A multisector, bilateral,
worldwide Services Database
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
Houssein Boumellassa, CEPII
Deniz Unal-Kesenci, CEPII
September 2008 – OECD
Main Motivations
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Services account for 70% of Developed Countries’ GDP.
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Due to technical progress, services sectors have become
more tradable.
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WTO negotiations: GATS (modes 1-4). Where do we stand
?
Analytical work is now needed.
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Methodology : A sequential database
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Gathering all available sources and organize between themselves. [STEP 1]
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Harmonizing mirror values: Which methodology ? [STEP 2]
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Filling in the missing values: Econometric work that gives first estimate flows.
[STEP 3]
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Methods to reconcile parts of information from heterogeneous sources and to
balance the database (how to allocate the marging of the aggregated flows ?).
[STEP 4]
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Expected output (End of 2008):
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2 datasets [STEP 2 and STEP 4]
80 countries, 11 sectors (and aggregates), flows by year.
Mode 1 and Mode 2.
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Available databases: “State of the Art”
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IMF – World coverage – 1995-20061
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EUROSTAT – EU relations coverage – 1995-20061
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Flows by reporter, partner & sectors.
Number of reporters: 42 (numerous aggregates)
Number of partners: 122 (numerous aggregates)
Unit: millions of euro - Imf nomenclature
OECD – OECD countries coverage – 1999-2006
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Balance of payment
Flows by reporter countries and sectors: 165 countries
Unit: millions of USD - Imf nomenclature
Flows by reporter, partner, sector
Number of reporters: 33
Number of partners: 269 (numerous aggregates)
Unit: millions of USD – Imf nomenclature
National sources: Balance of payments (France…)
1:
Previous years available
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Problems between databases
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Time constraint (1999-2007)
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Classification
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OECD database constraint
Scarcity of the data before for other databases
All databases use the IMF nomenclature (BOP 5).
11 sectors: 205 (transports), 245 (Travel), Other services (9 items).
Inconsistencies in values
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Differences between countries
Declaration topics (USA, OECD)
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Problems inside databases: World IMF
Position
Year
Topic (200)
Topic (detail)
Relative gap
Credit
1999
1 687 047.50
1 425 502.77
15.50%
Debit
1999
-1 685 765.43
-1 404 310.00
16.70%
Credit
2000
1 770 303.18
1 508 757.35
14.77%
Debit
2000
-1 776 402.22
-1 494 725.70
15.86%
Credit
2001
1 798 184.84
1 508 254.80
16.12%
Debit
2001
-1 803 967.21
-1 510 035.07
16.29%
Credit
2002
1 929 722.95
1 610 287.65
16.55%
Debit
2002
-1 896 172.86
-1 592 593.36
16.01%
Credit
2003
2 236 809.51
1 855 022.11
17.07%
Debit
2003
-2 172 654.37
-1 815 333.96
16.45%
Credit
2004
2 689 983.13
2 233 433.73
16.97%
Debit
2004
-2 572 914.53
-2 147 880.85
16.52%
Credit
2005
2 991 539.24
2 444 177.25
18.30%
Debit
2005
-2 834 298.18
-2 327 299.39
17.89%
Credit
2006
3 289 122.62
2 690 795.34
18.19%
Debit
2006
-3 083 181.78
-2 539 677.10
17.63%
Credit
2007
2 907 258.67
2 083 387.14
28.34%
Debit
2007
-2 587 703.19
-1 876 406.97
27.49%
In millions of current USD
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Problems inside databases
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Classification
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Some sectors remain “original” (“205291” for Canada (oecd), 9XX posts).
Case of the transportation sector (flags of convenience).
Negative and zero values
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Negative values
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0.88%
0%
10.6%
Zero
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Oecd:
Imf:
Eurostat:
Oecd:
Imf:
Eurostat:
36 %
0.6%
36%
Mirror flows
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The same flow corresponds to two different values.
Assumption: the “real” flow is somewhere between (or equal) the two values (to one value).
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Eurostat: 12 %
OECD: IMF: -
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Methodolgy
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Eurostat as main source for raw data
Filling the missing data with OECD when available
Harmonizing mirror flows
Controlling the total flow by country with IMF
Computing missing data with gravity regressions and allocating
the difference between total and its components
Balancing the database
Each step will be fully documented and the origin (raw data,
harmonized flow, constructed data) of each cell can be
distinguished (numerous flag), leading to different level of use.
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Harmonization of mirror values
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The procedure of harmonization consists in computing weighted averages of mirror flows on the basis of an estimated quality
indicator of import and export declarations for each country. Our methodology relies on Gaulier & Zignago (2005).
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The first step in the harmonization process consists in determining a ranking for the qualities of the country declarations. This
evaluation is obtained using a (weighted) variance analysis via a decomposition of the absolute value of the mirror flows
ratios (DDktij , for the term “Declaration Distances”).
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The second step is to translate the quality ranking of country’s declarations into weights.
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Other ideas: Evaluate reporters’ quality relatively to the best one (Lejour (based on Gehlhar, 1996), 2005).
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Estimation of missing values
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Filling the gaps when no data are available (Xij=Mji= (.,0)).
Idea: constructed data rely on estimates coming from gravity regression
(Francois (2001), Park (2002), (Grunfeld and Moxnes (2003), Kimura and
Lee (2004), Lejour and de Paiva Verheijden (2004), Lennon (2006), Walsh
(2006))
Type of equation:
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A balanced database
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Constructed data are not necessary consistent with countries’
flows from IMF.
Solution: using methods which reconcile such heterogeneous
pieces of information
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RAS (Iterative methods)
Entropy (optimisation methods)1.
1:
This approach can also endogenously determine mirror values (choosing the estimated bilateral flow will be the value
that distorts the matrix the least).
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THANK YOU !
houssein.boumellassa@cepii.fr
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