Overview: This page contains the latest trade data of Knit Men's Suits. In 2019, Knit Men's Suits were the world's 286th most traded product, with a total trade of $11.8B. Between 2018 and 2019 the exports of Knit Men's Suits grew by 1.79%, from $11.6B to $11.8B. Trade in Knit Men's Suits represent 0.065% of total world trade.
Exports: In 2019 the top exporters of Knit Men's Suits were China ($3.99B), Vietnam ($976M), Cambodia ($782M), Bangladesh ($684M), and Turkey ($423M).
Ranking: Knit Men's Suits ranks 861st in the Product Complexity Index (PCI).
Description: Men's suits are used to make clothing for men. Men's suits can be made from a variety of materials, including cotton, wool, silk, and polyester.
Top Destination Growth (2018 - 2019): United States, $120M
Between 2018 and 2019, the exports of Knit Men's Suits grew the fastest in Vietnam ($138M), Honduras ($66.2M), Bangladesh ($51.3M), India ($37M), and Italy ($35.7M).
This chart shows the evolution of the market concentration of exports of Knit Men's Suits.
In 2019, market concentration measured using Shannon Entropy, was 4.19. This means that most of the exports of Knit Men's Suits are explained by 18 countries.
This map shows which countries export or import more of Knit Men's Suits. Each country is colored based on the difference in exports and imports of Knit Men's Suits during 2019.
In 2019, the countries that had a largest trade value in exports than in imports of Knit Men's Suits were China ($3.77B), Vietnam ($933M), Cambodia ($775M), Bangladesh ($681M), and India ($368M).
In 2018, the average tariff for importing Knit Men's Suits was 23.8%. The countries with the highest tariffs for importing Knit Men's Suits were Iran (100%), Syria (73.5%), South Africa (39.9%), Bolivia (38.4%), and Sudan (35%).
The Complexity-Relatedness diagram compares the risk and the strategic value of a product's potential export opportunities. Relatedness is predictive of the probability that a country increases its exports in a product. Complexity, is associated with higher levels of income, economic growth potential, lower income inequality, and lower emissions.