1. Cambridge Univ. Press 2013
Schumpeterian Analysis of Economic Catch-up: Knowledge, Path-creation, & the Middle Income Trap
Keun Lee 李根
Prof. of Economics, Seoul Nat’l University
Director, Center for Economic Catch-up
Committee for Dev’t Policy, UN-ECOSOC  

3. Acemoglu and Robinson,
Why Nations Fail
Bill Gates’ book review “Never explain how to move to more “inclusive” institutions” Keun Lee Inclusive vs. extractive : -> relevant more in low income or pre-modern economy b/c less difference among middle income countries => Why Nations Fail at Middle Income Stage: Inclusive vs. Innovative systems

4. constraints on executives)
Quality of Institutions
constraints on executives)
1965
1980
2000
Korea 3 1 6
Taiwan 2
Philippines 5
Thailand 7
Malaysia 4
China
India
Brazil
Argentina
Chile
Mexico
Source: Polity IV Dataset; from Lee and Kim 2009 table 1

6. Record of Catching-up / Falling behind:
As % of the US per capita Income ( in 2005 Constant PPP)

7. Trend of the Income Levels as Percentage of that of Japan:
=> Korea, Taiwan: No catching up in 60s, 70s:-> only from 1980s

8. Middle income country trap: Per capita in 2000 Dollars, 1980-95
Income Groups
1980
1995
Annual growth
High Income
14985
20593
2.14
Lower Middle Income
958
1,280
1.95
Upper Middle Income
5001
4616
-0.53
Asian 4: Korea, Taiwan, Hong Kong, and Singapore
1980
1995
7041.5

9. Flat R&D/GDP as source of MIT (middle income trap)

10. Lee, Keun & B. Kim (2009, World Development)
Confirms importance of Innovation and high education
for middle and higher income countries;
cf) Institution and basic human capital matter
for low and lower middle C’s
This book beyond just patent counts (innovation measure)
=> more details of the NIS (national innovation systems)
Eg) cycle time of tech.
localization of knowledge creation,

11. Analysis at 3 levels => different question
Country: What determines catching-up growth:
-> per capita income growth
Sector: Why easy to catch up in some sectors;
why not in others ?
-> Country’s US Patent share in sectors
3) Which the CIS (corporate innovation system) a good fit for catching up;
sales growth, profitability, firm value, productivity
=> different question
-> same answers = knowledge variables

12. Key Variable = cycle time of technologies
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

13. Four Key Variables and Hypotheses
at three Levels of country, sector & Firms
4 Hypotheses : Growth strategies
Technological specialization 1
(short vs. long cycle)
Technological. Specialization 2
(high vs. low originality )
Localization of knowledge creation & diffusion
(vs. reliance on foreign sources)
Balanced vs. Concentration of knowledge creation

14. (1) Patent number; (2) Grant year (3) Grant date
Data: NBER USPTO patent data
Patents registered from 1963 to 1999; later update to 2006
Patent citation data made from 1975 to 1999; updates to 2006
: at (
: NBER website (
Information in the database
(1) Patent number; (2) Grant year (3) Grant date
(4) Application year (starting in 1967)
(5) Country of first inventor ;
(7) Assignee identifier, if the patent was assigned (starting in 1969)
(8) Assignee type (individual, corporate, or government; foreign or domestic)
(9) Main U.S. patent class (UPC);
(11) citing patent number and cited patent number (patent citation pair data)
Retrieved at the country, tech. classes (sectors)
and firm levels (Korean, US firms)
Regression analysis

15. Intra-national Citation in Patents (~self-citation)

19. Middle Income Countries
Basic Descriptive Data of the country groups
High Income Countries
Middle Income Countries
Korea and Taiwan
Mean(μ0)
Mean(μ1)
Mean(μ2)
Real GDP per capita growth rate (four-year average %)
0.102
0.067
0.260
Initial GDP per capita, each period
15823
2883
5170
Population growth rate (four-year average %)
0.032
0.077
0.054
Fixed investment per GDP (%)
23.5
23.0
27.9
Enrollment rate of secondary education (%)
95.6
58.6
80.7
Number of Patent
4965.2
52.4
920.7
Quality of Patent
73.0
1583.2
Technology capability (share)
9.00E+08
8.74E+03
3.09E+06
Notes: High Income Countries are those whose GDP per capita in 2000 constant prices exceed US$ In both groups, only those countries that have more than 10 U.S patents in every period are included.

