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Www.uis.unesco.org UIS activities in the collection and analysis of STI indicators and overview of data for South East Asia South East Asian Regional Workshop.

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Presentation on theme: "Www.uis.unesco.org UIS activities in the collection and analysis of STI indicators and overview of data for South East Asia South East Asian Regional Workshop."— Presentation transcript:

1 UIS activities in the collection and analysis of STI indicators and overview of data for South East Asia South East Asian Regional Workshop on Science, Technology and Innovation Statistics Hanoi, Viet Nam 5-8 December 2011 Martin Schaaper

2 Objectives of this presentation Present the work that UIS does to support the collection and analysis of STI indicators in developing countries Provide an overview of the availability of STI indicators worldwide and in the region

3 UNESCO Institute for Statistics (UIS) Formerly UNESCO Division of Statistics Established in 1999 September the UIS moved from Paris to the University of Montreal, Quebec, Canada 30 November 2001 – UNESCO Director-General inaugurates the UNESCO Institute for Statistics in Montreal Director: Mr. Hendrik van der Pol

4 UIS presence around the world Montreal Nairobi Luanda Bangkok Santiago Apia Paris Dakar Windhoek Bamako Yaounde Doha Delhi

5 UNESCO Institute for Statistics (UIS) United Nations data repository for: Education Science, Technology and Innovation Culture Communication

6 UIS is the UN lead agency for S&T statistics Official S&T data source for: UN Statistical Division: UN Statistical Year Book UNDP: Human Development Report World Bank: World Development Indicators Data publicly available at: UIS Publications (can be downloaded from the UIS website): S&T Bulletins; Fact sheet on R&D statistics UNESCO Reports: UNESCO Science Report UNESCO World Report - Towards Knowledge Societies International Report on S&T and Gender History of Science Statistics at UNESCO

7 Areas of work R&D personnel & expenditure Human resources devoted to S&T International mobility Gender Innovation data Since 2010 Longer term: Output & Impact

8 Lines of action 1.S&T survey operation and data guardianship 2.Training in S&T statistics: workshops & other training activities 3.Standard setting and methodological developments 4.Analysis and publications

9 1. S&T Survey operation and data guardianship Global survey on statistics of science & technology Global database on S&T Statistics Data dissemination: on the UIS website and through contributions to other agencies 2011: pilot survey of innovation data

10 Survey on Statistics of Science & Technology: R&D Survey Biennially. 2004, 2006, 2008 and 2010 R&D surveys completed. Results released on UIS website (http://stats.uis.unesco.org). OECD and Eurostat provide data for their Member States. RICYT provides data for Latin America and for a few Caribbean countries. UIS keeps direct contact with national S&T statisticians.

11 Data collection: R&D Survey R&D Personnel By sector of employment, occupation, qualification, and field of science In headcount and FTE By gender R&D Expenditure By sector of performance and source of funds By type of activity and field of science

12 Respondents to the UIS 2008 and 2010 questionnaires: South East Asia Country2008Q2010Q 1Brunei DarussalamData not provided 2CambodiaData not provided 3Hong Kong SAR, ChinaData provided 4Laos PDRData not provided 5IndonesiaData provided 6Macao SAR, ChinaData not providedData provided 7MalaysiaData provided 8MyanmarData not provided 9PhilippinesData provided 10ThailandData provided 11Timor-LesteData not provided 12Viet NamData not provided

13 UIS 2008 and 2010 Surveys on R&D: response rates & published data Regions (Countries and Territories covered) Effective responses Q 2008 Effective responses Q 2010 Published data (by June 2011) Sub-Saharan Africa (45) 1022% 26% 1227% 30% 3169% 70% Arab States-Africa (8) 450%4 675% Asia (31, excl. Arab States & OECD ) 1548% 42% 1652% 51% 2477% 67% Arab States - Asia (12) 325%650%542% Americas (14, excl. RICYT & OECD ) 17%00%429% Europe (16, excl. OECD & Eurostat ) 850%744%1169% Oceania (17, excl. OECD ) 424%00%318% Sub-total (143) 4531%4531%8459% Data from other sources: OECD + Eurostat (45) 45100%45100%45100% RICYT (25, incl. 10 Caribbean ) 1872%1872%1872% Total (213) 10851%10851%14769% Note: Effective responses: number of returned questionnaires with data.

