| us_fiscal_lsuw {bsvars} | R Documentation |
A system used to identify the US fiscal policy shocks.
data(us_fiscal_lsuw)
A matrix and a ts object with time series of 288 observations on 3 variables:
quarterly US total tax revenue expressed in log, real, per person terms
quarterly US total government spending expressed in log, real, per person terms
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 :
The sample period is from quarter 1 of 1950 to quarter 4 of 2021,
The population variable is not from Francis & Ramey (2009) but from the FRED (with the same definition),
The original monthly population data is transformed to quarterly by taking monthly averages.
U.S. Bureau of Economic Analysis, National Income and Product Accounts, https://www.bea.gov/products/national-income-and-product-accounts
FRED Economic Database, Federal Reserve Bank of St. Louis, https://fred.stlouisfed.org/
Francis, N., and Ramey, V.A. (2009) Measures of per capita Hours and Their Implications for the Technology‐hours Debate. 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, 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. (2022) Partial Identification of Heteroskedastic Structural VARs: Theory and Bayesian Inference.
data(us_fiscal_lsuw) # upload the data
plot(us_fiscal_lsuw) # plot the data