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Objectives of this presentation

UIS activities in the collection and analysis of STI indicators and o verview of data for West Africa. West African Regional Science, Technology and Innovation Policy Reviews and Statistics Workshop Bamako, Mali 10-13 May 2010. Objectives of this presentation.

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  1. UIS activities in the collection and analysis of STI indicators and overview of data for West Africa West African Regional Science, Technology and Innovation Policy Reviews and Statistics WorkshopBamako, Mali 10-13 May 2010

  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. 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 • UNESCO Reports: • UNESCO Science Report • UNESCO World Report - Towards Knowledge Societies • International Report on S&T and Gender

  4. UIS Strategy on S&T statistics • International Review of S&T Statistics and Indicators jointly with UNESCO Science Policy Division, 2002-03, involving all Member States and numerous experts. Resulting priorities: • Immediate term: • R&D personnel & expenditure • Human resources devoted to S&T • Science education & Higher education • International mobility • Gender • Medium term: Innovation data • Starts next month! • Longer term: Output & Impact

  5. UIS Medium-Term Strategy 2008-2013 Priorities: • Improving data quality • Reinforcing statistics and indicators on learning outcomes Strengthening statistics in science, culture and communication

  6. 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

  7. 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 • Next year pilot survey of innovation data

  8. Survey on Statistics of Science & Technology • Biennially. • The 2004, 2006 and 2008 S&T statistics surveys have been completed. 3rd round was launched in June 2008. • The latest results were released on the UIS website in September 2009 (see http://stats.uis.unesco.org). • 4th round will be launched in May 2010. • OECD and Eurostat provide data for their Member States. RICYT provides data for Latin America. UIS keeps direct contact with national S&T statisticians.

  9. Data collection 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 • New: by type of activity and field of science

  10. Other data of interest but not (yet?) collected by UIS • Researchers by age • Researchers by country of birth; citizenship/resident status • Researchers by fields of science at 2 digit level • R&D expenditure by type of cost (Current / Capital) • R&D expenditure by major socio-economic objective • Government budget appropriations or outlays for R&D (GBAORD): Total; by major socio-economic objective • Business enterprise researchers by industry / branch of economic activity (at 1 digit level of International Standard Industrial Classification, ISIC) • Business enterprise R&D expenditure by industry / branch of economic activity (at 1 digit level of ISIC)

  11. UIS 2006 and 2008 Surveys on R&DResponse rates & published data

  12. Respondents to the UIS 2006 and 2008 questionnaires from ECOWAS countries

  13. Number of researchers worldwide

  14. What are the national research densities? Researchers per million inhabitants, 2007 or latest available year 0–100 per million 101–300 per million 301–1000 per million 1001–2000 per million 2001 per million and above Data not available Note: Data in this map are based on FTE. However, figures in headcounts (HC) were considered for the following countries as the FTE figures were not available: Armenia; Azerbaijan; Bangladesh; Belarus; Benin; Botswana; Cameroon; Central African Rep.; Cuba; D.R. Congo; El Salvador; Gabon; Gambia; Georgia; Guinea; Jordan; Kazakhstan; Kyrgyzstan; Mauritius; Mongolia; Montenegro; Mozambique; Nauru; Nicaragua; Nigeria; Saint Lucia; Saint Vincent and the Grenadines; Saudi Arabia; Sudan; Tajikistan; Macedonia (FYR); Uganda; Venezuela; Zambia. This has to be taken into account when interpreting the data. Source: UIS, September 2009

  15. The gender gap in science.Women as a share of total researchers,2007 or latest available year 0%–30% 30.1%–45% 45.1%–55% 55.1%–70% 70.1%–100% Data not available Source: UIS, September 2009 Note: Data in this map are based on HC.

