Organisation for Economic Co-operation and Development

The OECD’s ANalytical Business Enterprise Research and Development (ANBERD) database presents annual data on Research and Development (R&D) expenditures by industry and was developed to provide analysts with comprehensive data on business R&D expenditures. The ANBERD database incorporates a number of estimations that build upon and extend national submissions of business enterprise R&D data by industry (main activity/industry orientation).

This table presents Gross Domestic Product (GDP) and its components according to the output approach. In the output approach, GDP is measured as the sum of gross value added (GVA) of all economic activities plus taxes less subsidies on products. This table includes breakdowns of GVA by type of economic activity according to Revision 4 of the International Standard Industrial Classification of All Economic Activities (ISIC). The presentation is on a country-by-country basis. Users are recommended to select one country (or area) at a time in the ‘Reference area’ filter. Data is presented for each country in national currency as well as in euros for the European Union and the euro area. Data is also presented converted to US dollars using exchange rates. It is also possible to select current prices, chain linked volumes etc using the ‘Price base’ filter (the default view is current prices). The table shows OECD countries and selected economies, as well as the OECD total, OECD Europe, European Union and euro area. These can be selected using the ‘Reference area’ filter. These indicators were presented in the previous dissemination system in the SNA_TABLE1 dataset. See ANA Changes for information on changes in methodology: ANA Changes Explore also the GDP and non-financial accounts webpage: GDP and non-financial accounts webpage OECD statistics contact: [email protected]

Business Tendency Surveys (BTS) – also called business opinion or business climate surveys – are economic surveys used to monitor and forecast business cycles. Covering 4 different economic sectors (manufacturing, construction, retail trade and services), they are designed to collect qualitative information useful in monitoring the current business situation and forecasting short-term developments by directly asking company managers about the pulse of their businesses. They are well known for providing advance warning of turning points in aggregate economic activity as measured by GDP or industrial production. As respondents provide answers on a 3 scale options (up, same, down, or above normal, normal, below normal), data are summarised in net balances corresponsing to the difference in % of positive over negative replies. Because of their collection mode, timeliness and immediate availability, they have proved to be a cost‑effective mean of generating timely information especially during crises. In the late '90, in collaboration with the European Commission, the OECD has developed a system of harmonised business tendency surveys in order to collect and compare data across countries. The EC Directorate General for Economic and Financial Affairs is since then in charge of running the program and collecting data across EU members, while the OECD helped the adoption and implementation of the same harmonised framework in non-EU OECD countries and BRIICS. By construction, BTS questions are formulated in order to exclude seasonal factors. Nevertheless all series are tested for seasonality by both the OECD (using x12) and by the EC for the EU member data (using DAINTIES). This dataset comprises a set of harmonised target indicators available across OECD and BRIICS countries, any departure from target definitions are documented in the metadata.

Data on enterprises and employment in tourism industry.

This dataset FDI by counterpart area and by economic activity, BMD4 includes inward and outward Foreign Direct Investment (FDI) flows, positions and income by partner country and by economic activity for OECD reporting economies. It is a simplified dataset with fewer breakdowns compared to the other separate datasets specifically dedicated to FDI flows, FDI positions or FDI income by counterpart area, or by economic activity. In this dataset, FDI exclude resident SPEs, when they exist (unless otherwise stated, see metadata attached at the reporting country level); and inward FDI positions are allocated to the ultimate counterpart country when available (see metadata attached at the reporting country level). Inward and outward FDI statistics in this dataset are presented on a directional basis (unless otherwise stated, see metadata attached at the reporting country level); they are measured in USD millions, in millions of national currency and as a share of total (for FDI positions only). This dataset supports FDI indicators by counterpart area and by economic activity available from the OECD Data Portal. In 2014, many countries implemented the latest international standards for Foreign Direct Investment (FDI) statistics:the OECD’s Benchmark Definition of FDI, 4th edition (BMD4); andthe IMF’s Balance of Payments and International Investment Position Manual, 6th edition (BPM6) This OECD database was launched in March 2015 which includes the data series reported by national experts according to BMD4. The data are for the most part based on balance of payments statistics published by Central Banks and Statistical Offices following the recommendations of the IMF’s BPM6 and the OECD’s BMD4. However, some of the data relate to other sources such as notifications or approvals.

