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Stress Testing As A Tool For Monitoring And Modelling The Dynamics Of Business Activity Of Manufacturing Enterprises In Russia In The Face Of Market Shocks: Short-Term Scenarios Of Industry Tendencies

Author

Listed:
  • Inna S. Lola

    (National Research University Higher School of Economics)

  • Anton Manukov

    (National Research University Higher School of Economics)

  • Murat Bakeev

    (National Research University Higher School of Economics)

Abstract

The article proposes a methodology for using macro-level stress testing based on the results of business tendency surveys to study possible scenarios for the development of crisis dynamics triggered by external unforeseen supply and demand shocks, as in the case of the COVID-19 pandemic, as well as a review of existing approaches in the field of stress testing and building stress indices with an emphasis on methods based on vector autoregressive models and their various modifications. The basis for empirical calculations is data from business tendency surveys of the leaders of Russian manufacturing enterprises, reflecting their combined estimates of the current state of business activity. Based on the results of business tendency surveys, four composite indices were formed reflecting various aspects of business activity of enterprises: demand index, production index, finance index and employment index. Index values calculated monthly from 2008 to March 2020 were used to build the Bayesian vector autoregressive model (BVAR). This model was used to predict the dynamics of indices under the condition of four possible shock scenarios: short-term shock, V-shaped shock, W-shaped shock and U-shaped shock. Moreover, for each of the scenarios, cases of a shock of demand, a shock of production, and a simultaneous shock of demand and production were separately considered. The results indicated the key role of demand in the dynamics of all the indices under consideration, the W-shaped shock, as the worst of the considered scenarios, as well as the relatively greater sensitivity of the employment index to the demand index and the finance index to the production index

Suggested Citation

  • Inna S. Lola & Anton Manukov & Murat Bakeev, 2020. "Stress Testing As A Tool For Monitoring And Modelling The Dynamics Of Business Activity Of Manufacturing Enterprises In Russia In The Face Of Market Shocks: Short-Term Scenarios Of Industry Tendencies," HSE Working papers WP BRP 108/STI/2020, National Research University Higher School of Economics.
  • Handle: RePEc:hig:wpaper:108sti2020
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    References listed on IDEAS

    as
    1. G. I. Idrisov & V. N. Knyaginin & A. L. Kudrin & E. S. Rozhkova., 2018. "New technological revolution: Challenges and opportunities for Russia," VOPROSY ECONOMIKI, N.P. Redaktsiya zhurnala "Voprosy Economiki", vol. 4.
    2. Marta Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Large Bayesian vector auto regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 71-92.
    3. Brooks,Chris & Tsolacos,Sotiris, 2010. "Real Estate Modelling and Forecasting," Cambridge Books, Cambridge University Press, number 9780521873390, January.
    4. Tim Ng, 2011. "The predictive content of financial cycle measures for output fluctuations," BIS Quarterly Review, Bank for International Settlements, June.
    5. repec:ulb:ulbeco:2013/13388 is not listed on IDEAS
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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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