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Structural breaks in panel data: COVID-19 pandemic in Russian regions

Author

Listed:
  • Rogneda Vasilyeva

    (RANEPA, Moscow, Russian Federation)

  • Anton Skrobotov

    (HSE University, RANEPA, Moscow; Russian Federation)

  • Aleksei Tsarev

    (RANEPA, Moscow, Russian Federation)

Abstract

This paper discusses contemporary methods of testing for structural breaks in panel data. We discuss the approaches for single and multiple breaks testing in cross-sectionally correlated panels. For empirical application, we use weekly data for the COVID-19 pandemic in Russian regions. We identify several structural breaks over the period and add them to the econometric model. The results show a significant difference compared to the model that ignores structural breaks, underscoring the importance of accounting for these breaks when analyzing Russian regional data.

Suggested Citation

  • Rogneda Vasilyeva & Anton Skrobotov & Aleksei Tsarev, 2025. "Structural breaks in panel data: COVID-19 pandemic in Russian regions," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 80, pages 117-142.
    • Handle: RePEc:ris:apltrx:021849
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    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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