20. Fixed Effect Panel Model
System-GMM Model
　per capita income growth
High Income
Middle Income
Dummy Model
Log of initial GDP per capita for each period
(-2.57)**
(-4.02)***
(-4.78)***
(-2.81)***
(-3.07)***
(-4.87)***
Growth rate of population for each four-year-period
(-1.71)*
(-1.70)*
(-2.90)***
(-0.09)
(-0.21)
(-0.39)
Fixed capital investment per GDP
0.0030
0.0146
0.0093
0.0089
0.0242
(1.08)
(4.12)***
(4.24)***
(2.58)***
(3.43)***
(2.68)***
Enrollment rate of secondary education
0.0006
0.0009
0.0001
(0.99)
(0.69)
(1.65)
(0.03)
(-1.40)
(-1.38)
Herfindhal index
(-2.40)**
(-2.14)**
(-3.17)***
(-1.94)*
(-2.85)***
(-2.70)***
Intra-national knowledge diffusion
0.5128
0.3296
0.6397
0.3581
1.0351
0.8361
(1.87)*
(0.90)
(1.96)**
(1.74)*
(1.07)
(3.32)***
Technology cycle
0.0249
0.0145
0.0319
0.0284
0.0274
0.0636
(3.13)***
(2.30)**
(3.50)***
(2.42)**
(2.01)**
Originality index
0.1152
0.0239
0.4870
(-0.52)
(0.73)
(0.10)
(-0.67)
(-0.90)
Dummy (middle )
(dropped) **
Dummy*Herfindhal index
0.2059
0.4534
(2.19)**
Dummy*Intra index
0.1565
(-0.63)
(0.49)
Dummy*Technology cycle
(-1.79)*
(-2.04)**
Dummy*Originality index
0.0674
0.8946
(0.26)
(1.73)*

21. Results with a dummy for 4 Asian : fixed effect models
High Income group (1)
Middle Income Group (2)
Whole World (3)
Log of initial GDP per capita for each period
(-4.57)***
(-4.32)***
(-5.48)***
Growth rate of population for each four-year-period
(-2.26)**
(-1.76)*
(-2.74)***
Fixed investment per GDP
0.0070
0.0140
0.0102
(2.72)***
(4.36)***
(5.05)***
Enrollment rate of secondary education
0.0008
0.0012
(1.70)*
(0.62)
(2.43)**
Herfindhal index
(-2.42)**
(-3.04)***
Intra-national knowledge diffusion index
0.5939
0.3411
0.4261
(2.52)**
(0.98)
(2.09)**
Technology cycle
0.0381
0.0147
0.0195
(5.21)***
(2.45)**
(4.49)***
Originality index
0.0200
0.1236
0.0741
(0.10)
(0.83)
(0.70)
Dummy (Asian 4)
1.2881
1.1123
1.1134
(2.37)**
(2.91)***
Dummy*Herfindhal index
(-2.11)**
(-1.87)*
(-1.88)*
Dummy*Intra index
(-0.31)
(-0.39)
(-0.68)
Dummy*Technology cycle
(-3.16)***
(-1.39)
(-1.78)*
Dummy*Originality index
(-1.53)
(-1.09)
(-1.48)
Constant
2.6933
2.3479
2.1035
(4.16)***
(4.11)***
(4.97)***
Number of obs
112 95
191
Number of groups 28 27 51 R2
0.282
0.204
0.118

22. Regressing growth onto National Innovation systems: Asian 4 as benchmark
High Income
middle Inc.
World
Tech cycle time
(-)*
(+)*
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

