The Macro-Management of Commodity Booms:Africa and Latin America’s responses to Asian Demand (OECD)

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The Macro-Management of Commodity Booms:

Africa and Latin America’s responses to Asian Demand

Rolando Avendaño, Helmut Reisen* and Javier Santiso

OECD Development Centre

Abstract

Strong growth in the Asian Drivers’ has benefited the terms of trade of raw-material exporting countries

and attracted complementary finance. However, the long-term challenge for countries with fragile

institutions is to avoid the resource curse. The Asian drivers are also contributing to heightened volatility

of both commodity prices and proceeds, thus raising a particular challenge to macro management. The

paper aims at informing policy choices in both Africa and Latin America. First, it highlights global

macroeconomic links. Second, it provides brief literature summaries on the optimal policy response from a

macroeconomic and development perspective. Third, empirical evidence is presented as for broad

macroeconomic and fiscal policy responses to Dutch disease and specialization effects caused by Asian

Drivers’ demand. Fourth, benefits and challenges due to the rise of the Asian Drivers are summarized from

a macro perspective.

JEL Classification: F00; O11; 057; E62.

Keywords: commodity booms; Asian Drivers; developing countries, Dutch disease.

* Corresponding author: [email protected]

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The Macro-Management of Commodity Booms:

Africa and Latin America’s responses to Asian Demand

1. Introduction

China and India are rapidly integrating their huge labour forces into the world economy and are growing

swiftly. Each year since 2001, their combined contribution to global output growth has been more than a

third. Moreover, this contribution has helped to hold world growth above the 4 per cent threshold which is

critical for improving the terms of trade for primary commodity producers. By investing huge foreign

exchange reserves in US securities, Asian investors have also contributed both to low US interest rates and

to higher raw material prices. This in turn helped to push down the spreads of most developing countries

contributing to improve their access to private capital and lower the cost of capital for their firms.

All in all, commodity producers benefited from a higher global demand for their exports and from

improved terms of trade. The Asian drivers’ desire for secure and ample access to natural resources

necessary for their continued growth has attracted complementary finance, both from the Asian Drivers

directly (e.g. infrastructure loans) and from global investors. All these factors have fuelled growth

performances in Africa and Latin America. In parallel, China’s and India’s growing demand for

commodities contributes to diversify export client portfolio, away from OECD countries. In a sense,

therefore, African and Latin American commodity exporters have been enjoying an important windfall

profit as a result of the Asian Driver related commodity booms.

Windfall profits imply challenges, not least for macroeconomic policy. By diverting resources from non-

resource sectors and contributing to real exchange appreciation (the so-called Dutch Disease), the boom

will tend to lock developing-country commodity exporters into the raw material corner, with little scope

for industrial learning by doing and limited absorption of low-skilled labour. In order to avoid the Dutch

Disease, resource-rich Africa and Latin America need to find ways to capitalize on windfall gains arising

from resource extraction and promote job-rich sectors. Managed currency floats, lowering vulnerability

through reduced short-term debt or higher foreign-exchange reserves and, above all, a countercyclical

fiscal stance are generally held to constitute the basic tenets of an appropriate development-friendly

macroeconomic response to raw material booms.

This papers aims at informing macroeconomic policy how to deal appropriately with Asian Driver (AD)

related commodity induced booms by tracing the macro responses of most AD affected countries in Africa

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and Latin America against a control group. The indicators observed are consumer price inflation indexes,

real effective exchange rates, official reserves and short-term debt, fiscal response functions, and Dutch

disease indicators.

2. The macroeconomic links

The sheer size of the Asian Drivers, their phenomenal rates of growth, their demand for natural resources,

and their growing economic and political power re-shape the world economy. They provide both

competition and opportunities across the board to major trading partners in OECD countries, to developing

countries and to other emerging economies (see for Africa Goldstein et al., 2006, and for Latin America

Santiso, ed., 2007 ). This section identifies the important conduits through which the rise of the Asian

Drivers impacts on the macroeconomies of commodity-oriented countries in Africa and Latin America.

These conduits are quite different from those that affect economies with important manufacturing sectors

that are subject to increased competition from the East. The integration of the Asian giants into the world

economy has dramatically changed the nature of global macroeconomic and financial interdependence

(Reisen et al. 2004) which in turn, shapes primary commodity markets:

• Global output growth is a major determinant for primary commodity prices. A recent estimate finds that

world commodity prices move pro-cyclically with the growth rate of world industrial production. This is

recorded around 1.5 per cent for every one per cent increase in world industrial output, with a one-quarter

lag at the most (Bloch et al. 2004).

• If world industrial growth exceeds 4 per cent, the barter terms of trade of primary commodity to finished

goods rise (Bloch et al. 2004). High global growth has recently halted and reversed the secular decline of

raw commodity prices since World War II. At the same time, Kaplinsky (2006) shows that the greater

China’s participation in global product markets, the more likely prices will fall.

• Lower US interest rates (which closely govern variations in global key interest rates) have a generally

positive impact, as higher output prospects and lower storage costs lead to higher raw material prices.

• Likewise, a weakening of the US dollar will raise raw material prices, partly for the same reasons which

were evoked for US interest rates, partly as a result of the fact that most commodity markets are dollar

denominated.

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Table 1: The Asian Drivers’ Contribution to Global Growth, 2000-2007

2000 2001 2002 2003 2004 2005 2006 2007

Global growth, % y/y 7.0 5.0 4.8 6.1 8.0 7.1 6.7 6.7

China 18.1 27.2 30.0 27.8 23.8 27.2 28.1 27.9

India 5.9 7.0 7.5 8.9 7.3 8.2 7.7 7.9 Source: Own calculation based on the IMF World Economic Outlook Database.

Note: The contribution to world growth is calculated as

w

rr

w

cc

w

cc

YY

YY

YY

×+×

×

γγ

γ, where cγ is the growth rate of the country (China,

India), wγ the growth rate of world output, and cYand wY are the country and the world output, respectively.

i.e. China’s (India’s) growth rate times China’s (India’s) percentage share in world output divided by the sum of China’s growth

rate plus the growth rate of the rest of the world, each weighted by their respective share in world output. Calculations are done on

a PPP basis.

What impact do the Asian Drivers have on these macroeconomic determinants of the price of raw

materials? China’s and India’s contribution to global output growth is substantial. Since 2001, their

combined part to global output growth has been around 35 per cent. This helped maintain global output

growth far above the 4 per cent threshold which is necessary for improving the terms of trade for primary

commodity producers (Goldstein et al. 2006).

The accumulation of foreign exchange reserves by the Asian Drivers and their investment in US Treasuries

have contributed to lower US rates (the Asian bid). By end 2005, China and Hong Kong had accumulated

more than one trillion dollars in foreign exchange reserves, of which 30 per cent were invested in US

Treasury Bills. This in turn constituted more than an eighth of all outstanding US Treasury Bills. Since

2006, China has started to lower the share of reserves invested in US treasuries. India’s foreign exchange

reserves were relatively lower at the end of 2005 and were more widely invested.

Closely related to the Asian Driver induced commodity boom is the recycling of Petrodollars, estimated in

early 2007 to exceed 1 trillion US dollars. Oil exporters became also net exporters of capital, contributing

to lowering the cost of capital for developing countries. Investors looking to recycle their petrodollars or

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commodity related dollars have also been engaged over the past years in the purchase of developing

countries assets (see Lubin, 2007).

