1 Data mining of the UN Comtrade database in cooperation with Customs Ronald Jansen Chief of the Trade Statistics Branch United Nations Statistics Division.

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Data mining of the UN Comtrade database in cooperation with Customs

Ronald JansenChief of the Trade Statistics BranchUnited Nations Statistics Division / DESAE-mail: [email protected] [email protected]

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Matching Imports and Exports Data

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Reason for bilateral trade asymmetrieso Country of Origin /Country of

Destination Adding Country of consignment

o Valuation CIF /FOB Imports and Exports FOB

o Trade System General Trade System for all

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Country of Origin / Destination

China (A)

Hong Kong (B)

Netherlands (C)

Germany (D)D records Imports of A (country of origin)

C records Imports of A

B records Imports of A Re-exports to C

Re-exports to D

A records exports to B

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Country of Consignment

China (A)

Hong Kong (B)

Netherlands (C)

Germany (D)D records Imports of C

C records Imports of B

B records Imports of A Re-exports to C

Re-exports to D

A records exports to B

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Imports CIF / FOB

Three Methods to obtain Imports FOB:1. Recording of Cost, Insurance

and Freight per transaction2. Recording of Cost, Insurance

and Freight per Shipment (and partition)

3. Sample Freight and Insurance by HS, Partner country and Mode of Transport and use to adjust CIF to FOB

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Trade System A 2006 global survey showed

that 50% of countries use General Trade system and 50% Special Trade system

Difference in coverage (free zones, customs warehousing, processing zones) will lead to discrepancies in recording

All countries encouraged to record all elements of General Trade system (even in addition to Special)

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Harmonization Process (M=X)

1. Reconciliation exercises – finding common ground

2. Reconciling large trade (Chatham House)

3. Use of imports (origin) as breakdown for partner exports

4. Estimation methods (USITC)5. Customs interest in solving

discrepancies

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SAS Visual Analytics for

UN Comtrade

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UN Comtradein the Sandbox

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Comtrade in the Sandbox

UNECE Big Data Project – Results by November 2015

Available data – 2000-2014 annual HS and Tariff line data

IT specialists – ISTAT, Statistics Netherlands, UNSD, OECD

Proposals – Regional Value Chain analysis, Trade asymmetries, Unit-value indices calculations, Trade flow estimations (missing data and forecasting)

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Regional Value Chain analysis Replicating – Network Analysis of World Trade

(De Benedictis et al., 2013)a) Global and local centrality measuresb) Sectoral Trade Networks

• Commodities? (Bananas; Olive Oil [Casieri et al.])• Industries? (DeBacker & Miroudot; Sturgeon &

Memedovic)c) Restricting to Intermediate Goods traded) Focusing on Geo-graphical groups

Building on “Mapping Global Value Chains”a) Intra- versus Extra-group trade in intermediate goods

Building on OECD work on “Regional economic integration” - Yamano et al; DeBacker and Miroudot; a) International I-O approach

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Trade Networks Commodities

o Bananas, Cement, Movies, Oil, Footwear, Engines (De Benedictis)

o Olive Oil (Casieri) Industries

o Agriculture and Food, Chemical products, Motor vehicles, electronics, business services, financial services (DeBacker & Miroudot)

o Electronics, Passenger vehicles, Apparel (Sturgeon & Memedovic)

o CGGC Duke: Electronics, Aerospace, Medical Devices, Horticulture, Wheat, Fruit and vegetables,

Project added-value Industry Mapping

o GVC Mappingo ISIC sectors (TiVA)o Other?

BEC and intermediate goodso BEC Revision 5 – Split of Economic

Categories and End-use; Goods and Services; differentiating within Intermediate goods – generic and specific intermediates

Estimating missing trade flows Analyzing bilateral trade asymmetries

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Thank you

Ronald JansenChief of the Trade Statistics BranchUnited Nations Statistics Division / DESAE-mail: [email protected] [email protected]