innovation complementarities, management … complementarities, management quality and export ......
TRANSCRIPT
Innovation Complementarities, Management Quality and Export Composition
W. F. Maloney
Research Department, World Bank
Ankara, December 2013
https://openknowledge.worldbank.org/handle/10986/9371
Ancient Latin American Growth Mystery I:
Same Good, Different Outcomes
0
1000
2000
3000
4000
5000
0
5
10
15
20
25
30
35
40
45
1870 1880 1890 1900 1910 1920 1930 1940 1950
Copper in Chile, 1870-1950: Production and % of World Production
% Prod. Mundial Production
Introduction of New Foreign Technologies
Ancient LA Growth Mystery II: Same Business Climate, Different Outcomes
Country Year % Immigrant Directors/Owners
Argentina 1900 80
Chile 1880 70
Colombia (Baranquilla) 1888 60
Mexico 1935 50
Source: Maloney 2013
Percentage of Firms Managed by Immigrants
Structure of the Presentation
• Part I: Export Composition: is this the missing ingredient?
• Part II: Innovation: the critical agenda
• Part III: Management quality as a missing complement
Export Composition-is this the critical ingredient?
Empirical concerns of policy makers about export composition
1. Yes, Externalities dictate that market will not generate optimal basket
2. How do we measure these externalities?
3. Doesn’t the whole world see the same benefit and drive the price down? (GE)
• Interindustry spillovers, assymetries
• Should we look for safe rents, too? Natural Resources
• More generally, must think of demand side as well
4. Do externalities necessarily come with a good, or does it matter how we produce it?
• Heterogeneity, Heterogeneity, Heterogeneity
In practice, measurement of MEs is difficult, so we take shortcuts
• Natural resources
• Low productivity (Smith, Matsuyama, Sachs), few Externalities
• Rent seeking
• High productivity goods
• Rich Country Goods (Rodrik, Hausmann)
• High tech (Lall) high inter-industry MEs
CURSED GOODS: NATURAL RESOURCES
Empirically, there is no resource curse
• In growth regressions • Minerals are good: Davis (1995), Sala-i-Martin et al. (2004), Stijns
(2005), Brunnschweiler (2008, 2009)
• Conditional on education (above 2 years of schooling): Bravo-Ortega & De Gregorio (2007)
• Existing resource curse findings fragile: Lederman & Maloney (2007, 2008)
• [Also, Jacob Viner and Douglass North years ago…]
There is lots of heterogeneity in experiences with NR
Log
GD
P p
er c
apita
199
0
Log Natural Resources (Leamer)-11.5041 11.7949
6
7
8
9
10
Algeria
Argentin
AustraliAustria
Banglade
Benin
Bolivia
Brazil
Burkina Burundi
Cameroon
Canada
Cape Ver
Chad
Chile
China
Colombia
Comoros
Congo, D
Costa Ri
Cyprus
Denmark
Dominica
Ecuador
Egypt, A El Salva
Fiji
FinlandFrance
Gabon
Gambia,
Germany
Ghana
Greece
Guatemal
GuineaGuinea-B
Guyana
Honduras
Hong Kon
Hungary
Iceland
India
Indonesi
Iran, Is
IrelandIsrael
Italy
Cote d'I
Jamaica
Japan
Jordan
Kenya
Korea, R
Madagasc
Malawi
Malaysia
Mali
Mauritan
MauritiuMexico
Morocco
Mozambiq
NetherlaNew Zeal
Nicaragu
Nigeria
Norway
Pakistan
Panama
Papua Ne
ParaguayPeru
Philippi
Poland
Rwanda
Senegal
Sierra L
South Af
Spain
Sri Lank
Sudan
SwedenSwitzerl
Syrian A
Thailand
Togo
Tunisia
Turkey
United K
United S
Uganda
Uruguay
Venezuel
Zambia
Zimbabwe
Leamer Measure: Net Exports of
NR/Worker
Resource Abundant Resource Scarce
Maloney 2007
HIGH PRODUCTIVITY GOODS
Does It Matter What We Export? Hausmann, Hwang, Rodrik (2007) • Model- broadly inter-industry spillover
• Country should produce the highest productivity good within its CA
• Empirics:
• PRODY= avg. income of countries producing good
• EXPY= income value of our export basket
• Similar to Lall (2000)
• Find higher EXPY correlated with higher growth.
Caveats • GE critique again?
• Rents- higher where rich countries already are?
• Not generally the case- Nokia and TVs
• If easy to move into these goods, then barriers to entry/rents low
• Empirical findings muddy
• Animals, electrical machinery same PRODY
Again, high degree of heterogeneity
0
5000
10000
15000
20000
25000
30000
35000 PRODYs (with +/- 1 SD*)
Caveats • GE critique again?
