Chapter

Chapter IV. Sustaining Growth in Africa

Author(s):
International Monetary Fund. African Dept.
Published Date:
April 2006
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Are improvements in growth in SSA since the mid-1990s sustainable? This chapter1 examines this question in three stages. First, it explores the factors contributing to this recent improvement in growth. To what extent is the growth recovery driven by favorable external conditions? Have improved policies played an important role? Has the improved growth performance been accompanied by improvements in investment, productivity growth, and basic institutions, suggesting a more durable foundation? How do these factors explain differences in performance across subgroups in the region? The analysis throughout considers correlations, as many of the factors considered are themselves strongly influenced by output growth, making it difficult to establish causal relationships. Second, although the recent improvement in growth is encouraging, it is insufficiently strong to put SSA on a path to make substantial reductions in poverty, as set out in the Millennium Development Goals. To shed some light on factors associated with substantial jumps in growth rates that are sustained in the medium term, a preliminary analysis of the correlates of growth accelerations is presented. Third, the chapter examines the consistency of the SSA data with some important predictions from the literature, directly linking such areas as fiscal policy, financial development, or institutions and growth. The chapter closes with some reflection on the lessons.

The literature on African growth has evolved from offering monocausal explanations for Africa’s stagnation (geography, ethnic fractionalization, or poor policies, for example) to suggesting that the wide diversity of performance indicates a complex set of factors at play. The literature has generally converged on the view that Africa does not grow differently from other regions; rather, Africa is particularly disadvantaged and has the poorest record on the factors that drive the growth process worldwide.2 New modes of analysis have also shed light on the growth process in Africa. A comparison of the aggregate growth regression evidence with the microeconomic literature suggests that high risk (policy and exogenous volatility), a lack of openness to trade, weak institutions, and poor public services are key constraints to growth in SSA. A new method for identifying robust explanatory variables finds that poor health indicators, ethnic diversity, expensive investment goods, low levels of education, excessive government expenditure, and a lack of openness contributed the most to SSA’s growth shortfall relative to the rest of the world.3

Recent papers have suggested that opportunities for growth vary among African countries, depending on the availability of natural resources and location, as well as the external environment, inherited institutions, and the prevalence of disease. According to this view, political and policy choices in the face of these economic opportunities are what determine countries’ growth outcomes. For example, growth opportunities may be quite different in resource-abundant countries, coastal countries without natural resources, and landlocked countries without natural resources.4 In an analysis of the diversity of growth experiences, other exogenous and endogenous structural characteristics of African economies could also be at play: membership in the CFA franc zone, whether a country is involved in conflict, and whether it has an IMF-supported program.

The stylized facts of growth during 1960–2003 are sobering. For the region as a whole, real GDP grew at an average rate of 3.7 percent a year, and real GDP per capita grew at 1.1 percent.5 Real per capita income is approximately the same as in the mid-1970s. Because of very weak overall growth, Africa’s real GDP per capita has steadily lost ground relative to both industrial and other developing country regions. Growth rates in Africa also tend to be more volatile than in other regions, particularly at short and medium horizons. Growth-accounting decompositions show that average TFP growth for SSA has declined in every decade since 1970,6 which has been called the primary reason for SSA’s slow growth.7

There has been a strong improvement in economic growth since the mid-1990s. SSA’s average real GDP per capita growth increased to 2.0 percent in 1995–99, from −1.1 percent in 1990–94, an improvement shared by all subgroups (Figure 4.1). The number of countries with real GDP growth rates exceeding 5 percent increased from 4 to 15. However, during 2000–03, growth slackened somewhat for all subgroups except oil producers and resource-intensive countries, where it was driven by the 21.6 percent growth in Equatorial Guinea, and conflict countries, where it was driven by the postconflict recovery in Sierra Leone. The post-1995 growth recovery has been fueled by a significant increase in TFP growth. We consider below the factors accounting for the strong growth in the fastest-growing economies of the 1990s; that is, those whose real GDP per capita growth rates place them in the top third of the distribution (see Appendix Table A3).8

Figure 4.1.Sub-Saharan Africa: Real GDP Per Capita Growth

(Percent)

Source: IMF, WEO/Economic Trends in Africa database, 2005.

Note: See Appendix, Table A2, for country groupings.

Explaining Differences in Growth Performance

Higher growth rates in the 1990s were accompanied by improved macroeconomic indicators (Figures 4.2 and 4.3). The average inflation rate in economies that grew the fastest during the 1990s was 12 percent, compared with an average of 21 percent in the slowest-growing economies.9 Despite spending roughly the same as slow-growing economies as a ratio to GDP, fast-growing economies exhibit lower fiscal deficits including grants because of their higher revenue collections. There is no doubt that the region’s stronger terms of trade growth since the second half of the 1990s has also contributed to the growth recovery. However, the fastest growers of the 1990s do not appear to have experienced more favorable terms of trade growth. They were, however, more open to trade, as indicated by higher ratios of exports plus imports to GDP (Figure 4.4).

Figure 4.2.Sub-Saharan Africa: Annual Inflation Rate

(Percent)

Source: IMF, WEO/Economic Trends in Africa database, 2005.

Figure 4.3.Sub-Saharan Africa: Fiscal Balance

(Percent of GDP)

Source: IMF, WEO/Economic Trends in Africa database, 2005.

