Modelling of Economic Development of Single-Industry Towns in the Mining Region

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


Release:

2018, Vol. 4. №4

Title: 
Modelling of Economic Development of Single-Industry Towns in the Mining Region


For citation: Antonova I. S., Pchelintsev E. A. 2018. “Modelling of Economic Development of Single-Industry Towns in the Mining Region”. Tyumen State University Herald. Social, Economic, and Law Research, vol. 4, no 4, pp. 200-218. DOI: 10.21684/2411-7897-2018-4-4-200-218

About the authors:

Irina S. Antonova, Cand. Sci. (Econ.), Associate Professor, School of Engineering Entrepreneurship, Tomsk Polytechnic University; antonovais@tpu.ru

Evgeny A. Pchelintsev, Cand. Sci. (Phys.-Math.), Associate Professor, Department of Mathematical Analysis and Function Theory, Tomsk State University; evgen-pch@yandex.ru

Abstract:

High concentration of single-industry towns in the Kemerovo Region opens additional possibilities for the application of mathematical analysis revealing regularities of single-industry towns’ development, the urgency of which is extremely high in the last decade.

This article aims to identify the factors and build the economic models of the region with a high concentration of mining companies. Based on the data of information-analytical system “SPARK-Interfax”, the authors form the database of 84 town-forming enterprises carrying out activity in 20 towns of the Kemerovo Region. The concentration and diversification indicators identify the highest concentration of the single industries revenues in Kiselevsk, Mezhdurechensk, Kaltan, and Yashkino, and the greatest diversification — in Novokuznetsk. The authors establish that the level of diversification and concentration depends on the population, as proven by correlation analysis. Dispersion analysis with the use of Kraskall-Wallis, Friedman, and Wilcoxon non-parametric criteria showed positive dynamics in the indicators of net profit and profitability, unrelated to the price growth. Based on the correlation and regression analysis, the authors constructed the dependence models for three groups of enterprises: security, medical, and building from town-forming enterprises.

The resulting models have showed a direct proportional relationship between these enterprises. The growing need for protection in towns with the growth of revenues of town-forming enterprises testifies to the level of crime situation. Proportional dependence between the revenues of medical institutions and single industry enterprises characterizes the level of corporate social responsibility of core enterprises. The obtained results allow high dependence of auxiliary branches from core industry.

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