Go for Quality and Quantity in Trading

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Finance English practice: Unit 34 — Futures

  • Complete the sentences below. Use the key words if necessary.
    • Commodity futures

    are agreements to sell an asset at a fixed price on a fixed date in the future. are traded on a wide range of agricultural products (including wheat, maize, soybeans, pork, beef, sugar, tea, coffee, cocoa and orange juice), industrial metals (aluminium, copper, lead, nickel and zinc), precious metals (gold, silver, platinum and palladium) and oil. These products are known as .

    Futures were invented to enable regular buyers and sellers of commodities to protect themselves against losses or to against future changes in the price. If they both agree to hedge, the seller (e.g. an orange grower) is protected from a fall in price and the buyer (e.g. an orange juiced manufacturer) is protected from a rise in price.

    Futures are contracts — contracts which are for fixed quantities (such as one ton of copper or 100 ounces of gold) and fixed time periods (normally three, six or nine months) — that are traded on a special exchange.

    Forwards are individual, contracts between two parties, traded — directly, between, two companies of financial institutions, rather than through an exchange. The futures price for a commodity is normally higher than its — the price that would be paid for immediate delivery. Sometimes, however, short-term demand pushes the spot price above the future price. This is called .

    Futures and forwards are also used by speculators — people who hope to profit from price changes.

    More recently, have been developed. These are standardized contracts, traded on exchanges, to buy and sell financial assets. Financial assets such as currencies, interest rates, stocks and stock market indexes — continuously vary — so financial futures are used to fix a value for a specified future date (e.g. sell euros for dollars at a rate of €1 for $1.20 on June 30).

    and are contracts that specify the price at which a certain currency will be bought or sold on a specified date.

    are agreements between banks and investors and companies to issue fixed income securities (bonds, certificates of deposit, money market deposits, etc.) at a future date.

    fix a price for a stock and fix a value for an index (e.g. the Dow Jones or the FTSE) on a certain date. They are alternatives to buying the stocks or shares themselves.

    Like futures for physical commodities, financial futures can be used both to hedge and to speculate. Obviously the buyer and seller of a financial future have different opinions about what will happen to exchange rates, interest rates and stock prices. They are both taking an unlimited risk, because there could be huge changes in rates and prices during the period of the contract. Futures trading is a , because the amount of money gained by one party will be the same as the sum lost by the other.

  • British English or American English?
    • aliminium
      • British English
      • American English

    • aluminum
      • American English
      • British English

  • Match the definitions with the words below.
    • 1. the price for the immediate purchase and delivery of a commodity — . . .

      Go for Quality and Quantity in Trading

      Eurostat, the statistical office of the European Union

      1.2. Contact organisation unit

      G5 – Trade in Goods

      1.5. Contact mail address

      2920 Luxembourg LUXEMBOURG

      2. Metadata update Top
      2.1. Metadata last certified 31/01/2020
      2.2. Metadata last posted 31/01/2020
      2.3. Metadata last update 31/01/2020

      International trade in goods statistics (ITGS) published by Eurostat measure the value and quantity of goods traded between the EU Member States (intra-EU trade) and goods traded by the EU Member States with non-EU countries (extra-EU trade). ‘Goods’ means all movable property including electricity. ‘European’ means that the statistics are compiled on the basis of the concepts and definitions set out in EU legislation. ‘National’ statistics, i.e. statistics published at national level by the Member States, are compiled on the basis of national rules which may differ from EU rules. European ITGS are the official harmonised source of information about exports, imports and the trade balances of the EU, its Member States and the euro area.

      Aggregated versus detailed data

      International trade in goods statistics are published through different datasets grouped into two categories:

      • Aggregated data refer to macroeconomic indicators for the EU and euro area. Monthly (short-term indicators) and annual (long-term indicators) data are aggregated by broad product categories. Broad product categories are defined as one-digit codes of the Standard International Trade Classification (SITC) or aggregates of the Broad Economic Categories (BEC).
      • Detailed data refer to the most detailed level of the following product nomenclatures: the Combined Nomenclature (CN), the SITC, the BEC, the Classification of Products by Activity (CPA) and the Standard Goods Classification for Transport Statistics/Revised (NSTR). Detailed data also contain product aggregations at higher levels.

      Statistical dimensions

      Data periodicity (monthly or yearly) and product nomenclature (CN, SITC, BEC or CPA) differ depending on the dataset, but the following statistical fields are always available:

      • reporting country: country or geo-economic area such as EU or euro area;
      • partner country: EU Member State, non-EU country or geo-economic area.
      • reference period: month and/or year;
      • trade flows: import and export; and
      • product according to the relevant classification.

      Besides the dimensions listed above, specific datasets contain information on the mode of transport (e.g. by sea, by air or by road) or the statistical procedure (normal trade versus trade for processing activities).

      Combined Nomenclature as primary product nomenclature

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      The Combined Nomenclature (CN) is the primary nomenclature as it is the one used by the EU Member States to collect detailed data on their trading of goods. It is based on the Harmonised Commodity Description and Coding System (managed by the World Customs Organisation (WCO)). The CN corresponds to the HS plus a further breakdown at eight-digit level defined to meet EU needs. It includes around 9 500 eight-digit codes and is subject to annual revisions that ensure it is kept up to date in the light of changes in technology or patterns of international trade in goods.

      Other product nomenclatures

      Eurostat manages correspondence tables enabling the transposition of detailed data collected according to the Combined Nomenclature into other classifications like the Standard International Trade Classification (SITC), the Classification of Products by Activity (CPA), the Broad Economic Activities (BEC) or the classification of goods for transport statistics NSTR/Rev.1.

      • Standard International Trade Classification (SITC) managed by the United Nations) is correlated with the subheadings of the Harmonised System. SITC Rev. 4 comprises 2 970 basing headings which are aggregated into 262 groups, 67 divisions and 10 sections. The section level is the one used to disseminate aggregated data.
      • Classification of Products by Activity (CPA) – The CPA is a European version of the United Nations’ Central Product Classification (CPC), but arranged so that each product heading is assignable to a single heading of the European activity classification, the NACE Rev. 2. CPA enables trade statistics to be considered jointly with other sets of general economic statistics — such as national accounts, employment statistics and industrial statistics — for productivity analysis, links with input-output tables and the impact of trade on employment.
      • Broad Economic Categories (BEC) – Like the SITC, the BEC is managed by the United Nations. It permits the conversion of international trade data based on the SITC into end-use categories. The BEC has 19 basic categories that can be aggregated to approximate the three basic classes of goods (capital, intermediate and consumption goods).
      • NSTR-rev.1 – The ‘Nomenclature uniforme des marchandises pour les Statistiques de Transport, Révisée’ is used to publish detailed trade in goods data by mode of transport. This classification is used since 1 January 1989. It comprises 99 chapter headings and 10 sections.

      Country classification

      An ISO alpha-2 coding applies, which means that each country is identified with a two-letter alphabetical code. See the publication Geonomenclature applicable to European statistics on international trade in goods for more information.

      Trade in goods statistics consist of both intra- and extra-EU trade flows. They cover all goods entering (imports) or leaving (exports) the statistical territories of the EU Member States. The statistical territory of a Member State corresponds to its customs territory with one exception: the statistical territory but not the customs territory of Germany includes Heligoland.

      Reporting country – Except for some specific goods like vessels and aircraft, ITGS follow the physical movements of the goods. Member States should record an import when goods enter their statistical territory and an export when goods leave that territory except if those goods are in simple transit. Goods should be recorded only when adding to or subtracting from the stock of national material resources or, in the context of extra-EU trade, when customs formalities are applied.

