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ИД «Финансы и кредит»






Financial Analytics: Science and Experience

Assessing the financial instability of economic systems: A variety of methods and models

Vol. 15, Iss. 2, JUNE 2022

Received: 3 April 2019

Received in revised form: 24 April 2019

Accepted: 17 May 2019

Available online: 30 May 2022


JEL Classification: C58, E44, G01

Pages: 205–231


Marina Yu. MALKINA National Research Lobachevsky State University of Nizhny Novgorod (UNN), Nizhny Novgorod, Russian Federation


Anton O. OVCHAROV National Research Lobachevsky State University of Nizhny Novgorod (UNN), Nizhny Novgorod, Russian Federation


Subject. The paper summarizes the existing methods and models for identification of financial instability in economic systems, analyzes interrelations between macroeconomic indicators of Russia that demonstrate the impact of destabilizing factors on economic processes.
Objectives. The main objective is to systematize methodological approaches to and specific models of quantitative assessment of financial instability and consider interrelations between the indicators of instability in the Russian economy.
Methods. We employ general scientific methods of analysis, comparison, generalization, statistical methods for processing economic data and constructing integral indicators, econometric techniques for autoregressive model estimation.
Results. The paper summarizes approaches and directions of quantitative assessment of financial instability in economic systems, evaluates the results of studies by Russian and foreign authors obtained on the basis of the developed system of early warning indicators of financial instability. We define possibilities for econometric modeling of a wide range of variables, which are indicative of instability, volatility or predictability of economic system behavior. Furthermore, we calculated the integral volatility index enabling to reveal a period of financial instability along with the main indicators trend movement.
Conclusions. The proposed dependencies and integral volatility indicator point to recurring periods of instability in the Russian economic system, which are strongly influenced by the changing situation in the world oil markets.

