“the development and future of factory asia”indonesia, thailand, turkey, poland stage share of...
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“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
VA export growth composition,
1995 to 2009
Manufactures Services Primary
Thinking about nation groups
0% 20% 40% 60% 80% 100%
JPN
CAN
ITA
DEU
USA
FRA
GBR
VA export growth composition,
1995 to 2009
Manufactures Services Primary
0% 25% 50% 75% 100%
SVK
HUN
SVN
CZE
POL
MEX
ROU
TUR
PRT
VA export growth composition,
1995 to 2009
Manufactures Services
Aside: BRICS asunder
0% 25% 50% 75% 100%
RUS
BRA
ZAF
CHN
IND
VA export growth composition,
1995 to 2009
Manufactures Services Primary
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%
34T35: Transport equipment
EA EMs
G5
Oth EM
SCTers
Relationship by nation & sector
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%
34T35: Transport equipment
EA EMs
G5
Oth EM
SCTers
Relationship by nation & sector
VNMPHL
CHN
IDN
KORTHAMYS
TWN
-200%
300%
800%
1300%
1800%
2300%
-100% 0% 100% 200% 300%
34T35: Transport equipment
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%
34T35: Transport equipment
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)
Trade-off: Specialisation vs coordination costs
a[n;]
Number of
stages/occupations
euros (n-1/2)
1 n1 n2
Better IT lowers benefit of fragmentation (automation)
Trade-off: Specialisation vs coordination costs
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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