economicsВестник РГГУ. Серия "Экономика и управление"RSUH/RGGU BULLETIN. Series Economics. Management. Law2073-6304Russian State University for the Humanities (RSUH)10.28995/2073-6304-2022-2-88-109economics-388Research ArticleЭКОНОМИКАECONOMYЭкономическое районирование Беларуси: определение количественных параметров административных единицEconomic regionalization of Belarus. Determination of quantitative parameters of administrative unitsДрагунН. П.DrahunM. P.

Николай П. Драгун, кандидат экономических наук, доцент

212000, Могилев, пр. Мира, д. 43 

Mikalai P. Drahun, Cand. of Sci. (Economics), associate professor

bld. 43, Mira Avenue, Mogilev, 212000 

dragunnp@gmail.comИвановскаяИ. В.IvanouskayaI. V.

Ирина В. Ивановская, кандидат экономических наук, доцент

212000, Могилев, пр. Мира, д. 43 

Iryna V. Ivanouskaya, Cand. of Sci. (Economics), associate professor

bld. 43, Mira Avenue Mogilev, 212000 

ivanovskayaiv@gmail.comБелорусско-Российский университетБеларусьBelarusian-Russian UniversityBelarus2022130720220288109Copyright © Драгун Н.П., Ивановская И.В., 20222022Драгун Н.П., Ивановская И.В.Drahun M.P., Ivanouskaya I.V.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://economics.rsuh.ru/jour/article/view/388

В целях повышения административной эффективности, выработки региональной политики, выявления проблем местного развития, распределения ресурсов и др. большинство стран мира подразделяют свою национальную территорию на административные единицы (регионы) (далее – АЕ). Однако, по мнению многих ученых и практиков, сложившиеся административные единицы, несмотря на их официальный статус и стабильность, в большинстве случаев имеют некоторые ограничения и недостатки, связанные с получением необходимой об их развитии информации, особенно когда речь идет о международной сопоставимости. Это обстоятельство вызывает большой интерес среди научной общественности и практиков к проблемам экономического районирования.В зарубежной литературе идентификация и разграничение регионов обычно основываются на концепции местных/региональных рынков труда. В то же время местные рынки труда подвержены влиянию большого количества внешних факторов и не являются стабильными во времени, что затрудняет процедуру определения оптимального количества и количественных параметров административных единиц. В статье представлена методика определения количественных параметров административных единиц различного уровня, основанная на применении алгоритма «случайного леса» для классификации территорий с использованием количественных и категориальных переменных, характеризующих уровень их социально-экономического развития. Апробация методики на примере Республики Беларусь позволила установить критические значения количественных параметров административных единиц первого и базового уровней, достижение которых позволит обеспечить равномерное их развитие.

In order to increase administrative efficiency, formulate regional policy, identify issues of local development, allocate resources, etc., most countries in the world subdivide their national territory into administrative units (regions). However, according to many scientists and practitioners, the established administrative units, despite their official status and stability, in most cases have some limitations and disadvantages associated with obtaining the necessary information about their development, especially when it comes to international comparability. That circumstance arouses great interest among the scientific community and practitioners in the issues of economic regionalization.In foreign literature, the identification and delineation of regions is usually based on the concept of local / regional labor markets. At the same time, local labor markets are influenced by a large number of external factors and are not stable over time, which complicates the procedure for determining the optimal number and quantitative parameters of administrative units. The article presents a methodology for determining the quantitative parameters of administrative units of various levels, based on the application of the “random forest” algorithm for the classification of territories using quantitative and categorical variables characterizing the level of their socio-economic development. Approbation of the methodology as exemplified by the Republic of Belarus made it possible to establish the critical values of the quantitative parameters of the administrative units of the first and basic levels, the achievement of which will ensure the uniform development of the selected regions.

