ItuMunicipality in São Paulo State in Brazil
Exports (2019): $207M, Rnk 190/2197
Top Destination (2019): $77.7M, Argentina
Top Export (2019): $66.4M, Vehicle Parts
Imports (2019): $290M, Rnk 116/2197
Top Origin (2019): $42.4M, United States
Top Import (2019): $42M, Plastic Pipes
Exports: In 2019, Brazil's Itu exported $207M, making it the 190th largest exporter out of the 2197 exporters in Brazil. In 2019 the top exports of Itu were Vehicle Parts ($66.4M), Plastic Pipes ($46M), Hand Saws ($16.5M), Pepper ($9.63M), and Air Pumps ($7.95M).
Imports: In 2019, Brazil's Itu imported $290M, making it the 116th largest importer out of the 2197 importers in Brazil. In 2019 top imports of Itu were Plastic Pipes ($42M), Vehicle Parts ($31.5M), Fork-Lifts ($22.9M), Insulated Wire ($9.83M), and Malt ($9.21M).
Top Destination (2019): Argentina, $77.7M
Top Product (2019): Vehicle Parts, $66.4M
In 2019 the top export destinations of Itu were Argentina ($77.7M), Colombia ($20.4M), Chile ($20.2M), United States ($19M), and Paraguay ($9.88M).
In 2019 the top exports of Itu were Vehicle Parts ($66.4M), Plastic Pipes ($46M), Hand Saws ($16.5M), Pepper ($9.63M), and Air Pumps ($7.95M).
Top Origin (2019): United States, $42.4M
Top Import (2019): Plastic Pipes, $42M
In 2019 the top import origins of Itu were United States ($42.4M), China ($39.4M), Japan ($37M), Uruguay ($35.5M), and Germany ($24.9M).
In 2019 the top imports of Itu were Plastic Pipes ($42M), Vehicle Parts ($31.5M), Fork-Lifts ($22.9M), Insulated Wire ($9.83M), and Malt ($9.21M).
This section shows differences between total trade from Itu throughout time.
The municipalities of Brazil with the highest exports in 2019 were Rio De Janeiro ($11.3B), Duque De Caxias ($10.4B), Parauapebas ($7.02B), Canaã Dos Carajás ($4.93B), and São Paulo ($4.14B)
The municipalities of Brazil with the highest imports in 2019 were Manaus ($10.1B), São Paulo ($10.1B), Rio De Janeiro ($9.48B), Itajaí ($7.3B), and Macaé ($5.31B)
This section shows forecasts for total exports and imports from Itu. The forecast is based in a Long Short-Term Memory Model constructed using monthly trade data.
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