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Econometric Models for Russia’s GDP Analysis and Forecasting in the Industrial Section of the Economy in Conditions of Its Digital Transformation

Author

Listed:
  • Taisa Kasimova

    (Dagestan State University)

  • Sabina Magomedova

    (Dagestan State University)

  • Zaur Ismikhanov

    (Dagestan State University)

Abstract

The digital transformation of the global economy leads to the system digital transition of production sector relations too. But the issue of digitalization impact on the country’s GDP has not been explored before. A set of econometric models for the analysis of gross domestic product dependence on the capital expenditures, labor ones, as well as the expenditures on information and communication technologies and their forecasting has been developed in the article. The figures for the period from 2010 to 2018 according to the Russian Federation data on the whole and those within the context of the main types of economic activity are considered. The approach made it possible to consider the features of digital transformation in different production sectors. While comparing different forecast indicators studied, the authors concluded that the forecast variables obtained from the models of time series and models of series of dynamics of a linear type practically coincide for the GDP of the Russian Federation as a whole and for most sectors of the economy taken separately. Based on the calculation of actual and forecast values of production efficiency indicators, it was found that labor productivity in the field of mining in 2021 will double if compared with its average value for 2010–2018. The growth of capital productivity is only foreseen in information and communication, financial and insurance activities, and education. The authors come to a conclusion that the volume of national expenditures on ICT to GDP of the Russian Federation in 2021 will be slightly higher than that in 2018, with the maximum input in information and communication.

Suggested Citation

  • Taisa Kasimova & Sabina Magomedova & Zaur Ismikhanov, 2021. "Econometric Models for Russia’s GDP Analysis and Forecasting in the Industrial Section of the Economy in Conditions of Its Digital Transformation," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 12(4), pages 1694-1716, December.
    • Handle: RePEc:spr:jknowl:v:12:y:2021:i:4:d:10.1007_s13132-020-00687-5
    DOI: 10.1007/s13132-020-00687-5
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    References listed on IDEAS

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    Cited by:

    1. Kai Chang & Huijia Zhang & Boyang Li, 2024. "The Impact of Digital Economy and Industrial Agglomeration on the Changes of Industrial Structure in the Yangtze River Delta," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(2), pages 9207-9227, June.

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