Bìznes Inform (Apr 2020)
Methodology for Forming a Balanced System of Regional Differentiation Indicators
Abstract
A step-by-step model of forming a balanced factor system of regional differentiation indicators in terms of the canonical correlation system is proposed. The canonical correlation relationships are researched between groups of source variables for the regions of Ukraine for 2015–2019 using the Statistica PPP. The main purpose of the research is to implement the methodology of canonical correlations by identifying the object of research in two characteristic spaces; maximizing communication (spatial display of the object); reducing the amount of raw data (the possibility of eliminating irrelevant factors). The selection of the most informative variables by the characteristic of the close relationship between two sets of variables and the content of the researched processes in dynamics is made by analyzing the structure of canonical variables and the magnitude of canonical correlations. The build up dynamic models of canonical correlations for the formation of a balanced factor system of regional differentiation indicators allow a more precise and logical implementation of meaningful interpretation of the obtained results in comparison with other multidimensional methods. According to the results of the research on forming a balanced representative system of indicators, the following sets of factors have been formed: the set of the most significant factors, the set of significant factors, the set of essential factors, and the set of non-essential factors. The methodology of canonical correlations is applied, which extends the possibilities of formation and research of interconnections of different phenomena and processes in socio-economic systems of different level of hierarchy as a result of involvement in the process of analysis of systems of a large set of studied factor and resultant indicators in one set, providing a fundamental basis for forming a balanced factor system of indicators of regional development and differentiation, both in spatial and temporal, dynamic context, which will improve and upgrade implementation of development strategies and will reduce the regional unevenness.
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