Organisation for Economic Co-operation and Development

ICT goods are those that are either intended to fulfil the function of information processing and communication by electronic means, including transmission and display, OR which use electronic processing to detect, measure and/or record physical phenomena, or to control a physical process. ICT goods are defined by the OECD in terms of the Harmonised System. The guiding principle for the delineation of ICT goods is that such goods must either be intended to fulfil the function of information processing and communication by electronic means, including transmission and display, OR use electronic processing to detect, measure and/or record physical phenomena, or to control a physical process.Another guiding principle was to use existing classification systems in order to take advantage of existing data sets and therefore ensure the immediate use of the proposed standard. In this case, the underlying system is the Harmonized System (HS). The HS is the only commodity classification system used on a sufficiently wide basis to support international data comparison. A large number of countries use it to classify export and import of goods, and many countries use it (or a classification derived from or linked to it) to categorise domestic outputs.The application of the ICT product definition to selection of in-scope HS categories is a somewhat subjective exercise. The fact that the HS is not built on the basis of the functionality of products makes it much more difficult. The distinction between products which fulfil those functions and products that simply embody electronics but fundamentally fulfil other functions is not always obvious.It is possible to adopt a narrow or broad interpretation of the guideline, though the OECD chose a broader interpretation, an approach which is consistent with that adopted to develop the ICT sector definition.

The allocation of bilateral intermediate imports across using industries assumes that import coefficients are the same for all trade partners, i.e. SHAREipkt is identical across exporter countries. Hence, the bilateral pattern of imported intermediates from industry p is the same across all using industries k. However, it is different from the bilateral pattern of total imports from industry p because trade data (measured by VALUEijpt) allows distinguishing bilateral imports of intermediates from final good imports in industry p. While the BEC classification enables the identification of intermediate goods, no similar classification is available for trade in services, due to the high level of aggregation in services trade data. While goods trade data are based on customs declarations allowing the identification of goods at a highly disaggregated level, services trade data are based on a variety of information such as business accounts, administrative sources, surveys, and estimation techniques (Manual on Statistics of International Trade in Services, 2002). Hence, in the case of trade in services, VALUEijpt is the total value of imports of service p, i.e. both final and intermediate (and not only services that are used in the production of other goods and services, as in the case of goods data). By making an additional assumption and adjusting SHAREipkt, it is however possible to calculate trade in intermediate services. In the case of services imports, SHAREipkt is the share of imported service inputs p used by industry k in total imports of p of country i. In the case of services, besides the assumption that all trading partners have the same distribution of intermediate imports p across using industries k, it is furthermore required that the share of intermediate services in overall bilateral services imports of country i is the same across all partner countries j. Finally, it should be mentioned that trade data reported in the trade statistics do not fully match imports as reported in I-O tables. One main reason is that while trade data is recorded at consumer prices, I-O tables are evaluated at producer prices. There are also other differences such as the treatment of re-exports, scrap metal, waste products and second hand goods or unallocated trade data.

Despite the growing importance of international trade, driven in large part by the rise of globalisation and the accompanying international fragmentation of production, the availability of statistics on price change in international merchandise trade at more graular level is still limited. To fill this data gap, the OECD has developed this new Merchandise Trade Price Index (MTPI) database using UN COMTRADE. The first release covers about 100 countries from 2011 to 2017. Indices by reporting country are available for both exports and imports, broken down by 30 products, aligned with the 2-digit level of the Classification of Products of Activity (CPA, version 2.1). Future releases are planned to expand the country coverage and the level of disaggregation.

This table presents export/import information by detailed activity sectors (ISIC Rev.4)

This dataset shows import and export values (in millions of UDS) using product classification at 2-digit level of CPA classification.

This dataset presents data by export intensity, that is the share of exports on total turnover.

The central issue of trade by enterprise characteristics is to disaggregate trade flows according the characteristics of the enterprises engaged in cross-border transactions. The feasibility of doing so largely depends on the possibility of using or developing common identifiers between the trade register and the business register. Countries differ in their ability to perform such a linking, and matching ratios (between business and trade registers) vary across countries, and as a consequence the degree of representativeness of the results also varies across countries.