экономическое районированиефункциональная единицаадминистративно-территориальная единицаэкономическая политикапространственное распределениерегионализацияeconomic zoningfunctional unitadministrative-territorial uniteconomic policyspatial distributionregionalizationReferencesБерченко, Драгун 2019 – Берченко Н.Г., Драгун Н.П. Критерии и факторы сложного экономического положения административно-территориальных единиц Республики Беларусь // Экономика, моделирование, прогнозирование: Сб. науч. тр. Минск: НИЭИ Мин-ва экономики Респ. Беларусь, 2019. Вып. 13. С. 22–32.Berchenko, N.G. and Drahun, M.P. (2019), “Criteria and factors of the difficult economic situation of the administrative-territorial units in the Republic of Belarus”, Ekonomika, modelirovanie, prognozirovanie: sb. nauch. tr. [Economics, modeling, forecasting, Coll. of sci. works], NIEI Min-va ekonomiki Resp. Belarus, Minsk, Belarus, vol. 13, pp. 22–32.Елизаров 2009 – Елизаров С.А. Формирование и функционирование системы административно-территориального деления БССР (1919–1991 гг.). Гомель: ГГТУ им. П.О. Сухого, 2009. 222 с.Elizarov, S.A. (2009), Formirovanie i funktsionirovanie sistemy administrativnoterritorial’nogo deleniya BSSR (1919–1991) [Formation and functioning of the system of administrative-territorial division of the BSSR (1919–1991)], Gomel, Belarus.Лис 1972 – Лис А.Г. Проблемы развития и размещения производительных сил Белоруссии. М.: Мысль, 1972. 276 с.Lis, A.G. (1972), Problemy razvitiya i razmeshcheniya proizvoditel’nykh sil Belorussii [Issues of development and distribution of the productive forces of Belarus], Mysl, Moscow, Russia.Родоман 2000 – Родоман Б.Б. Перспективы эволюции федеральных округов // Российские регионы и центр: взаимодействие в экономическом пространстве. М.: Ин-т географии РАН, 2000. С. 36–41.Rodoman, B.B. (2000), “Prospects for the evolution of federal districts. Russian regions and the centre. Interaction in the economic space”, Rossiiskie regiony i tsentr: vzaimodeistvie v ekonomicheskom prostranstve, Institut geografii RAN, Moscow, Russia, pp. 36–41.Чистобаев, Красовская, Скатерщиков 2010 – Чистобаев А.И., Красовская О.В., Скатерщиков С.В. Территориальное планирование на уровне субъектов России. СПб.: Изд-во СПбГУ, НПИ «ЭНКО»; Изд. дом «Инкери», 2010. 260 с.Chistobaev, A.I., Krasovskaya, O.V. and Skatershchikov, S.V. (2010). Territorial’noe planirovanie na urovne sub”ektov Rossii [Territorial planning at the level of constituent entities of Russia], Izdatel’skii dom “Inkeri”, Saint Petersburg, Russia.Andersen 2002 – Andersen A.K. Are commuting areas relevant for the delimitation of administrative regions in Denmark? // Regional Studies. 2002. Vol. 36. P. 833–844.Andersen, A.K. (2002), “Are commuting areas relevant for the delimitation of administrative regions in Denmark?”, Regional Studies, vol. 36, pp. 833–844.Ball 1980 – Ball R.M. The use and definition of travel-to-work areas in Great Britain: Some problems // Regional Studies: The Journal of the Regional Studies Association. 1980. Vol. 14 (2). P. 125–139.Ball, R.M. (1980), “The use and definition of travel-to-work areas in Great Britain: Some problems”, Regional Studies: The Journal of the Regional Studies Association, vol. 14 (2), pp. 125–139.Breiman 2001 – Breiman L. Random Forests // Machine Learning. 2001. Vol. 45 (1). P. 5–32.Breiman, L. (2001), “Random Forests”, Machine Learning, vol. 45 (1), pp. 5–32.Brown, Holmes 1971 – Brown L.A., Holmes J. The delimitation of functional regions, nodal regions, and hierarchies by functional distance approaches // Journal of Regional Science. 