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). The current version of the ANBERD database presents OECD countries' and selected non-member economies' business expenditure on R&D since 1987, broken down across 100 manufacturing and service industry groups. The reported data follow the International Standard Industrial Classification, Revision 4 (ISIC Rev. 4) and are expressed in national currencies as well as in US dollars at Purchasing Power Parity (PPP), both at current and constant prices.   Main activity and industry orientation: The 2015 Frascati Manual practice is to report BERD on an enterprise basis. The main economic activity of an enterprise is usually defined as that which accounts for most of its economic outputs; this may be identified directly from sales or indirectly proxied (such as by numbers of personnel devoted to different activities). This determines the industry in which the enterprise, and any BERD it carries out, is classified. As such, all BERD of a diversified enterprise (i.e. one with multiple lines of business) is allocated to the same industry, that of its main activity. This enables, as far as possible, the alignment and compatability of BERD data with other economic statistics (e.g. value added broken down by industry). In addition, the Frascati Manual also recommends reporting BERD by industry orientation, whereby the statistical unit’s R&D is distributed across the various lines of business to which it relates. In a few countries, hybrid approaches are followed and reported as main activity data. As an example, some countries primarily follow the main activity approach but redistribute the R&D of large diversified firms across the economic activities to which it relates. This can affect interpretation of the data and resulting statistics. There are also important differences between countries in the treatment of R&D undertaken by firms in the service sector but closely associated (though not necessarily contractually) with manufacturing firms. Industrial research institutes, largely funded by the manufacturing industries they serve, are the most frequent examples. With the implementation of the 2015 Frascati Manual, such hybrid data will be phased out in favour of a strict main activity approach. Countries still reporting hybrid data are flagged in the ANBERD country notes.

STAN Bilateral Trade Database by Industry and End-use category (BTDIxE) provides values of imports and exports (as well as re-imports and re-exports) of goods broken down by industrial sectors and by end-use categories. BTDIxE was designed to extend the old BTD database which provided bilateral trade in goods by industry only.  BTDIxE allows, for example, insights into the patterns of trade in intermediate goods between countries to track global production networks and supply chains, and it helps to address policy issues such as trade in value added and trade in tasks.  The database presents estimates of bilateral flows of goods from 1990 to the latest available year, i.e. 2018; the latest year shown is subject to the availability of underlying product-based annual trade statistics.  Reporters are the OECD member countries and a large number of non-OECD economies, including the BRIICS: Brazil, the Russian Federation, India, Indonesia, People's Republic of China and South Africa; other selected G20 and Asian economies; and major African and Latin American nations.  It should be noted that starting from mid-2012, the OECD and the United Nations agreed to centralise the data collection and processing procedures within UNSD Comtrade.  The list of partners covers the OECD countries, more than a hundred of non-member economies as well as the partners "World", "Rest of the World" and "Unspecified". The partner "Total foreign trade" corresponds to the flows with partner "World" excluding intra-country flows. Trade flows are divided into economic activities based on the Revision 4 of ISIC and nine end-use categories including capital goods, intermediate goods and household consumption.

Data are provided in million national currency (for the euro zone, pre-EMU euro or EUR), million current PPP USD and million constant USD (2000 prices and PPPs). Variables collected This table presents research and development (R&D) expenditure statistics performed in the business enterprise sector by industry according to the International Standard Industrial Classification (ISIC) revision 3.1. and by type of costs (current expenditure, capital expenditure). Data at the industry level are presented beginning 1987, year when most of the countries converted from ISIC rev.2 to the current ISIC rev. 3 classification. This breakdown between industries is, in principle, made at the enterprise level, although some countries are able to break down R&D data for multi product enterprises between their main lines of business. National statistical regulations prevent publication of results where there are very few firms in the given category, hence the many gaps in the tables. Depending on the country, R&D institutes serving enterprises are either classified with the industry concerned, or grouped under “Research and Development” (ISIC rev.3.1, Division 73). When these R&D institutes are classified with the industry served, the evaluation of R&D in these industries is more complete and more comparable between countries for the industries concerned. This results, however, in an underestimation of the percentage of BERD performed by the service sector as compared with other countries. The Frascati Manual recommendation concerning data on R&D by industry is to report BERD on an enterprise basis (see FM section 3.4). When this is interpreted strictly, all the BERD of a diversified enterprise will be allocated to the industrial class of its principal activity. In circumstances where a few large firms dominate R&D spending in several areas, this can and does lead to underestimates of R&D associated with the secondary activities of the firms. Overall, R&D is therefore overestimated for some industries and underestimated for others. However, not all countries follow a strict enterprise basis for allocating R&D expenditures to industrial classes. Some countries make a disaggregation of the R&D of their largest, diversified firms into a number of different activities. In other countries, the enterprise approach has been abandoned and data are reported on a product field basis. This is why two classification criteria for BERD by industry are included in the table “BERD by industry” (see the variable CLASSIFICATION CRITERIA: Main activity or Product field) depending on which approach is more closely followed by each country (only a few countries currently collect these data both ways and are therefore included according to both criteria). However, this table “BERD by industry and type of costs” and the preceding one “BERD by industry and source of funds” present data for only one of the criteria, depending on the country.

