% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data.R
\docType{data}
\name{us_gdp_vintage}
\alias{us_gdp_vintage}
\title{US Real GDP — FRED Vintage}
\format{
A \code{data.table} with one row per quarter and three columns:
\describe{
\item{\code{date}}{\code{Date}. Quarter start date (e.g. \code{1947-01-01} = 1947 Q1).}
\item{\code{gdp_real}}{\code{numeric}. Real GDP level, billions of chained 2017 USD.}
\item{\code{gdp_log}}{\code{numeric}. Natural logarithm of \code{gdp_real}, pre-computed
for convenience.}
}
}
\source{
Federal Reserve Bank of St. Louis — FRED Economic Data,
series GDPC1. Downloaded via the public CSV endpoint
\verb{https://fred.stlouisfed.org/graph/fredgraph.csv?id=GDPC1}.
See \code{data-raw/us_gdp_vintage.R} for the reproducible download script.
}
\usage{
us_gdp_vintage
}
\description{
Quarterly US Real Gross Domestic Product from the Federal Reserve Bank of
St. Louis (FRED) public data API (series \strong{GDPC1}), expressed in billions
of chained 2017 US dollars, seasonally adjusted annual rate.
}
\details{
The dataset covers 1947 Q1 through the latest vintage available at download
time (approximately 316 rows as of 2025). Rows with \code{NA} in \code{gdp_real} are
excluded.

The log-level column (\code{gdp_log}) is particularly useful for trend-cycle
decomposition because log-differences approximate quarter-on-quarter
percentage growth rates:
\deqn{\Delta \log(\text{GDP}_t) \approx g_t}
}
\examples{
data("us_gdp_vintage", package = "MacroFilters")
head(us_gdp_vintage)
plot(us_gdp_vintage$date, us_gdp_vintage$gdp_log,
     type = "l", xlab = "Date", ylab = "Log Real GDP",
     main = "US Real GDP (log level)")
}
\keyword{datasets}
