Abstract
This paper presents econometric methods and statistical datasets about changing socio-economic factors and their influence on electricity demand (on the example of Ukraine) as the instrument for forecasting electricity demand. For this purpose, based on the results of well-known economists' works in the energy field, we selected linear multiple regression equations as the main method and changes in volumes of gross domestic product, the average price for electricity and the Ukrainian population (adapted to the situation in Ukraine due to the lack of reliable statistical data on part of the territory occupied by the Russian Federation for the period of 2013-2017) as the main factors. In the course of the study, the correlation between the exploring variable factors and the demand for electricity was found to be close (for the period 2000-2017). So, the given variables were used to construct linear regression equations for forecasting electricity demand in Ukraine (for the period up to 2035). As a result, it was possible to obtain the value of demand volumes, comparable to the volumes of demand provided by the profile ministries and agencies of Ukraine.