Figure 4.4.Sub-Saharan Africa: Trade Openness in the Fast, Medium, and Slow Growers of the 1990s

(Percent of GDP)

Source: World Bank, World Development Indicators database, 2004.

Different aspects of the late 1990s growth recovery give mixed signals about its sustainability. On the negative side, except in the oil-producing countries, total and private investment has, on average, barely increased. Excluding Equatorial Guinea’s unique investment rates of 90 percent of GDP in the late 1990s, the fast-growing economies still had slightly better total investment than the medium or slow growers, and maintained it in 2000–03. Investment rates were also higher in non-CFA franc countries (again excluding Equatorial Guinea), but the differential eroded in the most recent period.

The positive news is that TFP growth, although moderating in the most recent period, improved strongly in the second half of the 1990s for the first time since the 1960s.10 The fast growers of the 1990s registered TFP growth of 2.3 percent in the second half of the decade (3.3 percent including Equatorial Guinea), while TFP growth in the other two performance groups was negative, or below 0.7 percent. These increases in TFP growth were significantly influenced by improvement in countries with on-track11 IMF-supported programs (Appendix Table A4).12 It is important to note, however, that standard estimates of TFP growth for oil-producing countries, given the structure of their economies, are problematic. While the progress on TFP growth in SSA is less strong when oil producers are excluded, the positive results for the fast growers of the 1990s and for countries with on-track Fund programs are not affected. (See Box 4.1 on the varied growth experiences in three countries and challenges relating to productivity improvements, responses to shocks, and management of oil revenues.)

Many of the inferences noted above are also supported by robustness analyses of cross-country growth regressions. Recent papers use a new Bayesian technique to address uncertainty about which explanatory variables belong in the model and to address endogeneity of these variables (in the second reference) (Sala-i-Martin, Doppelhofer, and Miller 2004; Tsangarides, 2005). Using a world sample, an extension of the latter found that, in addition to initial conditions, the following variables were robustly correlated with growth: factor accumulation (investment and education); policy variables (inflation, fiscal balance, government consumption, black market premium); and fixed geographical and exogenous factors (percentage of land in the tropics, arable land, and terms of trade growth).

The results of the cross-country growth analysis suggest that Africa’s growth has been substantially lower than that of other regions on account of weak policies, but lower levels of factor accumulation, particularly investment, have implied extremely large growth losses compared with other regions. Clearly, however, lower factor accumulation in SSA is also partly the consequence of weak policies. Appendix Table A5 shows that SSA’s growth could have been about 2 percentage points higher every year if policies had been as strong as those in other developing country regions, such as Latin America or South Asia, and these shortfalls increased slightly in the 1990s. But, strikingly, the estimates suggest that annual growth in SSA could have been substantially higher if it had been able to achieve the same factor accumulation rates—mainly investment—as other developing countries.

Higher growth in the second half of the 1990s than in earlier periods reflects the contribution of improved policies. Appendix Table A6 shows that the fast growers’ improvement in growth relative to the early 1980s reflected the combined positive impact of the policy variables, as well as a small positive contribution from the terms of trade.13 The contribution from investment, however, was smaller (and had a negative effect on growth for medium and slow growers). The result showing the contribution of policies to growth for the fast growers is propelled by the large improvement in the robust policy variables in countries with on-track IMF-supported programs. However, declines in investment for this group had a negative impact on growth. While investment declines negatively affected growth in CFA franc countries, small increases contributed positively to growth in non-CFA franc countries.

Box 4.1.Growth Experiences: Uganda, The Gambia, and Nigeria

For Uganda, the role of productivity gains is key to the sustainability of growth.1 Uganda has enjoyed a sustained postconflict recovery, characterized by impressive growth in real GDP (6.2 percent between 1986/87 and 2003/04, although, with very high population growth rates, per capita growth rates have been relatively moderate) and substantial reductions in the incidence of poverty. However, growth-accounting analysis and recent sectoral studies of agriculture and manufacturing show that the contribution of TFP growth has been extremely low. Capital accumulation explains about 85 percent of real GDP growth since the mid-1980s. Because increasingly higher investment rates (and, consequently, rising national or external saving) are not feasible, low TFP growth seriously threatens Uganda’s achievement of sustained high growth and poverty reduction. Sustainable high growth will require a structural reform agenda aimed at increasing productivity and gradually increasing investments by addressing such investor concerns as corruption, high transportation costs, erratic electricity supplies, and inadequate access to financial resources.

The volatility of growth declined substantially in The Gambia—and was, in fact, lower than that of all of SSA—during the period of comprehensive reforms (1985–95), underscoring the importance of appropriate policies in helping to mitigate the impact of shocks.2 While limited diversification makes the economy particularly prone to external shocks, frequent setbacks to economic reforms have contributed to growth volatility. Growth has been constrained by inappropriate policy responses to shocks, the existence of various policy distortions, and recurrent slippages in fiscal policy, which have fueled inflation and tended to increase the government’s recourse to domestic bank financing and to crowd out private investment. For example, while in the period following the military coup (1995–2001) many of the previous policy gains were quickly eroded, fiscal and trade reforms in the latter part of the period contributed to reviving growth, building on the foundation of earlier reforms. However, growth was derailed again by further fiscal slippages associated with elections and by governance problems. Sustained efforts to strengthen governance, maintain fiscal discipline, and strengthen public expenditure management are necessary for maintaining competitiveness and creating an enabling environment for private investment, which should lower growth volatility.

