National Innovation Systems NIS and Innovationled Growth in

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슘페터학파의 국가혁신체제론과 한국의 혁신성장 National Innovation Systems (NIS) and Innovation-led Growth in Korea 이근

슘페터학파의 국가혁신체제론과 한국의 혁신성장 National Innovation Systems (NIS) and Innovation-led Growth in Korea 이근 Keun Lee Professor Economics, Seoul National University Editor, Research Policy Former President, Int’l Schumpeter Society Council Member, World Economic Forum

Neo-Schumpeterian Perspective: National Innovation systems (NIS) Nelson; Lundval (1992): defines NIS = elements and

Neo-Schumpeterian Perspective: National Innovation systems (NIS) Nelson; Lundval (1992): defines NIS = elements and relationships 1) which interact in the production, diffusion and use of knowledge 2) rooted inside the borders of a nation state. ’ It is about efficiency in acquisition, creation, diffusion, and utilization of knowledge. -> The differences in NIS determines competitiveness of nations and their economic growth -> System Failure (시스템 실패: 지식의 암묵성) cf) Market failure (시장실패; 지식이 공공재) 3

Innovation systems at 3 Levels: country; Sector; firm => 2014 Schumpeter Prize

Innovation systems at 3 Levels: country; Sector; firm => 2014 Schumpeter Prize

5 Variables to measure the NIS (Lee 2013); Using US PTO (미국 특허 자료:

5 Variables to measure the NIS (Lee 2013); Using US PTO (미국 특허 자료: NBER +) 지식생산의 토착화 Localization( Intra-national creation and diffusion) of Knowledge (vs. reliance on foreign sources) 집중도Balanced vs. Concentration of knowledge creation (by assignees) 장/단주기의 특화Technological specialization 1 (short vs. long cycle technologies) Knowledge Combination /Convergence (by citing and combining widely) (formerly called originality of technologies 융복합도=독창성) 기술적 다각화Technological Diversification (Wide vs. Deep in patent portfolio) 5

12 Specializing in terms of Cycle Time of Technologies: 한국의 급속한 경제추격의 비밀= 단주기기술에

12 Specializing in terms of Cycle Time of Technologies: 한국의 급속한 경제추격의 비밀= 단주기기술에 특화 11 10 9 Short cycles by Korea and Taiwan 8 7 6 1975 1980 1985 1990 High Income countries Middle Income countries Korea and Taiwan Brazil and Argentina 1995 6

Why getting into Short Cycle Technologies matters Cycle time = speed of change in

Why getting into Short Cycle Technologies matters Cycle time = speed of change in the knowledge base of a technology = mean citation lag = time difference between the application year of the citing patent and of the cited patents “To catch up, specialize in Short cycle technology-based sectors“ because old knowledge quickly obsolete/useless + new knowledge tend to emerge more often -> less disadvantageous for the latecomers => technological sectors with less reliance on the old technologies but with greater opportunity for emergence of new technologies 7

Getting into Short cycles -> rapid localization -> Domestic Value chains &diversification 8

Getting into Short cycles -> rapid localization -> Domestic Value chains &diversification 8

Top 10 Classes of G 5 1 2 3 4 5 6 7 8

Top 10 Classes of G 5 1 2 3 4 5 6 7 8 9 10 Korea. Taiwan Class Name 514 428 73 123 424 210 435 250 264 324 Drug, Bio-Affecting and Body Treating Compositions Stock Material or Miscellaneous Articles Measuring and Testing Internal-Combustion Engines Drug, Bio-Affecting and Body Treating Compositions Liquid Purification or Separation Chemistry: Molecular Biology and Microbiology Radiant Energy Plastic & Nonmetallic Article Shaping or Treating Electricity: Measuring and Testing Class 1 2 3 4 5 6 7 8 9 10 vs Korea-Taiwan ->no overlap 438 348 439 257 362 280 365 70 360 482 Class Name Semiconductor Device Manufacturing: Process Television Electrical Connectors Active Solid-State Devices ( Transistors, Solid-State Diodes) Illumination Land Vehicles Static Information Storage and Retrieval Locks Dynamic Magnetic Information Storage or Retrieval Exercise Devices Patent count 10349 3883 3789 3479 3389 2853 2852 2639 2349 2325 Patent count 1189 712 408 374 355 346 340 313 311 9

