eurostat's statistics on science, technology and innovation (european commission) veijo ritola...

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


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


Institutions of the European Union(simplified diagram)


European Commission: Directorates-General and Services


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


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 credibility is based on

Independence Impartiality Objectivity


Eurostat’s Website: http://ec.europa.eu/eurostat

http://ec.europa.eu/eurostat




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


Six areas of STI


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

http://www.oecd.org/document/6/0,3343,en_2649_34451_33828550_1_1_1_1,00.html



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



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

http://ec.europa.eu/eurostat/ramon/index.cfm?TargetUrl=DSP_PUB_WELS





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



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



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)



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


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



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



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

http://lysander.sourceoecd.org/vl=1764186/cl=11/nw=1/rpsv/cgi-bin/fulltextew.pl?prpsv=/ij/oecdthemes/99980134/v2005n18/s1/p1l.idx





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

http://epp.eurostat.ec.europa.eu/portal/page/portal/microdata/cis




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



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)



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


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:


International Patent Classification (IPC)



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)


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


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


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


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


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.)


CAREERS OF DOCTORATE HOLDERS


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



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



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



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)


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


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


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



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



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)



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 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)


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

http://www.oecd.org/dataoecd/34/0/2096025.pdf



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


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


HRST SUB - CATEGORIES

HRSTE - individuals who have successfully completed tertiary-level education


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)




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


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).


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

http://epp.eurostat.ec.europa.eu/

http://www.oecd.org/statsportal/

http://ec.europa.eu/research/


Thank you !

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