Forecasting the impact of population aging on economic indicators (the case of Russia)

Authors

  • Lingjing Guo Immanuel Kant Baltic Federal University, Institute of Management and Territorial Development (Kaliningrad, Russia)
  • Nikita A. Zonin Immanuel Kant Baltic Federal University, Institute of Management and Territorial Development (Kaliningrad, Russia)
  • Natalia Yu. Lukyanova Immanuel Kant Baltic Federal University, Institute of Management and Territorial Development (Kaliningrad, Russia)

DOI:

https://doi.org/10.5281/zenodo.10385652

Keywords:

population aging, forecasting, capital ratio, Solow model, investments, demographic transition, economic growth

Abstract

The article explores the possibility of using a modified Solow model to assess the impact of demographic processes on economic growth in Russia over the next 10 years. The authors propose an adapted approach to predict the impact of population aging and formulate a hypothesis about the existence of a statistically significant relationship between indicators characterizing the non-working population and the Russian economy. To test the hypothesis, data from official statistics on the subjects of the Russian Federation are used. The analysis of using the Gretl econometric package shows the presence of a statistically significant inverse linear relationship between the GRP and the coefficients of the demographic dependency ratios for the retired people. Further, the article studies the possible impact of population aging on economic growth in Russia in the coming years, using the forecast demographical data of Federal State Statistics Service. For this purpose, the authors calculate predicted dynamic aging coefficient (DAC) for 2023–2036 using the formula proposed in their previous publication. The article discusses three scenarios and a forecasts the impact of population aging on the necessary investments, which in turn affects economic growth. The methods proposed in the article " The population aging and the volume of necessary investments (the case of Russia)" were used to plot the graphs. The year 2023 was taken as an example for the forecast.

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Author Biographies

Lingjing Guo, Immanuel Kant Baltic Federal University, Institute of Management and Territorial Development (Kaliningrad, Russia)

Graduate Student

Nikita A. Zonin, Immanuel Kant Baltic Federal University, Institute of Management and Territorial Development (Kaliningrad, Russia)

PhD in Economics, Associate Professor

Natalia Yu. Lukyanova, Immanuel Kant Baltic Federal University, Institute of Management and Territorial Development (Kaliningrad, Russia)

PhD in Economics, Associate Professor

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Published

2023-12-20

How to Cite

Guo Л., Zonin Н. А. ., & Lukyanova Н. Ю. . (2023). Forecasting the impact of population aging on economic indicators (the case of Russia). Service and Tourism: Current Challenges, 17(4), 43–51. https://doi.org/10.5281/zenodo.10385652

Issue

Section

REGIONAL ISSUES OF TOURISM SERVICE