Data are provided in million national currency (for the euro zone, pre-EMU euro or EUR), million current PPP USD and million constant USD (2005 prices and PPPs). Variables collected This table presents research and development (R&D) expenditure statistics performed in the business enterprise sector by industry according to the International Standard Industrial Classification (ISIC) revision 3.1. and by source of funds (business enterprise, government, other national funds, and funds from abroad). Data at the industry level are presented beginning 1987, year when most of the countries converted from ISIC rev.2 to the current ISIC rev. 3 classification. This breakdown between industries is, in principle, made at the enterprise level, although some countries are able to break down R&D data for multi product enterprises between their main lines of business. National statistical regulations prevent publication of results where there are very few firms in the given category, hence the many gaps in the tables. Depending on the country, R&D institutes serving enterprises are either classified with the industry concerned, or grouped under “Research and Development” (ISIC rev.3.1, Division 73). When these R&D institutes are classified with the industry served, the evaluation of R&D in these industries is more complete and more comparable between countries for the industries concerned. This results, however, in an underestimation of the percentage of BERD performed by the service sector as compared with other countries. The Frascati Manual recommendation concerning data on R&D by industry is to report BERD on an enterprise basis (see FM section 3.4). When this is interpreted strictly, all the BERD of a diversified enterprise will be allocated to the industrial class of its principal activity. In circumstances where a few large firms dominate R&D spending in several areas, this can and does lead to underestimates of R&D associated with the secondary activities of the firms. Overall, R&D is therefore overestimated for some industries and underestimated for others. However, not all countries follow a strict enterprise basis for allocating R&D expenditures to industrial classes. Some countries make a disaggregation of the R&D of their largest, diversified firms into a number of different activities. In other countries, the enterprise approach has been abandoned and data are reported on a product field basis. This is why two classification criteria for BERD by industry are included in the table “BERD by industry” (see the variable CLASSIFICATION CRITERIA: Main activity or Product field) depending on which approach is more closely followed by each country (only a few countries currently collect these data both ways and are therefore included according to both criteria). However, this table “BERD by industry and source of funds” and the one that follows, “BERD by industry and type of costs” present data for only one of the criteria, depending on the country.

Data are provided in million national currency (for the euro zone, pre-EMU euro or EUR), million current PPP USD and million constant USD (2010 prices and PPPs). Variables collected This table presents research and development (R&D) expenditure statistics performed in the business enterprise sector. Data include total business enterprise intramural expenditure on R&D by size class and source of funds.

This table presents research and development (R&D) statistics on personnel in the business enterprise sector. Measured in full-time equivalent are the number of total R&D personnel and researchers in the business enterprise sector by industry according to the International Standard Industrial Classification (ISIC) revision 3.1. Data at the industry level are presented beginning 1987, year when most of the countries converted from ISIC rev.2 to the current ISIC rev. 3 classification.

The OECD Science, Technology and Industry Outlook 2012 presents, in a series of country profiles, the main features, strengths and weaknesses of national STI systems and major recent changes in national STI policy. The statistical dimension of the country profiles has drawn on the work and empirical research conducted by the OECD on the measurement of innovation and the development of internationally comparable STI indicators for policy analysis.   

