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Sub-Saharan Africa: struggling, but still growing

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  • Sub-Saharan Africa is still growing fast, although growth is only bringing moderate reductions in poverty
  • Growth is suffering from lower commodity prices, causing larger current account and budget deficits, increased public debt and weakened currencies
  • The slowdown in China, the main export market, is negatively affecting Sub-Saharan Africa
  • East Africa is less vulnerable to falling commodity prices than West Africa
  • Demographic transition is slow and dependent on improvements in schooling and institutional quality

Sub-Saharan Africa has made good progress since its designation as the ‘hopeless continent’ by The Economist in May 2000, when floods, famine, war, disease and poverty were major problems. Since then, violent conflicts have been fewer (Dumitru and Hayat, 2015), education has improved (Hayat and Kalf, 2015) and deaths from preventable diseases have dropped.

Also, Sub-Saharan Africa is still one of the world’s fastest growing economies, mainly driven by public infrastructure investments, increased agricultural production and the services sector. But GDP growth has come down from its five-year average of 6% and we expect it to be about 4% in the coming few years.

Unfortunately, despite high GDP growth, per capita GDP growth has lagged behind due to high population growth (Sub-Saharan Africa: Letting economic development curb population growth) and poverty levels have hardly declined since the 1980s (Figure 1)[1]. An important reason why GDP growth has not translated into less poverty is that it has mainly benefitted the well-off rather than the poor, which in turn is largely due to high levels of corruption (Dumitru and Hayat, 2015). The Gini coefficient (a well-known measure of inequality) for Sub-Saharan Africa has hardly declined in the past decade (Figure 2).

Figure 1: Growth has sped up, but poverty has not declined much
Figure 1: Growth has sped up, but poverty has not declined muchSource: World Bank
Figure 2: Inequality has hardly decreased
Figure 2: Inequality has hardly decreasedSource: World Bank

Risks from commodity dependence are starting to show

Commodity prices (especially energy) have decreased  sharply in the past 17 months (Figure 3, Dumitru, 2015). Both oversupply and slower demand from China have played their parts, and both elements also weigh on the Sub-Saharan economic outlook as the region mainly consists of net commodity exporters (Figure 4). In Nigeria and Angola for example (jointly accounting for 42% of Sub-Saharan African GDP), net commodity exports represent 13% and 44% of GDP respectively. In addition, governments of Sub-Saharan countries rely heavily on commodities. Oil for example is responsible for 70% or more of government revenues in Angola, Republic of the Congo and Equatorial Guinea.

Figure 3: Commodity prices have been on a downward trend
Figure 3: Commodity prices have been on a downward trendSource: Macrobond
Figure 4: Sub-Saharan Africa mainly consists of commodity exporters
Figure 4: Sub-Saharan Africa mainly consists of commodity exportersSource: Unctad, Rabobank

The high dependence of Sub-Saharan countries on commodities is a risk. This is starting to show not just in slower economic growth, but also in widening current accounts and government budget deficits, increasing public debt, depreciating currencies and rising inflation.

Starting with the current accounts, these are generally already weak in Sub-Saharan Africa (the average current account deficit is 9% of GDP, see Annex). Moreover, they are expected to weaken further, especially in countries where exports are falling sharply while imports are not (for example because they consist of necessities like food).

Government budgets are also weak (the average government budget deficit is 4% of GDP, see Annex) and budget deficits are expected to widen in countries where governments rely heavily on commodity-based revenues. These governments face a fall in revenues but cannot easily reduce costs without creating unrest (since a large part of these costs are often public sector workers’ wages). Government budget deficits may also widen in the run-up to elections, which are scheduled in 2016 in Ghana, Zambia, Gabon and Uganda.