In Nigeria, more effective use of oil revenues could both better insulate the economy against the booms and busts of oil production and rejuvenate the non-oil economy. Nigeria’s poor per capita growth performance can be traced directly to the discovery of oil in the 1960s. Oil wealth resulted in a positive terms of trade shock and real exchange rate appreciation, which, in turn, undermined the competitiveness of non-oil exports. The labor-intensive sectors of agriculture and light manufacturing have undergone a structural decline, contributing to the deterioration in social indicators. In addition to oil, weak institutions and misguided policies—resulting in a lack of personal and property security, poor governance, and corruption—have also impeded growth in Nigeria. Moreover, spending on infrastructure (necessary for better farm-to-market roads and an efficient and reliable power supply, for example) has been inadequate and of poor quality. The current government is embarking on its own National Economic Empowerment and Development Strategy (NEEDS), with reforms that center on improving the management of oil revenues; enhancing the efficiency and effectiveness of government spending; improving public sector governance, including addressing corruption related to oil rents; and focusing on policies that will spur the non-oil economy. These are the right priorities; clearly, implementation is challenging.

1Mikkelsen (2005, forthcoming).2Randall (2005, forthcoming).

Growth Accelerations

Very large and sustained increases in growth rates are necessary if SSA is to have a realistic prospect of halving income poverty by the year 2015. To meet this Millennium Development Growth, SSA’s real GDP growth rates will have to double from a base scenario to about 7.5 percent.14 Although knowledge about what leads to sustainable, large accelerations of growth in SSA is limited, it is instructive to look at some recent success stories and do a preliminary analysis of the correlates of those accelerations.

By looking at jumps in countries’ medium-term growth trends, labeled growth accelerations, one can gain insight into the sources of successful growth transitions. A recent paper has proposed that the traditional focus of empirical growth research on long-horizon or panel-data-growth regressions can camouflage important medium-term patterns in a country’s growth.15 In addition, standard methods do not directly address a policymaker’s key question: how likely is it that a particular country will experience a growth acceleration that is sustained for a period of time? For our purposes, an acceleration occurs in a year when the five-year forward-looking per capita growth rate exceeds by at least 2 percent the comparable backward-looking rate and when the growth rate following the acceleration in that five-year period is at least 2 percent. This method identifies 34 growth acceleration episodes in the region since 1980, with more such episodes in the 1990s than in the 1980s, including several episodes currently under way (Table 4.1). Episodes occur in countries at all levels of per capita income.16

Table 4.1.Acceleration Start Dates and Per Capita Growth Rates for 1980s and 1990s
1980s1990s
Start dateEpisode growthPost-episode growthStart dateEpisode growthPost-episode growth
Botswana19867.71.2Angola19934.92.6
Burkina Faso19833.32.9Benin19932.22.0
Burundi19832.4−0.1Botswana19964.7
Chad19833.31.4Burkina Faso19944.73.2
Congo, Rep. of19845.2−2.7Cape Verde19924.55.1
Gabon19862.90.5Chad19998.3
Ghana19832.92.0Côte d’Ivoire19932.3−4.2
Kenya19842.5−1.6Equatorial Guinea199429.718.5
Lesotho19864.22.8Ethiopia19923.81.4
Mauritius19847.35.6Gambia, The19952.2
Mozambique19866.02.4Guinea19942.30.0
Seychelles19875.72.6Malawi19944.8−3.5
Tanzania19852.3−1.6Mozambique19947.15.1
Uganda19863.94.1Rwanda19962.6
Zimbabwe19862.6−1.2Senegal19942.21.5
Seychelles19957.5
Sierra Leone199910.9
Tanzania19994.0
Zambia19992.1
Source: IMF staff calculations from World Economic Outlook database, 2004.Notes: GDP per capita data in U.S. dollars. Acceleration episodes last five years and are identified as described in text. Post-episode growth refers to the annual growth rate in the five years after an episode ends. Since an episode itself lasts five years, post-episode growth rates cannot be calculated for accelerations beginning after 1994. A sustained acceleration (shaded) is one where the average per capita growth was at least 2 percent for five years after an acceleration ends. All growth rates are calculated by a regression of per capita income on a constant and a trend.

Empirical investigation sought to identify determinants of accelerations during the 1980s and 1990s. A broad range of explanatory variables covering macroeconomic stability, trade, debt, institutions, capital, and geography were examined, some of which can be thought of as triggering an acceleration, and some of which enable an acceleration to continue. Findings in Table 4.2 are based on a comparison of average values of economic variables during the acceleration episodes with those during times when there was no acceleration, as well as relative to the period prior to an acceleration, augmented by formal tests of statistical significance.17 In interpreting the results, one should bear in mind that the analysis is limited to correlations, not causal determinants; it is difficult to distinguish between the causes and the consequences of accelerations.

