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Modeling COVID-19 spread in the Russian Federation using global VAR approach

Author

Listed:
  • Zubarev, Andrei

    (RANEPA; Moscow, Russian Federation)

  • Kirillova, Maria

    (RANEPA; Moscow, Russian Federation)

Abstract

The aim of this study is to analyse the spread of COVID-19 in Russia taking into account various connections between regions and the effectiveness of isolation strategies using global vector autoregression (GVAR). We use regional data on new cases of coronavirus, self-isolation index, Google trends index reflecting social awareness of pandemic and passenger turnover in buses, trains and planes. It was found that the number of new COVID-19 cases reacts to Moscow outbreak shock significantly in most regions. During the second wave, the speed of reaction was faster but of a smaller size. The forecasts of new cases dynamics during the rising of the second wave turn out to be rather close to the actual dynamics in many regions. More rigorous social distancing strategy in Moscow reduced the number of cases in some regions but at the same time raised that number in some others

Suggested Citation

  • Zubarev, Andrei & Kirillova, Maria, 2022. "Modeling COVID-19 spread in the Russian Federation using global VAR approach," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 65, pages 117-138.
    • Handle: RePEc:ris:apltrx:0442
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    More about this item

    Keywords

    COVID-19; pandemic; global VAR; infection; cross-country spillovers; Google trends; second wave forecast;
    All these keywords.

    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
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis

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