INFLUENCE OF LOGISTICS INFRASTRUCTURE OF RUSSIAN FEDERAL DISTRICTS ON THEIR SOCIAL AND ECONOMIC INDICATORS

Pavel V. Popov, Marina V. Ledeneva and Victoria V. Batmanova

Applied Econometrics and International Development, 2021, vol. 21, issue 2, 29-40

Abstract: The article deals with the issue of assessment of the relationship between the economic indicators of the Russian Federation and the logistics infrastructure of Russian Federal districts. The goal is to construct a linear model of multiple regression, which shows the degree of influence of the components of the logistics infrastructure on the economic indicators of the Russian Federation. The solution of this problem can be used in the development of comprehensive plans and Federal target programs for the development of logistics infrastructure in Federal districts of Russia. The methodological tools include the use of correlation analysis, Kolmogorov criterion, the aggregate potential of multivariate variance analysis methods and multiple regression analysis. In order to exclude the redundant variables, multicollinearity testing was also made. For each indicator the t-Student criterion was calculated and the significance level assessment was made. The values of the elements of the logistics infrastructure were taken for the period 2004–2016. The calculation was made by means of program IBM SPSS STATISTICS 20. As a result of the study, the elements of the logistics infrastructure that have the greatest impact on the economic performance of the Russian Federation were identified. As a result of the construction of linear models of multiple regression, it was shown that the transport and logistics infrastructure of St. Petersburg, Krasnodar Krai, Kirov, Sverdlovsk and Novosibirsk regions, as well as the volume of imports of goods in the Stavropol region, has the greatest impact on the economic performance of the Russian Federation. The increase in the values of the components of the transport and logistics infrastructure of these subjects of the Russian Federation by one percentage point leads to an increase in key economic indicators from 0.74% to 1.01%. Linear multiple regression models can be interpreted meaningfully because the corrected R-square explains more than 80% of the variance of the dependent variable and the F-Fisher value does not exceed 5%.

Keywords: logistics infrastructure; economic indicators of the Russian Federation; multiple regression analysis; Federal districts. (search for similar items in EconPapers)
JEL-codes: R (search for similar items in EconPapers)
Date: 2021
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