The Machine Prediction of the Mutual Trade between the PRC and the Czech Republic in the Global Extraordinary Situation

Abstract

Research background: International trade is a substantial constituent of the global and regional economic development. The analysis of mutual trade serves as a tool for a monetary expression of economic transactions between a particular country and its foreign partners for a specific period. For the Czech Republic (CR), the People’s Republic of China (PRC) is the biggest exporter and the second biggest importer. The USA, however, imposes a number of economic sanctions against the PRC that do not have any significant impact on the trade between both countries and the overall growth of the Chinese economy, yet they affect the behavior of consumers and producers both in the USA and in the PRC. Purpose of the article: The aim of this paper is to use machine learning for predicting the future values of the mutual trade between the CR and the PRC for one calendar year (i.e. 12 months). Methods: Monthly data of these two states´ import and export are used to predict bilateral trade flow. The time series begins in January 2005 and ends in April 2020. Thus, the time series contains 184 data lines. Artificial intelligence - artificial neural networks - is used to predict bilateral trade flow between the PRC and the CR. The development of trade is then compared with the mutual sanctions of the PRC and the USA. Findings & Value added: This is expected that the mutual trade balance to be negative from the perspective of the CR. COVID-19 or the sanctions imposed in the international trade will not significantly affect the development of the mutual trade between the CR and the PRC.

Keywords

• international trade
• sanctions
• machine learning prediction
• time series