Africa – still connected to the world economy chiefly through raw material exports – and Latin America

are benefiting from the China-driven ‘super cycle’ – a significant rise in real commodity prices,driven by

the urbanization and industrialization of a major country- reinforced by India’s emergence. That said,

commodity prices passed historical lows by the beginning of the decade to unusual figures in 2007. Figure

1 documents the price development for oil, industrial and precious metals as well as for soft commodities

since 2001. These are the commodities that weigh most importantly in African and Latin American export

baskets and impact positively on their overall growth performance. As estimated by Collier (2007), in both

2005 and 2006, the boom added nearly 2.5 percentage points to the growth of the typical African economy.

As for the long-run growth effects of raw materials and the fiscal decision rules in the case of price booms,

Collier and Goderis (2007) show the importance of distinguishing between non-agricultural (depletable,

location bound) and agricultural (replenishable) resources.

Figure 1: Price index for selected commodities, January 2001 = 100

Source: OECD Development Centre and African Development Bank (2007), African Economic Outlook 2007, Paris, OECD

The benefits of China’s and India’s rising global demand (net imports) for commodities relevant to Africa

and most of the Latin American countries may be attenuated by the volatility of demand on the part of the

Asian giants. This is caused partly due to cyclical variations and to arbitrage between domestic production

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and imports. Moreover, as a large share of manufacturing exports from China are produced by

multinational corporations, high demand for raw materials partially reflects relocation of raw material

demand from production sites elsewhere. Such adjustments do not occur without friction, which in turn

could have fuelled demand volatility.

Goldstein et al. (2006) compare the volatility (measured as standard deviation around the trend) in

commodities relevant to Africa for two time periods. Volatility rose for oil, cotton and industrial minerals

except copper. Although it is difficult to separate the relative contribution of different factors, increased

volatility between 2000 and 2004 may have been partly due to the fact that China and India are swing

producers – exporting when prices are high and stockpiling when (be it for cyclical or exceptional reasons)

they are not as attractive. Given their large economies, any behavioural change is likely to translate into

volatility in world prices.

Another source of volatile foreign exchange inflows that macro management has to handle are the

commodity-related capital inflows. FDI, portfolio equity flows and project loans have been on the rise for

developing countries in recent years. Since the early 2000s, that is since the global re-emergence of China,

foreign direct investments in Africa, in particular, have been on the rise, multiplied by three over the

period. According to the African Economic Outlook 2007, the inward flows of FDI in Africa jumped from

less than 10 billion of dollars in 2000 to more than 30 billion in 2005 (the total cumulated inflows over the

period pass the threshold of 100 billion of dollars for all the continent). The annual flow of FDI going

from China to Africa has tripled since the beginning of the 2000s (Mühlberger, 2007). The Asian Drivers

have been new actors, entering with capitals into African markets. Not only China increased its foreign

direct investments in Africa but it also multiplied loans and trade credit lines all around the continent

(Goldstein et al., 2006). These are particularly pronounced for countries for which oil and gas reserves

provide an important share of export proceeds. Natural resources, in particular oil, and the required

network infrastructure, are the destinations for Chinese project lending. Annual statistics published by

China’s Ministry of Commerce indicate that new contractual commitments to Sub-Saharan Africa tripled

from just under US$2 billion to just over US$6 billion in 2005. In November 2006, during the first Sino-

African Summit, China strengthened its cooperation framework with the continent. The event came one

year after China announced 10 billion in concessional loans to Africa for the period 2006-2008.

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3. The macroeconomic policy challenge

The macroeconomic policy challenges posed by the Asian drivers relate to monetary policy including the

choice of the currency regime, the counter-cyclical stance of fiscal policy (both overall budget deficits and

government spending) as well as inter-temporal public spending decisions including reserve and asset

management. Since the government is the conduit for the mineral revenues to the rest of the economy,

fiscal policy is the key to managing booms (Gottschalk and Prates, 2007). Informed judgments about the

persistence and shape of the Asian Driver induced commodity boom will be fundamental to

macroeconomic policy formulation. Goldstein et al. (2006) argue that prospective growth patterns of the

Asian Drivers, in particular of China, can be expected to move from industrialization, exports and

urbanization towards domestic consumption, globalise eating habits and services, implying a shift in their

raw commodity demand patterns, away from iron ore, copper and other industrial minerals toward soft

commodities.

Sub-Saharan African countries, given their dependence on commodity exports, account for half the

commodity-currency countries. Moreover, for these 22 countries, over 80 percent of the variation in the

real exchange rate can, on average, be accounted for by movements in real commodity prices alone—a

surprisingly strong result (Cashin et al., 2003). While the variability of the real effective exchange rate is

similar across the various nominal exchange rate regimes, for countries with pegged nominal regimes, a

larger relative share of real exchange rate variability is driven by the variability of relative prices. Theory

tells us that, for economies prone to frequent real external shocks, flexible nominal exchange rates

facilitate the smoothing of real output to such shocks, especially when domestic wages and prices are slow

to change (e.g., Chen and Rogoff, 2003). Following a positive real shock (such as a rise in the world price

of a key export), a nominal appreciation lowers the domestic price of exported goods (to partially offset the

rise in the international price) and reduces real wages in line with reduced labour demand. In contrast, in

countries with inflexible nominal exchange rates experiencing such positive real shocks, prices and wages

need to rise to ensure that employment and output are in equilibrium.

Most low-income countries have preferred managed floats (unsterilized intervention on the foreign

exchange markets to target the real appreciation needed to accommodate the commodity boom) to either a

pure float or nominal exchange-rate pegs, for good reason (Buffie et al., 2006):

• With a commodity boom (just as with a surge in aid), a pure float results in nominal appreciation

and, with sticky prices and wages as well as with complementary capital flows, in exchange-rate

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overshooting up to a point where output contracts in the nontradables sector and where substitution

effects drive the economy in a recession.

• A currency peg allows a short-run spike in inflation; while bond sterilization can dampen the spike,

it does so at the cost of rising real interest rates, inciting further capital inflows. The sterilization

may also require bond sales on a scale that exceed the absorptive capacity of the shallow domestic

financial markets.

With countries’ increasing international financial integration, considerations regarding reserve adequacy

have shifted from an emphasis on trade (traditionally associated with the “three-months-of-imports” rule)

to the financial account and balance sheet fragilities (associated with the “Greenspan-Guidotti” rule,

according to which reserves should cover short-term debt). The rise of international reserves in developing

countries opened a new issue related to the optimal level and management of this commodity related

windfall. Since the classical Baumol-Tobin inventory model with fixed costs of depleting and replenishing

reserves (see Flood and Marion, 2002, for a review), the literature has focused on the optimal level that

developing countries should have (Jeanne and Rancière, 2006). Reserves tend to allow a country to smooth

domestic absorption in response to sudden stops but they also yield a lower return than the interest rate on

the country’s long term debt. The optimal answer is not however evident as there is not only the related

financial costs of holding reserves but also social costs (Rodrik, 2006).

Whatever the exchange-rate regime, the basic requirement for avoiding macroeconomic complications with

free capital flows is fiscal control. Since in general the government is the conduit for the mineral revenues

to the rest of the economy, fiscal policy is the key to managing booms. Unless the government commands

fiscal control for stabilization purposes, it has to violate the Mundell assignment and use monetary policy

for internal balance. According to Mundell (1962), however, once the capital account is open, even

imperfectly, monetary policy acquires a comparative advantage in dealing with external imbalances, while

fiscal policy is assigned to maintaining internal balance.

Households where goverments are fiscally weak, and in view of a commodity boom, force an unstable

assignment upon the authorities. If fiscal policy does not tighten sufficiently to cope with the boom,

monetary policy is left to hold down aggregate demand. This in turn would widen the interest differential

and thus reinforce the balance of payments surplus. Confronted with a commodity boom, fiscal policy

should be used to reduce demand for non-tradables, hence limiting unwarranted exchange-rate

appreciation. The aim is to eliminate instability in aggregate demand, and consequently the real exchange

rate, by smoothing expenditure over time, which implies self-insuring against revenue downfalls. Next to

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expenditure restraint, revenue management is important, consisting of self-insurance and asset

diversification. The ability to maintain expenditure during the bust depends on having been prudent during

the boom.

