The Ukraine and EU trade balance: prediction via various models of time series

Abstract

The article examines the market of cold logistics in Ukraine (logistics of products, which requires compliance with special temperature conditions). The main problem faced by the authors was the virtual absence of statistical data in this sector of the economy. Therefore, for the study, one of the methods of Multivariate Statistical Analysis was applied, namely, Hierarchical Cluster Analysis. This method made it possible to make a dynamic (for 2017-2020 years) classification of the regions of Ukraine with respect to a latent indicator - the stable development of the cold logistics market. A robust division of 24 regions into three groups- clusters was obtained: "leaders", "middle peasants", "outsiders". The factors-symptoms that had the most significant influence on the formation of a cluster (group of regions) of leaders were determined: the volume of exports and imports, the number of modern multi-temperature logistics warehouse complexes and the income of the population of the region. To assess the environmental impact of the functioning of the cold supply logistics network, an environmental factor was used in the analysis - the volume of CO2 emissions from transport, warehousing, postal and courier activities.