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Eurostat's Statistics on  Science, Technology and Innovation (European Commission) Veijo Ritola Head of Section Science, Technology and Innovation Statistics Eurostat – European Commission. Outline of the presentation. Short introduction to Eurostat in general

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  1. Eurostat's Statistics on Science, Technology and Innovation (European Commission)Veijo Ritola Head of Section Science, Technology and Innovation StatisticsEurostat – European Commission

  2. Outline of the presentation • Short introduction to Eurostat in general • Short briefing to the current policy needs • Six sub-categories of the Science, Technology and Innovation Statistics • Research and Development • Innovation • Patents • Careers of Doctorate Holders • High Tech • Human Resources in Science and Technology Eurostat's Statistics on Science, Technology and Innovation

  3. What is Eurostat? • Eurostat is a Directorate General of the European Commission - Commissioner Joaquín Almunia • Eurostat is the central institution of the European Statistical System (ESS) - a network of National Statistical Institutes from all EU and EFTA Countries Eurostat's Statistics on Science, Technology and Innovation

  4. Institutions of the European Union(simplified diagram) Eurostat's Statistics on Science, Technology and Innovation

  5. European Commission: Directorates-General and Services Eurostat's Statistics on Science, Technology and Innovation

  6. Eurostat’s organisation • Director General - Walter Radermacher • Deputy Director General - Marie Bohatá • Staff approximately 870 people • Seven Directorates • Resources & Cooperation in the ESS • Quality, methodology and information systems • National and European accounts • External cooperation, communication and key indicators • Sectoral and regional statistics • Social and information society statistics • Business statistics Eurostat's Statistics on Science, Technology and Innovation

  7. Responsibilities of Eurostat • Collect data from NSIs • Harmonise methods, definitions & classifications • Compile European aggregates – EU & Euro area • Disseminate statistics • International relations – enlargement & development • Programme planning (coordinating national programmes) Eurostat's Statistics on Science, Technology and Innovation

  8. Eurostat credibility is based on • Independence • Impartiality • Objectivity Eurostat's Statistics on Science, Technology and Innovation

  9. Eurostat’s Website: http://ec.europa.eu/eurostat Eurostat's Statistics on Science, Technology and Innovation

  10. Science, Technology and Innovation statisticsEstablishment and development of harmonised Community statistics on Science, Technology and Innovation (STI) is important tool for Providing the necessary evidence basis for the definition, implementation and analysis of Community policies on Science, Technology and Innovationin Europe Regular monitoring the progress achieved towards development of Knowledge-based economy (Lisbon objectives) and realisation of the European Research Area  Supplying the public and media with statistics needed to have an accurate picture of science and technology in Europe and to evaluate the performance of politicians and other actors Eurostat's Statistics on Science, Technology and Innovation

  11. STATISTICS ON STI POLICY NEEDS FOR STI STATISTICS LISBON STRATEGY Research Assessment and support to the EU actions and policies Analysing the progress made towards Lisbon goals and ERA initiatives Growth and jobs Education Innovation EUROPEAN RESEARCH AREA (ERA) • Realising a single labour market for researchers • with high level of mobility •  Developing world-class research infrastructures •  Strengthening research institutions, engaged in • effective public-private cooperation •  Effective knowledge-sharing •  Optimising research programmes and priorities, • including the joint programming •  A wide opening of ERA to the world 11 Eurostat's Statistics on Science, Technology and Innovation

  12. Six areas of STI Eurostat's Statistics on Science, Technology and Innovation

  13. RESEARCH AND DEVELOPMENT STATISTICSLEGAL BASEFramework legal act: Decision № 1608/2003/EC of the EP and of the Council concerning the production and development of Community statistics on S&TLegal implementation measure:Commission Regulation № 753/2004implementing Decision № 1608/2003/EC as regards statistics on S&TR&D INDICATORS  Intramural R&D expenditure (GERD) R&D personnel Government budget appropriations or outlays on R&D (GBAORD) HARMONISED R&D CONCEPTS, DEFINITIONS AND CLASSIFICATIONS  Proposed Standard Practice for Surveys on R&D - Frascati Manual, OECD, 2002 available at: http://www.oecd.org/document/6/0,3343,en_2649_34451_33828550_1_1_1_1,00.htmlDATA SOURCES IN MEMBER STATES Sample/census surveys, administrative sources or others of equivalent quality, or their mixtures, subsidiary principle Eurostat's Statistics on Science, Technology and Innovation