Table 2: Managing Public Sector Commodity Booms

Decision Rule

How much to deplete?

Arbitrage: The country should be indifferent

between keeping the natural resource under the

ground in which case the return is the capital gain

on the reserves compared to selling it and getting

a market rate of return on it.

1. Hotelling/Solow Rule. This requires that the

price of natural resource should grow at the

world rate of interest and that under some

conditions the rate of depletion should equal

the demand elasticity times the world rate of

interest.

2. The steady-state depletion rate is capital

return minus population growth, so that

societies with fast growing populations should

deplete their natural resources less rapidly.

How much to save?

To maximise intergenerational HH utility, which

saving rate sustains a stable consumption per

capita. Consuming rents from exhaustible

resources is literally consuming capital.

The mid-term saving decision is ruled by

stabilisation and diversification concerns. Fiscal

policy is superior to monetary policy to deal with

the first, active diversification involves use of

funds for new activities (see Norway & Chile).

1. Hartwick Rule. If there is no population

growth, to sustain a constant income per capita

all resource rents must be invested in capital,

including education. If consumption per head

were rising (falling) over time, social welfare

could be increased if earlier (later) generations

saved and invested less or consume capital at

the expense of later (earlier) generations.

2. Commodity price smoothing rule. Unlike the

savings generated by the Hartwick rule, these

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savings are intended to finance subsequent

consumption during periods when the oil price

is below its long run path. There is thus a

strong case for holding these assets in liquid

form, which implies the acquisition of

financial assets abroad.

How much to invest at home?

1. Excess return of home investment

2. Construction price smoothing rule

How much to invest abroad vs. retire public

debt?

1. Excess cost of public debt over global return

Source: Based on discussion in van der Ploeg (2006) and Collier (2007).

Economic theory offers useful insights into the optimal management of natural resources. One strand of

literature focuses on the Hotelling rule. The rationale behind this rule is arbitrage. The country should be

indifferent between keeping the natural resource under the ground in which case the return is the capital

gain on the reserves and selling it and getting a market rate of return on it. This requires that the price of

natural resource should grow at the world rate of interest and that under some conditions the rate of

depletion should equal the demand elasticity times the world rate of interest (van der Ploeg, 2006). Another

line of theoretical research investigates the optimality of the Hartwick rule, which demands that the

proceeds of natural resource revenues are reinvested in productive assets. The World Bank has calculated

that many resource abundant economies do not follow the Hartwick rule. In fact, many of these countries

have negative genuine saving rates and become poorer each year (World Bank, 2006).

Asset accumulation should not be confined to the central bank, but should cover the public sector as well.

There are good reasons to save part of the commodity bonanza. How much? In the case of depleteable

resources, the long run saving rule can be applied: the expected rate of increase in the commodity price,

divided by the extraction rate. If, for purposes of illustration, the expected price increase is one percent

annually and the extraction rate is three percent (sufficient reserves for 33 years of extraction at the present

rate), then one third of extraction proceeds can be consumed. However, if the judgment is that the current

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commodity price is way above the long run level, then the above-normal proceeds should be saved

entirely.

There are also good theoretical reasons for investing a substantial part of the windfall initially abroad: the

return to investment would fall below the world interest rate if the windfall were to be used entirely for

domestic investment. Investing abroad offers an escape from diminishing returns: foreign assets can be

repatriated gradually and used for domestic investment. The construction price smoothing rule can be

employed to dampen rising capital cost, such as typically occur in a construction boom, by deferring

domestic investment until the construction boom abates. However, in practice the efficient balance

between domestic and foreign assets is politically difficult to sustain. Domestic debt repayment may solve

this dilemma, and is lucrative as long as domestic debt cost exceeds expected foreign returns. It has the

added advantage of making foreign asset accumulation difficult to reverse by future predator governments.

To be sure, the management of commodity price booms in low-income countries goes beyond the standard

textbook prescription that might hold for OECD minerals-dependent countries such as Australia or Canada.

In all commodity exporters, the short-run growth effect of higher commodity prices is positive. In low-

income countries, the long-run effect of higher non-agricultural commodity prices has been shown to be

negative, while it has been positive for agricultural exporters, in a study covering the global experience of

primary commodity exporting countries over the period 1960-2004 (Collier and Goderis, 2007). This could

suggest a fundamental difference on the macroeconomic policies regarding hard and soft commodity

exporters. Three factors, which should be integrated in any macroeconomic policy prescription, have been

observed to generate the adverse long-run effect:

(a)

Dutch Disease

A surge in resource exports leads to a real appreciation of the county’s exchange rate and this hurts other

exporters and producers in import-competing sectors. This phenomenon is variously known as the “Dutch

disease” (Corden and Neary, 1982), “the Gregory effect” and “de-industrialization”. A resource boom

affects the economy through the resource movement effect and through the spending effect. For Dutch

Disease to arise and become a serious policy issue, there must be other sectors for which the rise in the real

exchange rate would create problems relating to competitiveness. Torvik (2001) has shown that the

conventional Dutch disease effects may be overturned if there are productivity spillovers in both tradable

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and non-tradable sectors. Adam and Bevan (2006) examine the case where public infrastructure investment

generates an inter-temporal productivity spillover for both tradable and non-tradable production, but in a

potentially unbalanced manner. For example public investment in rural roads is likely to impact more on

the production of (non-tradable) food crops than on urban-based (tradable) manufactures and vice versa

for, say, telecommunications infrastructure. Collier and Goderis (2007) find that Dutch disease, although

significant, can only explain a minor part of the long-run negative growth effect of higher non-agricultural

commodity prices on long-run growth.

(b) The Leamer Triangle

The concept of the Leamer Triangle may therefore be more relevant when it comes to studying the impacts

of both the resource boom and commodity price volatility that the Asian Drivers tend to exert on resource-

rich economies. Leamer (1987) has shown using a three-factor multi-good model that resource-rich

countries can take a development path very different from resource-poor countries. The corners of the

Leamer Triangle represent three factors of production: labour, natural resources, and physical as well as

human capital. A natural resource discovery, for instance, swings a country’s endowment point directly

toward the resource corner. This can be used to contrast the development path taken by resource poor

countries with the development path taken by resource rich countries. The Leamer analysis points to four

problems connected to a resource boom in raw-material rich economies (see also Leamer et al.,1999;

Alvarez and Fuentes, 2006): i) The absorption of low-skilled labour that goes along with the development

of manufactured goods is foregone, hence inequality is deepened; ii) Those manufacturing activities that do

emerge are capital intensive and skill intensive; iii) Human capital accumulation may be impeded, as skills

in the resource sector are very specific and spillovers limited; iv) Volatility in the prices of raw

commodities may raise capital risk in resource-dependent, undiversified countries, which might deter

investment and make it more difficult for other tradable activities to emerge.