This table presents data on Government appropriations or outlays for RD (GBAORD) by socio-economic objective (SEO), using the NABS 2007 classification i.e.: Exploration and exploitation of the Earth, Environment, Exploration and exploitation of space, Transport, telecommunication and other infrastructures, Energy, Industrial production and technology, Health, Agriculture, Education, Culture, recreation, religion and mass media, Political and social systems, structures and processes, General advancement of knowledge: RD financed from General University Funds (GUF), General advancement of knowledge: RD financed from sources other than GUF, Defence. Please note that in this new NABS 2007 classification, the three socio-economic objectives -- Education, Culture, recreation, religion and mass media, and Political and social systems, structures and processes -- were previously grouped under a single objective: Social structures and relationships. At the time of this publication there is no breakdown of historical data into the three new SEOs. Another issue relating to the transition from NABS 1993 to NABS 2007 is that what was formerly Other civil research is now to be distributed among the other chapters. This distribution has not yet been done in this database. Therefore, until the countries are in a position to provide breakdown according to the NABS 2007 classification, in some cases GBAORD by SEO is greater than the sum of its chapters.

This table contains research and development (R&D) expenditure statistics on gross domestic R&D expenditure by sector of performance (business enterprise, government, higher education, private non-profit, and total intramural) and by field of science (natural sciences, engineering, medical sciences, agricultural sciences, social sciences, and humanities). Data are provided in million national currency (for the euro zone, pre-EMU euro or EUR), million current PPP USD and million constant USD (2010 prices and PPPs).

Data are provided in million national currency (for the euro zone, pre-EMU euro or EUR), million current PPP USD and million constant USD (2010 prices and PPPs). Variables collected This table presents research and development (R&D) expenditure statistics. Data include gross domestic R&D expenditure by sector of performance (business enterprise, government, higher education, private non-profit, and total intramural) and by type of costs (current expenditures: labour costs, other current costs; and capital expenditures: land and buildings, and instruments and equipment).

This database presents the 2018 edition of OECD time-series indicators of implied R&D tax subsidy rates for OECD member countries and five non-member economies (Brazil, People's Republic of China, Romania, Russian Federation, and South Africa) over the period 2000-2018, drawing on data collected in the OECD-NESTI R&D tax incentive surveys from 2007 to 2018. The 2018 edition of RDTAXSUB contains time-series estimates that are based on headline tax credit and allowance rates, by firm size and profitability scenario. Due to limited historical data availability, the estimates are not adjusted for provisions that bound the tax benefits received by firms (e.g. ceilings, thresholds). They therefore provide an upper bound for the marginal tax subsidy implied by R&D tax relief measures across countries over time. These estimates should not be confused with separate contemporary cross-sectional OECD estimates of marginal tax subsidy rates (OECD, 2018) that compute adjusted (weighted) tax credit/allowance rates for a number of countries based on available information on the proportion of eligible R&D subject to different marginal levels of relief (see 2017).The tax subsidy rate is defined as 1 minus the B-index, a measure of the before-tax income needed by a “representative” firm to break even on USD 1 of R&D outlays (Warda, 2001). As tax component of the user cost of R&D, the B-Index is is directly linked to measures of effective marginal tax rates. Measures of tax subsidy rates such as those based on the B-index provide a convenient proxy for examining the implications of tax relief provisions. These provide a synthetic representation of the generosity of a tax system from the perspective of a generic or model type of firm for the marginal unit of R&D expenditure. To provide a more accurate representation of different scenarios, B-indices are calculated for “representative” firms according to whether they can claim tax benefits against their tax liability in the reporting period (OECD, 2013). When credits or allowances are fully refundable, the B-index of a firm in such a position is identical to the profit scenario. Carry-forwards are modelled as discounted options to claim incentives in the future, assuming a constant annual probability of returning to profit of 50% and a nominal discount rate of 10%. For general and country-specific notes on the time-series estimates of implied marginal tax subsidy rates on R&D expenditures (based on the B-index), see http://www.oecd.org/sti/rd-tax-stats-bindex-notes.pdf.

This dataset presents patent statistics and indicators that are suitable for tracking innovation in environment-related technologies. They allow the assessment of countries and firms' innovation performance as well as the design of governments' environmental and innovation policies.

