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Urban Studies
Правильная ссылка на статью:

Large cities of the Siberian Federal District: mutual influence of economic and demographic development / Крупные города Сибирского федерального округа: взаимовлияние экономического и демографического развития

Низамутдинов Марсель Малихович

кандидат технических наук

заведующий сектором экономико-математического моделирования, Уфимский федеральный исследовательский центр Российской академии наук

450054, Россия, республика Башкортостан, г. Уфа, Пр. Октября, 71

Nizamutdinov Marsel' Malikhovich

PhD in Technical Science

Head of the sector of Economic-Mathematical Modeling, Ufa Federal Research Center of the Russian Academy of Sciences

450054, Russia, respublika Bashkortostan, g. Ufa, Pr. Oktyabrya, 71

marsel_n@mail.ru
Другие публикации этого автора
 

 
Орешников Владимир Владимирович

кандидат экономических наук

старший научный сотрудник сектора экономико-математического моделирования, Уфимский федеральный исследовательский центр Российской академии наук

450054, Россия, республика Башкортостан, г. Уфа, ул. Пр. Октября, 71

Oreshnikov Vladimir Vladimirovich

PhD in Economics

Senior Scientific Associate, the sector of Economic-Mathematical Modeling, Ufa Federal Research Center of the Russian Academy of Sciences

450054, Russia, respublika Bashkortostan, g. Ufa, ul. Pr. Oktyabrya, 71

voresh@mail.ru
Другие публикации этого автора
 

 

DOI:

10.7256/2310-8673.2019.4.30281

Дата направления статьи в редакцию:

14-07-2019


Дата публикации:

03-01-2020


Аннотация: Работа посвящена проблеме оценки взаимовлияния экономических и демографических факторов развития крупных городов (на примере городов Сибирского федерального округа). Целью исследования является анализ тенденций и факторов взаимовлияния демографического потенциала и экономического развития крупных городов. Результаты исследования показали, что общее количество городов в СФО практически не изменилось за последнее десятилетие. Однако социально-экономическое развитие городов характеризуется неравномерностью, также произошли заметные изменения в структуре и численности населения городов. Предложен комплекс показателей для оценки динамики развития городов на основе анализа экономических и социо-демографических тенденций. Оценена динамика развития крупных городов СФО и их рейтинговая оценка, что позволило определить точки роста территории. При проведении использованы методы системного анализа, методы математической статистики, а также методы интегральной оценки, классификации и ранжирования. На основе анализа кривых Ципфа выявлена равномерная «насыщенность» городов Сибирского федерального округа. Одновременно, наблюдается обратная тенденция улучшения характеристик расселения на фоне опережающего роста крупнейших городов. Спрогнозировано, что доля населения, проживающего в городах, будет постепенно увеличиваться. Сделан вывод о необходимости учитывать выявленную взаимосвязь социо-демографических и экономических процессов при формировании мер государственной политики в сфере пространственного развития Сибирского федерального округа. Статья выполнена в рамках государственного задания ИСЭИ УФИЦ РАН по теме «Технологии и инструментарий моделирования влияния трансформации человеческого капитала на пространственно-экономическое развитие территориальных систем».


Ключевые слова:

социо-демографические процессы, городское расселение, экономическое развитие, рейтинги, закон Ципфа, Сибирский федеральный округ, пространственное развитие, крупные города, социально-экономические факторы, классификация

Abstract: This article is dedicated to the problem of assessing mutual influence of economic and demographic factors in the development of large cities (on example of cities of the Siberian Federal District). The goal lies in the analysis of trends and factors of mutual influence of demographic potential and economic development of the large cities. The research results demonstrate that the total number of cities in the Siberian Federal District for the past decade remains virtually the same. However, the author underlines the unevenness of socioeconomic development of cities, as well as noticeable changes in their structure and population. A set of indicators for assessing the dynamics of urban development based on the analysis of economic and socio-demographic trends is proposed. The dynamics of development of large cities of the Siberian Federal District and their rating is evaluated, which allows determining the areas of territorial growth. Using the Zipf curves, the author determines the even “saturation” of cities of the Siberian Federal District; and simultaneously observes the reverse trend of improving the parameters of settlement affected by rapid growth of the largest cities. It is forecasted that the portion of urban population will gradually increase The conclusion is made on the need to consider the determined link between socio-demographic and economic processing in elaboration of government policy measures in the area of spatial development of the Siberian Federal District.


