Перегляд за Автор "ZELINSKA, Oksana"

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    STRUCTURIZATION OF THE REGIONS OF UKRAINE BY THE INDICATOR OF CASH ESTIMATION OF AGRICULTURAL LANDS
    (Вінницький національний аграрний університет, 2020) VOLONTYR, Liudmila; ZELINSKA, Oksana; POTAPOVA, Nadiia
    The article reveals the issue of structuring the regions of Ukraine by indicators of monetary valuation of agricultural land. On the basis of the data of the State Statistics Service of Ukraine the analysis of the structure of agricultural land was carried out, which made it possible to establish a fraction of the area of individual species of land in total. The focus is on the concentration of significant amounts of land in private ownership, which exacerbates the issue of land valuation from the perspective of possible resource management and efficiency in its use. It has been argued that fragmentation of land is one of the good reasons for the inefficient use and changing purpose of land, lack of financial resources and smallholder coherence. In accordance with the Law of Ukraine "On Land Assessment" and the data of directories of the State Service of Ukraine on Geodesy, Cartography and Cadastre for 2017 - 2019. A comparative analysis of the normative monetary valuation of agricultural land by regions of Ukraine was carried out, which became the information base for their structuring by the method of cluster analysis. It was substantiated that one of the powerful methods of multivariate analysis is the cluster analysis, which is based on a set of selected economic indicators and objects of assessment. Estimates are based on the monetary valuation of agricultural land such as: arable land, perennial plantations, hayfields and pastures. On the basis of mathematical standardization of values of indicators the matrix of imaginary Euclidian distances is calculated, became a basis for formation of 7 clusters, each of which includes a final number of objects-regions distributed on homogeneous signs and approximation on estimations of the cost of land areas. The formation of clusters on such characteristics will identify the most similar groups of objects-regions to develop a system of monitoring changes in the cost of land resources with subsequent analysis of fluctuations relative to average levels within specific clusters and in Ukraine as a whole