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 Developmentand

Shift of Comparative Advantage

Manufacturing development patterns

Model

RVA – real value added per capitaEMP – employment-population ratioLP – labour productivityRGDP – real GDP per capita (in constant PPP 2005)RGDP2 – real GDP per capita square, RGDP3 – real GDP per capita cubicαc – country fixed effect e – unexplained residuali – manufacturing industry (ISIC 2 digit level - 18 industries)

• Unbalanced panel dataTime 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.

ictRVAlnictEMPln

ictLPln

ict

icctctct eRGDPRGDPRGDP 3

42

321 ln*ln*ln*

Non-parametric approach for estimation

Algeria

Argentina

Australia

Bangladesh

Canada

Sri Lanka

ChinaColombia

FranceGermany

India

Indonesia

Italy

Japan

Republic of KoreaMalaysia

Mexico

Morocco

Nepal

Netherlands

Pakistan

Peru

Philippines

PolandRomaniaRussian Federation

Viet Nam

South Africa

Spain

Sudan

Thailand

Turkey

Uganda

Egypt

United KingdomUnited States of AmericaUnited States of America

Venezuela (Bolivarian Republic of)

VA per cap

ita (U

S$)

403 1,097 2,981 8,103 22,026 59,874Real GDP per capita (US$)

Large countries: Basic metals

Source: UNIDO estimate based on UNIDO INDSTAT2

Estimated pattern with actual country observations

Algeria

Argentina Australia

Bangladesh

Brazil

Canada

Sri Lanka

China

Colombia

Ethiopia

FranceGermany

India

Indonesia

Iran (Islamic Republic of)

Italy

Japan

Kenya

Republic of Korea

Malaysia

MexicoMorocco

Nepal

Netherlands

NigeriaPakistan

Peru

Philippines

PolandRomania

Russian Federation

Viet Nam

South Africa

Spain

SudanThailand

Turkey

Egypt

United KingdomUnited States of AmericaUnited States of America

Venezuela (Bolivarian Republic of)

VA per

cap

ita (U

S$)

403 1,097 2,981 8,103 22,026 59,874Real GDP per capita (US$)

Large countries: Textiles

95% confidence intervals (after anti-log)

Source: UNIDO estimate based on UNIDO INDSTAT2

VA

per

cap

ita (U

S$)

1,097 2,981 8,103 22,026Real GDP per capita (US$)

Food and beverages TextilesWearing apparel ChemicalsBasic metals Fabricated metalsElectrical machinery and apparatus Motor vehicles

Large countries

Food and beverage

Textiles Wearing apparel

Chemical

Electrical machinery and apparatus

Motor vehicles

Fabricated metals

Basic metals

Development patterns

VA p

er c

apita

(US

$)

1,097 2,981 8,103 22,026Real GDP per capita (US$)

Food and beverages TextilesWearing apparel ChemicalsBasic metals Fabricated metalsElectrical machinery and apparatus Motor vehicles

Small countries

Textiles

Wearing apparel

Food and beverage

Chemical

Electrical machinery and apparatus

Fabricated metals

Basic metals

Motor vehicles

Development patterns

Motor vehiclesPrecision instruments

Electrical machinery and apparatusMachinery and equipment

Fabricated metalsBasic metals

Non-metallic mineralsRubber and plastic

ChemicalsCoke and refined petroleum

Printing and publishingPaper

Wood productsWearing apparel

TextilesTobacco

Food and beverages

0 10000 20000 30000 40000 50000

Large countries (population more than 12.5 million)

ela > 21<ela<20<ela<1ela = 0

Source: UNIDO estimate based on UNIDO INDSTAT2

Changes in growth rates

EP ∆∆ ∆∆ ∆∆ ∆∆ ∆ ∆ ∆ ∆ ∆ ∆ ∆ ∆ − − − − − − − − −VA ++ ++ ++ ++ ++ + + + + + + + + ∆∆ ∆∆ ∆∆ ∆∆ ∆∆ ∆∆ ∆∆ ∆∆LP ++ + + + + + + ∆∆ ∆∆ ∆∆ ∆∆ ∆∆ ∆∆ ∆∆ ∆∆ ∆∆ ∆∆ ∆∆ ∆∆ ∆∆ ∆∆

