| In the section | Articles |
| Title of the article | Estimating the Distances between Russian Regions with an Account for Transport Infrastructure |
| Pages | 96-124 |
| Author 1 | Dmitry Irekovich Galimov Senior Research Fellow Institute of Economic Forecasting RAS 47 Nakhimovsky Pr., Moscow, 117418, Russian Federation Leading Expert Center for Macroeconomic Analysis and Short-Term Forecasting 47 Nakhimovsky Pr., Moscow, 117418, Russian Federation Senior Research Fellow National Research University Higher School of Economics 20 Myasnitskaya St, Moscow, 101000, Russian Federation This email address is being protected from spambots. You need JavaScript enabled to view it. ORCID: 0009-0007-3619-3050 |
| Author 2 | Andrey Andreevich Gnidchenko Candidate of Sciences (Economics), Senior Research Fellow Institute of Economic Forecasting RAS 47 Nakhimovsky Pr., Moscow, 117418, Russian Federation Leading Expert Center for Macroeconomic Analysis and Short-Term Forecasting 47 Nakhimovsky Pr., Moscow, 117418, Russian Federation Senior Research Fellow National Research University Higher School of Economics 20 Myasnitskaya St, Moscow, 101000, Russian Federation This email address is being protected from spambots. You need JavaScript enabled to view it. ORCID: 0000-0002-0678-8324 |
| Author 3 | Vladimir Alekseevich Salnikov Candidate of Sciences (Economics), Head of Laboratory Institute of Economic Forecasting RAS 47 Nakhimovsky Pr., Moscow, 117418, Russian Federation Head of Department Center for Macroeconomic Analysis and Short-Term Forecasting 47 Nakhimovsky Pr., Moscow, 117418, Russian Federation Leading Research Fellow National Research University Higher School of Economics 20 Myasnitskaya St, Moscow, 101000, Russian Federation This email address is being protected from spambots. You need JavaScript enabled to view it. ORCID: 0000-0002-4528-4348 |
| Abstract | This study is devoted to assessing the weighted average distances between the regions of Russia according to different metrics – the shortest distances on the sphere, as well as distances by railways and highways. Such aggregated estimates are necessary for researchers of interregional processes (from migration to cargo transportation), but these estimates are not publicly available. The article fills this gap. We describe the methods for estimating distances using various metrics (relying on the Russian Railways data on ‘tariff distances’ between railway stations, information on cities’ coordinates and population, and web-services for calculating inter-city distances). The proposed metrics can be considered as an economic distance metric developed in the context of gravitational interaction studies. We estimate the distances between Russian regions using recent and highly detailed data (the distances between 2840 railway stations, the population data gathered for about 10,000 settlements). For scientific and practical purposes, the open access to resulting estimates is provided. We discuss and interpret the cases of significant discrepancies in the estimates of distances between Russian regions according to different metrics. We demonstrate that, for a number of regions, location of transport infrastructure determines the need to choose the metric of interregional distance carefully, depending on the task. We estimate the weighted distance between all regions of Russia with an account for changes in regional structure of population; on this basis, we show that since 1990s migration has been directed to regions with greater relative transport connectivity |
| Code | 332.1+338.4 |
| JEL | C82, L92, R40 |
| DOI | https://dx.doi.org/10.14530/se.2024.1.096-124 |
| Keywords | coordinates, metrics, population, distance, cargo turnover, regions, cities, stations, roads, highways, Russia |
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| For citation | Galimov D.I., Gnidchenko A.A., Salnikov V.A. Estimating the Distances between Russian Regions with an Account for Transport Infrastructure. Prostranstvennaya Ekonomika = Spatial Economics, 2024, vol. 20, no. 1, pp. 96–124. https://dx.doi.org/10.14530/se.2024.1.096-124 (In Russian) |
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| Financing | This work has been carried out within the framework of the program of fundamental research of the National Research University Higher School of Economics in 2024 (TOR-52) |
| Submitted | 20.02.2024 |
| Approved after reviewing | 28.02.2024 |
| Accepted for publication | 05.03.2024 |
| Available online | 01.04.2024 |