      Partner country – This is the last known country of destination for intra- and extra-EU exports, the country of origin for extra-EU imports and the country of consignment for intra-EU imports

      Product code – Goods are primarily classified by commodity code as set out in the EU Combined Nomenclature. Eurostat manages correspondence tables enabling the transposition of detailed data collected according to the Combined Nomenclature into other classifications like the Standard International Trade Classification (SITC), the Classification of Products by Activity (CPA), the Broad Economic Activities (BEC) or the classification of goods for transport statistics NSTR/Rev.1. All classifications and correspondence tables are available on Eurostat’s metadata server RAMON.

      Statistical procedure (only in detailed data relating to extra-EU trade) This relates to customs procedures and distinguishes between different types of imports and exports: imports/exports covered by the customs inward processing procedure and imports/exports covered by the customs outward processing procedure are distinguished from normal transactions or transactions not recorded from customs declarations.

      Mode of transport (only in detailed data)– This identifies the active means of transport (e.g. road, rail, sea) by which the goods leave/enter the statistical territory of a Member State for intra-EU trade and of the EU for extra-EU trade. Note that the collection of the mode of transport for intra-EU trade flows became optional in 2001. Therefore the information is not available for all the EU Member States since January 2001 as reference month.

      Container (only in detailed data relating to extra-EU trade)

      In addition to the mode of transport, for extra-EU trade, information is collected on whether or not goods are transported in containers (except when the mode of transport is postal consignment, fixed transport installation or the own propulsion category).

      Nationality of the active means of transport (only in detailed data relating to extra-EU trade)

      In addition to the mode of transport, for extra-EU trade, information is collected on the nationality of the active means of transport of the goods when they leave/enter the statistical territory of the EU (except when the mode of transport is rail, postal consignment, fixed transport installations and own propulsion). Note that the nationality of the means of transport became optional in 2020. Therefore the information is not available for all the EU Member States since January 2020 as reference month.

      Trade value

      This is the statistical value, i.e. the amount that would be invoiced in the event of sale or purchase at the national border of the reporting country. It is said to be a FOB (Free On Board) valuation for exports and a CIF (Cost Insurance Freight) valuation for imports. Hence, only incidental expenses (freight, insurance) are included and incurred for:

      • exports in the part of the journey located on the territory of the country where the goods are exported from;
      • imports in the part of the journey located outside the territory of the country where the goods are imported to.

      Quantity (only in detailed data)

      This is the weight of the goods in kilograms without packaging; this quantity is referred to as the ‘net mass’. For certain goods, a supplementary quantity is available. The supplementary unit varies according to the goods; it can be litres, number of pieces, carats, terajoules, square metres, etc. as detailed in the annual Commission regulation updating the Combined Nomenclature.

      Any natural and legal person lodging a customs declaration in a Member State is reporting to the extra-EU trade statistics on the condition that the customs procedure is of statistical relevance.

      Within intra-EU trade statistics any taxable person carrying out an intra-EU trade transaction is responsible for providing the information. However small and medium trade operators are exempted from the obligation to provide Intrastat declarations. The Intrastat system is based on thresholds which allow intra-EU traders not to report on their transactions or provide less detailed information on condition that their total trade value does not exceed a certain amount during the previous or present calendar year. Those thresholds are fixed according to quality standards defined in the Intrastat legislation.

      Trade in goods of the EU and its Member States includes all goods which add or subtract from the stock of material resources of the reporting Member State by entering (imports) or leaving (exports) its economic territory including goods for processing. Information on the goods is provided by legal or natural person.

      For long term indicators (annual data):

      • European Union and Euro area as reporting entity since 2002
      • All Member States since 2002

      For short term indicators (monthly data):

      • European Union as reporting entity since 2002, Euro area as reporting entity since 1999
      • All Member States since 1999 (except Croatia), Croatia since 2002

      Detailed data (monthly data)

      • European Union and Euro area as reporting entity since 2000
      • Member States since 1988 or a more recent year, depending on the dataset and reporting countries.

      Starting from October 2020 as release date, trade in goods indices (IVU – unit value index and IVOL – volume index) are calculated for the reference year 2020 (2020 = 100) instead of 2020. This change has a limited impact on the calculation of indices, because IVU and IVOL are chained indices, that is for every period the base year is the previous year.

      3. Statistical presentation Top
      3.1. Data description
      3.2. Classification system
      3.3. Coverage – sector
      3.4. Statistical concepts and definitions
      3.5. Statistical unit
      3.6. Statistical population
      3.7. Reference area
      • European Union (as aggregate and for each EU Member State)
      • Euro area (as aggregate and for each EA Member State)
      3.8. Coverage – Time
      3.9. Base period

      Aggregated data – Long-term indicators (annual data)

      • trade value (in billion euro);
      • shares by reporting country or by main trading partners;
      • unit-value indices;
      • volume indices; and
      • shares by invoicing currency.

      Aggregated data – Short-term indicators (monthly data)

      • gross and seasonally adjusted value (in million euro) for exports, imports and trade balances;
      • growth rates for exports and imports based on gross and seasonally adjusted values
      • unit-value indices;
      • gross and seasonally adjusted volume indices;
      • ratio of export and import indices; and
      • growth rates for gross and seasonally adjusted indices.

      Detailed data (monthly and annual data)

      • trade values (in euros or national currency
      • quantities in 100 kg (net mass)
      • wherever relevant, quantities in the supplementary unit, according to the Combined Nomenclature (e.g. litres, square metres, number of items)
      4. Unit of measure Top

      Theoretically, the reference period for the information on international trade in goods transactions should be the calendar month of export or import of the goods. However, in practice the reference period for extra-EU trade is generally the calendar month during which the customs declaration is accepted by customs authorities. The reference period for intra-EU trade may be adapted in case of sales or purchases to the calendar month during which the VAT on the intra-EU supplies or acquisitions becomes chargeable. The chargeable event relates to the issue date of the invoice.

      5. Reference Period Top

      General statistical legislation

      Regulation (EC) No 223/2009 of the European Parliament and of the Council on European statistics

      Intra-EU trade legislation (or Intrastat)

      • Regulation (EC) No 638/2004 of the European Parliament and of the Council
      • Implementing Commission Regulation (EC) No 1982/2004

      Extra-EU trade legislation (or Extrastat)

      • Regulation (EC) No 471/2009 of the European Parliament and of the Council
      • Implementing Commission Regulation (EC) No 92/2020
      • Implementing Commission Regulation (EC) No 113/2020

      All regulations relevant for the European statistics on international trade in goods can be found in the publication Legislation on European statistics on international trade in goods or consulted from the Legislation page of the International trade in goods section on Eurostat website. All legal texts of the EU are accessible on Eur-Lex.

      6. Institutional Mandate Top
      6.1. Institutional Mandate – legal acts and other agreements
      6.2. Institutional Mandate – data sharing

      Regulation (EC) No 223/2009 on European statistics (recital 24 and Article 20(4)) of 11 March 2009 (OJ L 87, p. 164), stipulates the need to establish common principles and guidelines ensuring the confidentiality of data used for the production of European statistics and the access to those confidential data with due account for technical developments and the requirements of users in a democratic society.

      As a general definition, data used by national and EU authorities for producing statistics are considered confidential if statistical units can be identified, either directly or indirectly, and information about individuals or businesses is disclosed as a result.

      Note that confidential information can be found only in detailed data or in data by enterprise characteristics. The aggregated data or the data by invoicing currency are not detailed enough to make it possible to identify a specific trader.

      Principle of passive confidentiality — The National Statistical Authority has to take appropriate measures only if requested to do so by companies which feel that their interests would be harmed by publication of the data. This principle is recommended by the United Nations in its IMTS 2020 publication and set out in the EU legislation for detailed statistics on intra- and extra-EU trade. It has the great advantage of limiting the loss of information for users and thus making the data more useful.