  14. RESEARCH AND DEVELOPMENT STATISTICS BREAKDOWNS OF R&D INDICATORS (in accordance with standard classifications) R&D personnel  Sector of performance  Occupation  Qualification (ISCED)  Gender  Fields of science (FOS)  Citizenship  Age groups  Economic activity (NACE)  Size class  Regions (NUTS) •  Sector of performance •  Source of funds •  Type of costs •  Type of R&D •  Fields of science (FOS) •  Socio-economic objectives (NABS) •  Economic activity (NACE) •  Size class • Regions (NUTS) GERD GBAORD  Socio-economic objectives (NABS) Eurostat's Statistics on Science, Technology and Innovation

  15. RESEARCH AND DEVELOPMENT STATISTICSSTANDARD CLASSIFICATIONS - available on Eurostat's Metadata Server RAMONhttp://ec.europa.eu/eurostat/ramon/index.cfm?TargetUrl=DSP_PUB_WELSTYPE OF R&D INDICATORS Obligatory  Preliminary R&D (T+10) / Provisional GBAORD (T+6)Optional  Final R&D (T+18) / Final GBAORD (T+12) FREQUENCY OF INDICATORS Annual - GERD by sectors of performance, R&D personnel and Researchers in FTE Biannual (on each odd year) - vast majority of indicators Four yearly - gender disaggregation of some indicatorsDEADLINES FOR DATA COLLECTION BY EUROSTATAnnually three rounds of data collection covering all data sets required, including revisions of the time series: In June: final R&D and provisional GBAORD data In October: preliminary R&D yearly data In December: final GBAORD data Eurostat's Statistics on Science, Technology and Innovation

  16. RESEARCH AND DEVELOPMENT STATISTICSSTANDARDISED APPROACH FOR DATA COLLECTIONJOINT OECD/EUROSTAT HARMONISED R&D QUESTIONNAIRE Comprises 3 modules:Common Core OECD/Eurostat module ESTAT supplementary module OECD supplementary moduleGoes beyond the requirements of EU legal baseContains around 50 Tables in two Excel workbooks Data validation rules in place within the questionnaireConfidential data provision Received from 33 countries: 27 MSs; HR,TR,CH, IS, NO and RU Transmission media - eDAMIS  Transmission format - ExcelEVALUATION OF DATA QUALITY  Data validation by Eurostat at the delivery point National Quality Reports - covering standard quality criteria:Relevance, Accuracy, Timelines and Punctuality, Accessibility and Clarity, Comparability, Coherence, Cost and Burden Eurostat's Statistics on Science, Technology and Innovation

  17. RESEARCH AND DEVELOPMENT STATISTICSDERIVED R&D VARIABLES (RATIO INDICATORS) produced by Eurostat EU AGGREGATES calculated by Eurostat:EU-27, EU-15, EA-16  R&D expenditure as а percentage of GDP (R&D intensity) For 2007: EU-27 = 1.85 % - still below the Lisbon target of 3% In two MS: > 3 % - SE (3.60%) FI (3.47%) In four MS: (2 % - 3%) - DE, FR, AT, DK  GBAORD as а percentage of GDP  GBAORD as а percentage general government expenditure  R&D expenditure and GBAORD in Euro per inhabitant R&D personnel/Researchers as а percentage of activepopulation  R&D personnel/Researchers as а percentage of total employment DERIVED R&D VARIABLES Eurostat's Statistics on Science, Technology and Innovation

