some concepts for understanding

Some Concepts for Understanding Export Diversification and Sustainable

GrowthPart I

Inclusive Growth Conference

Vandana Chandra Nairobi, Kenya

September 28 – 29, 2011

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Data and Sources of Information

• World Bank Open Data Initiative - Website• PREM Economic Policy and Debt – Economic Diversification Toolkit http://info.worldbank.org/etools/prmed/ (developed by V. Chandra and I. Osorio)• Combined with the Moving Forward Tool – made available on Excel

sheets• UN Comtrade1. World Integrated Trade Study (WITS – http://wits.worldbank.org)

2. Data exists for almost all countries3. Tools exist – constructed for export diversification analysis4. Country and sector-specific5. Applications – Uganda, Ghana, Benin, Burkina Faso; WDR 2009 –

Box 9 (regional integration)

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http://www.intracen.org/�

http://info.worldbank.org/etools/prmed/�

http://wits.worldbank.org/�



Objective

• Introduce a few questions and concepts that are useful in exploring the nexus between export diversification and sustainable growth in the longer term

• Discuss a few measures of export sophistication and diversification

• The country economist (CE) may not be able to dissuade an impatient client (government) from implementing its industrial policy but may find the concepts useful in informing policy decisions

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What this presentation does not do

• This presentation does not provide a survey of trade theory.

• The empirical evidence on trade between countries and its economic effects is growing rapidly. This presentation does not provide a survey of such evidence.

• It does not present a comprehensive coverage of the various tools economists use to understand trade and economic growth.

• Its purpose is much simpler. It explains how we can try to understand the pattern of trade in a country or across a group of countries by applying a few simple tools. Not exhaustive.

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Why would a country want to diversify?• By the mid-1990s, most developing countries had implemented the

macroeconomic reforms that are necessary for economic growth. BUT• Export diversification which is essential for sustained and inclusive growth

did not ensue in many developing countries. • Unemployment, social and political pressures – jobs!. • Some governments have announced industrial policies targeted at

industries they believe can deliver faster and more inclusive growth. Most choices are motivated by inclusive growth considerations.

• A government’s choice of industries is frequently ad hoc and targets non-traditional industries in which the country may not have a comparative advantage.

• This shift in public policy from an industry-neutral to an industry-specific approach has created a demand for analytical tools to study the economic growth implications of industrial policy – insights are interesting.

• We will focus on a few such tools.

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Why do policy makers care about export diversification?

• 1980 – 2010: except for a handful, in most LICs and MICs, GDP per capita barely increased

• Laggards are impatient to catch up with richer countries, especially since the emergence of the BRICs

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China and India in the Catch Up Game (trend in per capita income)

Lower Middle Income

China

India

Low Income

Source: World Development Indicators

Korea and Brazil Catching up with OECD Countries (trends in per capita income)

South Korea

Brazil

High Income OECD

Singapore High Incomenon OECD

Lower Middle Income

Source: World Development Indicators

Per capita income trends in Sub-Saharan Africa have been stagnant for 46 years!

Sub-Saharan Africa - trends in per capita income (2000 constant USD)

-

100

200

300

400

500

600

700

19601962

19641966

19681970

19721974

19761978

19801982

19841986

19881990

19921994

19961998

20002002

20042006

GDP

per c

apita

BDI Burundi ETH Ethiopia NER NigerMWI Malawi SLE Sierra Leone CAF Central African RepublicMDG Madagascar MLI Mali BFA Burkina FasoGHA Ghana MOZ Mozambique BEN BeninTZA Tanzania ZMB Zambia NGA NigeriaKEN Kenya SEN Senegal LSO Lesotho

Are natural resource-based economies less diversified?

• Is there a natural resource curse? Prebisch and Singer in 50s and 60s and Sachs and Warner ’90s). “Natural Resources are Neither Curse nor Destiny” – Lederman and Maloney, 2006.

• Is Sub-Saharan Africa special? Transactions costs, and risks of manufactured exports (Collier, 1998, 1999), Primary Commodity Dependence and Africa’s Future, Paul Collier (2002), low skills, land abundance (Mayer and Woods, 2001) and low Net TFP (Eifert, Gelb and Ramachandran, 2005); infrastructure (Habiyaremya and Ziesemer,2006).