      Criteria for granting confidentiality — The choice of the criteria to be met by the company is left to the National Statistical Authority. The most common criteria are the following:

      • the number of companies on the market is limited, e.g. fewer than three companies contribute to a single data cell; or
      • the company is in a dominant position on the market (by representing, for instance, at least 75 % of the total trade) or is at least an important stakeholder for a specific data cell.

      Data elements possibly hidden – In detailed data, confidentiality can apply to the product code and/or the partner country. Information about a product or partner may be considered commercially sensitive by the provider of the statistical information for the trade value, the quantity or the unit value (value/quantity) which can be considered a proxy for the price. When confidentiality is granted, data are hidden at the detailed level, which means that the trade is not allocated to the real product code and/or the real partner. It is nevertheless included in the total trade of the reporting country (EU Member State or EFTA country) and even, wherever possible, allocated to the real chapter (i.e. to the real HS2 code). This minimum level of provision is set out in the EU legislation: Member States shall transmit data declared confidential to Eurostat so that they may be published at least at chapter level of the CN provided confidentiality is thereby ensured.

      7. Confidentiality Top
      7.1. Confidentiality – policy
      7.2. Confidentiality – data treatment

      The precise date of the monthly release for international trade data is disseminated on the website. News releases are issued and Euro indicators are updated on the web at 11:00 am CET on the day indicated.

      In line with the EU legal framework and the European Statistics Code of Practice Eurostat disseminates European statistics on Eurostat’s website (see item 10 ‘Accessibility and clarity’) respecting professional independence and in an objective, professional and transparent manner in which all users are treated equitably. The detailed arrangements are governed by the Eurostat protocol on impartial access to Eurostat data for users.

      8. Release policy Top
      8.1. Release calendar
      8.2. Release calendar access
      8.3. Release policy – user access

      Aggregated data: Long-term and short-term indicators are updated on a monthly basis.

      Detailed data: Most datasets are updated on a monthly or daily basis. A few contain only annual data and are updated on a yearly basis.

      9. Frequency of dissemination Top

      News releases on-line

      Statistics Explained articles – Statistics Explained is an official Eurostat website presenting all statistical topics in an easily understandable way. Together, the articles make up an encyclopedia of European statistics, completed by a statistical glossary clarifying all terms used and numerous links to further information and the very latest data and metadata. The website is a portal for occasional and regular users alike. All Statistics Explained relating to ITGS can be accessed under this link. A series of articles are available, among them:

      The articles in Statistics Explained are regularly updated (usually once a year) and can be included in virtual publications, such as International trade in goods – a statistical picture.

      News Releases – First results on euro area and EU trade flows are published in the Euro indicators News Release on international trade in goods. The monthly news release is published online around 46 days after the reference month. The precise publication date is announced on the Eurostat website. Ad-hoc news releases are also published in particular when detailed data or data by invoicing currency are available for a new reference year.

      The Eurostat website is the only place the European ITGS are published. The data are accessible through different paths, the main one being the ‘Data’ page of the ‘International trade in goods’ dedicated section.

      The so-called ‘Main tables’ are predefined tables focusing on key indicators. They are refreshed automatically when data are loaded into the databases. The ITGS Main tables include key indicators for the EU, its Member States and the euro area both annually (long-term indicators) and monthly (short-term indicators). Data are available only for a limited range of products (e.g. SITC aggregates).

      The ‘Database’ entry point gives access to several datasets classified under the folders ‘International trade in goods – aggregated data’ (under which can be found the short- and long-term indicators) and ‘International trade in goods – detailed data’. The last heading under the latter folder concerns access to the Easy Comext database via a tailor-made application for ITGS. Easy Comext can also be accessed directly at http://epp.eurostat.ec.europa.eu/newxtweb/ or through an internet search for ‘Easy Comext’. Users needing to extract huge amounts of data should use Comext Analytical which is accessible through the Easy Comext interface but requires a login (‘Login’ button). User manuals are available under this link.

      The Bulk Download facility allows users to download Eurostat datasets in a format which can easily be imported into a chosen tool for further analysis. International trade in goods statistics are available in csv format from the Comext domain.

      User Guide on European statistics on international trade in goods – The purpose of this Guide is to explain to a wide range of users how the statistics relating to trade in goods, both between EU Member States and with non-EU countries, are collected, compiled, processed and published at European level. The different issues are tackled in a question and answer format.

      Compilers Guide on European Statistics on international trade in goods – This Guide provides clarifications, often through concrete examples, to help the compilers to better interpret and apply the complex legislation on ITGS.

      Quality Report on European statistics on international trade in goods — This Report provides users with a tool to assess the quality of the international trade in goods statistics published by Eurostat. The data quality can be assessed against indicators covering the following components: relevance, accuracy, timeliness and punctuality, accessibility and clarity, comparability and coherence.

      10. Accessibility and clarity Top
      10.1. Dissemination format – News release
      10.2. Dissemination format – Publications
      10.3. Dissemination format – online database
      10.4. Dissemination format – microdata access
      10.5. Dissemination format – other
      10.6. Documentation on methodology
      10.7. Quality management – documentation

      Quality reporting and assessment

      Both Intrastat and Extrastat basic acts (in force since 2009 for Intrastat and since 2020 for Extrastat) include standardised quality articles. These articles are in line with the ESS Quality definition, European Statistics Code of Practice and the Regulation of European Statistics. In particular, they require the Member States to provide Eurostat with annual quality reports within a fixed deadline.

      Data quality checks prior to any dissemination

      The prime responsibility for ensuring the data completeness and accuracy rests with the National Statistical Authorities. Further checks are carried out by Eurostat, essentially to ensure that the transmission of the requested data has been carried out satisfactorily, that datasets are complete, error-free, and there are no extreme values (outliers).

      Relevance

      The key users of European ITGS and their respective needs are very well known. The data relevance can be assessed as good thanks to regular satisfaction surveys and frequent contacts with users.

      Accuracy

      The European ITGS benefit from well-established data collection systems supported by effective validation and compilation tools. Nevertheless, the intra-EU trade statistics may suffer from late or non-response from the trade operators liable to statistical reporting. The issue is however limited to the detailed levels of the product classification as the Intrastat legislation makes mandatory the compilation of estimates for any missing data at least at the 2-digit level of the Combined Nomenclature (HS2) and by partner Member States. Over the last years, actions were also carried out to push the Member States facing high issues of non- or late-response to implement any necessary measures to ensure the data exhaustiveness.

      Additionally, confidentiality has an impact on data accuracy at very detailed (i.e. CN eight-digit) level. Aggregated levels are in general much less impacted thanks to the legal obligation for reporting countries to ensure dissemination at least at two-digit level of the Combined Nomenclature. The EU legislation however foresees derogation to that principle when the dissemination of real trade values at chapter level would disclose confidentiality information and would then harm the interest of the economic operator. In such a case, it is allowed to use the HS chapter 99 instead of the real chapter.

      That said, it should be kept in mind that basic data consist of millions of records to be produced every month, which means that it is impossible to achieve complete accuracy. As in all statistical work, a balance has to be struck between the resources devoted to checking and the likely benefit. Therefore the users should be aware of the margin of inaccuracy in the data used, at least at the most detailed level of data.

      Timeliness and punctuality

      The current timeliness is assessed as good for all data flows and no further acceleration is requested by the users except for data by enterprise characteristics which should be available only within 18 months after the reference year. This late availability is not due to the standard trade in goods data (first annual results available within 3 months after the reference year) but to the late update of the Business Register which is the information source for the enterprise characteristics.

      Thanks to well-established data collection and compilation procedures, the punctuality of data transmissions to Eurostat is very good. Issues are very rare and generally minor in terms of delay.

      Accessibility and clarity

      The accessibility of trade in goods data is very good thanks to the use of all Eurostat standard dissemination channels: news releases, pdf and on-line publications, visualisation tools, predefined tables, databases and bulk download facility allowing users to download Eurostat datasets in a format which can easily be imported into a chosen tool for further analysis.

