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
Doha
Delhi
Dakar●
Bamako
Yaounde
Windhoek

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 S&T survey operation and data guardianship
Training in S&T statistics: workshops & other training activities
Standard setting and methodological developments
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 (
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
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

13. 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.

14. 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

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
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
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 = Data in this graph are based on FTE data.

19. 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 = Data in this graph are based on FTE data (* based on HC data).
Source: UIS, July 2011

20. 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= Data in this graph are based on FTE data (* based on HC data).
Source: UIS, July 2011

21. 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 = Data in this graph are based on FTE data (* based on HC data).
Source: UIS, July 2011

22. 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

23. 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.

24. 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).

25. 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).

26. 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

27. 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

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

31. World’s 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
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
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

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
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.

36. 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.

37. 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.

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 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.

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 2005-2011
Countries and territories covered
Countries and territories not yet covered
Countries and territories not targeted

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)
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:
and

52. 4. Some publications
Data publicly available at: (
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 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

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!