23. Summary: country-levels
High income countries are those with
more even distribution of inventors,
higher rate of intra-national knowledge diffusion,
by higher rate of originality
shorter time of technology cycle (than other MICs)
but longer than Asian 4s.
2) These variables are all significantly related to growth,
except originality variable.
3) Among two suspects of catching-up growth:
intra-national knowledge diffusion; short cycle technologies

24. * Difference: Specialization into short cycle time technologies
Longer cycle time is positively related to economic growth in both of high and middle income countries,
but negatively (thus shorter time is positively) related to economic growth in the Asian 4
-> detour from long cycle to shorter cycles
over the catching up period
-> others, eg LA, MIC are still in the long cycle fields

25. Top 10 Classes of G5 vs Korea-Taiwan ->no overlap
Class Name
Patent count 1
514
Drug, Bio-Affecting and Body Treating Compositions
10349 2
428
Stock Material or Miscellaneous Articles
3883 3 73
Measuring and Testing
3789 4
123
Internal-Combustion Engines
3479 5
424
3389 6
210
Liquid Purification or Separation
2853 7
435
Chemistry: Molecular Biology and Microbiology
2852 8
250
Radiant Energy
2639 9
264
Plastic & Nonmetallic Article Shaping or Treating
2349 10
324
Electricity: Measuring and Testing
2325
Korea-Taiwan
Class
Class Name
Patent count 1
438
Semiconductor Device Manufacturing: Process
1189 2
348
Television
712 3
439
Electrical Connectors
408 4
257
Active Solid-State Devices ( Transistors, Solid-State Diodes)
374 5
362
Illumination 6
280
Land Vehicles
355 7
365
Static Information Storage and Retrieval
346 8 70
Locks
340 9
360
Dynamic Magnetic Information Storage or Retrieval
313 10
482
Exercise Devices
311

26. Top 10 Classes of G5 vs 8 middle-income countries -> similar
Class Name
Patent count 1
514
Drug, Bio-Affecting and Body Treating Compositions
10349 2
428
Stock Material or Miscellaneous Articles
3883 3 73
Measuring and Testing
3789 4
123
Internal-Combustion Engines
3479 5
424
3389 6
210
Liquid Purification or Separation
2853 7
435
Chemistry: Molecular Biology and Microbiology
2852 8
250
Radiant Energy
2639 9
264
Plastic & Nonmetallic Article Shaping or Treating
2349 10
324
Electricity: Measuring and Testing
2325
8 mid income's
Class
Class Name
Patent count 1
514
Drug, Bio-Affecting and Body Treating Compositions
120 2
424 76 3
435
Chemistry: Molecular Biology and Microbiology 54 4 75
Metallurgical Compositions, Metal Mixtures 52 5 65
Glass Manufacturing 44 6
604
Surgery 7
210
Liquid Purification or Separation 40 8
423
Chemistry of Inorganic Compounds 9
502
Catalyst, Solid Sorbent or Product 10
123
Internal-Combustion Engines 38

27. 2nd Question: Sectoral difference in catch-up Answer:
2nd Question: Sectoral difference in catch-up Answer: . (Sectoral Systems of Innovation; Technological Regimes of Sectors) Lee & Lim (2001, Research Policy) Park and Lee (2006: Industrial & Corporate Change) Jung and Lee (2010: Industrial & corp. change)

28. TFP Catch-up : Korea vs Japan
Rapid catch-up
(about 30%)
Sustain Gap
(about 10%)
Source: Jung and Lee (2010: Industrial & corp. change) 28

29. Convergence of Productivity in IT: korea vs Japan
Sam. Elect.:
OVER
While Industry : JUST 29

30. “Still Gap in Autors: Hyundai vs. Toyota
H.M. : Under
like industry 30

31. First tier 2 :Korea and Taiwan Extension of Park & Lee, 2006, (Industrial and Corporate Change) To: 2) Second Tier: 8 2-a) Asia 4: China, India, Malaysia, Thailand 2-b) LA 4: Brazil, Mexico, Argentina, Chile

