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Asymmetric Effects of Uncertainty over the Business Cycle: A Quantile Structural Vector Autoregressive Approach

Author

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  • Yves S. Schüler

    (Department of Economics, University of Konstanz, Germany)

Abstract

This paper proposes to relate conditional quantiles of stationary macroeconomic time series to the different phases of the business cycle. Based on this idea, I introduce a Bayesian Quantile Structural Vector Autoregressive framework for the analysis of the effects of uncertainty on the US real economy. For this purpose, I define a novel representation of the multivariate Laplace distribution that allows for the joint treatment of multiple equation regression quantiles. I find significant evidence for asymmetric effects of uncertainty over the US business cycle. The strongest negative effects are revealed during recession periods. During boom phases uncertainty shocks improve the soundness of the economy. Moreover, the phase of the financial sector matters when the real economy is at recession but not if the economy is at boom. When the financial system is in a bad state, an uncertainty shock leads to a deeper recession than in times when the financial system is in a good state.

Suggested Citation

  • Yves S. Schüler, 2014. "Asymmetric Effects of Uncertainty over the Business Cycle: A Quantile Structural Vector Autoregressive Approach," Working Paper Series of the Department of Economics, University of Konstanz 2014-02, Department of Economics, University of Konstanz.
  • Handle: RePEc:knz:dpteco:1402
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    File URL: http://www.uni-konstanz.de/FuF/wiwi/workingpaperseries/WP_02_Schueler_2014.pdf
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    References listed on IDEAS

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    Cited by:

    1. Schüler, Yves Stephan & Hiebert, Paul P. & Peltonen, Tuomas A., 2015. "Characterising the financial cycle: A multivariate and time-varying approach," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112985, Verein für Socialpolitik / German Economic Association.
    2. Pierdzioch Christian & Gupta Rangan, 2020. "Uncertainty and Forecasts of U.S. Recessions," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(4), pages 1-20, September.
    3. Korobilis, Dimitris, 2015. "Quantile forecasts of inflation under model uncertainty," 2007 Annual Meeting, July 29-August 1, 2007, Portland, Oregon TN 2015-72, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    4. Mehmet Balcilar & Zeynel Abidin Ozdemir & Huseyin Ozdemir, 2021. "Dynamic return and volatility spillovers among S&P 500, crude oil, and gold," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 153-170, January.
    5. Balcilar, Mehmet & Ozdemir, Zeynel Abidin & Ozdemir, Huseyin & Wohar, Mark E., 2020. "Transmission of US and EU Economic Policy Uncertainty Shock to Asian Economies in Bad and Good Times," IZA Discussion Papers 13274, Institute of Labor Economics (IZA).
    6. Chang, Kuang-Liang, 2021. "Do U.S. and Japanese uncertainty shocks play important roles in affecting transition mechanisms of Japanese stock market?," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    7. Tihana Skrinjaric, 2022. "Macroeconomic effects of systemic stress: a rolling spillover index approach," Public Sector Economics, Institute of Public Finance, vol. 46(1), pages 109-140.
    8. Haibo Wang & Lutfu S. Sua & Jun Huang & Jaime Ortiz & Bahram Alidaee, 2024. "Will Southeast Asia be the next global manufacturing hub? A multiway cointegration, causality, and dynamic connectedness analyses on factors influencing offshore decisions," Papers 2406.07525, arXiv.org.
    9. Fink, Fabian & Schüler, Yves S., 2015. "The transmission of US systemic financial stress: Evidence for emerging market economies," Journal of International Money and Finance, Elsevier, vol. 55(C), pages 6-26.
    10. Korobilis, Dimitris, 2015. "Quantile forecasts of inflation under model uncertainty," MPRA Paper 64341, University Library of Munich, Germany.
    11. Huiming Zhu & Xianfang Su & Yawei Guo & Yinghua Ren, 2016. "The Asymmetric Effects of Oil Price Shocks on the Chinese Stock Market: Evidence from a Quantile Impulse Response Perspective," Sustainability, MDPI, vol. 8(8), pages 1-19, August.
    12. Korobilis, Dimitris, 2017. "Quantile regression forecasts of inflation under model uncertainty," International Journal of Forecasting, Elsevier, vol. 33(1), pages 11-20.
    13. Sulkhan Chavleishvili & Simone Manganelli, 2024. "Forecasting and stress testing with quantile vector autoregression," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(1), pages 66-85, January.
    14. Rangan Gupta & Chi Keung Marco Lau & Mark E. Wohar, 2019. "The impact of US uncertainty on the Euro area in good and bad times: evidence from a quantile structural vector autoregressive model," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 46(2), pages 353-368, May.
    15. Balcilar, Mehmet & Ozdemir, Zeynel Abidin & Ozdemir, Huseyin & Aygun, Gurcan & Wohar, Mark E., 2021. "Effectives of Monetary Policy under the High and Low Economic Uncertainty States: Evidence from the Major Asian Economies," IZA Discussion Papers 14420, Institute of Labor Economics (IZA).
    16. Su, Xianfang, 2020. "Measuring extreme risk spillovers across international stock markets: A quantile variance decomposition analysis," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).

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    More about this item

    Keywords

    Uncertainty; Economic Cycles; Quantile SVAR; Multivariate Laplace;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G01 - Financial Economics - - General - - - Financial Crises

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