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ECONOMIC VALUE ADDED AS AN INDICATOR OF REGIONAL ECONOMIC GROWTH

A. Moskvina, I. Filimonenko, T. Likhacheva, Z. Vasilyeva

Abstract

Not only the economy, but also the whole society’s aim at economic growth in terms of qualitative and quantitative improvement of the population’s standard of living. At present, when the innovative economic sector, the service industry and knowledge have come to the fore, the concept of economic growth requires rethinking. Approaches to determining the quality of economic growth can be classified based on the absolute quantitative economic indicators (GDP, GNP, NI, national wealth, etc.), based on the relative quantitative economic indicators (GDP per capita, consumption, savings, etc.), based on the qualitative socio-economic indicators (educational level, health, level of infrastructure development, etc.). However, the implementation of economic growth ideas for strategic planning at the sub-regional level is considered the main indicator of economic performance. Various methods of economic growth evaluation at the sub-regional level are used for economic growth assessment in terms of its quality. This paper proposes “municipal economic value added” (EVAM) as an indicator of economic growth, which can be used for regional strategic planning and generates GRP in the region and on the municipality level. A large part of EVAM is created by mining and processing industries. In sum, these two form 92.3% of EVAM. The share of trade, catering and transport makes 2.81%, production and distribution of electricity, gas and water – 2.27%, construction – 1.7%. The smallest share is for agriculture, hunting and forestry, as well as governance, social services, education and health care. As for the territorial structure of EVAM, most (more than 80%) is created in Turukhansk, Norilsk, Krasnoyarsk, the North-Yenisei areas, Krasnoyarsk Krai being considered a specific case for the research. Clustering technique (Ward’s method) was used for data processing. The target function acts as intragroup sum of squares of deviations, which is the sum of squares of distances between each point (object) and the average for the cluster containing that object. The cluster analysis showed that in terms of EVAM, Krasnoyarsk Krai municipalities can be divided into 5 clusters. The highest EVAM value is created in clusters 1 and 2, including Norilsk city, Krasnoyarsk city, Turukhansk and the North-Yenisei areas.Clusters 3, 4 including Taimyr, Bolsheuluyskiy and Motyginsky areas, lag behind the leaders, but, at the same time, are far ahead “outsiders” – other areas of the region that represent clusters five and six. In conclusion, ADSM allows not only assessing economic growth in general, but also characterizing its sources, which in turn, reflect the interests of the stakeholders of municipalities, human capital and wages, business and innovation and investment resources, tax and budget sources of regional development.

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