Patterns of Industrialization and
effects of country-specific conditions
IPD/JICA Task Force on Industrial Policy
and Transformation
Jordan, June 5-6, 2014
Nobuya Haraguchi
Motivations
• To understand the process of industrial
development
• To identify development patterns and structural
change
• To find out the way in which country-specific
conditions affect country’s industrial development
Studying development characteristics
of manufacturing industries
Not only the patterns but also the development
characteristics of manufacturing industries
– Use of real value added per capita
– Analysis on output (value added), employment
and labor productivity together
– Their changes as countries develop
– Changes over time (time effects)
Patterns of Manufacturing Development
and
Shift of Comparative Advantage
Manufacturing development patterns
Model
ln RVActi
ln EMPcti  1   2 * ln RGDPct   3 * ln RGDPct2   4 * ln RGDPct3   c i  ect i
ln LPcti
RVA – real value added per capita
EMP – employment-population ratio
LP – labour productivity
RGDP – real GDP per capita (in constant PPP 2005)
RGDP2 – real GDP per capita square,
RGDP3 – real GDP per capita cubic
αc – country fixed effect
e – unexplained residual
i – manufacturing industry (ISIC 2 digit level - 18 industries)
•
Unbalanced panel data
Time series from 1963 – 2010; 75-110 countries depending on the industry
•
Model applied to large (with population more than 12.5 million) and small
country groups separately
•
In addition, we assessed the effects of population density, natural resource
endowment and time periods on industrial development.
Non-parametric approach for estimation
Estimated pattern with actual country observations
Large countries: Basic metals
Japan
1
4 1,0 2,9 8,1 22
2.7 7.3 20.0 54.5 48.4 03.4 96.6 80.9 03.0 ,026
.5
9
9
3
6
8
1
2
9
1
3
VA per capita (US$)
1,0 2,9 8,1 22
1
4
7.3 20.0 54.5 48.4 03.4 96.6 80.9 03.0 ,026
.5
9
9
3
6
8
9
1
3
Large countries: Textiles
Japan
Australia
Germany
Canada
United
United
Kingdom
States of America
France
Netherlands
Spain
RussianArgentina
Federation
South AfricaItaly
PeruRomania
Poland Venezuela (Bolivarian Republic of)
Mexico
United
Kingdom
United
States of America
Germany
France
Canada
Netherlands
Australia
Argentina
Italy Spain
1
2.7
2
Brazil
Turkey PeruRomania
Colombia South Africa
Poland Venezuela (Bolivarian Republic of)
Egypt
Mexico
Republic
ofMorocco
KoreaIran (Islamic
China
Philippines
of)
Nigeria
RussianRepublic
Federation
Pakistan
Bangladesh
Algeria
Thailand Malaysia
Viet
Nam
Sudan
IndiaNepal
Kenya
0.1 0.3
4
7
0.3
7
EthiopiaIndonesia
Indonesia
Colombia
Egypt
China Philippines
Turkey
RepublicMalaysia
of Algeria
Korea
Uganda
India Bangladesh
Thailand
Viet Nam
Morocco
Sri Lanka
Sudan
Pakistan
Nepal
0.1
4
Sri Lanka
403
1,097
2,981
8,103
22,026
59,874
403
Real GDP per capita (US$)
Source: UNIDO estimate based on UNIDO INDSTAT2
1,097
2,981
8,103
Real GDP per capita (US$)
22,026
59,874
95% confidence intervals (after anti-log)
Source: UNIDO estimate based on UNIDO INDSTAT2
Development patterns
Electrical
machinery and
apparatus
Chemical
Motor
vehicles
Wearing
apparel
Textiles
Fabricated
metals
Food and
beverage
20
.0
9
1,
09
14
40
54
6.
8.
3.
.5
63
4
4
9
1
3
Large countries
1
2.
72
7.
39
Basic metals
1,097
2,981
8,103
22,026
Real GDP per capita (US$)
Food and beverages
Wearing apparel
Basic metals
Electrical machinery and apparatus
Textiles
Chemicals
Fabricated metals
Motor vehicles
Development patterns
Chemical
Food and
beverage
Wearing
apparel
Electrical
machinery and
apparatus
Fabricated
metals
Textiles
20
.0
9
1,
09
14
40
54
6.
8.
3.
.5
63
4
4
9
1
3
Small countries
7.
