Garuva

Municipality in Santa Catarina State in Brazil

Exports (2019): $17.2M, Rnk 775/2197

Top Destination (2019): $5.41M, Uruguay

Top Export (2019): $9.9M, Other Small Iron Pipes

Imports (2019): $83.6M, Rnk 222/2197

Top Origin (2019): $30.8M, China

Top Import (2019): $31.1M, Vehicle Bodies

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

Exports: In 2019, Brazil's Garuva exported $17.2M, making it the 775th largest exporter out of the 2197 exporters in Brazil. In 2019 the top exports of Garuva were Other Small Iron Pipes ($9.9M), Tractors ($3.31M), Large Flat-Rolled Iron ($3.09M), Iron Wire ($190k), and Large Iron Containers ($136k).

Imports: In 2019, Brazil's Garuva imported $83.6M, making it the 222nd largest importer out of the 2197 importers in Brazil. In 2019 top imports of Garuva were Vehicle Bodies ($31.1M), Raw Zinc ($18.1M), Raw Aluminium ($12.9M), Vehicle Parts ($7.34M), and Combustion Engines ($3.66M).

Yearly Exports

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Value
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Top Destination (2019): Uruguay, $5.41M

Top Product (2019): Other Small Iron Pipes, $9.9M

In 2019 the top export destinations of Garuva were Uruguay ($5.41M), Mexico ($5.06M), Bolivia ($1.18M), Argentina ($1.14M), and Colombia ($1.08M).

In 2019 the top exports of Garuva were Other Small Iron Pipes ($9.9M), Tractors ($3.31M), Large Flat-Rolled Iron ($3.09M), Iron Wire ($190k), and Large Iron Containers ($136k).

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Yearly Imports

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Value
Depth

Top Origin (2019): China, $30.8M

Top Import (2019): Vehicle Bodies, $31.1M

In 2019 the top import origins of Garuva were China ($30.8M), South Korea ($16.9M), Peru ($10.4M), Mexico ($7.66M), and Russia ($6.42M).

In 2019 the top imports of Garuva were Vehicle Bodies ($31.1M), Raw Zinc ($18.1M), Raw Aluminium ($12.9M), Vehicle Parts ($7.34M), and Combustion Engines ($3.66M).

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Comparison in Time

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Flow
Value

This section shows differences between total trade from Garuva throughout time.

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

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