Keywords:

socio-demographic processes, urban resettlement, economic development, ranking, Zipf’s law, Siberian federal district, spatial development, large cities, social-economic factors, classification

Introduction

Today the urban development trends entirely determine the Russian economic growth. The modern cities are concentration of population, production and industrial capacities, financial flows, social and cultural facilities, and workforce. At the same time city’s economic development is connected with socio-demographic processes. Changes in demographic sphere parameters (age and gender structure, intensity of migration flows, reproductive behavior, etc.) are due to the influence heterogeneous factors, both social and economic.

Thus the potentials comparative analysis and estimation cites’ development prospects have actualized located in the same macro region. The research logic is to analyze trends and development prospects for the large cities and to estimate integral indicator and ranking cities based on its value. The Siberian Federal District (SFO) was chosen as the research object because the region characterized by the combination of such factors as the large areas and population concentration in different category cities.

1. Statement of the problem: urban development in the Siberian Federal District

The territory of the Siberian Federal District is 30.1% of the entire territory of the Russian Federation (5,145 thousand km²) and includes 12 regions. The population of the district exceeds 19.3 million people (13.2% population of Russia) and the urbanization level is about 72%. The Siberian Federal District is rich in natural resources: 85% of all-Russian reserves of lead and platinum, 80% of coal and molybdenum, 71% of nickel, 69% of copper, 44% of silver, 40% of gold [7].

Regarding the demographic situation, it should be noted that the total population of the Siberian Federal District has declined markedly over the past 10 years. At the same time the urban population is decreasing, but the cities’ proportion is growing up. More than 50% of the urban population lives in cities with a population over 100 thousand people, while in these cities there has also been a slight increase in the population. The largest population growth was observed in recent years in Norilsk, Tomsk and Ulan-Ude. At the same time it should be noted that during the same period the number of cities in the Siberian Federal District remained almost unchanged [9], but small structural changes took place according to their categories (Table 1).

Table 1

The urban residents number of the Siberian regions in 2005-2015

Regions

Number of cities

Change in urban population, thousand people

Change in urban population, percentage

2015

2005

Altai region

12

12

-2,3

-0,2

Altai Republic

1

1

7,9

14,8

The Republic of Buryatia

6

6

57,9

13,0

The Republic of Khakassia

5

5

3,1

1,0

Irkutsk region

22

22

-107,9

-6,0

Kemerovo region

20

20

-40,1

-1,8

Krasnoyarsk region

23

26

-15,2

-0,8

Novosibirsk region

14

14

115,4

6,3

Omsk region

6

6

26,0

2,1

Tomsk region

6

6

57,3

8,2

Tyva Republic

5

5

9,1

6,3

Zabaykal'skiy region

10

10

5,9

1,2

TOTAL

130

133

117,2

0,9

Source: Rosstat data.

The socio-economic development of the SFD cities in is uneven [5]. There was a decrease in population of up to 10% in 12 of the 25 cities with a population over 100 thousand people. At the same time both the number and the population of the cities with a population of up to 10 and more than 500 thousand people have been increased because the number of cities moved in this category that previously were in other categories.

Changes in the demographic parameters and the settlement system had the impact on the labor market and employment indicators [1; 6]. The number of people employed in the SFD economy has increased over 10 years. At the same time employees in large cities have decreased, their share also has slightly decreased. The largest share of employees in the total population was in such cities as Norilsk, Mezhdurechensk and Irkutsk. The reason for this is both demographic and economic factors. In particular, there is a positive growth rate of the average monthly wage in large cities of the Siberian Federal District. The real growth is noticeably lower than the nominal one. In the overwhelming majority of large cities in the Siberian Federal District, an increase in labor productivity was observed in the period under review.

The city’s economy development is significantly affected by the dynamics of assets [8; 2]. The Krasnoyarsk, Irkutsk, Kemerovo and Novosibirsk regions have the greatest significant influence on their total volume in the Siberian Federal District (60% of all assets of the Siberian Federal District). At the same time assets’ depreciation degree in the SFD is below the average Russian level. For large cities of the Siberian Federal District, an increase in the volume of investments in fixed assets per 1 employee is observed. Diverse cities are also heterogeneous according to other criteria. In particular, for the 8 of the 23 large cities the decrease in construction work volume is observed. For example, there is a decrease in retail trade turnover for all major cities in the Siberian Federal District.