      The dissemination of the European ITGS is supported by a complete set of structural metadata that make it easy to identify, retrieve and browse the data. The reference metadata describing the contents and the data quality are also quite exhaustive. In particular, it is worth mentioning the User Guide on European statistics on international trade in goods and the Quality Report on European statistics on international trade in goods.

      Coherence

      The coherence is first ensured by the Intrastat and Extrastat regulations which set up the concepts and definitions applicable to the compilation of European ITGS and secondly by a set of recommendations promoting the best methods and practices among the reporting countries.

      The coherence is further strengthened by Eurostat’s harmonised approach to data production and dissemination regardless of the type of data and the reporting country.

      Comparability

      • Comparability over time — The European ITGS benefit from a high level of comparability over time thanks to the stability of the concepts, definitions and classifications. As far as possible, this comparability is also maintained when methodological changes occur, thanks to the retroactive recalculation of the time series.
      • Comparability across countries — The European ITGS benefit from a high level of comparability across countries thanks to the implementation of harmonised rules for data collection and compilation. The comparability across countries could be however improved through further harmonisation in the national practices as regard some specific goods or movements.
      • Comparability across domains — The European ITGS constitute an essential source of information for the compilation of the balance of payments statistics and national accounts. Nevertheless, comparability across domains is affected by differences in concepts and definitions like, for instance, the application of the principle of physical movements through the national frontier for trade in goods statistics versus the change of economic ownership between residents and non-residents for the balance of payments.
      11. Quality management Top
      11.1. Quality assurance
      11.2. Quality management – assessment

      As international trade forms a major part of the world economy, statistics on trade in goods are an instrument of primary importance for numerous public and private sector decision makers. For example, international trade statistics

      • enable EU authorities to prepare multilateral and bilateral negotiations under the common commercial policy;
      • enable EU authorities to evaluate the progress of the Single Market and the integration of EU economies;
      • constitute an essential source of information for balance of payments statistics, national accounts and economic studies; and
      • help EU businesses conduct market research and define their commercial strategy.

      Statistics satisfy these needs in a variety of ways. Users may need either annual aggregated or detailed monthly data on products or partner countries. They may be interested in trade values in current prices or at constant prices. Alternatively, their interest may be in quantities rather than in values. These examples, which are far from exhaustive, show the diversity of users and their requirements. Eurostat tries to meet these various needs and toadapt toachanging environment, such as changes due to globalisation.

      User needs are monitored regularly. At EU level, there are regular contacts with key institutional users (e.g. Commission services or the European Central Bank) and with other main user groups such as trade associations. In daily work, users can easily communicate their requests and needs to Eurostat by using dedicated tools integrated in the data dissemination. Many countries also conduct regular user satisfaction surveys.

      Eurostat undertook its last large-scale user satisfaction survey focusing on ITGS in 2007. The survey found a very high level of satisfaction among users: 85 % were very or fairly satisfied with the data. This high level of satisfaction has been confirmed by every general User Satisfaction Survey carried out by Eurostat on an annual basis since then 2009. In the 2020 general survey, ‘International trade’ received the second most positive evaluation of all the statistical domains, with 62.3 % of respondents rating the data quality as very good or good and 20.4 % as adequate. ‘Economy and finance’ statistics received the highest evaluation, with 64.8 % (very good or good) and 16.8 % (adequate) respectively. These two domains outperformed the average rates

      The EU trade statistics are based on the EU legislation which is directly applicable in the Member States. In particular, the legislation includes a clear and precise list of all the statistical variables to be provided by the Member States to Eurostat. All the mandatory variables are provided by all the Member States.

      12. Relevance Top
      12.1. Relevance – User Needs
      12.2. Relevance – User Satisfaction
      12.3. Completeness

      The European ITGS benefit from well-established data collection systems supported by effective validation and compilation tools. Nevertheless, the intra-EU trade statistics may suffer from late or non-response from the trade operators liable to statistical reporting. The issue is however limited to the detailed levels of the product classification as the Intrastat legislation makes mandatory the compilation of estimates for any missing data at least at the 2-digit level of the Combined Nomenclature (HS2) and by partner Member States. Over the last years, actions were also carried out to push the Member States facing high issues of non- or late-response to implement any necessary measures to ensure the data exhaustiveness.

      Additionally, confidentiality has an impact on data accuracy at very detailed (i.e. CN eight-digit) level. Aggregated levels are in general much less impacted thanks to the legal obligation for reporting countries to ensure dissemination at least at two-digit level of the Combined Nomenclature. The EU legislation however foresees derogation to that principle when the dissemination of real trade values at chapter level would disclose confidentiality information and would then harm the interest of the economic operator. In such a case, it is allowed to use the HS chapter 99 instead of the real chapter.

      That said, it should be kept in mind that basic data consist of millions of records to be produced every month, which means that it is impossible to achieve complete accuracy. As in all statistical work, a balance has to be struck between the resources devoted to checking and the likely benefit. Therefore the users should be aware of the margin of inaccuracy in the data used, at least at the most detailed level of data.

      International trade in goods statistics are not collected via samples and so are not impacted by sampling errors. Intra-EU trade data are collected via the Intrastat system which is considered as a cut-off census. Extra-EU trade data are based on the records of trade transactions in customs declarations and are so considered to be of administrative source.

      Errors often arise when trying to capture movements of goods or trade activities about which little information is available or which are inherently complex to measure, such as:

      • Goods that by their nature are difficult to classify — Errors may arise in the product code allocated due to the complexity of the classification (around 9 500 subheadings in the CN), for instance for chemical or pharmaceutical products.
      • Processing trade valuation — Errors arise when the processing costs are reported rather than the trade value corresponding to the total amount which would be invoiced if the goods were sold or bought.
      • Product with embedded services — Errors arise when the total amount of the contract (transaction including the supply of goods and services) is reported rather than the value of the goods alone.
      • Repairs versus processing — Repairs should be excluded from trade in goods statistics but processing should be included. Errors may arise when the distinction between repairs and processing is difficult to make.
      • Quasi transit — Intrastat declarations may be missing for goods imported from a non-EU country for immediate dispatch to another Member State or goods imported from another Member State for immediate dispatch to a non-EU country.
      • Triangular trade — trade involving three Member States through sales/purchase contracts but with physical movement of goods between only two of them. A problem arises when the trade is reported according to the sales/purchase contract rather than the physical movement.

      Besides errors, the accuracy of trade in goods statistics at detailed level is impacted by estimates for non-collected data.

      • Estimates for missing intra-EU trade – In order to reduce the statistical burden on businesses, intra-EU trade data are collected only from the biggest intra-EU traders. Only traders whose annual intra-EU trade exceeds a certain threshold have to submit Intrastat declarations. This means that the Intrastat data collection does not cover 100 % of the intra-EU trade. However the EU legislation requires complete coverage, which means that the loss caused by the thresholds and by non-response from non-exempted traders must be compensated with estimates.
      • Estimates for missing extra-EU trade – Theoretically, the problem of late or non-response should not exist for extra-EU trade data as Extrastat, the data collection system, is based on customs declarations. Nevertheless, estimates may be still necessary to compensate for delayed or incomplete customs records. It should also be noted that, for simplification purposes, the reporting countries are allowed to compile less detailed information for transactions below the statistical threshold of EUR 1 000 and 1 000 kilograms.
      • Estimates for non-collected statistical value – In intra-EU trade, only the invoice value — the amount agreed on the sales agreement — is systematically collected from the providers of statistical information (PSIs). When not provided by the PSIs, the statistical value shall be estimated by the National Statistical Authority. Note that, in extra-EU trade, the statistical value is based on the value determined for customs purposes; therefore, there is generally no need to estimate it.
      • Estimates for non-collected net mass – Under the legal provisions on intra-EU trade statistics, where there is a supplementary unit laid down for a specific CN product code (e.g. litres, m², pieces), it is not mandatory to request the specification of net mass from the PSIs. However the net mass shall be transmitted to Eurostat whatever the CN8 code. It should be so estimated by the National Statistical Authorities if not collected.
      13. Accuracy Top
      13.1. Accuracy – overall
      13.2. Sampling error
      13.3. Non-sampling error

      According to the EU legislation, Member States shall provide Eurostat with monthly aggregated data within 40 calendar days after the reference month.

