K d th BIC (B il I di Chi ) C t hi UKorea and the BICs (Brazil, India, China): Catching Up Experiences

Carlos A. Primo Braga, Vandana Chandra, and Israel Osorio

Economic Policy and Debt Department, PREM, The World Bank

OutlineOutline

1. Introduction1. Does Technological Catch Up Matter?

2 Th ti l B k d2. Theoretical Background

3. Measurement Variables

4 C hi E i4. Catching up Experiences1. Korea

2 China2. China

3. Brazil

4. India

5. Empirical Model

6. Conclusion

1 Motivation1. Motivation

• What is our paper about:

– Catch up between Korea and the BICs in a global market (using industry level data)g ( g y )

– Objective: To analyze the interplay between competition and innovation in pcatch up

– Analysis focuses on:y• Comparison of different performances among Korea, China, Brazil and India

• Testing of Aghion et al. model

1.1 Catch up in income per capita: Korea and p p pBrazil Catching up with OECD Countries

High Income OECD

Singapore High Incomenon OECD

South Korea

B ilBrazil

Lower Middle Income

Source: World Development Indicators

1.1 Catch up in income per capita: China and India in the Catch Up Game

China

Lower Middle Income India

Low Income

Source: World Development Indicators

1 2 Catch up in productivity: labor1.2 Catch up in productivity: labor productivity, 1960‐2000

Source: Penn World Tables

1.2 Catch up in productivity: Total Factor Productivity Growth – Annual %

Source: Authors’ estimates using Penn World Tables

2 Theoretical Background2. Theoretical Background

• Conventional wisdom: Competition (e.g., trade liberalization) leads to productivity growth and innovation.

• Schumpeterian model: Innovation needs rents…;Schumpeterian model: Innovation needs rents…; too much competition can be bad for innovation. 

N S h t i M d l Wh th• New Schumpeterian Model: Whether competition is good/bad for innovation and 

h d d h di hgrowth depends on the distance to the technological frontier (inverse‐U shaped relation between competition and innovation; Aghion, Howitt, et al.). 

3 Measurement Variables3. Measurement Variables

1 P d ti it 1 O t f i

Policy VariablesMeasures of Competitiveness1. Productivity

Value Added per WorkerSource: UNIDO’S INDSTAT

1. Openness to foreign competition

Tariff levels S TRAINS

2. Competitiveness in the International Markets

Source: TRAINS

2. Export orientationExports as share of outputS C d d UNIDO’SRevealed Comparative Advantage

Source: Comtrade

Source: Comtrade and UNIDO’S INDSTAT  

Di t t th t h l i l3. Technological contentTechnology definition applied to exports

Distance to the technological frontier

For Brazil, China, and India a relative measure ofSource: Lall (2000) and Comtrade measure of

ProductivityExport Orientation

… in comparison with South Korea… in comparison with South Korea

3.1 Labor Productivity and distance to the technological frontier – Textiles

010

0V.A. per Worker (Korea=100)- product 321

40

V.A. per Worker (Current '000 US$/worker) - product 321 60

80

030

040

1020

02

1980 1985 1990 1995 2000 20050

1980 1985 1990 1995 2000 2005

KOR BRAIND CHN

KOR BRAIND CHN

Product: TextilesSource: UNIDO Industrial Statistics Database, Rev. 2 and 3

3.1 Labor Productivity and distance to the technological frontier – Electrical machinery

100

V.A. per Worker (Korea=100)- product 383

010

0

V.A. per Worker (Current '000 US$/worker) - product 383 60

80

6080

040

040

020

1980 1985 1990 1995 2000 20050

21980 1985 1990 1995 2000 2005

KOR BRAIND CHN

KOR BRAIND CHN

Product: Machinery, electricSource: UNIDO Industrial Statistics Database, Rev. 2 and 3

3.1 Labor Productivity and distance to the technological frontier – Transport equipment

100

V.A. per Worker (Korea=100)- product 384

80

V.A. per Worker (Current '000 US$/worker) - product 384 60

80

060

040

2040

020

1980 1985 1990 1995 2000 20050

1980 1985 1990 1995 2000 2005

KOR BRAIND CHN

KOR BRAIND CHN

Product: Transport equipmentSource: UNIDO Industrial Statistics Database, Rev. 2 and 3

3 2 Revealed Comparative Advantage Textiles3.2 Revealed Comparative Advantage ‐ Textiles

10RCA, 321 Textiles

68

24

02

1970 1980 1990 2000 20101970 1980 1990 2000 2010

BRA CHNIND KOR

Source: UN Comtrade - concordances between SITC and ISIC Codes

3.2 Revealed Comparative Advantage – Electrical Machinery

2.5

RCA, 383 Machinery, electric1.