This dataset FDI by counterpart area and by economic activity, BMD4 and historical BMD3 includes long time series of FDI statistics by partner country and by industry. It uses available BMD4 series and combines them with BMD3 historical series (from the unrevised OECD FDI datasets according to BMD3) as far back as 2005 and identifies breaks in series. For selected countries, breaks in series were removed as there was no significant impact of BMD4 implementation. In this dataset, inward and outward FDI flows, positions and income include resident SPEs when they exist (unless otherwise stated, see metadata attached at the reporting country level); and they are allocated to the immediate counterpart country (unless otherwise specified, see metadata attached at the reporting country level). Inward and outward FDI statistics in this datset are presented on a directional basis (unless otherwise stated, see metadata attached at the reporting country level); they are measured in USD millions, in millions of national currency and as a share of total (for FDI positions only). In 2014, many countries implemented the latest international standards for Foreign Direct Investment (FDI) statistics:the OECD’s Benchmark Definition of FDI, 4th edition (BMD4); andthe IMF’s Balance of Payments and International Investment Position Manual, 6th edition (BPM6) This OECD database was launched in March 2015 which includes the data series reported by national experts according to BMD4. The data are for the most part based on balance of payments statistics published by Central Banks and Statistical Offices following the recommendations of the IMF’s BPM6 and the OECD’s BMD4. However, some of the data relate to other sources such as notifications or approvals.

This dataset FDI flows by economic activity, BMD4 includes inward and outward Foreign Direct Investment (FDI) flows by economic activity for OECD reporting economies:Inward FDI flows by economic activity measure the value of cross-border direct investment transactions received by the reporting economy in a specific industry during a year, enabling, for example, the identification of the most attractive industries for FDI in each OECD economy in that year.Outward FDI flows by economic activity measure the value of cross-border direct investment transactions from the reporting economy during a year, by industry. The industry sector corresponds to the activity of the direct investment enterprise or to the activity of the direct investor (more details on the activity allocation method for outward FDI flows are indicated in the metadata information attached at the country level). Inward and outward FDI flows by economic activity are presented according to the directional principle (unless otherwise specified in the country level metadata); they are measured in USD millions and in millions of national currency. A cross-classification of inward and outward FDI flows by major ISIC4 sections and by main geographic aggregates are also available for some OECD reporting economies. In 2014, many countries implemented the latest international standards for Foreign Direct Investment (FDI) statistics:the OECD’s Benchmark Definition of FDI, 4th edition (BMD4); andthe IMF’s Balance of Payments and International Investment Position Manual, 6th edition (BPM6) An OECD database was launched in March 2015 which includes the data series reported by national experts according to BMD4. The data are for the most part based on balance of payments statistics published by Central Banks and Statistical Offices following the recommendations of the IMF’s BPM6 and the OECD’s BMD4. However, some of the data relate to other sources such as notifications or approvals. Historical and unrevised series of FDI flows by economic activity under the previous BMD3 methodology can be accessed in the archived dataset FDI flows by industry.

The ICT Access and Usage by Businesses database provides a selection of 59 indicators, based on the 2nd revision of the OECD Model Survey on ICT Access and Usage by Businesses.

Main Economic Indicators (MEI) provides a wide range of indicators on recent economic developments in the 35 OECD member countries and 15 non-member countries. The indicators published in MEI have been prepared by national statistical agencies primarily to meet the requirements of users within their own country. In most instances, the indicators are compiled in accordance with international statistical guidelines and recommendations. However, national practices may depart from these guidelines, and these departures may impact on comparability between countries.

