Atilio VivacquaMunicipality in Espírito Santo State in Brazil
Exports (2019): $22.6M, Rnk 710/2197
Top Destination (2019): $15.6M, United States
Top Export (2019): $21M, Building Stone
Imports (2019): $2.84M, Rnk 811/2197
Top Origin (2019): $1.53M, Italy
Top Import (2019): $2.05M, Milling Stones
Overview: This page contains the latest international trade data for Atilio Vivacqua, including export and import data.
Exports: In 2019, Brazil's Atilio Vivacqua exported $22.6M, making it the 710th largest exporter out of the 2197 exporters in Brazil. In 2019 the top exports of Atilio Vivacqua were Building Stone ($21M), Granite ($644k), Marble, Travertine and Alabaster ($578k), Quartz ($364k), and Precious Stones ($10.4k).
Imports: In 2019, Brazil's Atilio Vivacqua imported $2.84M, making it the 811th largest importer out of the 2197 importers in Brazil. In 2019 top imports of Atilio Vivacqua were Milling Stones ($2.05M), Polyacetals ($474k), Prepr binder for foundry ($229k), Glass Fibers ($72.2k), and Metalworking Machine Parts ($9.45k).
Top Destination (2019): United States, $15.6M
Top Product (2019): Building Stone, $21M
In 2019 the top export destinations of Atilio Vivacqua were United States ($15.6M), China ($1.58M), Canada ($698k), Russia ($540k), and Mexico ($496k).
In 2019 the top exports of Atilio Vivacqua were Building Stone ($21M), Granite ($644k), Marble, Travertine and Alabaster ($578k), Quartz ($364k), and Precious Stones ($10.4k).
Top Origin (2019): Italy, $1.53M
Top Import (2019): Milling Stones, $2.05M
In 2019 the top import origins of Atilio Vivacqua were Italy ($1.53M), China ($807k), Portugal ($383k), South Korea ($116k), and Canada ($5.19k).
In 2019 the top imports of Atilio Vivacqua were Milling Stones ($2.05M), Polyacetals ($474k), Prepr binder for foundry ($229k), Glass Fibers ($72.2k), and Metalworking Machine Parts ($9.45k).
This section shows differences between total trade from Atilio Vivacqua throughout time.
This section shows forecasts for total exports and imports from Atilio Vivacqua. The forecast is based in a Long Short-Term Memory Model constructed using monthly trade data.
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