14 Researchers, South East Asia, 2009 or last available year CountryYearResearchers (FTE) Researchers per million inhabitants (FTE) Brunei Darussalam* Cambodia* Hong Kong SAR, China , Laos PDR* Indonesia* ,27590 Macao SAR, China* Malaysia 20069, Myanmar* Philippines 20076,95778 Thailand , Timor-Leste ……… Viet Nam 20029, Source: UIS S&T Database, July 2011 FTE: Full-time equivalent; * Based on partial data

15 How many researchers are there? Number of researchers worldwide Source: UIS, August 2010

16 How many researchers are there? Number of researchers worldwide Source: UIS, August 2010 Note: Data for the USA are for 2006 instead of 2007

17 Where are researchers located? Shares of world researchers by principal regions, 2002 and 2007 (%) Source: UIS, August 2010

18 Which countries host the greatest number of researchers? Number of researchers, 2009 or latest available year Source: UIS, July 2011Note: -1 = 2008, -2 = 2007, -4 = Data in this graph are based on FTE data.

19 A breakdown of researchers in the Americas. Researchers by sector of employment, 2009 or latest available year Source: UIS, July 2011 Note: -1 = 2008, -2 = 2007, -5 = 2004, -6 = 2003, -7 = Data in this graph are based on FTE data (* based on HC data).

20 A breakdown of researchers in Europe. Researchers by sector of employment, 2009 or latest available year Source: UIS, July 2011 Note: +1 = 2010, -1 = 2008, -2= Data in this graph are based on FTE data (* based on HC data).

21 A breakdown of researchers in Africa, Asia and the Pacific. Researchers by sector of employment, 2009 or latest available year Source: UIS, July 2011 Note: -1 = 2008, -2 = 2007, -3 = 2006, -4 = 2005, -6 = 2002, -7 = 2001, -9 = 2000, -12 = Data in this graph are based on FTE data (* based on HC data).

22 What are the national research densities? Researchers per million inhabitants, 2009 or latest available year 0–100 per million 101–300 per million 301–1000 per million 1001–2000 per million Data not available 2001 per million and above Note: Data in this map are based on FTE. However, figures in headcounts (HC) were considered for the following countries since the FTE figures were not available: Armenia; Azerbaijan; Bangladesh; Belarus; Benin; Botswana; Cameroon; Central African Rep.; Cuba; Dem. Rep. of the Congo; El Salvador; Gabon; Gambia; Georgia; Guinea; Honduras; Jordan; Kazakhstan; Kyrgyzstan; Libya; Mauritius; Mongolia; Montenegro; Nauru; Nicaragua; Peru; Saint Lucia; Saint Vincent and the Grenadines; Saudi Arabia; Sudan; Tajikistan; Tanzania; Trinidad and Tobago; Uganda and U.S. Virgin Islands. This has to be taken into account when interpreting the data. Source: UIS, July 2011

23 What are the national research densities? Researchers per million inhabitants, 2009 or latest available year: Asia Source: UIS, July –100 per million 101–300 per million 301–1000 per million 1001–2000 per million Data not available 2001 per million and above Note: Data in this map are based on FTE. However, figures in headcounts (HC) were considered for the following countries since the FTE figures were not available: Benin; Botswana; Cameroon; Central African Rep; Dem. Rep. of the Congo; Gabon; Gambia; Guinea; Libya; Mauritius; Sudan; Tanzania and Uganda. This has to be taken into account when interpreting the data. 0–100 per million 101–300 per million 301–1000 per million 1001–2000 per million Data not available 2001 per million and above

24 The gender gap in science. Women as a share of total researchers, 2009 or latest available year 0%–30% 30.1%–45% 45.1%–55% 55.1%–70% Data not available 70.1%–100% Source: UIS, July 2011Note: Data in this map are based on HC, except for Congo and India (based on FTE).

