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Experience in Developing Early Warning System for Financial Crises and the Forecast of Russian Banking Sector Dynamic in 2012

Author

Listed:
  • Solntsev, O.

    (Center for Macroeconomic Analysis and Short-Term Forecasting (CMASF), Moscow, Russia)

  • Mamonov, M.

    (Center for Macroeconomic Analysis and Short-Term Forecasting (CMASF), Moscow, Russia)

  • Pestova, A.

    (Center for Macroeconomic Analysis and Short-Term Forecasting (CMASF), Moscow, Russia)

  • Magomedova, Z.

    (Center for Macroeconomic Analysis and Short-Term Forecasting (CMASF), Moscow, Russia)

Abstract

The article summarizes the key results of researches in the field of early warning systems for financial crises, conducted by the Center for Macroeconomic Analysis and Short-Term Forecasting (CMASF) since 2005. The proposed early warning system consists of three major blocks: the leading indicators of certain types of risks and the composite leading indicator of a systemic banking crisis; the medium-term scenario forecasting of key macroeconomic and financial indicators; stress testing of credit and liquidity risks of banks. On the basis of this early warning system we estimate the risks of financial crisis and some kinds of systemic risks in the different scenarios for the Russian economy in 2012. The analysis, in particular, revealed a sensitivity threshold of the domestic financial sector to changes in the world oil prices. Furthermore, it was found that the greatest destabilizing effect on the Russian financial sector may be caused by systemic credit risk.

Suggested Citation

  • Solntsev, O. & Mamonov, M. & Pestova, A. & Magomedova, Z., 2011. "Experience in Developing Early Warning System for Financial Crises and the Forecast of Russian Banking Sector Dynamic in 2012," Journal of the New Economic Association, New Economic Association, issue 12, pages 41-76.
    • Handle: RePEc:nea:journl:y:2011:i:12:p:41-76
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    References listed on IDEAS

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    Cited by:

    1. Mamonov, Mikhail, 2012. "The impact of market power of Russian banks on their credit risk tolerance: A panel study," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 28(4), pages 85-112.
    2. Belousova, Veronika & Karminsky, Alexander & Kozyr, Ilya, 2018. "The macroeconomic and institutional determinants of the profit efficiency frontier for Russian banks," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 49, pages 91-114.
    3. Agata Lozinskaia & Anastasiia Saltykova, 2019. "Fundamental Factors Affecting The Moex Russia Index: Structural Break Detection In A Long-Term Time Series," HSE Working papers WP BRP 77/FE/2019, National Research University Higher School of Economics.
    4. Karminsky, A. & Dyachkova, N., 2020. "Empirical study of the relationship between credit cycles and changes in credit ratings," Journal of the New Economic Association, New Economic Association, vol. 48(4), pages 138-160.
    5. Mikhail E. MAMONOV, Anna A. PESTOVA, Vera PANKOVA, Renat Akhmetov, 2020. "Digital Transformation of Capital Market Infrastructure [Цифровая Трансформация Инфраструктуры Рынка Капитала]," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 5, pages 130-159, November.

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    More about this item

    Keywords

    systemic financial crises; credit risks; liquidity risks; currency risks; early warning system; leading indicators; stress testing;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G01 - Financial Economics - - General - - - Financial Crises

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