• Rents- higher where rich countries already are?
• Not generally the case- Nokia and TVs
• If easy to move into these goods, then barriers to entry/rents low
• Empirical findings muddy
• Animals, electrical machinery same PRODY
• Finding of an impact on growth fragile
IS IT WHAT WE PRODUCE, OR HOW? BEYOND GOODS
Is High Tech Necessarily High Tech?
CAI=1
Fuente: Lederman and Maloney (2012)
Quality ladders by product and countries (relative unit
values, standardized)
Growth in Quality Driven by Both What and How
Source: Krishna and Maloney 2011
GOODS OR TASKS
Table 2 China: 10 Exports with the Lowest Domestic Value Added
Electronic computer 4.6
Telecommunication equipment 14.9
Cultural and office equipment 19.1
Other computer peripheral equipment 19.7
Electronic element and device 22.2
Radio, television, and communication equipment 35.5
Household electric appliances 37.2
Plastic products 37.4
Generators 39.6
Instruments, meters and other measuring equipment 42.2
China: 10 Exports with the Highest Domestic Value
Added
Agriculture, forestry, animal husbandry and fishing
machinery 81.8
Hemp textiles 82.7
Metalworking machinery 83.4
Steel pressing 83.4
Pottery, china and earthenware 83.4
Chemical fertilizers 84.0
Fireproof materials 84.7
Cement, lime and plaster 86.4
Other non-metallic mineral products 86.4
Coking 91.6
Source: Koopmans, Wang, and Wei (2008).
Goods or Tasks: Does China really export the iPOD?
“..the electronic components we
make in Singapore require less
skill than that required by
barbers or cooks, involving
mostly repetitive manual
operations”
Goh Keng Swee, Minister of
Finance Singapore (1972)
Innovation: The Critical Agenda
Weak innovative capacity meant LA
missed the 2nd Industrial Revolution
Source: Maloney y Valencia (2013)
Innovative Capacity vs Income 1900
Current literature focusing on R&D is not credible...
US firm level/industry data- social returns
Grilliches and Lichtenberg (1984) 71%
Terleckyj 1980, Scherer (1982 ) >100%
Griffith, Redding, Van Reenen (2004) 57%
Jones and Williams (1998) 28%
X country
Coe and Helpman (1995) G7 123%
Van Pottlesberghe and Lichtenberg (2001) G7 68%
…And imply social rates of return far above private
Jones and Williams (1998): US should quadruple investment in RD
Estimated returns to R&D are very high…
…and get higher with distance from the frontier Two Faces of R&D (Cohen and Levinthal 1989) Invention
Learning\Catch-up
Poor countries should have much greater returns
Griffith, Redding, Van Reenen (2004)
Dist. Frontier RoR R&D
USA -.18 57%
UK -.53 77%
Italy -.73 88%
What should the rate of return be for Korea (-1.33),
Malaysia (-2.28), Turkey (-2.5), Indonesia (-3.74)? 200%? 300%?
But poor countries do generally less R&D than rich countries…Why?
R&D/GDP vs Level of Development
2
21
&
CAP
GDP
CAP
GDP
GDP
DR
Innovation Superstars?
0.0%
0.5%
1.0%
1.5%
2.0%
2.5%
3.0%
3.5%
4.0%
4.5%
5.0%
4 5 6 7 8 9 10 11
Log GDP per Capita
Pre
dic
ted
& O
bserv
ed
R&
D/G
DP
IndiaArgentina
China
IsraelFinland
Korea
Mexico
2
21
&
CAP
GDP
CAP
GDP
GDP
DR
Source: Goni, Lederman, Maloney 2006
Rates of Return suggest missing complementary factors
AR
G(1
97
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AR
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AU
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AU
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AU
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BEL
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71
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BO
L(1
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BR
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CH
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CH
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CO
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CR
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CR
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DEU
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DN
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DN
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ECU
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ECU
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EGY(
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ESP
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FIN
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75
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GB
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GTM
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90
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HU
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HU
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IDN
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JAM
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90
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JOR