1971. Vol. 11. P. 57–72.Brown, L.A. and Holmes, J. (1971), “The delimitation of functional regions, nodal regions, and hierarchies by functional distance approaches”, Journal of Regional Science, vol. 11, pp. 57–72.Casado-Diaz 2000 – Casado-Diaz J.M. Local labour market areas in Spain: A case study // Regional Studies. 2000. Vol. 34. P. 843–856.Casado-Diaz, J.M. (2000), “Local labour market areas in Spain: A case study”, Regional Studies, vol. 34, pp. 843–856.Coombes 1986 – Coombes M.G., Green A.E., Openshaw S. An efficient algorithm to generate official statistical reporting areas: The case of the 1984 travel-to-workareas revision in Britain // Journal of the Operational Research Society. 1986. Vol. 37. P. 943–953.Coombes, M.G., Green, A.E. and Openshaw, S. (1986), “An efficient algorithm to generate official statistical reporting areas: The case of the 1984 travel-to-work-areas revision in Britain”, Journal of the Operational Research Society, vol. 37, pp. 943–953.Cörvers et al. 2009 – Cörvers F., Hensen M., Bongaerts D. Delimitation and coherence of functional and administrative regions // Regional Studies. 2009. Vol. 43. P. 19–31.Cörvers, F., Hensen, M., and Bongaerts, D. (2009), “Delimitation and coherence of functional and administrative regions”, Regional Studies, vol. 43, pp. 19–31.Drobne, Bogataj 2012 – Drobne S., Bogataj M. Evaluating functional regions // Croatian Operational Research Review (CRORR). 2012. Vol. 3. P. 14–26.Drobne, S. and Bogataj, M. (2012), “Evaluating functional regions”, Croatian Operational Research Review (CRORR), vol. 3, pp. 14–26.Drobne et al. 2010 – Drobne S., Konjar M., Lisec A. Delimitation of functional regions of Slovenia based on labour market analysis // Geod. vestn. 2010. Vol. 54. P. 481–500.Drobne, S., Konjar, M. and Lisec, A. (2010), “Delimitation of functional regions of Slovenia based on labour market analysis”, Geod. vestn., vol. 54, pp. 481–500.Erlebach et al. 2016 – Erlebach M., Tomáš, V., Tonev P. A functional interaction approach to the definition of meso regions: The case of the Czech Republic // Moravian geographical reports. 2016. Vol. 24 (2). P. 37–46.Erlebach, M., Tomáš, V. and Tonev, P. (2016), “A functional interaction approach to the definition of meso regions: The case of the Czech Republic”, Moravian geographical reports, vol. 24 (2), pp. 37–46.Farmer 2009 – Farmer C.J.Q. Data driven functional regions // Geocomputation. Sydney: University of New South Wale, 2009.Farmer, C.J.Q. (2009), “Data driven functional regions”, Geocomputation, University of New South Wales, Sydney.Farmer, Fotheringham 2011 – Farmer C.J.Q., Fotheringham, A.S. Network-based functional regions // Environment and Planning A. 2011. Vol. 43. P. 2723–2741.Florez-Revuelta, F., Casado-Diaz, J. and Martinez-Bernabeu, L. (2008), “An evolutionary approach to the delineation of functional areas based on travel-to-work flows”, International Journal of Automation and Computing, vol. 5, pp. 10–21.Florez-Revuelt 2008 – Florez-Revuelta F., Casado-Diaz J., Martinez-Bernabeu L. An evolutionary approach to the delineation of functional areas based on travel-towork flows // International Journal of Automation and Computing. 