U

GANDA: An export sophistication strategy for structural transformation

J. Boccardo and V. Chandra Poverty Reduction, Economic Policy and Debt Department January 18, 2008

Outline

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Growth in per capita income – some stylized facts Why does Uganda need to diversify its exports?

Why we need a link between exports and income PRODY and EXPY Towards an export diversification strategy - The Product Space What is good for export diversification, what is bad?

Short and longer term strategic options for Uganda Implications of STRATEX for Uganda 4/28/2020 2

Background – from low to middle income

 1980s – 2004: GDP per capita increased in all regions of the world but the gains were hugely uneven.

 Winners: First and Second East Asia.  Per capital incomes grew rapidly      China (425 %), Korea (225%), Thailand (150 %), Malaysia (100 %), India (100 %); Uganda only (40%).

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Catching-up: from low to middle-income status: how long will it take?

14000 12000 10000 8000 6000 4000 2000 0

Kenya Uganda Tanzania SSAnoZAF LAC GDP 90_95 Colombia Chile GDP 96_00 Vietnam Malaysia Korea, GDP 01_04 Rep.

 1980s – 2004: GDP per capita increased in all regions of the world but the gains were hugely uneven.   Winners: First and Second East Asia. Per capital incomes grew rapidly  China (425 %),  Korea (225%),  Thailand (150 %), Malaysia (100 %), 4/28/2020 India (100 %);  Uganda only (40%).

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2 Questions

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If comparative advantage determines what a country exports, 1.

Can Uganda become a middle income country by exporting more of its traditional exports - coffee, tea, cotton…..?

2.

Why did some developing countries such as Malaysia, Korea, China and Chile become richer and others not?

They developed the capability to export products with a high income potential (Prody).

The fostered a comparative advantage in products that transformed the structure of their exports and their economies

4/28/2020 5

SSA*

Trends in GDP and EXPY – Uganda and some comparators

LAC Tanzania South Africa 1975 1985 Year EXPY *no South Africa & no small states 1995 2004 GDP per capita Second EA 1975 1985 Year EXPY 1995 2004 GDP per capita Second EA 1975 1985 Year 1995 EXPY 2004 GDP per capita Kenya 1975 1985 Year 1995 EXPY 2004 GDP per capita Uganda 1975 1985 Year 1995 EXPY 4/28/2020 2004 GDP per capita 1970 1980 1990 Year EXPY 2000 2010 GDP per capita 1975 1985 Year 1995 EXPY 2004 GDP per capita 1975 1985 Year 1995 EXPY 6 2004 GDP per capita

Some hypotheses: the export mix and the growth path

• • • •

Technology classification (Lall, 2005)

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Links a product to its technology content.

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Example: Cereals and fish are primary (PP), minerals are resource-based (RB) and manufactured products are low, medium or hi tech (LT, MT,HT). Natural resources are a curse

. Prebisch and Singer Warner ’90s. Lederman and Maloney Sub-Saharan Africa is special. in 50s and 60s and Sachs and (2006) – Natural resoruces are

Neither curse nor destiny.

Collier (1998, 1999), Mayer and Woods (2001), Eifert, Gelb and Ramachandran (2005) and Habiyaremya and Ziesemer (2006) among others.

Conclusions:

1. For low income countries, manufactured exports are the Uganda’s landlockeness underscores the disadvantages of relying on exports that rely on imported inputs - may not be competitive.

only

route to growth. 2. Can it turn its natural resources into a blessing? 3. High value manufactured exports may happen in the longer term BUT not automatically. What does Uganda need to produce such products competitvely? 4. What about the short term? 4/28/2020 7

40% 30% 20% 10% 0% 100% 90% 80% 70% 60% 50% 4/28/2020 85-89

Uganda: Technological content of Exports

90-95 96-00 2001 pp hv rb lt mt ht 2004 8

Transformation of export mix

- link to income?

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Why do we need a new analytical framework?

There is no clear relationship in the literature between the structure of exports and per capita income.

• For low income Uganda, if exports are the only path to growth, what can it export?

• Middle income Malaysia still exports palm oil • Brazil’s leading export is soy beans • Chile’s leading export is salmon •

Lall (2005), Rodrik, Hwang, Hausmann (2005) – a new concept that links a product to its potential income – PRODY (what you export matters).

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PRODY & EXPY – the income potential of exports

• PRODY measures the income potential of a product. High is good.