Table 4.2.Differences Between Sample Averages for Acceleration Episodes: Own Past and Nonepisodes
1980s1980s
Accelerations vs. nonaccelerations: duringAccelerations: during vs. beforeAccelerations vs. nonaccelerations: duringAccelerations: during vs. before
Macroeconomic
Inflation−2.7−5.6*−1.9−2.3
Central govt. bal. to GDP2.4*1.4*−0.90.5
REER, percent change−6.0*−9.9*−1.8−2.0
REER, percent change, non-CFA−8.5*−14.3*−1.0−1.3
CPIA0.3*0.3*0.2*0.03
Trade
Partner growth0.3*1.1*0.3*0.3*
Sachs-Warner (updated)0.03*0.04*0.02
Real export growth10.2*14.4*5.8*6.5*
Debt
Debt service0.79.1*−2.4*−4.3*
Debt/GDP−39.3*27.6*5.68.8
NPV of debt growth0.8−9.4−4.0*−3.8*
NPV of debt/exports0.31.5*0.30.1
Institutions
Polity index1.1*−2.1*0.23.9*
Longtime leader change0.20.61.1*1.1
Capital and productivity
Investment to GDP1.8*−1.46.1*6.0*
TFP growth0.03*0.03*2.3*3.3*
Source: IMF staff calculations.Note: Asterisk (*) indicates that the difference in means was significant in at least a one-tailed test at 10 percent.

Growth accelerations do not come at the expense of macroeconomic stability; inflation and budget deficits are either insignificantly different or better in acceleration episodes than in control groups. Inflation is slightly lower during the episodes of accelerated growth, but not significantly so, and the episodes of the 1980s also feature better central government budget balance, including grants. Furthermore, the results for trade variables (discussed further below) show a real exchange rate depreciation in acceleration episodes, which also suggests that inflation expectations are well contained. The most striking finding here is that policies improve for accelerating countries and are better than for countries that did not experience an acceleration of growth. The World Bank’s Country Policy and Institutional Assessment (CPIA), a broad measure of policy stance, shows a positive association with acceleration episodes in both decades.

There is a strong association between acceleration episodes and trade. Episodes are correlated with strong growth in the economies of a country’s trade partners, export growth, and a more competitive real exchange rate. Exports were also facilitated by real effective exchange rate (REER) depreciations, a result that is nearly as strong as when countries in the CFA franc zone are excluded, pointing to the importance of careful management of competitiveness regardless of the exchange rate regime.

Measures of political and economic liberalization have a robust correlation with accelerations; some plausibly function as measures of reforms that trigger growth, such as trade liberalization and leadership transitions. Broader indices of democracy are likely to capture the enabling environment. The composite measure of the autocracy-democracy mix (polity) captures an association between alignment toward democratic institutions and accelerations. Consistent with recent research, the 1990s evidence also indicates an expansionary role for a transition to new leadership after the departure of a longtime incumbent.18

Accelerations coincide with increases in investment and productivity improvements; both higher investment and TFP growth seem to be required for an acceleration to occur. The results support, in particular, an investment-productivity nexus operating for the more recent accelerations. The most important finding here is the role of TFP growth, which is statistically significant for both decades and of considerable economic magnitude for the 1990s.19

The growth of the net present value (NPV) of debt falls significantly for 1990s accelerations, pointing to the important role of debt concessionality in supporting surges in growth in the region.20 Whereas accelerating countries in the 1980s had increased debt-service ratios, the 1990s episodes saw reduced debt-service ratios, as well as reduced growth in the NPV of debt levels. Although countries that experienced growth accelerations also experienced a general rise in the NPV of debt-to-export ratios in the 1980s, they avoided that problem in the 1990s. Concessionality is important for these results, as the face value of debt-to-GDP ratios increases for accelerating countries.21 It is plausible that relaxed claims on current fiscal revenues through debt relief and greater debt concessionality have facilitated the investment increases associated with growth accelerations.

When the focus is further narrowed to accelerations sustained over 10 years, the key correlates are robust trade and investment, lower debt burdens, and more democratic institutions. Half of the accelerations analyzed above can be considered sustained over the medium term, because per capita annual growth rates over five years following an acceleration episode were also above 2 percent (see Table 4.2).22 Analysis of the 5- to 10-year growth rates reveals some disappointments, such as Kenya and Zimbabwe in the 1990s and Côte d’Ivoire more recently, but also accelerations that were sustained over the medium term in Uganda, Burkina Faso, and Ghana, among others. The methodology looks for statistically significant differences in averages for these sustained episodes compared with unsustained accelerations (Table 4.3). The key finding is a strengthened emphasis on favorable trade and debt alignment along with political institutions and investment as correlates of sustained growth. The analysis also shows that sustained accelerations are associated with increases in aid. In addition, aid combined with a good policy and institutional environment is shown to be a strongly significant correlate of the sustained accelerations.23

Table 4.3.Differences Between Sample Averages: Sustained and Unsustained Accelerations
Difference in Means
During an Episode
Openness7.3
Real export growth15.1
Debt service−5.8
NPV of debt/exports−0.9
Aid/GDP3.5
Polity index1.8
Investment/GDP3.1
Source: IMF staff calculations.Notes: All reported differences are significant at the 10 percent level. A sustained acceleration is one where the average per capita growth was at least 2 percent for five years after an acceleration ends. Mozambique in 1986 was excluded as a case of sustained acceleration because the period in question overlapped with its postconflict recovery.

The strong association between accelerations and trade is consistent with literature suggesting that a lack of openness to trade has substantially reduced Africa’s growth. Cross-country regressions indicate that Africa’s greater closure to international trade than the average developing country has cost the region 0.4–0.7 percentage points a year in growth. Indeed, being less open is more costly to Africa than to other developing countries.24 These findings are not surprising given the large body of empirical literature that shows that open economies grow faster than closed ones. While these econometric findings should be treated with caution as the debate on the interpretation of such results continues to evolve,25 research based on other methodologies also supports the view that trade openness promotes growth in Africa (see also Chapter V on regional trade arrangements).26 Firm-level analysis shows that exporting manufacturers have achieved higher TFP than their nonexporting counterparts. A case study of South Africa shows that trade liberalization has contributed significantly to growth through higher productivity.27 In general, African countries with lower average tariffs tend to have higher TFP growth (Figure 4.5), and more open economies have grown faster (see Figure 4.4).