      Member States shall provide Eurostat with monthly detailed data within 40 calendar days after the reference month for extra-EU trade and within 70 calendar days after the reference month for intra-EU trade.

      First results (including estimates) on Euro area and EU trade balances are published on line around 46 days after the reference month in the Euro-indicators news release on international trade in goods.

      The latest supplied detailed data (new reference periods and revisions) are published at the date of the monthly news release. Long-term and short-term indicators are updated at the same date.

      Thanks to well-established data collection and compilation procedures, the punctuality of data transmissions to Eurostat is very good. Issues are very rare and generally minor in terms of delay.

      14. Timeliness and punctuality Top
      14.1. Timeliness
      14.2. Punctuality

      European figures versus national figures

      EU legislation serves as a basis for compiling the intra- and extra-EU trade statistics published by Eurostat. However, European statistics, which cover the EU as a whole, and the statistics published by the Member States, are not always directly comparable. Member States may apply a different concept at national level but they have to provide Eurostat with harmonised data according to the Community concept. The most common differences between the Community concept and the national concepts are as follows:

      • Use of the general trade system at national level while the Community statistics are compiled according to the special trade system;
      • Exclusion from national statistics of ‘quasi-transit’, which means of
        • goods imported from a non-EU country, cleared through customs and immediately dispatched to another Member State (the Member State of final destination); or
        • goods imported from another Member State (the Member State of actual export), cleared through customs and immediately dispatched to a non-EU country.

      The customs formalities distinguish between simple transit, which is not recorded in Community statistics, and quasi-transit.

      • Inclusion of repairs in national statistics — these are excluded from the scope of Community statistics from 2006; and
      • Country of origin vs. Member State of consignment — for Community statistics for intra-EU imports, the partner country is the Member State of consignment but for national statistics it may be the country of origin.

      Asymmetries in intra-EU trade statistics

      In theory, intra-EU trade statistics should be less affected by asymmetries than extra-EU trade statistics as issued from more harmonised rules. Exports from Member State A to Member State B, as reported by A, should be almost equal to imports into B from A, as reported by B. Due to a different valuation principle (CIF > FOB), imports should be slightly higher than exports.

      However, since the Intrastat system came into operation, bilateral comparisons have revealed major and persistent discrepancies in the intra-EU trade statistics. Therefore, comparisons based on intra-EU trade statistics must be handled with caution and should take these into account. The main reasons for the discrepancies are known and are partly the same as in the case of extra-EU trade. There are also factors that are specific to intra-EU trade, such as estimates for non-collected data.

      Asymmetries in extra-EU trade statistics

      There are two main approaches for measuring international trade in goods: the general trade system and the special trade system. EU ITGS use the latter, which means that goods from a non-EU country that are received into customs warehouses are not recorded unless they subsequently go into free circulation in the Member State of receipt (or are placed under the customs procedures for inward processing). Similarly, outgoing goods from customs warehouses are not recorded as extra-EU exports. The general trade system, which is used by most of the EU’s main partner countries, is broader, including all goods entering or leaving the country.

      Since intra-EU trade statistics are not directly linked to customs procedures, they are not compiled on a general or special trade basis.

      Comparing extra-EU trade statistics with the figures published by non-EU countries for the same trade flows inevitably highlights some discrepancies. Besides the trade system and errors such as product or partner misclassification, the most common reasons for asymmetries are:

      • Methodological differences: trade coverage (e.g. data collection thresholds, treatment of specific goods or movements of goods), definition of partner country (e.g. country of re-export vs. country of origin), definition of statistical territory, different valuation principles (e.g. FOB valuation for exports and CIF valuation for imports);
      • Time lag: the same operation is recorded for a different reference period;
      • Statistical confidentiality: the goods movement is made confidential by one of the partners;
      • Different practices in the treatment of revisions; and
      • Problems of currency conversion.

      Changes in the product nomenclature

      A particular issue of comparability over time concerns the product classification used for trade in goods detailed data. The most detailed data are collected and published by eight-digit codes of the Combined Nomenclature (CN). Some changes are made to the CN every year. Eurostat maintains conversion tables between successive versions of the CN in order to improve comparison over time.

      15. Coherence and comparability Top
      15.1. Comparability – geographical
      15.2. Comparability – over time
      Year Creations Deletions Total Net change CN Codes
      2020 54 104 158 -50 9 483
      2020 9 9 18 +0 9 533
      2020 18 13 31 +5 9 533
      2020 687 573 1 260 +114 9 528
      2020 55 27 82 +28 9 414
      2020 21 14 35 +7 9 386
      2020 43 40 83 +3 9 379
      2020 35 42 77 -7 9 376
      2020 907 818 1 725 +89 9 383
      2020 132 281 413 -149 9 294
      2020 180 306 486 -126 9 443
      2009 127 257 384 -130 9 569
      2008 75 96 171 -21 9 699
      2007 917 1 039 1 956 -122 9 720
      2006 486 740 1 226 -254 9 842
      2005 97 175 272 -78 10 096
      2004 273 503 776 -230 10 174
      2003 19 15 34 +4 10 404
      2002 780 654 1 434 +126 10 400
      2001 50 90 140 -40 10 274

      Methodological changes

      The most important methodological changes or other events affecting ITGS in the past years are listed in the table below.

      For intra-EU imports, minimum coverage from collected data reduced from 95 % to 93 % of total trade value

      Type of trade Event
      2020 Intra- and extra-EU Change in the definition of intra- and extra-EU trade due to the United Kingdom withdrawal from the European Union from 31 January 2020.
      2020 Intra-EU
      2020 Intra- and extra-EU Change in the definition of intra- and extra-EU trade due to Croatia’s EU accession on 1 July 2020
      2020 Intra- and extra-EU Combined Nomenclature impacted by the revision of the Harmonised System
      2020 Intra- and extra-EU Introduction of the concept of change in economic ownership to record the trade in ships and aircraft and to determine the partner country allocation for deliveries to ships and aircraft and sea products (based on the economic ownership of the ships/aircraft)
      Intra- and extra-EU Reporting Member State and partner country for goods delivered to and from offshore installations determined by the exclusive rights of a country to exploit seabed or subsoil of the area (exclusive economic zone) where the offshore installation is established
      Intra-EU Estimates for non-collected net mass mandatory
      2009 Intra-EU For intra-EU imports, minimum coverage from collected data reduced from 97 % % to 95 % % of total trade value
      2007 Intra- and extra-EU Change in the definition of intra- and extra-EU trade due to EU enlargement (accession of Bulgaria and Romania on 1 January 2007)
      Intra- and extra-EU Combined Nomenclature impacted by the revision of the Harmonised System
      2006 Extra-EU Repairs excluded from the scope of extra-EU trade
      Intra-EU Collection of net mass in Intrastat no longer mandatory if a supplementary quantity is collected
      2005 Intra-EU Repairs excluded from the scope of intra-EU trade
      Intra-EU Collection of net mass in Intrastat no longer mandatory for a specific list of CN8 codes for which a supplementary quantity is collected
      2004 Intra- and extra-EU Change in the definition of intra- and extra-EU trade due to EU enlargement (accession of Czechia, Estonia, Cyprus, Latvia, Lithuania, Hungary, Malta, Poland, Slovenia and Slovakia on 1 July 2004)
      15.3. Coherence – cross domain

      Apart from the ITGS, information on trade flows can be found in national accounts, business statistics and balance of payments data. These are compiled and produced according to the recommendations (sources and methods) of various international organisations, e.g. Eurostat, International Monetary Fund, United Nations. The table below gives an overall idea of the main differences between these sources.

