8 results · AI-generated index news
W
wto.org
official

Global Trade Outlook 2026-2030

The World Trade Organization projects a 3.5% annual increase in global trade from 2026 to 2030, with Asia leading the growth. China, the US, and India are expected to be the top exporters.

I
imf.org
research

Country-wise Trade Projections 2026-2030

The International Monetary Fund forecasts that emerging markets like Brazil, Russia, and Indonesia will drive trade growth, while developed economies like the US, EU, and Japan will experience slower growth.

U
unctad.org
research

Global Trade Trends and Projections

The United Nations Conference on Trade and Development reports that global trade is expected to reach $32 trillion by 2030, with a significant increase in South-South trade and the rise of new trade corridors.

E
economist.com
article

2026-2030 Global Trade Forecast by Country

The Economist Intelligence Unit predicts that Vietnam, Malaysia, and Thailand will be among the fastest-growing exporters, while the US, China, and Germany will remain the top three trading nations.

B
brookings.edu
article

Trade Projections 2026-2030: A Global Perspective

Brookings Institution analysis suggests that global trade will be shaped by technological advancements, shifting global value chains, and the growing importance of services trade, with significant implications for trade policy.

B
bloomberg.com
video

Global Trade Outlook 2026-2030: Video Analysis

Bloomberg's video analysis discusses the key drivers of global trade growth, including the rise of emerging markets, the impact of trade agreements, and the growing importance of digital trade.

T
trademap.org
tool

Country Trade Data and Projections 2026-2030

The International Trade Centre's Trade Map provides detailed trade data and projections for over 200 countries, including trade balances, export and import growth rates, and top trading partners.

H
harvard.edu
research

Global Trade Projections 2026-2030: A Data-Driven Approach

Harvard University researchers use machine learning algorithms to forecast global trade patterns, highlighting the importance of data-driven approaches in understanding complex trade relationships and predicting future trends.