IDEAS home Printed from https://ideas.repec.org/p/ecb/ecbwps/20232808.html
   My bibliography  Save this paper

Medium-term growth-at-risk in the euro area

Author

Listed:
  • Lang, Jan Hannes
  • Rusnák, Marek
  • Greiwe, Moritz

Abstract

Financial stability indicators can be grouped into financial stress indicators that reflect heightened spreads and market volatility, and financial vulnerability indicators that reflect credit and asset price imbalances. Based on a panel of euro area countries, we show that both types of indicators contain information about downside risks to real GDP growth (growth-at-risk) in the short-term (1-year ahead). However, only vulnerability indicators contain information about growth-at-risk in the medium-term (3-years ahead and beyond). Among various vulnerability indicators suggested in the literature, the Systemic Risk Indicator (SRI) proposed by Lang et al. (2019) outperforms in terms of in-sample explanatory power and out-of-sample predictive ability for medium-term growth-at-risk in euro area countries. Shocks to the SRI induce a rich ”term structure” for growth-at-risk: downside risks to real GDP growth are reduced in the short-term, but over the medium-term the effect reverses and downside risks to real GDP growth go up considerably. We also show that using cross-country information from the panel of euro area countries can improve the out-of-sample forecasting performance of growth-at-risk for the euro area aggregate. JEL Classification: E37, E44, G01, G17, C22

Suggested Citation

  • Lang, Jan Hannes & Rusnák, Marek & Greiwe, Moritz, 2023. "Medium-term growth-at-risk in the euro area," Working Paper Series 2808, European Central Bank.
  • Handle: RePEc:ecb:ecbwps:20232808
    Note: 2731285
    as

