Assessing the Spatial Dependence of the Shipped Products Volume in Dynamics

Purpose of the study. The relevance of studying the issues of assessing the volume of shipped products is due to at least two reasons. On the one hand, its role as a resultant indicator of the activity of territorial systems, on the other, its primary nature in relation to the subsequent stages of distribution and consumption. The increase in production is directly related to domestic consumption and the possibilities of promoting manufactured goods to foreign markets, which is characterized by the volume of retail and wholesale trade. The need to search for opportunities for growth in production determines the need to expand the existing ideas about these connections, including the effects of time and space. In the context of the economic space network development, the changes cannot be ignored in production and trade processes in some territories in isolation from the processes taking place in other territories. At the same time, it is obvious that any current state is a consequence of the position achieved by the considered territory in the past. The purpose of the study is to assess the spatial dependence of the volume of the shipped products in dynamics in relation to the indicators of wholesale and retail trade.

Materials and methods. The paper evaluates spatial autocorrelation using univariate and bivariate Moran's indexes – indicators, characterizing production, distribution and exchange of goods. Based on the selected spatial dependencies, three models were consistently built on the panel data from 2010-2019 for 85 regions of the Russian Federation: pooled model, panel-based spatial lag model; model with a spatially weighted factor variable. The calculations were performed using the GeoDA program.

Results. The results showed that spatial effects should be taken into account in the study of the volume of products shipped. The value of the global Moran's index shows a high direct connection between the regions of the Russian Federation in terms of the volume of shipped products (0.29-0.39), with a weak connection for the wholesale trade turnover (0.06-0.18). In turn, the bivariate Moran's index showed that the volume of shipped products has a spatial relationship with the turnover of wholesale trade in neighboring regions of the Russian Federation. Domestic final consumption, characterized by per capita retail trade turnover, also has a positive effect on the volume of products shipped per capita. The constructed models showed that the volume of shipped products is positively affected by an increase in wholesale trade in the region and in neighboring territories, retail trade in the region and the development of production in neighboring territories.

Conclusion. The article discusses a model that allows linking the development of the production of goods with the state of the channels of their promotion both inside the territory and outside it. At the same time, the use of panel data in the calculations helps to obtain reliable and meaningful estimates in the models. Within the framework of the proposed models, it was possible to identify the connection between production and wholesale trade, which was not previously determined on cross-sectional data. The results obtained make it possible to improve the quality of decisions made in matters of the territorial organization of economic activity in the regions, contributing to the development of production that depends on the possibilities of promoting manufactured goods through the wholesale and retail network.

manufacturing, wholesale and retail trade, spatial statistics, panel data

1. Minakir P. A. Russian economic space. Strategic dead ends. Ekonomika regiona = Economy of the region. 2019; 15; 4: 967-980. DOI: 10.17059/2019-4-1. (In Russ.)

2. Mitrofanova I.V., Selyutin V.V., Ivanov N.P. “White spots” of the strategy of spatial development of Russia: discussion of the project. Regional'naya ekonomika. Yug Rossii = Regional economy. South of Russia. 2019; 7; 1: 42–55. DOI: 10.15688/ re.volsu.2019.1.4. (In Russ.)

3. Polozhentseva YU. S. Quantitative assessment of the level of development of interregional connectivity of economic space. Innovatsionnaya ekonomika: perspektivy razvitiya i sovershenstvovaniya = Innovative economy: prospects for development and improvement. 2018; 3 (29): 116–128. (In Russ.)

4. Kirillova S.A., Kantor O.G. Regional development and the quality of economic space. Region: ekonomika i sotsiologiya = Region: economics and sociology. 2010; 3: 57–80. (In Russ.)

5. Rudneva L.N., Simarova I.S. Commodity exchange as a factor of interregional connectivity of the economic space. Problemy formirovaniya yedinogo prostranstva ekonomicheskogo i sotsial'nogo razvitiya stran SNG: materialy yezhegodnoy Mezhdunarodnoy nauchnoprakticheskoy konferentsii = Problems of the formation of a single space for economic and social development of the CIS countries: materials of the annual International scientific and practical conference. Resp. ed. O.M. Barbakov, deputy. ed. Yu.A. Zobnin. 2014: 276–283. (In Russ.)

6. Volchkova I.V., Danilova M.N., Podoprigora Yu.V., Seliverstov A.A., Ufimtseva Ye.V., Shadeyko N.R. Approaches to assessing the connectivity of the socio-economic space of the agglomeration. V sbornike: Issledovaniya molodykh uchonykh: ekonomicheskaya teoriya, sotsiologiya, otraslevaya i regional'naya ekonomika= In the collection: Research of young scientists: economic theory, sociology, sectoral and regional economics. Novosibirsk; 2016: 211–217. (In Russ.)

7. Simarova I. S. Obosnovaniye regional'nogo razvitiya s uchetom svyazannosti ekonomicheskogo prostranstva: dissertatsiya kandidata ekonomicheskikh nauk: 08.00.05 = Justification of regional development taking into account the connectedness of economic space: dissertation of the candidate of economic sciences: 08.00.05. Tyumen, 2014. 146 p. (In Russ.)

8. Bakumenko O.A. Mezhregional'noye vzaimodeystviye kak faktor razvitiya regional'nykh sotsial'no-ekonomicheskikh sistem: na primere Severo – Zapadnogo federal'nogo okruga: avtoreferat dissertatsii kandidata ekonomicheskikh nauk: 08.00.05 = Interregional interaction as a factor in the development of regional socio-economic systems: on the example of the North-Western Federal District: abstract of the dissertation of the candidate of economic sciences: 08.00.05. Saint Petersburg, 2017. 16 p. (In Russ.)