(c) Volatility

Volatility is an important dimension when explaining growth paths in developing countries. Those where

fundamentals have experienced significant variations (e.g. Brazil or Mexico in the 1990s) have

experienced strong growth fluctuations, and the negative correlation between both variables has been

stressed elsewhere (see Hnatkovska and Loayza 2004). Aghion and Marinescu (2006) emphasise the effect

of fiscal policy, where a counter cyclical budgetary policy fosters innovation and growth by easing the

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impact of a shock on innovating-firms. Consistently, they find that a procyclical public debt growth is

negatively correlated with growth. Therefore, a more countercyclical public debt growth tends to enhance

growth, even more when there is low financial development. In practice, in many developing countries

fiscal policy tends to display the opposite properties: it is procyclical (Hausmann and Gavin, 1996). In

particular, government spending as a share of GDP goes up during booms and down in recessions, while

deficits increase in booms and decrease in recessions. In some commodity-exporting countries, not all, the

government acts as “trustee” of the resources for the country and is an important recipient of the mineral

rents. A political explanation particularly relevant for commodity-dependent countries has been advanced

by Tornell and Lane (1999): when more resources are available (i.e. in booms), the common pool problem

is more severe and the fight over common resources intensifies, leading to budget deficits. Again, this

problem seems less relevant for agriculture-based economies as these do not normally produce rents (the

surplus of export revenue over the cost of production); by contrast, non-agricultural commodities provide

persistent location-specific rents, the bulk of which accrues to the government (Collier, 2007).

3. Some recent policy evidence

This section will focus on the period 2000-2005, where we examine to what extent authorities in Africa

and Latin America followed the policy script outlined in section 3 and how this helped commodity-boom

economies to contain inflationary pressures, escape excessive specialisation effects, avoid being ‘Leamer-

cornered’ and to reduce vulnerabilities to possible future currency attacks.

An approach for assessing the impact of the Asian Drivers on the regions studied consists on decomposing

the demand effect and the price effect on different commodities markets. On this basis, a selection and

control groups are defined in each region, categorizing countries by these two impacts. Regarding the first

effect, we consider for the selection group those countries where the Asian Drivers weigh particularly

strong in terms of both a country’s share in export receipts and Gross Domestic Product (GDP). Those

countries were chosen that displayed above-region median values for both the AD share in exports.

For the second effect, we propose a different technique, regarding at the increase on export commodity

prices on both Latin America and Africa. Our hypothesis is that the rise on the Asian Drivers’ demand for

commodities has boosted prices, creating a heterogeneous effect, depending on both trade structure and

commercial partners for each country. We follow a similar methodology to the one by Kamin et al.

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(2006)1. In this case, we assess the impact of commodity imports into global prices, to estimate the

individual contribution of the AD boom. Data is obtained from the UN/Comtrade database, SITC Revision

3 classification. Initially the estimated equation is as follows:

itcommainntcommaintcommainti ADimportADimportP υααα +++=Δ − _,2_,10_,, _*_*

where commaintP _,Δ represents the percentage change on the price of the main commodity export for country

i to the rest of the world, commaintADimport _,_ is the import share for the commodity by the Asian Drivers

at time t and commainntADimport _,_ − is their initial import share. To determine the price effect, we regard

the magnitude on estimator 1α .2 Results from the sampling are summarized in Table 3.

We run the discussion along the rising degree of endogeneity of macroeconomic variables. This means that

we start out with estimating fiscal response functions for the various country groups, both for government

spending and government deficits. Then we look at the Greenspan-Guidotti indicators as an indicator for

the effective currency regimes employed and lower exposure to short-term debt achieved. This will lead to

the discussion of inflation trends and developments in the real effective exchange rates.

1 See Kamin, S. Marazzi, M. and John W. Schindler. “The impact of Chinese Exports on Global Import Prices”. Review of International Economics, 14(2), 179-201, 2006. 2 The dominant commodities per country in Africa were mainly gold (Burundi, Tanzania), textile fibres (Benin), petroleum (Egypt, Cameroon, Sudan, Senegal), non-ferrous metals (South Africa, Zambia), coffee (Ethiopia), apparel/clothing (Tunisia, Morocco) and tobacco (Zimbawe). For Latin America the predominant commodities were petroleum (Venezuela, Colombia, Ecuador), copper (Chile), gas (Bolivia), metalliferous ores and metal scrap (Peru), and coffee, tea, cocoa and other grains (Honduras, Nicaragua, El Salvador).

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Table 3. Selection and Control Groups (Latin America and Africa)

- each region’s median values in bold -

Country

Exports to Asian

Drivers/Total Exports (Avg.

2003-05)

Memo: Exports to

Asian Drivers/GDP (Avg 2003-

05)

Country

Exports to Asian

Drivers/Total Exports (Avg.

2003-05)

Memo: Exports to

Asian Drivers/GDP (Avg 2003-

05)

Chile 0.115 0.040 Benin 0.382 0.041Peru 0.099 0.021 Gabon 0.150 0.019Argentina 0.097 0.012 Senegal 0.141 0.035Brazil 0.068 0.010 Nigeria 0.105 0.017Uruguay 0.041 0.006 Tanzania 0.098 0.011Paraguay 0.029 0.006 Egypt 0.078 0.003

Selection Costa Rica 0.027 0.009 South Africa 0.045 0.012Groups Panama 0.024 0.002 Mali 0.042 0.009

Morocco 0.042 0.010Zambia 0.039 0.014Cameroon 0.037 0.008Madagascar 0.030 0.002

L. America 0.024 0.002 Africa 0.030 0.007

Colombia 0.009 0.002 Cote d'Ivoire 0.027 0.017Bolivia 0.009 0.002 Mozambique 0.026 0.007Mexico 0.007 0.002 Kenya 0.020 0.002Honduras 0.007 0.002 Ghana 0.016 0.006Venezuela 0.006 0.002 Tunisia 0.010 0.004

Control Guatemala 0.006 0.001 Malawi 0.010 0.003Groups Ecuador 0.005 0.002 Mauritius 0.009 0.003

Nicaragua 0.004 0.001 Uganda 0.008 0.001Algeria 0.007 0.002Niger 0.003 0.000Burkina Faso 0.000 0.000Botswana 0.000 0.000

Latin America Africa

4.1. Government Budget Response Function

Fiscal response functions are estimated for both government spending (as percentage of GDP) and for

government budget deficits or surpluses (as percentage of GDP). We distinguish two different estimation

periods: First, we will assess the degree of procyclicality for a set of Latin American and African countries

during the period 1987-1999. Second, we will focus on the recent upsurge of commodity prices and the

terms of trade for these countries, and assess their impact on public revenue management during 2000 -

2005. The equation is estimated for the whole sample of countries, and for the selection and control

16

groups. The fixed-effects estimation is supported by a Hausman test on each sample. The estimation

procedure follows Alesina and Tabellini (2005) and Jimenez and Tromben (2006).

The first panel regression is defined in the following equation:

itititititit ZTOTFgapoutputF εβββββ +++++=Δ − ***_* 431210

where itF is an indicator of fiscal policy (in this case government expenditure, expressed as a percentage

of GDP). The output gap is a measure of the business cycle, itTOT is are the terms of trade, and itZ is a set

of variable controls. Information on government expenditure and some controls for this period is obtained

on the World Development Indicators (World Bank) and the International Financial Statistics (IMF). The

output gap is calculated as the log deviation of real GDP from its Hodrik-Prescott trend. Identically,

itTOT is a deviation between the terms of trade and its Hodrik-Prescott filtered trend, also obtained from

the World Development Indicators. In this equation, a positive value for the output gap coefficient ( 1β ) is

assumed to denote a procyclical behaviour. The measure compares the actual GDP (output) of an economy

and the potential GDP (efficient output). When the economy is running an output gap, either positive or

negative, it is thought to be running at an inefficient rate as the economy is either overworking or

underworking its resources. Economic theory suggests that positive output gap will lead to inflation as

production and labour costs rise.

For countries with full fiscal control, the null hypothesis is that government spending will neither be

affected by varying output gaps, terms of trade or AD shares in exports; the only objective, to smooth

government spending over different states of nature, is fully respected. Countries without fiscal control and

hence pro-cyclical (due to rent seeking, fragile institutions, etc.), by contrast, should be expected to show

significant positive correlation coefficients for government spending and varying output gaps as well as

terms of trade. It would be unsurprising to find such a positive association as well for government

expenditures and AD export shares as many would argue that the Asian Drivers tend to engage particularly

in countries with weak governance scores.