EP ∆ ∆ ∆ ∆ ∆ − − − − − − − − − − − − − − − − − − − − − − − − − − − − − − − − − − − −

VA + ++ ++ ++ ++ + + + + ∆∆ ∆∆ ∆∆ ∆∆ ∆ ∆ ∆ ∆ − − − −LP ++ + + + + + + + + + + + + + + + + + + + +

EP + ++ ++ ++ ++ + + ∆∆ ∆∆ ∆ ∆ ∆ − − − − − − − − − − − − − − − − − − − −

VA +++ +++ +++ ++ ++ + + ∆∆ ∆∆ ∆∆ ∆ ∆ ∆ ∆ − − − − − − −LP − ∆ ∆ ∆ ∆ ∆ ∆∆ ∆∆ ∆∆ ∆∆ ∆∆ ∆∆ ∆∆ ∆∆ ∆∆ ∆∆ ∆∆ ∆∆ ∆∆ ∆∆ ∆∆

Food

&

beve

rag

e

Texti

les

Wea

ring Ap

pare

l

+++ ++ + ∆∆∆ − −− 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

1000 2000 3000 4000 5000 6000 7000 8000 9000 10000 11000 12000 13000 14000 15000 16000 17000 18000 19000 20000 210000

0.1

0.2

0.3

0.4

0.5

0.6Employment, labour intensive industries

EP ra

tio

Wearing apparel

Food and beverage

Textiles

0

50

100

150

200

250

300

Value added, labour-intensive industriesVa

lue

adde

d pe

r cap

ita

Food & beverages

TextilesWearing apparel

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

Rubb

er

plas

ticEl

ectr

ical

m

achi

nery

0

0.05

0.1

0.15

0.2

0.25

0.3

Employment - late industriesEP

ratio

Rubber & plastic

Electrical machinery

0

50

100

150

200

250

300

350

400Value added - late industry

Valu

e ad

ded

per c

apita

Electrical machinery

Rubber & plastic

Effects of Country-Given Conditions

High Population Density High Resource Endowments

strongly

positive

Strongly PositiveMachinery and equipmentElectrical machinery and apparatus Motor vehicles ChemicalsRubber and plasticNon-metallic minerals Fabricated metals Food and beverages

Strongly Positive

Machinery and equipment

strongly negative

Textiles Paper Wood products Wearing apparel Tobacco Furniture, n.e.c.

Strongly Negative

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

Effects of Population Density and Resource Endowments on manufacturing value added

Large countries

Source: UNIDO estimate based on UNIDO INDSTAT2

Time Specific Effects

Emerging trends

.

.

.

.

Source: UNIDO estimate based on UNIDO INDSTAT2

Textiles

70s 80-85 85-90 90-95 95-00 00-05 05-10Tobacco - - - - - - -Textiles - - - - - - -Wood products - - - - - - -Coke, refined petro + - - - - -Chemical products - - - - -Non-metallic mineral - - - - -Basic metals - - - - -Fabricated metals - - - - - - -Machinery and equipment

+ + - - - -

Electrical machinery + + - - - -Motor vehicles - - - - -Furniture, nec + + + +

Emerging trends (Employment pattern)

Source: UNIDO estimate based on UNIDO INDSTAT2

70s 80-85 85-90 90-95 95-00 00-05 05-10Tobacco + - - - - -Textiles + - - -Wearing apparel + - - -Wood products + - - - - - -Paper + + + + + + -Chemical products + + + + + Rubber and plastic + + + + + + Basic metals + + + + + Electrical machinery + + + + + - +Motor vehicles + + + + + -

Emerging trends (Value added pattern)

Source: UNIDO estimate based on UNIDO INDSTAT2

Emerging characteristics of manufacturing industries since 1980

Emerging characteristics since

1980 Industry

Rising Rubber and plastic Declining Tobacco Textiles Paper Chemicals Non-metallic minerals Intensifying capital use 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 developmentIndustry Republic of Korea Malaysia Sri Lanka

Food and beverages 4.74 1.46 0.64Textiles 11.49 0.6 0.61Wearing apparel 13.37 0.66 1.43Chemicals 3.55 1.32 0.19Basic metals 3.62 0.38 0.03Fabricated metals 2.71 0.24 0.09Electrical machinery and apparatus 7.53 0.78 0.1Motor 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

Source: UNIDO estimate based UNIDO INDSTAT2

1965 1970 1975 1980 1985 1990 1995 2000 2005 20080

0.5

1

1.5

2

2.5

3

3.5

Korea, RepChinaPakistantColombia

Cons

umer

goo

ds/c

apita

l goo

ds v

alue

add

ed

ratio

$3,000 GDP per capita (PPP)

Value added per capita

$10,000

Comparative advantage

Country-specific and time effects

Industry A

Industry BSpeed

SpeedLevel deviation

Source: UNIDO’s elaboration

Graphic representation of the role of comparative advantage and country-specific and time effects in manufacturing development