25 The gender gap in science. Women as a share of total researchers, 2009 or latest available year: Asia Source: UIS, July %–30% 30.1%–45% 45.1%–55% 55.1%–70% Data not available 70.1%–100% Note: Data in this map are based on HC, except for Congo (based on FTE). 0%–30% 30.1%–45% 45.1%–55% 55.1%–70% Data not available 70.1%–100%

26 Gender gap in research career? Proportion of women and men graduates in tertiary education and those employed as researchers, 2008 Source: UIS, October 2010

27 Gross Domestic Expenditure on R&D (GERD), South East Asia, 2009 or last available year CountryYear GERD ('000) – Local currencyGERD - PPP$ ('000) GERD – as % of GDP Brunei Darussalam* 20044,9256, Cambodia* 20028,357,0106, Hong Kong SAR, China ,833,0002,389, Laos PDR* 20026,560,0002, Indonesia* 20094,671,354,585801, Macao SAR, China* ,76624, Malaysia 20063,646,7002,090, Myanmar* 20029,122,008…0.16 Philippines 20077,556,360341, Thailand ,225,2531,116, Timor-Leste ………… Viet Nam 20021,032,560,900252, * Based on partial dataSource: UIS S&T Database, July 2011

28 Gross domestic expenditure on R&D (GERD) worldwide Source: UIS, August 2010 Figures are in Purchasing Power Parity Dollars (PPP$)

29 Gross domestic expenditure on R&D (GERD) worldwide Source: UIS, August 2010 Figures are in Purchasing Power Parity Dollars (PPP$)

30 Where are R&D investments made? Shares of world R&D expenditure (GERD) by principal regions, 2002 and 2007 (%) Source: UIS, August 2010

31 Worlds top 10 leaders in R&D investment GERD (000 PPP$), 2009 or latest available year Source: UIS, July 2011 Note: -1 = 2008.

32 A snap-shot of R&D intensity. Gross domestic expenditure on R&D (GERD) as a percentage of GDP, 2009 or latest available year 0.00%–0.25% 0.26%–0.50% 0.51%–1.00% 1.01%–2.00% Data not available 2.01% and above Source: UIS, July 2011

33 A snap-shot of R&D intensity. Gross domestic expenditure on R&D (GERD) as a percentage of GDP, 2009 or latest available year: Asia Source: UIS, July %–0.25% 0.26%–0.50% 0.51%–1.00% 1.01%–2.00% Data not available 2.01% and above 0.00%–0.25% 0.26%–0.50% 0.51%–1.00% 1.01%–2.00% Data not available 2.01% and above

34 R&D intensity (GERD as a % of GDP) by principal regions, 1990 – 2007 Sources: For 1990 – 2000, UIS estimates, For , UIS estimates, September 2009.

35 A breakdown of R&D investment in the Americas. GERD by sector of performance, 2009 or latest available year Source: UIS, July 2011Note: -1 = 2008, -2 = 2007, -5 = 2004, -7 = 2002.

36 A breakdown of R&D investment in Europe. GERD by sector of performance, 2009 or latest available year Source: UIS, July 2011Note: +1 = 2010, -1 = 2008, -2 = 2007.

37 A breakdown of R&D investment in Africa, Asia and the Pacific. GERD by sector of performance, 2009 or latest available year Source: UIS, July 2011Note: -1 = 2008, -2 = 2007, -3 = 2006, -4 = 2005, -5 = 2004, -7 = 2002, -8 = 2001.

38 1.2 Innovation Statistics: Why? Medium-term objective of the International Review of S&T Statistics & Indicators ; May provide information on the business sector in developing countries that R&D statistics wont supply; Many developing countries recently starting to carry out innovation surveys; UIS has a natural coordinating role as UN lead agency on S&T statistics.

39 The UIS strategy on Innovation Statistics Inventory of innovation surveys in developing countries; Pilot data collection (in 15 countries in June 2011); 2013: Regular data collection every two years; Online worldwide database; Analysis and publications; Capacity building and training activities; Methodological developments and survey help; In partnership with international and regional organisations (ASEAN, AU/NEPAD, Eurostat, OECD, RICYT, …). –Will be presented separately

40 2. Capacity building There are many problems: Lack of understanding of importance of S&T (indicators) Lack of political will and action Lack of coordination Lack of trained personnel High staff turnover

41 Capacity building (2) Measurement problems: Measuring real effort (full-time equivalents) Private sector R&D Budget data vs. surveys Role of foreign entities

42 S&T statistics workshops Increase the number of countries regularly producing quality S&T indicators. Create local capacities and establish sustainable local S&T statistics systems. Promote the use of S&T indicators for evidence-based S&T policy making. Share experiences with other developing countries and address problems. Gain knowledge about the particular characteristics of S&T statistics data. Demonstrate good practices in other countries of the region.