17

Table 4a. Government Expenditure Response

- All countries -

Regression Government Expenditure All Countries

Latin America Africa OECD Latin America Africa OECDoutput_gap 4.7818e-11* 5.03E-11 2.53E-13 2.53E-12 -5.8470e-10*** -3.02E-12

[1.92] [0.27] [0.17] [0.09] [2.98] [1.46]lag_gov_exp 0.7562*** 0.4753*** 0.7842*** 0.3450* 0.5717*** 0.6558***

[16.73] [9.46] [16.10] [1.93] [6.75] [6.39]terms_trade 8.0764e-13* -2.7668e-12*** 2.48E-13 -1.85E-13 2.05E-13 -4.69E-14

[1.79] [2.70] [1.36] [0.89] [0.32] [0.23]Observations 207 318 195 89 144 72Number of id_gen 16 25 15 16 25 15R-squared 0.6 0.28 0.65 0.07 0.31 0.47Absolute value of t statistics in brackets* significant at 10%; ** significant at 5%; *** significant at 1%

1987-1999 2000-2005

In this estimation a positive coefficient for the output gap denotes procyclicality. The regression shows that

Latin America had a significant procyclical behaviour (at 10% of significance) during the period 1987-

1999, which was not the case during the period 2000 – 2005, indicating increased fiscal control. For the

case of Africa results are not conclusive, but seems to suggest a high degree of volatility in public

spending. In the OECD group, results indicate fiscal control for both sub-periods as the output gap does not

exert a significant impact on government expenditure.

The following regressions takes into account the selection (4b) and control (4c) groups in each region in

order to find further differences. Table 4b confirms the existence of procyclicality for the Latin American

selection group during the period 1987-1999. During the second period the null hypothesis of non-

significance for the output gap cannot be rejected, and therefore it is assumed that no-cyclicality prevailed

in the region in after 2000. While the signs of the output gap turn from positive to negative in the African

selection group (indicating a move toward an anti-cyclical stance), they are not significant in both sub-

periods. By contrast, the African control group displays a surprisingly significant anti-cyclical response of

public spending in both sub-periods and for both explanatory variables, i.e. the output gap and the terms of

trade.

18

Table 4b. Government Expenditure Response

- Selection Group -

Regression Government Expenditure Selection Group

Latin America Africa Latin America Africaoutput_gap 3.8198e-11** 2.05E-10 1.0716E-11 -2.14E-10

[2.25] [1.06] [0.24] [1.29]lag_gov_exp 0.7746*** 0.4904*** 0.6225* 0.2270***

[13.30] [7.33] [1.79] [2.71]terms_trade -4.2171E-13 -2.6502E-12 -1.8463E-13 3.3567E-12

[0.51] [1.02] [0.41] [0.78]Observations 103 151 45 66Number of id_gen 8 12 8 12R-squared 0.68 0.3 0.1 0.14Absolute value of t statistics in brackets* significant at 10%; ** significant at 5%; *** significant at 1%

1987-1999 2000-2005

Table 4c. Government Expenditure Response

- Control Group -

Regression Government Expenditure Control Group

Latin America Africa OECD Latin America Africa OECDoutput_gap 7.2943E-11 -1.1254e-09** 2.53E-13 -1.0326E-11 -1.5932e-09*** -3.02E-12

[1.18] [2.07] [0.17] [0.43] [4.00] [1.46]lag_gov_exp 0.7533*** 0.4353*** 0.7842*** 0.11 1.0084*** 0.6558***

[11.48] [5.76] [16.10] [0.83] [8.04] [6.39]terms_trade 9.5359E-13 -2.9224e-12** 2.48E-13 -2.0351E-13 9E-14 -4.69E-14


2000-20051987-1999

To confirm the robustness of results, a second set of regression was estimated for the different samples,

using the growth rate of government expenditure. As they neither added nor modified the results reported

here, they have not been reproduced here.

Next we took government budget balances as a proxy (dependent variable) for fiscal policy . Data on

government budget balances, expressed as a percentage of GDP, were obtained from The Economist

Intelligence Unit, the OECD African Economic Outlook and Jimenez and Tromben (2006). Results are

reported in the following tables.

19

Table 5a. Government Budget Balance Response

- All Countries -

Regression Budget Balance All Countries

Latin America Africa OECD Latin America Africa OECDoutput_gap 5.45E-11 -3.62E-10 9.14E-13 2.76E-11 1.05e-09*** 1.70e-11**

[1.49] [0.60] [0.22] [1.10] [3.57] [2.33]lag_budg_bal 0.28*** 0.1232 0.85*** 0.45*** 0.08 0.33**

[3.71] [1.31] [16.75] [4.07] [0.97] [2.49]terms_trade 1.00e-12** 4.70e-11*** 8.02E-13 2.84E-13 2.23E-14 1.19E-12


1987-1999 2000-2005

Table 5b. Government Budget Balance Response

- Selection Group -

Regression Budget Balance Selection Group

Latin America Africa Latin America Africaoutput_gap 5.76E-11 -1.16E-09 1.65E-11 1.09e-09***

[1.19] [1.40] [0.60] [3.63]lag_budg_bal 0.24** 0.1 0.42*** 0.11

[2.12] [0.67] [3.06] [1.05]terms_trade 2.08e-12** 4.45e-11** 9.95e-13*** -1.95e-11***

[2.34] [2.48] [2.90] [2.87]Observations 75 58 48 72Number of id_gen 8 12 8 12R-squared 0.15 0.21 0.42 0.27Absolute value of t statistics in brackets* significant at 10%; ** significant at 5%; *** significant at 1%

1987-1999 2000-2005

20

Table 5c. Government Budget Balance Response

- Control Group -

Regression Budget Balance Control Group

Latin America Africa OECD Latin America Africa OECDoutput_gap 5.11E-11 2.2330e-09** 9.14E-13 4.93E-11 1.20e-09* 1.70e-11**

[0.94] [2.28] [0.22] [1.04] [1.79] [2.33]lag_budg_bal 0.29*** 0.08 0.85*** 0.44** 0.15 0.33**

[2.78] [0.73] [16.75] [2.55] [1.16] [2.49]terms_trade 8.51E-13 1.7810e-10*** 8.02E-13 1.53E-14 2.73E-13 1.19E-12


2000-20051987-1999

The null hypothesis as for government budget balances is for countries with fiscal control to find a

significant positive correlation coefficient between government budget balances and varying output gaps as

well as terms of trade. To save for bad days in good times is a precondition for governments to be able to

smooth public spending over different states of natures. Absence of a significant positive correlation would

indicate pro-cyclical fiscal stance and hence more macroeconomic complication as a result of the AD

induced commodity booms, such as higher price levels for non-tradables, thus higher inflation levels, and

higher real currency appreciation than warranted by the fundamental equilibrium exchange rate.

During the period 1987-99, the terms of trade explain significantly in both Africa and Latin America the

government budget balance, which rise when the terms of trade do so. In the second sub-period the terms-

of-trade effect on budget balances (Table 5a) has turned insignificant in both regions, suggesting less direct

dependence of government finance on raw materials. However, in the AD selection group (Table 5b), the

terms-of-trade effect continues to impact significantly on government budget balances during 2000 – 2005.

In both Africa and the OECD sample the output gap starts to significantly explain budget balances since

2000, suggesting an increased anti-cyclical fiscal stance. In Latin America, no statistical significance can

be detected for the output gap variable.

