“The development and future of Factory Asia”Indonesia, Thailand, Turkey, Poland Stage Share of...

“The development and future of Factory Asia”

Richard Baldwin and Rikard Forslid

RIETI seminar: Ideas for a research agenda

4 December 2013, Tokyo

Overarching question

• How to make global value chains (GVC) work for developing nations?

• Study Factory Asia = best example.

Some background

• Globalisation changed

• Today’s process should not be studied using only 20th century tools.

• KEY change:

– “De-nationalisation of comparative advantage”

Globalisation changed

G7 nations’ share of global GDP, 1820 – 2010.

G7 nations’ share of global manufacturing, 1970 – 2010.

1820,

22%

1988,

67%

2010,

50%

0%

10%

20%

30%

40%

50%

60%

70%

80%1

82

01

83

91

85

81

87

71

89

61

91

51

93

41

95

31

97

21

99

12

01

0

1990,

65%

G7, 47%

3%

China,

19%

5% 6 Risers,

9%

RoW

0%

10%

20%

30%

40%

50%

60%

70%

80%

19

70

19

75

19

80

19

85

19

90

19

95

20

00

20

05

20

10

Wo

rld

ma

nu

fact

uri

ng

sh

are

Source: unstats.un.org; 6 risers = Korea, India,

Indonesia, Thailand, Turkey, Poland

Stage

Share of value

added

Pre-fab

services

Post-fab

services

Fabrication

1970s & 1980s

value

distribution

‘Smile curve’: Distribution of value

Post-1990 value

distribution

67%

11%

RoW

G7,

48%

10

gainers

27%

0%

10%

20%

30%

40%

50%

60%

70%

80%

Global GDP shares, 1960-2012

Post-1990: • G7 share loss goes to 10

developing nations. • RoW see little change.

1990

China, Brazil, Mexico, Poland, India, Turkey, Russia, Korea, Indonesia, Venezuela

Low

Lo-

middle

Hi-

Middle

1993

-

200

400

600

800

1,000

1,200

1,400

1,600

1981

1984

1987

1990

1993

1996

1999

2002

2005

2008

2010

Millions under $2/day by

national income class

People in poverty (under $2/day)

Post 1993 • Hi-middle poverty plummets.

- 650 million fewer poor! • Others’ poverty keeps rising.

1990

Globalisation: 3 cascading constraints

High High High

Stage B Stage A

Stage C

1st unbundling =

Stage B

Stage A Stage C

2nd unbundling =

Pre- globalised

world =

Low Low

High

ICT revolution

Low

High High

Steam revolution

20th century comparative advantage

• Goods = ‘bundle’ on national knowhow, labour, capital, institutions, etc.

• National economies only connected via competition in goods markets.

Stage

B

Stage

A

Stage

C

Stage

B

Stage

A

Stage

C

Goods crossing borders

Stage B

Stage A

Stage C

1) Supply-chain linkages: Cross-border flows of goods, know-how, ideas, capital & people.

2) Doing business abroad: Application of tangible & intangible assets in developing nations.

21st century comparative advantage

• Goods = mixture of national knowhow, labour, capital, institutions, etc. (e.g. hi-tech + low wages).

• National economies connected via much richer flows: knowhow, goods, services, people, capital, etc.

Why it matters

• OLD: Study national performance looking at national factors. – ‘Team Japan’ versus ‘Team Germany’

Regress growth/exports/etc on national right-hand side variables.

• NEW: Study national performance looking at regional and national factors. – ‘Factory Asia’ versus ‘Factory North America’

Regress growth/exports/etc on national & regional right-hand side variables and/or allow interactions depending upon supply-chain exposure.

First steps in study GVC and development

• Shifting resources to trade sectors is pro-development.

• Growth in value added exports is one measure of this.

• First axis of investigation:

– Is rapid value-added export growth related to supply-chain participation?

Value added v. Gross exports

0% 500% 1000%

Other EMs in GVCsPRTSVNMEXTURCZE

HUNPOLSVKROU

Primary exportersZAFAUSCHLNORBRNRUSBRASAU

Total export growth, 1995-2009

Gross export

growth

VA export

growth

0% 500% 1000%

East AsiansJPN

TWNHKGPHLKORMYSIDN

THASGPBRN

KHMCHNVNM

G7 nationsFRAITA

CANUSAGBRDEU

Total export growth, 1995-2009

Gross export

growth

VA export

growth

Special interest of VA exports

• Indirectly measures growth in domestic resources in trade sector (worldclass).

• Close to many development mechanisms:

– Technology adoption;

– Skill upgrading;

– Formation of domestic industrial capacities:

• Human, institutional, infrastructure, etc.

How measure supply chain participation?

• TiVa has several; many more construct-able.

– FVA (Foreign Value Added share)

– REI (Reexported intermediates)

• REI seems to work better.

First look at relationship

Hope

• Faster domestic value-added export growth correlated with faster REI growth.