9. Polyakova A.G., Simarova I.S. Regional economic space and territorial development: evaluation of the action of the forces of connectivity. Vestnik UrFU. Seriya: Ekonomika i upravleniye = Bulletin of the UrFU. Series: Economics and Management. 2014; 2: 48–60. (In Russ.)

10. Zemtsov S.P., Baburin V.L. Assessment of the potential of the economic-geographical position of the regions of Russia. Ekonomika regiona = Economy of the region. 2016; 12; 1: 117–138. DOI: 10.17059/2016-1-9. (In Russ.)

11. Blanutsa V.I. Economic-geographical location: generalization of conceptual attitudes and generation of new meanings. Geografiya i prirodnyye resursy = Geography and natural resources. 2015; 4: 7–16. (In Russ.)

12. Moran P. The interpretation of statistical maps. Journal of the Royal Statistical Society. 1948; 10: 243–251.

13. Geary R. The continiguity ratio and statistical mapping. The Incorporated Statistician. 1954; 5: 115–145. DOI: 10.2307/2986645.

14. Cliff A. D., Ord J. K. Space-Time Modelling with an Application to Regional Forecasting. Transactions of the Institute of British Geographers. 1975; 64: 119-128. DOI:10.2307/621469.

15. Cliff A. D., Ord J. K. Spatial Autocorrelation. Ord. London: Pion; 1973. 178p.

16. Anselin L. Spatial Dependence and Spatial Structural Instability in Applied Regression Analysis. Journal of Regional science. 1990; 30: 185-207. DOI:10.1111/j.1467-9787.1990.tb00092.x.

17. Anselin L., Syabri I., Smirnov O. Visualizing Multivariate Spatial Correlation with Dynamically Linked Windows [Internet]. Computing Science and Statistics. 2002. 33 p. Available from: https:// www.semanticscholar.org/paper/Visualizing- Multivariate-Spatial-Correlation-with-Mirnov/4e34 bd70317377971ba8df7259288b972ad6a239.

18. Anselin L. Local Indicators of Spatial Association-LISA. Geographical Analysis. 1995; 27(2): 93–115.

19. Davidson N. B., Mariev O. S. The impact of spatial concentration on enterprise performance. Ekonomika regiona. 2015; 4: 95-105. DOI: 10.17059/2015-4-8.

20. Zemtsov S. P., Tsareva Yu. V. Entrepreneurial Activity in the Russian Regions: How Spatial and Temporal Effects Determine the Development of Small Busines. Journal of the New Economic Association. 2018; 1(37): 118–134. DOI: 10.31737/2221-2264-2018-37-1-6.

21. Ye X., Wei Y.D. Geospatial Analysis of Regional Development in China: The Case of Zhejiang Province and the Wenzhou Model. Eurasian Geography and Economics. 2005; 46(6): 445-464. DOI:10.2747/1538-7216.46.6.445.

22. Demidova, O. Spatial effects for the eastern and western regions of Russia: a comparative analysis. International Journal of Economic Policy in Emerging Economies. 2015; 8(2): 153-168. DOI: 10.1504/ijepee.2015.069594.

23. Plyakin, A.V., Orekhova Ye. A. Spatial analysis of the economic potential of municipal districts for the management of inter-municipal interactions. Biznes. Obrazovaniye. Pravo = Business. Education. Right. 2019; 1(46): 81–89. (In Russ.)

24. Mohanty B., Bhanumurthy N.R. Regional growth policy experience in India: the spatial dimension. Asia-Pacific Journal of Regional Science. 2018; 2(2): 479–505. DOI: 10.1007/s41685-018-0075-3.

25. Villaverde J., Maza A. Productivity convergence in the European regions, 1980–2003: a sectoral and spatial approach. Applied Economics. 2008; 40 (10): 1299-1313. DOI: 10.1080 / 00036840600771361.

26. Lehmann H., Oshchepkov A., Silvagni M.G. Regional Convergence in Russia: Estimating a Neoclassical Growth Model [Internet]. ZA Discussion Papers. 2020. no. 13039. Available from: https://www.econstor.eu/bitstream/10419/216351/1/dp13039.pdf.

27. Alexeev M., Chernyavskiy A. A tale of two crises: Federal transfers and regional economies in Russia in 2009 and 2014–2015. Economic Systems. 2018; 42 (2): 175-185. DOI: 10.1016 /j.ecosys.2017.07.002.

28. Di Berardino C., D'Ingiullo D., Sarra A. Distributive trade and regional productivity growth. The Service Industries Journal. 2017; 37 (13-14): 833–857. DOI: 10.1080 / 02642069.2017.1359261.

29. Balash V.A., Fayzliyev A.R. Spatial correlation in statistical research. Vestnik Saratovskogo gosudarstvennogo sotsial'no-ekonomicheskogo universiteta = Bulletin of the Saratov State Social and Economic University. 2008; 4 (23): 122-125. (In Russ.)

30. Demidova O.A. Spatial autoregressive model for two groups of interconnected regions (on the example of the eastern and western parts of Russia). Prikladnaya ekonometrika = Applied Econometrics. 2014; 2(34): 19-35. (In Russ.)

31. Nekotoryye podkhody k modelirovaniyu otdel'nykh makroekonomicheskikh pokazateley = Some approaches to modeling selected macroeconomic indicators. Moscow: Gaidar Institute Publishing House; 2019. 312 p. (In Russ.)

32. Kupova M. K., Suslov D. A. Assessment and use of the reproductive potential of regions. Regional'naya ekonomika: teoriya i praktika = Regional economy: theory and practice. 2009; 7; 40: 33–39. (In Russ.)