The National Accounts at a Glance (NAAG) is based on the original publication and has nine chapters: The first chapter focuses on indicators of Gross Domestic Product (GDP). The second is about income and related indicators and presents measures of net national income, savings and net lending/net borrowing. The third chapter looks at the expenditure approach to GDP, with information on the key components of demand and imports. The fourth chapter presents indicators from a production perspective. The fifth chapter looks at household sector indicators such as household disposable income, saving and net worth. The sixth chapter focuses on general government, presenting indicators such as general government revenue, expenditure and gross debt. The seventh chapter looks at financial and non-financial corporations. The eighth chapter presents indicators of capital stock and depreciation. Finally, chapter 9 provides reference indicators, important in their own right but also because they are used in the construction of many of the indicators presented elsewhere in NAAG.

Statistical population: Its presents output, intermediate consumption and the gross value added and its components, in particular compensation of employees and gross operating surplus and mixed income, broken down by detailed industries. It has been prepared from statistics reported to the OECD by Member countries in their answers to annual national accounts questionnaire. Data presented in this table will not be updated after summer 2010. Data reported to the OECD by countries in their answers to the annual national accounts questionnaire are now available on theme Industry and Services, Structural Analysis (STAN) Databases. Unit of measure used: In national currency, in current prices and constant prices (national base year, previous year prices and OECD base year i.e. 2010). Expressed in millions. For the Euro area countries, the data in national currency for all years are calculated using the fixed conversion rates against the euro.

This dataset reports data on pharmaceutical consumption and sales, according to the Anatomical Therapeutic Chemical (ATC) classification, and on the share of generics in the pharmaceutical market.

DUE TO CHANGES IN THE METHODOLOGY THE 2018 PMR VALUES CANNOT BE COMPARED WITH PREVIOUS VINTAGES. The 2018 OECD Indicators of Product Market Regulation (PMR) are a comprehensive and internationally-comparable set of indicators that measure the degree to which laws and policies promote or inhibit competition in areas of the product and service market where competition is viable. These indicators measure the de iure regulatory environments in 34 OECD countries and in a set of non-OECD countries in 2018. The economy-wide indicators cover the extent to which the involvement of the state in the economy can generate distortions to competition and the level of the barriers to entry and expansion to domestic and foreign firms in different sectors of the economy. Users of the data must be aware that they may no longer fully reflect the current situation in fast reforming countries.

The OECD Productivity Database aims at providing users with the most comprehensive and the latest productivity estimates. The update cycle is on a rolling basis: each variable in the dataset is made publicly available as soon as it is updated in the sources databases. The productivity database contains data on labour productivity both measured using employment or hours worked and the compenents of capital and labour inputs. The productivity database in levels, in growth rates and by industry contains annual data, while the database on productivity and unit labour costs are quarterly estimates. Further information for all datasets and the methodology may be found in the attached file OECD-Productivity-Statistics-Database-metadata

The OECD STRI is a unique, evidence-based tool that collects information on services trade restrictions across 22 services sectors. The project has two distinct but complementary instruments: a services trade regulatory database and a services trade restrictiveness index. Based on the qualitative information in the database, composite indices quantify the identified restrictions across five standard policy categories, with values between zero and one. Complete openness to trade and investment gives a score of zero, while being completely closed to foreign services providers yields a score of one.

STAN database for structural analysis provides analysts and researchers with a comprehensive tool for analysing industrial performance at a relatively detailed level of activity across countries. It includes annual measures of output, value added and its components, labour input, investment and capital stock thus allowing to construct indicators which focus on productivity growth, competitiveness and general structural change. STAN is primarily based on Member countries' Annual National Accounts by economic activity tables compiled according to the recommendations of System of National Accounts 2008 (SNA 2008). Previous versions of STAN (from 2000) were based on SNA93 statistics. Missing data are estimated using other sources such as national industrial surveys/censuses. Time series are extended back to the 1970's where possible. This is done using vintage SNA93 or STAN estimates. In STAN, many data points are Secretariat's estimates and are flagged to the attention of users; as such, they do not represent official Member countries' submissions. The current version of STAN is using an industry list based on the International Standard Industrial Classification of all economic activities, Revision 4 (ISIC Rev. 4). Earlier versions of STAN were based on ISIC Rev. 3 and, prior to 2000, ISIC Rev. 2 (the latter covering the manufacturing industries only).The industries covered in STAN provide sufficient detail to highlight technology and digital-intensive sectors. • Structure • Documentation • Coverage Note that STAN updates resume progressively starting from the 1st quarter of 2024. Users are encouraged to send comments or questions to [email protected]

