TradeFlows}{Bilateral trade flow series used in GVAR examples as a proxy measure of cross-country conectdness.}
#'   \item{TradeFlows_covid}{Bilateral trade flow series used in GVAR examples as a proxy measure of cross-country conectdness.}
#'   \item{Yields}{Monthly series of bond yields by maturity for multiple economies.}
#'   \item{Yields_covid}{Weekly series of sovereign bond yields by maturity for multiple economies.}
#'   \item{RiskFacFull}{Full set of risk factors (global and domestic) data used throughout the package}
#'   \item{GVARFactors}{List of risk factors used in the estimation of GVAR models.}
#'   \item{BR_jps_out}{Replications of the JPS outputs by Bauer and Rudebusch (2017)}
#'   \item{InpForOutEx}{List of inputs for an illustrative JPS model with Brazilian data}
#'   \item{ParaSetEx}{List of set of parameterafter optimization for an illustrative JPS model with Brazilian data}
#'   \item{NumOutEx}{List of numerical outputs for an illustrative JPS model with Brazilian data}
#'   \item{Out_Example}{re-loaded examaple of a complete list of several model outputs. Used in the package vignette.}
#' }
#'
#' Each dataset is documented separately using `?GlobalMacro`, `?DomMacro`, `?TradeFlows`, `?Yields`, etc.
#' Datasets ending with the suffix \code{_covid} are based on those used in Candelon and Moura (2023) and cover Brazil, India, Mexico, and Russia.
#' The remaining datasets correspond to Candelon and Moura (2024) and include Brazil, China, Mexico, and Uruguay.
#' @references
#' \enumerate{
#' \item Candelon, B. and Moura, R. (2023) "Sovereign yield curves and the COVID-19 in emerging markets". (Economic Modelling)
#' \item Candelon, B. and Moura, R. (2024) "A Multicountry Model of the Term Structures of Interest Rates with a GVAR". (Journal of Financial Econometrics)
#' }
#' @docType data
#' @aliases MultiATSM_datasets
#' @name MultiATSM_datasets
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