Figure 4.5.Tariffs and Total Factor Productivity (TFP) Growth in Sub-Saharan Africa, 1997–2003

(Percent of GDP)

Source: IMF staff estimates.

The HIV/AIDS epidemic is jeopardizing the sustainability of growth in several SSA countries. Although some countries have undertaken bold steps to slow the epidemic and recent large increases in donor funds for prevention and treatment are encouraging, the HIV/AIDS epidemic is taking a serious toll on societies and economies in the region. Studies identify several channels through which HIV/AIDS affects economic growth. In addition to reducing the labor supply, which translates into lower output, increased mortality and morbidity lower private and public sector productivity and lower the efficiency of labor by eroding human capital; at the same time increased health expenditures tend to crowd out savings and reduce investment. For the worst-affected countries (those with HIV prevalence rates for the working-age population of over 20 percent), studies have projected that that the epidemic could reduce growth by 1 to 1.5 percentage points.28 These estimates omit an important concern of the business communities, namely that an uncertain and deteriorating outlook could deter domestic and foreign investment. In addition, in the longer term, HIV/AIDS could discourage individuals and companies from investing in human capital, given significantly lower expected returns. It is these risks to the outlook for investment and productivity (important for growth accelerations) that raise concerns about the sustainability of growth in some countries.

Poverty outcomes in countries experiencing sustained accelerations have been varied. Given the infrequency of household surveys and the lack of data on the share of the population living below national poverty lines in the 1980s, it is difficult to trace the evolution of poverty rates in many SSA countries. For the seven countries that experienced sustained accelerations, and for which some poverty data are available, poverty rates declined significantly during the 1990s in Ghana, Uganda, and (in the early 1990s) Seychelles.29 Burkina Faso and Benin report increases in poverty rates of less than 1 percent. In contrast, poverty rates increased significantly during the 1990s in Cape Verde and Lesotho.

Policies, Institutions, and Growth in SSA

Some additional examination is warranted of selected policies that the growth acceleration analysis could not probe deeply. Although many countries’ fiscal policies have improved, they still face major challenges in maintaining low deficits, reforming public expenditure management to improve the productivity and efficiency of spending, and designing institutions that reduce the procyclicality of fiscal policy, particularly if they are resource-intensive. Financial sector development has been identified as an important correlate of growth accelerations in the literature, but less is known about the link between financial development and growth in SSA. The scope of the discussion below is limited and selective: it explores the consistency of SSA data with some important predictions from the literature directly linking fiscal policy or financial development and growth. These areas, as well as institutions—which the growth acceleration analysis highlighted and recent literature suggests are fundamental for growth—are discussed.30 The coverage of policies is also selective: some of the most critical reforms now needed to improve SSA growth prospects are microeconomic or related to governance—that is, improving the quality of public services, particularly in health and education; improving the private sector business climate; and expanding and upgrading the quality of infrastructure.

Fiscal Policy

The literature suggests several propositions about the impact of fiscal policy on growth in low-income countries. First, recent papers have found that the channels through which fiscal policy affects growth in low-income countries are different from those in industrial countries, giving rise to a nonlinear effect of deficits on growth.31 One paper found a threshold of 2.5 percent of GDP (deficit including grants) at which further fiscal consolidation does not benefit growth.32 This threshold should be considered more of a range, as the relationships between deficits and growth will vary according to country specifics. Second, in general, fiscal consolidations that reduce reliance on domestic financing enhance growth.33 Third, the composition of fiscal spending affects growth. A higher share of spending on education and health benefits growth, but with a lag. However, this positive effect is reduced if governance is poor or macroeconomic policies are unsound.34

Recent data support the hypothesis of a threshold in the growth-deficit linkage in SSA. While causality runs in both directions, a simple way to highlight the deficit-growth channel is to relate lagged changes in deficits to growth and conduct a separate analysis of the link between the direction of changes in the deficit and growth, depending on whether the country is above or below a particular deficit threshold. While clearly not definitive, the simple calculations in Appendix Table A7 support a stronger association between growth and deficit reduction when the deficit is above the 2.5 percent threshold. For high-deficit countries, average growth is higher when the deficit is reduced, while low-deficit countries show much smaller growth improvements. The difference in growth rate changes in the two groups is statistically significant.

Since the early 1990s, SSA has seen an overall improvement in fiscal balances accompanied by a more prudent financing mix. Since the mid-1990s, growth has improved and deficits have declined. Since 2000, growth has moderated slightly whereas deficits show further improvement, allowing countries to reduce the burden on domestic financing sources. Oil producers switched to making net repayments to both domestic and foreign sources, but the trend of reduced use of domestic financing is more general. By 2004, on average, SSA governments were making net repayments to domestic sources (Appendix Table A8).

