Africa’s Growth Turnaround: From Fewer Mistakes to ... · Africa’s Growth Turnaround: From Fewer Mistakes to Sustained Growth iii . About the Series The Commission on Growth and

Africa’s Growth Turnaround:From Fewer Mistakesto Sustained Growth

John Page

WORKING PAPER NO.54

www.growthcommission.org

[email protected]

Commission on Growth and Development Montek AhluwaliaEdmar BachaDr. BoedionoLord John Browne Kemal DervişAlejandro FoxleyGoh Chok TongHan Duck-sooDanuta HübnerCarin JämtinPedro-Pablo KuczynskiDanny Leipziger, Vice ChairTrevor ManuelMahmoud MohieldinNgozi N. Okonjo-IwealaRobert RubinRobert SolowMichael Spence, ChairSir K. Dwight VennerHiroshi WatanabeErnesto ZedilloZhou Xiaochuan

The mandate of the Commission on Growth and Development is to gather the best understanding there is about the policies and strategies that underlie rapid economic growth and poverty reduction.

The Commission’s audience is the leaders of developing countries. The Commission is supported by the governments of Australia, Sweden, the Netherlands, and United Kingdom, The William and Flora Hewlett Foundation, and The World Bank Group.

A fter stagnating for much of its postcolonial history, economic performance in Sub-Saharan Africa has markedly improved. Since 1995, average economic growth has been close to 5 percent per year. Has Africa fi nally turned the corner? This paper analyzes growth accelerations and decelerations—that is, country-level deviations from long-run trend growth. Seen from this perspective, Africa’s record of slow and volatile growth refl ects a pattern of offsetting accelerations and declines, and much of the improvement in economic performance in Africa post 1995 turns out to be due to a substantial reduction in the frequency and severity of growth decelerations. The fall in economic declines since 1995 is largely due to better macroeconomic policies, but changes in such “growth determinants” as investment, export diversifi cation, and productivity have not accompanied the growth boom. Lack of change in these variables—and the signifi cant role played by natural resources in sparking growth accelerations—suggest that Africa’s growth recovery was fragile, even before the recent global economic crisis. The paper concludes by setting out four elements of a strategy that can help move Africa from fewer mistakes to sustained growth: managing natural resources better, pushing nontraditional exports, building the African private sector, and creating new skills.

John Page, Senior Fellow, The Brookings Institution

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wb350881Typewritten Text57753

WORKING PAPER NO. 54

Africa’s Growth Turnaround: From Fewer Mistakes to Sustained Growth

John Page

© 2009 The International Bank for Reconstruction and Development / The World Bank On behalf of the Commission on Growth and Development 1818 H Street NW Washington, DC 20433 Telephone: 202‐473‐1000 Internet: www.worldbank.org www.growthcommission.org E‐mail: [email protected] [email protected] All rights reserved 1 2 3 4 5 11 10 09 08 This working paper is a product of the Commission on Growth and Development, which is sponsored by the following organizations: Australian Agency for International Development (AusAID) Dutch Ministry of Foreign Affairs Swedish International Development Cooperation Agency (SIDA) U.K. Department of International Development (DFID) The William and Flora Hewlett Foundation The World Bank Group The findings, interpretations, and conclusions expressed herein do not necessarily reflect the views of the sponsoring organizations or the governments they represent. The sponsoring organizations do not guarantee the accuracy of the data included in this work. The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgment on the part of the sponsoring organizations concerning the legal status of any territory or the endorsement or acceptance of such boundaries. All queries on rights and licenses, including subsidiary rights, should be addressed to the Office of the Publisher, The World Bank, 1818 H Street NW, Washington, DC 20433, USA; fax: 202‐522‐2422; e‐mail: [email protected]. Cover design: Naylor Design

Africa’s Growth Turnaround: From Fewer Mistakes to Sustained Growth iii

About the Series

The Commission on Growth and Development led by Nobel Laureate Mike Spence was established in April 2006 as a response to two insights. First, poverty cannot be reduced in isolation from economic growth—an observation that has been overlooked in the thinking and strategies of many practitioners. Second, there is growing awareness that knowledge about economic growth is much less definitive than commonly thought. Consequently, the Commission’s mandate is to “take stock of the state of theoretical and empirical knowledge on economic growth with a view to drawing implications for policy for the current and next generation of policy makers.”