These findings may, perhaps surprisingly, suggest that in the recent years when the AD driven commodity

boom gained full traction, macroeconomic policy challenges have been better coped with and monetary

21

policy better assisted by an anti-cyclical fiscal stance in Africa than this has been the case on average in

Latin America.

4.2. Respecting the Guidotti-Greenspan Rule: Higher Reserves, Lower Debt

A rise in commodity proceeds should neither affect the level of foreign exchange reserves nor the level of

short-term debt if this rise was fully accommodated by a pure float in the exchange rate. Just the nominal

exchange rate would appreciate, immediately on impact. Any other currency regime, from a hard peg to

dirty float, will show up in a rise of the Guidotti-Greenspan indicator, the level of official foreign exchange

reserves as a fraction of the country’s short-term foreign debt. For those countries where this indicator had

been below one, any rise above one can be interpreted as a step toward lowered exposure to a speculative

currency attack by foreign and domestic investors as the assets easily cancelled fall short of the reserves to

defend the exchange rate.

Figure 2, based on data from the World Bank Global Development Finance Database, related official

foreign exchange reserves and short-term external debt. (Ideally, the indicator could be broadened to

include all liquid assets held abroad instead of official reserves only and all liquid liabilities, both external

and domestic; however, data availability precludes to establish time series as presented in Figure 2). The

Guidotti-Greenspan rule indicator improved and now exceeds one in all sample countries. This leads to the

observation that the Asian driver induced commodity boom served to reduce vulnerability to future

speculative attacks. Especially Argentina, Cameroon and Gabon managed to climb out of the danger zone,

from very low levels below one, to close to one or above while the rest of the selection group countries

shows even more comfortable values.

22

Figure 2: Ratio Foreign Exchange Reserves to Short Term Debt – Selection Group

Africa

0.001

0.01

0.1

1

10

100

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

% (

Log

arit

hm

ic S

cale

)

Cameroon

Benin

Mali

Egypt

Madagascar

0.001

0.01

0.1

1

10

100

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

% (

Log

arit

hm

ic S

cale

)

Nigeria

Gabon

South Africa

Tanzania

Zambia

Latin America

Source: OECD Development Centre, computed on the basis of World Bank Global Development Finance Database, 2007.

Changes in debt composition, maturities and structure have importantly contributed to improved

Greenspan-Guidotti Rule indicators. Figure 3 displays some evidence for the reduced percentage share of

0.1

1

10

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

% (

Logar

ithm

ic S

cale

) .

Argentina

Brazil

Chile

Costa Rica

0.1

1

10

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

% (

Logar

ithm

ic S

cale

)

Panama

Peru

Uruguay

Paraguay

23

short-term domestic debt in total domestic debt. The risk debt management to the current commodity

boom, partly driven by increasing Asian demand, has been therefore every different from the previous

commodity shocks, in particular the one of the 1970s that ended in Latin America with the debt crisis of

the 1980s (Blommestein and Santiso, 2007). Since the global re-emergence of China, exchange rate-

indexed debt also has been reduced all around in Latin America, the most impressive case being Brazil

where the share of such indexed debt in total public debt fell from 37 per cent in 2002, the year of the

crisis, to 2.3 per cent at the start of 2006. However, the reallocation towards more local currency debt is

also inducing a change in the risk profile of sovereign issuers. Foreign currency debt is decreasing,

although this meant in some countries that debt maturity became shorter (even if things are changing

quickly as some other emerging bond issuers are starting to be able to issue bonds in local currencies with

maturities now over ten years as for example Mexico).

Figure 3: Short Term Domestic Debt in Emerging Markets

0

10

20

30

40

50

60

70

Brazil Mexico Chile Venezuela India Colombia China Russia

% D

omes

tic D

ebt

.

1996

2004

Source: Blommestein and Santiso, 2007.

At the same time, during the 2000s, current account surpluses in most emerging markets enabled several

countries to reduce their external debt. They have also helped reduce one major source of vulnerability (to

liquidity crisis in particular), the net open forward positions in hard currencies taken by central banks of

some emerging countries which played a key role in the collapse of the Thai baht in 1997 and was regarded

as a major source of vulnerability for South Africa until the trimming down of its forward book in 2003.

24

In some cases external debt levels have been reduced drawing on these foreign reserves. In 2005, Brazil

repaid the IMF, the Paris Club creditor countries and in 2006 it paid off all its remaining Brady bonds

($ 6.6 billion), the securities that kick-started the emerging market bonds boom in the 1990s (albeit partly

funded by new external debt), officially ending the debt restructuring process of the 1980s. Argentina

followed also the Brazilian example, repaying its outstanding debt to the international financial institutions.

In 2006, Nigeria became the first African country to cancel its Paris Club debt (totalling $ 30 billion; one

third being repaid and the remaining being forgiven). These mechanisms of self-insurance through

increased levels of reserves continue to be pursued even after repayments as underlined by the Brazilian

and Argentinean examples.

4.3. Inflation and Real Effective Exchange rates

Figure 4 concentrates for each region – Africa and Latin America – on those selection countries for the

period 2000 - 2006, where the commodity import demand from China is most felt. In general, the picture

that emerges is one of macroeconomic stability, with inflation and real effective appreciation well

contained.

Strong appreciation of the real effective exchange (REER) – exceeding 50 percent during that period - can

be noted for Zambia in particular, partly reflecting not just higher commodity prices but also simultaneous

debt relief and renewed capital inflows. According to Collier (2007), dramatic contrasting examples of the

consequences of different public savings strategies for the real exchange rate are Chile and Zambia during

2005, a period when the world price of their common commodity export, copper, was exceptionally high.

The Government of Chile followed a savings rule such that all the incremental revenue was saved, whereas

the government of Zambia continued to run a fiscal deficit. During 2005, the real exchange rate mildly

depreciated in Chile despite the boom, whereas in Zambia it appreciated by around 80%, causing intense

problems for non-copper exports. Note, however, that the equilibrium exchange rate may have appreciated

more in Zambia than in Chile as the former benefited from important debt relief measures. Therefore, the

fundamental equilibrium exchange rate may have appreciated correspondingly; an appreciation (REER)

should not be confounded with real effective overvaluation.

25

Figure 4: Real Effective Exchange Rates and CPI Inflation

Africa – Selected countries

Benin

707274767880828486

1995

1997

1999

2001

2003

2005

0246810121416

REER Inflation (right axis)

Cameroon

949698

100102104106108110112114

1995

1997

1999

2001

2003

2005

0

2

4

6

8

10


Egypt

0

20

40

60

80

100

120

140

1995

1997

1999

2001

2003

2005

024681012141618


Madagascar

0100020003000400050006000700080009000

10000

1995

1997

1999

2001

2003

2005

-10

010

20

30

4050

60


Mali

0100200300400500600700800

1995

1997

1999

2001

2003

2005

-5

0

5

10

15


Morocco

86889092949698

100102

1995

1997

1999

2001

2003

2005

0123

4567


South Africa

0

20

40

60

80

100

120

140

1995

1997

1999

2001

2003

2005

0

2

4

6

8

10


Nigeria

0

50

100

150

200

250

1995

1997

1999

2001

2003

2005

01020304050607080


Senegal

85

90

95

100

105

110

1995

1997

1999

2001

2003

2005

-10123456789


Tanzania

0

20

40

60

80

100

120

140

1995

1997

1999

2001

2003

2005

0

5

10

15

20

25

30


Zambia

020406080

100120140160

1995

1997

1999

2001

2003

2005

0

10

20

30

40

50


26

Latin America – Selected Countries

Source: Authors, 2007; based on Economist Intelligence Unit and IMF Statistical Yearbook, 2007. Data on inflation for Africa

from World Economic Outlook and Penn World Tables, 2007.

