Russian Federation
Russian Federation
Russian Federation
Russian Federation
UDC 332.146.2
The development of rural areas and agriculture, as the basic sector of agricultural settlements, is determined by a large number of simultaneously and cumulatively acting factors. The conducted correlation analysis of the significance of selected statistical indicators of municipalities allowed us to identify three resulting criteria that reflect the effectiveness of socio-economic development of territories from the point of view of the population, business and government: average monthly wages of employees of organizations (excluding small businesses); the volume of shipped goods of own production, performed works and services in-house; actually executed local budget revenues. Accordingly, three types of regression models were built and the degree of influence of common variables, which are significant in all models and act as the basis for conducting cluster analysis of municipalities, was assessed. The results of clustering made it possible to identify the main groups and subgroups of districts with different characteristics of indicators and directions for the development of economic potential.
statistical indicators, rural municipalities, correlation analysis, multifactor regression model, factor assessment, cluster analysis, economic potential
1. Bulkina A.M. Statisticheskiy analiz differenciacii social'no-ekonomicheskogo razvitiya municipal'nyh obrazovaniy: dis. ... kand. ekonom. nauk: 08.00.12. Novosibirsk, 2017. 241 s.
2. Voroshilov N.V. Konceptual'nyy podhod k formirovaniyu monitoringa social'no-ekonomicheskogo razvitiya municipal'nyh obrazovaniy regionov Rossii // Ekonomicheskie i social'nye peremeny: fakty, tendencii, prognoz. 2023. T. 16. № 3. S. 118-140.
3. Maslihina V.Yu. Kolichestvennaya ocenka ekonomicheskogo i social'nogo prostranstvennogo neravenstva v Privolzhskom federal'nom okruge // Internet-zhurnal «Naukovedenie». 2013. № 4. S. 1-9. URL: https://naukovedenie.ru/PDF/22evn413.pdf (data obrascheniya: 20.03.2024).
4. Spicyna L.Yu., Tatarnikova V.V., Spicyn V.V. Issledovaniya faktorov, vliyayuschih na razvitie municipal'nyh obrazovaniy v Rossii: formirovanie bazy dannyh dlya ekonometricheskogo modelirovaniya // Informacionnye tehnologii v nauke, upravlenii, social'noy sfere i medicine: sbornik nauchnyh trudov V Mezhdunarodnoy nauchnoy konferencii, Tomsk, 17-21 dekabrya 2018 g. Tomsk: Tomskiy politehnicheskiy universitet, 2018. S. 96-100.
5. Federal'naya sluzhba gosudarstvennoy statistiki Rossiyskoy Federacii: baza pokazateley municipal'nyh obrazovaniy. URL: https://rosstat.gov.ru/dbscripts/munst/ (data obrascheniya: 10.04.2024).
6. Hill, T., Lewicki, P. (2007). STATISTICS: methods and applications. Tulsa, OK, StatSoft, 719 p.
7. Gafarova E.A., Lakman I.A. Ekonometricheskoe modelirovanie razvitiya municipal'nyh obrazovaniy regiona s uchetom ih neodnorodnosti (na primere Respubliki Bashkortostan) // Voprosy statistiki. 2017. № 4. S. 54-63.
8. Mirkin B.G. Metody klaster-analiza dlya podderzhki prinyatiya resheniy: obzor / preprint WP7/2011/03. M.: ID Nacional'nogo issledovatel'skogo universiteta «Vysshaya shkola ekonomiki», 2011. 88 s.
9. Tatarnikova V.V. Klasterizaciya municipal'nyh obrazovaniy po urovnyu byudzhetnoy obespechennosti i ekonomicheskogo razvitiya territoriy // Nauchnoe obozrenie. Seriya 1. Ekonomika i pravo. 2019. № 3-4. S. 90-103.
10. Vinnichek L.B., Kindaev A.Yu., Moiseev A.V. Sistema indikativnyh pokazateley dlya klassifikacii territoriy po tipam prirodno-klimaticheskogo i agrarno-ekonomicheskogo razvitiya // Ekonomika sel'skogo hozyaystva Rossii. 2023. № 5. S. 62-68.