To help explore the state of knowledge, the Commission invited leading academics and policy makers from developing and industrialized countries to explore and discuss economic issues it thought relevant for growth and development, including controversial ideas. Thematic papers assessed knowledge and highlighted ongoing debates in areas such as monetary and fiscal policies, climate change, and equity and growth. Additionally, 25 country case studies were commissioned to explore the dynamics of growth and change in the context of specific countries.

Working papers in this series were presented and reviewed at Commission workshops, which were held in 2007–08 in Washington, D.C., New York City, and New Haven, Connecticut. Each paper benefited from comments by workshop participants, including academics, policy makers, development practitioners, representatives of bilateral and multilateral institutions, and Commission members.

The working papers, and all thematic papers and case studies written as contributions to the work of the Commission, were made possible by support from the Australian Agency for International Development (AusAID), the Dutch Ministry of Foreign Affairs, the Swedish International Development Cooperation Agency (SIDA), the U.K. Department of International Development (DFID), the William and Flora Hewlett Foundation, and the World Bank Group.

The working paper series was produced under the general guidance of Mike Spence and Danny Leipziger, Chair and Vice Chair of the Commission, and the Commission’s Secretariat, which is based in the Poverty Reduction and Economic Management Network of the World Bank. Papers in this series represent the independent view of the authors.

iv John Page

Acknowledgments

This paper draws on recent work with colleagues Jorge Arbache and Delfin Go to understand the improvement in Africa’s economic performance. Their intellectual contributions are gratefully acknowledged. They are absolved of any responsibility for the policy conclusions, which are wholly my own.

Africa’s Growth Turnaround: From Fewer Mistakes to Sustained Growth v

Abstract

After stagnating for much of its postcolonial history, economic performance in Sub‐Saharan Africa has markedly improved. Since 1995, average economic growth has been close to 5 percent per year. Has Africa finally turned the corner? This paper analyzes growth accelerations and decelerations—that is, country‐level deviations from long‐run trend growth. Seen from this perspective, Africa’s record of slow and volatile growth reflects a pattern of offsetting accelerations and declines, and much of the improvement in economic performance in Africa post 1995 turns out to be due to a substantial reduction in the frequency and severity of growth decelerations. The fall in economic declines since 1995 is largely due to better macroeconomic policies, but changes in such “growth determinants” as investment, export diversification, and productivity have not accompanied the growth boom. Lack of change in these variables—and the significant role played by natural resources in sparking growth accelerations—suggest that Africa’s growth recovery was fragile, even before the recent global economic crisis. The paper concludes by setting out four elements of a strategy that can help move Africa from fewer mistakes to sustained growth: managing natural resources better, pushing nontraditional exports, building the African private sector, and creating new skills.

Africa’s Growth Turnaround: From Fewer Mistakes to Sustained Growth vii

Contents

About the Series ............................................................................................................. iii Acknowledgments ..........................................................................................................iv Abstract .............................................................................................................................v I. Introduction...................................................................................................................1 II. Africa’s Growth 1975–2005 ........................................................................................3 III. Good Policy or Good Luck?....................................................................................10 IV. Is Growth Sustainable? ...........................................................................................17 V. Toward a Strategy for Sustained Growth. .............................................................20 VI. Conclusions...............................................................................................................39 Annex...............................................................................................................................40 References .......................................................................................................................42

Africa’s Growth Turnaround: From Fewer Mistakes to Sustained Growth 1

Africa’s Growth Turnaround: From Fewer Mistakes to Sustained Growth John Page 1

I. Introduction

After stagnating for much of its postcolonial history, economic performance in Sub‐Saharan Africa (Africa) has markedly improved. Since 1994, average economic growth has been close to 5 percent per year. Countries with at least 4 percent GDP growth now constitute about 70 percent of the region’s total population and 80 percent of its GDP. As a group, these countries have been growing consistently at nearly 7 percent a year since the mid‐1990s. The number of countries in economic decline has fallen from 15–18 in the early 1990s to 2–5 in recent years, and only one economy—Zimbabwe—has experienced a significant economic collapse since 2000. Per capita income grew by 1.6 percent a year in the late 1990s and by 2 to 3 percent in each year since 2000. Average incomes in Africa have been rising in tandem with the rest of the world, and Africa’s top performers are doing well compared with fast‐growing countries in other regions.