52

10

.5

1970 1980 1990 2000 2010

BRA CHNIND KORIND KOR

Source: UN Comtrade - concordances between SITC and ISIC Codes

3.2 Revealed Comparative Advantage – Transport equipment

1.5

RCA, 384 Transport equipment1

.50

1970 1980 1990 2000 2010

BRA CHNIND KOR

Source: UN Comtrade - concordances between SITC and ISIC Codes

3 3 Competitiveness (Tech Definition)3.3 Competitiveness (Tech Definition)

South Korea: Export competitiveness and catch up in products with a revealed comparative advantage

80%

50%60%

70%

oduc

ts

20%

30%

40%

hare

of p

ro

0%

10%20%

1980 84 1985 89 1990 94 1995 99 2000 04 2005 06

Sh

1980-84 1985-89 1990-94 1995-99 2000-04 2005-06

Low Tech 1 Low Tech 2 Med Tech 1&2 Med Tech 3High Tech 1 High Tech 2

Source: Authors’ calculations using UN Comtrade database and Lall’s (2000) technology definition

3 3 Competitiveness (Tech Definition)3.3 Competitiveness (Tech Definition)

China: Export competitiveness and catch up in products with a revealed comparative advantage

80%

50%

60%70%

rodu

cts

20%

30%40%

Sha

re o

f pr

0%

10%

1980-84 1985-89 1990-94 1995-99 2000-04 2005-06

S

1980 84 1985 89 1990 94 1995 99 2000 04 2005 06

Low Tech 1 Low Tech 2 Med Tech 1&2 Med Tech 3High Tech 1 High Tech 2

Source: Authors’ calculations using UN Comtrade database and Lall’s (2000) technology definition

3 3 Competitiveness (Tech Definition)3.3 Competitiveness (Tech Definition)

Brazil: Export competitiveness and catch up in products with a revealed comparative advantage

40%

25%

30%

35%

oduc

ts

10%

15%

20%

hare

of p

ro

0%

5%

10%

Sh

1980-84 1985-89 1990-94 1995-99 2000-04 2005-06

Low Tech 1 Low Tech 2 Med Tech 1&2 Med Tech 3High Tech 1 High Tech 2g g

Source: Authors’ calculations using UN Comtrade database and Lall’s (2000) technology definition

3 3 Competitiveness (Tech Definition)3.3 Competitiveness (Tech Definition)

India: Export competitiveness and catch up in products with a revealed comparative advantage

60%

40%

50%

oduc

ts

20%

30%

hare

of p

ro

0%

10%

1980 84 1985 89 1990 94 1995 99 2000 04 2005 06

Sh

1980-84 1985-89 1990-94 1995-99 2000-04 2005-06

Low Tech 1 Low Tech 2 Med Tech 1&2 Med Tech 3High Tech 1 High Tech 2g g

Source: Authors’ calculations using UN Comtrade database and Lall’s (2000) technology definition

3.4 Competition (weighted tariffs) –South Korea

South Korea: Reduction in tariffs (weighted, %)

18

12

15

rate

s (%

)

6

9

Wei

ghte

d ta

riff

0

3

1988 1990 1992 1994 1996 1998 2000 2002 2004 2006

Textiles Wearing apparelIron and steel Non-ferrous metals Fabricated metals Non-electrical machineryElectrical machinery Transport equipmentProfessional &Scientif ic equip

Source: TRAINS

3.4 Competition (weighted tariffs) –China

China: Reduction in weighted tariffs (%)

80

90

Wearing Apparel

Non metallic mineral

Transport equipment

50

60

70

TextilesNon-metallic mineral

products

30

40

50

Food ProductsIron and steel

Non-ferrous metals

Non-electrical machinery

0

10

20

01992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

Food Products Textiles Wearing Apparel

Industrial chemicals Petroleum refineries Non-metallic mineral

Iron and steel Non-ferrous metals Fabricated metal pro

Non-electrical machinery Electrical machinery Transport equipmen

Source: TRAINS

3.4 Competition (weighted tariffs) –Brazil

Brazil: Weighted tariff rates (%)

El t i l hi45

50

Electrical machinery

30

35

40

Iron & steel

Non-electrical machinery

Transport equipment

15

20

25

Industrial chemicals

Petroleum refineries

Food Manuf.

