eurostat's statistics on science, technology and innovation (european commission) veijo ritola...
Post on 22-Dec-2015
218 views
TRANSCRIPT
Eurostat's Statistics on Science, Technology and Innovation (European Commission)Veijo Ritola Head of Section Science, Technology and Innovation StatisticsEurostat – European Commission
2Eurostat's Statistics on Science, Technology and Innovation9/10/2009
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
3Eurostat's Statistics on Science, Technology and Innovation9/10/2009
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
4Eurostat's Statistics on Science, Technology and Innovation9/10/2009
Institutions of the European Union(simplified diagram)
5Eurostat's Statistics on Science, Technology and Innovation9/10/2009
European Commission: Directorates-General and Services
6Eurostat's Statistics on Science, Technology and Innovation9/10/2009
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
7Eurostat's Statistics on Science, Technology and Innovation9/10/2009
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)
8Eurostat's Statistics on Science, Technology and Innovation9/10/2009
Eurostat credibility is based on
Independence Impartiality Objectivity
9Eurostat's Statistics on Science, Technology and Innovation9/10/2009
Eurostat’s Website: http://ec.europa.eu/eurostat
10Eurostat's Statistics on Science, Technology and Innovation9/10/2009
Science, Technology and Innovation statistics
Establishment 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 Innovation in 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
11Eurostat's Statistics on Science, Technology and Innovation9/10/2009 11
STATISTICS ON STI
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
EUROPEAN RESEARCH AREA (ERA)
Assessment and support to the EU actions and policies
Analysing the progress made towards Lisbon goals and ERA initiatives
Growth and jobs
Research
Education Innovation
LISBON STRATEGY
POLICY NEEDS FOR STI STATISTICS
12Eurostat's Statistics on Science, Technology and Innovation9/10/2009
Six areas of STI
13Eurostat's Statistics on Science, Technology and Innovation9/10/2009
RESEARCH AND DEVELOPMENT STATISTICS
LEGAL 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 № 753/2004 implementing Decision № 1608/2003/EC as regards statistics on S&T
R&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.html
DATA SOURCES IN MEMBER STATES Sample/census surveys, administrative sources or others of equivalent quality, or their mixtures, subsidiary principle
14Eurostat's Statistics on Science, Technology and Innovation9/10/2009
RESEARCH AND DEVELOPMENT STATISTICS
BREAKDOWNS OF R&D INDICATORS (in accordance with standard classifications)
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 Sector of performance Occupation Qualification (ISCED) Gender Fields of science (FOS) Citizenship Age groups Economic activity (NACE) Size class Regions (NUTS)
Socio-economic objectives (NABS)
R&D personnel
GBAORD
15Eurostat's Statistics on Science, Technology and Innovation9/10/2009
RESEARCH AND DEVELOPMENT STATISTICS
STANDARD CLASSIFICATIONS - available on Eurostat's Metadata Server RAMONhttp://ec.europa.eu/eurostat/ramon/index.cfm?TargetUrl=DSP_PUB_WELS
TYPE 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 indicators
DEADLINES 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
16Eurostat's Statistics on Science, Technology and Innovation9/10/2009
RESEARCH AND DEVELOPMENT STATISTICS
STANDARDISED APPROACH FOR DATA COLLECTION
JOINT 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 - Excel
EVALUATION 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
17Eurostat's Statistics on Science, Technology and Innovation9/10/2009
RESEARCH AND DEVELOPMENT STATISTICS
DERIVED 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 active population R&D personnel/Researchers as а percentage of total employment
DERIVED R&D VARIABLES
18Eurostat's Statistics on Science, Technology and Innovation9/10/2009
RESEARCH AND DEVELOPMENT STATISTICS