32. 1st step: Occurrence of Catch-up : (1 or 0 in positive change in paten shares in 417 classes, 80-95) No differ. bt. Asia 4 and LA
Mean G5
0.348
Korea_Taiwan
0.814
Asia 4 + LA4
0.151
Asia4
0.140
Latin America4
0.162
China
0.226
India
0.170
Malaysia
0.096
Thailand
0.066
Argentina
0.130
Brazil
0.276
Chile
0.059
Mexico
0.181

33. 2nd step: Speed of Catch-up (%P. change, 80-95): Big difference bt
2nd step: Speed of Catch-up (%P. change, 80-95): Big difference bt. Asia 4 and LA
Mean G5
-2.246
Korea_Taiwan
3.677
Asia 4 + LA4
0.030
Asia 4
0.059
Latin America4
0.000
China
0.106
India
0.066
Malaysia
0.035
Thailand
0.028
Argentina
-0.015
Brazil
-0.008
Chile
0.023
Mexico
0.002

34. 3rd step: Level of technological capability: (average share for the 1980-95)
Mean % G5
8.804
Korea_Taiwan
2.164
Asia 4 + LA
0.080
Asia 4
0.041
Latin America
0.120
China
0.061
India
0.059
Malaysia
0.024
Thailand
0.019
Argentina
0.078
Brazil
0.211
Chile
0.020
Mexico
0.170

35. 8 Independent variables measuring tech regimes
1) Technological opportunities : average growth rate
2) Cumulativeness of technical advances (persistence) : share of persistent registrant (with more than one at every year)
3) Appropriability of innovations : share of self-citation received
4) Property of the knowledge base :
originality (broad base of knowledge)
*5) Fluidity (Uncertainty) of technological trajectory :
Fluid2 = (Maximum count-Minimum)/average count of patent
*6) Initial stock of accumulative knowledge : initial share
*7) Relative technological cycle time (speed of change) : relative citation lag
*8) Accessibility to external knowledge flows (spillover/ACCESS) : citation from non-G7 to G7

36. Regression models 1) Occurrence of technological catch-up
= F (technological regimes)
whether or not there is positive change in the US patent share of a country (probit regressions)
2) Speed of technological catch-up
degree of positive change in share
(regressions for the sectors with occurrence)
3) Level of technological Capability (share by a country)

37. Sector level: In which sector more patents? (Korea +Taiwan) vs. G5
=> Korea+Taiwan: more share in short cycle;
cf) G5 more share in long cycle sectors

38. 8 Catch-up (Asia 4 + LA), Asia 4, LA : Catch-up and capability
Variable
Level of tech. capability
8 catch
4 Asia
4LA
OPPOR
-0.078
-0.00
-0.15
CUMUL1
-0.134**
-0.02
-0.25**
APPRO
0.210***
0.18***
0.24*
NATURE
0.034
0.09*
FLUID2
-0.001
-0.01
0.01
INITIAL
0.00
0.02
CYCLE
-0.04
0.07
ACCESS
0.31
0.04
0.58
Adjusted R2
0.045
F-statistic
10.5
3.86
6.6
No. obs.
3008
1504
For next tier 8: cycle time-> positive and insignificant
Cf) Korea+Taiwan: negative and significant

39. Levels of technological capabilities
First 2, higher in short cycle time sectors, but
Next 8, lower in short cycle sectors
 Two faces of leapfrogging argument (Perez & Soete): new technological paradigm may permits leapfrogging or act as additional barriers with truncation of learning (Lall 1992; 2000)
Changing paradigm = either
a window of opportunity or a barrier to catch-up
 How to ride well this changing paradigm determines the chance for sustained catch-up (vs. short-lived)

40. 3rd Question:
Catch-up at the firm level:
CIS (corporate Innovation systems);

41. in the advanced countries and the late-comer countries
Our departing point
Firms
in the advanced countries
and the late-comer countries
are different in many aspects,
including
their levels of capabilities and behavior.
*There should be more differences => this study
-> knowledge bases of the firms
cf) Schumpeterian theory of the firms (Winter, Nelson): accounting inform. not enough to show heterogeneity of firms