Has Africa finally turned the corner? Predictions of Africa’s imminent economic recovery or demise have proved wrong on numerous occasions in the past 40 years. This essay summarizes recent work with several colleagues to try to understand the improvement in Africa’s economic performance.2 Section II looks at Africa’s long‐run growth from 1975 to 2005 and addresses two questions: what characterizes the pattern of long‐run growth in Africa and what has caused the recent growth acceleration? Most attempts to explain Africa’s growth performance have focused on investigating the determinants of growth over time and across countries using cross‐country models and comparative case studies (Collier and Gunning 1999; O’Connell and Ndulu 2000; Ndulu et al. 2007). We approach our growth diagnostics from a somewhat different perspective.

1 John Page is a Distinguished Visiting Fellow in the Global Economy and Development Program at the Brookings Institution in Washington, DC. He is also a nonresident Senior Fellow of the Global Development Network and an advisor to the African Development Bank. 2 This work is reported in Arbache and Page, 2007, 2008, 2009; Arbache, Go, and Page, 2008; and Go and Page, 2008.

2 John Page

Africa’s growth over the past three decades has not only been low; it has been highly volatile (see for example Ndulu et al., 2007; Arbache, Go, and Page 2008; Raddatz, 2008). For this reason instead of looking for “determinants” of long‐term growth, we identify medium‐term deviations from its long‐run trend—growth accelerations and decelerations—at the country level. Using this approach, we find that African countries have experienced numerous episodes of accelerated growth in the past 30 years, but also a comparable number of growth declines.

In short, Africa’s long‐run record of slow and volatile growth reflects a pattern of offsetting accelerations and declines, rather than random variations of growth rates around the long‐run trend. From this perspective much of the improvement in economic performance in Africa post‐1995 is attributable to African economies avoiding bad economic times. The region’s recent growth boom turns out to be due to a substantial reduction in the frequency and severity of growth decelerations, combined with an increase in the frequency and country coverage of growth accelerations.

While avoiding bad times is an important achievement in itself, it raises some questions concerning the origins of Africa’s growth recovery. Since this paper was written in the winter of 2008, the global economy has suffered a major recession. The abrupt decline in economic activity in the OECD and in Asia has resulted in rapidly falling commodity prices and exports. Projections of growth for 2009 and beyond for the region are substantially lower. From the perspective of understanding how the continent may react to the global downturn a key question is: was the reduction in economic declines between 1995 and 2008 largely the outcome of a benign global environment, of better economic management, or both?

Section III addresses the question: good policy or good luck? Our assessment of recent commodity price trends indicates that while until the recent downturn the terms of trade have been favorable on average for Africa since 1995, they have not been uniformly favorable for all African countries. To address the public policy questions posed by our results, we look for correlates associated with acceleration and deceleration episodes and examine the probability that an economy will undergo a growth acceleration or deceleration. We conclude that the reduction in economic declines since 1995 is due both to better policies and some luck. In the post 2008 crisis better policies will provide some cushion to the external shock but they cannot prevent transmission of the global recession to Africa.

One of the most striking results of the analysis of Section III is that the policies and institutions needed to avoid bad economic times are much better understood than those needed to achieve growth accelerations. Since sustained growth after 2005 will depend more on achieving and sustaining growth accelerations at the country level than avoiding mistakes, Section IV draws on the more traditional growth literature to examine differences in “growth fundamentals”—savings, investment, and productivity change—between 1995–2005 and the preceding decade. It also looks at these variables in international


perspective. Although there has been some improvement in economic fundamentals since 1995, it is not large enough—particularly in comparison with levels found in rapidly growing economies—to support complacency with respect to the durability of Africa’s growth recovery.

Section V sets out four elements of a strategy that would move Africa from its current recovery to sustained growth: managing natural resource rents well, pushing nontraditional exports, building the African private sector, and creating new skills. These elements are drawn from the empirical results of the paper and the experience of successfully growing economies in Africa and elsewhere.

