A multisector, bilateral, A multisector, bilateral, worldwide Services worldwide Services DatabaseDatabase

Houssein Boumellassa, CEPII Deniz Unal-Kesenci, CEPII

September 2008 – OECD

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Main MotivationsMain Motivations

Services account for 70% of Developed Countries’ GDP.

Due to technical progress, services sectors have become more tradable.

WTO negotiations: GATS (modes 1-4). Where do we stand ?

Analytical work is now needed.

Methodology : A sequential Methodology : A sequential databasedatabase Gathering all available sources and organize between

themselves. [STEP 1]

Harmonizing mirror values: Which methodology ? [STEP 2]

Filling in the missing values: Econometric work that gives first estimate flows. [STEP 3]

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]

Expected output (End of 2008): 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 Available databases: “State of the Art”of the Art” IMFIMF – World coverage – 1995-20061

Balance of payment Flows by reporter countries and sectors: 165 countries Unit: millions of USD - Imf nomenclature

EUROSTATEUROSTAT – EU relations coverage – 1995-20061

Flows by reporter, partner & sectors. Number of reporters: 42 (numerous aggregates) Number of partners: 122 (numerous aggregates) Unit: millions of euro - Imf nomenclature

OECDOECD – OECD countries coverage – 1999-2006 Flows by reporter, partner, sector Number of reporters: 33 Number of partners: 269 (numerous aggregates) Unit: millions of USD – Imf nomenclature

National sourcesNational sources: Balance of payments (France…)

1: Previous years available

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Problems between databasesProblems between databases

Time constraint (1999-2007) OECD database constraint Scarcity of the data before for other databases

Classification All databases use the IMF nomenclature (BOP 5). 11 sectors: 205 (transports), 245 (Travel), Other services (9 items).

Inconsistencies in values Differences between countries Declaration topics (USA, OECD)

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Problems inside databases: Problems inside databases: World IMFWorld IMF

Position Year Topic (200) Topic (detail) Relative gapCredit 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 databasesProblems inside databases Classification

Some sectors remain “original” (“205291” for Canada (oecd), 9XX posts). Case of the transportation sector (flags of

convenience). Negative and zero values

Negative values Oecd: 0.88% Imf: 0% Eurostat: 10.6%

Zero Oecd: 36 % Imf: 0.6% Eurostat: 36%

Mirror flows The same flow corresponds to two different values. Assumption: the “real” flow is somewhere between (or equal) the two values (to one

value). Eurostat: 12 % OECD: - IMF: -

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MethodolgyMethodolgy 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 Harmonization of mirror valuesvalues

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).

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”).

The second step is to translate the quality ranking of country’s declarations into weights.

Other ideas: Evaluate reporters’ quality relatively to the best one (Lejour (based on Gehlhar, 1996), 2005).

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Estimation of missing valuesEstimation of missing values

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 databaseA balanced database

Constructed data are not necessary consistent with countries’ flows from IMF.

Solution: using methods which reconcile such heterogeneous pieces of information 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).

THANK YOU !

houssein.boumellassa@cepii.fr

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