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Time variation in the dynamic effects of unanticipated changes in tax policy

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  • Joris de Wind

Abstract

Using a structural vector autoregression with time-varying parameters, I analyze to what extent the dynamic effects of unanticipated changes in tax policy have changed structurally over the post World War II period in the United States. Read also: CPB Discussion Paper 270 'Reduced-rank time-varying vector autoregressions'. The estimated time variation points to a permanent decline in the tax multiplier as well as a faster response of the economy. Despite the permanent decline, the estimated tax multiplier is still at the higher end of the range of existing empirical estimates, which is consistent with Mertens and Ravn (2013b), whose identification strategy I follow. Furthermore, the estimated time variation also suggests that fiscal policy has become more countercyclical over time. In particular, spending policy used to be procyclical and has become countercyclical after the beginning of the 1990s, whereas tax policy already used to be countercyclical and has become even more countercyclical over time.

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  • Joris de Wind, 2014. "Time variation in the dynamic effects of unanticipated changes in tax policy," CPB Discussion Paper 271, CPB Netherlands Bureau for Economic Policy Analysis.
    • Handle: RePEc:cpb:discus:271
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    References listed on IDEAS

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    1. Alan J. Auerbach & Yuriy Gorodnichenko, 2012. "Measuring the Output Responses to Fiscal Policy," American Economic Journal: Economic Policy, American Economic Association, vol. 4(2), pages 1-27, May.
    2. Andrew Mountford & Harald Uhlig, 2009. "What are the effects of fiscal policy shocks?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(6), pages 960-992.
    3. Koop, Gary & Korobilis, Dimitris, 2010. "Bayesian Multivariate Time Series Methods for Empirical Macroeconomics," Foundations and Trends(R) in Econometrics, now publishers, vol. 3(4), pages 267-358, July.
    4. Lawrence Christiano & Martin Eichenbaum & Sergio Rebelo, 2011. "When Is the Government Spending Multiplier Large?," Journal of Political Economy, University of Chicago Press, vol. 119(1), pages 78-121.
    5. Sims, Christopher A & Zha, Tao, 1998. "Bayesian Methods for Dynamic Multivariate Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 949-968, November.
    6. Christiane Baumeister & Gert Peersman, 2013. "Time-Varying Effects of Oil Supply Shocks on the US Economy," American Economic Journal: Macroeconomics, American Economic Association, vol. 5(4), pages 1-28, October.
    7. Karel Mertens & Morten O. Ravn, 2013. "The Dynamic Effects of Personal and Corporate Income Tax Changes in the United States," American Economic Review, American Economic Association, vol. 103(4), pages 1212-1247, June.
    8. Giorgio E. Primiceri, 2005. "Time Varying Structural Vector Autoregressions and Monetary Policy," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(3), pages 821-852.
    9. Joris de Wind & Luca Gambetti, 2014. "Reduced-rank time-varying vector autoregressions," CPB Discussion Paper 270.rdf, CPB Netherlands Bureau for Economic Policy Analysis.
    10. Alan J. Auerbach, 2008. "Federal Budget Rules: The US Experience," NBER Working Papers 14288, National Bureau of Economic Research, Inc.
    11. Joris de Wind & Luca Gambetti, 2014. "Reduced-rank time-varying vector autoregressions," CPB Discussion Paper 270, CPB Netherlands Bureau for Economic Policy Analysis.
    12. Olivier Blanchard & Roberto Perotti, 2002. "An Empirical Characterization of the Dynamic Effects of Changes in Government Spending and Taxes on Output," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 117(4), pages 1329-1368.
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    Cited by:

    1. Joris de Wind & Luca Gambetti, 2014. "Reduced-rank time-varying vector autoregressions," CPB Discussion Paper 270.rdf, CPB Netherlands Bureau for Economic Policy Analysis.
    2. Hachula, Michael & Nautz, Dieter, 2018. "The dynamic impact of macroeconomic news on long-term inflation expectations," Economics Letters, Elsevier, vol. 165(C), pages 39-43.
    3. Joris de Wind & Luca Gambetti, 2014. "Reduced-rank time-varying vector autoregressions," CPB Discussion Paper 270, CPB Netherlands Bureau for Economic Policy Analysis.
    4. Pascal Paul, 2020. "The Time-Varying Effect of Monetary Policy on Asset Prices," The Review of Economics and Statistics, MIT Press, vol. 102(4), pages 690-704, October.

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    More about this item

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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