• Plot vertical axis = Growth in domestic value added in exports

• Plot horizontal axis = Growth in REI trade (supply-chain participation)

Data

• Plot all nations, all 18 goods sectors.

• Growth from 1995 to 2009.

Little correlation

-500%

0%

500%

1000%

1500%

2000%

2500%

-200% -100% 0% 100% 200% 300%

REI vs Growth in Domestic VA in exports

?

?

But theory to rescue

• The correlation should depend upon:

– Nations:

• Headquarter v factory economies

• Primary-resource exporters v manufactures exporters

– Sectors:

• GVC sectors (mech & elec machinery, chemicals, etc)

• nonGVC sectors

Thinking about nation groups

-25% 0% 25% 50% 75% 100%

HKG

BRN

KHM

VNM

JPN

SGP

MYS

IDN

THA

KOR

TWN

CHN

PHL

VA export growth composition,

1995 to 2009

Manufactures Services Primary

-20% 0% 20% 40% 60% 80% 100%

BRA

KHM

ZAF

RUS

CAN

AUS

VNM

NOR

CHL

SAU

BRN


1995 to 2009


Thinking about nation groups

0% 20% 40% 60% 80% 100%

JPN

CAN

ITA

DEU

USA

FRA

GBR


1995 to 2009


0% 25% 50% 75% 100%

SVK

HUN

SVN

CZE

POL

MEX

ROU

TUR

PRT


1995 to 2009

Manufactures Services

Aside: BRICS asunder

0% 25% 50% 75% 100%

RUS

BRA

ZAF

CHN

IND


1995 to 2009


Relationship by nation groups?