      International Trade Statistics National Accounts Balance of Payments Business Statistics
      Concepts & Definitions Community concept and definitions Aggregation of national statistics based on ESA 2020 Aggregation of national statistics based upon IMF Balance of Payments Manual (Sixth edition) (BPM6). It implies some methodological discrepancies (FOB/FOB, difference of coverage). BoP statistics in Member States are most of the time derived from Member States’ ITGS. BoP statistics sent to Eurostat are compiled according to the Community concept. Statistics are based on activity sector
      Statistical unit/ object/ population Cross-border movement of goods International transaction with change of ownership Enterprise, local unit
      Classifications (nomenclature) Combined Nomenclature (CN) Institutional sectors IMF classification NACE
      Geographical breakdown Detailed geographical breakdown Intra-EU, Extra-EU, World Detailed geographical breakdown All partners
      Reference period Monthly Annual Quarterly Annual
      Correction methods National corrections National corrections National corrections National corrections
      15.4. Coherence – internal

      A key feature of the EU ITGS is their coherence. Aggregated data are constructed from detailed data across Member States and product classifications with the help of official correspondence tables. This ensures internal coherence. In addition, in order to maintain coherence, Eurostat calculates derived indicators such as unit value indices or seasonally adjusted series from the detailed data provided by Member States.

      Performance and cost

      In order to improve performance and reduce the costs of data collection and processing, the use of IT tools in data collection has been identified as a priority. Consequently, the proportion of paper declarations has decreased over time. 99% of the total intra-EU trade and 100% of the extra-EU trade are collected electronically. Paper declarations are no longer used to collect intra-EU detailed data in half of the EU Member States. Also several measures have been taken to develop and promote common tools for data validation.

      Burden assessment

      Intrastat is considered to be the largest business survey in the EU. In 2020 it was estimated that there were around 3.7 million European businesses involved in trade in goods between the Member States, out of which only about 13.1 % – around 485 000 – were liable to Intrastat reporting. Out of these 485 000 reporting businesses, 207 000 (43 %) reported only imports, 129 000 (27 %) only exports and 150 000 (31 %) reported both flows.

      From the beginning of Intrastat, it became clear that the reporting burden imposed by this system on businesses was quite heavy. The Intrastat system has so undergone a number of changes and amendments of legislation in its 25-year history. These revisions have however not changed its basic characteristics but have rather enabled Member States to exempt more of their smallest businesses from Intrastat reporting obligations without making too drastic compromises in quality. While the objective of these revisions has always been clear, there has been recurring discussion on how the Intrastat system should be further simplified. Two alternative approaches were often put forward: raising the exemption thresholds and a single flow system.

      In November 2020, the European Council called upon the European Statistical System (ESS) to take effective measures ensuring a substantial reduction of the response burden by redeveloping Intrastat, while maintaining at the same time, a sound level of quality. In response to this call, the ESS adopted an innovative statistical approach consisting in exchanging micro-data on intra-EU exports between the EU Member States allowing them to use those mirror data for the compiling of their own intra-EU imports statistics. Such an approach follows the principle that data collected and available within the ESS need not to be collected more than once. Thus, each trade transaction collected in one Member State may serve as a data source for two Member States: first, for compiling the intra-EU exports of the exporting Member State and, second, for compiling and/or verifying the intra-EU imports of the partner Member State. The modernised Intrastat system will be implemented on the basis of new legal provisions laid down by the Framework regulation integrating business statistics (FRIBS). The FRIBS legislation is currently foreseen to become applicable for the modernised Intrastat system starting from 1 January 2021.

      16. Cost and Burden Top

      International trade in goods statistics, like many published statistics, must balance the need for timely information with the need for accuracy. Inevitably, the detailed data sent for a given month are subject to the possibility of later revision as a consequence of errors, omissions or — particularly with the Intrastat system — late declarations by the providers of the statistical information.

      Data are revised frequently according to national needs and practices. However, it is recommended that the countries provide Eurostat with final detailed data at the latest by October following the reference year. At that time data become ‘final’ and should not be revised further except in exceptional and well-justified cases.

      When monthly results already transmitted to Eurostat are subject to revision at national level, revised results must be transmitted no later than the month following their availability.

      Metadata reports on revisions to trade in goods data are published monthly measuring the revision both in terms of the value change and the percentage change. Both are useful complementary measures for different users of trade in goods data. Measuring the percentage change can inform users on the effect of changes on individual Member States data. Measuring the value change allows users to be informed on the impact of the changes in trade figures from both large and small economies on EU and EA aggregate figures.

      The definition a ‘large’ revision will depend very much on the data user and how they use the data. To aid both revisions monitoring and user understanding of the impact of revisions, Eurostat and Member States have agreed on thresholds to define different levels of revision and these definitions are included with the published metadata reports mentioned above. Thresholds have been defined for both changes between subsequent data publication and between when the data were first published and the most recently available data.

      The metadata reports (revisions between subsequent data deliveries and revisions between first and last data deliveries) can be found on the Focus on Comext page of the International trade in goods section on Eurostat website.

      17. Data revision Top
      17.1. Data revision – policy
      17.2. Data revision – practice

      Extrastat and Intrastat: two data collection systems

      Traditionally ITGS are based on the data collected by customs authorities on trade transactions between countries. Customs declarations are used for statistical purposes as the basic data source which provides detailed information on exports and imports of goods with a geographical breakdown.

      The first piece of EU legislation on ITGS was adopted in 1975; it provided general guidelines on data collection and obliged Member States to send their data to Eurostat. The advent of the Single Market on 1 January 1993, with its removal of customs formalities between Member States and subsequent loss of trade statistics data sources, required the establishment of a new data collection system: Intrastat. Since then ITGS are based on two data collection systems: Extrastat and Intrastat.

      • Extrastat data on trade in goods with non-EU countries are collected by customs authorities and are based on the records of trade transactions in customs declarations.
      • Intrastat data are directly collected from intra-EU trade operators once a month. Alternative data sources may be used for some specific goods and movements like for among with ships, aircraft, gas and electricity.

      Extra-EU trade statistics are collected via customs declarations. Trade operators fulfilling their reporting obligations to the Customs Authority in a Member State are providing statistical data on the same occasion. The statistical information depends, therefore, very much on customs practices, definitions and policies and only few dimensions are collected purely for statistical purposes. The dependence on customs procedures entails to a high quality and nearly total coverage of data on trade with non-EU countries.

      Intra-EU trade statistics are collected directly from trade operators as a consequence of the abolishment of customs formalities at the borders between the EU Member States. Less statistical data elements are collected compared to extra-EU trade. In addition, private individual and small- and medium-scale traders are excluded from any statistical reporting obligations. The providers of the statistical information (PSI) are any taxable persons in a Member State carrying out intra-EU trade and being above a certain threshold of annual trade. The National Statistical Authority use the taxable amounts of intra-EU acquisitions and deliveries provided by the National Fiscal Authority to identify the target population and ensure that the PSIs comply with their statistical obligations.

      The prime responsibility for ensuring the accuracy of international trade data rests with national authorities. Further checks are carried out by Eurostat, essentially to ensure that the transmission of the requested data has been carried out according to the requirements, that datasets are complete, error-free, and that the correctness of extreme values (outliers) is confirmed.

      EU and euro area aggregates are calculated on the basis of the harmonised figures provided by the Member States according to the Community concept.