Public debt in Sub-Saharan Africa is also expected to increase. Currently, public debt is not very high (30% of GDP on average). But this is due to a lack of access to international capital markets for Sub-Saharan governments (they generally lack a confidence-inspiring track record and have narrow tax bases apart from commodity-related revenues). In that sense, debt levels are not low either and likely to increase now that commodity-based revenues have fallen. Moreover, governments will have to pay higher interest rates to attract this debt as they have become riskier due to a slowdown in growth. Thus, governments in Sub-Saharan Africa face more difficult financing conditions going forward.

As a result of the above, Sub-Saharan currencies have depreciated considerably (Figure 5). Not all depreciations have been driven entirely by lower commodity prices, though. The South African rand (ZAR) for example has depreciated against the US dollar by 26% since January 2014, despite its natural hedge against commodity price fluctuations (it exports precious metals but imports oil). The ZAR depreciation has more to do with lower mining output (driven by strikes by miners and power outages) and a possible interest rate hike by the US Fed (which makes South African government bonds less attractive). This has generated capital flight from South Africa, facilitated by South Africa’s well developed capital market. 

Figure 5: Commodity-dependent currencies have depreciated
Figure 5: Commodity-dependent currencies have depreciatedSource: Macrobond

Depreciating currencies have a significant impact on Sub-Saharan Africa for two reasons. First, they generate imported inflation as imports become more expensive in the local currency. This has happened for example in Ghana, where inflation has reached 15% as the Ghanaian cedi has depreciated by 41% against the US dollar since January 2014. Second, depreciating currencies put pressure on Sub-Saharan countries with high foreign currency debt levels. It is difficult to gauge the size of this problem as (i) data on the amount of foreign currency debt in Sub-Saharan Africa is hard to come by, (ii) the countries with foreign currency debt can have a natural hedge since they have foreign currency income via commodity exports and (iii) the borrowing parties in the countries may hedge their foreign currency exposure using derivatives. Still, two countries to watch in this respect are Zambia, Ghana and Angola where foreign currency public debt is 26%, 32% and 37% of GDP respectively.

Countries that have a currency pegged to the US dollar (see Annex), whether directly (for example Eritrea) or indirectly (for example Nigeria), may see foreign reserves being drained in order to maintain the peg before being forced to abandon the peg.

The effects of lower commodity prices described above should be interpreted with care. They mask big differences between the individual countries in Sub-Saharan Africa. East Africa, for example, is less commodity-intensive in general and is a net importer of commodities rather than an exporter (Figure 4). For Kenya, Mozambique and Tanzania for example, net commodity imports represent 4%, 3% and 2% of GDP respectively. On balance, these countries have benefitted from lower commodity prices[2]. Commodity imports in Ethiopia, Rwanda and Uganda are about the same size as their exports, which makes these countries less vulnerable to commodity price fluctuations.

Risks from commodity dependence may also extend beyond the short-run, cyclical effects described above. Commodity dependence can (i) make governments complacent about implementing necessary economic reforms and (ii) increase inequality. The government then has to ‘buy off’ civil unrest through (inefficient) subsidies and other handouts, which gives it less flexibility to reduce costs when commodity prices fall.

In the case of Sub-Saharan Africa, commodity dependence is also dependence on China in disguise as China is the world’s largest commodity consumer and the main export market for Sub-Saharan Africa. The Chinese economy is in transition from a construction-, manufacturing- and export-oriented economy to one that is based on services and consumption, and growth is slowing (Loman, 2015). This will create a ‘double whammy’ for certain African countries, because on the one hand they suffer from the lower commodity prices and on the other hand they suffer from reduced demand (from China) for their exports. Some notable countries in this sense are Sierra Leone, the Republic of the Congo and Angola, where respectively 80%, 59% and 51% of exports go to China (see Annex). China’s slower growth not only hurts Africa via exports, but also via foreign direct investments (FDI), because lower Chinese growth may also mean less Chinese FDI into Africa (a large part of FDI in Africa is from China).

