Américo Brasiliense

Municipality in São Paulo State in Brazil

Exports (2019): $111M, Rnk 295/2197

Top Destination (2019): $23.1M, Bangladesh

Top Export (2019): $101M, Raw Sugar

Imports (2019): $3.75M, Rnk 756/2197

Top Origin (2019): $1.66M, India

Top Import (2019): N/A, N/A

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

Exports: In 2019, Brazil's Américo Brasiliense exported $111M, making it the 295th largest exporter out of the 2197 exporters in Brazil. In 2019 the top exports of Américo Brasiliense were Raw Sugar ($101M), Alcohol > 80% ABV ($7.4M), Aqueous Paints ($2.21M), Nonaqueous Paints ($205k), and Excavation Machinery ($48.8k).

Imports: In 2019, Brazil's Américo Brasiliense imported $3.75M, making it the 756th largest importer out of the 2197 importers in Brazil. In 2019 top imports of Américo Brasiliense were N/A.

Yearly Exports

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Value
Depth

Top Destination (2019): Bangladesh, $23.1M

Top Product (2019): Raw Sugar, $101M

In 2019 the top export destinations of Américo Brasiliense were Bangladesh ($23.1M), Nigeria ($19.5M), Algeria ($11.9M), United States ($9.96M), and United Arab Emirates ($7.27M).

In 2019 the top exports of Américo Brasiliense were Raw Sugar ($101M), Alcohol > 80% ABV ($7.4M), Aqueous Paints ($2.21M), Nonaqueous Paints ($205k), and Excavation Machinery ($48.8k).

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Export Dynamics

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Fastest Growing Exports Destination (July 2019 - July 2020)

Rapidly Declining Export Origins (July 2019 - July 2020)

Yearly Imports

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Value
Depth

Top Origin (2019): India, $1.66M

Top Import (2019): N/A, N/A

In 2019 the top import origins of Américo Brasiliense were India ($1.66M), Spain ($660k), China ($570k), United States ($321k), and Germany ($285k).

In 2019 the top imports of Américo Brasiliense were N/A.

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Comparison in Time

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Flow
Value

This section shows differences between total trade from Américo Brasiliense throughout time.

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

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