  18. RESEARCH AND DEVELOPMENT STATISTICSCURRENT CHALLENGES  DEVELOPMENT OF NEW INDICATORS FOR MONITORING EUROPEAN RESEARCH AREA (ERA)  National public funding to trans-nationally coordinated research  National contributions to trans-national public R&D performers (CERN, ILL, ERSF, EMBL, EMBO, ESO, JRC) National contributions to Europe-wide trans-national public R&D programmes (ERA-NETs, ESA, EFDA, EUREKA, COST etc.)National contributions to bi- or multi-lateral public R&D programmes established between MSs governments  Total amount of Structural Funds for R&D (national and EU funding) Breakdown of R&D expenditure financed by abroad by type of source (including EU/non-EU origin of source) Eurostat's Statistics on Science, Technology and Innovation

  19. RESEARCH AND DEVELOPMENT STATISTICS CURRENT CHALLENGES DIRECT DATA COLLECTION FROM TRANS-NATIONAL PUBLIC R&D PERFORMERS  Launched by Eurostat on core R&D indicators DEVELOPMENT OF NEW R&D DATABASE Based on Eurostat standard tools - GSAST, EBB More efficient data treatment - automatic data validation, estimation, conversion, aggregation, derivation, dissemination Eurostat's Statistics on Science, Technology and Innovation

  20. INNOVATION STATISTICSLEGAL BASEFramework legal act: Decision № 1608/2003/EC of the EP and of the Council concerning the production and development of Community statistics on S&TLegal implementation measure:Commission Regulation № 1450/2004 implementing Decision № 1608/2003/EC concerning the production and development of Community statistics on innovation (amended by CR № 540/2009) INDICATORS  Innovation active enterprises  Innovating enterprises that introduced new or significantly improved products, new to the market Turnover from innovation, related to new or significantly improved products, new to the market Turnover from innovation, related to new or significantly improved products, new to the firm, but not new to the market Innovation active enterprises involved in innovation cooperation - by type of cooperation EVERY TWO YEARS Eurostat's Statistics on Science, Technology and Innovation

  21. INNOVATION STATISTICS INDICATORS Beyond the variables listed above, MS compile additional statistics (including their breakdowns) in accordance with the main themes listed in the Oslo Manual (optional).  Innovation expenditure (optional)  Innovation active enterprises that indicated highly important objectives of innovation - by type of objectives  Innovation active enterprises that indicated highly important sources of information for innovation - by type of source (optional)  Enterprises facing important hampering factors - by type of hampering factors EVERY FOUR YEARS Eurostat's Statistics on Science, Technology and Innovation

  22. INNOVATION STATISTICS HARMONISED CONCEPTS, DEFINITIONS AND CLASSIFICATIONSGuidelines for Collecting and Interpreting Innovation Data-Oslo Manual, OECD, 2005 available at: http://lysander.sourceoecd.org/vl=1764186/cl=11/nw=1/rpsv/cgi-bin/fulltextew.pl?prpsv=/ij/oecdthemes/99980134/v2005n18/s1/p1l.idxDATA SOURCES IN MEMBER STATES  Combination of different sources - sample surveys, administrative data or others of equivalent qualityTYPE OF INDICATORS Obligatory  Optional FREQUENCY OF INDICATORS Biannual, on each even year - 5 obligatory variables  Four yearly - 7 obligatory and 2 optional variables (plus more) DEADLINE FOR DATA COLLECTION BY EUROSTAT 18 months after the end of the calendar year of the reference period Eurostat's Statistics on Science, Technology and Innovation

  23. INNOVATION STATISTICS TYPES OF DATA TRANSMITTED  Aggregated statistics - compulsory Individual (micro) data records - voluntaryConfidential data provisionSTANDARD TRANSMISSION FORMAT For aggregated data - Excel; For individual data - CSV file Data received from 29 countries: 27 MS, IS and NOTransmission media - eDAMISACCESS TO MICRODATAAnonymised microdata: on CDNon-anonymised microdata: via the SAFE Centre in EurostatInformation how to obtain microdata available at:http://epp.eurostat.ec.europa.eu/portal/page/portal/microdata/cisEVALUATION OF DATA QUALITY  Data validation by Eurostat at the delivery point National Quality Reports - covering standard quality criteria:Relevance, Accuracy, Timelines and Punctuality, Accessibility and Clarity, Comparability, Coherence, Cost and Burden Eurostat's Statistics on Science, Technology and Innovation