• Deterministic – These hypotheses suggest that in poor countries, manufactured exports are the PATH to growth

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The relationship between sustained growth and openness/exports

In natural resource-based economies, diversification helps to dissipate the negative effects of terms of trade shocks. In more developed ones, agglomeration effects reinforce economic concentration.

We need a better measure of diversification that links exports to a country’s per capita GDP.

Q: What type of products should China export to catch up with Brazil?

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Some hypotheses about the export mix and the growth path

• Technology classification (Lall, 2005)– Links a product to its technology content. – Cereals and fish are primary (PP), minerals are resource-

based (RB) and manufactured products are low, medium or hi tech (LT, MT,HT)

– We need a better measure of diversification that links exports to a country’s per capita GDP. Q: What type of products should China export to catch up with Brazil? Cannot answer with the Herfdindahl Index.

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Technology classification - High and sustained growth has occurred in countries that export mostly LT, MT and HT products

Cereals and fish are primary (PP), minerals are resource-based (RB) and manufactured products are low, medium or hi tech (LT, MT,HT)

• Problem: Too deterministic. Implies manufactured exports (from OECD and East Asia) are the only path to growth.

0.2

.4.6

.81

SA LAC SSAnoZAF OECD First_EA

First EA: HKG, TWN, KOR and SGP

1990-95

HT MTLT RBHV PP

0.2

.4.6

.81

SA SSAnoZAF LAC OECD First_EA

First EA: HKG, TWN, KOR and SGP

2000-04

HT MTLT RBHV PP

Regional export composition, Tech categories

Technology classification – The technological composition of Burkina Faso’s exports changed very little in 22 years

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

BFA

PRY

VNM

GTM

MLI

BEN

NIC

BGD

1980-84

PP RB LT MT HT

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

BFA

PRY

VNM

GTM

MLI

BEN

NIC

BGD

2000-06

PP RB LT MT HT

Pattern of export diversification in China

Are some new products richer than others?

• The technology classification does not offer a metric that objectively indicates whether the new products are good or bad for a sustained increase in per capita income.

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Metric: PRODY denotes a product’s sophistication which suggests a notional level

of per capita income

• Designed by Hausmann, Hwang, and Rodrik (2007).

• PRODY and EXPY are indexes that measure export sophistication or which suggest a notional level of income for a product and country’s exports respectively.

• The core idea is that (ceteris paribus) “An economy is better off producing goods that richer countries export.”

• “Countries that export goods associated with higher productivity levels grow more rapidly”

• Sources: Hausmann, Ricardo, Jason Hwang, and Dani Rodrik. 2007. What you export matters. Journal of Economic Growth (U.S.) 12, No. 1:1-25.

• Rodrik, D. (2006). “What’s So Special About China’s Exports,” NBER Working Paper Series, No. 11947.

PRODY – THE INCOME-LEVEL OF A PRODUCT

“Rich countries export rich country products.”

The productivity level associated with product k:

*GDP_j

� Where xjk=Xj , is the value-share of the commodity in the country’s overall export basket. � The denominator aggregates the value-shares across all countries exporting the good � The index represents a weighted average of per-capita GDPs, � Weights are the revealed comparative advantage of each country in good k

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Sophistication of a Product: PRODY

Prody value of selected Products (by tech category)

0

5,000

10,000

15,000

20,000

25,000

30,000

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HT & MT LT RB PP

Prod

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S$)

Designed by Hausmann, Hwang and Rodrik (2005). (Lall (2005)..)

Reflects the per capita GDP of each country that exports the product weighted by the exporter’s revealed comparative advantage in it.

Attaches to each product a value that reflects the income potential/level of the product.

More PRODYs ….

-

5

10

15

20

25

30

PRO

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('000

)

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High-Medium-Low Tech Manufactures Primary Products and Resource Based

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EXPY – The income potential of a country’s export basket

Defining EXPY – summation of the PRODYs (weighted) The productivity level associated with a country’s i’s export basket, EXPY, is in turn defined by

This is a weighted average of the PRODY for that country, where the weights are simply the value shares of the products in the country’s total exports. Source: Hausmann, Hwang and Rodrik (2005)

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EXPY is a good measure of the export sophistication of a country’s exports. EXPY & GDP per capita are highly correlated

Source: Hausmann, Hwang and Rodrik (2005)

Pitfalls of PRODY and EXPY

• In general, they are good indicators of income-enhancing diversification for low income countries or countries that export mostly primary or resource-based commodities.