    Download full text from publisher

    File URL: https://www.ecb.europa.eu//pub/pdf/scpwps/ecb.wp2808~573fdb4019.en.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lucrezia Reichlin & Giovanni Ricco & Thomas Hasenzagl, 2020. "Financial Variables as Predictors of Real Growth Vulnerability," Documents de Travail de l'OFCE 2020-06, Observatoire Francais des Conjonctures Economiques (OFCE).
    2. 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.
    3. Laura Nowzohour & Livio Stracca, 2020. "More Than A Feeling: Confidence, Uncertainty, And Macroeconomic Fluctuations," Journal of Economic Surveys, Wiley Blackwell, vol. 34(4), pages 691-726, September.
    4. Ivan A. Canay, 2011. "A simple approach to quantile regression for panel data," Econometrics Journal, Royal Economic Society, vol. 14(3), pages 368-386, October.
    5. Acharya, Sushant & Benhabib, Jess & Huo, Zhen, 2021. "The anatomy of sentiment-driven fluctuations," Journal of Economic Theory, Elsevier, vol. 195(C).
    6. Bernanke, Ben S. & Gertler, Mark & Gilchrist, Simon, 1999. "The financial accelerator in a quantitative business cycle framework," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 21, pages 1341-1393, Elsevier.
    7. Adams, Patrick A. & Adrian, Tobias & Boyarchenko, Nina & Giannone, Domenico, 2021. "Forecasting macroeconomic risks," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1173-1191.
    8. Kremer, Manfred & Lo Duca, Marco & Holló, Dániel, 2012. "CISS - a composite indicator of systemic stress in the financial system," Working Paper Series 1426, European Central Bank.
    9. Hartwig, Benny & Meinerding, Christoph & Schüler, Yves S., 2021. "Identifying indicators of systemic risk," Journal of International Economics, Elsevier, vol. 132(C).
    10. Alessi, Lucia & Detken, Carsten, 2011. "Quasi real time early warning indicators for costly asset price boom/bust cycles: A role for global liquidity," European Journal of Political Economy, Elsevier, vol. 27(3), pages 520-533, September.
    11. repec:ecb:ecbwps:20111426 is not listed on IDEAS
    12. Falconio, Andrea & Manganelli, Simone, 2020. "Financial conditions, business cycle fluctuations and growth at risk," Working Paper Series 2470, European Central Bank.
    13. Aikman, David & Bridges, Jonathan & Burgess, Stephen & Galletly, Richard & Levina, Iren & O'Neill, Cian & Varadi, Alexandra, 2018. "Measuring risks to UK financial stability," Bank of England working papers 738, Bank of England.
    14. Giacomini, Raffaella & Komunjer, Ivana, 2005. "Evaluation and Combination of Conditional Quantile Forecasts," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 416-431, October.
    15. Ferrara, Laurent & Mogliani, Matteo & Sahuc, Jean-Guillaume, 2022. "High-frequency monitoring of growth at risk," International Journal of Forecasting, Elsevier, vol. 38(2), pages 582-595.
    16. Brownlees, Christian & Souza, André B.M., 2021. "Backtesting global Growth-at-Risk," Journal of Monetary Economics, Elsevier, vol. 118(C), pages 312-330.
    17. Galina Besstremyannaya & Sergei Golovan, 2019. "Reconsideration of a simple approach to quantile regression for panel data," The Econometrics Journal, Royal Economic Society, vol. 22(3), pages 292-308.
    18. Thibaut Duprey & Alexander Ueberfeldt, 2020. "Managing GDP Tail Risk," Staff Working Papers 20-3, Bank of Canada.
    19. Figueres, Juan Manuel & Jarociński, Marek, 2020. "Vulnerable growth in the euro area: Measuring the financial conditions," Economics Letters, Elsevier, vol. 191(C).
    20. Mathias Drehmann & Anamaria Illes & Mikael Juselius & Marjorie Santos, 2015. "How much income is used for debt payments? A new database for debt service ratios," BIS Quarterly Review, Bank for International Settlements, September.
    21. Martin Gächter & Martin Geiger & Elias Hasler, 2023. "On the Structural Determinants of Growth-at-Risk," International Journal of Central Banking, International Journal of Central Banking, vol. 19(2), pages 251-293, June.
    22. De Santis, Roberto A. & Van der Veken, Wouter, 2020. "Forecasting macroeconomic risk in real time: Great and Covid-19 Recessions," Working Paper Series 2436, European Central Bank.
    23. Lang, Jan Hannes & Izzo, Cosimo & Fahr, Stephan & Ruzicka, Josef, 2019. "Anticipating the bust: a new cyclical systemic risk indicator to assess the likelihood and severity of financial crises," Occasional Paper Series 219, European Central Bank.
    24. Tobias Adrian & Federico Grinberg & Nellie Liang & Sheheryar Malik & Jie Yu, 2022. "The Term Structure of Growth-at-Risk," American Economic Journal: Macroeconomics, American Economic Association, vol. 14(3), pages 283-323, July.
    25. repec:hal:spmain:info:hdl:2441/4nn4ojjkth8qe9ci5b0hpu7ala is not listed on IDEAS
    26. Giglio, Stefano & Kelly, Bryan & Pruitt, Seth, 2016. "Systemic risk and the macroeconomy: An empirical evaluation," Journal of Financial Economics, Elsevier, vol. 119(3), pages 457-471.