  24. INNOVATION STATISTICS STANDARDISED APPROACH FOR DATA COLLECTION COMMUNITY INNOVATION SURVEY (CIS)  Target population (NACE and size class coverage, statistical unit, observation period) Survey methodology (sampling frame, type of survey, stratification variables, sample size, sample selection and allocation) Collecting and processing the data (survey questionnaire, data collection and data editing) Data quality (response rate, non- response survey, precision of results, imputation, weighting and calibration) Transmission of data (types of data, output tabulation scheme, deadlines, transmission tool) HARMONISED METHODOLOGICAL RECOMMENDATIONS Eurostat's Statistics on Science, Technology and Innovation

  25. INNOVATION STATISTICSCOMMUNITY INNOVATION SURVEY (CIS) STANDARD SURVEY QUESTIONNAIRE (CIS 2008) 1/ General information about the enterprise 2/ Product innovation (good or service) 3/ Process innovation 4/ Ongoing or abandoned innovation activities for process and product innovations 5/ Innovation activities and expenditures for process and product innovations 6/ Sources of information and co-operation for innovation activities 7/ Innovation objectives during 2006 - 2008 8/ Organisational innovation 9/ Marketing innovation 10/ Innovations with environmental benefits 11/ Basic economic information on the enterprise (turnover, employees) Eurostat's Statistics on Science, Technology and Innovation

  26. INNOVATION STATISTICSCURRENT CHALLENGES  REVISION OF THE REGULATION 1450/2004 Extension to the organisational and marketing innovation  Revision/extension of the economic activities covered Introduction of one-off modules Introduction of the quality annex From voluntary to mandatory microdata deliveries Frequency of the variables MODULE SELECTION FOR CIS 2010 User driven innovation  Creativity and skills to innovate TRACKING ENTERPRISES IN CONSECUTIVE MICRODATA SETS OBSERVATION PERIOD (2/3 YEARS) MEASUREMENT OF THE DESIGN IN THE INNOVATION SURVEYS  EVALUATION OF THE NATIONAL QUESTIONNAIRES Eurostat's Statistics on Science, Technology and Innovation

  27. PATENT STATISTICSPATENT STATISTICS Patent statistics measure Research output Innovation activities Technological progress Capacity to exploit knowledgeDATA SOURCES One single raw database (PATSTAT) compiled on the basis of input from European Patent Office (EPO) US Patent and Trademark Office (USPTO) Japanese Patent Office (JPO)HARMONISED R&D CONCEPTS, DEFINITIONS AND CLASSIFICATIONS Patent StatisticsManual, OECD,2009, available at: http://www.oecd.org/document/29/0,3343,en_2649_34451_42168029_1_1_1_1,00.htmlInternational Patent Classification (IPC) Eurostat's Statistics on Science, Technology and Innovation

  28. PATENT STATISTICS Data extracted from a single patent statistics raw database (PATSTAT), held by the European Patent Office (EPO) and further edited, aggregated and disseminated by Eurostat for all EU Member States, Candidate Countries, EFTA members and other countries APPROACH FOR COMPILATION OF PATENT STATISTICS • Eurostat’s database contains data on: • Patent applications to the EPO • Patents granted by the USPTO • Triadic patent families (based on raw patent data from OECD) • Patents in high-technology fields • High-tech patents • ICT patents • Biotechnology patents • Nanotechnology patents Eurostat's Statistics on Science, Technology and Innovation

  29. PATENT STATISTICS TYPES OF INDICATORS • Patent applications to EPO by priority year •  Patent applications to the EPO by priority year at the national level • Patent applications to the EPO by priority year at the regional level • Ownership of inventions  European and international co-patenting •  Patent citations • Patents granted by the USPTO by priority year • Patents granted by the USPTO by priority year at the national level • Ownership of inventions • European and international co-patenting • Patent citations • Triadic patent families by earliest priority year Eurostat's Statistics on Science, Technology and Innovation

