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WIOD Data on Trade in Goods: Data Issues and Patterns of Trade in Intermediates

Joe Francois, Olga Pindyuk , Johannes Pöschl , Robert Stehrer WIOD Conference , 26. May 2010. WIOD Data on Trade in Goods: Data Issues and Patterns of Trade in Intermediates. Data progress. Starting point: trade data for 39 WIOD countries at HS 6-digit level

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WIOD Data on Trade in Goods: Data Issues and Patterns of Trade in Intermediates

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  1. Joe Francois, Olga Pindyuk, Johannes Pöschl, Robert Stehrer WIOD Conference , 26. May 2010 WIOD Data on Trade in Goods:Data Issues and Patterns of Trade in Intermediates

  2. Data progress Starting point:trade data for 39 WIOD countries at HS 6-digit level Processing data – correspondences: effort to adapt HS6-BEC correspondence HS6 data matched with... NACE 3-digit industry correspondence use categories WIOD codes problems with correspondences and product code orphans have been solved

  3. Data reporting issue Some issues of coverage exist (CZK, DNK – 1997) but we are in contact with the UN and the data will be available soon Missing trade compare sum of HS 6-digit codes to total value reported 2007: 14%

  4. Missing trade1/2 Not a minor problem: examples RUS, CAN, CHN >40% of total export/imports for several years not constant over time! Sum over all HS6 codes in percent of total trade reported

  5. Missing trade2/2 Phenomenon not related to certain reporters but an issue for a lot of countries with missing imports > 15%(AUS, DEU, IND, JPN, KOR, MEX, NLD, …) Problem exists at HS 6-digit level as well as theSITC 5-digit level (for which it is mostly worse)

  6. How to find and adjust for missing trade? Proportional adjustment over all products not applicable since missing trade is most certainly related to specific products If a reporting country does not want the partner breakdown to be disclosed it can report trade with a confidential partner “Special Categories“ Countries report both at the HS 6 and 2-digit level data reporting should be better at the aggregated HS 2-digit level (less confidentiality issues)

  7. Two step approach 1. Step: Use trade with confidential partner “Special Categories“ for each country at HS 6-digit level Add it to the trade with partner countries according to the difference between the sum of trade at the HS6 level and total trade reported RUS AUT DEU Spec.Cat. • 2. Step: • Use HS 2-digit data to adjust HS 6-digit reported trade flows

  8. Open Issues Transport costs included in imports lead to relatively higher share of countries further away estimation gravity equations to reduce distortion in the trade data Re-Imports and Re-Exports (especially China‘s special administrative regions) Data availability Taiwan Comext Data for EU15 available (EU27 since 1999), OECD Gravity Equations Further comments / suggestions?

  9. Classification by end use categories Data at HS6 level Correspondence to WIOD-BEC Correspondence to NACE 3-digit (CPA?) What is WIOD BEC HS6-BEC (UN) correspondence reclassified at HS6 level Split into four categories: INTC, CONS, GFCF and MIX Should meet purpose of bringing together trade data and SUTs Aggregation to products and end-use by country

  10. ‘Stylized’ facts Patterns of trade by end-use category Imports and exports Trends Specialisation structures Two-way trade in intermediates

  11. Structure of imports by end use category, 2006

  12. Structure of exports by end use category, 2006

  13. Correlation of export and import sharesfor intermediates trade, 2006

  14. Revealed specialisation in intermediates trade, 2006

  15. Changes in the shares of intermediates trade

  16. Changes in the share of intermediates trade, in percentage point differences, 1996-2006 • Changes driven by between or within shifts? • Cross-country differences driven by within or between • industry specialisation?

  17. Share of intermediate imports by industry, 2006

  18. Share of intermediate exports by industry, 2006

  19. Structure by industry Shares are highly correlated across countries in general However, significant differences when looking at individual industries Rather persistent over time Though less so for some industries

  20. Share of two-way trade in intermediates

  21. Share of two-way trade in intermediates, 2006

  22. Share of two-way trade in intermediatesby industry, 2006 Note: Mean over countries

  23. Comparisons to SIOT data Eurostat symmetric IO tables with import tables Note: pxp tables Shares of imported intermediates in total imports Comparison to trade data Strong positive correlation Hides significant differences in some cases

  24. Comparisons to SIOT data NACE 34 - Motor vehicles, trailers and semi-trailers 2000 2005

  25. Comparisons to SIOT data NACE 35 - Other transport equipment 2000 2005 Note: Mixed category not yet considered

  26. Comparisons to SIOT data Differences More industry specific than country specific Not always consistent over time

  27. Summary Data issues and next steps (Re-)classification of end-use categories Stylized facts on trade in intermediates Intermediates: Broad category More distinct patterns for more detailed product groups (e.g. parts and components) and industry level Consistency with information from import tables Country/industry specific deviations are hard to assess Compare with import use tables (however hardly accessible)

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