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Harmonising international trade data for inter-country input-output analysis: statistical issues

Harmonising international trade data for inter-country input-output analysis: statistical issues . Dong GUO, Norihiko YAMANO and Colin WEBB September 22 nd , 2008 WPGTS, Paris. Background. Economic globalization: the significant trade in intermediate goods and services globally

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Harmonising international trade data for inter-country input-output analysis: statistical issues

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  1. Harmonising international trade data for inter-country input-output analysis: statistical issues Dong GUO, Norihiko YAMANO and Colin WEBB September 22nd , 2008 WPGTS, Paris

  2. Background • Economic globalization: the significant trade in intermediate goods and services globally • More fragmented production process across countries • Inter-regional input-output model: tools for wide range of global analyses

  3. Trade data and IO analysis • Input-Output tables by OECD • Separated the domestic transaction from the imported transaction • Harmonised for 40 countries • Multi-Regional IO • Trade structure integrated into IO analysis • Interregional feedback effects • Challenges • Optimal data for trade structure between countries required (goods and services)

  4. Linking trade data with IO Country B Country A Sector 1 Sector 2 Sector 1 IMD FD CP Country C IP Sector 1 Sector 2 IMD FD CP Sector 2 IP Country A IO + = Country B Country C Sector 1 Sector 1 = + Sector 2 Country B Country C Sector 2

  5. Trade in goods – Data issues • Re-exports • Trade discrepancies: Classic case = China /HK/USA • Un-allocated trade data • Possibly concentrated in certain industries and partners • Trade in second-handed goods • Not linked to recent manufacturing production • Scrap and waste products • SomeidentifiedbyHS, others not (e.g. PCs) • Trade by industry classifications • OECD IO: by industry; trade statistics: by products

  6. China-US: trade discrepancies(official statistics, billion USD) Source: Fung and Lau (2003) Table1

  7. Unallocated trade(% total trade)

  8. Trade in services / BOP • Improvement in recent years with available data allows improved MRIO modelling • Conceptual differences between EBOPS and Industry classification • Particular issues • Goods sent abroad for processing • Merchanting

  9. Differences in published trade statistics • Merchandise trade statistics • ITCS v. COMTRADE: notably pre-2000 data; subtle differences after ‘synchronization’. • Service trade statistics • Between OECD TIS and UNSITS • Exports of manufactured goods • Between OECD BTD and I-O datasets

  10. ITCS data as % of COMTRADE data, Germany, 2006

  11. Possible solutions • short-term • Re-exports: more information from countries, particularly for key I-O years (1995, 2000). • Un-allocated trade: more information on composition. • longer-term • Systematic reporting of re-exports • New products codes to identify scrap, waste, recycled goods etc. • Reporting of BOP trade in goods by product groups

  12. Summary • More to international trade statistics than meets the eye • Attempt at guide for researchers with limited experience of using trade statistics • Highlights issues to be considered when using trade statistics – particularly for I-O related analyses

  13. Thank you !

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