Relationship by sector: Primary

VNM

PHLCHN IDNKOR THAMYS TWNUSADEUFRAGBRJPN

TURSVKPOLHUNMEX

IND

BRA ZAFRUSCAN

-200%

300%

800%

1300%

1800%

2300%

-100% 0% 100% 200% 300%

01T05: Agriculture, hunting,

forestry and fishing

VNM

PHLCHNIDN KOR

THAMYSTWNUSADEUFRAGBRJPN

TUR SVKPOLHUNMEX

IND

BRAZAF RUSCAN

-200%

300%

800%

1300%

1800%

2300%

-100% 0% 100% 200% 300%

10T14: Mining and quarrying

VNM

PHL CHNIDNKORTHAMYS TWN

USA DEUGBRJPN

TURSVK

POLHUN

MEXINDBRA ZAFRUSCAN

-200%

300%

800%

1300%

1800%

2300%

-100% 0% 100% 200% 300%

15T16: Food products, beverages

and tobacco

Relationship by sector: Light manuf

VNM

PHL

CHNIDNKORTHAMYSTWNUSA DEUFRAGBR JPN

TURSVKPOLHUN MEXINDBRA ZAFRUSCAN

-200%

300%

800%

1300%

1800%

2300%

-100% 0% 100% 200% 300%

17T19: Textiles, textile products,

leather and footwear

VNM

PHL

CHNIDN KORTHA MYSTWN

USADEUFRAGBR JPN

TURSVKPOL

HUNMEXINDBRAZAF RUS

CAN

-200%

300%

800%

1300%

1800%

2300%

-100% 0% 100% 200% 300%

20T22: Wood, paper, paper

products, printing and publishing

Relationship by sector: heavy manuf

VNM

PHL

CHN IDNKOR THAMYSTWN

USADEUFRAGBRJPN

TURSVKPOL

HUNMEXINDBRA ZAFRUSCAN

-200%

300%

800%

1300%

1800%

2300%

-100% 0% 100% 200% 300%

23T26: Chemicals and non-metallic

mineral products

VNM

PHL

CHN IDNKOR THAMYSTWNUSADEUFRAGBRJPN

TURSVK POLHUNMEX

IND

BRAZAFRUSCAN

-200%

300%

800%

1300%

1800%

2300%

-100% 0% 100% 200% 300%

27T28: Basic metals and fabricated

metal products

Relationship by sector: GVC manuf

VNM PHL

CHN

IDN

KORTHAMYSTWNUSADEUFRAGBR JPN

TUR

SVKPOL

HUN

MEX

IND

BRAZAF RUSCAN

-200%

300%

800%

1300%

1800%

2300%

-100% 0% 100% 200% 300%

30T33: Electrical and optical

equipment

VNMPHL

CHN

IDNKORTHA

MYSTWNUSADEU FRAGBRJPN

TURSVK

POLHUN

MEX

IND

BRA ZAF

RUSCAN

-200%

300%

800%

1300%

1800%

2300%

-100% 0% 100% 200% 300%

34T35: Transport equipment

VNM

PHL

CHN

IDNKORTHAMYSTWNUSADEUFRAGBR JPN

TUR

SVK

POL HUNMEX

IND

BRAZAFRUSCAN

-200%

300%

800%

1300%

1800%

2300%

-100% 0% 100% 200% 300%

29: Machinery and equipment, nec

Relationship by nation & sector

VNM

CHN IDNTHAMYSKOR

TWN PHL

-200%

300%

800%

1300%

1800%

2300%

-100% 0% 100% 200% 300% 400% 500%

15T16: Food products, beverages and

tobacco

VNM

CHN

IDNTHA MYSKOR TWNPHL

-200%

300%

800%

1300%

1800%

2300%

-100% 0% 100% 200% 300%

20T22: Wood, paper,

printing&publishing

VNM

CHN

IDN

THA

MYSKORTWNPHL

-100%

0%

100%

200%

300%

400%

500%

600%

700%

800%

-50% 0% 50% 100% 150%

17T19: Textiles, leather & footwear

VNMPHL

CHN

IDN

KORTHAMYS

TWN

-200%

300%

800%

1300%

1800%

2300%

-100% 0% 100% 200% 300%


EA EMs

G5

Oth EM

SCTers


VNM

CHN

IDN THAMYS KORTWNPHL

-200%

300%

800%

1300%

1800%

2300%

-100% 0% 100% 200% 300%

23T26: Chemicals & non-metallic

mineral prod

VNM

CHN

IDNTHA

MYS KORTWNPHL

-200%

300%

800%

1300%

1800%

2300%

-100% 0% 100% 200% 300%

27T28: Basic metals and fabricated

metal products

VNMPHL

CHN

IDN

KORTHAMYS

TWN

-200%

300%

800%

1300%

1800%

2300%

-100% 0% 100% 200% 300%


EA EMs

G5

Oth EM

SCTers


VNMPHL

CHN

IDN

KORTHAMYS

TWN

-200%

300%

800%

1300%

1800%

2300%

-100% 0% 100% 200% 300%


EA EMs

G5

Oth EM

SCTers

VNM

CHN

IDN

KORTHAPHLMYSTWN

-200%

300%

800%

1300%

1800%

2300%

-100% 0% 100% 200% 300%

29: Machinery and equipment, nec

VNM CHN

PHL

IDN

TWNMYSTHAKOR

-200%

300%

800%

1300%

1800%

2300%

-100% 0% 100% 200% 300%

30T33: Electrical and optical

equipment

VNMPHL

CHN

IDN

KORTHAMYS

TWN

-200%

300%

800%

1300%

1800%

2300%

-100% 0% 100% 200% 300%


EA EMs

G5

Oth EM

SCTers

Facts to theory

• How does unbundling happen?

– Fractionalisation of production process;

– Geographical dispersion of stages.

Production unbundling: Some theory

Trade-off: Specialisation vs coordination costs

a[n;]

Number of

stages/occupations

euros (n-1/2)

1 n1

Marginal costs (coordination)

Marginal benefits (specialisation)


a[n;]

Number of

stages/occupations

euros (n-1/2)

1 n1 n2

Better IT lowers benefit of fragmentation (automation)


a[n;]

Number of

stages/occupations

euros (n-1/2)

1 n1 n3

Better CT lowers cost of fragmentation (coordination easier)

Geographical dispersion

• Odd economics:

– Clustering/agglomeration

– Convex coordination costs

euros

Stages011/2

ns(1- ns)

Total cost of coordinating given number of stages in two locations

N

Research agenda?

• Link between domestic value-added exports and development (industrial production, GDPPC, etc). – Finer look at domestic value added exports and

domestic value added, by sector, nation groups, etc.

• ‘Dense-ifying’ participation in value network – Not really a ‘chain’; IO matrix, not a IO column.

• Does the partner matter? – Does the REI-growth link vary by source of

intermediates?

• What institutional & policy variables determine supply-chain participation (as measured by REI)

Three policy issues

• Geography matters – Geography is an important determinant of the ease of

participating in Factory Asia.

– This is nothing more than an assertion that forward and backward linkages matter at the regional level as well as at the national or industrial district level.

– ERGO: Policy to foster participation in Factory Asia should have a geographical dimension as well as the usual income level dimension.

– In particular, proximity may be less important for certain sectors and distant nations may be well advised to focus on these.

Three policy issues

• Size matters.

– Nations that have over a billion consumers (the PRC and India) can pursue policies that smaller nations cannot.

– In essence the two giants can leverage their local market as a powerful attraction force for supply chain segments.

– ERGO: Policy recommendations should not blinding point to China’s success as the right way forward. Costa Rica’s success in supply-chains maybe be more relevant to some small Asian nations.

Three policy issues

• Regulatory network effects matter.

– Factory Asia requires firms’ tangible and intangible assets to be protected inside the participating nations.

– Disciplines for these are emerging from mega-regionals.

– Asian policy should focus on what this means for Factory Asia; one-size may not fit all, but one-size disciplines may foster the development and spread of Factory Asia.

END

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