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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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    File URL: https://www.bancaditalia.it/pubblicazioni/temi-discussione/2019/2019-1242/en_tema_1242.pdf
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    References listed on IDEAS

    as
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    Cited by:

    1. Gonzalez Rivera, Gloria & Rodríguez Caballero, Carlos Vladimir, 2021. "Expecting the unexpected: economic growth under stress," DES - Working Papers. Statistics and Econometrics. WS 32148, Universidad Carlos III de Madrid. Departamento de Estadística.
    2. 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.
    3. Busetti, Fabio & Caivano, Michele & Delle Monache, Davide & Pacella, Claudia, 2021. "The time-varying risk of Italian GDP," Economic Modelling, Elsevier, vol. 101(C).
    4. Milan Szabo & Zlatuse Komarkova & Martin Casta, 2020. "Vulnerable growth: Bayesian GDP-at-Risk," Occasional Publications - Chapters in Edited Volumes,, Czech National Bank.
    5. 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.
    6. Škrinjarić, Tihana, 2024. "Growth-at-risk for macroprudential policy stance assessment: a survey," Bank of England working papers 1075, Bank of England.
    7. Martínez-Jaramillo, Serafín & Montañez-Enríquez, Ricardo & Ossandon Busch, Matias & Ramos-Francia, Manuel & Rodríguez-Martínez, Anahí & Sánchez-Martínez, Manuel, 2022. "Stress-ridden finance and growth losses: Does financial development break the link?," IWH Discussion Papers 3/2022, Halle Institute for Economic Research (IWH).

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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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