  16. Where are researchers located?Shares of world researchers by principal regions/countries, 2002 and 2007 (%) Source: UIS, September 2009

  17. R&D Personnel, selected countries in ECOWAS countries, 2007 or LYA Source: UIS S&T Database, March 2009. FTE: Full-time equivalent - HC: Headcount - * Based on partial data

  18. A snap-shot of R&D intensity.Gross domestic expenditure on R&D (GERD) as a percentage of GDP, 2007 or latest available year 0.00%–0.25% 0.26%–0.50% 0.51%–1.00% 1.01%–2.00% 2.01% and above Data not available Source: UIS, September 2009

  19. Which regions are most R&D intensive?Gross domestic expenditure on R&D (GERD) as a % of GDP by principal regions/countries, 2007 or latest year available Source: UIS, September 2009 Notes: -1 = 2006, -2 = 2005

  20. The evolution of R&D intensityGERD as a percentage of GDP, 1996 (or earliest available year) and 2007 (or latest available year), countries with R&D intensity below 1.5% in both years. Source: UIS, September 2009

  21. GERD by region

  22. Where are R&D investments made?Shares of world R&D expenditure (GERD) by principal regions/countries, 2002 and 2007 (%) Source: UIS, September 2009

  23. Gross Domestic Expenditure on R&D (GERD), selected countries in ECOWAS countries, 2007 or LYA Source: UIS S&T Database, March 2009 * Based on partial data

  24. Funding in Africa, Asia and the Pacific.GERD by source of funds, 2007 or latest available year Source: UIS, September 2009 Notes: -1 = 2006, -2 = 2005, -3 = 2004, -5 = 2002, -6 = 2001

  25. Funding in Europe.GERD by source of funds, 2007 or latest available year Source: UIS, September 2009 Notes: -1 = 2006, -2 = 2005, -3 = 2004, -4 = 2003, -5 = 2002

  26. Funding in the Americas.GERD by source of funds, 2007 or latest available year Source: UIS, September 2009 Notes: -1 = 2006, -2 = 2005, -3 = 2004, -5 = 2002, -9 = 1998.

  27. A breakdown of R&D investment in Africa, Asia and the Pacific. GERD by sector of performance, 2007 or latest available year Source: UIS, September 2009 Notes: -1 = 2006, -2 = 2005, -3 = 2004, -5 = 2002

  28. A breakdown of R&D investment in Europe.GERD by sector of performance, 2007 or latest available year Source: UIS, September 2009 Notes: -1 = 2006, -3 = 2004

  29. A breakdown of R&D investment in the Americas.GERD by sector of performance, 2007 or latest available year Source: UIS, September 2009 Notes: -1 = 2006, -2 = 2005, -3 = 2004, -5 = 2002

  30. 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

  31. 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

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

  33. 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.

  34. UIS S&T Statistics workshops 2005: Uganda, India 2006: Indonesia, Senegal, Kazakhstan 2007: Tunisia, FYR of Macedonia, Jordan, Brazil, Russia, Cameroon 2008: Oman, Cambodia 2009: Kenya, Egypt But also contributing to similar workshops of partner organisations (e.g. RICYT, NEPAD)

  35. Countries that have participated in UNESCO S&T statistics workshops 2005-2009 Countries and territories covered Countries and territories covered but absent Countries and territories not yet covered Countries and territories not targeted

  36. 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.

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

  38. 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.

  39. Relevance of the CDH project • There is a new 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) are very week. • The 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.

  40. 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.

  41. 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

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

  43. 4. Some publications • Data publicly available at: www.uis.unesco.org • UIS Publications (can be downloaded from the UIS website): • S&T Bulletin 1 – Investment in R&D; • S&T Bulletin 2 – Bibliometric Indicators; • S&T Bulletin 3 – Women in Science • Fact sheet: R&D statistics (recently updated) • UNESCO Science Report 2005 (next edition: 2010) • International Report on Science, Technology and Gender 2007 • UNESCO World Report • History of Science Statistics at UNESCO • Paper on ‘current status of International Science statistics for Africa’ in African Statistical Journal

  44. 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 Collaborations / Partnerships

  45. Collaboration with AU/NEPAD • MOU between AU/NEPAD and UIS • Attend each other’s meetings • Separate data collection for now • Closer collaboration over the next few years

  46. Way forward • There is still a lot to do! • Looking forward to further cooperation. • 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.

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

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