Since the mid-1980s, SSA countries have increased their outlays on education and health. Government spending on education and health has increased both as a ratio of GDP and as a share of total government spending (Figure 4.6).35 The only exception to this trend is oil-producing countries, where, beginning in the late 1980s, both measures of social sector spending have been declining. In addition, SSA data support the literature’s prediction that strong governance augments the effectiveness of social sector spending.36 SSA countries were ranked according to the quality of governance (World Bank CPIA data, average over the 1990s), level of social sector spending, and education and health outcomes (net enrollment in primary schools and under-five child mortality in 2000).37 All seven countries that ranked in the top third of the distribution on both governance and education spending also ranked in the top third on education outcomes. Five of the eight countries that ranked in the top third on governance and health spending also ranked in the top third on health outcomes. In contrast, top outcome rankings were relatively few for countries ranking in the top third on only one of the governance or spending indicators. While these trends are encouraging, modest declines in capital expenditure ratios from the 1980s are cause for concern. Further analysis of the quality and type of projects and the efficiency of capital expenditures would be useful.

Figure 4.6.Sub-Saharan Africa: Government Spending on Education and Health

(Percent of total spending; averages)

Source: IMF, WEO/Economic Trends in Africa database, 2004.

Financial Development

The economies in SSA with the best-developed financial sectors have experienced a higher per capita growth rate than the average, and the differential has widened since the financial liberalization of the 1990s. However, the development of financial markets, as measured by the ratio of liquid liabilities to GDP, has been slow and uneven.38 Differences in growth are wider if the oil producers, which experienced high growth but remained financially underdeveloped, are excluded. The weak financial development-growth link in the oil producers may help explain indications from the literature of a somewhat weaker relation between growth and financial development in Africa. Excluding oil producers, the economies that grew fastest over 1960–2003 also are those that are the most financially developed (Figure 4.7).

Figure 4.7.Financial Development of Sub-Saharan African Countries Classified by Growth

(Percent)

Source: WEO, 2004.

Note: The six oil-producing countries are classified separately. The remaining countries are classified by quartiles, according to real growth over 1960–2003.

For financial development to stimulate growth, the policy environment must be favorable. In the early 1990s, the persistence of fiscal imbalances, which tend to crowd out credit flows to the private sector, may have weakened the effects of financial liberalization for some African countries.39 Substantial government ownership and interference in the banking sector may reduce the quality of banks’ decisions, lowering investment efficiency and growth. A crude segmentation of African countries into four categories depending on financial sector development and growth suggests that the growth-promoting effects of financial sector development may materialize only in conditions of macroeconomic stability (Appendix Table A9). Among the countries with relatively strong financial development indicators, those that grew faster achieved greater macroeconomic stability; that is, they had much lower budget deficits, including grants and lower inflation. This supportive effect of macroeconomic stability for the financial development-growth nexus was even stronger during 1997–2003.

Institutions

Recent evidence in the literature suggests that institutions are the most important determinant of long-run growth. However, improving basic institutions—the laws, rules, and other practices that govern property rights; the freedom to do business; and the sanctity of contracts—can take a long time. In fact, as causation operates in both directions, spurring large improvements in basic institutions may be difficult without sustained growth.40 Policies also seem to play a role in fostering institutional development—for example, strengthening competition through trade openness, expanding the public’s access to information, increasing transparency, providing assistance in building institutional capacity, and creating external incentives, such as the peer pressure mechanisms to be used in the New Partnership for Africa’s Development (NEPAD).41

The overall quality of both economic and political institutions in SSA has been improving.42 Fast-growing countries generally had better-quality institutions than slow-growing countries. Also, fast- and medium-growing countries have had more improvement in institutional quality than slow-growing countries (Figure 4.8). These observations have been confirmed by recent objective measures of countries’ economic institutions. In fast-growing countries, starting a business, registering property, enforcing contracts, and closing a business are less costly; urban and rural land property rights for investors and for the poor are more secure, and there are fewer land-related conflicts (Figure 4.9).43

Figure 4.8.Evolution of Economic and Political Institutions in Sub-Saharan Africa

Source: The PRS Group, International Country Risk Guide (ICRG).

Note: Fast, medium, and slow growers refer to 1960–2003 period.

Figure 4.9.Objective Measures of Economic Institutions in Sub-Saharan Africa, 2004

Sources: World Bank (1994); Diankov (2003); Diankov and others (2002); and World Bank database (2004).

The quality of economic institutions is correlated with the quality of political institutions, as well as with geographical and other factors. Recent evidence shows that the quality of political institutions and the degree of political stability influence economic institutions, which, in turn, affect economic performance.44 Measures of the economic and political institutions in SSA tend to be strongly correlated; for example, there is a 30–50 percent difference in the index of security of property rights between countries in SSA that have political freedom and those that do not, as measured by Freedom House.45 Also, on average, institutions in SSA tend to be strongest in coastal countries, followed by resource-rich countries, and then landlocked countries.46 Institutions also tend to be weaker in oil-producing countries, in members of the CFA franc zone, and in conflict countries. Finally, institutional improvement is stronger in countries with on-track IMF programs than it is in both nonprogram countries and countries with off-track programs. While causality is difficult to determine, a recent paper finds that strong institutions improve IMF program implementation.47

Conclusions

Improvements in macroeconomic policies contributed strongly to the recovery of the fastest-growing economies of the 1990s, and these improvements were strongest for countries with on-track IMF-supported programs. More favorable terms of trade also aided the stronger growth performance. However, different aspects of the growth recovery give mixed signals about its sustainability. While total investment has not increased significantly for the fast-growing economies (excluding Equatorial Guinea), TFP growth has improved strongly for the first time since the 1960s. Clearly, the most challenging and difficult question facing SSA is how to generate large sustained accelerations in growth rates. A preliminary analysis suggests that accelerations are spurred by strong trade growth and by trade and political liberalizations and are also accompanied by increases in investment and TFP growth. Improved TFP growth, particularly pronounced in countries with on-track IMF programs, likely reflected efficiency gains stemming from the implementation of macro-economic and structural reforms. Countries that have experienced jumps in their growth rates have registered improvements in broad measures of their policy positions. In the 1990s (in contrast to the 1980s), debt indicators did not deteriorate during accelerations. Encouragingly, a fair number of these countries succeeded in sustaining the acceleration for 10 years. They had stronger trade and investment, lower debt burdens and higher aid, and more democratic institutions than countries that did not sustain their accelerations.