  30. PATENT STATISTICSBREAKDOWNS OF PATENT INDICATORSDERIVED PATENT VARIABLES (RATIO INDICATORS)  Institutional sector  IPC sections and classes,  Economic activities (NACE classes)  Type of ownership  Inventors’/ applicants' country of residence BREAKDOWNS  Per million inhabitants  Per million labour force  Relative to Gross domestic product (GDP) in euro  Relative to Gross domestic expenditure on R&D (GERD)  Relative to Expenditure on R&D in Business enterprise sector DERIVED VARIABLES FOR EPO AND USPTO PATENTS Eurostat's Statistics on Science, Technology and Innovation

  31. PATENT STATISTICS FIELDS OF INVESTIGATION  PATENTS IN NUCLEAR TECHNOLOGY Nuclear Reactor Technique Radiation Acceleration Technique  PATENTS IN WIND ENERGY Wind Motors Relevant surrounding techniques (Circuit arrangements or systems for supplying or distributing electric powers, Control or regulation of electric motors, generators, or dynamo-electric converters, Dynamo-electric machines)  PATENTS IN ENVIRONMENTAL RELATED ENERGY Environmental Related Renewable Energy Automobile Pollution Control Technology Eurostat's Statistics on Science, Technology and Innovation

  32. PATENT STATISTICSCURRENT CHALLENGES  CREATE NEW INDICATORS AND MORE BREAKDOWNS Specific technological sectors Triadic patent families Regional level SEARCH WAYS TO COMBINE PATENT STATISTICS WITH THE BUSINESS DATA Eurostat's Statistics on Science, Technology and Innovation

  33. CAREERS OF DOCTORATE HOLDERS CDH 2006 VOLUNTARY SURVEY (NO LEGAL BASE) Widely supported project (EU Commission, OECD, UNESCO) Measuring the mobility, careers and expectations of research educated peoplePARTICIPATING COUNTRIES21 EU MSs, Australia, Switzerland, Iceland, Norway and USAREFERENCE YEAR  2006 (except for Belgium, Netherlands, Norway: 2005, Italy, Malta: 2007)CARRIED OUT In 2007 - 2008DATA SOURCES IN MS Variety of sources for compiling the target population (registers, administrative data, census of population etc.) Eurostat's Statistics on Science, Technology and Innovation

  34. CAREERS OF DOCTORATE HOLDERS STANDARDISED APPROACH FOR DATA COLLECTION CORE MODEL QUESTIONNAIRE  INSTRUCTION MANUAL FOR COMPLETING THE QUESTIONNAIRE METHODOLOGICAL GUIDELINES  OUTPUT INDICATORS TEMPLATE VARIABLES IN PROPOSED TABULATIONS - definitions and sources  Module EDU - Doctoral education  Module REC - Recent graduates  Module POS - POSTDOCS  Module EMP - Employment situation  Module MOB - International mobility  Module CAR - Career related experience and scientific productivity  Module PER - Personal characteristics CORE MODEL QUESTIONNAIRE Eurostat's Statistics on Science, Technology and Innovation

  35. CAREERS OF DOCTORATE HOLDERSMAINCHARACTERISTICS Personal characteristics Educational characteristics  Gender  Age  Country of birth  Type of citizenship/residential status  Country of doctorate award  Field of doctorate award Work perception Employment characteristics  Job qualification  Perception to salary  Occupation  Researcher function / non -  Earnings  Length of stay with current employer Eurostat's Statistics on Science, Technology and Innovation

  36. CAREERS OF DOCTORATE HOLDERS GROSSING-UP - applied by all countries except for Belgium, Czech Republic, Poland, Romania and Slovak RepublicFIRST RESULTS  Presented in the December 2008 Brussels meeting Lack of comparability, mainly due to coverage inconsistencies Additional request for ‘restricted’ data on specific set of output tables Restriction 1: ISCED6 graduates aged below 70 years old Restriction 2: ISCED6 graduates awarded after 1990 Revised data was gathered in March 2009 - comparability issues are still apparent Eurostat's Statistics on Science, Technology and Innovation