      Seasonally and working days adjusted figures – As with most economic data, interpretation of monthly trade in goods data is made more difficult by regular seasonal fluctuations. For instance, trade in many agricultural products is highly seasonal and month to month fluctuations are often dominated by these seasonal factors. Monthly data are also affected by the varying lengths of months (and in particular the number of working days they contain) and the effects of public holidays whose dates may change from year to year: Easter is the prime example. One partial solution to the effects of seasonality on comparisons over time is to make comparisons only with the same month of the previous year but this is not a completely satisfactory procedure since it cannot provide a proper measure of the fluctuations through a year. To deal with this problem, Eurostat adjusts the trade in goods data provided by Member States for seasonal components and working days. Raw data are processed by JDemetra+, a tool developed by Eurostat. JDemetra+ carries out corrections for working days and applies a method of seasonal adjustment known as SEATS. The parameters and the models are revised once a year. ARIMA and regression coefficients are updated for each monthly release. Under special circumstances, such as a sudden economic slowdown, seasonal factors may be frozen until changes can be properly incorporated into the model. A full technical discussion of the methods available and the criteria for the choice is available on the Eurostat web page dedicated to seasonally adjusted data.

      Compilation of indices – Data provided by Member States are in current prices, which are prices relevant to the reference period concerned. For several analyses it is satisfactory to work in those values and, if needed, to convert the series of values into an index form following a simple arithmetic operation. However, the development over time of the value of trade flows is determined by both the quantities sold and price variations. For a number of analytical purposes it is then necessary to distinguish between these two elements and in particular to measure movements in the volume of trade estimated in the constant prices of some previous base years. It is therefore desirable to have some measure of how price movements in international trade have developed. Information on values and related quantities is taken from ITGS to estimate a set of deflators which are then used to calculate unit value indices and derive estimates of volumes. Intra‑ and extra‑EU trade statistics are used at their most detailed level — eight-digit CN subheadings by partner country — for calculating indices. The fluctuations in ‘unit values’, which are derived from current price values divided by quantities for each flow, are used as indicators of price variations. Although the calculation system uses weights which are changed annually, for the convenience of users the published indices are based on reference years that are normally changed every five years. The current reference year for the unit value and volume indices is 2020. Data are available monthly as an index (2020=100) showing the percentage change from both the previous month and the same month of the previous year. Unit value and volume indices are calculated for the various aggregates. Volume indices are also adjusted for working days and seasonal variations. Unit value indices are available in euro, national currency for Member States not belonging to the euro area and US dollars. The first compilation step consists in compiling unit-value indices from trade values all expressed in euros. The indices in euro are then converted in national currencies and US dollars.

      Go for Quality and Quantity in Trading

      The concepts of quality and property. In his practical activity and search for knowledge man selects from the multiplicity of surrounding phenomena “something” on which he concentrates. Philosophers call this an object. It may be a thing, a phenomenon, an event, a mental condition, a thought, a feeling, an intention and so on. An object can be singled out from the background of reality because it, as a fragment of existence, is delimited from everything else. Its limits may be spatial, temporal, quantitative or qualitative. If, for example, we are confronted with a plot of land of, say 20 sq m, these are quantitative limits. But this plot may also be a meadow as opposed to a forest, and this is its qualitative limit. Quality determines the kind of existence of an object.

      The category of quality is an integral definition of the functional unity of an object’s essential properties, its internal and external definiteness, its relative stability, its distinction from and resemblance to other objects. Quality is an existing definiteness, as distinct from other definitenesses. It is the expression of the stable unity of an object’s elements and structure. Quality is at the same time the limits of an object within which it exists as that object and no other. This means that quality is inseparable from the object. In losing its quality any object ceases to exist as such.

      The quality of the object is revealed in the sum-total of its properties. The unity of properties is, in fact, quality. Thus an overall definition of the quality of a thing or phenomenon is a definition of the thing as a system with a certain structure. The nature of a thing is revealed in its properties, which constitute the mode of the object’s relationship with other things. It is thanks to their properties that things interact. A thing has the property of evoking one or another action in something else and of manifesting itself in its own way in relation to other things.

      A property is the way in which a certain aspect of the quality of an object manifests itself in relation to other objects with which it interacts. A property is that by means of which something manifests its existence in relation to something else. To speak of the properties of a given thing out of connection with other things is to say nothing about these properties. A property of an object thus consists in its being able to produce this or that action in another object and reveal itself in its own way in this action. Moreover, the mode of its manifestation in acting on another object substantially depends on the properties or condition of the latter; a spark falling on a gunpowder store is far more dangerous than the same spark falling on damp ground, where it dies without a trace.

      Properties not only manifest themselves, they may also change or even take shape in these relations. Just as matter cannot be reduced to the sum-total of its properties, so no object dissolves in its properties: it is their vehicle, their substratum. A thing should not be regarded, as it sometimes is, as a kind of hook on which its properties should hang. n object glows, as it were, with various aspects of its properties, depending on the context. For example, a person is seen in different qualitative lights by the doctor, lawyer, writer, sociologist, anatomist or psychiatrist. The properties of an object are conditioned by its structure, the internal and external interactions of its elements. Since an object’s interactions with other objects are infinite, the properties of the object are also infinite.

      Every property is relative. In relation to wood steel is hard, but it is soft in relation to diamonds. Properties may be universal or specific, essential or inessential, necessary or accidental, internal or external, natural or artificial, and so on. The concept of quality is often used in the sense of an essential property. The higher the level of organisation of matter, the greater the number of qualities it possesses.

      Quantity. Every group of homogeneous objects is a set. If it is finite it can be counted. We may have, for example, a herd of 100 cows. To be able to consider each cow as “one”, we must ignore all the qualitative peculiarities of these animals and see them as something homogeneous. One and the same number “100” is the quantitative characteristic of any set of 100 objects—cows, sheep, diamonds or whatever. Consequently, any quantity is a set if it can be counted, or a dimension if it can be measured.

      Quantity expresses the external, formal relation of objects, their parts, their properties, their connections, number, dimension, set, element (unit), individual, class, degree of manifestation of this or that property.

      In order to establish the quantitative aspect of an object we compare its constituent elements— spatial measurements, rate of change, degree of development, using a certain standard as a unit of computation or measurement. The more complex the phenomenon, the more difficult it is to study it by quantitative methods. For example, it is not so simple to count or measure phenomena in the sphere of morality, politics, aesthetic perception of the world, religion and so on. So it is no accident that the process of getting to know the real world both historically and logically takes place in such a way that knowledge of quality precedes knowledge of quantitative relations. Knowledge of the quantitative aspect of a system is a step towards deepening our knowledge of this system. Before a person can count, for instance, he must know what he is counting. Science proceeds from general qualitative estimates and descriptions of phenomena to exact mathematical laws of quantity.

      The basis of quantitative thinking is the objective discrete ness of things and processes. Quantity is expressed by number, which has two main meanings: the measure of generality of the elements when put together; the divisibility (real or putative) of an object, its properties and relations, into homogeneous elements relatively independent of its quality. For example, we form the number 5 in the process of counting, thus turning this five into a simple quantity. Five people are not simply a formal unit of five human beings, they are not something singular but a specifically divisible unity of five elements. Any number is a relatively independent, integral assembly of a certain set or a divisible unity of quantity. Moreover, quantity is not identical with number. One and the same quantity as a dimension—length, for example—may be expressed in different scales of measurement (metres, centimetres) and therefore in different numbers.

      Besides discreteness, which serves as the real premise for the concepts of quantity and number, it is important for an understanding of the objective basis of mathematics to realise that discrete things, their properties and relations, are united in sets.

      Measure. For centuries people have said, “everything has its measure”. The reasonable person has a sense of measure in everything: behaviour, dress, eating, taste, and so on. Loss of the sense of measure, of proportion, is a bad sign and takes its revenge by putting the offender in a comic and sometimes tragic situation. Not for nothing do people dislike exaggeration, the superfluous. The perfect is something that has no defects of proportion. The imperfect can never be the measure of anything. Measure is the quantitative limit of a given quality. Quality cannot be more or less than that limit. The whole history of philosophy from ancient times to the present day is permeated with the idea of measure.