5

10

15

0Brazil 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

Paper & products Printing, publishing and allied industriesIndustrial chemicals Petroleum refineriesIron & steel Non-electrical machineryElectrical machinery Transport equipment

fy p q p

Food Manuf.

Source: TRAINS

3.4 Competition (weighted tariffs) –India

India - Trade liberalization (weighted tariffs %)100

Food product s

Wearing apparel

Non-elect r ical machinery

75

ff ra

te (%

)

Iron and st eelTransport equipment

25

50

Wei

ghte

d ta

ri

Pet roleum ref iner ies

01990 1992 1994 1996 1998 2000 2002 2004 2006

W

1990 1992 1994 1996 1998 2000 2002 2004 2006

Food products Textiles Wearing apparelIndustrial chemicals Petroleum refineries Iron and steelN l t i l hi El t i l hi T t i tNon-electrical machinery Electrical machinery Transport equipment

Source: TRAINS

5.1 South Korea, benchmark

R id l f i / l i i• Rapid structural transformation/selectivity• High savings rate/macro stability/education• Outward looking strategy (contingent export promotion)

• Trade liberalization (late 1980s: Average  t= 18.1%, 1988)

• Distance shortening policies:– Seeding and expansion of chaebols– Increasing focus on industries with high technological content

– Support to investments in R&D/focus on building indigenous technological capabilities

5 2 China5.2 China

St t l T f ti / l ti it• Structural Transformation/selectivity• Shift towards high tech industries• Export‐led growth• Distance shortening policies:

– Allow FDI flows conditional on technology transfer and capability buildingLong term finance– Long term finance

– Foster industries with high technological content– Attention to government‐business interfaceAttention to government business interface– Growing investments in S&T/R&D

5 3 Brazil5.3 Brazil

B ili Mi l 1967 74/79 f ll d b h L• Brazilian Miracle 1967‐74/79, followed by the Lost Decade C t h t t li d ISI (i l di it l• Catch up strategy relied on ISI (icluding on capital goods)

• Strong anti export bias only began to fall in the 1990s• Strong anti‐export bias only began to fall in the 1990s (trade liberalization and export credits)

• Diffuse distance shortening policies• Diffuse distance shortening policies– Unstable support for investment in S&T/R&D– Barriers to absorption of embedded knowledge (capitalBarriers to absorption of embedded knowledge (capital 

goods protection; FDI driven by domestic market)– Policies to enhance innovation competencies of firms were 

not able to correct for weak educational endowment– Weak linkages between private sector and innovation 

s stems (basic science orientation)

5 4 India5.4 India

C l b f t l ti d t l• Complex web of government regulations and controls during the 1960s‐90s (barriers to entry/exit)

• Late and slow pace of trade liberalizationLate and slow pace of trade liberalization• Limited structural transformation towards high tech industries

• Distance shortening policies– Hand‐picked industries, but no export orientation– Discouraged/Deterred FDI flows– Financing provided by the government, but the chosen 

industries focused on the domestic marketindustries  focused on the domestic market– Did not foster industries with high technological content– Heavy investment in technical skills – law of unintended 

( )consequences (services revolution)

5.5 Comparison of competition and i i li iinnovation policies

Korea Brazil China IndiaCompetition FDI (Foreign Competition) x

Policies Relaxed Antitrust Regulation x

Import Substitution x x

Export led growth x x

Distance shortening /

Selectivity ‐ Few/High‐tech/Performance x xFDI (Conditional Technology

Innovation policiesFDI (Conditional Technology Transfer)                                                  x                x x

Fiscal Incentives x x x x

i iFinancing x x x xPolicies to strengthen linkages between private sector and academia/public sector X Weak x Weakacademia/public sector X Weak x Weak

