Transcript WIOD Database Construction Marcel Timmer

This project is funded by the European Commission, Research Directorate General as part
of the 7th Framework Programme, Theme 8: Socio-Economic Sciences and Humanities.
Grant Agreement no: 225 281
An Empirical Evaluation of Methods to
Estimate Use Tables with Imports Only
Bart Los
University of Groningen
(WIOD Conference, Vienna, 26-28 May 2010)
country A
product
country A
industry
Structure of national supply and use table for
country
Other countries
Supply
Intermediate use
product
industry
Intermediate use
(incl. imported
inputs)
Domestic supply
Imports
Total supply
Gross value added
Gross output
Notes:
total use = total supply
C: deliveries for household consumption
I: deliveries for investment purposes
G: deliveries for government consumption
Domestic final
use
C
I
Exports
G
Total Use
Domestic final
use
Exports Total use
Structure of inter-country supply and use table for
country A
industry
Total use
of imports
from B
Intermediate use of
imports from C
Domestic final
use of imports
from C
Reexports
-
Total use
of imports
from C
Domestic supply
Imports from B
industry
industry
Reexports
industry
-
country A
row
Total Use
Domestic final
use of imports
from B
country C
country C
G
Intermediate use of
imports from B
country B
row
I
Domestic final
Total use
Intermediate use of
Exports Exports
use of domestic
of domestic
domestic output
to B
to C
output
output
country A
country B
C
Exports to
country country
B
C
product
product
Domestic final
use
product
Intermediate use
product
Supply
Step 1: Distinction between
use of domestic inputs and
imported inputs
Step 2: Attribution of use of
imported inputs to country
of origin
Imports from C
Total supply
Gross value added
Gross output
Availability of Imports Data
Country
Australia
Austria
Belgium
Brazil
Bulgaria
Canada
China
Cyprus
Czech Rep.
Denmark
Estonia
Finland
France
FY Macedonia
Germany
Greece
Hungary
India
Indonesia
Ireland
Column SIOT Use
X
X
X
X
X
X
Benchmarks
1998, 2001, 2004
1995, 2000, 2005
1995, 2000
?
n.a.
X
X
n.a.
n.a.
2005
2001-2005
1997, 2001, 2005
1995-2005
1995, 1997,1999-2005
2005
1995, 2000-2006
2000, 2005
2000
2003
2000, 2005
1998, 2000, 2005
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Country
Italy
Japan
Latvia
Luxembourg
Malta
Mexico
Netherlands
Poland
Portugal
Romania
Russia
Slovakia
Slovenia
South Korea
Spain
Sweden
Taiwan
Turkey
UK
US
Column SIOT Use Benchmarks
X
1995, 2000, 2005
X
X
X
X
X
1996, 1998
n.a.
n.a.
n.a.
1995-2002, 2004-2006
2005
1995, 1999, 2005
2000, 2003-2006
X
X
X
X
X
X
X
X
2000,
1996,
1995,
1995,
1995,
2001,
1998,
1995
X
X
X
X
2005
2000-2001, 2005
2000, 2003, 2005
2000, 2005
2000, 2005
1996, 2004
2002
Domestic vs. Imported Use

Only the import vector from the supply table is available:
1. Assume that ratio of imported use over total use of a product is
identical across industries and final demand
2. Use information from (modified) BEC to split imports vector
and assume identical ratios across industries. Different ratios
for final demand.

A SIOT of imports is available (for the projection year or
another year):
•

‘Reverse engineer’ a use table of imports and use
product/industry-specific ratios (plus scaling)
Benchmark Use table(s) of imports is/are available:
3. Use product/industry-specific ratios for benchmark (plus
scaling)
SIOT-Construction: Beta
version
• Table for 3 countries: Germany, Japan, USA (’95) (→ 8A)
• Assumption: BEC-corrected proportions
• Sensible results, but some implausible results for
individual cells:
• Negative intermediate inputs
• Negative exports
• Underlying data material (use tables in basic prices) not
optimal yet
• Approximations of split into use of domestic products and
imported products imperfect
Testing of Methods
Four countries for which all types of data are available
(IPTS/Eurostat):
Austria, Finland, Germany and Spain
1. Estimate tables of use of imports and use of domestically
produced imports for 2000 (as if this information is not
available), using methods 1, 2, 3a/3b.
2. Compare estimated tables to “true” tables (by means of
weighted average percentage errors)
Information about performance of methods and evidence
on effects of having imperfect information.
Stability of Import Ratios
(Finland)
Product-Specific Import
Ratios 2000
1
y = 1.0973x
R² = 0.8361
0.9
0.8
Office Machinery
0.7
0.6
Tobacco Products
0.5
0.4
0.3
0.2
Computer and Related Services
0.1
Services Auxiliary to Financial Intermediation
0
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
Product-Specific Import Ratios 1995
0.8
0.9
1
Stability of Import Ratios
(Germany)
Product Specific Import
Ratios 2005
1
y = 1.0244x
R² = 0.9778
0.9
0.8
0.7
0.6
Coal and Lignite
0.5
0.4
0.3
0.2
0.1
0
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
Product Specific Import Ratios 2000
0.8
0.9
1
WAPE (all intermediate inputs)
Row-unif BEC-corr Cell-spec(1) Cell-spec(2)
Austria
Finland
Germany
Spain
3.65
3.66
1.04
2.60
12.92
12.53
1.46
1.01
0.42
0.40
0.42
0.16
1.80
0.97
1.80
0.94
Problems and Potential
Solutions (I)
General conclusion: use as much information as possible,
gains in accuracy can be small but are rarely negative.
But:
 Important advantage of row-uniform ratios of imports to total use:
no negatives in use table for domestic use, if total use is positive
 BEC-corrected and Cell-specific ratios yield negatives (not too
many, and generally small). Example: investment office
machinery products in Finland
Systematic check across countries for such products and
check modify BEC if needed
Changes in inventories (often negative) have an impact
Problems and Potential
Solutions (II)
Minimum Cross Entropy Approach
 Cell-specific import ratios as close as possible to
benchmark year(s)
 Constraints 1: uses of imports do not exceed total use
of the industry
 Constraint 2: use of imports by industries add up to
imports in the supply table
Try to get ideas of specific methods in construction of
tables of imported use (SIOTs and Use Tables) by
individual NSIs