HS Icon Prepared Cotton

5203 (Harmonized System 1992 for 4-digit)

 2019
World Trade
: $247M, Rnk 1116 / 1217

2019
Top Exporter | Top Importer
: $37.7M | $45.9M, Mexico | Vietnam

2018 - 2019
Export Growth (CAGR)
: -1.25%, Rnk 493 / 1217

2018
Mean Tariff
: 2.74%, Rnk 1163 / 1259

 2019
Share of World Trade
: 0.0014%, Rnk 1116 / 1217

Overview:  This page contains the latest trade data of Prepared Cotton. In 2019, Prepared Cotton were the world's 1116th most traded product, with a total trade of $247M. Between 2018 and 2019 the exports of Prepared Cotton decreased by -1.25%, from  $250M to $247M. Trade in Prepared Cotton represent 0.0014% of total world trade.

Exports: In 2019 the top exporters of Prepared Cotton  were Mexico ($37.7M), Indonesia ($30.1M), United States ($26.7M), India ($20.5M), and Turkey ($20.1M).

Imports: In 2019 the top importers of Prepared Cotton were Vietnam ($45.9M), Pakistan ($24.1M), Chinese Taipei ($20.6M), United Kingdom ($13.4M), and France ($12.8M).

Tariffs: In 2018 the average tariff for Prepared Cotton was 2.74%, making it the 1163rd lowest tariff using the HS4 product classification.

The countries with the highest import tariffs for Prepared Cotton are Bahamas (40.2%), India (24.8%), China (20.5%), Haiti (15%), and Maldives (14.6%). The countries with the lowest tariffs are Angola (0%), Kenya (0%), Mauritius (0%), Rwanda (0%), and Tanzania (0%).

Exporters and Importers

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Trade By Country

Top Origin (2019): Mexico, $37.7M

Top Destination (2019): Vietnam, $45.9M

Prepared Cotton are the world's 1116th most traded product.

In 2019, the top exporters of Prepared Cotton were Mexico ($37.7M), Indonesia ($30.1M), United States ($26.7M), India ($20.5M), and Turkey ($20.1M).

In 2019, the top importers of Prepared Cotton were Vietnam ($45.9M), Pakistan ($24.1M), Chinese Taipei ($20.6M), United Kingdom ($13.4M), and France ($12.8M).

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Market Dynamics

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Trade by country

Value

Top Origin Growth (2018 -  2019): Indonesia, $13.8M

Top Destination Growth (2018 - 2019): Vietnam, $24.7M

Between 2018 and 2019, the exports of Prepared Cotton grew the fastest in Indonesia ($13.8M), Mexico ($9.78M), United States ($4.87M), India ($4.55M), and Lesotho ($4.41M).

Between 2018 and 2019, the fastest growing importers of Prepared Cotton were Vietnam ($24.7M), France ($4.13M), Hong Kong ($3.69M), Japan ($3.17M), and Belgium ($2.92M).

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Market Concentration

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Cumulative market share

This chart shows the evolution of the market concentration of exports of Prepared Cotton.

In 2019,  market concentration measured using Shannon Entropy, was 4.37. This means that most of the exports of Prepared Cotton are explained by 20 countries.

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TOP NET EXPORTER (2019): Mexico, $35.6M

TOP NET IMPORTER (2019): Vietnam, $39.1M

This map shows which countries export or import more of Prepared Cotton. Each country is colored based on the difference in exports and imports of Prepared Cotton during 2019.

In 2019, the countries that had a largest trade value in exports than in imports of Prepared Cotton were Mexico ($35.6M), Indonesia ($29.4M), United States ($25.1M), Turkey ($19M), and India ($18.2M).

In 2019, the countries that had a largest trade value in imports than in exports of Prepared Cotton were Vietnam ($39.1M), Chinese Taipei ($20.5M), Pakistan ($12.9M), United Kingdom ($12.4M), and France ($10.5M).

Disaggregation

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Value

In 2019, the world most traded Prepared Cotton, disaggragated by their HS6 level were Cotton, carded or combed ($247M)

Import Tariffs

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In 2018, the average tariff for importing Prepared Cotton was 2.74%.  The countries with the highest tariffs for importing Prepared Cotton were Bahamas (40.2%), India (24.8%), China (20.5%), Haiti (15%), and Maldives (14.6%).

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Product Complexity

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Diversification Frontier

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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.