• They are not suitable for large countries such as China and India –both outliers on the EXPY chart.

• Across-Product versus Within Product Specialization in International Trade, Peter K. Schott, The Quarterly Journal of Economics, May 2004

• The Relative Sophistication of Chinese Exports, Peter K. Schott, Yale School of Management & NBER, March 2007

• Draw upon empirical evidence but cannot explain it.

• Caution – should not be used as lone indicators to guide production patterns.

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Product Space

• Hausmann and Klinger’s (2007) Product Space concepts link one product to another by using similarities in the capabilities of a country to export both products – rigorous and objective

Contribution:• (1) a framework to analyze how export sophistication can become

a channel of growth – cross-country, SSA-specific, regional trading arrangements and country-specific level

• (2) Policy implications –– manuf exports: not the only way to grow; – variety of growth paths and many different ways of “how to” – CA can be acquired; – role of capability building – puts the burden of development

policy on government as opposed to grappling with external factors, as per CA.

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Towards Export Diversification –Path and export possibilities in the Product Space

R. Hausmann and Klinger (2007): “Product space is used to describe the network of relatedness between products.”

Relatedness is based on the observed similarity in inputs required to produce products, and includes everything from natural factors, skills, institutional and infrastructural requirements, to technological capabilities etc..

Distance measures the conditional probability of exporting a new product if you already have a revealed comparative advantage in one. The distance between textiles and garments is shorter than the (a) distance between textiles and cotton; or (b) the distance between textiles and coffee.

Distance between a pair of products

The first step is to identify the products on which each country experiences a revealed comparative advantage (RCA). For this, we have calculated the Balassa-RCA Index for each country, commodity and year in our sample. In a given year (t), a country (c) has a revealed comparative advantage in a certain product (i) if the RCA Index is greater than 1. For example, Ghana has a revealed comparative advantage in cocoa because Ghana’s cocoa share in world cocoa exports is greater than Ghana’s share in total world exports.

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In the third step, we construct a measure that can identify revealed distance between products that can avoid any priors we might have as to the root cause of that similarity. Hausmann and Klinger (2006) call it product distance. Product distances (φ) for each pair of products (i,j) are calculated using the minimum of two conditional probabilities: the probability of having RCA in product j, given that countries experience RCA in product i; and the probability of having RCA in product i, given that countries experience RCA in product j.


With these calculations we can construct a matrix with all the minimum conditional probabilities for each pair of products. This matrix is a representation of the product space. It contains a numerical measure of revealed distance between each pair of products in the classification.

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Distances between products reflect similarity in inputs of production

Dist=0.18

Prepared crustaceans

FreshVegetables

Wood

Dist=0.12

Dist=0.15

Plywood

Paper

Parts of engines

Dist=0.16

Frozen Fish fillet

Structural transformation- the process of how firms move from the poor to the rich part of the forest. It is easier for firms to jump short distance to products that use similar pre-existing factors

Dist=0.45

Dist=0.04

Cotton

Coffee

Dist=0.32

Dist=0.09

Examples of distances between products

The Product Space Can Be Understood as a Network of Products

Source: Hidalgo, Klinger, Barábasi, Hausmann (2007)

The Product Space - a Forest or Network of Products

Density – a country’s capability to export a product – country-specific concept

we develop the concept of product density. It is obtained using previously calculated product distances and categorical variables.

The concept of density recognizes that the more one pair of exporting products are related, the stronger the force to create RCA in one, given that the other had already attained it.

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Density is a country’s capability to jump to new products e.g. to jump to fish fillet from the current export basket

(higher is better)

Cotton seed oil

Benin’s Density in Cotton seed oil= 0.08

India’s Densityin Cotton seed oil= 0.35

USA and South Africa have the Highest Density in cotton seed oil: 0.46 and 0.36 respectively

Fabrics,woven Distance: 0.04DENSITY:0.039

Manufactures of wood for domestic use Distance= 0.17DENSITY: 0.39

Cotton uncarded : Distance: 0.33DENSITY:0.13

Manufactures of wood for domestic use Distance= 0.17DENSITY: 0.08

Fabrics,woven Distance: 0.04DENSITY:0.31

Cotton uncarded : Distance: 0.33DENSITY: 0.42

Our framework: A classification of Burkina Faso’s exports by Revealed Comparative Advantage

(table 1)

CLASSICS – prodcuts in which BF’s RCA in the earlier period was high and in recent period continues to remain high.

