IDEAS home Printed from https://ideas.repec.org/p/ecb/ecbwps/20212565.html
   My bibliography  Save this paper

The risk management approach to macro-prudential policy

Author

Listed:
  • Chavleishvili, Sulkhan
  • Engle, Robert F.
  • Fahr, Stephan
  • Kremer, Manfred
  • Manganelli, Simone
  • Schwaab, Bernd

Abstract

Macro-prudential authorities need to assess medium-term downside risks to the real economy, caused by severe financial shocks. Before activating policy measures, they also need to consider their short-term negative impact. This gives rise to a risk management problem, an inter-temporal trade-off between expected growth and downside risk. Predictive distributions are estimated with structural quantile vector autoregressive models that relate economic growth to measures of financial stress and the financial cycle. An empirical study with euro area and U.S. data shows how to construct indicators of macro-prudential policy stance and to assess when interventions may be beneficial. JEL Classification: G21, C33

Suggested Citation

  • Chavleishvili, Sulkhan & Engle, Robert F. & Fahr, Stephan & Kremer, Manfred & Manganelli, Simone & Schwaab, Bernd, 2021. "The risk management approach to macro-prudential policy," Working Paper Series 2565, European Central Bank.
    • Handle: RePEc:ecb:ecbwps:20212565
    Note: 373346
    as

    Download full text from publisher

    File URL: https://www.ecb.europa.eu//pub/pdf/scpwps/ecb.wp2565~e7b85e3982.en.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Aikman, David & Kiley, Michael & Lee, Seung Jung & Palumbo, Michael G. & Warusawitharana, Missaka, 2017. "Mapping heat in the U.S. financial system," Journal of Banking & Finance, Elsevier, vol. 81(C), pages 36-64.
    2. Schüler, Yves S. & Hiebert, Paul P. & Peltonen, Tuomas A., 2020. "Financial cycles: Characterisation and real-time measurement," Journal of International Money and Finance, Elsevier, vol. 100(C).
    3. Tobias Adrian & Nina Boyarchenko & Domenico Giannone, 2021. "Multimodality In Macrofinancial Dynamics," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 62(2), pages 861-886, May.
    4. 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.
    5. Illing, Mark & Liu, Ying, 2006. "Measuring financial stress in a developed country: An application to Canada," Journal of Financial Stability, Elsevier, vol. 2(3), pages 243-265, October.
    6. repec:ecb:ecbwps:20111426 is not listed on IDEAS
    7. Robert F. Engle & Simone Manganelli, 2004. "CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 367-381, October.
    8. Brownlees, Christian & Chabot, Ben & Ghysels, Eric & Kurz, Christopher, 2020. "Back to the future: Backtesting systemic risk measures during historical bank runs and the great depression," Journal of Banking & Finance, Elsevier, vol. 113(C).
    9. James D. Hamilton, 2018. "Why You Should Never Use the Hodrick-Prescott Filter," The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 831-843, December.
    10. Koenker, Roger & Bassett, Gilbert, Jr, 1982. "Robust Tests for Heteroscedasticity Based on Regression Quantiles," Econometrica, Econometric Society, vol. 50(1), pages 43-61, January.
    11. Tobias Adrian & Nina Boyarchenko & Domenico Giannone, 2019. "Vulnerable Growth," American Economic Review, American Economic Association, vol. 109(4), pages 1263-1289, April.
    12. White, Halbert & Kim, Tae-Hwan & Manganelli, Simone, 2015. "VAR for VaR: Measuring tail dependence using multivariate regression quantiles," Journal of Econometrics, Elsevier, vol. 187(1), pages 169-188.
    13. Koenker, Roger & Park, Beum J., 1996. "An interior point algorithm for nonlinear quantile regression," Journal of Econometrics, Elsevier, vol. 71(1-2), pages 265-283.
    14. Christian Brownlees & Benjamin Chabot & Eric Ghysels & Christopher J. Kurz, 2015. "Backtesting Systemic Risk Measures During Historical Bank Runs," Working Paper Series WP-2015-9, Federal Reserve Bank of Chicago.
    15. Freixas, Xavier & Laeven, Luc & Peydró, José-Luis, 2015. "Systemic Risk, Crises, and Macroprudential Regulation," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262028697, December.
    16. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
    17. Eun Ryung Lee & Hohsuk Noh & Byeong U. Park, 2014. "Model Selection via Bayesian Information Criterion for Quantile Regression Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(505), pages 216-229, March.
    18. Buchinsky, Moshe, 1995. "Estimating the asymptotic covariance matrix for quantile regression models a Monte Carlo study," Journal of Econometrics, Elsevier, vol. 68(2), pages 303-338, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tihana Skrinjaric & Maja Sabol, 2024. "Easier Said than Done: Predicting Downside Risks to House Prices in Croatia," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 74(1), pages 43-72, March.
    2. Chavleishvili, Sulkhan & Kremer, Manfred & Lund-Thomsen, Frederik, 2023. "Quantifying financial stability trade-offs for monetary policy: a quantile VAR approach," Working Paper Series 2833, European Central Bank.
    3. Škrinjarić, Tihana, 2024. "Growth-at-risk for macroprudential policy stance assessment: a survey," Bank of England working papers 1075, Bank of England.
    4. Kirstin Hubrich & Daniel F. Waggoner, 2022. "The transmission of financial shocks and leverage of financial institutions: An endogenous regime switching framework," Finance and Economics Discussion Series 2022-034, Board of Governors of the Federal Reserve System (U.S.).
    5. 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.
    6. Tihana Škrinjarić, 2023. "Macroprudential stance assessment: problems of measurement, literature review and some comments for the case of Croatia," Working Papers 72, The Croatian National Bank, Croatia.
    7. Shuffield Seyram Asafo & Michal Moszynski, 2022. "The combined effects of monetary and macroprudential policies," SN Business & Economics, Springer, vol. 2(9), pages 1-20, September.
    8. Kremer, Manfred & Chavleishvili, Sulkhan, 2021. "Measuring Systemic Financial Stress and its Impact on the Macroeconomy," VfS Annual Conference 2021 (Virtual Conference): Climate Economics 242346, Verein für Socialpolitik / German Economic Association.
    9. 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.
    10. Chavleishvili, Sulkhan & Fahr, Stephan & Kremer, Manfred & Manganelli, Simone & Schwaab, Bernd, 2021. "A novel risk management perspective for macroprudential policy," Research Bulletin, European Central Bank, vol. 87.
    11. Chavleishvili, Sulkhan & Kremer, Manfred, 2023. "Measuring systemic financial stress and its risks for growth," Working Paper Series 2842, European Central Bank.

