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Assessment of Interregional Economic Interactions Using Statistics of Freight Railway Transportation

  • MACROECONOMIC AND STRUCTURAL MEASUREMENTS
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Studies on Russian Economic Development Aims and scope

Abstract

This paper considers problems of analyzing and forecasting the system of interregional economic interactions. The possibilities of creating an interregional balance of manufacturing and consumption of products using data on freight traffic on the railway network are shown. The calculations of the economic connectivity of individual macroregions of the country are provided.

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Notes

  1. The position of Rosstat on this issue is described in sufficient detail in article [10].

  2. In the post-Soviet period, only a handful of studies related to compiling input-output tables for individual regions can be noted [11, 12].

  3. For a number of years, the INP RAS has been collaborating with the Institute of Economics and Transport Development (IERT) in generating forecasts for freight rail transportation. The basis of the forecast is the statistics of JSC Russian Railways [13].

  4. The structure of the real sector includes the following economic activities: agriculture and forestry, mining, manufacturing, production and distribution of electricity, gas, and water, construction, and transport and communications.

  5. If we consider the actual output and intermediate consumption throughout the economy, then the model can describe the entire set of relations existing in the country. This is exactly how models like those of L. Moses and W. Isard function [15, 16], in which, for example, trade coefficients important for a particular model are calculated on the basis of transportation data.

  6. Coefficients of full and direct costs for the most important relationships at the level of individual regions are given in the Appendix.

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ACKNOWLEDGMENTS

The author thanks researchers of the IEF RAS N.N. Mikheeva, V.V. Potapenko, N.N. Sapova, A.R. Sayapova, A.V. Suvorov, and A.A. Yantovskii for useful tips and help in writing this article.

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Authors and Affiliations

  1. Institute of Economic Forecasting, Russian Academy of Sciences, 117418, Moscow, Russia

    A. A. Shirov

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  1. A. A. Shirov
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Correspondence to A. A. Shirov.

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Translated by K. Lazarev

APPENDIX

APPENDIX

Assessment of the most important interregional ties in the consumption of intermediate products in 20177

Rank

Manufacturing

Consumption

Total cost factor

Direct cost factor

1

Khabarovsk krai

Primorskii krai

0.224

0.198

2

Krasnoyarsk krai

Khabarovsk krai

0.169

0.145

3

Khabarovsk krai

Jewish Autonomous oblast

0.096

0.077

4

Irkutsk oblast

Transbaikal krai

0.086

0.069

5

Kemerovo oblast

Altai krai

0.073

0.060

6

Irkutsk oblast

Primorskii krai

0.072

0.049

7

Kemerovo oblast

Primorskii krai

0.071

0.053

8

Krasnoyarsk krai

Republic of Khakassia

0.070

0.067

9

Altai krai

Lipetsk oblast

0.066

0.064

10

Tyumen oblast

St. Petersburg

0.062

0.062

11

Kemerovo oblast

Novosibirsk oblast

0.058

0.047

12

Vologda oblast

Kostroma oblast

0.057

0.054

13

Chelyabinsk oblast

Volgograd oblast

0.057

0.050

14

Omsk oblast

Novosibirsk oblast

0.051

0.046

15

Belgorod oblast

Lipetsk oblast

0.050

0.048

16

Chelyabinsk oblast

Sverdlovsk oblast

0.049

0.049

17

Leningrad oblast

Novgorod oblast

0.048

0.046

18

Vologda oblast

Ivanovo oblast

0.047

0.045

19

Yaroslavl oblast

Republic of Karelia

0.047

0.043

20

Amur oblast

Khabarovsk krai

0.047

0.040

21

Omsk oblast

Kemerovo oblast

0.046

0.036

22

Kemerovo oblast

Tula oblast

0.043

0.035

23

Chelyabinsk oblast

Ulyanovsk oblast

0.043

0.043

24

Samara oblast

Krasnodar krai

0.042

0.038

25

Yaroslavl oblast

Tver oblast

0.041

0.038

26

Ryazan oblast

Smolensk oblast

0.040

0.037

27

Belgorod oblast

Tula oblast

0.040

0.039

28

Chelyabinsk oblast

Republic of Bashkortostan

0.040

0.035

29

Yaroslavl oblast

Pskov oblast

0.039

0.034

30

Lipetsk oblast

Nizhny Novgorod oblast

0.038

0.036

31

Perm krai

Kirov oblast

0.038

0.035

32

Nizhny Novgorod oblast

Kaliningrad oblast

0.037

0.034

33

Komi Republic

Vologda Region

0.034

0.030

34

Chelyabinsk oblast

Novosibirsk oblast

0.031

0.026

35

Volgograd oblast

Astrakhan oblast

0.030

0.028

  1. 7 The direct cost coefficient shows what is the share of products of region r in the structure of manufacturing in region k; the coefficient of total costs shows the costs of the rth region for manufacturing a unit of final product in region k taking into account the system of interregional cooperation. When compiling the table, intraregional (diagonal) matrix coefficients were not taken into account.

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Shirov, A.A. Assessment of Interregional Economic Interactions Using Statistics of Freight Railway Transportation. Stud. Russ. Econ. Dev. 31, 153–161 (2020). https://doi.org/10.1134/S1075700720020112

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