  37. CAREERS OF DOCTORATE HOLDERS SELECTED FINDINGS  Male doctorate holders are in general more than female doctorate holders (more than 60% in most of the countries)Most doctorate holders have been awarded in the reporting country (exceptions are CY IS MT)  Most popular occupation is teaching profession  Doctorate holders are most employed as researchers than non- researchers in all countries (exceptions are BE NL RO) Doctorate holders are generally far better paid compared to the total population (SES 2006 results)Doctorate holders tend to stay with the same employer for more than 5 years and in many countries for more than 10 years(except for DK)Most employed doctorate holders have a job that is related to their doctoral degree (except for AT) Eurostat's Statistics on Science, Technology and Innovation

  38. CAREERS OF DOCTORATE HOLDERSUPCOMING CHALLENGES  Voluntary countries participation in CDH 2009. Financial support (grants) from Eurostat  Revision of the CDH technical documents - end of September 2009 CDH 2009 national data collection:  Preparation phase at country level - end of 2009  Data collection - 2010 Output tables to UIS/OECD/Eurostat before end 2010 Data publication and analysis Eurostat's Statistics on Science, Technology and Innovation

  39. MAIN APPROACHES IN COMPILATION OF HIGH-TECH STATISTICS Sectors identified following the Statistical Classification of Economic Activities in the European Community (NACE) Products identified following the Standard International Trade Classification (SITC) HIGH-TECH STATISTICS SECTORAL APPROACH PRODUCT APPROACH Sectors identified according to the technological intensity: R&D expenditure/value added Products identified according to the high value of R&D intensity: R&D expenditure/total sales PATENTS High-tech and biotechnology patents identified according to International Patent Classification (IPC 8th edition) Eurostat's Statistics on Science, Technology and Innovation

  40. SECTORAL APPROACH BASED ON NACE NACE  common EU classification of economic activities  covers a whole range of economic activities  4-digit level  Manufacturing sector High-technology manufacturing Medium-high technology manufacturing Medium-low technology manufacturing Low-technology manufacturing  Services Knowledge intensive services Less knowledge intensive services HIGH-TECH STATISTICS • Manufacturing and services • classified according to: • the level of technological intensity R&D expenditure/value added • the share of the highest educated staff • Classification is relative to • variables used • the data of the countries used • the time the data refer to • threshold set Eurostat's Statistics on Science, Technology and Innovation

  41. PRODUCT APPROACH BASED ON SITC HIGH-TECH PRODUCTS Aerospace Armament Computers-Office machines Electronics-Telecommunication Pharmacy Scientific instruments Electrical machinery Non-electrical machinery Chemistry  Data collection Traders’ customs declarations (extra-EU27) Direct enterprise declarations (intra-EU27)  Data source and coverage Comext database - EU trade Comtrade database - World trade HIGH-TECH STATISTICS Indicators • Import/export in Mio Euro • World shares • Ratio of country’s high-tech trade in its total trade • Share of intra-EU trade Classification is less relative as the products are assumed to be more homogeneous (than the sectors) and therefore less dependent on the set of countries used Eurostat's Statistics on Science, Technology and Innovation

  42. INDICATORS AND SOURCES FOR HIGH-TECH SECTORS (NACE) SECTORAL APPROACH R&D personnel and expenditure Employment statistics for high-tech sectors Innovation activities Structural business statistics (number of enterprises, turnover, value added at factor costs, production value, social security costs etc) Mean annual earnings by sex, age and level of education Venture capital investment by stage of development (for all sectors) R&D survey Labour Force Survey (LFS) Community Innovation Survey (CIS) Structural Business Survey (SBS) Structure of Earnings Survey (SES) European Private Equity and Venture Capital Association (EVCA) HIGH-TECH STATISTICS Eurostat's Statistics on Science, Technology and Innovation