42. Comparing Korean firms with the American firms
the former representing firms from late-comer countries ;
the latter representing the firms from the advanced countries.
; focuses on innovation systems of firms,
-> such as cycle times of firms’ technology,
self-citation (self-production of knowledge)
technological diversity of firms,
Originality of firms’ knowledge base,

43. Specializing in Short cycle technologies and Leapfrogging: Hypo 1
A shorter cycle =>
latercomers do not have to master older knowledge and patents.
-> less disadvantageous in such sectors;
-> So, catching-up firms better specialize in short-cycle technologies.
-- consistent with the leapfrogging hypothesis (Perez & Soete 1988):
So far no research that confirms this view at the firm level,
cf) Park and Lee (2006:ICC) confirm this at the sector level using patent data.

44. Catching-up (Korean) vs. Mature (US) firms:
The former in short cycle technologies

45. Consolidation of self-production of knowledge: high in US vs
Consolidation of self-production of knowledge: high in US vs. low in Korea : Hypo 2
Will compare the self-citation ratio in the patent citations
between catching-up vs. advanced firms.
self-citation:
= degree to which one’s innovation builds upon its own knowledge pool accumulated over the past.
Hypo. : the more advanced a firm is, the higher self-citation ratio.
Hypo: some correlation between self-citations and performance

46. Catching-up (Korean) vs. Mature (US) firms:
The former in low self-citation (localization)
USA Firms

47. Self-citation Ratio of Samsung Electronics and Sony:
(Joo and Lee 2010)

49. Comparison of the Knowledge Variable: means
Part A: Sample means
Variable US
Korea
US-KOR Gap
t-value
Patent Count
18.5
9.56
8.94
4.592**
Patent quality
1.14
0.73
0.41
6.821**
Number of sectors with patents
6.9
4.15
2.75
5.044**
HH index
0.51
0.71
-0.2
-8.808**
(degree of sector concentration)
Originality
0.42
0.3
0.12
7.662**
Technology cycle (years)
14.05
11.91
2.15
4.39**
Intra-firm diffusion (self-citation)
0.03
0.09
18.001**
Catching-up or Korean firms , inferior to the American firms
in every aspects of knowledge variables:
patent counts, quality, originality, and its diversity.
* But note that : Korean firms to have patents with shorter cycle times than the American firms.

50. Catching up firms tend to pursue sales growth
Comparing the catching-up (Korean) firms with the advanced (US) firms : behavior
　Variables US
Korea
Difference
(US-KOR)
t-value
Number of employees
7.634**
(unit : person)
Sales per employee
187.11
294.47
-7.445**
(unit : thousand dollars)
ROA: Return on assets(%)
9.3
8.2
1.1
3.232**
ROS: Return on sales(%)
4.7
9.9
-5.2
-5.228**
TOBIN-Q
1.76
1.01
0.74
34.171**
Sales growth rate(%)
8.8
12.1
-3.3
-2.788**
Investment Propensity(%)
1.0
2.6
-1.6
-3.356**
Debt to equity ratio(%)
266.1
302.7
-36.6
-0.342
Capital Labor ratio
( unit : thousand dollar)
60.24
153.91
-93.67
-7.251**
Catching up firms tend to pursue sales growth
by borrowing and investing more,
while the advanced firms, to purse profitability and firm values.