In none of the sample countries has inflation risen during the Asian Driver induced boom period. These

findings suggest some degree of sterilized foreign exchange intervention and the absence of hard nominal

exchange rate pegs, which would have had to accommodate the commodity-induced appreciation pressures

through a rise in inflation. In Zambia, inflation had been exceeding 20 percent until 2004. This

uncomfortably high level of inflation was also brought down through some exchange-rate based

stabilization.

Argentina

0

20

40

60

80

100

120

1995

1997

1999

2001

2003

2005

-5

0

5

10

15

20

25

30


Brazil

0

20

40

60

80

100

120

1995

1997

1999

2001

2003

2005

0

10

20

30

40

50

60

70


Chile

0

20

40

60

80

100

120

1995

1997

1999

2001

2003

2005

0123456789


Costa Rica

8486889092949698

100102104106

1995

1997

1999

2001

2003

2005

0

5

10

15

20

25


Panama

80

85

90

95

100

105

110

115

1995

1997

1999

2001

2003

2005

0

0.20.4

0.60.8

1

1.21.4

1.6


Paraguay

0

20

40

60

80

100

120

1995

1997

1999

2001

2003

2005

0

24

6

8

1012

14

16


Peru

80

85

90

95

100

105

1995

1997

1999

2001

2003

2005

0

2

4

6

8

10

12

14


Uruguay

0

20

40

60

80

100

120

1995

1997

1999

2001

2003

2005

051015202530354045


27

A priori, the AD export share can be expected to lower inflation as a result of nominal appreciation. This

expected response will depend very much on the degree to which nominal currency appreciation is allowed

to operate. To estimate the impact of the Asian Drivers on inflation, we estimate the following equation:

ititit growthgovADortlatdev εβαα +++= exp__*_exp*inf_ 210

where the inflation deviation is defined as the difference between the average CPI-inflation during the

period 1987-1999 and the CPI-inflation in year t, and export_AD represents the export share of country i to

the Asian Drivers. Data on inflation was obtained from the Economist Intelligence Unit (based on the IFS

Database in Datastream). Information on the export shares was collected through the World Integrated

Trade Statistics (WITS) Database. The equation is estimated over the period 2000-2005, using a Hausman

tested fixed-effect estimator for both samples. Results are as follows:

Table 6a. Inflation Deviation and Exports to Asian Drivers

- All countries -

Inflation Deviation vs Export AD 2000-2005 All countries

Latin America Africaexport_ad -4.91E+01 -3.19E+00

[0.55] [0.23]gov_exp_growth 0.21 0.06**

[0.81] [2.19]Observations 9.10E+01 1.23E+02Number of id_gen 16 23R-squared 0.01 0.05Absolute value of t statistics in brackets* significant at 10%; ** significant at 5%; *** significant at 1%

2000-2005

For the total country sample, there is a negative relationship between inflation deviation and the export

share to the Asian drivers, although these results are not significant. However, they suggest that the recent

increase of AD exports could have had the expected impact on the gap between the observed inflation and

the average inflation before the Asian boom. The second explanatory variable, the growth of government

expenditure, seems to be positively correlated with this deviation, being significant (at 5%) for the African

case. This finding suggests that Africa would have experienced higher inflation in the absence of its

general anti-cyclical fiscal stance observed in section 4.1.

28

Table 6b. Inflation Deviation and Exports to Asian Drivers

- Selection Group -

Inflation Deviation vs Export AD 2000-2005 Selection Group

Latin America Africaexport_ad -2.90E+01 -2.96E+00

[0.67] [0.29]gov_exp_growth 0.2 0.05**


2000-2005

Results for the selection group are quite similar to the previous sample. Both coefficients for the export

share are negative, but statistically non-significant. However, the government expenditure growth

coefficient for Africa is consistently positive and significant, which suggests again an important role of

fiscal policy in explaining inflation deviations. Interestingly, for the control group, the coefficient for the

export shares in Africa turns positive (although not-significant). As in the previous cases, the government

spending coefficient results positive and significant for the African case.

Table 6c. Inflation Deviation and Exports to Asian Drivers

- Control Group -

Inflation Deviation vs Export AD 2000-2005 Control Group

Latin America Africaexport_ad -4.98E+02 2.05E+01

[0.85] [0.21]gov_exp_growth 0.12 0.31*


2000-2005

29

5. Export diversification

As shown previously debt management and fiscal responses have been in general more prudent that during

previous episodes of bonanzas. The effects on the real economy and the management of trade impacts have

also changed. In this section we concentrate on the trade impacts looking through the lens of different

indexes (concentration, competition and specialisation).

In order to analyze the degree of diversification (or concentration) in developing countries, two samples are

studied, Latin America and Africa. We used a classic Herfindahl-Hirschmann index for that purpose,

calculated for the years 2000 and 2005, which corresponds to the period of Asian Drivers emergence. This

concentration measure takes into account the weighted average of each good and country, so where values

exported values are low (high), the influence on the indicator is reduced (increased). The index is

calculated as follows:

n

np

HH

n

jj

11

11

2

−

⎟⎟⎠

⎞⎜⎜⎝

⎛−

=∑=

where iijj Xxp /= represents the market share of country j on the exports of country i in its total exports

( iX ). The squared-sum of all shares in also known as the Herfindahl-Hirschmann Index. Given that shares

are weighted by the number of observations, the Herfindahl-Hirschmann index is adopted, allowing to

compare different sets of goods and destinations.

30

Figure 5a. Herfindahl-Hirschmann Index for destinations

Africa – selected countries

AfricaHerfindahl-Hirschmann Index by Destination

00.10.20.30.40.50.60.70.80.9

Moz

ambi

que

Zam

bia

Tuni

sia

Nig

er

Mau

ritiu

s

Beni

n

Mor

occo

Gha

na

Sene

gal

Cam

eroo

n

Cot

ed'Iv

oire

Malaw

i

Tanz

ania

Uga

nda

Sout

h Africa

HH

Ind

ex

2000

2005

In the case of Africa, two major groups of countries showing different patterns can be discerned. On the

one side, in countries like Mozambique, Zambia, Tunisia, Benin, Ghana, Cote d’Ivoire and Malawi,

experienced deterioration between 2005 and 2005 with an increased of the HH indexes. Mozambique and

Zambia experienced the sharpest increases of the concentration indexes by destination. In the case of

Mozambique the major explanation lies in a boom of aluminium exports to one destination that is the

trading platform of this commodity located in Switzerland (China and India are among the major

purchasers). In the case of Zambia, increased exports of copper are behind this further specialisation and

here again China became a major buyer. The others on the contrary experienced more trade diversification

by destination, in particular countries like Niger, Tanzania, Cameroon or Uganda, large soft commodities

exporters. Also South Africa managed to diversify its client portfolio.

31

Figure 5b. Herfindahl-Hirschmann Index for Destinations

Latin America – selected countries

Latin AmericaHerfindahl-Hirschmann Index by Destination

00.10.20.30.40.50.60.70.80.9

Mex

ico

Beliz

e

Ven

ezue

la

Hon

dura

s

Gua

tem

ala

Ecua

dor

Pana

ma

LAC a

vg

Cos

ta R

ica

Col

ombi

a

Boliv

ia

Nicar

agua

Para

guay

Peru

Guy

ana

Dom

inica

Uru

guay

Chi

le

Arg

entin

a

Braz

il

HH

Ind

ex

2000

2005

Source: OECD Development Centre, 2007.