As part of the study, a set of 12 most significant indicators was determined [11] which allows assessing both the economic potential of urban development and the socio-demographic trends that characterize them as a comfortable environment for living and the center of the population gravity. The analysis showed that during the study period there were significant changes in socio-economic development indicators for the overwhelming majority of large cities in the Siberian Federal District. Assessing the trends of their development, all cities could be divided into 3 groups: with excess of positive trends; with an equal ratio of positive and negative trends; with excess of negative trends.

Fig.1 - Development indicators trends for large cities of the Siberian Federal District in 2005-2015

The first group includes such cities as Kyzyl, Biysk, Irkutsk, Krasnoyarsk, Novosibirsk, Omsk, Barnaul, Abakan, Kemerovo, Leninsk-Kuznetsky, Tomsk. The second group includes such cities as Ulan-Ude, Angarsk, Novokuznetsk, Mezhdurechensk, Achinsk with an equal ratio of positive and negative trends. The third group includes Rubtsovsk, Chita, Bratsk, Prokopyevsk and Norilsk. These cities are characterized by an excess of negative trends over positive, decrease in the population and the assets value that indicates decrease in the cities productive potential.

2. Methods: evaluation the urban settlement prospects using the Zipf’s rule and integral index

The population is used as one of the cities’ importance indicator. In accordance with the “Zipf’s rule” (law of “Rank-Size”) the population of any city tends to be equal to the population of the largest city divided by the sequence number of the city in the ranked series [13]. In the course of the study, Zipf’s curves were constructed for large cities of the Siberian Federal District (Fig. 2).

Источник: исследование авторов

Figure 2 - Distribution of the largest cities by the rank and size in 2005 (left) and in 2015 (right)

The Zipf’s curve for large cities of the SFD in 2015 is above the ideal curve. That characterizes the cities’ uniform “saturation” on the territory. The line goes sharply upwards and looks like a straight line explains that the first 8 cities are much larger than the subsequent ones. The Zipf’s curves location is preserved with respect to the ideal curve. It indicates that in the last 10 years the laws have not changed fundamentally. If analyze logarithms for Zipf’s curves formula then we have revealed the tendency to increasing the amount of medium and small cities and their population. Thus, the rapid growth of million-plus cities is preserved. But at the same time share of the population living in smaller cities will slightly increase.

At the next step of the analysis, it seems appropriate to rank the cities of the Siberian Federal District with population more than 100 thousand people. The complex estimation requires some integral indicator covering various characteristics of the socio-economic infrastructure. In our opinion, the most important indicators are the following: population dynamics which vividly show the true preferences of people and objective factors of urban development; income level (welfare) of the population; housing affordability; natural and environmental conditions; transport infrastructure and others. We’ve used the technique presented in [12] to assess these characteristics.

The calculation shows that the leading position is occupied by Novosibirsk (Table 2) which is the third most populous city in the Russian Federation. The leading industries in Novosibirsk are energy, gas, water, metallurgy, metalworking, mechanical engineering. They account is above 94% of the total industrial production of the city. The city has an advantageous geographical position and it allows having the largest logistics complex in the Siberian region. The developed economy, favorable position and a high level of wages make this city attractive not only for business but also for the population.

Table 2

SFD cities attractiveness rating

City

The value of the integral indicator

Place in the ranking

City

The value of the integral indicator

Place in the ranking

Novosibirsk

42,4

1

Achinsk

28,48

13

Krasnoyarsk

37,87

2

Novokuznetsk

28,07

14

Omsk

31,44

3

Biysk

27,32

15

Irkutsk

30,74

4

Chita

26,62

16

Abakan

30,04

5

Rubtsovsk

26,51

17

Kemerovo

29,99

6

Mezhdurechensk

26,04

18

Barnaul

29,75

7

Belovo

25,87

19

Angarsk

29,75

8

Kyzyl

24,94

20

Tomsk

29

9

Gorno-Altaisk

24,65

21

Norilsk

28,83

10

Leninsk-Kuznetsky

22,45

22

Bratsk

28,77

11

Prokopyevsk

21,34

23

Ulan-Ude

28,71

12

Source: authors study

Also leading positions are occupied by Krasnoyarsk, Omsk and Irkutsk. There are the largest cities of the Siberian Federal District and have developed industry as the main locomotives. At the same time, there is a tendency of their growth not only from the point of view of the population (size, social security) but also of the economy (growth of industrial indicators).

