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Government spending effects on the business cycle in times of crisis

Author

Listed:
  • Tino Berger
  • Tore Dubbert

Abstract

The literature on fiscal multipliers has long established a positive impact of public spending on output. However, the size of this effect strongly depends on the employed identification strategy. Moreover, fiscal multipliers are uninformative as regards the state of the economy. Using counterfactual scenario analyses based on a conditional forecast algorithm in combination with the Beveridge-Nelson decomposition, we address both issues by assessing the effectiveness of public spending in terms of its influence on the output gap. Our approach is independent of the chosen identification strategy and allows us to make (quantitative) statements about potential downsides from public spending measures by looking at its effects on the business cycle. Using a US dataset and analyzing hypothetical government spending scenarios in times of historical crises, we find that, to avoid an overheating of the economy in combination with high inflation and public debt, the dosage of fiscal stimulus is crucial for targeted fiscal policy measures and depends on the severity of the crisis.

Suggested Citation

  • Tino Berger & Tore Dubbert, 2022. "Government spending effects on the business cycle in times of crisis," CQE Working Papers 10022, Center for Quantitative Economics (CQE), University of Muenster.
    • Handle: RePEc:cqe:wpaper:10022
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    File URL: https://www.wiwi.uni-muenster.de/cqe/sites/cqe/files/CQE_Paper/cqe_wp_100_2022.pdf
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    References listed on IDEAS

    as
    1. James Morley & Benjamin Wong, 2020. "Estimating and accounting for the output gap with large Bayesian vector autoregressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 1-18, January.
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    5. Valerie A. Ramey, 2019. "Ten Years after the Financial Crisis: What Have We Learned from the Renaissance in Fiscal Research?," Journal of Economic Perspectives, American Economic Association, vol. 33(2), pages 89-114, Spring.
    6. repec:ulb:ulbeco:2013/13388 is not listed on IDEAS
    7. Beveridge, Stephen & Nelson, Charles R., 1981. "A new approach to decomposition of economic time series into permanent and transitory components with particular attention to measurement of the `business cycle'," Journal of Monetary Economics, Elsevier, vol. 7(2), pages 151-174.
    8. Andrew Blake & Haroon Mumtaz, 2015. "Applied Bayesian Econometrics for central bankers," Handbooks, Centre for Central Banking Studies, Bank of England, number 36, April.
    9. Berger, Tino & Morley, James & Wong, Benjamin, 2023. "Nowcasting the output gap," Journal of Econometrics, Elsevier, vol. 232(1), pages 18-34.
      • Tino Berger & James Morley & Benjamin Wong, 2020. "Nowcasting the Output Gap," CAMA Working Papers 2020-78, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    10. Daniel F. Waggoner & Tao Zha, 1999. "Conditional Forecasts In Dynamic Multivariate Models," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 639-651, November.
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    Cited by:

    1. Dubbert, Tore & Kempa, Bernd, 2024. "Nowcasting the output gap with shadow rates," Economics Letters, Elsevier, vol. 236(C).
    2. Tore Dubbert & Adrian Schroeder, 2025. "Conditioning business and financial cycles on multivariate information," CQE Working Papers 11225, Center for Quantitative Economics (CQE), University of Muenster.

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    Keywords

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    JEL classification:

    • E62 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Fiscal Policy; Modern Monetary Theory
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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