43 UIS S&T Statistics workshops 2005:Uganda, India 2006:Indonesia, Senegal, Kazakhstan 2007:Tunisia, FYR of Macedonia, Jordan, Russia, Cameroon 2008:Oman, Cambodia, Botswana 2009:Kenya, Egypt 2010:Mali, Syria, Jordan*, Uzbekistan, Ethiopia*, Nepal 2011:Grenada, Gabon, Azerbaijan*, Vietnam But also contributing to similar workshops of partner organisations (e.g. RICYT, NEPAD, other partner orgs)

44 Countries that have participated in UNESCO S&T statistics workshops Countries and territories not yet covered Countries and territories not targeted Countries and territories covered

45 Results of workshops Increased response rate – non-responding countries learn how to do it from UIS and neighbours. Immediate problems solved. Increased data quality – improved understanding of application of international standards. Face to face contacts = more effective networking. Inputs to UIS programme development.

46 3. Standard setting/methodological developments Measuring R&D in Developing Countries: Technical Guide and Annex to the Frascati Manual (2010) Will be presented separately Measuring Innovation in Developing countries: Annex to the Oslo Manual (2005) Will be presented separately Careers of Doctoral Holders – CDH (since 2004)

47 The careers of doctorate holders survey (CDH) A joint project with the OECD and Eurostat. Methodology developed from scratch. Aimed both at developed and developing countries. With participation from experts from both developed and developing countries. Promoting the methodology by encouraging developing countries to conduct such surveys and produce cross-nationally comparable statistics on careers of doctorate holders.

48 Relevance of the CDH project Focus on the crucial role of highly qualified individuals who represent a key to the production, application and transmission of knowledge. Statistics on the global trends in human resources for Science and Technology (HRST) very weak. Quality and comparability of international data on migration is particularly weak. Diversity of data collection methods hinders international comparability, and does not provide information on career paths and mobility patterns.

49 Objectives of CDH Objectives: To design an internationally comparable tool for tracking the careers of doctorates holders and highly qualified people in different countries. To collect and exchange information on the career paths of holders of doctorates from existing data sources and the new survey tool.

50 CDH modules Doctoral Education (EDU) Early Career Research positions (ECR) Employment situation (EMP) International mobility (MOB) Career-related experience (CAR) Personal characteristics (PER)

51 CDH toolkit Components: Model questionnaire and Instruction Manual Output tables and variables definitions Methodological guidelines Bridge table model questionnaire - output tables See: URL_DO=DO_TOPIC&URL_SECTION=201 and

52 4. Some publications Data publicly available at: (http://stats.uis.unesco.org/unesco/ReportFolders/R eportFolders.aspx?IF_ActivePath=P,54&IF_Langua ge=eng)http://stats.uis.unesco.org/unesco/ReportFolders/R eportFolders.aspx?IF_ActivePath=P,54&IF_Langua ge=eng UIS Fact Sheets UNESCO Science Report 2010 International Report on Science, Technology and Gender 2007 Planned: Global R&D e-publication 2011

53 Collaborations / Partnerships UNESCO HQs World Bank Eurostat AU-NEPAD ADB ATPS ISDB EU-Medibtikar IDRC (Canada) IRD (France) UNESCO offices worldwide OECD RICYT (Latin America) ALECSO Arab Academy of Science ISESCO Inter-Academy Council INRS (Quebec, Canada) ASEAN Centre for Social Innovation (ZSI), Austria ECO

54 Quality of data Efficient use of resources Consistency over time and space Accessibility and affordability Validity and reliability Comparability through standards Relevance to policy Potential for disaggregation Currency and punctuality Coherence across sources Clarity and transparency

55 Way forward There is still a lot to do! UIS needs to keep direct contact with statisticians: Quality and relevance. Countries to establish sustainable S&T statistics systems, involving line ministries (S&T Ministries or Research Councils) and National Statistical Offices. Looking forward to further cooperation.

56 Thank you!


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