IDEAS home Printed from https://ideas.repec.org/p/imf/imfwpa/10-29.html
   My bibliography  Save this paper

Systemic Risks and the Macroeconomy

Author

Listed:
  • Marcella Lucchetta
  • Gianni De Nicolo

Abstract

This paper presents a modeling framework that delivers joint forecasts of indicators of systemic real risk and systemic financial risk, as well as stress-tests of these indicators as impulse responses to structural shocks identified by standard macroeconomic and banking theory. This framework is implemented using large sets of quarterly time series of indicators of financial and real activity for the G-7 economies for the 1980Q1-2009Q3 period. We obtain two main results. First, there is evidence of out-of sample forecasting power for tail risk realizations of real activity for several countries, suggesting the usefulness of the model as a risk monitoring tool. Second, in all countries aggregate demand shocks are the main drivers of the real cycle, and bank credit demand shocks are the main drivers of the bank lending cycle. These results challenge the common wisdom that constraints in the aggregate supply of credit have been a key driver of the sharp downturn in real activity experienced by the G-7 economies in 2008Q4- 2009Q1.

Suggested Citation

  • Marcella Lucchetta & Gianni De Nicolo, 2010. "Systemic Risks and the Macroeconomy," IMF Working Papers 10/29, International Monetary Fund.
  • Handle: RePEc:imf:imfwpa:10/29
    as

    Download full text from publisher

    File URL: http://www.imf.org/external/pubs/cat/longres.aspx?sk=23593
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Andrew T. Foerster & Pierre-Daniel G. Sarte & Mark W. Watson, 2011. "Sectoral versus Aggregate Shocks: A Structural Factor Analysis of Industrial Production," Journal of Political Economy, University of Chicago Press, vol. 119(1), pages 1-38.
    2. 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.
    3. 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.
    4. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    5. James H. Stock & Mark W. Watson, 2005. "Implications of Dynamic Factor Models for VAR Analysis," NBER Working Papers 11467, National Bureau of Economic Research, Inc.
    6. Huang, Xin & Zhou, Hao & Zhu, Haibin, 2009. "A framework for assessing the systemic risk of major financial institutions," Journal of Banking & Finance, Elsevier, vol. 33(11), pages 2036-2049, November.
    7. Elena Loukoianova & Gianni De Nicolo & John H. Boyd, 2009. "Banking Crises and Crisis Dating; Theory and Evidence," IMF Working Papers 09/141, International Monetary Fund.
    8. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-162, April.
    9. Huang, Xin & Zhou, Hao & Zhu, Haibin, 2012. "Assessing the systemic risk of a heterogeneous portfolio of banks during the recent financial crisis," Journal of Financial Stability, Elsevier, vol. 8(3), pages 193-205.
    10. Ethan Cohen-Cole & Burcu Duygan-Bump & José Fillat & Judit Montoriol-Garriga, 2008. "Looking behind the aggregates: a reply to “Facts and Myths about the Financial Crisis of 2008”," Risk and Policy Analysis Unit Working Paper QAU08-5, Federal Reserve Bank of Boston.
    11. Ben S. Bernanke & Jean Boivin & Piotr Eliasz, 2005. "Measuring the Effects of Monetary Policy: A Factor-Augmented Vector Autoregressive (FAVAR) Approach," The Quarterly Journal of Economics, Oxford University Press, vol. 120(1), pages 387-422.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Financial risk; Economic models; Economic indicators; External shocks; Banking sector; Capital markets; Economic forecasting; Prices; International financial system; Group of seven; Time series; Systemic risk; Dynamic Factor Model; Quantile Regressions; bank credit; forecasting; banking; bank lending; Econometric Modeling; Business Fluctuations; And Cycles; financial Institutions And Services;

    JEL classification:

    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

    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:imf:imfwpa:10/29. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Jim Beardow) or (Hassan Zaidi). General contact details of provider: http://edirc.repec.org/data/imfffus.html .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.