Patents are a key measure of innovation output, as patent indicators reflect the inventive performance of countries, regions, technologies, firms, etc. They are also used to track the level of diffusion of knowledge across technology areas, countries, sectors, firms, etc., and the level of internationalisation of innovative activities. Patent indicators can serve to measure the output of R&D, its productivity, structure and the development of a specific technology/industry. Among the few available indicators of technology output, patent indicators are probably the most frequently used. The relationship between patents as an intermediate output resulting from R&D inputs has been investigated extensively. Patents are often interpreted as an output indicator; however, they could also be viewed as an input indicator, as patents are used as a source of information by subsequent inventors. Like any other indicator, patent indicators have many advantages and disadvantages. The advantages of patent indicators are : patents have a close link to invention; patents cover a broad range of technologies on which there are sometimes few other sources of data; the contents of patent documents are a rich source of information (on the applicant, inventor, technology category, claims, etc.); and patent data are readily available from patent offices. However, patents are subject to certain drawbacks: the value distribution of patents is skewed as many patents have no industrial application (and hence are of little value to society) whereas a few are of substantial value; many inventions are not patented because they are not patentable or inventors may protect the inventions using other methods, such as secrecy, lead time, etc.; the propensity to patent differs across countries and industries; differences in patent regulations make it difficult to compare counts across countries; and changes in patent law over the years make it difficult to analyse trends over time.

This table contains figures on the shares of industrial sectors that are "controlled" by affiliates under foreign control in each country (inward investment as a percentage of national total).

This table contains figures on the activity of affiliates under foreign control and all firms by industry according to the International Standard Industrial Classification (ISIC Revision 4).

This table contains figures on the activity of affiliates under foreign control by industry according to the International Standard Industrial Classification (ISIC Revision 3).

The IPP.Stat is the statistics portal of the Innovation Policy Platform containing the main available indicators relevant to a country’s innovation performance. In addition to the traditional indicators used to monitor innovation, the range of the coverage to be found in the IPP.Stat calls for the inclusion of indicators from other domains that describe the broader national and international context in which innovation occurs. Indicators are sourced primarily from the OECD and the World Bank, as well as from other sources of comparable quality. The statistics portal is still under development.

This biannual publication provides a set of indicators that reflect the level and structure of the efforts undertaken by OECD member countries and seven non-member economies (Argentina, People's Republic of China, Romania, Russian Federation, Singapore, South Africa, Chinese Taipei) in the field of science and technology. These data include final or provisional results as well as forecasts established by government authorities. The indicators cover the resources devoted to research and development, patent families, technology balance of payments and international trade in R&D-intensive industries. Also presented are the underlying economic series used to calculate these indicators. Indicators on R&D expenditures, budgets and personnel are derived from the OECD's Research and Development Statistics (RDS) database, which is based on the data reported to OECD and Eurostat in the framework of a co-ordinated collection. The sources for the other indicators include the OECD databases on Activities of Multinational Enterprises (AMNE), on Bilateral Trade in Goods by Industry and End-use Category database (BTDIxE), on Patents and on Technological Balance of Payments (TBP). The R&D data used in this publication have been collected and presented in line with the standard OECD methodology for R&D statistics as laid out in the OECD "Frascati Manual". The 2002 edition of the manual has now been superseded by the 2015 edition. The revised guidelines and definitions are in the course of being implemented and are not expected to change the main indicators significantly although some terminology changes will occur. This edition of MSTI has been compiled in accordance with the 2002 Frascati Manual; these changes will be made in a coming edition as R&D surveys move to the new standard.   2018 values are estimated value.

National values have been computed based on regional estimates. For this reason, it is possible that in some cases these values differ from national statistics. Status:  Discontinued 

National values have been computed based on regional estimates. For this reason, it is possible that in some cases these values differ from national statistics. Status:  Discontinued 

The OECD Science, Technology and Industry Outlook reviews key trends in STI policies and performance in OECD countries and major emerging economies. It is published every two years and draws on a unique international policy survey conducted by the OECD - with more than 45 countries involved in 2014 - and the latest OECD work on STI policy analysis and measurement. Following an overview of the recent STI global landscape, key current policy issues are discussed across a series of thematic policy profiles. Country profiles report the STI performance of individual countries and the most recent national policy developments.

