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Identifying Discretionary Fiscal Policy Reactions with Real-Time Data

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  • ULF VON KALCKREUTH
  • GUNTRAM B. WOLFF

Abstract

We propose a method of identifying discretionary fiscal policy reactions using real‐time data. Automatic stabilizers should depend on true GDP, while discretionary fiscal policy is contingent on the information that policy makers have in real time. We can compute a real‐time measurement error by comparing the first release of GDP data with later revisions. Discretionary fiscal policy is influenced by this measurement error, whereas automatic fiscal policy is not. We use this identification approach to test the central identifying assumption of Blanchard and Perotti’s (2002) seminal structural vector autoregression (VAR). According to this assumption, fiscal policy makers do not react to GDP developments contemporaneously in a discretionary fashion. We find that government expenditure is adjusted upward if GDP growth in real time is lower than true GDP. This suggests that fiscal policy makers use short‐term funds to buy goods and services in response to their perception of GDP dynamics.
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Suggested Citation

  • Ulf Von Kalckreuth & Guntram B. Wolff, 2011. "Identifying Discretionary Fiscal Policy Reactions with Real-Time Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 43(6), pages 1271-1285, September.
    • Handle: RePEc:mcb:jmoncb:v:43:y:2011:i:6:p:1271-1285
    DOI: j.1538-4616.2011.00425.x
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    1. Alan S. Blinder, 2004. "The Case Against the Case Against Discretionary Fiscal Policy," Working Papers 102, Princeton University, Department of Economics, Center for Economic Policy Studies..
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    8. Alan J. Auerbach, 2002. "Is there a role for discretionary fiscal policy?," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, pages 109-150.
    9. Tenhofen Jörn & Wolff Guntram B. & Heppke-Falk Kirsten H., 2010. "The Macroeconomic Effects of Exogenous Fiscal Policy Shocks in Germany: A Disaggregated SVAR Analysis," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 230(3), pages 328-355, June.
    10. S. Borağan Aruoba, 2008. "Data Revisions Are Not Well Behaved," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(2‐3), pages 319-340, March.
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    Cited by:

    1. Yutaka Kurihara, 2017. "Recent monetary policy effects on Japanese macroeconomy," Journal of Economic and Financial Studies (JEFS), LAR Center Press, vol. 5(5), pages 12-17, October.
    2. Jacopo Cimadomo, 2016. "Real-Time Data And Fiscal Policy Analysis: A Survey Of The Literature," Journal of Economic Surveys, Wiley Blackwell, vol. 30(2), pages 302-326, April.
    3. Yutaka Kurihara, 2016. "Can the Disparity between GDP and GDP Forecast Cause Economic Instability? The Recent Japanese Case," International Journal of Economics and Financial Research, Academic Research Publishing Group, vol. 2(8), pages 155-160, 08-2016.
    4. repec:spo:wpmain:info:hdl:2441/5a3rl1um0d9rdbe3itnk6f8m89 is not listed on IDEAS
    5. Pierre Aldama & Jérôme Creel, 2020. "Asymmetric Macroeconomic Stabilization And Fiscal Consolidation In The Oecd And The Euro Area," SciencePo Working papers Main hal-03403071, HAL.
    6. repec:hal:spmain:info:hdl:2441/5a3rl1um0d9rdbe3itnk6f8m89 is not listed on IDEAS
    7. Aldama, Pierre & Creel, Jérôme, 2022. "Real-time fiscal policy responses in the OECD from 1997 to 2018: Procyclical but sustainable?," European Journal of Political Economy, Elsevier, vol. 73(C).

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