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When Is Growth at Risk?

Author

Listed:
  • Mikkel Plagborg-Moller

    (Princeton University)

  • Lucrezia Reichlin

    (London Business School)

  • Giovanni Ricco

    (University of Warwick)

  • Thomas Hasenzagl

    (University of Minnesota)

Abstract

This paper empirically evaluates the potentially nonlinear nexus between financial indicators and the distribution of future GDP growth, using a rich set of macroeconomic and financial variables covering thirteen advanced economies. We evaluate the out-of-sample forecast performance of financial variables for GDP growth, including a fully real-time exercise based on a flexible nonparametric model. We also use a parametric model to estimate the moments of the time-varying distribution of GDP and evaluate their in-sample estimation uncertainty. Our overall conclusion is pessimistic: moments other than the conditional mean are poorly estimated, and no predictors we consider provide robust and precise advance warnings of tail risks or indeed about any features of the GDP growth distribution other than the mean. In particular, financial variables contribute little to such distributional forecasts, beyond the information contained in real indicators.

Suggested Citation

  • Mikkel Plagborg-Moller & Lucrezia Reichlin & Giovanni Ricco & Thomas Hasenzagl, 2020. "When Is Growth at Risk?," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 51(1 (Spring), pages 167-229.
    • Handle: RePEc:bin:bpeajo:v:51:y:2020:i:2020-01:p:167-229
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    Citations

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    Cited by:

    1. Xu, Qifa & Xu, Mengnan & Jiang, Cuixia & Fu, Weizhong, 2023. "Mixed-frequency Growth-at-Risk with the MIDAS-QR method: Evidence from China," Economic Systems, Elsevier, vol. 47(4).
    2. Corradi, Valentina & Fosten, Jack & Gutknecht, Daniel, 2023. "Out-of-sample tests for conditional quantile coverage an application to Growth-at-Risk," Journal of Econometrics, Elsevier, vol. 236(2).
    3. Chuliá, Helena & Garrón, Ignacio & Uribe, Jorge M., 2024. "Daily growth at risk: Financial or real drivers? The answer is not always the same," International Journal of Forecasting, Elsevier, vol. 40(2), pages 762-776.
    4. Eraslan, Sercan & Schröder, Maximilian, 2023. "Nowcasting GDP with a pool of factor models and a fast estimation algorithm," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1460-1476.
    5. Busetti, Fabio & Caivano, Michele & Delle Monache, Davide & Pacella, Claudia, 2021. "The time-varying risk of Italian GDP," Economic Modelling, Elsevier, vol. 101(C).
    6. Zheng, Tingguo & Gong, Lu & Ye, Shiqi, 2023. "Global energy market connectedness and inflation at risk," Energy Economics, Elsevier, vol. 126(C).
    7. Iseringhausen, Martin, 2024. "A time-varying skewness model for Growth-at-Risk," International Journal of Forecasting, Elsevier, vol. 40(1), pages 229-246.
    8. Gloria González‐Rivera & C. Vladimir Rodríguez‐Caballero & Esther Ruiz, 2024. "Expecting the unexpected: Stressed scenarios for economic growth," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(5), pages 926-942, August.
    9. Huang, Yu-Fan & Liao, Wenting & Wang, Taining, 2024. "Does US financial uncertainty spill over through the (asymmetric) international credit channel? The role of market expectations," Journal of International Money and Finance, Elsevier, vol. 148(C).
    10. Hongqi Chen & Ji Hyung Lee, 2024. "Predictive Quantile Regression with High-Dimensional Predictors: The Variable Screening Approach," Papers 2410.15097, arXiv.org.
    11. Yao, Shouyu & Liu, Zezhong & Wang, Chunfeng & Palma, Alessia & Goodell, John W., 2024. "Is macroeconomic tail risk contagious to stock idiosyncratic risk?," Finance Research Letters, Elsevier, vol. 63(C).
    12. Michael T. Kiley, 2024. "Growth at risk from climate change," Economic Inquiry, Western Economic Association International, vol. 62(3), pages 1134-1151, July.
    13. Forni, Mario & Gambetti, Luca & Maffei-Faccioli, Nicolò & Sala, Luca, 2024. "The effects of monetary policy on macroeconomic risk," European Economic Review, Elsevier, vol. 167(C).

    More about this item

    Keywords

    US economy; GDP growth;

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