This table contains statistics on research and development (R&D) expenditure performed in the higher education and private non-profit sectors by field of science (natural sciences, engineering, medical sciences, agricultural sciences, social sciences, and humanities) and type of costs (current expenditures, capital expenditures).

This dataset presents patent statistics and indicators that are suitable for tracking innovation in environment-related technologies. They allow the assessment of countries and firms' innovation performance as well as the design of governments' environmental and innovation policies.

The OECD Environment Directorate, in collaboration with the Directorate for Science, Technology and Innovation, has developed patent-based innovation indicators that are suitable for tracking developments in environment-related technologies. The indicators allow the assessment of countries' and firms' innovative performance as well as the design of governments' environmental and innovation policies. The patent statistics presented here are constructed using data extracted from the Worldwide Patent Statistical Database (PATSTAT) of the European Patent Office (EPO) using algorithms developed by the OECD. Consistent with other patent statistics provided in OECD.Stat, only published applications for "patents of invention" are considered (i.e. excluding utility models, petty patents, etc.). The relevant patent documents are identified using search strategies for environment-related technologies (ENV-TECH) which were developed specifically for this purpose. They allow identifying technologies relevant to environmental management, water-related adaptation and climate change mitigation. An aggregate category labelled "selected environment-related technologies" includes all of the environmental domains presented here.

The OECD Environment Directorate, in collaboration with the Directorate for Science, Technology and Innovation, has developed patent-based innovation indicators that are suitable for tracking developments in environment-related technologies. The indicators allow the assessment of countries' and firms' innovative performance as well as the design of governments' environmental and innovation policies. The patent statistics presented here are constructed using data extracted from the Worldwide Patent Statistical Database (PATSTAT) of the European Patent Office (EPO) using algorithms developed by the OECD. Consistent with other patent statistics provided in OECD.Stat, only published applications for "patents of invention" are considered (i.e. excluding utility models, petty patents, etc.). The relevant patent documents are identified using search strategies for environment-related technologies (ENV-TECH) which were developed specifically for this purpose. They allow identifying technologies relevant to environmental management, water-related adaptation and climate change mitigation. An aggregate category labelled "selected environment-related technologies" includes all of the environmental domains presented here.

 Description The OECD's Directorate for Science, Technology and Industry has developed patent data and indicators that are suitable for statistical analysis and that can help addressing S&T policy issues. To date, the OECD Patent Database fully covers:Patent applications to the European Patent Office (EPO) (from 1978 onwards);Patents applications to the US Patent and Trademark Office (USPTO) (granted patents from 1976 onwards, patent filings as of 2001 only);Patents filed under the Patent Co-operation Treaty (PCT), at international phase, that designate the EPO (from 1978 onwards);Patents that belong to Triadic Patent Families (OECD definition): i.e. sub-set of patents all filed together at the EPO, at the Japanese Patent Office (JPO) and at the USPTO, protecting the same set of inventions. EPO and PCT patent counts are based on data received from the EPO (EPO Bibliographic database, patent published until November 2015).  Series on USPTO patents and Triadic patent families are mainly derived from EPO's Worldwide Statistical Patent Database (PATSTAT, Autumn 2015). Regional data are based on OECD, REGPAT database, February 2016. Indicators based on patent families improve the international comparability and the quality of patent's indicators (overcoming the drawbacks of traditional patent-based indicators, such as the "home advantage")

Patents are a key measure of innovation output, as patent indicators reflect the inventive performance of countries, regions, technologies, firms, etc. They are also used to track the level of diffusion of knowledge across technology areas, countries, sectors, firms, etc., and the level of internationalisation of innovative activities. Patent indicators can serve to measure the output of R&D, its productivity, structure and the development of a specific technology/industry. The relationship between patents as an intermediate output resulting from R&D inputs has been investigated extensively. Patents are often interpreted as an output indicator; however, they could also be viewed as an input indicator, as patents are used as a source of information by subsequent inventors. Like any other indicator, patent indicators have many advantages and disadvantages. The advantages of patent indicators are :patents have a close link to invention;patents cover a broad range of technologies on which there are sometimes few other sources of data;the contents of patent documents are a rich source of information (on the applicant, inventor, technology category, claims, etc.); andpatent data are readily available from patent offices. However, patents are subject to certain drawbacks:the value distribution of patents is skewed as many patents have no industrial application (and hence are of little value to society) whereas a few are of substantial value;many inventions are not patented because they are not patentable or inventors may protect the inventions using other methods, such as secrecy, lead time, etc.;the propensity to patent differs across countries and industries;differences in patent regulations make it difficult to compare counts across countries; andchanges in patent law over the years make it difficult to analyse trends over time. 