II. Africa’s Growth 1975–2005

This section presents a perspective on long‐run growth in Africa based on a series of studies conducted by Arbache and Page (2007, 2008, 2009). We use the most recent time‐series of purchasing power parity (PPP) income data for 45 African countries from 1975 to 2005.3 This period follows the first oil shock and includes the commodity prices plunge, the introduction of structural reforms, and the recent growth recovery. Because from a public policy perspective we want to focus on the representative country, we mainly use unweighted country data and report regional or subregional averages.4

Between 1975 and 2005 mean per capita income in Africa grew slowly. Trend growth declined until the late 1980s (table 1) and then increased substantially during 1995–2005. The per capita growth rate rose from −0.23 percent in 1985–94 to 1.88 percent during 1995–2005. Statistical analysis suggests that a structural break occurred in the time series of per capita income growth as growth picked up in the mid‐1990s.5

Income growth was highly volatile, especially in comparison with other developing regions (figures 1 and 2), but the post 1995 growth acceleration was accompanied by a sharp reduction in growth volatility. The absolute value of the coefficient of variation fell from 90.4 percent in 1975–94 to 3.2 percent in after 1995. Interestingly, however, there is no statistical evidence that growth volatility per se was associated with Africa’s poor long‐term economic performance (Arbache and Page 2008b).

3 Data on per capita income (PPP at 2000 international prices) and its growth rate are taken from the World Bank’s World Development Indicators (WDI) (various years) unless otherwise specified. The WDI’s GDP per capita PPP series starts in 1975. The sample includes all Sub‐Saharan countries except Liberia and Somalia, for which there are no data. Thus, there is an unbalanced panel of data with T = 31 and N = 45. 4 This contrasts with Collier’s contribution in this working paper series which uses population weighted aggregates to focus on the welfare of the representative African. 5 Recursive residual estimations, Chow breakpoint tests, and Chow forecast tests indicate that a structural break in the growth series occurred between 1995 and 1997 (Arbache and Page 2008).

4 John Page

Table 1: Per Capita Income, Mean Growth, and Variation for Different Periods in Africa

Growth rate

Period Mean Standarddeviation

Coefficient of variation GDP per capita

1975–2005 0.70 6.27 8.96 2,299 1975–84 0.13 6.92 53.23 2,180 1985–94 −0.23 5.87 −25.52 2,183

1995–2005 1.88 5.99 3.19 2,486 1975–94 −0.07 6.33 −90.43 2,182

(1995–2005) minus (1985–94) 2.11 0.12 28.71 303 (1995–2005) minus (1975–94) 1.95 -0.34 93.61 304 Source: Arbache and Page (2007).

Figure 1: Per Capita Income

–8–4048

–4

0

4

8

1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004

Growth Trend Cycle Source: Arbache and Page (2007a). Notes: Right axis = per capita income; left axis= cycle of p.c. income.

Figure 2: Growth Rate of Per Capita Income

–100

0

1002,000

2,400

2,800

1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004

GDP per capita Trend Cycle Source: Arbache and Page (2007). Notes: Right axis = growth of p.c. income; left axis = cycle of growth rate.


Identifying Good Times and Bad To investigate the impact of growth volatility on economic performance we identify growth accelerations (good times) and decelerations (bad times) using a variation of the methodology developed by Hausmann, Pritchett, and Rodrik (2005). Our approach differs from theirs and that of researchers applying their method to Africa (IMF, 2007) in two important respects. First, it identifies both growth accelerations and decelerations in countries. Second, it does not use a common threshold growth rate to identify growth accelerations. Instead, it defines good and bad times relative to each country’s long‐run economic performance. In Africa’s volatile, low‐growth environment this seems appropriate.

To identify a growth acceleration we require that the following three conditions are met in each of at least three consecutive years:

Condition 1—The forward four‐year moving average growth rate minus the backward four‐year moving average growth rate exceeds 0;6

Condition 2—The forward four‐year moving average growth rate exceeds the country’s average growth rate, meaning that the pace of growth during acceleration is higher than the country’s trend;

Condition 3—The forward four‐year moving average GDP per capita exceeds the backward four‐year moving average.

