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Autoregression model for the GDP of the Russian Federation, supplemented by the indicator of business activity of trading partner countries
[Модель Авторегрессии Для Ввп Рф, Дополненная Показателем Деловой Активности Стран Торговых Партнеров]

Author

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  • Tadzhibaeva, Liana (Таджибаева, Лиана)

    (The Russian Presidential Academy of National Economy and Public Administration)

Abstract

The model proposed in this paper is a modification of the second-order autoregressive process with the addition of an external variable that allows taking into account the cycles of trading partners to predict output. This model has shown a significant advantage in forecasting for the long-term horizon, which confirms the importance of taking into account the economic activity of partner countries when forecasting the GDP of the Russian Federation.

Suggested Citation

  • Tadzhibaeva, Liana (Таджибаева, Лиана), 2023. "Autoregression model for the GDP of the Russian Federation, supplemented by the indicator of business activity of trading partner countries [Модель Авторегрессии Для Ввп Рф, Дополненная Показателем," Working Papers w20220233, Russian Presidential Academy of National Economy and Public Administration.
    • Handle: RePEc:rnp:wpaper:w20220233
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    More about this item

    Keywords

    GDP forecasting; business activity of trading partners; vector autoregressions; Bayesian methods;
    All these keywords.

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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