Inner Mongolia Autonomous Region

Province in China

Exports (2019): $4.99B, Rnk 23/31

Top Destination (2019): $394M, Mongolia

Top Export (2019): $361M, Sunflower seeds

Imports (2019): $9.32B, Rnk 23/31

Top Origin (2019): $4.25B, Mongolia

Top Import (2019): $2.66B, Bituminous coal, not agglomerated

Economic Complexity (2019): -0.046, Rnk 24 / 31

Exports: In 2019, China's Inner Mongolia Autonomous Region exported $4.99B, making it the 23rd largest exporter out of the 31 exporters in China. In 2019 the top exports of Inner Mongolia Autonomous Region were Sunflower seeds ($361M), Flat rolled iron or non-alloy steel,... ($343M), Glutamic acid, salts ($333M), Amino-alcohol-phenols etc with oxygen function ($246M), and Hot rolled alloy-steel, not in coil... ($204M).

Imports: In 2019, China's Inner Mongolia Autonomous Region imported $9.32B, making it the 23rd largest importer out of the 31 importers in China. In 2019 top imports of Inner Mongolia Autonomous Region were Bituminous coal, not agglomerated ($2.66B), Iron ore, concentrate, not iron pyrites,unagglomerate ($1.17B), Copper ores and concentrates ($1.17B), Wood; coniferous species, of pine (Pinus... ($795M), and Petroleum oils, oils from bituminous minerals,... ($340M).

Economic Complexity: In 2019, the highest complexity exports of Inner Mongolia Autonomous Region according to the product complexity index (PCI) are Disc Chemicals for Electronics (2.16), Silicone (1.77), Carboxyimide Compounds (1.59), Flat Flat-Rolled Steel (1.57), and Papermaking Machines (1.53). PCI measures the knowledge intensity of a product by considering the knowledge intensity of its exporters.

Value
Depth

Top Destination (2019): Mongolia, $394M

Top Product (2019): Sunflower seeds, $361M

In 2019 the top export destinations of Inner Mongolia Autonomous Region were Mongolia ($394M), Vietnam ($371M), Russia ($361M), United States ($343M), and South Korea ($332M).

In 2019 the top exports of Inner Mongolia Autonomous Region were Sunflower seeds ($361M), Flat rolled iron or non-alloy steel,... ($343M), Glutamic acid, salts ($333M), Amino-alcohol-phenols etc with oxygen function ($246M), and Hot rolled alloy-steel, not in coil... ($204M).

Export Dynamics

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Fastest Growing Exports Destination (April 2019 - April 2020)

Rapidly Declining Export Origins (April 2019 - April 2020)

Value
Depth

Top Origin (2019): Mongolia, $4.25B

Top Import (2019): Bituminous coal, not agglomerated, $2.66B

In 2019 the top import origins of Inner Mongolia Autonomous Region were Mongolia ($4.25B), Russia ($1.98B), Australia ($1.16B), United States ($244M), and New Zealand ($182M).

In 2019 the top imports of Inner Mongolia Autonomous Region were Bituminous coal, not agglomerated ($2.66B), Iron ore, concentrate, not iron pyrites,unagglomerate ($1.17B), Copper ores and concentrates ($1.17B), Wood; coniferous species, of pine (Pinus... ($795M), and Petroleum oils, oils from bituminous minerals,... ($340M).

Import Dynamics

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Fastest Growing Import Origins (April 2019 - April 2020)

Rapidly Declining Import Origins (April 2019 - April 2020)

Comparison in Time

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Flow
Value

This section shows differences between total trade from Inner Mongolia Autonomous Region throughout time.

Comparison Map

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Value

The territories of China with the highest exports in 2019 were Guangdong Province ($444B), Jiangsu Province ($347B), Zhejiang Province ($314B), Shanghai Province ($176B), and Shandong Province ($153B)

The territories of China with the highest imports in 2019 were Guangdong Province ($373B), Beijing ($293B), Shanghai Province ($288B), Jiangsu Province ($223B), and Shandong Province ($133B)

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

Explore Forecasts

Economic Complexity

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Economic Complexity of China

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Inner Mongolia Autonomous Region ranks 24th out of the 31 territories in China according to ECI.

Estimated using exports data.

Export Opportunities by Relatedness

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The top export opportunities according to the relatedness level, without considering those products were Inner Mongolia Autonomous Region already has a comparative advantage, are led by Portable Lighting (0.19), Umbrellas (0.18), Combs (0.18), Woven Fabric of Synthetic Staple Fibers (0.18), and Woven Fabrics (0.18).

Most Complex Products by PCI

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The highest complexity exports of Inner Mongolia Autonomous Region according to the product complexity index (PCI) are Disc Chemicals for Electronics (2.16), Silicone (1.77), Carboxyimide Compounds (1.59), Flat Flat-Rolled Steel (1.57), and Papermaking Machines (1.53). PCI measures the knowledge intensity of a product by considering the knowledge intensity of its exporters.

Most Specialized Products by RCA Index

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The most specialized products according to the RCA index are led by Non-Retail Animal Hair Yarn (435), Sunflower Seeds (322), Alkaline Metals (287), Locust beans, seaweed, sugar beet, cane,... (196), and Natural Polymers (146).

The product space is a network connecting products that are likely to be co-exported. The product space can be used to predict future exports, since Inner Mongolia Autonomous Region is more likely to start exporting products that are related to current exports. Relatedness measures the distance between a product, and all of the products it is currently specialized in.

Relatedness Space

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This network shows the products most related to the production structure of  Inner Mongolia Autonomous Region. These are products that tend to be co-exported with the products that Inner Mongolia Autonomous Region exports. Higher relatedness values ​​indicate greater knowledge, which predicts a greater probability of exporting that product in the future.

Diversification Frontier

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Depth

The Complexity-Relatedness diagram compares the risk and the strategic value of a territory's potential export oppotunities. Relatedness is a predictive of the probability that a country increases its exports in a product. Complexity, is associated with higher levels of income, economic growth, less income inequality, and lower emissions.