Cities occupying the last places (Leninsk-Kuznetsky and Prokopyevsk) are characterized by a significant decrease in population, due to the influence of the negative factors (difficult environmental situation, high level of hazardous industries, high share of the population over 65 years). The main type of economic activity for them is the coal industry which determined their development in the status of single-industry towns. However, today there is a problem of depletion of mineral deposits, as well as the risk of labor resources shortage [10]. Thus, maintaining excessive dependence on enterprises engaged in the extraction and primary processing of coal is dangerous for the sustainable development of these cities.

It is necessary to take measures to diversify the economy and develop new innovative industries [3]. The most important areas in this area are the revitalization of small and medium-sized businesses, science, technology and innovation, the modernization of industries and development of cost-effective high-tech equipment and technologies. The transport infrastructure development, innovative and knowledge-intensive industries aimed at modernizing existing facilities will lead to an increase in the investment attractiveness of both individual cities and the region as a whole. It does also help solve the problem of diversification and intensification of economic development [4]. To achieve the objectives at the initial stage, it is necessary to attract large investments that are impossible without the joint efforts of the state and business.

Conclusion

The analysis revealed that cities play a crucial role in the Siberian Federal District development. The aggregated groups of large cities of the Siberian Federal District were identified by study the negative and positive changes in their socio-economic situation: with predominance of positive trends; with equal ratio of positive and negative trends; with a predominance of negative trends. The study of the mutual influence of economic and demographic factors shows that the growth of industrial production and the creation of new jobs is the condition for increasing the level of urban development and the way to increase the business environment competitiveness.

Zipf’s curves study allowed concluding about the cities uniform "saturation" on the territory of the SFD. At the same time the analysis outpaced growth in million-plus cities and some growth in cities with smaller population.

The ranking of cities by the integral attractiveness indicator, in general, confirmed the leading positions of the largest cities of the Siberian Federal District which are the capitals of the regions and are characterized by the high life quality, significant investments inflow. It was noted that the mutual influence of economic and demographic factors determines the overall development of the territory. In this regard, the demographic and economic policies of government should be interconnected.