A sign change from (+) to (–) in Condition 1 suggests a growth trend shift. A deceleration episode occurs when in three consecutive years: the forward three‐year moving average growth rate minus the backward three‐year moving average growth rate is less than zero (Condition 1); the forward three‐year moving average growth rate is below the country’s average growth rate (Condition 2); and the forward three‐year moving average GDP per capita is below the backward three‐year moving average (Condition 3). A growth acceleration or deceleration episode is defined to include the three years following the last year that satisfies conditions 1–3.7

Condition 2 makes our definition of a growth acceleration or deceleration endogenous to each country’s long‐run rate of growth. There is clearly a risk that by identifying a period of modest, sustained growth in a low‐growth economy as a growth acceleration we will assign too much significance to a minor change in economic performance. But it is also true that a period of relatively modest per capita growth may signal an important economic change in a country with very low growth rates, and a decline in per capita income of equal magnitude could

6 This requires the forward moving average window (t, t+1, t+2, t+3) to be higher than the backward window (t, t‐1, t‐2, t‐3) and above 0. 7 As an example, if conditions 1 to 3 identify a growth acceleration during, say, 1991 to 1995, the years 1996, 1997, and 1998 are included as part of the episode. The growth acceleration episode comprises a period that starts in 1991 and ends in 1998.

6 John Page

spell a serious economic collapse in a stagnant economy.8 Condition 3 ensures that the growth acceleration episode is not a recovery from a recession.

Table 2 shows the relative frequency of accelerations and decelerations, and their respective growth rates, for different periods. Between 1975 and 2005, there was a slightly higher probability that the representative African economy was in a growth acceleration than a deceleration: 25 percent of the 1,243 total country‐year observations (per country per year) identify countries experiencing growth accelerations, while 22 percent identify countries experiencing growth decelerations.9 The remaining country‐year observations reflect normal economic times with countries growing at about their trend growth rate.

The frequency of good and bad times over the past three decades is reflected in Africa’s long–run pattern of growth. Growth declines dominated the period 1975–1994: between 1975 and 1994 growth decelerations were more than twice as frequent as accelerations. In contrast 42 percent of the 494 country–year observations for 1995–2005 were growth accelerations and only 12 percent were growth decelerations. Since 1995 long‐stagnant economies, such as the Central African Republic, Ethiopia, Mali, Mozambique, Sierra Leone, and Tanzania, have shown sustained growth, relative to their long‐run trend. Table 2: Likelihood and Growth Rates of Economic Acceleration and Deceleration in Africa, 1975–2005

All ctry years in the period

Ctry years with growth acceleration

Ctry years with growth deceleration

Ctry years with trend

growth

Period

Obs (country-

years) Growth

rate

Freq (of ctry years)

Growth rate

Freq (of ctry-years)

Growth rate

Frequency (of ctry-years)

1995–2005 (after trend break) 494 1.88 0.42 3.76 0.12 –1.29 0.46 1975–94 (before trend break) 749 –0.07 0.14 3.39 0.29 –3.14 0.57 1985–94 433 –0.23 0.21 3.21 0.36 –3.18 0.43 1975–84 316 0.13 0.04 4.61 0.18 –3.06 0.78 1975–2005 (All years) 1,243 0.7 0.25 3.64 0.22 –2.74 0.53 Source: Arbache and Page (2007). Notes: Ctry: country; Freq: frequency; obs: observation.

8 Condition 2 also helps to limit the number of identified accelerations in countries with sustained, long‐run growth. If a country is growing rapidly it will lift the growth trend, reducing the number of estimated accelerations. This is particularly significant for countries experiencing very low or very high growth rates. 9 As a means of checking the robustness of the results, growth accelerations and decelerations were also identified by replacing 0 with +1 percent and −1 percent for acceleration and deceleration, respectively, in condition 1, but the results did not change substantially. Therefore, only the base‐case results are reported, because they are less restrictive.


Seven countries—the Democratic Republic of Congo, Eritrea, Gabon, The Gambia, Madagascar, Mauritania, and Niger—have never had a growth acceleration. Of those seven, only Eritrea shows good long‐term per capita income growth. Four of the seven had long‐run declines in per capita income. Sixteen countries have avoided growth decelerations altogether. Many—Botswana, Cape Verde, Equatorial Guinea, Lesotho, Mauritius, Mozambique, and Uganda—are among the region’s top performers in per capita income growth over the past three decades, but not all. Burkina Faso, Guinea, Namibia, São Tomé and Príncipe, and Swaziland are not among the region’s growth leaders.

Richer countries had more growth accelerations, and poorer countries experienced more growth declines. This result is, of course, to some extent endogenous; average income per capita will tend to rise in countries with more frequent growth accelerations and fall in countries with more frequent declines. But the result also holds in each 10‐year period, where the compounding effects may be assumed to be less important, perhaps indicating that richer countries can take better advantage of circumstances favorable to accelerated growth.