Some aspects of fiscal policy are moving in the right direction, but more progress is needed in this area and on trade and the financial sector to promote growth. Reliance on domestic financing of fiscal deficits is declining, and the composition of spending is generally moving in favor of social sectors. Progress on financial development in the region has been fragile and uneven. On trade, bold reforms are required to contribute to the overall growth strategy for Africa. Consistent with recent evidence in the literature, fast-growing countries in SSA generally have better basic institutions than slow-growing countries, and political institutions are correlated with better economic institutions.

Addressing the constraint on growth from low levels of investment is a key priority for SSA. The very limited investment response to reforms in the region is a concern, particularly as increases in investment appear to be necessary for sustained growth accelerations. The World Bank’s 2005World Development Report concluded that reducing the costs of doing business (from weak contract enforcement, inadequate infrastructure, crime, corruption, and regulation) and lowering policy-related risks and barriers to competition were key to improving the investment climate in developing countries. These obstacles are central for SSA, where 16 of the top 20 countries in the world with the most difficult business conditions are located.48 There is also a role for well-targeted and efficient public investment that can crowd in private investment and productivity improvements. In addition to promoting domestic savings, higher aid inflows—consistent with absorptive capacity—and lower debt burdens are important for supporting higher and more efficient investment rates.

To make further progress in improving growth, SSA must implement additional reforms. The record shows that reasonable jumps in growth rates that are sustained for 10 years are possible. Growth accelerations in these countries need to be sustained further and spread to other countries in the region. However, even countries that have sustained a 10-year growth acceleration need to do more, because substantially higher per capita growth rates are needed to make big strides in reducing poverty in these countries.49

See also Pattillo and others (2005, forthcoming).

Extensions of the standard growth model have largely eliminated the “Africa dummy” in cross-country growth regressions. Sachs and Warner (1997); Easterly and Levine (1997); Hoeffler (2002).

Collier and O’Connell (2004) suggest that a key factor accounting for Africa’s increasing divergence from growth experiences in the rest of the developing world since 1980 is the underperformance of Africa’s coastal resource-scarce economies relative to similar countries in other regions. See also O’Connell (2004).

Unweighted averages of the 42 SSA countries covered in the Statistical Appendix.

Tahari and others (2004), Bosworth and Collins (2003). The following sections use TFP data kindly provided by Tahari and others.

Country-level growth-accounting studies conducted in the IMF’s African Department support these findings (for example, Republic of Congo: Ghura, 2004; Kenya: Cheng, 2004; Swaziland: Erasmus and Ricci, 2002; WAEMU countries: Wane, 2004). Nsengiyumva (2004) on Benin and Bagattini (2004) on Zambia find that structural reforms and an increased role for the private sector contributed to improvements in TFP in recent periods. Sectoral-level growth-accounting studies have also shed light on sector-specific growth constraints (Democratic Republic of Congo: Akitoby and Cinyabuguma, 2005; South Africa: Arora, Bhundia, and Bagattini, 2002). See Calamitsis, Basu, and Ghura (1999) for an analysis of factors affecting growth using an SSA-specific cross-country growth model.

The top third of the distribution includes 14 countries. Of these, 1 is an oil producer, 4 are CFA franc countries, and 9 have an IMF-supported program. On the natural resources/location classification, 2 are resource-intensive, 6 are coastal and resource-scarce, and 6 are landlocked and resource-scarce countries.

The average figures exclude the instances of hyperinflation in Angola for the fast growers and in the Democratic Republic of Congo for the slow growers.

This trend is robust to the exclusion of Equatorial Guinea.

For 1990–2003, a program country is designated as “off track” if half or more of its programs in a given five-year period experienced an irreversible interruption; that is, the program was either canceled or allowed to lapse because of policy slippages. Data from Nsouli, Atoian, and Mourmouras (2004) (see for more details on index derivations) were extended to cover all SSA program countries.

Higher TFP growth in countries with on-track programs may reflect better implementation of macroeconomic and structural policies. However, the causality between IMF program implementation and growth is difficult to ascertain (see Nsouli, Atoian, and Mourmouras, 2004). It is also possible that countries that experience higher growth because of external factors are better able to implement IMF programs.

Equatorial Guinea is excluded, and results would be even stronger had it been included. Note also that results are somewhat different depending on whether changes are measured relative to the early 1980s, late 1980s, or early 1990s.

World Bank and IMF (2004).

Of the 28 countries experiencing growth accelerations (6 countries had two accelerations each), 4 are oil producers, 7 are CFA franc countries, 8 are resource-intensive, 11 are coastal and resource-scarce, and 9 are landlocked and resource-scarce countries. There is no statistically significant association between accelerations and a country’s status as an oil producer or as resource-intensive. For the 15 acceleration episodes in the 1980s, 8 of the countries had IMF-supported programs, and 15 of the 19 accelerating countries of the 1990s had programs.