2008. Vol. 5. P. 10–21.Farmer, C.J.Q. and Fotheringham, A.S. (2011), “Network-based functional regions”, Environment and Planning A, vol. 43, pp. 2723–2741.Halas et al. 2017 – Halas M., Klapka P., Bacik V., Klobucnik M. The spatial equity principle in the administrative division of the Central European countries // PLoS ONE. 2017. Vol. 12. Issue 11. P. 1–18.Halas, M., Klapka, P., Bacik, V. and Klobucnik, M. (2017), The spatial equity principle in the administrative division of the Central European countries, PLoS ONE, vol. 12, iss. 11, pp. 1–18.Karlsson, Olsson 2006 – Karlsson C., Olsson M. The identification of functional regions: theory, methods, and applications // Ann Reg Sci. 2006. Vol. 40. P. 1–18.Karlsson, C. and Olsson, M. (2006), “The identification of functional regions: theory, methods, and applications”, Ann Reg Sci, vol. 40, pp. 1–18.Karlsson, Olsson 2006 – Karlsson C., Olsson M. The identification of functional regions: theory, methods, and applications // Ann Reg Sci. 2006. Vol. 40. P. 1–18.Klapka, P., Halás, M., Netrdová, P. and Nosek, V. (2016), “The efficiency of areal units in spatial analysis: Assessing the performance of functional and administrative regions”, Moravian Geographical Reports, vol. 24, iss. 2, pp. 47–59.Klapka et al. 2016 – Klapka P., Halás M., Netrdová P., Nosek V. The efficiency of areal units in spatial analysis: Assessing the performance of functional and administrative regions // Moravian Geographical Reports. 2016. Vol. 24. Issue 2. P. 47–59.Konjar, M., Lisec, A. and Drobne, S. (2010), “Methods for delineation of functional regions using data on commuters”, Geospatial thinking, proceedings of the 13th AGILE International Conference on Geographic Information Science, Guimarães, Portugal, pp. 1–10.Konjar 2010 – Konjar M., Lisec A, Drobne S. Methods for delineation of functional regions using data on commuters // Geospatial thinking: proceedings of the 13th AGILE International Conference on Geographic Information Science. Guimarães, Portugal. 2010. P. 1–10.Laan, L.V.D. and Schalke, R. (2001), “Reality versus policy: The delineation and testing of local labour market and spatial policy areas”, European Planning Studies, vol. 9, pp. 201–221.Laan, Schalke 2001 – Laan L.V.D., Schalke R. Reality versus policy: The delineation and testing of local labour market and spatial policy areas // European Planning Studies. 2001. Vol. 9. P. 201–221.Masser, I. and Brown, P.J.B. (1975), “Hierarchical aggregation procedures for interaction data”, Environment and Planning A, vol. 7, pp. 509–523.Masser, Brown 1975 – Masser I., Brown P.J.B. Hierarchical aggregation procedures for interaction data // Environment and Planning A. 1975. Vol. 7. P. 509–523.Masser, I. and Brown, P.J.B. (1977), “Spatial representation and spatial interaction”, Papers of the Regional Science Association, vol. 38, pp. 71–92.Masser, Brown 1977 – Masser I., Brown P.J.B. Spatial representation and spatial interaction // Papers of the Regional Science Association. 1977. Vol. 38. P. 71–92.Masser, I. and Scheurwater, J. (1980), “Functional regionalisation of spatial interaction data: an evaluation of some suggested strategies”, Environment and Planning A, vol. 12, pp. 1357–1382.Masser, Scheurwater 1980 – Masser I., Scheurwater J. Functional regionalisation of spatial interaction data: an evaluation of some suggested strategies // Environment and Planning A. 1980. Vol. 12. P. 1357–1382.Slater, P.B. (1976), “Hierarchical Internal Migration Regions of France”, IEEE Trans. Syst., Man, Cybern., vol. 6, pp. 321–324.Slater 1976 – Slater P.B. Hierarchical Internal Migration Regions of France // IEEE Trans. Syst., Man, Cybern. 1976. Vol. 6. P. 321–324.Smart, M. W. (1974), “Labour market areas: Uses and definition”, Progress in Planning, vol. 2, pp. 239–353.Smart 1974 – Smart M.W. Labour market areas: Uses and definition // Progress in Planning. 1974. Vol. 2. P. 239–353.Smart 1974 – Smart M.W. Labour market areas: Uses and definition // Progress in Planning. 1974. Vol. 2. P. 239–353.

The authors declare that there are no conflicts of interest present.