Influence of international trade disputes on the world industrial economic system based on inoperability input-output model

Since January 2018, the U.S. government has announced steep tariffs on a range of imports from China who then retaliated, thus triggering trade disputes. How much economic losses have the international trade disputes brought to the related parties? Which countries and industries are highly sensitive to the trade disputes? These are all important questions that have undoubtedly aroused mass concern of all circles. However, few scholars have carried out related empirical research on this issue, with little dynamic quantitative evaluation results on industry and country level obtained. Based on the static and dynamic inoperability input-output models and on the premise of several assumptions, the industrial economic system's indirect economic losses resulting from the trade disputes between China and the United States are evaluated according to the EU input-output table (WIOD2016) from January 1st to April 4th, 2018. The results show that the trade disputes severely affected the trading among China, the United States, and other countries (regions) in the world and brought about greater economic loss. Meanwhile, the countries and industries highly sensitive to the disputes are picked out. This paper provides an empirical reference for governments, industry management departments and related companies concerned with international trade disputes in assessing losses of similar events.

Automated summary

Since January 2018, the U.S. and China have been engaged in trade disputes with steep tariffs imposed on imports. This paper provides empirical research on the economic losses resulting from these disputes, using input-output models and assumptions. The study reveals that the trade disputes have significantly affected global trading and caused substantial economic losses. It also identifies the countries and industries highly sensitive to the disputes, serving as a reference for assessing losses in similar events.