Localization = Intra-national Citation in Patents (~self-citation, national) Localization of Knowledge creation & diffusion

Localization = Intra-national Citation in Patents (~self-citation, national) Localization of Knowledge creation & diffusion 0. 12 0. 1 0. 08 Korea & Taiwan 0. 06 Into short cycles = Period of increasing domestic value chains, reducing GVC 0. 04 0. 02 0 1975 1980 1985 1990 1995 High Income countries Middle Income countries Korea and Taiwan Brazil and Argentina 10

Regressing growth onto National Innovation systems: Asian 4 as benchmark Asian 4 High Income

Regressing growth onto National Innovation systems: Asian 4 as benchmark Asian 4 High Income middle Inc. Tech cycle time World (-)* (+)* Localization of knowledge + (+)* Originality + + (-)* (+)* (+) * HH: inventor concentration Asian 4 Dummy Controls: Initial income, Population, Investment, secondary enrollment Shorter cycle leading to growth in Asian 4 (Lee 2013)

Korean Detour from Short to long cycle technologies 2 nd 1 st in the

Korean Detour from Short to long cycle technologies 2 nd 1 st in the mid 80 s: to short cycle sectors in the 2000 s: to long cycle sectors; ex. Samsung’s biosimilar 2 Tech. turning point 10. 00 9. 00 8. 00 7. 00 Telephone switches 6. 00 5. 00 4. 00 3. 00 Steel & Automobiles Apparel & textiles Memory chips Medicine & Basic Science Cell Phones 2. 00 1. 00 Digital TVs 19 75 19 76 19 77 19 78 19 79 19 80 19 81 19 82 19 83 19 84 19 85 19 86 19 87 19 88 19 89 19 90 19 91 19 92 19 93 19 94 19 95 19 96 19 97 19 98 19 99 20 00 20 01 20 02 20 03 20 04 20 05 0. 00 12

NIS in 4 European Countries and Korea (Lee et al 2016)

NIS in 4 European Countries and Korea (Lee et al 2016)

Italy = longest Cycle time (machineries) = good for profitability Korea = shortest cycle

Italy = longest Cycle time (machineries) = good for profitability Korea = shortest cycle time = vehicle for late entry and catch-up average Cycle time 14 13 12 11 10 9 8 7 6 2007 2008 2009 Germany 2010 France 2011 2012 U. K. 2013 Italy 2014 Korea 2015 2016

UK = lowest localization = highest internationalization Germany = high; Korean rapid catch-up Intra-national

UK = lowest localization = highest internationalization Germany = high; Korean rapid catch-up Intra-national diffusion of knowledge =localization 0. 19 0. 17 0. 15 0. 13 0. 11 0. 09 0. 07 0. 05 2006 2007 2008 2009 Germany 2010 France 2011 2012 U. K. 2013 Italy 2014 Korea 2015 2016

Concentration of Innovation in Korea vs. Balanced in Europe HHI of assignee concentration 0.

Concentration of Innovation in Korea vs. Balanced in Europe HHI of assignee concentration 0. 3 0. 25 0. 2 0. 15 0. 1 0. 05 0 2006 2007 2008 Germany 2009 2010 France 2011 2012 U. K. 2013 Italy 2014 Korea 2015 2016

Germany = most diversified; Italy = least diversified (not ready for 4 IR? )

Germany = most diversified; Italy = least diversified (not ready for 4 IR? ) Tech. diversification (No. of patented sectors divided by 438) 0. 9 0. 85 0. 8 0. 75 0. 7 0. 65 0. 6 0. 55 0. 45 0. 4 2006 2007 2008 2009 Germany 2010 France 2011 2012 U. K. 2013 Italy 2014 Korea 2015 2016