    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 & Kremer, Manfred, 2023. "Measuring systemic financial stress and its risks for growth," Working Paper Series 2842, European Central Bank.
    2. 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.
    3. Hartwig, Benny & Meinerding, Christoph & Schüler, Yves S., 2021. "Identifying indicators of systemic risk," Journal of International Economics, Elsevier, vol. 132(C).
    4. Komunjer, Ivana, 2005. "Quasi-maximum likelihood estimation for conditional quantiles," Journal of Econometrics, Elsevier, vol. 128(1), pages 137-164, September.
    5. Thomas Q. Pedersen, 2015. "Predictable Return Distributions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(2), pages 114-132, March.
    6. Kremer, Manfred & Chavleishvili, Sulkhan, 2021. "Measuring Systemic Financial Stress and its Impact on the Macroeconomy," VfS Annual Conference 2021 (Virtual Conference): Climate Economics 242346, Verein für Socialpolitik / German Economic Association.
    7. 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.
    8. Altınkeski, Buket Kırcı & Cevik, Emrah Ismail & Dibooglu, Sel & Kutan, Ali M., 2022. "Financial stress transmission between the U.S. and the Euro Area," Journal of Financial Stability, Elsevier, vol. 60(C).
    9. Hyeongwoo Kim & Wen Shi & Hyun Hak Kim, 2020. "Forecasting financial stress indices in Korea: a factor model approach," Empirical Economics, Springer, vol. 59(6), pages 2859-2898, December.
    10. Gehrig, Thomas & Iannino, Maria Chiara, 2021. "Did the Basel Process of capital regulation enhance the resiliency of European banks?," Journal of Financial Stability, Elsevier, vol. 55(C).
    11. Leopoldo Catania & Alessandra Luati & Pierluigi Vallarino, 2021. "Economic vulnerability is state dependent," CREATES Research Papers 2021-09, Department of Economics and Business Economics, Aarhus University.
    12. Velasco, Sofia, 2024. "Asymmetries in the transmission of monetary policy shocks over the business cycle: a Bayesian Quantile Factor Augmented VAR," Working Paper Series 2983, European Central Bank.
    13. Gelos, Gaston & Gornicka, Lucyna & Koepke, Robin & Sahay, Ratna & Sgherri, Silvia, 2022. "Capital flows at risk: Taming the ebbs and flows," Journal of International Economics, Elsevier, vol. 134(C).
    14. Lee, Dong Jin & Kim, Tae-Hwan & Mizen, Paul, 2021. "Impulse response analysis in conditional quantile models with an application to monetary policy," Journal of Economic Dynamics and Control, Elsevier, vol. 127(C).
    15. Chadwick, Meltem Gulenay & Ozturk, Huseyin, 2019. "Measuring financial systemic stress for Turkey: A search for the best composite indicator," Economic Systems, Elsevier, vol. 43(1), pages 151-172.
    16. Polat, Onur & Ozkan, Ibrahim, 2019. "Transmission mechanisms of financial stress into economic activity in Turkey," Journal of Policy Modeling, Elsevier, vol. 41(2), pages 395-415.
    17. Wang, Bo & Li, Haoran, 2021. "Downside risk, financial conditions and systemic risk in China," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    18. Long, Shaobo & Li, Zixuan, 2023. "Dynamic spillover effects of global financial stress: Evidence from the quantile VAR network," International Review of Financial Analysis, Elsevier, vol. 90(C).
    19. Tibor Szendrei & Katalin Varga, 2020. "FISS - A Factor-based Index of Systemic Stress in the Financial System," Russian Journal of Money and Finance, Bank of Russia, vol. 79(1), pages 3-34, March.

    More about this item

    Keywords

    financial conditions; growth-at-risk; macro-prudential policy; quantile vector autoregression; stress testing;
    All these keywords.

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

    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:20212565. 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.