Assessment the development of the commodity structure а country’s exports and imports (case study of Ukraine)

The article discusses the solution of the problem of splitting the mixture in order to solve the problem of estimating the development of the commodity structure of exports and imports of the country, using the example of quarterly values of economic indicators of Ukraine during 2016 - 2020 g.g. Ana...

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Bibliographic Details
Published in:Montenegrin journal of economics 2021-09, Vol.17 (4), p.7-16
Main Author: Malyarets, Liudmila
Format: Article
Language:English
Subjects:
Case studies
Cluster analysis
Commodities
Dimensional analysis
Economic development
Economic indicators
Evolution
Exports
Food products
Global economy
Imports
International trade
Investigations
Methods
Normal distribution
Raw materials
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Summary:The article discusses the solution of the problem of splitting the mixture in order to solve the problem of estimating the development of the commodity structure of exports and imports of the country, using the example of quarterly values of economic indicators of Ukraine during 2016 - 2020 g.g. Analysis of the scientists work involved in the solution of the mixture separation shows that there are many approaches and methods. Most of these methods provide a classical approach, supported by Pearson K., which proposed an asymmetric distribution of values to represent a mixture of two normal laws, while applying the moment method to determine the parameters of individual distributions. In modern conditions, there are other methods of mixing separation, such as EM algorithms, cluster analysis methods. The practical application of Ward s method in cluster analysis to determine the structure of the population of objects in the economy and its mathematical content is evidenced by his recommendation for the separation of the mixture. Measuring the evolution of the product structure of exports and imports is always a challenge for all countries of the world. In the asymmetric distribution of economic indicators, it is useful to distinguish two distributions by cluster analysis using the Ward's method. At the same time, to characterize these distributions use well-established estimates, namely median and interquartile range, divided by 1,35. This allows us to establish a trend of growth or decline.
ISSN:1800-5845
1800-6698
DOI:10.14254/1800-5845/2021.17-4.1