• Different from a value chain methodology • The core idea is that

(Ceteris Paribus

) “An economy is better off producing goods that rich countries export,” (Hausmann, Hwang and Rodrik (2005)).

• PRODY reflects the per capita GDP of each country that exports the product weighted by the exporter’s revealed comparative advantage in that product. • EXPY measures the income potential of a country’s total exports. It is the sum of the export shares of each product weighted by each product’s PRODY.

• “Countries that export goods associated with higher productivity levels (EXPY) grow more rapidly.” 4/28/2020 10

PRODY of selected products

20000 18000 16000 14000 12000 10000 8000 6000 4000 2000 0 Primary products Resource-based Low-tech High and Medium tech 4/28/2020 11

Why is the Prody of fish so high and of coffee so low?

Product Frozen Fish GDP per capita Main exporters

36450 United States 39352 Norway 15838 Taiwan, China 5436 Chile 15355 Spain

Share in World's exports

15.0% 9.4%

Share in country's export baskets Prody

0.23% 1.50% 8.1% 6.2% 5.1% 0.40% 2.40% 0.35%

5931 Product Coffee Frozen Fish STRATEX: Coffee GDP per capita Main exporters

3563 Brazil 501 Vietnam 2099 Colombia Germany 1721 Guatemala

Uganda

262 Uganda 262 Uganda

Share in World's exports

16.0%

World's shares

1.80%

Prody

10.0% 8.9% 6.5% 5.0% 3.16% 6.20% 0.08% 9.70%

637

0.006000% 2.5% 1.00% 33.00% • • Prody of Coffee is LOW because its main exporters of Coffee have: Low GDP per capita and a high share of coffee in total exports.

If they have a high GDP per capita, the share of coffee in their total exports is very low. • Prody of Frozen Fish is HIGH because its main exporters have: High GDP per capita and Frozen Fish represents a low share of Less Developed countries’ exports.

12 5931 637

EXPY is a good indicator of per capita GDP (2000-04 ) - to grow faster, Uganda needs a larger EXPY

GDP per capita and EXPy TMP IND SLE AGO LBR NPL ZAR NER GHA TCD TZA ZMB UGA MNG LSO PNG CIV RW A BEN CMR NIC IDN COG PHL CHN THA MYS MEX SER COL ZAF BRA CRI PAN VEN CHL URY ECU BOL SLV GTM PRY JAM ARG 100 200 4/28/2020 300 400 500 600 700 800 900 1000 2000 3000 GDP per capita 4000 5000 6000 7000 8000 TW N SGP SVN CYP ISR HKG BHR ARE KW T 28000 13

Towards a, Export diversification Path: Product Space

• R. Hausmann and Klinger (2007): – “Product space is a term used to describe the network of relatedness between products.” – Relatedness is based on the observed similarity in inputs required to produce products, and includes capabilities etc..

everything

from natural factors, skills, institutional and infrastructural requirements, to technological – Technically, 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. – Like a forest of all products (800) where each product is a tree; some are fruitier than others (higher PRODY). A country/firm that exports it is like a monkey on that tree. Monkeys want to jump from one “fruity tree” to another. Some of which are close, others are far away; and from trees with low to trees with high PRODY fruits.

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The Product Space Can Be Understood as a Forest or Network of Products

 In the product space, diversification is easier if exports are closer to the core than the periphery. Few cotton exporters export textiles or garments (distance is long). But many textiles exporters also export garments (distance is short).

Coffee Fish Tea & /tobacco Oil seeds Fruits Petroleum cluster Core of the forest - goal Garments

4/28/2020 Source: Hidalgo, Klinger, Bar ábasi, Hausmann (2007)

Textiles Cotton

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Distances

between products reflect the similarity in inputs of production –

shorter is better

Textiles Flowers Vegetables Fish fillet Tea Frozen fish Tubes and Pipes Auto parts

 Shorter distances make it easier for a country to diversify into neighboring products.

 Eg. inputs used to produce flowers in Uganda are more similar to those for fruits and vegetables than textiles.

 Inputs used to produce machinery are closer to those for tubes and pipes than auto parts.

 4/28/2020 16

PRODUCT PATHS: Possibilities for Diversification- Longer is better Firm/countries need to move to : Higher Trees; Fruiter Trees ( with higher Prodys reflected in size of tree branches)

Paper Furniture

Oven- ready Fish

Pulp Plywood Venee r logs

Special ty coffee Coffee

4/28/2020

Froze n Fish

Fresh Fish

Fish Fillet

Sawlo gs Wood 17

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

Density implies skills, technology, infrastructure – all that makes a sector competitive – public goods?