Letting economic development curb population growth

Although Sub-Saharan economic growth is still high, much of it is still generated by high population growth. Figure 6 shows that there has been quite substantial progress in GDP per capita growth since the start of the 2000s. That said, population growth is very high and will result in the Sub-Saharan African population growing from its current level of 974 million to 2.4 billion by 2050. This could lead to all sorts of problems in areas where vital resources (e.g. food or water) are scarce. That is why it is imperative for Sub-Saharan Africa to increase crop yields for example and add more value in food and agriculture value chains (Barendregt, 2015). Fortunately, there are some countries that already have relatively high GDP per capita growth (above the regional average) combined with relatively low population growth. These include Mauritius, the Seychelles, Botswana and Angola. Burundi, Niger and Eritrea on the other hand have low GDP per capita growth.

Figure 6: The demographic transition finally taking off?
Figure 6: The demographic transition finally taking off?Source: United Nations, Macrobond, Rabobank
Figure 7: Per capita GDP growth vs population growth (2005-2014)
Figure 7: Per capita GDP growth vs population growth (2005-2014)Source: United Nations, Macrobond, Rabobank

The theory behind the demographic transition

Galor and Weil (2000) have argued that economic development itself can generate declining population growth. Using Western Europe as a case study, they describe how regions make a demographic transition from population-driven growth (in Europe’s case before 1820) to economic growth that is driven by GDP per capita growth. Technological change is the backbone of Galor and Weil’s model: it leads to higher per capita GDP growth, which in turn leads to a higher level of development. However, technological change also affects the rate of return on human capital. This is because technology usually requires knowledge and skills to work with. The rate of return on human capital leads parents to substitute the quality of their children’s upbringing (i.e. the amount of schooling) for the number of children. This substitution effect is reinforced by the decline in mortality. As richer parents have better access to food and healthcare, the higher per capita income in turn lowers the mortality rate of their children. Finally, reduced mortality also raises the rate of return on investments in a child's human capital. As parents have fewer children, the fertility rate falls. The result is declining rates of population growth and rising growth of per capita income. As can be readily gleaned from Table 1, Sub-Saharan Africa still has a long way to go in this transition, as it has the highest fertility and mortality rates of all regions.

Table 1: Fertility and mortality rates are still high in Sub-Saharan Africa
Table 1: Fertility and mortality rates are still high in Sub-Saharan AfricaSource: United Nations, Macrobond, Rabobank

To illustrate that the Galor and Weil transition mechanism is nevertheless at work, Figure 8 shows the number of children per woman (quantity) in relation to secondary school enrolment (quality) across Sub-Saharan Africa. This figure suggests that there is a negative relationship between secondary school enrolment rates and the number of children per woman. Countries like Botswana, the Seychelles and Cape Verde have higher enrolments rates and lower births per woman. On the other hand, countries like Angola, Burkina Faso, Burundi, Niger, Zambia and Uganda still have higher fertility rates while fewer than 25% of children are enrolled in secondary school[3]. As The Economist suggested, private education may be a better indicator of the larger investments in their children’s upbringing that parents are willing to make. Based on Figure 9, there is no clear negative correlation between the share of privately educated children and fertility. That said, the share of privately educated children can also be affected by many other factors. Within Galor and Weil’s transition framework, this leaves us with the fertility conundrum: why is fertility not dropping faster? There are two possibilities: either the substitution effect between the number of children and schooling is not strong enough to curb fertility, or the return on the human capital acquired by the children is too low to raise the per capita growth rate.

Figure 8: Net enrolment rate of children in age range
Figure 8: Net enrolment rate of children in age rangeSource: United Nations, World Bank, Rabobank
Figure 9: Share of privately educated children
Figure 9: Share of privately educated childrenSource: United Nations, World Bank, Rabobank

While it is difficult to test the first hypothesis with macro-level data, we can explore the second hypothesis further. Looking at Figure 10, we see that human capital per capita is steadily increasing over time. Growth in GDP per capita on the other hand is lagging behind and has barely grown over the last 45 years.