Bivariate correlations are a useful first step in the analysis. Pattillo and others (2005, forthcoming) also estimate probit models for growth accelerations, and the results are broadly consistent with the bivariate analysis.

Accelerations are also associated with higher private investment, although the 1990s results are not significant when Equatorial Guinea is excluded.

This is consistent with recent evidence that above certain thresholds, external debt has a negative effect on growth (Pattillo, Poirson, and Ricci, 2002; Clements, Bhattacharya, and Nguyen, 2004).

Starting from the late 1980s, the terms of new lending and debt relief have become increasingly concessional, which explains why nominal debt-to-GDP ratios increase for accelerating countries while NPV debt indicators fall.

Because this selection requires a 10-year window, only sustained accelerations up to 1994 can be identified.

The variable is aid as a percent of GDP interacted with the value of the CPIA for countries in the top quartile of CPIA rankings. This result is merely suggestive, and would need to be tested in a probit model that controlled for endogeneity. In the growth literature, critics have questioned the Burnside and Dollar (2000) finding that aid has a positive effect on growth in good policy environments (Easterly, Levine, and Roodman, 2004).

Based on Sachs and Warner (1997) and Easterly and Levine (1997). Block (2001) offers some evidence on the greater marginal impact of trade openness in Africa.

See Dollar (1992); Edwards (1992); Sachs and Warner (1995); and Frankel and Romer (1999). See Rodrik and Rodríguez (2001) for a critique of cross-country regression-growth analysis.

Several IMF African Department studies support the trade-growth linkage (Calamitsis, Basu, and Ghura, 1999) or the hindering effect of restricted trade regimes on trade (Sharer, 1999; Subramanian and Tamirisa, 2001; Lane, 2002; Lukonga, 2000).

Mengistae and Pattillo (2004) report a TFP premium of 11–28 percent for exporting firms, based on data from Ethiopia, Ghana, and Kenya. Bigsten and others (2004) also find efficiency premiums for African manufacturing exporters, attributable to learning by doing. See Jonsson and Subramanian (2000) on South Africa.

See Haacker (2004), which draws on Joint United Nations Programme on HIV/AIDS studies. Note that data limitations prevent the formal consideration of the role of HIV/AIDS in the growth acceleration analysis.

The percentage of households living below the poverty line in Seychelles fell to 19 percent from 30 percent between 1984 and 1992 (World Bank, 1994). This is a slightly different measure than that considered for other countries, that is, percentage of the population living below the poverty line. Inferences are based on poverty data from the World Bank’s World Development Indicators and on country PRSP documents.

Financial sector development and governance are key issues for SSA. Forthcoming issues of the African Regional Economic Outlook will examine them in more detail.

Gupta and others (2004). Adam and Bevan (2003), using a smaller sample, including 11 African countries, estimated a threshold of 1.5 percent of GDP.

Gupta and others (2004).

One should expect a significant time lag between increases in the scaling up of aid for social expenditures and their full effects on social indicators and growth. Baldacci and others (2004) find the highest positive effects of social expenditures in SSA, because marginal returns are high given lower levels of social outlays.

See also Gupta, Davoodi, and Tiongson (2002) on the negative effect of corruption on social indicators.

Qualitatively, similar findings hold using International Country Risk Guide (ICRG) or Kaufman, Kraay, and Zoido-Lobaton (1999) governance data.

Since the 1990s, banking reforms have evolved: countries have eliminated harmful government interventions; addressed weak or distressed banks through restructuring, privatization, and strengthened regulation; reduced crowding out through fiscal adjustments; and adapted the regulatory environment to allow broader access to credit. Further reform in the last area remains a priority: addressing the key legal, regulatory, and institutional bottlenecks to access to banking services and credit, particularly for underserved groups.

It is interesting to note, however, that of the very few countries that seem to have improved their institutions significantly before achieving high growth, two of these—Botswana and Mauritius—are in SSA.

For SSA as a whole, while the improvement in political institutions continued throughout the 1990s, the strengthening of economic institutions plateaued in the late 1990s (Johnson and Subramanian, 2005).

Zimbabwe is a prime example of a country where, in addition to political and economic policy problems, insecure land tenure and land-related conflicts have contributed to a severe downward spiral of growth.

However, Johnson and Subramanian (2005) show limited correlation among SSA’s political and economic institutions in the long run. Bates (2005) also suggests that democratization in SSA in the 1990s may have made countries more prone to destabilizing political business cycles, because of, in part, the limited availability of information that citizens need in order to hold governments accountable.

Different types of institutions might be particularly important for growth in different types of economies. For example, low corruption levels are critical for resource-intensive countries. Institutions that lower the cost of doing business, particularly for exporting manufacturers, are important for coastal countries, and weak rural property rights may be the key constraint for landlocked countries. These issues warrant further investigation.

Using data from a broad sample of IMF-supported programs, Nsouli, Atoian, and Mourmouras (2004) find that strong institutions lead to better program implementation. The paper shows that program implementation also exerts an independent effect on macroeconomic outcomes, but not on growth.

World Bank (2004b and 2005, forthcoming).

Countries with sustained accelerations have average annual per capita growth rates of at least 2 percent over 10 years. Estimates suggest much higher rates are needed for SSA to have a reasonable prospect of halving income poverty by 2015.

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