Chile’s Density in Frozen Fish Fillet = 0.23

Uganda’s Density in Frozen Fish Fillet = 0.12

Worked Copper : distance= 0.13

Cotton: distance: 0.15

Fresh fish: distance= 0.4

Coffee: distance: 0.26

Tobacco

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How can we use the Product Space concepts to inform Uganda’s export diversification strategy ?

– Goal: jump from present location in the forest to fruitier trees: • Higher PRODY • Longer PATHS • Higher densities – How far it can jump depends on its current location – I it is at the periphery in most products whose inputs are not easily usable in other products – long distances – Capabilities are not easily transferable – densities are low – Policy challenge - Trade-offs 4/28/2020 19

……..Continued

• One strategic option

: use non-traditional products in which it has a RCA and are high PRODY to gradually move towards goal. If scare resources, support products with longer paths.

• Short term

– pick high PRODY products with a critical mass in which you have a high density – low hanging fruits with visible growth impact!!

• Longer term

– pick high PRODY, long paths in which you currently have a low density but develop the capabilities to diversify into them.

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Findings - The proposed strategy has two

stages

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Short to medium term

– horticultural; – fishery and : quick wins imply scaling up fresh or processed products that are a part of the – floricultural sectors which engage small producers who have the basic skills but need other complementary inputs such as public goods to attract investors. High PRODY, high Density.

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Longer term goal

• Animal products - oils • Wood products • Metals – scale up • Chemicals-based sectors. • High PRODY and long PATH. Need to develop density.

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How much can STRATEX contrbute to export diversification in Uganda?

• The STRATEX identified 17 products • The Classics – cotton, coffee, tea and animals • Marginals – horticultural products. Only 0.02 percent of Uganda’s total exports in 2003-05; total value is only $168,000. The value of potatoes was only $1000 in 2003-05. Marginal contribution negligible. • Emerging champions – fishery and floriculture -potential of broadening and deepening Uganda’s export platform the most. The choice of 5 fishery products and 2 flower-related products is desirable as it can help to scale up high value non-traditional exports in the medium term • in the short to medium term, careful support for public goods in the horticultural, floricultural, and fishery export sectors can have significant results 4/28/2020 22

A application of the Product Space methodology to Ugandan exports

CLASSICS

– prodcuts in which Uganda’s RCA in the earlier period was high and in recent period continues to remain high. Implication – its strength, maintain them

1980-84: RCA = 1 2000-04: RCA = 1 DISAPPEARANCES

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

1980-84: RCA = 1 2000-04: RCA = 0

1 2 SITC Name Density PRODY Path $ ‘80-84 $ ‘’00-04

MARGINALS

– prodcuts in which Uganda did not and does not have a RCA Implication – let them grow

1980-84: RCA = 0 2000-04: RCA = 0

SITC Name Density PRODY Path $ ‘80-84 $ ‘’00-04 1 2 4/28/2020 1 SITC Name Density PRODY Path $ ‘80-84 $ ‘’00-04 2

EMERGING CHAMPIONS

– products in which Uganda’s RCA was low in the earlier period but high in recent period. Implication – build on this new strengths

1980-84: RCA = 0 2000-04: RCA = 1

1 SITC Name Density PRODY Path $ ‘80-84 $ ‘’00-04 2 23

Short Term strategy: High density and high Prody – low hanging fruit

-5000

Uganda: STRATEX products_emerging champions and others (Size: growth from 1980-2004)

0.250

STRATEX

0.200

0.150

0.100

0.050

0.000

0

Emerging Champions

15000 20000 Fish,dried,salted or in brine Cut flowers and foliage 5000 10000

Prody

Fish,fresh(live/dead)or chilled Coffee,whether or not roasted Cotton (other than linters) Fish,frozen (excluding fillets) Animals,live,n.e.s

Bulbs,tubers & rhizomes 25000

Long Term strategy: high Prody and long paths

A High Path shows the products that are in the dense part of the forest (dominated by manufactured products), and a Low Path, those which are on the Periphery (i.e. un-processed agricultural goods) 200 180 160 140 120 100 80 60 40 20 0 4/28/2020 0

Emerging Champions with higher Path (size of bubble: growth 80_04) Maize (corn),unmilled Portland cement

5000 10000

Prody

15000 20000

Margarine Meal and flour of wheat and flour Other sheets and plates,of iron Chemicals (Soap) Paper products Anim./veget.oils & fats Plywood

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Conclusions

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Sector-Specificity

marginals

– implies rewarding some sectors more than others

– Scale up the Emerging Champions as opposed to discovering new products/ – Combine them with high PRODY Classics to identify high PRODY long term

sectors

– Nurture high PRODY sectors with long paths (tradeoff between path and densities) – Use product density to identify low hanging fruit in the short term and richer fruits in the 4/28/2020 26

Policy Implications – country-specific

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Competitive advantage can be acquired with appropriate policy interventions (it is not natural!!)

