Spatial clustering of single-industry towns and a dynamic model of economic growth

Tyumen State University Herald. Social, Economic, and Law Research


Release:

2019, Vol. 5. №4(20)

Title: 
Spatial clustering of single-industry towns and a dynamic model of economic growth


For citation: Antonova I. S., Pchelintsev E. A., Popova S. N. 2019. “Spatial clustering of single-industry towns and a dynamic model of economic growth”. Tyumen State University Herald. Social, Economic, and Law Research, vol. 5, no 4 (20), pp. 138-154. DOI: 10.21684/2411-7897-2019-5-4-138-154

About the authors:

Irina S. Antonova, Cand. Sci. (Econ.), Associate Professor, School of Engineering Entrepreneurship, Tomsk Polytechnic University; ORCID: 0000-0002-4993-2904, Scopus Author ID: 57190000309, WoS ResearcherID: Q-4782-2016, antonovais@tpu.ru

Evgeny A. Pchelintsev, Ph. D., Cand. Sci. (Phys.-Math.), Associate Professor, Department of Mathematical Analysis and Function Theory, Tomsk State University; ORCID: 0000-0001-7496-2606, Scopus Author ID: 55588677200, WoS ResearcherID: N-8354-2016, evgen-pch@yandex.ru

Svetlana N. Popova, Cand. Sci. (Econ.), Associate Professor, School of Engineering Entrepreneurship, Tomsk Polytechnic University; snp@tpu.ru

Abstract:

This article studies the problems of economic growth and spatial development of regions with a high concentration of single-industry towns. The authors aim to identify the factors of development of single-industry towns at the microeconomic level on the basis of clustering and dynamic modeling of single-industry towns in three regions with the highest concentration — Kemerovo, Sverdlovsk, and Chelyabinsk Regions. This paper performs the clustering of single-industry towns by entropy indicators and the number of newly created enterprises, which allows distinguishing three “central” single-industry towns in each of the respective regions: Novokuznetsk, Nizhniy Tagil, and Magnitogorsk.
The clustering of single-industry towns with the use of the population-normalized index of the number of newly created enterprises allows us to refer these cities to two different clusters: Novokuznetsk against Nizhniy Tagil and Magnitogorsk with different parameters dominating. The correlation analysis of aggregate revenue, fixed assets, the share of the single industry, the entropy of revenue, the number of newly created enterprises of three single-industry towns allows suggesting a dynamic regression model. The peculiarity of this model is the inclusion as a variable of the number of the newly created enterprises in Nizhniy Tagil for all the cities under consideration, as well as the inclusion of a dummy variable reflecting the year of introduction of the program for the development of single-industry towns. Using the bootstrap method for Novokuznetsk, the authors have confirmed the significance of the introduction of this variable.
The results of the study have revealed both common patterns of regional development — the positive effect of reducing the share of monaurally and monocentric provision of single-industry towns in the regions for economic growth — and their differences — a contradictory effect of diversity in the central towns, as well as the assignment of Novokuznetsk and Nizhniy Tagil with Magnitogorsk from different clusters. In conclusion, the authors justify the early completion of the program of diversification of single-industry towns, designed to be ineffective in 2019.

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