This database provides a set of indicators that reflect the level and structure of central government support for business R&D; in form of R&D; tax incentives and direct funding across OECD member countries and ten non-member economies (Argentina, Brazil, Bulgaria, Croatia, Cyprus, People's Republic of China, Romania, Russian Federation, and South Africa). This includes time-series indicators of tax expenditures for R&D;, based on the latest 2017 OECD data collection on tax incentive support for R&D; expenditures that was completed in July 2017. These estimates of the cost of R&D; tax relief have been combined with data on direct R&D; funding, as compiled by National Statistical Offices based on reports from firms, in order to provide a more complete picture of government efforts to promote business R&D.; The latest indicators and information on R&D; tax incentives also feature on the dedicated OECD website Measuring R&D; tax incentives.Tax expenditures are deviations from a benchmark tax system (OECD, 2010) and countries use different national benchmarks. Available estimates typically reflect the sum of foregone tax revenues – on an accruals basis – and refunds where applicable, with no or minimal adjustments for behavior effects. Some countries only report claims realised in a given year (cash basis), while others report losses to government on an accrual basis, excluding claims referring to earlier periods and including claims for current R&D; to be used in the future. For general and country-specific notes on the estimates of government tax relief for R&D; expenditures (GTARD), see http://www.oecd.org/sti/rd-tax-stats-gtard-notes.pdfThe sources for the other indicators (direct funding of BERD, BERD and GDP) include the OECD databases on Main Science and Technology Indicators and Eurostat R&D; statistics.

This table contains research and development (R&D) expenditure statistics on current domestic R&D and gross domestic R&D expenditures by sector of performance (business enterprise, government, higher education, private non-profit, and total intramural) and by type of R&D within each sector (basic research, applied research, experimental development, non-specified, and total activity). Unit of measure used - Data are provided in million national currency (for the euro zone, pre-EMU euro or EUR), million current PPP USD and million constant USD (2005 prices and PPPs).

These tables present research and development (R&D) personnel statistics for : - Total R&D personnel by sector of employment and field of science, in full-time equivalent on R&D; - Researchers by sex, sector of employment and field of science, in full-time equivant on R&D; - Researchers by sex, sector of employment and field of science, in headcounts. Sectors of employment are business enterprise, government, higher education, private non-profit and total. Breakdown by field of science includes natural sciences, engineering, medical sciences, agricultural sciences, social sciences, and humanities.

These tables contain research and development (RD) personnel statistics. Number of RD personnel is provided in both headcounts and full-time equivalent on RD by sex, sector of employment (business enterprise, government, higher education, and private non-profit) and by occupation (researchers, technicians and other support staff).

This table presents research and development (R&D) personnel statistics. Number of R&D personnel is provided in headcounts and/or full-time equivalent on R&D by sex, sector of employment (business enterprise, government, higher education, and private non-profit) and by formal qualification (university and other diplomas by ISCED classification). Unit of measure used - Headcounts and/or Full-time equivalent on R&D (FTE)

STAN Indicators provides annual indicators related to production and employment structure, labour productivity and labour costs, investment, business research and development expenditures and international trade patterns. Data are presented for OECD countries and cover the time-period 1970-2011, although the time coverage may vary across countries and indicators. Series are provided for a wide range of economic activities (according to an ISIC Rev.4 based hierarchy) compatible with the list in the underlying STAN Database in ISIC Rev. 4. STAN Indicators belong to the STAN family datasets; they are primarily drawn from STAN Database for Structural Analysis (STAN), STAN Bilateral Trade (BTDIxE) and STAN Research & Development Expenditures in Industry (ANBERD). Indicators are compiled to respond to the needs of analysts and researchers interested in measuring economic performance, productivity growth, competitiveness and structural changes. They also complement the OECD publications, Science Technology and Industry Scoreboard and Economic Globalisation Indicators.