us_fiscal_lsuw {bsvars}

A 3-variable US fiscal system for the period 1948 Q1 – 2023 Q2

Description

A system used to identify the US fiscal policy shocks.

Usage

data(us_fiscal_lsuw)

Format

A matrix and a ts object with time series of 302 observations on 3 variables:

ttr

quarterly US total tax revenue expressed in log, real, per person terms

gs

quarterly US total government spending expressed in log, real, per person terms

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 :

• The sample period is from quarter 1 of 1948 to quarter 2 of 2023,

• 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.

Source

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/

References

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.

Examples

data(us_fiscal_lsuw)   # upload the data
plot(us_fiscal_lsuw)   # plot the data