CURRENT 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)
19Eurostat's Statistics on Science, Technology and Innovation9/10/2009
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
20Eurostat's Statistics on Science, Technology and Innovation9/10/2009
INNOVATION STATISTICS
LEGAL 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
21Eurostat's Statistics on Science, Technology and Innovation9/10/2009
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
22Eurostat's Statistics on Science, Technology and Innovation9/10/2009
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.idx
DATA SOURCES IN MEMBER STATES Combination of different sources - sample surveys, administrative data or others of equivalent quality
TYPE 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
23Eurostat's Statistics on Science, Technology and Innovation9/10/2009
INNOVATION STATISTICS
TYPES OF DATA TRANSMITTED Aggregated statistics - compulsory Individual (micro) data records - voluntary Confidential data provision
STANDARD TRANSMISSION FORMAT For aggregated data - Excel; For individual data - CSV file Data received from 29 countries: 27 MS, IS and NO Transmission media - eDAMIS
ACCESS TO MICRODATA Anonymised microdata: on CD Non-anonymised microdata: via the SAFE Centre in Eurostat Information how to obtain microdata available at: http://epp.eurostat.ec.europa.eu/portal/page/portal/microdata/cis
EVALUATION 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
24Eurostat's Statistics on Science, Technology and Innovation9/10/2009
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
25Eurostat's Statistics on Science, Technology and Innovation9/10/2009
INNOVATION STATISTICS
COMMUNITY INNOVATION SURVEY (CIS)
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)
STANDARD SURVEY QUESTIONNAIRE (CIS 2008)
26Eurostat's Statistics on Science, Technology and Innovation9/10/2009
INNOVATION STATISTICS
CURRENT 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
27Eurostat's Statistics on Science, Technology and Innovation9/10/2009
PATENT STATISTICS
PATENT STATISTICS Patent statistics measure Research output Innovation activities Technological progress Capacity to exploit knowledge
DATA 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 Statistics Manual, 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)
28Eurostat's Statistics on Science, Technology and Innovation9/10/2009
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
Patents in high-technology fields
High-tech patents ICT patents Biotechnology patents Nanotechnology patents
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)
29Eurostat's Statistics on Science, Technology and Innovation9/10/2009
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
Triadic patent families by earliest priority year
PATENT STATISTICS
TYPES OF INDICATORS
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
30Eurostat's Statistics on Science, Technology and Innovation9/10/2009
PATENT STATISTICS
BREAKDOWNS OF PATENT INDICATORS
DERIVED PATENT VARIABLES (RATIO INDICATORS)
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
Institutional sector IPC sections and classes, Economic activities (NACE classes) Type of ownership Inventors’/ applicants' country of residence
BREAKDOWNS
31Eurostat's Statistics on Science, Technology and Innovation9/10/2009
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
PATENT STATISTICS
32Eurostat's Statistics on Science, Technology and Innovation9/10/2009
PATENT STATISTICS
CURRENT 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
33Eurostat's Statistics on Science, Technology and Innovation9/10/2009
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 people
PARTICIPATING COUNTRIES 21 EU MSs, Australia, Switzerland, Iceland, Norway and USA
REFERENCE YEAR 2006 (except for Belgium, Netherlands, Norway: 2005, Italy, Malta: 2007)
CARRIED OUT In 2007 - 2008
DATA SOURCES IN MS Variety of sources for compiling the target population (registers, administrative data, census of population etc.)
