Biguaçu

Municipality in Santa Catarina State in Brazil

Exports (2019): $10.3M, Rnk 910/2197

Top Destination (2019): $5.81M, United States

Top Export (2019): $6.04M, Plastic Lids

Imports (2019): $13.8M, Rnk 485/2197

Top Origin (2019): $7.62M, China

Top Import (2019): $3.82M, Non-woven Textiles

Overview: This page contains the latest international trade data for Biguaçu, including export and import data.

Exports: In 2019, Brazil's Biguaçu exported $10.3M, making it the 910th largest exporter out of the 2197 exporters in Brazil. In 2019 the top exports of Biguaçu were Plastic Lids ($6.04M), Animal Meal and Pellets ($1.5M), Monofilament ($836k), Washing and Bottling Machines ($678k), and Glass Mirrors ($273k).

Imports: In 2019, Brazil's Biguaçu imported $13.8M, making it the 485th largest importer out of the 2197 importers in Brazil. In 2019 top imports of Biguaçu were Non-woven Textiles ($3.82M), Rubber Apparel ($2.06M), Poultry Meat ($1.4M), Other Plastic Products ($1.36M), and Electrical Lighting and Signalling Equipment ($1.33M).

Yearly Exports

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Value
Depth

Top Destination (2019): United States, $5.81M

Top Product (2019): Plastic Lids, $6.04M

In 2019 the top export destinations of Biguaçu were United States ($5.81M), Chile ($1.54M), Argentina ($651k), Paraguay ($565k), and Bangladesh ($394k).

In 2019 the top exports of Biguaçu were Plastic Lids ($6.04M), Animal Meal and Pellets ($1.5M), Monofilament ($836k), Washing and Bottling Machines ($678k), and Glass Mirrors ($273k).

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Yearly Imports

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Value
Depth

Top Origin (2019): China, $7.62M

Top Import (2019): Non-woven Textiles, $3.82M

In 2019 the top import origins of Biguaçu were China ($7.62M), Argentina ($2.75M), Malaysia ($1.31M), Thailand ($432k), and Germany ($387k).

In 2019 the top imports of Biguaçu were Non-woven Textiles ($3.82M), Rubber Apparel ($2.06M), Poultry Meat ($1.4M), Other Plastic Products ($1.36M), and Electrical Lighting and Signalling Equipment ($1.33M).

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This section shows forecasts for total exports and imports from Biguaçu. The forecast is based in a Long Short-Term Memory Model constructed using monthly trade data.

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