In the case of Latin America, there is a considerable number of countries with high degrees of client

concentration, especially Mexico, Venezuela, Honduras, Guatemala and Ecuador. Other countries like

Colombia, Bolivia, and Peru display a moderate level of concentration, while Chile, Argentina and Brazil

present low concentration levels. However, some countries have experienced more important changes in

the last five years than others. While client concentration has increased importantly in Guatemala, Ecuador,

Peru and Bolivia, all the countries experienced an increasing trade client diversification: China and the

Asian drivers have been helping hands, inducing a trade diversification of Latin American exports in terms

of destination.

The picture of the HH indexes by product confirm the increasing impact of the Asian Drivers in nearly all

the African continent (Figure 6a). As shown in the graph, almost all African countries monitored by the

African Economic Outlook experienced an increasing specialization of their trade profiles in terms of

products. The sharpest movements between 2001 and 2005 are registered in soft commodities exporters

like Mali and Niger. Hard commodities exporters like Angola, Chad, Nigeria, Congo, Mozambique or

Mozambique also experienced sharp concentration movements. Interestingly, manufacturing exporters like

South Africa, and to a lesser extend Morocco experienced, a trade deterioration, impacted both by foreign

exchange appreciations and increased competition from the Asian Divers (Kaplinsky and Morris, 2007; in

this Special issue). Note, however, that the results are biased by changes in commodity prices as they are

32

not computed at constant prices. So a fall of commodity prices would show fewer tendencies for product

specialization.

Figure 6a: Herfindahl-Hirschmann Index for Sectors

Africa – selected countries

Export Concentration in Products for AfricaHerfindahl Hirschman Index

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Angola

Chad

Nigeria

Congo

Mali

Niger

Mozam

bique

Algeria

Zambia

Cameroon

Ghana

Gam

bia

Nam

ibia

Côte d'Ivoire

Senegal

Zimbabw

e

Kenya

South Africa

Tunisia

Morocco

2000

2005

Source: African Economic Outlook 2005-2006, OECD Development Centre, 2007.

Figure 6b:. Herfindahl-Hirschmann Index by Product

Latin America – Selected countries

Export Concentration in Products for Latin AmericaHerfindahl Hirschman Index

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

Venezuela

Ecuador

Chile

Panama

Bolivia

Peru

Paraguay

Honduras

Guyana

Uruguay

Colombia

Costa Rica

Mexico

Guatemala

Brazil

2001

2006

Source: OECD Development Centre. Based on World Integrated Trade Statistics (WITS). Nomenclature: SITC Revision 3 (4-

digit).

33

Latin America does not seem to display major movements in product specialization nor diversification,

once the HH-Indexes are corrected for price effects. The only exception of importance is Mexico, as a

result of resource depletion rather than diversification success.

In terms of trade diversification, it seems that, for the majority of countries studied, the Asian Drivers

helped to diversify the destinations of exports both for Latin American and for African countries, even if in

the case of Africa the picture is more nuanced. When we focus on trade diversification by products, the

picture is also more mixed, with some African and Latin American countries in particular experiencing a

deepening of resource dependence.

Conclusive remarks: an opportunity for better management

This paper arrives at an overall optimistic assessment about the net macroeconomic policy responses to the

impact of Asian Driver induced commodity booms in Africa and Latin America.

Commodity-exporting countries have accrued clearshort-term benefits from the current boom accrued by

higher prices and export proceeds and greater profits. The commodity boom has also had a positive impact

in terms of broadening exporters’ client base, enabling them to retire costly debt and improve credit

profile, increase foreign exchange reserves so as to reduce vulnerability to future speculative attacks,

finance infrastructure for future growth and to build nest eggs abroad and at home for leaner times.

Meanwhile, the negative Dutch disease effects and increased ‘Leamer corner’ solutions and lower non-

resource exports that might have resulted from the commodity boom have been milder than is often argued.

The prospective sources of commodity demand from the Asian Drivers could well migrate from

mineral/depletable to agricultural/replenishable commodities which recent research (Collier and Goderis,

2007) has shown to exert more positive long-run benefits for development.

Much of the beneficial effects observed so far are due to policy performance. The monetary policy choices

have in general tried to target both inflation and real effective exchange rates, with some success (with

exceptions such as Zambia). These findings, unexpectedly, suggest that over recent years, when the AD

34

driven commodity boom gained full traction, macroeconomic policy challenges have been better coped

with and monetary policy better managed in Africa than has been the case ,on average, in Latin America.

The rapid growth of Asian emerging economies is raising demand for Africa's and Latin America’s

commodities (oil, metals and precious stones) and has resulted in improved terms of trade as well as rapid

growth in primary commodity exports. Yet, deficient infrastructure, insufficient investment in human

capital, and inadequate policies limit the ability of African and Latin American economies to fully seize the

opportunities opened up by global markets. The increased global demand for agricultural and food

products gives hope for a more even development pattern than that which can be achieved under a solely

extractive model, and therefore resources need to be dedicated, and productivity enhanced in these sectors.

For exporters of natural resources, the challenge is to capitalise on mineral windfalls to ensure that a large

proportion of the proceeds from the minerals sector are invested in infrastructure and human-capital

development. Diversification remains an imperative, it is a medium-term objective that will depend, among

other things, on the capacity to promote private-sector development, particularly in Africa, and to expand

markets.

Commodity exporters are aware of their potential to consolidate export proceeds in sovereign wealth funds

(SWF). These government controlled investment vehicles have stimulated protectionist sentiments in some

OECD countries. Their asset size, so as their owners (governments) create fertile ground for suspicion.

Nonetheless, several motives can be mentioned for commodity-oriented countries to run such funds: First,

foreign exchange reserves – mostly held in US treasury bonds – have grown excessively large: interest rate

and currency risk argue in favour of portfolio diversification, and central banks cannot control monetary

aggregates anymore. Second, reducing resource dependence through vertical and horizontal sector

diversification. Third, responding to expected demographic pressures, while smoothing consumption levels

of future generations when resources are exhausted. Fourth, raising production efficiency as a future driver

of growth.

As discussed earlier, commodity exporters in both Africa and Latin America should be indifferent to

whether keeping resources unextracted (in which case the return is the expected rise in future prices) and

getting a market rate of return on its sale (Hotelling Rule for efficient depletion). Extracting and selling

raw-commodity amounts to running down capital, unless the receipts are fully reinvested in financial,

physical or human capital (Hartwick Rule for intergenerational equity); ‘genuine’savings are negative if

the Hartwick rule is not respected. Funds can also be helpful for stabilising notoriously volatile raw

35

material prices. The law of diminishing returns forces commodity exporters to invest a large share of the

savings abroad. They would be forced to disregard both the Hotelling and the Hartwick rules, if SWFs

could not invest in OECD countries. The Hotelling rule warns that lowering the returns on investment from

commodity receipts, by preventing investments by SWFs from commodity-rich countries, would lead to a

reduced supply and higher commodity prices. This would be counter-productive for resource-abundant

economies. If they do not follow the Hartwick rule, they have negative ‘genuine’ savings rates and become

poorer each year3. This highlights the important policy question of what resource-rich economies can do to

avoid the resource curse. Funds are an option, to the extent that commodity receipts are eventually

transformed into other forms of wealth.

Next to shifting out of excessive reserves and saving for future generations and old age, economic

diversification and efficiency gains are major economic motives for establishing SWFs. Some countries

(i.e. United Arab Emirates) are using their fund for rapid diversification of their economies away from oil

toward tourism, aerospace and finance. Such a diversification motive is as legitimate as the desire to raise

the efficiency of their economy through acquiring stakes in leading global companies. The insertion of

commodity-based funds into the financial architecture could guarantee a more efficient management of

proceeds and a sustainable instrument for enhancing growth.

3 The World Bank, Where Is the Wealth of Nations?, Washington, 2006.

36

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Documents

The Macro-Management of Commodity Booms:Africa and Latin America’s responses to Asian Demand (OECD)