TextilesXI (Harmonized System 1992 for Section)
2020 World Trade: $774B, Rnk 7 / 21
2020 Top Exporter | Top Importer: $276B | $122B, China | United States
2020 Product Complexity: -0.39, Rnk 14 / 21
2019 - 2020 Export Growth (CAGR): -4.67%, Rnk 13 / 21
2018 Mean Tariff: 15%, Rnk 5 / 21
2020 Share of World Trade: 4.62%, Rnk 7 / 21
Overview This page contains the latest trade data of Textiles. In 2020, Textiles were the world's 7th most traded product, with a total trade of $774B. Between 2019 and 2020 the exports of Textiles decreased by -4.67%, from $812B to $774B. Trade in Textiles represent 4.62% of total world trade.
Textiles include Non-Knit Women's Suits, Knit Sweaters, Non-Knit Men's Suits, Knit T-shirts, Synthetic Filament Yarn Woven Fabric, Light Rubberized Knitted Fabric, Knit Women's Suits, Non-Retail Synthetic Filament Yarn, House Linens, and Raw Cotton, among others.
Exports In 2020 the top exporters of Textiles were China ($276B), Vietnam ($38.9B), Bangladesh ($37.3B), Germany ($35.9B), and India ($29.7B).
Imports In 2020 the top importers of Textiles were United States ($122B), Germany ($63B), United Kingdom ($35.3B), Japan ($35.3B), and France ($32.7B).
Tariffs In 2018 the average tariff for Textiles was 15%, making it the 5th lowest tariff using the Section product classification.
Ranking Textiles ranks 14th in the Product Complexity Index (PCI).
The following visualization shows the latest trends on Textiles. Countries are shown based on data availability.
For a full breakdown of trade patterns, visit the trend explorer or the product in country profile.
* Using January 2020 exchange rates when trade data is reported in local currency.
Trade By Country
Top Origin (2020): China, $276B
Top Destination (2020): United States, $122B
Textiles are the world's 7th most traded product.
In 2020, the top exporters of Textiles were China ($276B), Vietnam ($38.9B), Bangladesh ($37.3B), Germany ($35.9B), and India ($29.7B).
In 2020, the top importers of Textiles were United States ($122B), Germany ($63B), United Kingdom ($35.3B), Japan ($35.3B), and France ($32.7B).
Trade by country
Between 2019 and 2020, the exports of Textiles grew the fastest in China ($19.9B), Poland ($1.62B), Brazil ($468M), Sweden ($228M), and Saudi Arabia ($173M).
Between 2019 and 2020, the fastest growing importers of Textiles were Germany ($3.51B), Switzerland ($2.21B), Poland ($1.74B), United Kingdom ($1.17B), and United States ($1.11B).
Cumulative market share
This chart shows the evolution of the market concentration of exports of Textiles.
In 2020, market concentration measured using Shannon Entropy, was 4.39. This means that most of the exports of Textiles are explained by 21 countries.
TOP NET EXPORTER (2020): China, $250B
TOP NET IMPORTER (2020): United States, $99.6B
This map shows which countries export or import more of Textiles. Each country is colored based on the difference in exports and imports of Textiles during 2020.
In 2020, the countries that had a largest trade value in exports than in imports of Textiles were China ($250B), Bangladesh ($26.5B), India ($23.5B), Turkey ($19.2B), and Vietnam ($18.6B).
In 2020, the countries that had a largest trade value in imports than in exports of Textiles were United States ($99.6B), Japan ($28.1B), Germany ($27.1B), United Kingdom ($25.3B), and France ($18.7B).
In 2020, the world most traded Textiles, disaggragated by their HS6 level were Other Cloth Articles ($77.7B), Non-Knit Women's Suits ($56.1B), Knit Sweaters ($51.7B), Knit T-shirts ($39.8B), and Non-Knit Men's Suits ($38.4B)
This visualization shows the countries that have an important ratio of their trade related to Textiles. It is possible to select the main countries that export or import Textiles in the world, or by continent, as well as select the measure of interest.
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.
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