51. Knowledge and firm performance I: benchmark with patent count only
-> not much new and not much difference of US and Korea
( based on Hausman test: random vs fixed
US firms
Dependent variables:
GROWTH
ROA
ROS
SALES/EMP
TOBINQ
Patent Count
(-)
(+)*
(+)
(+)**
No. of workers
(-)**
(-)*
Investment Propensity
Debt to Equity Ratio
Capital Labor Ratio
Obs
3475
3479
3478
3362
Korea firms
(+)+
(-)+
239
240
127

52. Investment propensity
Knowledge and firm performance II: US;
one variable in each model: no significance of cycle time
US firms
Dependent
GROWTH
ROA
ROS
SALES/EMP
TOBINQ
HH Index
(+)*
(-)
(+) **
Originality
(+)**
Tech. Cycle
Self-citation
(+)+
No. of Emp. +
Investment propensity
Debt to
Equity Ratio
Capital Labor Ratio
(-)** (-
)**

53. Investment Propensity
Knowledge and firm performance II: Korean;
no significance of self-citations
Korea firms
Dependent
GROWTH
ROA
ROS
SALES/EMP
TOBINQ
Independent
HH Index
(-)
(+)
(-)+
Originality
(+)+
(+)*
Tech. Cycle
(-)**
(-)*
Self-citation
No. of Emp.
Investment Propensity
Debt to Equity Ratio
Capital Labor Ratio
Obs
239
231
217
240
232
218
127
122
114

54. Knowledge and firm performance III: with 3 relevant variables only
US firms
Dependent
GROWTH
ROA
ROS
SALES/EMP
TOBINQ
H-H Index
(+)*
(-)
(+)
(-)**
Originality
(+)**
Self-citation
(+)+
No. of workers
(-)+
Investment Propensity
Debt to Equity Ratio
Capital Labor Ratio
Obs
3468
3472
3471
3355
Korea firms
H-H Index
Tech. Cycle
(-)*
Investment propensity
231
232
122

55. Summary: From Knowledge to Performance 1
Self-citation: significant in US firms,
not in Korean firms
Cycle time: not important in the US firms;
quite significant in Korean firms
originality does not matte much in both US and Korea firms
For Korea: Short cycle leading to higher profitability
(but not to high growth or value):
-> catching-firm pursued growth by physical investment but pursued profitability by moving into emerging/new industries,

56. From Knowledge to Performance 2
2) self-citation pattern at firm level:
-> insignificance in the Korean firms indicates still weak level
of the mechanism of self-production of knowledge,;
self-citation is only 3% in the Korean firms,
compared to four time higher level of 12% in the US firms;
medians: zero for the Korean firms, 9% US firms.
The next task for the Korean firm is to consolidate more their intra-firm knowledge creation mechanism
so that it may translate into higher productivity and firm values.

57. Synthesis 3 variables out of 5 more closely related to catch-up
= those showed a different pattern
between more and less successful economies
-> cycle time, localization, & diversification
One Transition variables
= cycle time (how to catch up)
and
Two End-state variables
= localization (who is leading catching-up)
and diversification (what is catch-up)

58. Tech. Diversification = No of sector with patents / 417
cf) 417 = No of 3 digit classes in USPTO;
Diversification matter but where to diversify? => into short cycle

59. shorter cycle technology sectors
Diversification by moving into
shorter cycle technology sectors
Tech. turning point

60. Overall: Short cycle technology matter

61. in academic research, too
Short cycle matters
in academic research, too
Jones and Weinberg (2012)
on the age-achievement relationship in the natural sciences
Young scientists (late entrants)
to make more contributions at a younger age
in the fields of abstract /deductive knowledge
than in the more inductive fields that draw on accumulated knowledge, and in which existing knowledge is slow to reach obsolescence

62. Entry into shorter cycle technologies; International comparisons
Technological
Turning Point:
Entry into shorter cycle technologies;
International comparisons

63. Path-creation (Detour => short cut)
Cycle Time of Korea & Taiwan Patents getting longer recently
Lee’s turning point

65. China from late 90’s but India not yet?
India still not shorter than 9 years

66. China and India Average Cycle Time of China’s top 30 class US patents
= 8.1 years ( yrs)
Cf) Korea and Taiwan = 7.7 yrs (avg of )
Brazil & Argentina = 9.3 yrs (avg )
China more similar to Korea & Taiwan
than to Brazil and Argentina
Cf) India: applying IT (short-cycle tech) to Services
Average weighed Cycle time = 8.7 yrs ( )

