1. 1 Grouping Countries by National Models of Technological Learning Tatyana P. Soubbotina Consultant, S&T Program HDNED Presentation to STI Thematic Group November 10, 2005 TSoubbotina@comcast.net

2. 2 Practical Questions: 1. Should the WB develop some standard guidelines on S&T assistance to client countries? 2. Should these guidelines be customized for groups of developing countries with similar STI capacity- building needs? 3. Should the WB rely on one of the existing classifications of countries by S&T capacity or develop some new approach?

3. 3 Composite Indices of S&T Capacity: UNDP – Technology Achievement Index UNIDO – Competitive Industrial Performance Index WEF – National Innovative Capacity Index WB – Knowledge Economy Index UNCTAD –Innovation Capability Index Francisco Sagasti – S&T Capacity Index

4. 4 UNDP – Technology Achievement Index Human skills Diffusion of old innovations Diffusion of new innovations Creation of technology Mean years of schooling + Tertiary enrolment in science, math and engineering Electricity consumption per capita + Telephones per capita Internet hosts per capita + High- and medium-tech exports as % of total exports Patents granted per capita + Receipts of royalty and license fees from abroad per capita

5. 5 UNIDO - Competitive Industrial Performance Index 1. Manufacturing value added (MVA) per capita 2. Manufactured exports per capita 3. Share of medium and high-tech activities in MVA 4. Share of medium and high-tech products in manufactured exports

6. 6 WEF – National Innovative Capacity Index 1. Share of scientists and engineers in population 2. Innovation policy 3. Cluster innovation environment 4. Innovation linkages 5. Operations and strategy

7. 7 WB – Knowledge Economy Index Economic incentive & institutional regime Education and human resources Innovation system ICT infra- structure Tariff & non- tariff barriers Adult literacy rate Number of researchers in R&D Telephones per 1,000 population Regulatory quality Secondary enrolment rate Patent applications granted by USPTO Computers per 1,000 population Rule of lawTertiary enrolment rate S&T journal articles Internet users per 1,000 population

8. 8 UNCTAD –Innovation Capability Index Human capital Index Technological Activity index Literacy rate as % of population X 1 R&D personnel per million population Secondary school enrolment as % of age group X 2 US patents granted per million population Tertiary enrolment as % of age group X 3 Scientific publications per million population

9. 9 F. Sagasti – S&T Capacity Index SCIENCETECHNOLOGYPRODUCTION Internal capacity: R&D expenditure as % of GDP Number of scientists & engineers per million people High-tech exports as % of total exports External linkages: Number of scientific publications (in log.) Number of patent applications by residents and non- residents (in log.) Infrastructure, communications, and technology index

10. 10 Different S&T indices can be used depending on the task Because they all have different focuses: UNCTAD – underlying technological capacity (focus on inputs – education and R&D) UNIDO – revealed technological capacity in industry only (focus on manufacturing competitiveness) UNDP – revealed technological capacity across the economy (focus on broad diffusion of old and new technologies) WEF – institutional and policy environment for innovation WB KAM – the advantage is in its flexibility, select indicators at your own risk!

11. 11 Considerations in selecting S&T capacity indicators Select input or output indicators depending on whether you want to measure technological effort or technological achievement, underlying (potential) technological capacity or revealed S&T capacity. Absolute size of inputs can matter no less than input intensity because of economies of scale and critical mass effect (e.g. Number of researchers or Total R&D expenditure vs. their shares in population and GDP) Some indicators reflect present-time capacity, others reflect expected but still uncertain future capacity (e.g. Mean years of education of adults vs. Secondary and tertiary enrolment rates) Indicators of knowledge sales (e.g. Share of high-tech exports or Receipts of royalty and license fees) reflect quality of knowledge rather than just its quantity (e.g. as reflected by Share of high-tech industries in MVA or Number of patent applications). However, exports indicators should be compared to similar MVA indicators, because fast improvement in exports often reflects enclave FDI activities rather than national S&T capacity growth.

