Abstract
The aim of this paper is to mechanically predict the import of the United States of America (USA) from the People's Republic of China (PRC). The trade restrictions of the USA and the PRC caused by the USA feeling of imbalance of trade between the two states have significantly influenced not only the trade between the two players, but also the overall climate of international trade. The result of this paper is the finding that multilayer perceptron networks (MLP) appear to be an excellent tool for predicting USA imports from the PRC. MLP networks can capture both the trend of the entire time series and its seasonal fluctuations. It also emerged that time series delays need to be applied. Acceptable results are shown to delay series of the order of 5 and 10 months. The mutual sanctions of both countries did not have a significant impact on the outcome of the machine learning prediction.
Highlights
If the value of these imported components is subtracted from Chinese export, the business deficit between the United States of America (USA) and China will be reduced by a half to roughly 1% of gross national product (GNP)
The USA strongly relies on the import from China which means that the US economy is weak in regard to industry and production
The objective of this paper was to forecast the import of the United States of America from the Peoples Republic of China using machine learning techniques
Summary
As a matter of fact, “Made in China” is a backbone of the majority of retails in the USA. These retails strongly encourage domestic consumption in all distinct categories of goods – clothes, shoes, hardware, electronics, toys, jewellery, household needs, food, TV, mobile phones etc. “Made in China” is an excellent source of profit and wealth in the USA since consumer commodities imported from low-wage Chinese economy are often sold in retails for more than a tenfold price of their production costs [6]
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