39
Basic metals
1
2.
72
Motor
vehicles
1,097
2,981
8,103
22,026
Real GDP per capita (US$)
Food and beverages
Wearing apparel
Basic metals
Electrical machinery and apparatus
Textiles
Chemicals
Fabricated metals
Motor vehicles
Changes in growth rates
Large countries (population more than 12.5 million)
Food and beverages
Tobacco
Textiles
Wearing apparel
Wood products
Paper
Printing and publishing
Coke and refined petroleum
Chemicals
Rubber and plastic
Non-metallic minerals
Basic metals
Fabricated metals
Machinery and equipment
Electrical machinery and apparatus
Precision instruments
Motor vehicles
ela=0
0<ela<1
1<ela<2
ela > 2
0
10000
20000
Source: UNIDO estimate based on UNIDO INDSTAT2
30000
40000
50000
Employment,
labour intensive industries
industries
Value
added, labour-intensive
per capita
Value added
EP ratio
0.6
300
Food and
beverage
0.5
250
Food &
beverages
0.4
200
Wearing
apparel
150
0.3
Wearing
apparel
Textiles
100
0.2
Textiles
50
0.1
0
0
EP
∆∆
∆∆
∆∆
∆∆
∆
∆
∆
∆
∆
∆
∆
∆
−
−
−
−
−
−
−
−
−
VA
++
++
++
++
++
+
+
+
+
+
+
+
+
∆∆
∆∆
∆∆
∆∆
∆∆
∆∆
∆∆
∆∆
LP
++
+
+
+
+
+
+
∆∆
∆∆
∆∆
∆∆
∆∆
∆∆
∆∆
∆∆
∆∆
∆∆
∆∆
∆∆
∆∆
∆∆
Textiles
EP
∆
∆
∆
∆
∆
−
−
−
−
−−
−−
−−
−−
VA
+
++
++
++
++
+
+
+
+
∆∆
∆∆
∆∆
∆∆
∆
∆
∆
∆
−
−
−
−
LP
++
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
Wearing
Apparel
Food &
beverage
1000 2000 3000 4000 5000 6000 7000 8000 9000 10000 11000 12000 13000 14000 15000 16000 17000 18000 19000 20000 21000
EP
+
++
++
++
++
+
+
∆∆
∆∆
∆
∆
∆
−
−
−−
−−
−−
+++
+++
++
++
+
+
∆∆
∆∆
∆∆
∆
∆
∆
∆
−
−
−
−
−
−
−
∆
∆
∆
∆
∆
∆∆
∆∆
∆∆
∆∆
∆∆
∆∆
∆∆
∆∆
∆∆
∆∆
∆∆
∆∆
∆∆
∆∆
∆∆
VA +++
LP
−
+++
e≥2
++
2 > e ≥ 1.5
+
1.5 > e ≥ 1
∆∆
∆
1 > e ≥ 0.5
0.5 > e ≥ 0
−−− −−− −−− −−− −−− −−− −−− −−−
−
0 > e ≥ - 0.5
−−− −−− −−− −−−
−−
- 0.5 > e ≥ -1
−−−
-1> e
EP ratio
per capita
Value added
Value added - late industry
Employment - late industries
400
0.3
350
0.25
300
Electrical
machinery
Electrical
machinery
0.2
250
200
0.15
150
0.1
100
0.05
50
Rubber & plastic
Rubber & plastic
00
Electrical
machinery
Rubber
plastic
6000 7000 8000 9000 10000 11000 12000 13000 14000 15000 16000 17000 18000 19000 20000 21000 22000 23000 24000 25000 26000
EP
∆∆
∆∆
∆∆
∆∆
∆∆
∆
∆
∆
∆
∆
∆
∆
∆
∆
∆
∆
∆
∆
−
−
−
VA
++
++
++
++
++
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
LP
∆∆
∆∆
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
EP
+
+
+
∆∆
∆∆
∆∆
∆∆
∆
∆
∆
−
−
−
−
−−
−−
−−
−−
VA
+++
+++
+++
+++
+++
+++
+++
+++
+++
++
++
++
++
++
++
++
++
++
++
++
++
LP
+
+
+
+
+
+
+
++
++
++
++
++
+++
+++
+++
+++
+++
+++
+++
+++
+++
+++
e≥2
++
2 > e ≥ 1.5
+
1.5 > e ≥ 1
∆∆
∆
1 > e ≥ 0.5
0.5 > e ≥ 0
−
0 > e ≥ - 0.5
−−− −−− −−−
−−
- 0.5 > e ≥ -1
−−−
-1> e
Effects of Country-Given Conditions
Effects of Population Density and Resource Endowments
on manufacturing value added
strongly negative
strongly positive
Large countries
High Population Density
Strongly Positive
Machinery and equipment
Electrical machinery and apparatus
Motor vehicles
Chemicals
Rubber and plastic
Non-metallic minerals
Fabricated metals
Food and beverages
Textiles
Paper
Wood products
Wearing apparel
Tobacco
Furniture, n.e.c.
