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#' @title A 3-variable US fiscal system for the period 1948 Q1 -- 2024 Q2
#'
#' @description A system used to identify the US fiscal policy shocks.
#' Last data update was implemented on 2024-10-20.
#'
#' @usage data(us_fiscal_lsuw)
#'
#' @format A matrix and a \code{ts} object with time series of over three hundred observations on 3 variables:
#' \describe{
#' \item{ttr}{quarterly US total tax revenue expressed in log, real, per person terms}
#' \item{gs}{quarterly US total government spending expressed in log, real, per person terms}
#' \item{gdp}{quarterly US gross domestic product expressed in log, real, per person terms}
#' }
#'
#' The series are as described by Mertens & Ravn (2014) in footnote 3 and main body on page S3 of the paper.
#' Differences with respect to Mertens & Ravn's data :
#' \itemize{
#' \item The sample period is from quarter 1 of 1948 to the last available observation,
#' \item The population variable is not from Francis & Ramey (2009) but from the FRED (with the same definition),
#' \item The original monthly population data is transformed to quarterly by taking monthly averages.
#' }
#'
#' @references
#' Francis, N., and Ramey, V.A. (2009) Measures of per capita Hours and Their Implications for the Technology‐hours Debate. \emph{Journal of Money, Credit and Banking}, 41(6), 1071-1097, DOI: \doi{10.1111/j.1538-4616.2009.00247.x}.
#'
#' Mertens, K., and Ravn, M.O. (2014) A Reconciliation of SVAR and Narrative Estimates of Tax Multipliers, \emph{Journal of Monetary Economics}, 68(S), S1–S19. DOI: \doi{10.1016/j.jmoneco.2013.04.004}.
#'
#' Lütkepohl, H., Shang, F., Uzeda, L., and Woźniak, T. (2024) Partial Identification of Heteroskedastic Structural VARs: Theory and Bayesian Inference. \emph{University of Melbourne Working Paper}, 1--57, \doi{10.48550/arXiv.2404.11057}.
#'
#' @source
#' U.S. Bureau of Economic Analysis, National Income and Product Accounts, \url{https://www.bea.gov/}
#'
#' FRED Economic Database, Federal Reserve Bank of St. Louis, \url{https://fred.stlouisfed.org/}
#'
#' @examples
#' data(us_fiscal_lsuw) # upload the data
#' plot(us_fiscal_lsuw) # plot the data
"us_fiscal_lsuw"
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