Pacatuba

Municipality in Ceará State in Brazil

Exports (2019): $634k, Rnk 1528/2197

Top Destination (2019): $460k, Bolivia

Top Export (2019): $147k, Knit Women's Suits

Imports (2019): $5.7M, Rnk 665/2197

Top Origin (2019): $1.87M, China

Top Import (2019): $812k, Non-Retail Synthetic Filament Yarn

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

Exports: In 2019, Brazil's Pacatuba exported $634k, making it the 1528th largest exporter out of the 2197 exporters in Brazil. In 2019 the top exports of Pacatuba were Knit Women's Suits ($147k), Knit Men's Suits ($89.7k), Knit T-shirts ($86.3k), Knit Women's Shirts ($85.8k), and Non-Knit Women's Suits ($54.6k).

Imports: In 2019, Brazil's Pacatuba imported $5.7M, making it the 665th largest importer out of the 2197 importers in Brazil. In 2019 top imports of Pacatuba were Non-Retail Synthetic Filament Yarn ($812k), Malt ($734k), Non-Knit Men's Suits ($676k), Rubber Thread ($653k), and Cellulose ($385k).

Yearly Exports

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Top Destination (2019): Bolivia, $460k

Top Product (2019): Knit Women's Suits, $147k

In 2019 the top export destinations of Pacatuba were Bolivia ($460k), Paraguay ($162k), and United States ($11.5k).

In 2019 the top exports of Pacatuba were Knit Women's Suits ($147k), Knit Men's Suits ($89.7k), Knit T-shirts ($86.3k), Knit Women's Shirts ($85.8k), and Non-Knit Women's Suits ($54.6k).

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Yearly Imports

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Top Origin (2019): China, $1.87M

Top Import (2019): Non-Retail Synthetic Filament Yarn, $812k

In 2019 the top import origins of Pacatuba were China ($1.87M), Bangladesh ($1.2M), Thailand ($653k), India ($437k), and Russia ($371k).

In 2019 the top imports of Pacatuba were Non-Retail Synthetic Filament Yarn ($812k), Malt ($734k), Non-Knit Men's Suits ($676k), Rubber Thread ($653k), and Cellulose ($385k).

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Comparison in Time

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

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

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