Science & Tech Education  x x xScience & Tech Parks x xSource: Authors’ diagram

5.6 South Korea ‐ Selectivity in economic transformation from low to high tech industries

Share in total ManufacturingValue Added Rank in Rank in

Korea 1980-84 1995-99 2000-04 1980-01 2004-05Machinery electric 10 18 24 3 1Machinery, electric 10 18 24 3 1Transport equipment 8 12 14 6 2Machinery, except electrical 4 10 10 12 3electricalIndustrial chemicals 9 10 9 2 4Iron and steel 7 5 7 4 5Fabricated metal 4 5 5 11 6products 4 5 5 11 6

Food products 7 6 5 5 7Plastic products 2 3 3 18 8P t l d t 5 4 3 7 9Petroleum products 5 4 3 7 9Textiles 12 5 3 1 10Other non-metallic mineral products 3 3 2 10 11mineral products

% of total 71 81 84

Source: Authors’ calculations using UNIDO’s INDSTAT4 Database

5.6 China – Selectivity in economic transformation from low to high tech industries (Korean style)

Share in total ManufacturingValue Added Rank in Rank in

China 1980-84 1995-99 2000-04 1980-01 2004-05Machinery, electric 4 12 16 10 1Industrial chemicals 12 12 11 3 2Iron and steel 7 7 10 4 3M hi tMachinery, except electrical 15 8 8 2 4

Food products 5 7 7 8 5Transport equipment 3 7 7 11 6Transport equipment 3 7 7 11 6Textiles 14 7 6 1 7Other non-metallic mineral products 5 6 4 7 8mineral productsTobacco 5 5 4 9 9Petroleum products 5 4 3 6 10Non-ferrous metals 2 2 3 16 112 2 3 16 11

% of total 76 76 79

Source: Authors’ calculations using UNIDO’s INDSTAT4 Database

5.6 Brazil ‐Weak selectivity in economic transformation 

Share in total ManufacturingShare in total ManufacturingValue Added Rank in Rank in

Brazil 1980-84 1995-99 2000-04 1995-96 2004-05Food products 15 14 1 1Industrial chemicals 13 12 2 2Transport equipment 9 10 3 3Petroleum products 5 10 7 4Iron and steel 4 8 8 5Iron and steel 4 8 8 5Machinery, except electrical 7 7 4 6

Machinery, electric 6 4 5 7Paper and products 4 4 10 8Fabricated metal products 4 4 9 9

Printing and publishing 5 3 6 10

Other non-metallic mineral products 3 3 11 11p

% of total 76 79

Source: Authors’ calculations using UNIDO’s INDSTAT4 Database

5.6 India – Weak selectivity in economic transformation

Share in total ManufacturingShare in total ManufacturingValue Added Rank in Rank in

India 1980-84 1995-99 2000-04 1980-01 2004-05Industrial chemicals 15 21 17 2 1Iron and steel 12 10 15 3 2Petroleum products 3 4 11 9 3Transport equipment 9 9 10 4 4Textiles 15 9 6 1 5Food products 9 9 6 6 6Machinery, except electrical 9 7 6 5 7electricalMachinery, electric 8 7 5 7 8Other non-metallic mineral products 4 4 4 8 9pNon-ferrous metals 1 3 4 11 10Fabricated metal products 3 3 2 10 11

% of total 87 85 87

Source: Authors’ calculations using UNIDO’s INDSTAT4 Database

5 7 Export led growth5.7 Export‐led growth

KOREA CHINAGrowth in Manuf Share of output Share of output

1980-04 1980-81 2000-04 1980-81 2000-04Machinery, electric 3008 38 64 3 34T t i t 2004 5 33 2 15

Growth in Manuf. Value Added (%)

Share of output exported (%)

Share of output exported (%)

Transport equipment 2004 5 33 2 15Machinery, except electrical 3085 20 46 1 67Industrial chemicals 937 9 36 3 10Iron and steel 906 28 23 2 7Fabricated metal products 1292 39 14Food products 647 16 5 8 10Plastic products 1681 5 6Petroleum products 326 2 1 12 3Textiles 147 30 43 9 37Other non-metallic mineral products 657 13 4 1 6Non-ferrous metals 788 3 12