This dataset presents data by type of ownership, that is foreign or domestically controlled enterprise (with or without own affiliates abroad).

This table presents export/import information by enterprise size class and partner country.

This dataset shows the number of exporters and importers and their associated trade values for a selected set of partner countries and zones, broken down by three economic sectors: industry, trade and repair and other sectors. Total values for the wide economy are also displayed.Recommended uses and limitations EU countries break down trade data into Intra- and extra- EU zones, whereas non EU countries report their Total trade. Trade values have been aggregated for EU countries and Total (Intra-EU plus Extra-EU) trade flows are displayed, whereas Intra and Extra-EU data expressed in term of number of enterprises cannot be summed up, because of possible double-counting (same enterprise can be trader in both intra- and extra- EU trade). Data have been collected in ISIC revision 3 from 2003 up to 2007 and in ISIC revision 4 as from reference year 2008. Time series are affected by this change in classification, and thus data are displayed into two separate databases.

The central issue of trade by enterprise characteristics is to disaggregate trade flows according the characteristics of the enterprises engaged in cross-border transactions. The feasibility of doing so largely depends on the possibility of using or developing common identifiers between the trade register and the business register. Countries differ in their ability to perform such a linking, and matching ratios (between business and trade registers) vary across countries, and as a consequence the degree of representativeness of the results also varies across countries.

This dataset shows imports/exports by type of trader that is exporter only, importer only or both importer and exporter (Two-way trader).

This dataset (TEC 01) presents a breakdown by economic activity according to International Standard Industrial Classification, Revision 4 (ISIC Rev. 4) and by employment size class. International trade statistics are among the most widely available and consulted data, and offer a picture of trade flows between countries, broken down by types of goods and services. However, such conventional international trade statistics do not offer insights into the actors who are actually engaged in cross-border trade. The Trade by Enterprise Characteristics (TEC) database aims to fill this gap, and contains international annual trade in goods data broken down by different categories of enterprises. The data provide a solid basis for policy analyses that explore which types of firms are responsible for international trade in goods. It answers questions like who are the firms that are engaged in foreign markets, and what are their characteristics. Both the export and import values and the number of exporting and importing enterprises are available for 26 OECD and 8 non-OECD countries: including 27 EU member states plus Canada, Costa Rica, Norway, Israel, Turkey, the United Kingdom and the United States. Data for the United Kingdom haven't been updated since reference year 2018, for Korea and Mexico since reference year 2015. The database consists of ten datasets presenting various combinations of breakdowns by economic activity, employment size class, concentration of trade, partner countries, commodity, type of traders, type of ownership (foreign vs. domestic), exports intensity. TEC data are collected in co-operation with Eurostat and directly from National Statistical Authorities (NSOs). To create TEC data, NSOs have to attribute trade flows to enterprises with different characteristics by merging data on international trade (usually customs data) with statistical business register information on enterprises at the individual enterprise level. Related datasets: Employer Business Demography Statistics, Business Demography Statistics, Regional Business Demography, Structural Business Statistics by Size Class, Timely Indicators of Entrepreneurship by Enterprise Characteristics.

The TiVA database contains a range of indicators measuring the value added content of international trade flows and final demand. The indicators are derived from the 2016 version of OECD's Inter-Country Input-Output (ICIO) Database.  The ICIO has been constructed from various national and international data sources all drawn together and balanced under constraints based on official (SNA93) National Accounts by economic activity and National Accounts main aggregates.  Underlying sources used are notably:  • National supply and use tables (SUTs)  • National and harmonised Input-Output Tables • Bilateral trade in goods by industry and end-use category (BTDIxE) and  • Bilateral trade in services.  Compared to the old versions of the TiVA database, this current version includes two more countries, Morocco and Peru. The data are presented for all years from 1995 to 2011. The industry breakdown remains the same.