OECD statistics contact: [email protected] The OECD Secretariat collects a wide range of statistics on businesses and business activity. The Structural Business Statistics by size class dataset is part of the Structural and Demographic Business Statistics (SDBS) database featuring the harmonised data collection of the OECD Statistics and Data Directorate relating to a number of key variables, such as value added, operating surplus, employment, and the number of business units. Data are broken down to class (4-digit) level of International Standard of Industrial Classification (ISIC Revision 4), and by enterprise size class based on the number of persons employed. Data cover OECD member and partner countries, non-OECD countries that are members of the European Statistical System who provide data to Eurostat, as well as countries participating in OECD Regional initiatives.

This dataset describes the matrix of trade and transport margins (trade margins are the difference in price realised by a wholesaler or retailer when reselling a good compared with the price to replace the good ; transport margins are transportation charges explicitly invoiced for the delivery). This dataset is one of the valuation matrices that are used to transform the Use table at purchasers’ prices (the price paid by the buyer) into the Use table at basic prices (the price received by the producer or for imports, the value at the border). The columns provide information about trade and transport margins related to intermediate consumption by economic activities (at the 2-digit level of the International Standard Industrial Classification of All Economic Activities (ISIC) Rev 4, containing 89 industries); final consumption expenditure of households, general government and non-profit institutions serving households (NPISHs); gross capital formation (broken down between gross fixed capital formation, changes in inventories, and acquisitions less disposals of valuables); and exports. The rows provide a breakdown by product (using the comparable European Classification of Products by Activities (CPA) breakdown). The dataset has been prepared from statistics reported to the OECD by countries in their answers to the annual Supply and Use questionnaire. Information about data availability is available in SUT updates The dataset corresponds to SNA_TABLE44 dataset in the previous dissemination system. A mapping between the new codes and previous codes is available in SUT_VALUATION_Codes_mapping The file SUT_Tips contains further suggestions on how to navigate and use the various Supply and Use tables (SUTs) in the new dissemination system. Explore the OECD SUT webpage SUT webpage

Since new and young firms contribute critically to job creation, innovation and growth, observing recent trends of firm formation provides valuable information to policy makers. Seasonal adjustment: For the purpose of presentation of quarterly series, seasonal adjustment is applied using TramoSeats algorithm with 5 regressors: log/level, trading days, Easter, outlier detection, and automatic model identification). Series are log-transformed and decomposed into a trend component. Finally, index is calculated based on a 2007 (2007 = average of 2007 quarters) in order to present movements between the base year and a given quarter.

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 Trade by Enterprise Characteristics (TEC) database contains international annual trade data broken down in different categories of enterprises. Its aim is to provide a solid basis for analysts who explore, in the context of globalisation, the characteristics of trade actors. The TEC data are collected in co-operation with Eurostat, directly from the NSOs, through a linkage exercise of trade and business registers made. Data in export/import values and in number of exporting/importing enterprises are available for 19 EU member states (Czech Republic, Denmark, Germany, Estonia, France, Italy, Cyprus, Latvia, Lithuania, Luxembourg, Hungary, Austria, Poland, Portugal, Romania, Slovenia, Slovakia, Finland and Sweden), plus Canada, Norway, Israel and the Unites States. Key Statistical Concept The central issue of trade by enterprise characteristics is to try to classify trade operators according to enterprise characteristics and 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 are different in their ability to perform such a linking, and matching ratios (between business and trade registers) vary between countries, thus the degree of representativeness of the results varies between countries.

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.