Harmonising international trade data for inter-country input-output analysis: statistical issues

Dong GUO, Norihiko YAMANO and Colin WEBBSeptember 22nd , 2008WPGTS, Paris

Background

• Economic globalization: the significant trade in intermediate goods and services globally

• More fragmented production process across countries

• Inter-regional input-output model: tools for wide range of global analyses

Trade data and IO analysis

• Input-Output tables by OECD– Separated the domestic transaction from

the imported transaction– Harmonised for 40 countries

• Multi-Regional IO– Trade structure integrated into IO analysis– Interregional feedback effects

• Challenges– Optimal data for trade structure between

countries required (goods and services)

Sector 1Sector 1

Sector 1

Country B

Sector 2

Sector 2Sector 2

Country A

Sector 1

Sector 2

Country A

IMDFD

CPIP

IMDFD

CPIP

Sector 1Sector 1

Country C

Sector 2Sector 2

Country B

Country B

Linking trade data with IO

Country C

Country C

Sector 1Sector 1

Sector 2Sector 2

+

+

=

=

IO

Trade in goods – Data issues

• Re-exports– Trade discrepancies: Classic case = China /HK/USA

• Un-allocated trade data– Possibly concentrated in certain industries and

partners

• Trade in second-handed goods– Not linked to recent manufacturing production

• Scrap and waste products– Some identified by HS, others not (e.g. PCs)

• Trade by industry classifications– OECD IO: by industry; trade statistics: by products

China-US: trade discrepancies(official statistics, billion USD)

Year

US exports

to China (US

data)

Chinese imports from the

US (Chinese data)

US imports

from China (US

data)

Chinese exports to the

US (Chinese Data)

US- China trade

balance (US data)

US-China trade

balance

(Chinese

data)

1995 11.7 16.1 45.6 24.7 -33.8 -8.6

2002 22.1 27.2 125.2 70.0 -103.1 -42.8

Source: Fung and Lau (2003) Table1

Unallocated trade(% total trade)

Exports Imports

1990 1995 2000 1990 1995 2000

Australia 14.4 15.9 19.1 3.6 2.3 2.1

Germany 1.6 3.6 2.3 2.1 5.5 5.2

Ireland 4.4 6.9 4.3 2.9 9.2 5.8

Norway 5.6 7.3 4.4 0.8 0.9 1.0

USA 3.9 3.3 3.5 3.5 3.4 4.4

Russia - - 12.3 - - 13.2

South Africa - - 24.7 - - 8.8

Trade in services / BOP

• Improvement in recent years with available data allows improved MRIO modelling

• Conceptual differences between EBOPS and Industry classification

• Particular issues– Goods sent abroad for processing– Merchanting

Differences in published trade statistics

• Merchandise trade statistics– ITCS v. COMTRADE: notably pre-2000

data; subtle differences after ‘synchronization’.

• Service trade statistics– Between OECD TIS and UNSITS

• Exports of manufactured goods– Between OECD BTD and I-O datasets

ITCS data as % of COMTRADE data, Germany, 2006

Exports Imports

Total 100.0 100.0Commodities not specified according to kind 66.2 86.863: Other textile articles; clothing etc 102.2 100.073: Articles of iron or steel. 101.4 100.082: Tools and implements of base metal 103.1 100.984: Machinery and mechanical appliances and parts; boilers etc. 101.5 100.185: Electrical machinery and equipment and parts thereof 100.8 100.087: Vehicles other than railway or tramway rolling-stock; parts 104.7 105.288: Aircraft, spacecraft, and parts thereof. 105.7 106.0Sum of all other 2-digit HS commodities 100.0 100.0

Possible solutions• short-term

– Re-exports: more information from countries, particularly for key I-O years (1995, 2000).

– Un-allocated trade: more information on composition.

• longer-term– Systematic reporting of re-exports– New products codes to identify scrap, waste,

recycled goods etc.– Reporting of BOP trade in goods by product

groups

Summary

• More to international trade statistics than meets the eye

• Attempt at guide for researchers with limited experience of using trade statistics

• Highlights issues to be considered when using trade statistics – particularly for I-O related analyses

Thank you !