Combination of Knowledge (from wider fields) =originality = 융복합도 (readiness for 4 IR 4차혁명

Combination of Knowledge (from wider fields) =originality = 융복합도 (readiness for 4 IR 4차혁명 적합도): UK, Germany highest; Korea lowest 한국 최저: Knowledge combination/ Originality 0. 6 0. 55 0. 45 0. 4 0. 35 0. 3 2006 2007 2008 Germany 2009 2010 France 2011 2012 U. K. 2013 Italy 2014 2015 Korea 2016

4차산업혁명 (4 IR) 기술과 3차혁명 (3 IR) 기술의 특성 비교, US patent data: 4차기술이

4차산업혁명 (4 IR) 기술과 3차혁명 (3 IR) 기술의 특성 비교, US patent data: 4차기술이 융복합도 높고, 일반성 낮음 (서로 반대) 4 IR Technologies 3 D printing Io. T Cloud computing Big data AI Average 융복합도 Originality 0. 60 0. 56 0. 51 0. 47 0. 55 0. 54 일반성 Generality 0. 37 0. 31 0. 35 0. 29 0. 37 0. 34 Generality 0. 64 0. 75 0. 61 0. 68 0. 70 0. 68 누적성 cumulativeness 0. 23 0. 45 0. 56 0. 47   cumulativeness 0. 56 0. 45 0. 56 0. 31 0. 56 0. 49 전유성 appropriability 0. 06 0. 05 0. 08 0. 07   appropriability 0. 08 0. 05 0. 08 0. 04 0. 08 0. 07 3 IR Technologies ASIC Internet Memory chips Mobile phone Personal computer Average Originality 0. 40 0. 39 0. 41 0. 43 0. 52 0. 43 Two-sample t test (H 0: NT-OT=0) 2. 41*** -13. 47*** -0. 12 0. 36

Summary of NIS by countries 1) Italy: longest cycle time-based technologies (good for profit

Summary of NIS by countries 1) Italy: longest cycle time-based technologies (good for profit & growth) but low degree of tech. diversification, lower degree of knowledge localization, and medium level of combination 2) UK: highest originality and longer cycle tech but less diversified; lowest intra-national diffusion. -> maybe, better to try to increase intra-national diffusion (which is lower than Korea); a bit more diversification. 3) Germany: highest diversification and highest localization relatively high combination and medium cycle time 4) Korea: highest localization and concentration = nationalistic and big business led NIS has still yet to catch up in terms of longer cycle tech, diversification, less concentration (too much by Samsung; too Few by SMEs); 5) France = Always in the middle; no clear-cut distinction

Country’s Readiness for 4 th IR 1) Korea short cycle-tech & Big business based

Country’s Readiness for 4 th IR 1) Korea short cycle-tech & Big business based catch-up mode of NIS; -- low readiness for 4 th = lowest combination/fusion IR; medium diversification; highest concentration by BB 2) Italy = long cycle tech. and Medium sized firm based NIS ; good basis for profitable growth; but lower readiness for 4 th IR (low combination and lowest diversification) 3) Germany = best ready for 4 th IR (highest diversification; high combination and fusion) 4) UK = ready for 4 IR with highest combination but needs to be more diversified 21

Long Term Evolution of NIS around the world (Lee and Lee 2019; J of

Long Term Evolution of NIS around the world (Lee and Lee 2019; J of Evolutionary Economics)

Clustering of NIS by 5 variables (normalized, 2010 -2017): Developed, Developing (MICs), and Catching-up

Clustering of NIS by 5 variables (normalized, 2010 -2017): Developed, Developing (MICs), and Catching-up NIS (Lee & Lee 2018) NIS Less Concentration localization Tech. Combination relative cycle diversification /originality time Developed NIS 0. 9327 0. 6760 0. 8381 0. 6399 0. 7222 Developing (MICs) NIS 0. 2960 0. 0802 0. 0588 0. 5846 0. 8683 Catching-up NIS 0. 3316 0. 6598 0. 7507 0. 1259 0. 1322 v Developed (mature) NIS = all high scores v Developing NIS = long cycle, high originality but very low localization/diversification v Catching up NIS = short cycle and low originality but high localization/diversification 23

