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Generalized Vector Autoregression Controlling Intervention and Volatility for Climatic Variables

In: Data Science and SDGs

Author

Listed:
  • Md. Ashek Al Naim

    (University of Rajshahi, Department of Statistics)

  • Md. Abeed Hossain Chowdhury

    (BARC)

  • Md. Abdul Khalek

    (University of Rajshahi, Department of Statistics)

  • Md. Ayub Ali

    (University of Rajshahi, Department of Statistics)

Abstract

The purpose of this study is to build a time series model for forecasting the climatic variables of Rajshahi district using the VAR model controlling intervention and volatility. Seven models for seven climatic variables are found, and the stability of every model is checked with proper validation techniques. The fitted models are GVAR with GARCH (2,1) and intervention for Cloud coverage; GVAR with GARCH (3,1) and intervention for Relative Humidity; ARIMA (1,0,1) with GARCH (1,1) for rainfall, GVAR with GARCH (2,1), and intervention for maximum Temperature; GVAR with ARCH (2) and intervention for minimum temperature; GVAR with intervention for sunshine; and ARIMA (2,0,2) for wind speed. The stable models are used to forecast the daily data which may be beneficial to people and policymakers. Finally, it is found by forecasting that Maximum Temperature (T1), Humidity (H), Bright Sunshine (S), and Wind Speed (W) might be shown upward trend while Minimum Temperature (T2), Rainfall (R), and Cloud Coverage (Cl) might be shown decreasing trend from the year 2018 to 2022. Considering the finding of this study, Government and policymakers can make people aware of the adverse effect of climate change.

Suggested Citation

  • Md. Ashek Al Naim & Md. Abeed Hossain Chowdhury & Md. Abdul Khalek & Md. Ayub Ali, 2021. "Generalized Vector Autoregression Controlling Intervention and Volatility for Climatic Variables," Springer Books, in: Bikas Kumar Sinha & Md. Nurul Haque Mollah (ed.), Data Science and SDGs, pages 79-91, Springer.
    • Handle: RePEc:spr:sprchp:978-981-16-1919-9_7
    DOI: 10.1007/978-981-16-1919-9_7
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