Figure 10: Human capital and GDP growth per capita
Figure 10: Human capital and GDP growth per capitaSource: Penn World Tables, World Bank, Rabobank.

Only the 2000s saw significant growth (Figure 10) but this is probably still too modest to sufficiently influence the choice in the number of children. Figure 10 clearly suggests that most Sub-Saharan African countries are unable to fully reap the benefits of their human capital stock. For that to happen, two important pre-conditions need to be met: fewer conflicts and improvements to the quality of institutions. The number of conflicts in Sub-Saharan Africa has fallen, but the region still has poor overall institutional quality (Dumitru and Hayat, 2015). These factors will make or break the demographic transition that is so vital to Sub-Saharan Africa’s further economic development.

Footnotes

[1] Poverty rate (or rather, the extreme poverty rate) is defined here as the percentage of the population that lives on less than USD 1.25 per day.

[2] Barring distributional effects within the countries that may feed into inequality measures.

[3] Country-level data for the relevant variables can be found in the Annex. 

References

The Economist (2015), Learning unleashed, The Economist print edition of 1 August

Galor, O and D. Weil, (2000), Population, technology and growth: from the Malthusian regime to the demographic transition and beyond, American Economic Review, 90, pp. 806-828.

Loman, H. (2015),  China: onzekerheden nemen toe (in Dutch), Rabobank Economic Research

Barendrecht, E. (2015), Sub-Saharan Africa: Developing Food and Agricultural value chains in Sub-Saharan Africa, Rabobank Economic Research

Dumitru, A. and R. Hayat (2015),  Sub-Saharan Africa: Stronger But Still Fragile, Rabobank Economic Research

Dumitru, A. (2015), Latin America: The Tide Has Turned, Rabobank Economic Research

To the Sub Saharan Africa overview page 

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This study is a publication of Economic Research (KEO) of Rabobank.

The views presented in this publication are based on data from sources we consider to be reliable. Among others, these include Macrobond. The economic growth forecasts are generated from the NiGEM global econometric structure models.

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Abbreviations for sources: FAO: Food and Agriculture Organization of de United Nations, FAOstat: The statistics division of the FAO  USDA: US Department of Agriculture

Abbreviations used for countries: Angola: AO, Benin: BJ, Burkina Faso: BF, Botswana: BW, Burundi: BI, Cameroon: CM, Cape Verde: CV, Central African Republic: CF, Chad: TD, Comoros: KM, Congo (Democratic Republic): CD, Congo: CG, Djibouti DJ, Equatorial Guinea: GQ, Eritrea: ER, Ethiopia: ET, Gabon: GA, Gambia: GM, Ghana: GH, Guinea: GN, Guinea-Bissau: GW, Ivory Coast: CI, Kenya: KE, Lesotho: LS, Liberia: LR, Madagascar: MG, Malawi: MW, Mali: ML, Mauritania: MR, Mauritius: MU, Mozambique: MZ, Namibia: NA, Niger: NE, Nigeria: NG, Rwanda: RW, Sao Tome & Principe: ST, Senegal: SN, Sierra Leone: SL, Seychelles: SC, South Africa: ZA, South Sudan: SS, Swaziland: SZ, Tanzania: TZ, Togo: TG, Uganda: UG, Zambia: ZM, Zimbabwe: ZW

Abbreviations used for currencies: AOA: Angolan kwanza, ETB: Ethiopian birr, KES:  shilling, MZN: Mozambican Metical, RWF: Rwandan franc TZS: Tan shilling UGX: Ugandan shilling, ZAR: South African Rand, ZMW: Zambian kwacha

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Editors-in-chief: 
Allard Bruinshoofd, head of International Research, Economic Research

Graphics: Selma Heijnekamp and Reinier Meijer

Production coordinator: Ester Barendregt and Christel Frentz

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