Investment Attractiveness of Regions: Classification Analysis for the Volga Federal District

ERI FEB RAS	Issue's contents	RUS
	Regionalistica 2021 Volume 8 number 4 pages 57-64

Title of the article	Investment Attractiveness of Regions: Classification Analysis for the Volga Federal District
Pages	57-64
Author 1	Mitrofanov Evgenii Petrovich candidate of sciences (economics), associate professor, head of the Department of Information Technology and Applied Mathematics Moscow State University of Humanities and Economics 49, Losinoostrovskaya Street, Moscow, Russia, 107150 This email address is being protected from spambots. You need JavaScript enabled to view it. ORCID: 0000-0002-8722-2321
Author 2	Kulagina Alevtina Grigorievna candidate of sciences (economics), associate professor Chuvash State University named after I.N. Ulyanov 15, Moskovsky Prospect, Cheboksary, Russia, 428015 This email address is being protected from spambots. You need JavaScript enabled to view it. ORCID: 0000-0001-5914-6029
Abstract	Based on 15 indicators of socio-economic situation, an integral indicator of the assessment of investment attractiveness was formed and ranking the subjects of the Russian Federation, which are part of the Volga Federal District. As a result of hierarchical cluster analysis, the Volga Regions are distributed in five clusters, taking into account the standard of living of the population, financial opportunities and industrial production dynamics in 2018. From the point of view of authors, the obtained classification of regions can be used in making decisions on the implementation of investment projects in the Volga Federal District.
Code	330.43+332.144
DOI	10.14530/reg.2021.4.57
Keywords	investment attractiveness of region ♦ principal component method ♦ hierarchical cluster analysis ♦ clusters ♦ Volga Federal District
Download	2021-04.57.pdf
For citation	Mitrofanov E.P., Kulagina A.G. Investment Attractiveness of Regions: Classification Analysis for the Volga Federal District. Regionalistica [Regionalistics]. 2021. Vol. 8. No. 4. Pp. 57–64. http://dx.doi.org/10.14530/reg.2021.4.57 (In Russian)
References	1. Beketova A.M. Review of Methods of Evaluation of Investment Attractiveness of the Region. Ekonomika i menedzhment innovatsionnykh tekhnologiy [Economics and Innovations Management]. 2015. No. 4. Part 1. Pp. 30–35. (In Russian) 2. Zimin V.A. Investment Activities in the Region, the Mechanisms of Its Improvement. Samara, 2019. 286 p. (In Russian) 3. Kapusta A.S. A Comparison of Existing Methods of Evaluation of Investment Attractiveness of Regions. In: WORLD SCIENCE: PROBLEMS AND INNOVATIONS : Collection of Articles of the XXVIII International Scientific and Practical Conference. In 2 Parts. Part 2. Penza, 2019. Pp. 47–50. (In Russian) 4. Kulagina A.G., Mitrofanov E.P. Formation of an Economic Entity Investment Strategy Based on a Model Analysis of the Stock Market. Kazanskiy ekonomicheskiy vestnik [Kazan Economic Vestnik]. 2020. No. 4 (48). Pp. 114–120. (In Russian) 5. Kulagina A.G., Mikhaylova T.A. Statistical Analysis of Socio-Demographic Development of Regions. Aktual’nye problemy ekonomicheskoy teorii i regional’noy ekonomiki [Actual Problems of Economic Theory and Regional Economy]. 2013. No. 1 (9). Pp. 50–54. (In Russian) 6. Sherstobitova A.A., Korneeva E.V. Modern Methods for Assessing the Investment Attractiveness of the Regions. In: Marine Technologies: Problems and Solutions – 2018. Collection of Works on Proceedings of Scientific and Practical Conferences of Teachers, Postgraduates and Employees of the KSMTU of 2018. Ed. by E.P. Masyutkin. Kerch, 2018. Pp. 36–52. (In Russian) 7. Rencher A.C. Methods of Multivariate Analysis. New York: Wiley, 2003. 738 р. 8. Ward J.H., Jr. Hierarchical Grouping to Optimize an Objective Function. Journal of the American Statistical Association. 1963. Vol. 58. No. 301. Pp. 236–244.
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