– The diversity of leap-froggers indicates that there is more than one way to do it. The East Asian way is not the only way. – Notion of distances suggests that technological capabilities are necessary for scaling up Emerging Champions – need new technologies, capability to use them and other factors to export (marketing, logisitics, phyto-sanitry standards, infrastructure) – Empirical evidence – a country can import new technology but not the skills needed to use them – technological learning has to be fostered domestically – FDI does not flow easily to countries with weak technological capabilities but incentives to attract FDI can trigger technological learning initiallyI 4/28/2020 27

How smart export diversification strategies altered the structure of exports and supported rapid growth in per capita incomes in Korea, Malaysia

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What does a country’s export product space look like before and after diversification Korea’s export product space in 1980-84 vs 2000-04. Malaysia’s export product space in 1980-84 vs 2000-04 Uganda’s export product space in 1980-84 vs 2000-04 How STRATEX products are likely to alter Uganda’s product space Uganda’s technological capabilities – education Uganda’s technological capabilities – innovation International comparisons 4/28/2020 28

KOREA: Developed strong capabilities (density) to grow richer 1980-84 – Korea had weak capabilities in high-Prody emerging champions.

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

KOREA: Product Space, 1980-84

Goal

KOREA: Product Space, 2000-04

Goal Computers Ships

iPods

Fabrics

-2 4/28/2020 -1.8

-1.6

-1.4

-1.2

Density (in logs) Emerging champions Classics -1 Marginals Dissaperance -.8

-.6

-2 -1.8

-1.6

-1.4

-1.2

Density (in logs) Emerging champions Classics -1 -.8

Marginals Dissaperance 29 -.6

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 Computer Goal

MALAYSIA: Product Space, 1980-84

Goal

MALAYSIA: Product Space, 2000-04

iPods Palm oil

-3.5

4/28/2020 -3 -2.5

-2 Density (in logs) Emerging champions Classics -1.5

Marginals Dissaperance -1 -3.5

Palm nuts Natural rubber

-3 -2.5

-2 Density (in logs) Emerging champions Classics -1.5

Marginals Dissaperance 30 -1

Making progress but still along way to go………..

In 1980-84 – Uganda’s capabilities (density) supported low-Prody classics & emerging champions By 2000-04 – Uganda’s had stronger capabilities but they still supported mostly low-Prody products; a few fishery products were the exception

UGANDA: Product Space, 1980-84

GOAL

UGANDA: Product Space, 2000-04

GOAL Frozen Fish fillet Sheets of Iron

-6 4/28/2020 -5 -4 Density (in logs) Emerging champions Classics -3 Marginals Dissaperance -2 -6

Cotton seeds Coffee

-5 -4 Density (in logs) Emerging champions Classics -3 Marginals Dissaperance 31 -2

GoU’s export strategy: many STRATEX Products are low-Prody Uganda’s capabilities in most STRATEX products are weak

UGANDA: Product Space, 2000-04 4/28/2020 -4 Fish,dried,salted or in brine ; smo Fish fillets,frozen Bulbs,tubers & rhizomes of flowerin Fish fillets,fresh or chilled Fish,fresh(live/dead)or chilled,exc Animals,live,n.e.s.,incl. zoo-anima Tea Coffee,whether or not roasted or fr Cotton (other than linters),not car -3 -2 Emerging champions Classics STRATEX Density (in logs) Marginals Dissaperance -1 32

References for product space diagram • Hidalgo, C.A., Klinger, B., Barábasi A.L., Hausmann, R., The Product Space Conditions the Development of Nations. Supporting Online Materials, Science 317, 482 (2007), http://www.sciencemag.org/cgi/data/317/5837/482/DC1/ 1 • Hausmann, Klinger (2007) • Rodrik (2005), What you Export Matters • Lall (2003) • Lall (2005) 4/28/2020 33