Strongly Negative
High Resource Endowments
Strongly Positive
Machinery and equipment
Paper
Rubber and plastic
Non-metallic minerals
Printing and publishing
Wood products
Food and beverages
Motor vehicles
Basic metals
Chemicals
Coke and refined petroleum
Electrical machinery and apparatus
Tobacco
Strongly Negative
Source: UNIDO estimate based on UNIDO INDSTAT2
Time Specific Effects
Emerging trends
Textiles
.
.
.
.
Source: UNIDO estimate based on UNIDO INDSTAT2
Emerging trends (Employment pattern)
Tobacco
Textiles
Wood products
Coke, refined petro
Chemical products
Non-metallic mineral
Basic metals
Fabricated metals
Machinery and equipment
Electrical machinery
Motor vehicles
Furniture, nec
70s
+
+
+
80-85 85-90 90-95 95-00 00-05 05-10
+
+
+
+
+
+
Source: UNIDO estimate based on UNIDO INDSTAT2
Emerging trends (Value added pattern)
Tobacco
Textiles
Wearing apparel
Wood products
Paper
Chemical products
Rubber and plastic
Basic metals
Electrical machinery
Motor vehicles
70s
+
+
+
+
+
+
+
+
+
+
80-85 85-90 90-95 95-00 00-05 05-10
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
-
Source: UNIDO estimate based on UNIDO INDSTAT2
Emerging characteristics of manufacturing industries
since 1980
Emerging characteristics since
1980
Rising
Declining
Intensifying capital use
Industry
Rubber and plastic
Tobacco
Textiles
Paper
Chemicals
Non-metallic minerals
Basic metals
Fabricated metals
Electrical machinery and apparatus
Motor vehicles
Intensifying labour use
Furniture
Stable
Food and beverages
Source: UNIDO’s elaboration based on CIC 2009; UNIDO Database (UNIDO 2012a).
Country-Specific Effects
Country experiences
Source: UNIDO estimate based on UNIDO INDSTAT2
Country experiences
Source: UNIDO estimate based on UNIDO INDSTAT2
Country experiences
Source: UNIDO estimate based on UNIDO INDSTAT2
Country specific effects
Source: UNIDO estimate based on UNIDO INDSTAT2
Speed of manufacturing development
Industry
Food and beverages
Textiles
Wearing apparel
Chemicals
Basic metals
Fabricated metals
Republic of Korea
Malaysia
Sri Lanka
4.74
11.49
13.37
3.55
3.62
2.71
1.46
0.6
0.66
1.32
0.38
0.24
0.64
0.61
1.43
0.19
0.03
0.09
Electrical machinery and apparatus
7.53
0.78
0.1
Motor vehicles
5.28
0.4
0.13
Note: The speed is expressed as an
increase in value added per capita divided
by the number of years taken over the
range of GDP per capita from US$ 3,000 to
US$ 4,500.
Source: UNIDO calculations based on UNIDO INDSTAT2
Speed of structural change
Consumer goods/capital goods value added
ratio
3.5
3
2.5
Korea, Rep
2
China
1.5
Pakistant
Colombia
1
0.5
0
1965 1970 1975 1980 1985 1990 1995 2000 2005 2008
Source: UNIDO estimate based UNIDO INDSTAT2
Graphic representation of the role of comparative advantage and
country-specific and time effects in manufacturing development
Country-specific and
time effects
Value added
per capita
Level deviation
Speed
Speed
Industry A
Comparative
advantage
$3,000
Source: UNIDO’s elaboration
Industry B
$10,000
GDP per capita (PPP)