Библиография
1. Gorin N., Neshchadin A., Nizamutdinov M., Sos'kova O. (2013). Problemy razvitiya gorodskogo rasseleniya v RF, In journal “Obshchestvo i ekonomika”, 7–8, 157–166.
2. Gottmann J. (1962). Megalopolis, The Twentieth Century Fund, 157 p.
3. Kobzeva A.YU. (2014). Perspektivy razvitiya ekonomiki regiona: problemy perekhoda k innovatsionnoy ekonomike (na primere Respubliki Bashkortostan), In “Sotsial'no-ekonomicheskiye problemy razvitiya territorial'nykh sistem i mekhanizmy povysheniya ikh konkurentosposobnosti”, Trudy XII Mezhdunarodnoy konferentsii molodykh uchenykh. – Ufa, ISEI UNTS RAN, 49-52.
4. Las'ko A.I.(2014). Urbanizatsiya kak prichina ekonomicheskogo krizisa, In journal “Ekonomika i menedzhment innovatsionnykh tekhnologiy”, 7 (34), 51–53.
5. Murzin A.D. (2010). Vliyaniye urbanizatsii na ustoychivost' kompleksnogo razvitiya territorii krupnykh gorodov, In journal “Rossiyskiy Akademicheskiy Zhurnal”, 13(3), 15–18.
6. Nizamutdinov M.M. (2009). Imitatsionnoye modelirovaniye kak instrument obosnovaniya srednesrochnykh strategiy regional'nogo razvitiya, In journal “Ekonomika i upravleniye”, 5, 104–111.
7. Rozenfel'd YU.N. (2014). Problemy analiza sovremennogo urovnya urbanizirovannosti v Rossiyskoy Federatsii, In journal “Ekonomika, statistika, informatika. Vestnik UMO”, 2, 119–122.
8. Senyavskiy A.S. (2003). Urbanizatsiya Rossii v XX veke: Rol' v istoricheskom protsesse, Izd-vo Nauka, 258 p.
9. Stroyev P.V. (2014). Transformatsiya prostranstvennoy struktury Rossii, In journal “Vestnik Instituta ekonomiki Rossiyskoy akademii nauk”, 4, 61–70.
10. Trubina Ye.G. (2011). Gorod v teorii: opyty osmysleniya prostranstva, M.: Novoye literaturnoye obozreniye, 520 p.
11. Fattakhov R.V., Abdulova L.R. (2015). Ekonomiko-demograficheskiye faktory formirovaniya sistemy gorodskogo rasseleniya (na primere Tsentral'nogo federal'nogo okruga), In journal “Regional'naya ekonomika: teoriya i praktika”, 11 (386), 2–15.
12. Fattakhov R.V., Nizamutdinov M.M. (2014). Gorodskoye rasseleniye v Rossii za 50 let: otsenka tendentsiy i perspektiv, In journal “Ekonomika i matematicheskiye metody”, 50(2), 24–34.
13. Zipf G.K. (1936). The Psycho-Biology of Language: An Introduction to Dynamic Philology, L.: Routledge, 281 p.
References
1. Gorin N., Neshchadin A., Nizamutdinov M., Sos'kova O. (2013). Problemy razvitiya gorodskogo rasseleniya v RF, In journal “Obshchestvo i ekonomika”, 7–8, 157–166.
2. Gottmann J. (1962). Megalopolis, The Twentieth Century Fund, 157 p.
3. Kobzeva A.YU. (2014). Perspektivy razvitiya ekonomiki regiona: problemy perekhoda k innovatsionnoy ekonomike (na primere Respubliki Bashkortostan), In “Sotsial'no-ekonomicheskiye problemy razvitiya territorial'nykh sistem i mekhanizmy povysheniya ikh konkurentosposobnosti”, Trudy XII Mezhdunarodnoy konferentsii molodykh uchenykh. – Ufa, ISEI UNTS RAN, 49-52.
4. Las'ko A.I.(2014). Urbanizatsiya kak prichina ekonomicheskogo krizisa, In journal “Ekonomika i menedzhment innovatsionnykh tekhnologiy”, 7 (34), 51–53.
5. Murzin A.D. (2010). Vliyaniye urbanizatsii na ustoychivost' kompleksnogo razvitiya territorii krupnykh gorodov, In journal “Rossiyskiy Akademicheskiy Zhurnal”, 13(3), 15–18.
6. Nizamutdinov M.M. (2009). Imitatsionnoye modelirovaniye kak instrument obosnovaniya srednesrochnykh strategiy regional'nogo razvitiya, In journal “Ekonomika i upravleniye”, 5, 104–111.
7. Rozenfel'd YU.N. (2014). Problemy analiza sovremennogo urovnya urbanizirovannosti v Rossiyskoy Federatsii, In journal “Ekonomika, statistika, informatika. Vestnik UMO”, 2, 119–122.
8. Senyavskiy A.S. (2003). Urbanizatsiya Rossii v XX veke: Rol' v istoricheskom protsesse, Izd-vo Nauka, 258 p.
9. Stroyev P.V. (2014). Transformatsiya prostranstvennoy struktury Rossii, In journal “Vestnik Instituta ekonomiki Rossiyskoy akademii nauk”, 4, 61–70.
10. Trubina Ye.G. (2011). Gorod v teorii: opyty osmysleniya prostranstva, M.: Novoye literaturnoye obozreniye, 520 p.
11. Fattakhov R.V., Abdulova L.R. (2015). Ekonomiko-demograficheskiye faktory formirovaniya sistemy gorodskogo rasseleniya (na primere Tsentral'nogo federal'nogo okruga), In journal “Regional'naya ekonomika: teoriya i praktika”, 11 (386), 2–15.
12. Fattakhov R.V., Nizamutdinov M.M. (2014). Gorodskoye rasseleniye v Rossii za 50 let: otsenka tendentsiy i perspektiv, In journal “Ekonomika i matematicheskiye metody”, 50(2), 24–34.
13. Zipf G.K. (1936). The Psycho-Biology of Language: An Introduction to Dynamic Philology, L.: Routledge, 281 p.

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