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Evaluating the Role of Global Factors in GDP Nowcasting
[Анализ Важности Глобальных Факторов Для Наукастинга Ввп]

Author

Listed:
  • Konstantin S. Rybak

    (Russian Presidential Academy of National Economy and Public Administration)

Abstract
This work shows that use of more than two global factors in standard factor-augmented model leads to significantly better nowcasts of Russian GDP growth rate. Global inflation and nominal factors are available for estimation almost in real-time which leads to earlier and better nowcasts.

Suggested Citation

  • Konstantin S. Rybak, 2023. "Evaluating the Role of Global Factors in GDP Nowcasting [Анализ Важности Глобальных Факторов Для Наукастинга Ввп]," Russian Economic Development, Gaidar Institute for Economic Policy, issue 12, pages 18-23, December.
  • Handle: RePEc:gai:recdev:r2399
    as

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    References listed on IDEAS

    as
    1. Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 2005. "The Generalized Dynamic Factor Model: One-Sided Estimation and Forecasting," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 830-840, September.
    2. Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 2004. "The generalized dynamic factor model consistency and rates," Journal of Econometrics, Elsevier, vol. 119(2), pages 231-255, April.
    3. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    4. Karim Barhoumi & Olivier Darné & Laurent Ferrara, 2010. "Are disaggregate data useful for factor analysis in forecasting French GDP?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 132-144.
    5. Tony Chernis & Rodrigo Sekkel, 2017. "A dynamic factor model for nowcasting Canadian GDP growth," Empirical Economics, Springer, vol. 53(1), pages 217-234, August.
    6. S. M. Drobyshevsky & G. I. Idrisov & A. S. Kaukin & P. N. Pavlov & S. G. Sinelnikov‑Murylev, 2018. "Decomposition of Russian GDP growth rates in 2007—2017 and forecast for 2018—2020," Voprosy Ekonomiki, NP Voprosy Ekonomiki, issue 9.
    7. Porshakov, A. & Ponomarenko, A. & Sinyakov, A., 2016. "Nowcasting and Short-Term Forecasting of Russian GDP with a Dynamic Factor Model," Journal of the New Economic Association, New Economic Association, vol. 30(2), pages 60-76.
    8. Mehrara, Mohsen & Oskoui, Kamran Niki, 2007. "The sources of macroeconomic fluctuations in oil exporting countries: A comparative study," Economic Modelling, Elsevier, vol. 24(3), pages 365-379, May.
    9. S. M. Drobyshevsky & G. I. Idrisov & A. S. Kaukin & P. N. Pavlov & S. G. Sinelnikov-Murylev., 2018. "Decomposition of Russian GDP growth rates in 2007—2017 and forecast for 2018—2020," VOPROSY ECONOMIKI, N.P. Redaktsiya zhurnala "Voprosy Economiki", vol. 9.
    10. Matheson, Troy D., 2010. "An analysis of the informational content of New Zealand data releases: The importance of business opinion surveys," Economic Modelling, Elsevier, vol. 27(1), pages 304-314, January.
    11. Modugno, Michele & Soybilgen, Barış & Yazgan, Ege, 2016. "Nowcasting Turkish GDP and news decomposition," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1369-1384.
    12. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
    13. Valery Charnavoki & Juan J. Dolado, 2014. "The Effects of Global Shocks on Small Commodity-Exporting Economies: Lessons from Canada," American Economic Journal: Macroeconomics, American Economic Association, vol. 6(2), pages 207-237, April.
    14. Полбин Андрей Владимирович & Скроботов Антон Андреевич, 2016. "Тестирование Наличия Изломов В Тренде Структурной Компоненты Ввп Российской Федерации," Higher School of Economics Economic Journal Экономический журнал Высшей школы экономики, CyberLeninka;Федеральное государственное автономное образовательное учреждение высшего образования «Национальный исследовательский университет «Высшая школа экономики», vol. 20(4), pages 588-623.
    15. Chernis, Tony & Cheung, Calista & Velasco, Gabriella, 2020. "A three-frequency dynamic factor model for nowcasting Canadian provincial GDP growth," International Journal of Forecasting, Elsevier, vol. 36(3), pages 851-872.
    16. Zubarev, A. & Rybak, K., 2022. "The impact of global shocks on the Russian economy: FAVAR approach," Journal of the New Economic Association, New Economic Association, vol. 56(4), pages 48-68.
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    More about this item

    Keywords

    GDP nowcasting; factor model;

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications

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