12. 12 Country rankings on 3 indices differ quite radically UNCTAD (117 countries) UNIDO (87 countries) UNDP (72 countries) China723745 Russia2344- Malaysia672230 Mexico592332 Philippines602544 Singapore30110 Sweden173

13. 13 All of these groupings focus on S&T levels achieved or expected to be achieved by various countries, but fail to account for: Different speed of S&T progress, and Different sources of S&T progress. That is what grouping countries by models of S&T learning can add

14. 14 Concept of “National technological learning” National technological learning is the process of creating or acquiring from foreign sources of new (for this particular learner) S&T knowledge & skills, as well as adapting, disseminating, and using those for improving the technological structure of national production and exports.

15. 15 National technological learning occurs at all levels and implies acquiring different kind of knowledge & skills, e.g. at the level of national labor force – science, math, & engineering education & training + life-long learning, enterprises & firms – learning to innovate by absorbing foreign and investing in own new technologies, governments – learning to receive expert advice, develop S&T strategies and create enabling & stimulating conditions for national technological progress.

16. 16 Factors of national technological learning S&T learning capacity S&T learning opportunities Knowledge generation capacity Capital imports Inward FDI Internet Licensing S&T co- operation + Knowledge absorption capacity Education R&D

17. 17 “Crystals of S&T Learning” - graphical/statistical illustrations

18. 18 “Crystals of S&T Learning” - graphical/statistical illustrations Human capital accumulated / human capability for S&T learning (see indicators 11, 12, 1), The most accessible opportunities for learning from foreign sources created by capital goods imports and FDI (indicators 9, 10), The more demanding opportunities for learning from domestic and foreign sources through domestic R&D (indicators 2, 3), The most demanding opportunities for learning through knowledge markets and international S&T cooperation (indicators 4, 5, 6), Success in using S&T knowledge for improving technological structures of a country’s MVA and manufactured exports (indicators 7, 8).

19. 19 ‘Crystals’ can ‘grow’, but only in the right (learning) environment

20. 20 6 models of national technological learning: Traditionalist slow learning, Passive FDI-dependent, Active FDI-dependent, Autonomous, Creative-isolated, Creative-cooperative.

21. 21 Traditionalist slow S&T learning Relying mostly on traditional technologies, low S&T learning capacity, minimal S&T learning opportunities, low international competitiveness, high risk of further economic marginalization, most urgent need of international S&T assistance.

22. 22 ‘Crystals’ of sample Slow-Learning Countries

23. 23 Passive FDI-dependent learning passively relying on FDI to bring in new technologies, low S&T learning capacity, no or week government technological strategy, limited opportunities for technological learning, high risk of losing in economic competition with poorer, lower-wage countries.

24. 24 Active FDI-dependent learning relatively high S&T learning capacity, active government strategy aimed at building national human capital and accelerating national technological learning from FDI, active targeting of the most beneficial FDI, much wider opportunities for technological learning from FDI, lower risk of losing in economic competition with lower-wage but lower-skill countries.

25. 25 Crystals of sample Passive and Active FDI-dependent learners

26. 26 Autonomous S&T learning High S&T learning capacity and favorable international environment, active government strategy aimed at building national human capital and accelerating national technological learning via open sources, foreign consultants, contract manufacturing, licensing, copying & re-engineering, own R&D, even outward FDI, minimal reliance on FDI or international S&T cooperation, aspiring to compete with technological leaders.

27. 27 Creative-cooperative S&T learning Capacity for both, generating and absorbing S&T knowledge among the highest in the world, global technological leadership in at least some niches of the global economy, active government S&T strategy directly linked to global competitiveness strategy, extensive R&D and efficient NIS, active participation in and control over international S&T cooperation, the fastest S&T learning.

28. 28 Creative-isolated S&T learning High S&T learning capacity, but unfavorable international environment or isolationism, limited opportunities for S&T learning from foreign sources, aspiring to produce most of the needed technologies inside the country, low international competitiveness of high-tech industries, high risk of lagging further behind in technological and economic development.

