IbitingaMunicipality in São Paulo State in Brazil
Exports (2019): $440k, Rnk 1602/2197
Top Destination (2019): $276k, Argentina
Top Export (2019): $251k, Other Plastic Products
Imports (2019): $2.87M, Rnk 809/2197
Top Origin (2019): $1.77M, China
Top Import (2019): $513k, Synthetic Filament Yarn Woven Fabric
Overview: This page contains the latest international trade data for Ibitinga, including export and import data.
Exports: In 2019, Brazil's Ibitinga exported $440k, making it the 1602nd largest exporter out of the 2197 exporters in Brazil. In 2019 the top exports of Ibitinga were Other Plastic Products ($251k), Other Inedible Animal Products ($76.2k), Plastic Lids ($27.1k), Bedspreads ($26.6k), and House Linens ($16.9k).
Imports: In 2019, Brazil's Ibitinga imported $2.87M, making it the 809th largest importer out of the 2197 importers in Brazil. In 2019 top imports of Ibitinga were Synthetic Filament Yarn Woven Fabric ($513k), Unprocessed Synthetic Staple Fibers ($436k), Plastic Coated Textile Fabric ($427k), Sewing Machines ($423k), and Pile Fabric ($242k).
Top Destination (2019): Argentina, $276k
Top Product (2019): Other Plastic Products, $251k
In 2019 the top export destinations of Ibitinga were Argentina ($276k), United Arab Emirates ($99.7k), Angola ($44.2k), Uruguay ($8.82k), and Canada ($4.67k).
In 2019 the top exports of Ibitinga were Other Plastic Products ($251k), Other Inedible Animal Products ($76.2k), Plastic Lids ($27.1k), Bedspreads ($26.6k), and House Linens ($16.9k).
Top Origin (2019): China, $1.77M
Top Import (2019): Synthetic Filament Yarn Woven Fabric, $513k
In 2019 the top import origins of Ibitinga were China ($1.77M), Canada ($356k), South Korea ($238k), Hong Kong ($122k), and Belgium ($87.7k).
In 2019 the top imports of Ibitinga were Synthetic Filament Yarn Woven Fabric ($513k), Unprocessed Synthetic Staple Fibers ($436k), Plastic Coated Textile Fabric ($427k), Sewing Machines ($423k), and Pile Fabric ($242k).
This section shows forecasts for total exports and imports from Ibitinga. The forecast is based in a Long Short-Term Memory Model constructed using monthly trade data.
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