Analysis of Long-Term and Short-Term Relationships between Electricity Consumption and Economic Growth in Industrialized Regions of Russia

Abstract

The purpose of the proposed study is to identify long-term and short-term cause-and-effect relationships between industrial electricity consumption and economic growth through comparative analysis of two neighboring regions with approximately the same industrial potential - the Sverdlovsk and Chelyabinsk regions. To solve this problem, an econometric approach is used, based on the method of testing the boundaries of autoregressive and distributed lag (ARDL) models, which determines the presence of cointegration between series. The use of this method is indispensable when studying regional problems due to the insufficient length of time series of economic indicators in the region. The variables in the comparative analysis were industrial electricity consumption, industrial production volume, economic growth rate, per capita income, and average annual number of employees. When analyzing the data, it was revealed that significant cointegrated variables for the Sverdlovsk region are the rate of economic growth and electricity consumption. Accordingly, for the Chelyabinsk region these variables are the volume of industrial production, electricity consumption and the average annual number of employees. That is, the electricity consumption of the Sverdlovsk region in the long term does not depend on the volume of industrial production and the number of employees but depends only on the rate of economic growth. In the Chelyabinsk region, accordingly, in the long term, electricity consumption depends on the volume of industrial production, the number of employees and does not depend on growth rates. Thus, the regions that, at first glance, are similar in industrial potential differ in the cause-and-effect relationships between economic growth and industrial electricity consumption. The use of causality tests made it possible to identify long-term and short-term cause-and-effect relationships between variables. The results obtained in this study illustrate the explanatory and predictive capabilities of the econometric approach in the context of analyzing cause-and-effect relationships in the economy of two neighboring regions and its energy system. These results may be important when analyzing electricity consumption and energy saving in the industrial sector of the economy of these areas.