29. 29 Sample crystals of Autonomous, Creative-Cooperative, & Creative-Isolated learners

30. 30 ‘Rules’ of national technological learning National S&T learning requires a certain minimal stock of human capital and a favorable economic & institutional ‘learning environment’. Government S&T policies and international aid should target both prerequisites. Different models of S&T learning can be also seen as consecutive stages in the same country’s development (‘crystals’ are growing from 9 a.m. to 6 p.m.). But there are some policy choices, e.g. active FDI- dependent vs. autonomous and creative-isolated strategies. The higher a country’s underlying S&T capacity, the broader its choice of S&T learning strategies.

31. 31 ‘Tree’ of national technological learning Slow learning Passive FDI- dependent Creative- cooperative Aid supported Creative- isolated Autonomous Active FDI- dependent Time Human capital accumulation

32. 32 5 major learning paths: 1.From slow-learning traditionalism to passive and active FDI-dependent learning, 2.From passive FDI-dependent to active FDI- dependent or autonomous, 3.From active FDI-dependent to more autonomous or creative-cooperative, 4.From autonomous to creative-cooperative, 5.From creative-isolated to creative-cooperative learning.

33. 33 Prioritization Table of Policies for Transitioning from Non-learning Traditionalism to Passive/Active FDI-dependent S&T Learning

34. 34 Prioritization Table of Policies for Transitioning from Passive to Active FDI-dependent S&T Learning

35. 35 How to help the majority of slow-learning countries? What should be the main features of international aid-supported S&T learning? What can be learned from previous international aid projects with S&T components? What should be the role of the World Bank in these countries?

36. 36 ‘Crystals’ assessment – Modified indicators for SSA

37. 37 The advantages of S&T Learning Models approach compared to any S&T capacity indices are that it 1.Looks forward, helps predict future difficulties, 2.Allows for diversity of learning paths, 3.Underlines the importance of policy choices made by developing countries themselves.

38. 38 “First of all, I think that sense of assuming responsibility [by developing country governments] is really critical. We often talk about building institutions or building capacity. And my feeling is that sort of suggests you can come in like an outside contractor and bring some bricks and mortar and you construct capacity. It doesn't work that way. You grow it. Its got to be indigenous. It's got to have indigenous roots. You can fertilize it. You can water it. You can rip the weeds out, which I think is part of fighting corruption. Or you can help people do it. But they need to do it themselves.” Paul Wolfowitz on ‘capacity building’ vs. ‘capacity growing’ at his first Town Hall Meeting in the World Bank, 2005.

39. 39 School teachers and university professors know the advantages of active teaching and learning methods. Should the World Bank aim to help all client countries turn into active learners of modern science and technology?

40. 40 Models of S&T Learning approach is an alternative to Regional models of development – e.g. East Asian vs. Latin American “High-tech” model vs. low-tech “Latin” model

41. 41 “High-tech” success stories are obviously too different to be treated as one model Source: W.F. Maloney. 2005. Patterns of Innovation. Innovation Policies II Regional Study, World Bank.

42. 42 Further improvements to ‘crystals’ indicators are needed, e.g. A brain drain/brain gain statistics instead of ‘brain retention’ survey results Taking into account strong economies of scale and ‘critical mass’ effect in R&D A better indicator of benefits from participation in cross-border R&D cooperation Building data bases for historical and sub-national crystals of S&T learning

43. 43 Practical application of ‘crystals’ assessment Is the country’s S&T learning likely to be fast enough compared to its major competitors? Is national S&T learning constrained mainly by the lack of human capital or the lack of learning opportunities? Which additional learning opportunities could be available but are currently underused? How successful is this country in using its S&T capacity for improving technological structure of its production and exports?

44. 44 ‘Crystals’ assessment – Mauritius

45. 45 ‘Crystals’ assessment – Malaysia

46. 46 Is there a need in an on-line interactive data base and an automatic graphing tool? (similar to KAM)

47. 47 ‘Crystals’ for further discussion: Creative-cooperative leaders

48. 48 ‘Crystals’ for further discussion: high-income Slow learners

49. 49 ‘Crystals’ for further discussion: former Creative-isolated learners