  43. HIGH-TECH STATISTICS INDICATORS AND SOURCES FOR HIGH-TECH TRADE (SITC) – PRODUCT APPROACH  Import and export of high-tech group of products Comext / Comtrade Patent indicators (IPC) EPO, USPTO High-tech patents in high-technology fields and biotechnology patents Eurostat's Statistics on Science, Technology and Innovation

  44. HIGH-TECH STATISTICS UPCOMING CHALLENGES Establishment of transitional definitions to accommodate the revised NACE Rev.2 source data More in-depth revision waits the R&D intensity data with NACE 2 (2011) and more recent OECD's input-output tables (2009-2010)Updating theHigh-Tech classifications Presently both main High-Tech classifications (in terms of economic activities and in terms of products) are based on 'old' reference data for very limited set of (more developed) countries  Development of new sectoral classification based on the knowledge intensity, measured through LFS data on the share of tertiary educated employed, by economic activity (NACE) Eurostat's Statistics on Science, Technology and Innovation

  45. HUMAN RESOURCES IN S&T (HRST) HRST STATISTICS  HRST statistics review the supply of and demand for highly qualified staff in a broad sense Statistics show stocks and flows of HRST at EU, national and regional levelDATA SOURCES Data extracted from two Eurostat sources (Labour force survey and Statistics on education) and edited, aggregated and disseminated by Eurostat for all EU27 (+)HARMONISED CONCEPTS, DEFINITIONS AND CLASSIFICATIONSManual on the measurement of Human Resources devoted to S&T - Canberra Manual, OECD, 1995available at: http://www.oecd.org/dataoecd/34/0/2096025.pdf Eurostat's Statistics on Science, Technology and Innovation

  46. HUMAN RESOURCES IN S&T (HRST) DEFINITION Definition based on the cross tabulation of education and occupation, used often as proxy for ‘researchers’ Human Resources in S&T are all individuals who fulfil at least one of the following conditions: The conditions of the above educational or occupational requirements are considered according to internationally harmonised standards: - International Standard Classification of Occupation - ISCO- International Standard Classification of Education - ISCED  Have successfully completed tertiary-level education and/or  Work in S&T occupation as professionals or technicians, where the above qualifications are normally required Eurostat's Statistics on Science, Technology and Innovation

  47. HUMAN RESOURCES IN S&T (HRST) HRST SUB - CATEGORIES • HRSTC - individuals who have successfully completed tertiary-level • education and work in an S&T occupation as professionals • or technicians • HRSTE - individuals who have successfully completed tertiary-level • education • HRSTO - individuals who work in an S&T occupation as professionals • or technicians • HRSTU - individuals who have successfully completed tertiary-level • education but are unemployed Eurostat's Statistics on Science, Technology and Innovation

  48. APPROACHES IN COMPILATION OF HRST STATISTICS HUMAN RESOURCES IN S&T (HRST) From Labour Force Survey (LFS) From Education statistics Statistics over participants and graduates from tertiary level education is used for inflow statistics Data over employed and unemployed is used for stock and mobility statistics Eurostat's Statistics on Science, Technology and Innovation

  49. HUMAN RESOURCES IN S&T (HRST) MAIN INDICATORS HRST sub-category  Gender  Age  Occupation  Sector of economic activity  Field of education studied  Unemployment rate  Nationality / country of birth  Region HRST STOCK  Job-to-job mobility  Tertiary level education participants  Tertiary level education graduates  Tertiary level education foreign students HRST FLOWS Eurostat's Statistics on Science, Technology and Innovation

  50. HUMAN RESOURCES IN S&T (HRST)UPCOMING CHALLENGES Updating the Canberra Manual HRST concept and definitions are based on the OECD's Canberra Manual which was published more than 20 years ago. Since then both underlying classifications has been revised, International Standard Classification of Occupation (ISCO) and International Standard Classification of Education (ISCED97). Eurostat's Statistics on Science, Technology and Innovation

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