STUDY OF THE ROAD TRANSPORT INDICATORS BY METHODS OF FORMING AN INTEGRAL FACTOR

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Abstract

The transport system of Russia is an important component of the industrial infrastructure, and its development is one of the priorities of state activities. In the context of integrated regional development, transport is a tool for implementing the economic interests of subjects. Currently, the transport system of the Russian Federation is actively developing. This largely determines the development of economic indicators, such as imports and exports, as well as an increase in the volume of sales of goods of their own production. In this regard, it is important and relevant to study the current state of the transport system and the factors of its development. The paper explores the forms of dependent indicators of the road transport industry of the Volga Federal District. Due to the limited sample size, it is proposed to study this area using the formation of integral indicators using discriminant and canonical analysis methods. The use of canonical variables as integral indicators expands the possibilities of applying canonical correlation in other analyses, including in econometric modeling. The integral factor calculated by the discriminant analysis algorithm reduces the dimension and allows us to estimate the degree of crowding and the form of dependence between the integral variables in conditions of a small sample size.

About the authors

Evgeniya N. Barysheva

Samara National Research University

Author for correspondence.
Email: barisheva.en@ssau.ru
ORCID iD: 0000-0002-2455-1152

senior lecturer of the Department of Mathematics and Business Informatics

Russian Federation

Irina S. Maximova

Samara National Research University

Email: irina.maximova@yandex.ru
ORCID iD: 0000-0002-8531-2497

Master of the direction of Business Informatics

Russian Federation

References

  1. Gaysin I.T., Gaysin R.I., Vlasova E.I. Features of studying geography of the transport complex of the Volga Federal district in the course of the economic geography of Russia. Modern high technologies, 2016, pp. 94–98. Available at: https://www.elibrary.ru/item.asp?id=26098134. (In Russ.)
  2. Bobrova V.V., Berezhnaya L.Yu. Investigating the problems of transport infrastructure development: The Volga Federal District case. Regional Economics: Theory and Practice, 2018, vol. 16, no. 12, pp. 2292–2302. DOI: http:// doi.org/10.24891/re.16.12.2292. (In Russ.)
  3. Tindova M.G. Dynamic analysis of russian rail transport. Economic Development Research Journal, 2019,
  4. no. 11, pp. 64–Available at: https://www.elibrary.ru/item.asp?id=41552390. (In Russ.)
  5. Trusova A.Yu. Analysis of indicators of innovative potential by multimeasuring statistical methods. Vestnik Samarskogo Universiteta. Ekonomika i upravlenie = Vestnik of Samara University. Economics and Management, 2018, vol. 9, no. 4, pp. 82–87. URL: https://journals.ssau.ru/index.php/eco/article/view/6705. (In Russ.)
  6. Svetunkov S.G., Zagranovskaya A.V., Svetunkov I.S. Complex analysis and modeling of uneven socio-economic development of Russian regions: scientific publication. Saint Petersburg: Nauchnaya kniga, 2012,
  7. p. (In Russ.)
  8. Soshnikova L.A., Tamashevich V.N. Multidimensional statistical analysis in economics: textbook for universities. V.N. Tamashevich (Ed.). Moscow: YuNITI-DANA, 1999, 201 p. (In Russ.)
  9. Sokolov G.A., Sagitov R.V. Introduction to regression analysis and planning of regression experiments in economics: textbook. Moscow: Infra-M, 2016, 352 p. (In Russ.)
  10. Bazhenov O.V. [et al.] Econometric estimation of factor's influence on the size of the financial sector. Economics and Mathematical Methods, 2017, no. 53 (2), pp. 40–49. Available at: https://www.elibrary.ru/
  11. item.asp?id=(In Russ.)
  12. Draper N. Applied regression analysis. Translation from English by Yu.P. Adler, V.G. Gorsky. Moscow: Finansy i statistika, 2016, 349 p. (In Russ.)
  13. Goridko N.P., Nizhegorodtsev R.M. Points of growth of regional economy and regression assessment of industry investment multipliers. Economy of Region, 2018, vol. 14, issue 1, pp. 29–42. DOI: http:// doi.org/10.17059/2018-1-3. (In Russ.)
  14. Ayvazyan S.A. Applied statistics and fundamentals of econometrics. Moscow: Yuniti, 2014, 1024 p.
  15. (In Russ.)
  16. Federal State Statistics Service. Russian Statistical Yearbook. Available at: http://www.gks.ru/
  17. wps/wcm/connect/rosstat_main/rosstat/ru/statistics/publications/catalog. (In Russ.)

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