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Quarterly Projection Model for the Siberian Macroregion

Author

Listed:
  • Igor Savchenko

    (Bank of Russia)

  • Marya Butakova

    (Bank of Russia)

  • Leonid Markov

    (Bank of Russia)

  • Margarita Lyakhnova

    (Bank of Russia)

  • Olga Erushina

    (Bank of Russia)

  • Roman Gartvich

    (Bank of Russia)

  • Maxim Yakovina

    (Bank of Russia)

  • Vasilii Shcherbakov

    (Bank of Russia)

Abstract

Russia's regions are characterised by strong heterogeneity of economic conditions, and, accordingly, the regions' reaction to macroeconomic shocks throughout the country, including shocks of the single monetary policy, may be heterogeneous. This paper is devoted to the development of a tool to analyse the economy of the Siberian macroregion, a semistructural model consisting of three blocks: Siberia, the rest of Russia, and the outside world. The main difference between this model and an all-Russian model lies in the different Phillips and aggregate demand curves for Siberia and the rest of Russia. The model takes into account the specifics of Siberia, including the small contribution of the region to the main macroeconomic indicators for Russia, the high share of extractive industries in output, and others. It is shown that the model describes ongoing processes in accordance with economic intuition, which allows it to be used for medium-term forecasting and analysis.

Suggested Citation

  • Igor Savchenko & Marya Butakova & Leonid Markov & Margarita Lyakhnova & Olga Erushina & Roman Gartvich & Maxim Yakovina & Vasilii Shcherbakov, 2024. "Quarterly Projection Model for the Siberian Macroregion," Russian Journal of Money and Finance, Bank of Russia, vol. 83(4), pages 48-75, December.
    • Handle: RePEc:bkr:journl:v:83:y:2024:i:4:p:48-75
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    References listed on IDEAS

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    1. Ioan Carabenciov & Charles Freedman & Mr. Roberto Garcia-Saltos & Mr. Douglas Laxton & Mr. Ondrej Kamenik & Mr. Petar Manchev, 2013. "GPM6: The Global Projection Model with 6 Regions," IMF Working Papers 2013/087, International Monetary Fund.
    2. Daniel Baksa & Mr. Aleš Bulíř & Mr. Roberto Cardarelli, 2021. "A Simple Macrofiscal Model for Policy Analysis: An Application to Morocco," IMF Working Papers 2021/190, International Monetary Fund.
    3. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    4. Oleg Kryzhanovsky & Alexander Zykov, 2022. "DEMUR: A Regional Semi-Structural Model of the Ural Macroregion," Russian Journal of Money and Finance, Bank of Russia, vol. 81(4), pages 52-85, December.
    5. Mr. Rafael A Portillo & Ms. Yulia Ustyugova, 2015. "A Model for Monetary Policy Analysis in Uruguay," IMF Working Papers 2015/170, International Monetary Fund.
    6. Stephen S. Poloz & David Rose & Robert Tetlow, 1994. "The Bank of Canada's new Quarterly Projection Model (QPM): An introduction," Bank of Canada Review, Bank of Canada, vol. 1994(Autumn), pages 23-38.
    7. Alex Pienkowski, 2019. "A Three-Country Macroeconomic Model for Portugal," IMF Working Papers 2019/281, International Monetary Fund.
    8. Mr. Jaromir Benes & Kevin Clinton & Asish George & Pranav Gupta & Joice John & Mr. Ondrej Kamenik & Mr. Douglas Laxton & Pratik Mitra & G.V. Nadhanael & Mr. Rafael A Portillo & Hou Wang & Fan Zhang, 2017. "Quarterly Projection Model for India: Key Elements and Properties," IMF Working Papers 2017/033, International Monetary Fund.
    9. Marco Bellifemine & Adrien Couturier & Rustam Jamilov, 2023. "The Regional Keynesian Cross," Discussion Papers 2311, Centre for Macroeconomics (CFM).
    10. Mr. Nils O Maehle & Tibor Hlédik & Mikhail Pranovich & Carina Selander, 2021. "Taking Stock of IMF Capacity Development on Monetary Policy Forecasting and Policy Analysis Systems," IMF Departmental Papers / Policy Papers 2021/026, International Monetary Fund.
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    Cited by:

    1. Sophia Panteeva & Sergey Arzhenovskiy & Karen Tumanyants, 2025. "Semi-Structural Model of Economy of the Southern Macroregion of Russia," Russian Journal of Money and Finance, Bank of Russia, vol. 84(2), pages 65-88, June.

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    Keywords

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    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • 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
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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