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Economic Analysis: Theory and Practice
 

Forecast of changes in the attractiveness of the Russian cities

Vol. 21, Iss. 9, SEPTEMBER 2022

Received: 12 February 2019

Received in revised form: 27 February 2019

Accepted: 22 March 2019

Available online: 29 September 2022

Subject Heading: MATHEMATICAL METHODS AND MODELS

JEL Classification: R11

Pages: 1765–1782

https://doi.org/10.24891/re.17.4.749

Vladimir V. ORESHNIKOV Institute of Socio-Economic Research, Ufa Science Centre of RAS, Ufa, Republic of Bashkortostan, Russian Federation
voresh@mail.ru

https://orcid.org/0000-0001-5779-4946

Marsel' M. NIZAMUTDINOV Institute of Socio-Economic Research, Ufa Science Centre of RAS, Ufa, Republic of Bashkortostan, Russian Federation
marsel_n@mail.ru

https://orcid.org/0000-0001-5643-1393

Subject. The research studies topical aspects of determining the attractiveness of cities as a whole and from perspectives of a certain economic entity.
Objectives. The research evaluates how the attractiveness of large Russian cities changes over the mid-term time horizon.
Methods. We conducted a factor and correlation-regression analysis so as to identify the correlation among socio-economic development indicators of the Russian cities. We used methods of structural analysis, trend analysis, scenario forecast.
Results. We pointed out steps in forecasting the attractiveness of the Russian cities and determined key metrics of their attractiveness for people, business and tourists. We outlined a set of regression equations for the said aspects and proposed an approach to forming the integral indicator. The article sets out three scenarios reflecting how the situation may unfold and forecasts how the attractiveness of the Russian cities will change in the mid-term.
Conclusions. We traced the tendency of a persistent substantial gap among leading cities and most of the other Russian cities. The competition among cities is noted to increase in the bottom part of the ranking. The findings may be used to substantiate the strategic development of the Russian cities.

Keywords: Russian cities, attractiveness, rating, modeling, forecast

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