The 3 NIS compared (Lee and Lee 2019): catch-up NIS = detour for the

The 3 NIS compared (Lee and Lee 2019): catch-up NIS = detour for the Dev’d (mature) NIS Developed NIS: NIS All indices are high. Middle-income NIS Catching-up NIS 0

Dynamic Change of the NIS over time: why the detour makes sense; emergence of

Dynamic Change of the NIS over time: why the detour makes sense; emergence of the Catching-up NIS: Cluster Analysis ( Lee & Lee 2018) Period G 1 G 2 (MICs) Argentina Malaysia Brazil China Denmark Finland Hong Kong 1996 -1999 Argentina Brazil China Denmark Finland Hong Kong India 1988 -1991 2004 -2007 2008 -2011 India Mexico Norway Singapore South Korea Taiwan Malaysia Mexico Norway Singapore Thailand  - Argentina Brazil Chile China Denmark Hong Kong India Malaysia Mexico Norway Singapore Thailand  - Argentina Brazil Chile Denmark Hong Kong India Malaysia Mexico Norway Singapore Thailand G 3 G 4 (EU 4) G 5 (Catch-up) G 6 G 7 Chile Thailand France Germany Italy, UK Sweden -  Japan US Chile France Germany Italy, UK Sweden South Korea Japan Taiwan US -  France Germany Italy, UK Sweden Finland South Korea Japan Taiwan US  - France Germany Italy, UK Sweden China Finland South Korea Taiwan Japan US

NIS around the world: Average using the 2011~15 values Silicon Valley United States Japan

NIS around the world: Average using the 2011~15 values Silicon Valley United States Japan Germany United Kingdom France Italy Israel Denmark Norway Taiwan South Korea Sweden China Brazil Mexico Finland India Hong Kong Singapore Chile Malaysia Beijing Shenzhen Argentina Thailand Russia ① 1 -HHI ② Localization ③ Diversification 0. 99 0. 98 0. 99 0. 97 0. 85 0. 82 0. 94 0. 96 0. 93 0. 77 0. 96 0. 92 0. 94 0. 92 0. 96 0. 85 0. 91 0. 82 0. 89 0. 69 0. 25 0. 41 0. 14 0. 07 0. 11 0. 09 0. 07 0. 08 0. 13 0. 14 0. 10 0. 05 0. 02 0. 01 0. 10 0. 03 0. 04 0. 01 0. 04 0. 05 0. 04 0. 01 0. 04 0. 63 0. 94 0. 87 0. 84 0. 69 0. 73 0. 61 0. 43 0. 37 0. 27 0. 67 0. 71 0. 57 0. 64 0. 16 0. 10 0. 42 0. 24 0. 29 0. 32 0. 04 0. 08 0. 36 0. 39 0. 03 0. 10 ④ Knowledge combination 0. 51 0. 50 0. 35 0. 46 0. 45 0. 40 0. 41 0. 50 0. 43 0. 48 0. 33 0. 34 0. 39 0. 33 0. 39 0. 43 0. 37 0. 39 0. 44 0. 43 0. 40 0. 39 0. 33 0. 39 0. 47 0. 42 ⑤ Relative Cycle Time 0. 87 1. 00 0. 94 1. 11 1. 16 1. 08 1. 16 1. 04 1. 17 1. 20 0. 83 0. 85 0. 99 0. 85 1. 24 1. 22 0. 98 1. 06 0. 98 0. 89 1. 18 1. 13 0. 8 0. 9 1. 14 1. 11 0. 93 NIS 5 =①+②+③+④+⑤ 3. 69 3. 55 3. 53 3. 36 3. 31 3. 25 3. 04 3. 02 2. 93 2. 88 2. 87 2. 82 2. 76 2. 74 2. 68 2. 67 2. 66 2. 60 2. 56 2. 52 2. 51 2. 44 2. 39

