Key statistics and trends in trade policy 2019: retaliatory tariffs between the United States and China

The report analyzes trade policies and trends, focusing on retaliatory tariffs between the United States and China, highlighting their impact on global trade dynamics and economic growth.

(Generated with the help of GPT-4)

Quick Facts
Report location: source
Language: English
Publisher: United Nations
Publication date: 2020
Authors: Alessandro Nicita
Geographic focus: United States, China, Global

Methods

The research method involved analyzing trade statistics and policy measures, utilizing data from various sources including UNCTAD's TRAINS database, WTO's tariff schedules, and COMTRADE trade data. The report also included calculations of tariff restrictiveness and trade flows across different regions and sectors.

(Generated with the help of GPT-4)

Key Insights

The report discusses the state of international trade policies in 2019, emphasizing the significant rise in retaliatory tariffs between the United States and China. Prior to the trade tensions, the U.S. imported approximately $500 billion worth of goods from China, while China imported around $130 billion from the U.S. By 2019, these figures were projected to drop to $430 billion and $100 billion, respectively. The report indicates that these tariffs have broader implications for global economic growth, as they create adjustment costs for international firms, affecting investment and productivity. It also notes that while tariffs have remained stable in many sectors, non-tariff measures are increasingly prevalent, contributing to trade tensions. The report is structured into two main parts: the first focuses on the U.S.-China trade conflict, while the second examines various trade policy instruments, including tariffs, trade agreements, non-tariff measures, trade defense measures, and exchange rates. Overall, the findings suggest that ongoing trade frictions could lead to significant shifts in global trade patterns and economic stability.

(Generated with the help of GPT-4)

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Last modified: 2024/09/13 02:55 by davidpjonker