Source: Authors’ calculations using UNIDO’s INDSTAT4 Database and Comtrade

5 7 Export led growth5.7 Export‐led growth

IndiaBrazil

1980-04 1980-81 2000-04 1980-81 2000-04

Food products -14 29 13 11

Share of output exported (%)

Share of output exported (%)

Growth in Manuf. Value Added (%)

Food products -14 29 13 11Industrial chemicals -16 9 1 14Transport equipment 2 33 6 7Petroleum 108 0 0 0I d t l 64 29 1 13Iron and steel 64 29 1 13Machinery, except electrical -24 22 4 14Machinery, electric -38 19 3 12Paper and products -6 23Fabricated metal products -23 9 12 27Printing and publishing -46 2 Other non-metallic mineral products -11 12 1 7Textiles 12 35 Textiles 12 35

Source: Authors’ calculations using UNIDO’s INDSTAT4 Database and Comtrade

5.9 Reduction in tariffs in comparative perspective: the Chinese “revolution”

Source: TRAINS

5.9 Liberalization in a comparative perspective: Tariffs and Non‐Tariff Barriers

Table 3. Tariff and Non Tariff Measures in BICs - Total Trade

Weighted Averaged Tariffs in Total Trade 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

Brazil 19.0 12.7 12.7 10.4 10.0 9.4 9.0 8.5 8.5 8.7China 32.2 23.8 14.7 14.1 10.3 6.5 6.0 4.9 4.4 4.7India 49.6 23.2 27.5 26.5 25.3 24.1 22.8 13.4 11.9 10.4Korea 9.5 6.8 7.2 8.6 10.0 9.6 9.2 8.3 7.4 7.4

1OTRI1 (MFN applied tariffs plus Non Tariff Measures)2001 2005 2006

Brazil 27.2 22.3 21.9Chi 21 1 11 2 10 1China 21.1 11.2 10.1India 32.2 19.7 21.9Korea 10.0 - 10.0

Source: TRAINS and World Trade Indicators

6 Empirical Methodology6. Empirical Methodology

C titiDF tiL VAPW ββ ++tjitji

tjitjitji

tjinCompetitioDFrontiernCompetitioDFrontierLnVAPW

,,1,,3

1,,21,,1,,

1,,

1

* εβββα++++=

−−

−−

Distance to the frontier = Korea's exports to output ratio / each one of the BICs export to output ratios at the ISIC Rev. 2‐3 digit disaggregation 

Competition = (‐) natural logarithm of the tarifs at the industry level multiplied 

Interactive term = Distance to the frontier x CompetitionInteractive term = Distance to the frontier x Competition 

GMM: System Generalized Method of Momentums using the Arellano‐Bond Methodology.gy

Avoided the excessive use of lagged instruments that diminishes efficiency in the estimates. 

6.1 Results: A negative sign in the interactive term 

Dependent Variable: Natural Log of Value Added per Worker

Fixed Effects GMMFixed Effects GMM

Distance to the Frontier (lagged) -0.00149*** -0.00218***

Competition (lagged) 0 31653*** 0 34582***Competition (lagged) 0.31653*** 0.34582***

Distance to the Frontier * Competition -0.00067*** -0.00075***

2 9636 *** 3 0 23 ***constant 2.96365*** 3.07235***

Observations = 1285 1285Groups = 71 71

Observations per groupminimum = 6 6average = 18.1 18.1g

maximum = 27 24F_test that all ui=0

F(70,1211) = 39.86Prob>F = 0.000Prob F 0.000

Number of instruments - 78

Source: Authors’ estimates

6 2 Simulation of Results6.2 Simulation of Results30

Ti di i

25

L)PastPresent

Time dimension

20

Wor

ker (

USD

/ L

Brazil

10

15

e Ad

ded

per W

India

5

Valu

e

China

0

0 20 40 60 80 100

120

140

160

180

200

220

240

260

280

300

320

340

360

380

400

420

440

460

Distance to the FrontierDistance to the Frontier

Low Competition High Competition Increasing Competition

Source: Authors’ representation

ConclusionsConclusions

• Different experiences in catching up

• Competition is a plus for innovation, but…Competition is a plus for innovation, but…– “Distance” matters

• Role of “distance‐shortening” measures, importance of outward orientation and sequencing

• Replicability ?• Replicability…?