Keywords: financial instability, modeling, assessment, macroeconomic indicator


  1. Trunin P.V., Kamenskikh M.V. Monitoring finansovoi stabil'nosti v razvivayushchikhsya ekonomikakh (na primere Rossii) [Monitoring the financial stability in emerging economies (the Russia case)]. Moscow, Institute for Economy in Transition Publ., 2007, 106 p.
  2. Guillaumont Jeanneney S., Kpodar K. Financial Development, Financial Instability and Poverty. CERDI, Etudes et Documents, 2006, no. 7. URL: Link
  3. Loayza N., Ranciere R. Financial Development, Financial Fragility, and Growth. IMF Working Paper, 2005, no. 170. URL: Link
  4. Eggoh C. Financial Development, Financial Instability and Growth: A Reappraisal. Law, Economics and Management Faculty, University of Orleans, 2008.
  5. Klomp J., Jakob de Haan. Central Bank Independence and Financial Instability. Journal of Financial Stability, 2009, vol. 5, iss. 4, pp. 321–338. URL: Link
  6. Fedorova E.A. [Methodological approaches to building the financial sustainability index for the Russian financial market]. Finansy i kredit = Finance and Credit, 2015, no. 5, pp. 11–20. URL: Link (In Russ.)
  7. Kaminsky G., Lizondo S., Reinhart C. Leading Indicators of Currency Crises. IMF Staff Papers, 1998, vol. 45, no. 1, pp. 1–48. URL: Link 3867328?origin=pubexport&seq=1#page_scan_tab_contents
  8. Kaminsky G. Currency Crises: Are They All the Same? Journal of International Money and Finance, 2006, vol. 25, iss. 3, pp. 503–527. URL: Link
  9. Oviedo P.M. Macroeconomic Risk and Banking Crises in Emerging Market Countries: Business Fluctuations with Financial Crashes. URL: Link
  10. Komulainen T., Lukkarila J. What Drives Financial Crises in Emerging Markets? BOFIT Discussion Paper, 2003, no. 5. URL: Link
  11. Nitschka T. About the Soundness of the US-cay Indicator for Predicting International Banking Crises. The North American Journal of Economics and Finance, 2011, vol. 22, iss. 3, pp. 237–256. URL: Link
  12. Kumar M., Moorthy U., Perraudin W. Predicting Emerging Market Currency Crashes. IMF Working Paper, 2002, no. WP/02/7. URL: Link
  13. Fedorova E., Lukasevich I. [Forecasting Financial Crises by Using Key Indicators in Developing Countries]. Voprosy Ekonomiki, 2011, no. 12, pp. 35–45. (In Russ.) URL: Link
  14. Ulyukaev A.V., Trunin P.V. [Applying the signaling approach to elaboration of indicators warning about financial instability in Russia]. Problemy prognozirovaniya = Problems of Forecasting, 2008, no. 5, pp. 100–109. URL: Link (In Russ.)
  15. Solntsev O.G., Pestova A.A., Mamonov M.E., Magomedova Z.M. [Experience in Developing Early Warning System for Financial Crises and the Forecast of Russian Banking Sector Dynamic in 2012]. Zhurnal Novoi ekonomicheskoi assotsiatsii = Journal of the New Economic Association, 2011, no. 12, pp. 41–76. URL: Link (In Russ.)
  16. Strategiya ekonomicheskoi bezopasnosti pri razrabotke indikativnykh planov sotsial'no-ekonomicheskogo razvitiya na dolgosrochnuyu i srednesrochnuyu perspektivu: monografiya [Economic security strategy when developing indicative long-term and mid-term plans of socio-economic development: a monograph]. Moscow, IE RAS Publ., 2009, 232 p.
  17. Chepurko V.V., Vints S.B. [Methodological aspects of financial crisis indication]. Nauchnyi vestnik: finansy, banki, investitsii = Scientific Bulletin: Finance, Banking, Investment, 2016, no. 2, pp. 18–26. URL: Link (In Russ.)
  18. Fedorova E.A., Lukasevich I.Ya. [Forecasting the financial crises using economic indicators in the CIS]. Problemy prognozirovaniya = Problems of Forecasting, 2012, no. 2, pp. 112–122. URL: Link (In Russ.)
  19. Bannikov V.A. [Vector autoregression and error correction models]. Prikladnaya ekonometrika = Applied Econometrics, 2006, no. 3, pp. 96–129. URL: Link (In Russ.)
  20. Shchepeleva M. [Financial Contagion: Global Transmission of Systemic Risk]. Mirovaya ekonomika i mezhdunarodnye otnosheniya = World Economy and International Relations, 2017, vol. 61, no. 1, pp. 17–28. URL: Link (In Russ.)
  21. Tiunova M.G. [The monetary policy impact on the dynamics of Russia's real economy]. Vestnik Moskovskogo universiteta. Ser. 6. Ekonomika = Moscow University Economics Bulletin, 2017, no. 3, pp. 80–108. URL: Link (In Russ.)
  22. Bernanke B., Boivin J., Eliasz P. Measuring the Effects of Monetary Policy: A Factor-Augmented Vector Autoregressive (FAVAR) Approach. NBER Working Paper, 2004, no. 10220. URL: Link