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81
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85
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JOR
(19
86
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90
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JPN
(19
71
-19
75
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JPN
(19
96
-20
00
)
KO
R(1
97
1-1
97
5)
KO
R(1
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0) M
EX(1
97
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97
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MEX
(19
96
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)
MU
S(1
98
6-1
99
0)
MYS
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91
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95
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MYS
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96
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NLD
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80
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NLD
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96
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NO
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97
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NO
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99
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NZL
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PA
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99
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PER
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USA
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EN(1
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ZAF(
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-4,0
-3,0
-2,0
-1,0
0,0
1,0
2,0
3,0
4,0
-4,0 -3,5 -3,0 -2,5 -2,0 -1,5 -1,0 -0,5 0,0
Ret
irn
s to
R&
D
Distance to the economic frontier
Source: Goni and Maloney 2012
Perceived Quality of Research Institutions
ARG
AUS
AUT
BEL
BRA
CAN
CHE
CHL CHN
CRI
DEU DNK
ECU
EGY
ESP
FIN FRA
GBR
GRC
HUN
IDN
IND
IRL
ISL
ISR
ITA
JPN
KOR
MEX
MYS
NLD
NOR
NZL
PAN
PER
POL
PRT
ROM
SEN
SLV
SWE
TUN
TUR UGA
URY
USA
VEN
0,0
1,0
2,0
3,0
4,0
5,0
6,0
7,0
-5,5 -5,0 -4,5 -4,0 -3,5 -3,0 -2,5 -2,0 -1,5 -1,0 -0,5 0,0
Qu
ali
ty
Distance to the economic frontier (1996-2000)
University-Industry Collaboration
ARG
AUS AUT
BEL
BRA
CAN
CHE
CHL CHN CRI
DEU DNK
ECU
EGY
ESP
FIN
FRA
GBR
GRC
HUN
IDN IND
IRL ISL
ISR
ITA
JPN KOR
MEX
MYS NLD
NOR
NZL
PAN
PER POL
PRT
ROM
SEN
SLV
SWE
TUN TUR UGA
URY
USA
VEN
0,0
1,0
2,0
3,0
4,0
5,0
6,0
7,0
-5,5 -5,0 -4,5 -4,0 -3,5 -3,0 -2,5 -2,0 -1,5 -1,0 -0,5 0,0
Co
lla
bo
rati
on
Distance to the economic frontier (1996-2000)
Business Share in R&D
ARG
AUS
BEL
BRA
CAN
CHE
CHN
CRI
DEU
ESP
FIN
FRA
GBR
HUN
IDN
IND
IRL
ISL
ISR
ITA
JPN
KOR
MEX
MYS
NLD
PER
POL
PRT
ROM
TUN
TUR
URY
USA
0,0
10,0
20,0
30,0
40,0
50,0
60,0
70,0
80,0
90,0
-5,5 -5,0 -4,5 -4,0 -3,5 -3,0 -2,5 -2,0 -1,5 -1,0 -0,5 0,0
GE
RD
-per
form
ed b
y B
usi
nes
s en
terp
rise
%
(yea
r=2
00
0)
Distance to the economic frontier (1996-2000)
Ability to manage risk
Krishna and Maloney 2011
Export Quality Growth and Risk
So, China: Waste or Wisdom?
0.0%
0.5%
1.0%
1.5%
2.0%
2.5%
3.0%
3.5%
4.0%
4.5%
5.0%
4 5 6 7 8 9 10 11
Log GDP per Capita
Pre
dic
ted
& O
bserv
ed
R&
D/G
DP
IndiaArgentina
China
IsraelFinland
Korea
Mexico
2
21
&
CAP
GDP
CAP
GDP
GDP
DR
Who’s doing R&D? Patents granted by the USPTO to inventors based in China
Branstetter 2012
China differs from Taiwan and Korea in the composition of their innovation surges
Branstetter (2012)
Management Quality: A Missing Complement?
Management Quality and Productivity
Argentina
Brazil
China
France
Germany
Great BritainGreece
India
Italy
Japan
Mexico
Northern Ireland
Poland
Portugal
Sweden
US
23
45
6
Lo
g o
f S
ale
s/E
mp
loyees
2.6 2.8 3 3.2 3.4Overall Management Scores
.
Fuente: Bloom et al. 2010+LAC, Sarrias and Maloney (2013)
• Colombia
• Chile
China: Unprepared for indigenous Innovation
Source: Maloney 2013
Convergence to the management frontier-not just more competition
Source: Maloney and Sarrias 2013
Direct interventions in management quality?
• Japan, Korea, Singapore: All employed management promotion programs for SMEs
• Korea: The Small and Medium Industries Promotion program
• Singapore: Local Industry Upgrading Program (LIUP)
• India
• Colombia
• Lays the foundation for progressively more adoption and invention of new technologies.
India-Successful Management Intervention
.2.3
.4.5
.6
-10 -8 -6 -4 -2 0 2 4 6 8 10 12Months after the diagnostic phase
Treatment plants (●)
Control plants (♦)
Shar
e o
f ke
y te
xtile
man
agem
ent
pra
ctic
es a
do
pte
d
Source: Bloom, et al 2013
11
%
pro
du
ctividad
Colombia
• Technological Extension pilot-Autoparts
• RCT 180 firms
• Individual company intervention
• Group intervention- Lower cost, more dynamism?
• Current plans to scale up to whole sector
Thank You