      Measure is thought of as a perfect whole, a unity of quantity and quality. The concept of measure is used in various senses: as a unit of measurement, volume, as proportion of the parts to the whole, as the limit of the permissible, the legitimate, as law, as unity of quantity and quality, as their perfect wholeness, integration (a molecule of ordinary water must have two atoms of hydrogen and one of oxygen), and as a self-developing system. Measure is also a certain stage in the historical development of something.

      Measure expresses unity of quality and quantity. For example, the atoms of various chemical elements are only distinguished from each other by the fact that their nuclei contain various quantities of protons. If we change the number of protons in the nucleus, we change that element into another. Every colour has its wavelength and corresponding frequency of oscillation. Every drug has its measure: its good or bad effect depends not only on its quality but also its quantity. One and the same chemical substance in various doses may stimulate growth or inhibit it. Measure is proportion. It may embrace certain normative features: in morality a knowledge of measure in everything, moderation, modesty; in aesthetics, symmetry, proportion. Gracefulness, for example, is freely organised harmony, proportion in motion. Rhythm, melody and harmony in music are based on the strict observation of measure. Measure is the zone in whose limits a given quality may be modified or varied by virtue of changes in the quantity of certain inessential properties while retaining its essential ones.

      The transformation of quantity into quality and vice versa . The path of development in nature, society and consciousness is not a direct line, but a zigzag. Every turn signifies the appearance of new laws that hold good for that particular leg. The limits of these laws are by no means always clearly fixed, sometimes they are conditional. Who can determine the exact limits showing where childhood ends and adolescence begins, where youth begins and when it enters the quality known as “young person”?

      The transition from an old to a new quality involves a leap—a break in the gradualness of development. The process of development combines a unity of the continuous and the discontinuous. Continuity in the development of a system indicates relative stability, its qualitative definiteness. Discontinuity in a system’s development indicates its transition to a new quality. Figuratively, one may compare this process with the action of a spring and cogwheels in a clock: the spring operates continuously, but thanks to the regulating effect of the cogwheels the energy transmitted by the spring is converted into rhythmical work. The world is not a steady stream, nor is it a stagnant pond, it is a combination of relatively stable and changing systems. Systems develop rhythmically and every stroke of the “clock of the universe” signifies the birth of the new. This is where the law of the transformation of quantity into quality and vice versa reveals itself. This law has an objective and universal character admitting no exceptions.

      Quantitative changes show themselves in various ways: as changes in the number of elements of an object, the order of their connection, their spatial dimensions, their velocity, degree of development, and so on. In short, any change in quantity amounts to a change in the elements of a system. The degree of difference between an old and a new quality depends on what quantitative changes have taken place in them. For example, water is heated (increase in the speed of its molecules), but it remains water although it is much hotter or perhaps very hot. Only some of its properties have changed. This change is gradual or phased, a movement from one state to another. But then comes the critical boiling point. The agitated water molecules start bubbling to the surface and leave it in the form of steam. From its liquid state water passes into steam. Basically the appearance of a new property means the appearance of a new object with new laws of existence, with a new measure possessing a different quantitative definiteness. Moreover, the degree of qualitative change may differ. It may confine itself to the level of the given form of motion or it may go beyond this level. Thus measure expresses a unity of quality and quantity in relation to objects for which simple transformation is characteristic, that is to say, change within the limits of the given form of motion of matter, as, for example, in the case of the transformation of water into steam or elementary particles into each other. But measure also expresses the limits of transition from one level of a system’s organisation to another, for example, the emergence of the animate from the inanimate. On the threshold of the new, measure grows old and this is the sign of the necessity for transition to another measure.

      The process of radical change of quality, the breakup of the old and the birth of the new is what we mean by a “leap”.

      A leap is a spontaneous discharge of mounting tension, a resolving of contradictions. The passage of a phenomenon from one qualitative state to another is essentially contradictory, it is a unity of destruction and renewal, existence and non-existence, negation and affirmation.

      A leap includes the moment of cancellation of the previous phenomenon by the new. The transformation of one phenomenon into another is a unity, an interaction of quantitative and qualitative changes, which pass through a number of intermediate phases. Moreover, different phases of change in a given quality signify changes in the degree of the given quality, in other words a quantitative change.

      The big leaps in the development of objective reality were the formation of stars, particularly the solar system and its planets, the origin of life on earth, the origin of man and his consciousness, the formation of new species of animals and plants and the emergence and replacement of socio-economic formations in the history of human society, the great landmarks in the development of science, art, and so on. The social revolution is a special kind of leap, characteristic of social development.

      We sometimes use the concept of “evolution” to denote continuous changes, that is to say, gradual changes in quantity and changes of certain properties within the framework of a given quality. However, in the wider sense this term is used to mean development in general, for example, in relation to cosmogony (evolution of stars), and to biology, the evolution of the vegetable and animal worlds.

      As a rule, two basic forms of leap take place in the process of development. A leap may be momentary in time, that is to say, a sharp transition from one quality to another, and it may also be a process of a certain duration. A leap may last for a billionth of a second, as in microprocesses, for example, for billions of years, as in cosmic processes, and hundreds of thousands of years, as in the formation of animal species. A distinctive feature of the leap is the fact that the emergence of a new quality puts an end to the former pattern of quantitative changes. Leaps of the first kind have sharply defined frontiers, great intensity, and high velocity in the process of transition; they signify an all-embracing reorganisation of the whole system at a single stroke. Such transformations are to be found in the atomic explosion or the political revolution in society. But political and particularly social revolutions rarely take place in the form of a one-off destruction of the old and construction of the new. The transition may not necessarily be clearly expressed, there may be intermediate stages combining the old and the new.

      Assuming the nature of quality as a system of properties, one should distinguish individual or particular leaps associated with the appearance of new particular properties, and general leaps associated with the transformation of the whole system of properties, that is, the quality as a whole.

      Changes in quantity and quality are interconnected, a change in quality also involves quantitative change. This is generally expressed in the fact that as the level of organisation of matter rises the rate of its development accelerates. Every level of organisation of matter has its specific laws of quantity. A new, better adapted animal species yields a progeny whose greater power of survival guarantees wider opportunities for it to spread.

      The law of the transformation of quantitative into qualitative changes and vice versa places a number of methodological demands on cognition. It allows and requires us to study an object from the standpoint of quantity as well as quality. Study of the quantitative aspect of things has enormous significance in science, technology, and everyday practice. Access to the deep-going problems of science, including biology and social research, demands extremely refined mathematical methods.

      Until quite recently, biology, physiology, linguistics, psychology, and many other sciences made little or no use of mathematics, but now they are forging ahead largely due to the application of mathematical methods. Cybernetics has opened up particularly tempting opportunities for their use in modern science. The degree to which mathematics may be used in the study of this or that science is determined by the degree to which quantity may be abstracted from quality. In every specific case this abstraction has its limits.

      In scientific research the application of mathematical methods always presupposes a profound knowledge of the subject. Scientists need mathematics not only for computations and calculations—although, of course, this role of mathematics in science is highly important—but as an effective heuristic technique, and also for developing the rigour and discipline of logical thinking. The followers of Pythagoras assumed that universal order was based on the harmony of numbers. Later thinkers suggested that numbers indicate how the world is governed. The reasonable approach is to make sure that quantitative definitions do not over shadow the qualitative definiteness of facts and laws. We can fully understand the essence of an object only by considering both quantity and quality in their unity, their interconnection.

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      18. Statistical processing Top
      18.1. Source data
      18.2. Frequency of data collection
      18.3. Data collection
      18.4. Data validation
      18.5. Data compilation