A multisector, bilateral, worldwide Services Database Houssein Boumellassa, CEPII Deniz Unal-Kesenci, CEPII September 2008 – OECD

2 Main 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 database 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. 3

4 Available databases: “State of the Art” IMF IMF – World coverage –  Balance of payment  Flows by reporter countries and sectors: 165 countries  Unit: millions of USD - Imf nomenclature EUROSTAT EUROSTAT – EU relations coverage –  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 – OECD countries coverage –  Flows by reporter, partner, sector  Number of reporters: 33  Number of partners: 269 (numerous aggregates)  Unit: millions of USD – Imf nomenclature National sources National sources: Balance of payments (France…) 1 : Previous years available

5 Problems between databases Time constraint ( )  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)

6 Problems inside databases: World IMF PositionYearTopic (200)Topic (detail)Relative gap Credit % Debit % Credit % Debit % Credit % Debit % Credit % Debit % Credit % Debit % Credit % Debit % Credit % Debit % Credit % Debit % Credit % Debit % In millions of current USD

7 Problems 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: -

8 Methodolgy 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.

9 Harmonization of mirror values 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).

10 Estimation 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:

11 A 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).

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