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Abstract <p>The article analyzes interregional trade in Russia using gravity model tools. The model estimates the elasticity of trade by the size of regions (GRP), as well as by the distance between them. In addition, the impact on trade of additional factors is studied, such as the proximity of trading regions, the presence or absence of a railway in the region, a land or sea border with other states. Particular attention is paid to the issue of measuring distances between regions. The influence of the method of calculating the distance matrix (from the simplest orthodromic to the proposed weighted one from the shortest automobile and railway distances) on the coefficients of the models is investigated. The estimates of trade elasticities by regional size obtained in the study, 1.15 and 1.05, demonstrate high accuracy and stability to the composition of factors included in the model, the observation period, and the choice of the distance matrix. Distance is also particularly important in Russia (the distance elasticity of trade is 1.15, which is lower than previously obtained estimates for Siberia and the Far East). This indicates insufficient development of transport infrastructure and other difficulties associated with distance trading. It is estimated that the absence of a railway in a region reduces its trade by approximately 30%, while the proximity of regions, in contrast, increases the volume of their mutual trade by approximately 75%. Land and sea borders with neighboring countries hinder internal exports from the region (the hypothesis about the dominance of the factor of competitive advantages of other countries was justified), while it facilitates the import of products from other regions. The type of distance matrix significantly influences the distance elasticity of trade, with limited effect on the other coefficients of the model. The importance of choosing the type of distance matrix turned out to be lower than expected. Key modeling results can be obtained in virtually any format of the matrix.</p>

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Russian Interregional Trade from the Viewpoint of the Gravity Approach

  • 期刊论文

  • 发表日期：

    2025年6月1日

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  • A. Yu. Filatov,
  • K. N. Salnikov

摘要

Abstract

The article analyzes interregional trade in Russia using gravity model tools. The model estimates the elasticity of trade by the size of regions (GRP), as well as by the distance between them. In addition, the impact on trade of additional factors is studied, such as the proximity of trading regions, the presence or absence of a railway in the region, a land or sea border with other states. Particular attention is paid to the issue of measuring distances between regions. The influence of the method of calculating the distance matrix (from the simplest orthodromic to the proposed weighted one from the shortest automobile and railway distances) on the coefficients of the models is investigated. The estimates of trade elasticities by regional size obtained in the study, 1.15 and 1.05, demonstrate high accuracy and stability to the composition of factors included in the model, the observation period, and the choice of the distance matrix. Distance is also particularly important in Russia (the distance elasticity of trade is 1.15, which is lower than previously obtained estimates for Siberia and the Far East). This indicates insufficient development of transport infrastructure and other difficulties associated with distance trading. It is estimated that the absence of a railway in a region reduces its trade by approximately 30%, while the proximity of regions, in contrast, increases the volume of their mutual trade by approximately 75%. Land and sea borders with neighboring countries hinder internal exports from the region (the hypothesis about the dominance of the factor of competitive advantages of other countries was justified), while it facilitates the import of products from other regions. The type of distance matrix significantly influences the distance elasticity of trade, with limited effect on the other coefficients of the model. The importance of choosing the type of distance matrix turned out to be lower than expected. Key modeling results can be obtained in virtually any format of the matrix.