  23. Litterman R. Forecasting with Bayesian Vector Autoregressions – Five Years of Experience. Journal of Business & Economic Statistics, 1986, vol. 4, iss. 1, pp. 25–38. URL: Link_ tab_contents
  24. Shevelev A.A. [Bayesian approach to evaluate the impact of external shocks on Russian macroeconomics indicators]. Mir ekonomiki i upravleniya = World of Economics and Management, 2017, vol. 17, no. 1, pp. 26–40. URL: Link (In Russ.)
  25. Engle R.F. Autoregressive Conditional Heteroscedasticity with Estimates of Variance of United Kingdom Inflation. Econometrica, 1982, vol. 50, iss. 4, pp. 987–1007. URL: Link_ scan_tab_contents
  26. Bollerslev T. Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 1986, vol. 31, iss. 3, pp. 307–327. URL: Link
  27. Fedorova E.A., Buzlov D.A. [Forecasting of stock market of the Russian Federation by means of GARCH modeling]. Finansovaya analitika: problemy i resheniya = Financial Analytics: Science and Experience, 2013, no. 16, pp. 2–10. URL: Link (In Russ.)
  28. Galvão A.B. Data Revisions and DSGE Models. Journal of Econometrics, 2017, vol. 196, iss. 1, pp. 215–232. URL: Link
  29. Fagiolo G., Roventini A. Macroeconomic Policy in DSGE and Agent-Based Models Redux: New Developments and Challenges Ahead. Journal of Artificial Societies and Social Simulation, 2017, vol. 20, iss. 1. URL: Link
  30. Mikusheva A. [Evaluation of dynamic stochastic general equilibrium models]. Kvantil', 2014, no. 12, pp. 1–21. (In Russ.) URL: Link
  31. Drobyshevskii S., Polbin A. [Decomposition of the Structural Shocks Contribution to the Russian Macroeconomic Indicators Dynamics on the Basis of the DSGE Model]. Ekonomicheskaya politika = Economic Policy, 2015, vol. 10, no. 2, pp. 20–42. URL: Link (In Russ.)
  32. Seegert N. Optimal Taxation with Volatility: A Theoretical and Empirical Decomposition. URL: Link TaxationwithVolatility_Seegert.pdf
  33. Castro G.Á., Camarillo D.B.R. Determinants of Tax Revenue in OECD Countries over the Period 2001–2011. Contaduría y Administración, 2014, vol. 59, iss. 3, pp. 35–59. URL: Link71265-3
  34. Karagianni S., Pempetzoglou M., Anastasios A. Tax Burden Distribution and GDP Growth: Non-linear Causality Considerations in the USA. International Review of Economics and Finance, 2012, vol. 21, iss. 1, pp. 186–194. URL: Link
  35. Malkina M.Yu., Balakin R.V. [Correlation Assessment of Tax System Risk and Profitability in the Russian Regions]. Ekonomika regiona = Economy of Region, 2015, no. 3, pp. 241–255. URL: Link (In Russ.)
  36. Malkina M.Yu. [Instability of financial return of regional economies and its determinants]. Prostranstvennaya ekonomika = Spatial Economics, 2018, no. 3, pp. 88–114. URL: Link (In Russ.)
  37. Yashina N.I., Pronchatova-Rubtsova N.N. [Determination of budget risks of the Nizhni Novgorod region based on the performance of the revenue and expenditure sides of the budget]. Vestnik Nizhegorodskogo universiteta imeni N.I. Lobachevskogo. Ser.: Sotsial'nye nauki = Vestnik of Lobachevsky State University of Nizhny Novgorod. Series: Social Sciences, 2014, no. 4, pp. 16–24. URL: Link (In Russ.)
  38. Kurochkina L.P., Tikhonova S.S. [Factorial model of emergence of the budgetary risk in system of regional government]. Upravlenie ekonomicheskimi sistemami, 2012, no. 4. (In Russ.) URL: Link
  39. Gamukin V.V. [Budgetary risks: Introduction to the general axiomatics]. TERRA ECONOMICUS, 2013, vol. 11, no. 3, pp. 52–61. URL: Link (In Russ.)
  40. Espen Frøyland, Kai Larsen. How Vulnerable are Financial Institutions to Macroeconomic Changes? An Analysis Based on Stress Testing. Norges Bank Economic Bulletin, 2002, vol. LXXIII, no. 3. URL: Link
  41. Arestis P., Jia M. Credit Risk and Macroeconomic Stress Tests in China. Journal of Banking Regulation, 2018, pp. 1–15. URL: Link
  42. Sujit K., Drehmann M., Elliott J., Sterne G. Liquidity Risk, Cash Flow Constraints, and Systemic Feedbacks. Bank of England Working Paper, 2012, no. 456. URL: Link
  43. Hirtle B., Kovner A., Vickery J., Bhanot M. Assessing Financial Stability: The Capital and Loss Assessment under Stress Scenarios (CLASS) Model. Federal Reserve Bank of New York Staff Reports, 2014, no. 663. URL: Link medialibrary/media/research/staff_reports/sr663.pdf
  44. Ershov M. [On the mechanisms of growth of the Russian economy under conditions of worsening financial problems in the world]. Voprosy Ekonomiki, 2016, no. 12, pp. 5–25. URL: Link (In Russ.)

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Vol. 15, Iss. 2
June 2022