Artificial filament tow550200 (Harmonized System 1992 for 6-digit)
2020 World Trade: $1.76B, Rnk 1361 / 4613
2020 Top Exporter | Top Importer: $625M | $188M, United States | Nigeria
2020 Product Complexity: 1.53, Rnk 214 / 4783
2019 - 2020 Export Growth (CAGR): -7.87%, Rnk 2242 / 4613
2018 Mean Tariff: 4.72%, Rnk 4429 / 6538
2020 Share of World Trade: 0.011%, Rnk 1361 / 4613
Overview This page contains the latest trade data of Artificial filament tow. In 2020, Artificial filament tow were the world's 1361st most traded product, with a total trade of $1.76B. Between 2019 and 2020 the exports of Artificial filament tow decreased by -7.87%, from $1.91B to $1.76B. Trade in Artificial filament tow represent 0.011% of total world trade.
Artificial filament tow are a part of Artificial Filament Tow.
Exports In 2020 the top exporters of Artificial filament tow were United States ($625M), Germany ($228M), Japan ($222M), Belgium ($217M), and China ($146M).
Imports In 2020 the top importers of Artificial filament tow were Nigeria ($188M), Netherlands ($147M), Indonesia ($132M), United Arab Emirates ($92.5M), and Turkey ($83.9M).
Tariffs In 2018 the average tariff for Artificial filament tow was 4.72%, making it the 4429th lowest tariff using the HS6 product classification.
Ranking Artificial filament tow ranks 214th in the Product Complexity Index (PCI).
The following visualization shows the latest trends on Artificial filament tow. 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): United States, $625M
Top Destination (2020): Nigeria, $188M
Artificial filament tow are the world's 1361st most traded product.
In 2020, the top exporters of Artificial filament tow were United States ($625M), Germany ($228M), Japan ($222M), Belgium ($217M), and China ($146M).
In 2020, the top importers of Artificial filament tow were Nigeria ($188M), Netherlands ($147M), Indonesia ($132M), United Arab Emirates ($92.5M), and Turkey ($83.9M).
Trade by country
Between 2019 and 2020, the exports of Artificial filament tow grew the fastest in China ($23.3M), Netherlands ($14.3M), United Arab Emirates ($10.7M), United States ($10.2M), and Germany ($9.89M).
Between 2019 and 2020, the fastest growing importers of Artificial filament tow were Nigeria ($39.6M), Poland ($24.2M), Netherlands ($14.4M), United Arab Emirates ($12.9M), and Egypt ($8.9M).
Cumulative market share
This chart shows the evolution of the market concentration of exports of Artificial filament tow.
In 2020, market concentration measured using Shannon Entropy, was 3.05. This means that most of the exports of Artificial filament tow are explained by 8 countries.
TOP NET EXPORTER (2020): United States, $620M
TOP NET IMPORTER (2020): Indonesia, $131M
This map shows which countries export or import more of Artificial filament tow. Each country is colored based on the difference in exports and imports of Artificial filament tow during 2020.
In 2020, the countries that had a largest trade value in exports than in imports of Artificial filament tow were United States ($620M), Japan ($220M), Germany ($180M), Belgium ($136M), and China ($84.1M).
In 2020, the countries that had a largest trade value in imports than in exports of Artificial filament tow were Indonesia ($131M), Netherlands ($88.6M), Turkey ($82.1M), United Arab Emirates ($68M), and Poland ($60.7M).
This visualization shows the countries that have an important ratio of their trade related to Artificial filament tow. It is possible to select the main countries that export or import Artificial filament tow 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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