Both NIS & Complexity significant to Economic growth (Lee and Lee 2019: J. of

Both NIS & Complexity significant to Economic growth (Lee and Lee 2019: J. of Evolutionary Economics) Dependent: 4 year average of annual growth of GDP per capita (1) 83~15 (2) 83~99 (3) 99~15 b t b t -0. 056*** -8. 29 -0. 11*** -4. 56 -0. 083*** -6. 77 Growth rate of population -0. 93** -2. 52 -0. 71 -0. 67 -1. 12 -1. 3 Fixed capital investment per GDP 0. 25*** 5. 67 0. 36*** 4. 08 0. 36*** 4. 11 Enrollment: secondary education 0. 0098 0. 81 0. 072*** 3. 76 0. 002 0. 17 NIS 4 0. 053*** 4. 24 0. 058*** 3. 68 0. 057** 2. 2 ECI (Econ. Complexity) 0. 013** 2. 55 0. 0035 0. 2 0. 016** 2. 38 Constant 0. 39*** 7. 86 0. 78*** 4. 01 0. 63*** 6. 97 adj. R-sq 0. 28   0. 36   0. 35   Observations 294   135   159   Groups 40   38   40   49. 02***   33. 28***   35. 99***   Log of initial GDP per capita Hausmann v NIS 5 = Localization + decentralization + Originality + Diversification + Relative cycle time 27

10. 00 한국 혁신성장의 방향: 단주기 short cycle에서 장주기long cycler기술 기반산업으로 이행해야 2 Tech.

10. 00 한국 혁신성장의 방향: 단주기 short cycle에서 장주기long cycler기술 기반산업으로 이행해야 2 Tech. turning point 9. 00 8. 00 Short 7. 00 Long 6. 00 5. 00 4. 00 Apparel & textiles 3. 00 Long Telephone switches Steel & Automobiles Medicine & Basic Science Memory chips Cell Phones 예) 바이오시밀러 2. 00 Digital TVs 1. 00 19 75 19 76 19 77 19 78 19 79 19 80 19 81 19 82 19 83 19 84 19 85 19 86 19 87 19 88 19 89 19 90 19 91 19 92 19 93 19 94 19 95 19 96 19 97 19 98 19 99 20 00 20 01 20 02 20 03 20 04 20 05 0. 00

Cambridge Univ. Press, 2019/03 The Art of Economic Catch-up: Barriers, Detours and Leapfrogging in

Cambridge Univ. Press, 2019/03 The Art of Economic Catch-up: Barriers, Detours and Leapfrogging in Innovation systems

References (www. keunlee. com) • Lee, Keun, 2013 , Schumpeterian Analysis of Economic Catch-up:

References (www. keunlee. com) • Lee, Keun, 2013 , Schumpeterian Analysis of Economic Catch-up: Knowledge, Path-creation and middle income trap, Cambridge Univ. Press • Lee, Keun, 2019, The Art of Economic Catch-up: barriers, detours and leapfrogging in innovation systems, Cambridge U. Press. • Lee, K. , and F. Malerba. (2018). "Economic Catch-up as Evolutionary Process. " in Nelson, R. R. (Eds), Modern Evolutionary Economics: An Overview. Cambridge: Cambridge University Press. • ____. (2017). "Catch-up Cycles and Changes in Industrial Leadership: Windows of Opportunity and Responses of Firms and Countries in the Evolution of Sectoral Systems. " Research Policy, 46(2): 338351. • Lee, Keun, and J. Lee, 2019 “NIS, economic complexity, and economic growth, ” Journal of Evolutionary Economics, forthcoming. • Lee, Keun Lee, et al. 2016. "The National Innovation System (NIS) for the Catch-up and Post-Catchup Stages in South Korea. " in Choi, J. et al, Eds. The Korean Government and Public Policy in Development Nexus: Springers 이근, 김호원 외, 2018. 중국을 뛰어넘고 4차혁명을 이끄는 미래산업 전략 보고서: 21세기 북스 • 이근, 2014. 경제추격론의 재창조, 43

Thank you!! www. keunlee. com 44

Thank you!! www. keunlee. com 44