34Eurostat's Statistics on Science, Technology and Innovation9/10/2009
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
35Eurostat's Statistics on Science, Technology and Innovation9/10/2009
CAREERS OF DOCTORATE HOLDERS
MAIN CHARACTERISTICS
Gender Age Country of birth Type of citizenship/residential status
Personal characteristics
Country of doctorate award
Field of doctorate award
Educational characteristics
Occupation
Researcher function / non -
Earnings
Length of stay with current employer
Employment characteristics
Job qualification
Perception to salary
Work perception
36Eurostat's Statistics on Science, Technology and Innovation9/10/2009
CAREERS OF DOCTORATE HOLDERS
GROSSING-UP - applied by all countries except for Belgium, Czech Republic, Poland, Romania and Slovak Republic
FIRST 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
37Eurostat's Statistics on Science, Technology and Innovation9/10/2009
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)
38Eurostat's Statistics on Science, Technology and Innovation9/10/2009
CAREERS OF DOCTORATE HOLDERS UPCOMING 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
39Eurostat's Statistics on Science, Technology and Innovation9/10/2009
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)
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
High-tech and biotechnologypatents identified according to
International Patent Classification(IPC 8th edition)
PATENTS
PRODUCT APPROACHSECTORAL APPROACH
HIGH-TECH STATISTICS
40Eurostat's Statistics on Science, Technology and Innovation9/10/2009
SECTORAL APPROACH BASED ON NACENACE 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
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
HIGH-TECH STATISTICS
41Eurostat's Statistics on Science, Technology and Innovation9/10/2009
PRODUCT APPROACH BASED ON SITC
HIGH-TECH PRODUCTSAerospaceArmamentComputers-Office machinesElectronics-TelecommunicationPharmacyScientific instrumentsElectrical machineryNon-electrical machineryChemistry
Data collection– Traders’ customs declarations (extra-
EU27)– Direct enterprise declarations (intra-
EU27)
Data source and coverage– Comext database - EU trade– Comtrade database - World trade
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) andtherefore less dependent on the set of countries used
HIGH-TECH STATISTICS
42Eurostat's Statistics on Science, Technology and Innovation9/10/2009
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
43Eurostat's Statistics on Science, Technology and Innovation9/10/2009
INDICATORS AND SOURCES FOR HIGH-TECH TRADE (SITC) – PRODUCT APPROACH
Comext / Comtrade
Patent indicators (IPC) EPO, USPTO
Import and export of high-tech group of products
High-tech patents in high-technology fields and biotechnology patents
HIGH-TECH STATISTICS
44Eurostat's Statistics on Science, Technology and Innovation9/10/2009
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 the High-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)
45Eurostat's Statistics on Science, Technology and Innovation9/10/2009
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 level
DATA 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, 1995 available at: http://www.oecd.org/dataoecd/34/0/2096025.pdf
46Eurostat's Statistics on Science, Technology and Innovation9/10/2009
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 educationand/or Work in S&T occupation as professionals or technicians, where the above qualifications are normally required
47Eurostat's Statistics on Science, Technology and Innovation9/10/2009
HRSTC - individuals who have successfully completed tertiary-level education and work in an S&T occupation as professionals or technicians
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
HUMAN RESOURCES IN S&T (HRST)
HRST SUB - CATEGORIES
HRSTE - individuals who have successfully completed tertiary-level education
48Eurostat's Statistics on Science, Technology and Innovation9/10/2009
APPROACHES IN COMPILATION OF HRST STATISTICS
Data over employed
and unemployed
is used for stockand mobility statistics
Statistics overparticipants
andgraduates
from tertiary level educationis used for inflow statistics
From Education statisticsFrom Labour Force Survey (LFS)
HUMAN RESOURCES IN S&T (HRST)
49Eurostat's Statistics on Science, Technology and Innovation9/10/2009
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
50Eurostat's Statistics on Science, Technology and Innovation9/10/2009
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).
51Eurostat's Statistics on Science, Technology and Innovation9/10/2009
WHERE TO FIND S&T&I STATISTICS?
WEB– Eurostat/Science, Technology
and Innovationhttp://epp.eurostat.ec.europa.eu
– OECD databasehttp://www.oecd.org/statsportal/
– DG Researchhttp://ec.europa.eu/research/
PUBLICATIONS– Eurostat collections
Statistical Book on Science, technology and innovation – 2009Pocketbook on Science, technology and innovation – 2008Statistics in Focus
News release– DG Research
Key figures on Science, technology and competitiveness 2008/2009
52Eurostat's Statistics on Science, Technology and Innovation9/10/2009
Thank you !