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Short-Term Inflation Projection Based on Marker Models

Author

Listed:
  • E. V. Balatskii

    (Central Economics and Mathematics Institute, Russian Academy of Sciences)

  • N. A. Ekimova

    (Financial University under the Government of the Russian Federation)

  • M. A. Yurevich

    (Financial University under the Government of the Russian Federation)

Abstract

The article proposes a hybrid model for inflation projection that combines econometric and neural network models. At the same time, both factor variables and market markers of consumer price index growth are used as explanatory variables. It has been shown that such an approach makes it possible both to maintain the theoretical fullness of the model and to ensure high accuracy of calculations, which is unattainable when using only one type of model toolkit.

Suggested Citation

  • E. V. Balatskii & N. A. Ekimova & M. A. Yurevich, 2019. "Short-Term Inflation Projection Based on Marker Models," Studies on Russian Economic Development, Springer, vol. 30(5), pages 498-506, September.
    • Handle: RePEc:spr:sorede:v:30:y:2019:i:5:d:10.1134_s1075700719050034
    DOI: 10.1134/S1075700719050034
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    References listed on IDEAS

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    1. Ömer Özgür Bozkurt & Göksel Biricik & Ziya Cihan Tayşi, 2017. "Artificial neural network and SARIMA based models for power load forecasting in Turkish electricity market," PLOS ONE, Public Library of Science, vol. 12(4), pages 1-24, April.
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