Implication – its strong, maintain it

1980-84: RCA = 1

2001-05: RCA = 1

DISAPPEARANCES – prodcuts in which BF’s RCA in the earlier period was high but in recent period is low. Implication – declining competitiveness, leave them alone.

1980-84: RCA = 1

2001-05: RCA = 0

MARGINALS – products in which BF did not and does not have a RCA

Implication – observe and let them grow

1980-84: RCA = 0

2001-05: RCA = 0

EMERGING CHAMPIONS – products in which BF’s RCA was low in the earlier period but high in recent period. Implication – build on these new discoveries and nascent products.

1980-84: RCA = 0

2001-05: RCA = 1

RCA 80-84 = 1 SHARE SHARE RCA 80-84 = 1 SHARE SHARERCA 00-04 = 1 80-84 00-06 RCA 00-04 = 0 80-84 00-06 Cotton uncarded 32.1 62.3 1,500 Gold 2.3 1.2 5,716 Sesame seeds 4.0 3.9 1,179 Oil cake & residues 2.6 0.3 5,718 Leather 0.9 1.5 2,159 Sheep and lamb skins 2.1 - 4,956 Other Vegetables 4.0 1.3 5,477 Basketwork, wickerwork 0.2 - 7,789

RCA 80-84 = 0 SHARE SHARE PRODY RCA 80-84 = 0 SHARE SHARE PRODYRCA 00-04 = 1 80-84 00-06 RCA 00-04 = 0 80-84 00-06 Sugar - 3.4 4,516 Cotton seeds - 0.9 2,473 Cigarretes - 3.2 12,204 Cotton yarn - 0.8 4,262 Sheep/lamb skin leather 0.1 1.7 2,526 Bovine animals 3.4 0.1 4,391 Cotton seed oil - 0.8 3,173 Work of Art 0.2 0.2 8,542

(a) The Classics (b) Disappearances

(c) Emerging Champions (d) Marginals

PRODY PRODY

A classification of Burkina Faso’s exports by Revealed Comparative Advantage and PRODY (table 2)

Classics Emerging Champions Disappearances Marginals

Burkina Faso Product Space

Cotton (other than linters),not carFruit,fresh or dried, n.e.s.

Sesame (sesamum)seeds

Oil seeds and oleaginous fruit. n.e

Leather of other hides or skins

Other fresh or chilled vegetables


Burkina Faso Product SpaceClassics

Maize (corn),unmilled

Buckwheat,millet,canary seed,grain

Vegetable products,roots & tubers,

Sugars,beet and cane,raw,solid

Sugar confectionery and other sugar

Cigarettes

Natural rubber latex; nat.rubber &

Plants,seeds,fruit used in perfumer

Cotton seed oil

Fixed vegetable oils,n.e.s

Sheep and lamb skin leather

Manufactures of wood for domestic/d

Sacks and bags,of textile materials

Household appliances,decorative art

Other musical instruments; not 898.

Soap;organic surface-active product


Burkina Faso Product SpaceEmerging Champions

Cotton (other than linters),not carFruit,fresh or dried, n.e.s.

Sesame (sesamum)seeds

Oil seeds and oleaginous fruit. n.e

Leather of other hides or skins

Other fresh or chilled vegetables

Maize (corn),unmilled

Buckwheat,millet,canary seed,grain

Vegetable products,roots & tubers,

Sugars,beet and cane,raw,solid

Sugar confectionery and other sugar

Cigarettes

Natural rubber latex; nat.rubber &

Plants,seeds,fruit used in perfumer

Cotton seed oil

Fixed vegetable oils,n.e.s

Sheep and lamb skin leather

Manufactures of wood for domestic/d

Sacks and bags,of textile materials

Household appliances,decorative art

Other musical instruments; not 898.

