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Financial Conditions and 'Growth at Risk' in Italy

Author

Listed:
  • Piergiorgio Alessandri

    (Bank of Italy)

  • Leonardo Del Vecchio

    (Bank of Italy)

  • Arianna Miglietta

    (Bank of Italy)

Abstract

This paper studies the relationship between financial conditions and economic activity in Italy using quantile regression techniques in the spirit of Adrian, Boryachenko and Giannone (2019). We exploit the volatility of the 2008-2012 period to assess the plausibility of ‘tail’ predictions obtained from a broad range of financial indicators. We find that, although spikes in financial distress are typically followed by economic contractions, using this relationship for out-of-sample forecasting is not trivial. To some extent, the models predict the slowdowns experienced by Italy after 2008, but the forecasts are volatile, their quality varies across indicators and horizons, and the predictions tend to overestimate the likelihood of an upcoming recession. As such, these tools represent a complement to, rather than a substitute for, an articulated and diversified systemic risk assessment framework.

Suggested Citation

  • Piergiorgio Alessandri & Leonardo Del Vecchio & Arianna Miglietta, 2019. "Financial Conditions and 'Growth at Risk' in Italy," Temi di discussione (Economic working papers) 1242, Bank of Italy, Economic Research and International Relations Area.
  • Handle: RePEc:bdi:wptemi:td_1242_19
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    References listed on IDEAS

    as
    1. Duprey, Thibaut & Klaus, Benjamin & Peltonen, Tuomas, 2017. "Dating systemic financial stress episodes in the EU countries," Journal of Financial Stability, Elsevier, vol. 32(C), pages 30-56.
    2. Arianna Miglietta & Fabrizio Venditti, 2019. "An indicator of macro-financial stress for Italy," Questioni di Economia e Finanza (Occasional Papers) 497, Bank of Italy, Economic Research and International Relations Area.
    3. Urban Jermann & Vincenzo Quadrini, 2012. "Macroeconomic Effects of Financial Shocks," American Economic Review, American Economic Association, vol. 102(1), pages 238-271, February.
    4. Piergiorgio Alessandri & Haroon Mumtaz, 2017. "Financial conditions and density forecasts for US output and inflation," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 24, pages 66-78, March.
    5. Zhigu He & Arvind Krishnamurthy, 2012. "A Model of Capital and Crises," Review of Economic Studies, Oxford University Press, vol. 79(2), pages 735-777.
    6. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003. "Modeling and Forecasting Realized Volatility," Econometrica, Econometric Society, vol. 71(2), pages 579-625, March.
    7. Piergiorgio Alessandri & Haroon Mumtaz, 2017. "Financial conditions and density forecasts for US output and inflation," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 24, pages 66-78, March.
    8. Simon Gilchrist & Egon Zakrajsek, 2012. "Credit Spreads and Business Cycle Fluctuations," American Economic Review, American Economic Association, vol. 102(4), pages 1692-1720, June.
    9. Howard D. Bondell & Brian J. Reich & Huixia Wang, 2010. "Noncrossing quantile regression curve estimation," Biometrika, Biometrika Trust, vol. 97(4), pages 825-838.
    10. Gianni De Nicolò & Marcella Lucchetta, 2017. "Forecasting Tail Risks," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(1), pages 159-170, January.
    11. Garcia-de-Andoain, Carlos & Kremer, Manfred, 2017. "Beyond spreads: Measuring sovereign market stress in the euro area," Economics Letters, Elsevier, vol. 159(C), pages 153-156.
    12. Serena Ng & Jonathan H. Wright, 2013. "Facts and Challenges from the Great Recession for Forecasting and Macroeconomic Modeling," Journal of Economic Literature, American Economic Association, vol. 51(4), pages 1120-1154, December.
    13. Piergiorgio Alessandri & Pierluigi Bologna & Roberta Fiori & Enrico Sette, 2015. "A note on the implementation of the countercyclical capital buffer in Italy," Questioni di Economia e Finanza (Occasional Papers) 278, Bank of Italy, Economic Research and International Relations Area.
    14. James H. Stock & Mark W.Watson, 2003. "Forecasting Output and Inflation: The Role of Asset Prices," Journal of Economic Literature, American Economic Association, vol. 41(3), pages 788-829, September.
    15. Urban Jermann & Vincenzo Quadrini, 2012. "Erratum: Macroeconomic Effects of Financial Shocks," American Economic Review, American Economic Association, vol. 102(2), pages 1186-1186, April.
    16. 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.
    17. Valentina Aprigliano & Lorenzo Bencivelli, 2013. "Ita-coin: a new coincident indicator for the Italian economy," Temi di discussione (Economic working papers) 935, Bank of Italy, Economic Research and International Relations Area.
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    Cited by:

    1. Gloria Gonzalez-Rivera & Vladimir Rodriguez-Caballero & Esther Ruiz, 2021. "Expecting the unexpected: economic growth under stress," Working Papers 202106, University of California at Riverside, Department of Economics.
    2. Busetti, Fabio & Caivano, Michele & Delle Monache, Davide & Pacella, Claudia, 2021. "The time-varying risk of Italian GDP," Economic Modelling, Elsevier, vol. 101(C).

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    More about this item

    Keywords

    financial conditions; quantile regression; growth risk;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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