FEATURES OF BUILDING FOREIGN ECONOMIC ACTIVITY PREDICTIVE MODELS WITHIN THE INTERNATIONAL COOPERATION OF THE EAEU COUNTRIES

A. Kislyakov
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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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欧亚经济联盟国家国际合作中对外经济活动预测模型构建的特点
文章论证了利用大数据分析方法和机器学习方法调整区域对外贸易指标预测方法的必要性。国际贸易预测有很多特征,这些特征在本研究中得到了体现。研究对外经济活动指标的特征,提出构建对外经济活动指标预测模型的构想,确保提高我国对外经济活动管理效率。本文考虑需要使用经济复杂性指数、产品复杂性指数和识别比较优势指标作为描述内生和外生因素的复杂指标来构建模型。拟议的方法可以提高管理国际活动的效率,并确保该区域的可持续经济发展。
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