FORECASTING THE LEVEL OF REGIONAL INDUSTRIAL COMPLEXES COMPETITIVENESS (EXAMPLES FROM SLOBOZHANSKY REGION)

Abstract

A methodological toolkit for forecasting the level of regional industrial complexes competitiveness has been developed basing on the examples from the Slobozhansky region. It has been noted that the development of individual industrial complexes in Ukraine is associated with the peculiarities of the geographical location, the presence of mineral resources, scientific and technical potential, historically determined processes, etc. Therefore, for the dynamic development of the regions, it is necessary to identify priority activity areas and build a strategy for regional industrial complexes management. To find out the future alternatives for the development of industrial complexes of the regions of Ukraine, (which were singled out as a result of cluster analysis), the forecasting of their economic activity results in terms of the available industry of the Slobozhansky region has been carried out. Formalized methods of mathematical statistics, basing on the quantitative characteristics of the economic objects performance, have been used as a forecasting tool. Taking into account the dynamics of changes in all areas of Ukraine's economy, the author has chosen a medium-term forecast (up to 5 years).
Among the many methods of forecasting, the author has focused on extrapolation methods, the essence of which is to spread to the future the trends that were discovered in retrospect. The scope of extrapolation methods is limited by systems that have fairly stable development rates. Those methods are rarely used in the study of microeconomic objects, but in terms of the analysis of macroeconomic objects, which include regional industrial complexes, the viability of their application is very high. The forecast of the sales volume share of all clusters of the Slobozhansky region is presented. A comparative analysis allows the author to argue that preference can be given to algorithms built on the basis of the extrusion smoothing method; when choosing algorithms built on the least squares method, an exponential function is used as the trend line.
It has been concluded that all the methods for which the prediction was carried out gave identical results. That is, the development of such industrial complexes can be called predictable, and the forecast is reliable.