Abstract

The article substantiates the need to adjust approaches to forecasting regional foreign trade indicators using big data analysis methods and machine learning methods. There are a large number of features of forecasting international trade, which are shown in this study. The purpose of the work is to study the features and develop a concept for constructing predictive models of indicators of foreign economic activity and ensuring an increase in the efficiency of managing the country's foreign economic activity. The article considers the need to use the economic complexity index, the product complexity index and the indicator of the identified comparative advantages as complex indicators describing endogenous and exogenous factors for building models. The proposed methodology makes it possible to increase the efficiency of managing international activities and ensure the sustainable economic development of the region.

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