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

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

UNESCO Institute for Statistics (UIS) Formerly UNESCO Division of Statistics Established in 1999 September 2001 - 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

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

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

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: http://www.uis.unesco.org 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

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

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

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

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.

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

Respondents to the UIS 2008 and 2010 questionnaires: South East Asia Country 2008Q 2010Q 1 Brunei Darussalam Data not provided 2 Cambodia 3 Hong Kong SAR, China Data provided 4 Laos PDR 5 Indonesia 6 Macao SAR, China 7 Malaysia 8 Myanmar 9 Philippines 10 Thailand 11 Timor-Leste 12 Viet Nam

UIS 2008 and 2010 Surveys on R&D: response rates & published data Regions (Countries and Territories covered) Effective responses Q 2008 Q 2010 Published data (by June 2011) Sub-Saharan Africa (45) 10 22% 26% 12 27% 30% 31 69% 70% Arab States-Africa (8) 4 50% 6 75% Asia (31, excl. Arab States & OECD) 15 48% 42% 16 52% 51% 24 77% 67% Arab States - Asia (12) 3 25% 5 Americas (14, excl. RICYT & OECD) 1 7% 0% 29% Europe (16, excl. OECD & Eurostat) 8 7 44% 11 Oceania (17, excl. OECD) 24% 18% Sub-total (143) 45 31% 84 59% Data from other sources:  OECD + Eurostat (45) 100% RICYT (25, incl. 10 Caribbean) 18 72% Total (213) 108 147 Note: Effective responses: number of returned questionnaires with data.

Researchers per million inhabitants (FTE) Researchers, South East Asia, 2009 or last available year Country Year Researchers (FTE) Researchers per million inhabitants (FTE) Brunei Darussalam* 2004 101.9 286 Cambodia* 2002 222.9 17 Hong Kong SAR, China 2009 19,283 2759 Laos PDR* 87 16 Indonesia* 21,275 90 Macao SAR, China* 389.9 734 Malaysia 2006 9,694.5 364 Myanmar* 837 18 Philippines 2007 6,957 78 Thailand 21,392 315 Timor-Leste … Viet Nam 9,328 116 Source: UIS S&T Database, July 2011 FTE: Full-time equivalent; * Based on partial data

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

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

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

Which countries host the greatest number of researchers Which countries host the greatest number of researchers? Number of researchers, 2009 or latest available year Source: UIS, July 2011 Note: -1 = 2008, -2 = 2007, -4 = 2005. Data in this graph are based on FTE data.

A breakdown of researchers in the Americas A breakdown of researchers in the Americas. Researchers by sector of employment, 2009 or latest available year Note: -1 = 2008, -2 = 2007, -5 = 2004, -6 = 2003, -7 = 2002. Data in this graph are based on FTE data (* based on HC data). Source: UIS, July 2011

A breakdown of researchers in Europe A breakdown of researchers in Europe. Researchers by sector of employment, 2009 or latest available year Note: +1 = 2010, -1 = 2008, -2= 2007. Data in this graph are based on FTE data (* based on HC data). Source: UIS, July 2011

A breakdown of researchers in Africa, Asia and the Pacific A breakdown of researchers in Africa, Asia and the Pacific. Researchers by sector of employment, 2009 or latest available year Note: -1 = 2008, -2 = 2007, -3 = 2006, -4 = 2005, -6 = 2002, -7 = 2001, -9 = 2000, -12 = 1997. Data in this graph are based on FTE data (* based on HC data). Source: UIS, July 2011

What are the national research densities 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

What are the national research densities What are the national research densities? Researchers per million inhabitants, 2009 or latest available year: Asia 0–100 per million 0–100 per million 101–300 per million 101–300 per million 301–1000 per million 301–1000 per million 1001–2000 per million 1001–2000 per million 2001 per million and above 2001 per million and above Data not available Data not available Source: UIS, July 2011 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.

The gender gap in science 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 2011 Note: Data in this map are based on HC, except for Congo and India (based on FTE).

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

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

GERD ('000) – Local currency Gross Domestic Expenditure on R&D (GERD), South East Asia, 2009 or last available year Country Year GERD ('000) – Local currency GERD - PPP$ ('000) GERD – as % of GDP Brunei Darussalam* 2004 4,925 6,268 0.04 Cambodia* 2002 8,357,010 6,816 0.05 Hong Kong SAR, China 2009 12,833,000 2,389,657 0.79 Laos PDR* 6,560,000 2,652 Indonesia* 4,671,354,585 801,398 0.08 Macao SAR, China* 132,766 24,640 Malaysia 2006 3,646,700 2,090,512 0.63 Myanmar* 9,122,008 … 0.16 Philippines 2007 7,556,360 341,231 0.11 Thailand 18,225,253 1,116,747 0.21 Timor-Leste Viet Nam 1,032,560,900 252,019 0.19 Source: UIS S&T Database, July 2011 * Based on partial data

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

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

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

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

A snap-shot of R&D intensity 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

A snap-shot of R&D intensity 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 0.00%–0.25% 0.00%–0.25% 0.26%–0.50% 0.26%–0.50% 0.51%–1.00% 0.51%–1.00% 1.01%–2.00% 1.01%–2.00% 2.01% and above 2.01% and above Data not available Data not available Source: UIS, July 2011

R&D intensity (GERD as a % of GDP) by principal regions, 1990 – 2007 Sources: For 1990 – 2000, UIS estimates, 2004. For 2002 -2007, UIS estimates, September 2009.

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

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

A breakdown of R&D investment in Africa, Asia and the Pacific 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 2011 Note: -1 = 2008, -2 = 2007, -3 = 2006, -4 = 2005, -5 = 2004, -7 = 2002, -8 = 2001.

1.2 Innovation Statistics: Why? Medium-term objective of the International Review of S&T Statistics & Indicators 2002-03; May provide information on the business sector in developing countries that R&D statistics won’t 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.

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

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

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

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.

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)

Countries that have participated in UNESCO S&T statistics workshops 2005-2011 Countries and territories covered Countries and territories not yet covered Countries and territories not targeted

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.

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) Careers of Doctoral Holders – CDH (since 2004)

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.

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.

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.

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

CDH toolkit Components: Model questionnaire and Instruction Manual Output tables and variables definitions Methodological guidelines Bridge table model questionnaire - output tables See: http://www.uis.unesco.org/ev.php?URL_ID=5219&URL_DO=DO_TOPIC&URL_SECTION=201 and www.oecd.org/sti/cdh

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

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

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

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.

Thank you! http://www.uis.unesco.org m.schaaper@unesco.org