MULTIDIMENSIONAL ANALYSIS OF THE SPATIAL STRUCTURE OF THE AGRICULTURAL SECTOR OF UKRAINIAN REGIONS: A DISCRIMINANT APPROACH
Abstract
This research presents a comprehensive analysis of the agricultural sector across Ukrainian regions, aiming to reveal regional disparities and patterns essential for informed policy-making and strategic development. Given the critical role of agriculture in Ukraine’s economy, understanding the agricultural performance of different regions is vital for optimizing policies and fostering regional growth. The research systematically classifies and evaluates agricultural indicators to uncover regional similarities and differences. A multi-step analytical approach was employed, consisting of Principal Component Analysis (PCA) to identify key indicators, Hierarchical Cluster Analysis (HCA) to group regions, and Discriminant Analysis (DA) to validate the clustering results. The study focused on six primary agricultural indicators: crop cultivation areas, agricultural product value per capita, grain production volume, average monthly agricultural wage, crop yield, and livestock live weight per capita. Based on the study's findings, three distinct clusters of regions were identified, each exhibiting unique characteristics in terms of agricultural sector development. The first cluster, comprising 12 regions is characterized by the lowest indicators of agricultural sector development. The second cluster, which includes five regions, is marked by an average level of development, with the highest average monthly agricultural wages. The third cluster, consisting seven regions, is distinguished by the highest agricultural development indicators. The analysis demonstrated excellent statistical validity, with a Wilks' Lambda value of 0.033, and a 100% accuracy rate in regional classification. Classification functions were developed to precisely categorize regions based on agricultural indicators. The research provides valuable insights for targeted agricultural policy development, regional development strategies, investment planning, and resource allocation. By establishing a data-driven framework for regional agricultural analysis, the study offers a useful tool for policymakers, agricultural experts, and regional development planners. The methodology and findings can guide future agricultural management practices and regional economic development efforts in Ukraine.
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