67. Not yet over the Turning points In Latin American countries

68. How about Japan in the past? vs. Germany vs. Korea vs. future China

69. Japan caught up with Germany by the mid 1970s

70. Japan also specializing in shorter cycle sectors than Western incumbents ->path creation

71. Localization of Knowledge Creation and Diffusion:
European G5 vs. amazing Japan

72. Localization of Knowledge Creation and Diffusion:
G5, Korea+Taiwan, China

73. From Middle to High Income Countries
From Trade Specialization to Technology Specialization
Stages
Low or low middle income
Upper middle income
To high income
Type of specialization
Trade specialization
Technology specialization
Source of specialization
Comparative advantages
from resource endowment
Absorption/design capability
from learning/R&D effort
Type of sector
Labor intensive/resource
industries
Short cycle/emerging technologies
End goal
competitive export industries
Indigenous knowledge
creation & diffusion
Background theory
Product life cycle (inheriting)
Catch-up cycle (leapfrogging)

74. More Examples
Late Entry: Entering Mature Segment of Short cycle Sectors:
eg) High speed Train in China,
India’s IT service,
Middle sized Jets by Brazil
Entry into notebooks by P-P in Taiwan
Suggestion: Nigeria can build oil refinery,
rather than keep exporting crude oils
Leapfrogging into New/Emerging Segments of Shorter-cycle Sectors:
eg) Solar PV and Wind power in China and India,
Electric Vehicles by China
Ethanol or Biofuels in Brazil

75. Can take a Detour if you have a high driving skill
, when the straight road is jammed
Straight Road: but traffic jam (adding-up problem)
1980
Detour:
No jam but rough & winding road
-> need skill (tech. capability)

76. Should allow ‘detour’ for latecomers
Should allow ‘detour’ for latecomers!!! cf) direct replication of the developed
1) Immediate trade liberalization
vs. asymmetric/selective liberalization
=> Korea, Taiwan used to be more protective;
but now most open
2) High vs. gradual protection of IPRs
=> used be low in Korea & Taiwan but now very high
3) Big Bang vs. Gradualism in system transition
=> Washington Consensus
vs. BeST (Beijing-Seoul-Tokyo) Consensus

77. Now, How to drive the Detour: Implementation Strategies
The detour is not just smooth and easy;
-> requires certain level of
technology capacity,
not only firm-level but also at the national-level

78. 3 Steps along the Detour (to move beyond OEM/assembly)
Acquiring Design Capability
(to move beyond OEM/assembly)
2) Targeting/Entering the mature /low-end segment
of short cycle Sectors
3) Leapfrogging into New/Emerging Technologies
in the Short-cycle Sectors

80. References (www.keunlee.com)
Lee, Keun, & BY Kim,”Both Institutions & Policies matter but differently at differnent income levels: long run economic growth,: World Development (2009)
Lee, Keun, & C. Lim (2001), “Technological Regimes, Catching-up & Leapfrogging: the Findings from the Korean Industries”, Research Policy,
Lee, Keun, Chaisung Lim, and Wichin Song (2005), "Digital Technology as a Window of Opportunity and Technological Leapfrogging: Catch-up in Digital TV by the Korean Firms”, Inter.J. of Tech. Management, Vol. 29, 1/2, pp
Lee, Keun, “Making a technological Catchup.” Asian J.of Tech. Innovation, 2005.
Mu, Qing, and Keun Lee (2005), “Knowledge Diffusion, Market Segmentation and Technological Catch-up: The Case of Telecommunication Industry in China”, Research Policy.
Park, K., and Keun Lee (2006), “Linking the Technological Regime to Technological Catch-up: An Empirical Analysis Using the US Patent Data,” Industrial and Corporate Change, July 2006
Jung, M & K. Lee, (2010), “Sectoral systems of Innovation and Productivity Catch-up: between the Korean and Japanese firms,” Industrial & Corporate Change.

81. Thank you!
ありがとう!
Gracias!
Meu Amigo! Obrigado!
謝謝大家
Danke Shon
감사합니다