Soap;organic surface-active product


Burkina Faso Product SpaceClassics & Emerging Champions


Oil-cake & other residues (except d

Bovine & equine hides (other than c

Goat & kid skins,raw (fresh,salted,

Sheep & lamb skins with wool on,raw Sheep & lamb

skins without the wool

Basketwork,wickerwork etc. of plait

Gold,non-monetary

Burkina Faso Product SpaceDisappearances


Animals of the bovine species,incl.

Sheep and goats, live

Poultry,dead & edible offals ex.liv

Other fresh,chilled,frozen meat or

Milk & cream,fresh,not concentrated

Milk & cream,preserved,concentrated

Other wheat (including spelt) and m

Rice in the husk or husked,but not

Rice semi-milled or wholly milled,

Beans,peas,lentils & other legumino

Spices (except pepper and pimento)

Bran,sharps & other residues deriveTobacco,not

stripped

Tobacco,wholly or partly stripped

Calf skins,raw (fresh,salted,dried,

Groundnuts (peanuts),green,whether Cotton

seeds

Cotton waste (including pulled or g

Sheep's or lambs'wool,degreased,in

Building and monumental stone not f

Gypsum,plasters,limestone flux & ca

Other materials of animal origin,

Seeds,fruit & spores,nes,of a kind

Shellac,seed lac,stick lac,resins,gAnim./veget.oils &

fats,wholly/part

Cotton yarn

Works of art,collectors pieces & an

Burkina Faso Product SpaceMarginals

KOREA: Developed strong capabilities (density) to grow richer1980-84 – Korea had weak capabilities in high-Prody emerging

champions.By 2000-04, Korea’s strongest capabilities were in high-Prody

emerging champions

67

89

10

Pro

dy

(in

logs)

-2 -1.8 -1.6 -1.4 -1.2 -1 -.8 -.6Density (in logs)

Emerging champions Marginals Classics Dissaperance

KOREA: Product Space, 1980-84

67

89

10

Pro

dy

(in

logs)

-2 -1.8 -1.6 -1.4 -1.2 -1 -.8 -.6Density (in logs)


KOREA: Product Space, 2000-04

Computers

Ships

iPods

Fabrics

Goal Goal

67

89

10

Pro

dy

(in

logs)

-3.5 -3 -2.5 -2 -1.5 -1Density (in logs)


MALAYSIA: Product Space, 2000-04

67

89

10

Pro

dy

(in

logs)

-3.5 -3 -2.5 -2 -1.5 -1Density (in logs)


MALAYSIA: Product Space, 1980-84

Palm nuts

iPods

Computer

Natural rubber

Palm oil

GoalGoal

MALAYSIA: Developed strong capabilities (density) to grow richer 1980-84 – Malaysia had weak capabilities in high-Prody emerging champions.By 2000-04, Malaysia’s strongest capabilities were in high-Prody

electronics

67

89

10

Pro

dy

(in

logs)

-6 -5 -4 -3 -2Density (in logs)


UGANDA: Product Space, 2000-04

67

89

10

Pro

dy

(in

logs)

-6 -5 -4 -3 -2Density (in logs)


UGANDA: Product Space, 1980-84Frozen Fish fillet

Cotton seeds

Sheets of Iron

Coffee

Making progress but still along way to go………..In 1980-84 – Uganda’s capabilities (density) supported low-Prody classics & emerging championsBy 2000-04 – Uganda’s had stronger capabilities but they still supported mostly low-Prody products; a few fishery products were the exception

GOAL GOAL

Fish,fresh(live/dead)or chilled,exc

Fish,frozen (excluding fillets)

Fish fillets,fresh or chilled

Fish fillets,frozenFish,dried,salted or in brine ; smo

Potatoes,fresh or chilled,excl.sweeVegetables,frozen or in temporary p

Vegetable products,roots & tubers,fVegetables,dried,dehydrated or evap

Coffee,whether or not roasted or frTeaCotton (other than linters),not car

Bulbs,tubers & rhizomes of flowerin

Cut flowers and foliageAnimals,live,n.e.s.,incl. zoo-anima

67

89

10

Pro

dy(in logs

)

-4 -3 -2 -1Density (in logs)

Emerging champions Marginals Classics DissaperanceSTRATEX

UGANDA: Product Space, 2000-04

Government of Uganda’s vision: industrial policy (STRATEX)

some concepts for understanding

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