    27. Claudio Borio & Mathias Drehmann, 2009. "Assessing the risk of banking crises - revisited," BIS Quarterly Review, Bank for International Settlements, March.
    28. Carsten Detken & Olaf Weeken & Lucia Alessi & Diana Bonfim & Miguel M. Boucinha & Christian Castro & Sebastian Frontczak & Gaston Giordana & Julia Giese & Nadya Jahn & Jan Kakes & Benjamin Klaus & Jan, 2014. "Operationalising the countercyclical capital buffer: indicator selection, threshold identification and calibration options," ESRB Occasional Paper Series 05, European Systemic Risk Board.
    29. Chavleishvili, Sulkhan & Manganelli, Simone, 2019. "Forecasting and stress testing with quantile vector autoregression," Working Paper Series 2330, European Central Bank.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chavleishvili, Sulkhan & Fahr, Stephan & Kremer, Manfred & Manganelli, Simone & Schwaab, Bernd, 2021. "A risk management perspective on macroprudential policy," Working Paper Series 2556, European Central Bank.
    2. Aikman, David & Bridges, Jonathan & Hacioglu Hoke, Sinem & O’Neill, Cian & Raja, Akash, 2019. "Credit, capital and crises: a GDP-at-Risk approach," Bank of England working papers 824, Bank of England, revised 18 Oct 2019.
    3. Lhuissier, Stéphane, 2022. "Financial conditions and macroeconomic downside risks in the euro area," European Economic Review, Elsevier, vol. 143(C).
    4. Ferrara, Laurent & Mogliani, Matteo & Sahuc, Jean-Guillaume, 2022. "High-frequency monitoring of growth at risk," International Journal of Forecasting, Elsevier, vol. 38(2), pages 582-595.
    5. James Mitchell & Aubrey Poon & Dan Zhu, 2022. "Constructing Density Forecasts from Quantile Regressions: Multimodality in Macro-Financial Dynamics," Working Papers 22-12R, Federal Reserve Bank of Cleveland, revised 11 Apr 2023.
    6. Todd E. Clark & Florian Huber & Gary Koop & Massimiliano Marcellino & Michael Pfarrhofer, 2023. "Tail Forecasting With Multivariate Bayesian Additive Regression Trees," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 64(3), pages 979-1022, August.
    7. Cabral, Inês & Detken, Carsten & Fell, John & Henry, Jérôme & Hiebert, Paul & Kapadia, Sujit & Pires, Fatima & Salleo, Carmelo & Constâncio, Vítor & Nicoletti Altimari, Sergio, 2019. "Macroprudential policy at the ECB: Institutional framework, strategy, analytical tools and policies," Occasional Paper Series 227, European Central Bank.
    8. Jorge E. Galán, 2020. "The benefits are at the tail: uncovering the impact of macroprudential policy on growth-at-risk," Working Papers 2007, Banco de España.
    9. Lang, Jan Hannes & Izzo, Cosimo & Fahr, Stephan & Ruzicka, Josef, 2019. "Anticipating the bust: a new cyclical systemic risk indicator to assess the likelihood and severity of financial crises," Occasional Paper Series 219, European Central Bank.
    10. Stolbov, Mikhail & Shchepeleva, Maria, 2022. "Modeling global real economic activity: Evidence from variable selection across quantiles," The Journal of Economic Asymmetries, Elsevier, vol. 25(C).
    11. Wang, Bo & Li, Haoran, 2021. "Downside risk, financial conditions and systemic risk in China," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    12. Borio, Claudio & Drehmann, Mathias & Xia, Fan Dora, 2020. "Forecasting recessions: the importance of the financial cycle," Journal of Macroeconomics, Elsevier, vol. 66(C).
    13. Andrea Carriero & Todd E. Clark & Marcellino Massimiliano, 2020. "Nowcasting Tail Risks to Economic Activity with Many Indicators," Working Papers 20-13R2, Federal Reserve Bank of Cleveland, revised 22 Sep 2020.
    14. Suarez, Javier, 2022. "Growth-at-risk and macroprudential policy design," Journal of Financial Stability, Elsevier, vol. 60(C).
    15. Bochmann, Paul & Dieckelmann, Daniel & Fahr, Stephan & Ruzicka, Josef, 2023. "Financial stability considerations in the conduct of monetary policy," Working Paper Series 2870, European Central Bank.
    16. Botelho, Vasco & Foroni, Claudia & Renzetti, Andrea, 2023. "Labour at risk," Working Paper Series 2840, European Central Bank.
    17. Jorge E. Galán & María Rodríguez Moreno, 2020. "At-risk measures and financial stability," Revista de Estabilidad Financiera, Banco de España, issue Autumn.
    18. 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.
    19. Jorge E. Galán & Javier Mencía, 2021. "Model-based indicators for the identification of cyclical systemic risk," Empirical Economics, Springer, vol. 61(6), pages 3179-3211, December.

    More about this item

    Keywords

    financial stress; financial vulnerabilities; growth-at-risk; local projections; quantile regression;
    All these keywords.

    JEL classification:

    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G01 - Financial Economics - - General - - - Financial Crises
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ecb:ecbwps:20232808. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Official Publications (email available below). General contact details of provider: https://edirc.repec.org/data/emieude.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.