Transcript Harmonising international trade data for intercountry input-output analysis: statistical issues Dong GUO, Norihiko YAMANO and Colin WEBB September 22nd , 2008 WPGTS, Paris.

Harmonising international
trade data for intercountry input-output
analysis: statistical issues
Dong GUO, Norihiko YAMANO and
Colin WEBB
September 22nd , 2008
WPGTS, 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)
Linking trade data with IO
Country B
Country A
Sector 1
IMD
FD
Sector 2
Sector 1
Sector 2
CP
IP
Country C
Sector 1
Sector 2
IMD
FD
CP
IP
Country A
Sector 1
Sector 2
IO
Sector 1
=
Country B
+
Country C
Sector 2
=
Country B
+
Country C
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)
USChina
trade
balanc
e
(Chine
se
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
Total
Commodities not specified according to kind
63: Other textile articles; clothing etc
73: Articles of iron or steel.
82: Tools and implements of base metal
84: Machinery and mechanical appliances
and parts; boilers etc.
85: Electrical machinery and equipment and
parts thereof
87: Vehicles other than railway or tramway
rolling-stock; parts
88: Aircraft, spacecraft, and parts thereof.
Sum of all other 2-digit HS commodities
Imports
100.0
66.2
102.2
101.4
103.1
100.0
86.8
100.0
100.0
100.9
101.5
100.1
100.8
100.0
104.7
105.7
100.0
105.2
106.0
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 !