Table 3 shows the frequency of growth acceleration and deceleration episodes for several types of countries. In general, there is not much difference in the probabilities of growth acceleration and deceleration episodes for different geographical locations. Table 3: Frequency of Growth Acceleration and Deceleration by Country Category

Growth acceleration Growth deceleration

Country category

Frequency (country-

years) Above/below all countries’ mean

Frequency (country-

years) Above/below all countries’ mean

All countries’ mean 0.25 — 0.22 — Coastal 0.26 Above 0.22 Equal Landlocked 0.23 Below 0.22 Equal Coastal without resources 0.24 Below 0.23 Above Landlocked without resources 0.22 Below 0.22 Equal Oil exporters 0.29 Above 0.23 Above Nonoil exporters 0.24 Below 0.22 Equal Resource-rich 0.30 Above 0.21 Below Non-resource-rich 0.23 Below 0.23 Above Major conflict 0.16 Below 0.17 Below Minor conflict 0.19 Below 0.32 Above Source: Arbache and Page (2007).

8 John Page

Landlocked countries fair about the same as their coastal neighbors. But, while geography does not appear to matter, geology and conflict do.10 As might be expected, oil exporters and resource‐rich countries had more frequent growth accelerations but, somewhat unexpectedly, about the same frequency of growth decelerations as the regional average. Major conflict countries had both fewer growth accelerations and fewer decelerations than the regional average. They also had significantly lower average growth than the regional average. Because our definition of accelerations and decelerations is endogenous to the long‐run growth rate, these results suggest that major conflict countries were trapped in a low‐level equilibrium. Minor conflict countries had a substantially higher probability of a growth deceleration than the average and were much more likely to experience bad times than good times.

Characteristics of Good and Bad Times Good times and bad differ quite a bit in terms of their economic and social characteristics. Table 4 shows sample averages during growth accelerations, decelerations, and “normal” times (defined as the absence of either) for a number of key economic and social variables. It also gives the simple correlation coefficients between these economic, social, and institutional characteristics and the frequency of acceleration and deceleration episodes.

The major changes in national accounts during growth episodes take place in investment and savings rather than in consumption. Savings and investment are higher during accelerations, compared with normal times and substantially lower during bad economic times. Foreign direct investment (FDI) during accelerations is six times the figure for deceleration episodes. Consumption is relatively lower during growth accelerations. This is consistent with the higher allocation of resources to investment, but consumption also falls during decelerations, which is probably due to the fall in the purchasing power of households.

Macroeconomic management is an important factor in both good times and bad. Decelerations are accompanied by high inflation. The real effective exchange rate is more competitive during growth accelerations and highly appreciated during decelerations. Official development assistance (ODA) as a percentage of GDP is similar in both good and normal times but falls during growth decelerations. Per capita ODA is higher during growth accelerations and lower during decelerations. Interestingly, public debt is higher during both accelerations and decelerations than it is during normal times, but government consumption falls in both episodes relative to normal times. Trade is substantially lower during decelerations. Exports and especially imports drop sharply. Somewhat surprisingly, the terms of trade are less favorable during growth accelerations.

10 See the country assignment criteria in table A.2 of Arbache and Page (2008).


Table 4: Means of Economic, Social, Governance, and Institutional Characteristics during Growth Accelerations/Decelerations and Their Correlations with the Frequency of Acceleration/Deceleration Episodes


Mean during normal times

or trend growth Mean Correlation Coefficient Mean

Correlation Coefficient

Savings, Investment & Consumption Savings (% GDP) 11.4 15.2 .180 7.5 −.177 Investments (% GDP) 20.0 23.7 .176 15.9 −.236 Private sector investment (% GDP) 12.2 13.7 .125 9.2 −.166 FDI net flow (% GDP) 2.51 4.12 .130 0.77 −.135 Consumption (% GDP) 93.4 88.5 −.091 89.4 −.058 Macroeconomic Management Consumer price index (%) 109.5 105.1 −.102 177.0 .082 GDP deflator (%) 69.5 16.6 .011 168.1 .011 Public debt (% GNI) 95.2 112.0 .001 115.3 −.059 Government consumption (% GDP) 16.8 15.9 .100 15.1 −.122 Real effective exchange rate (2000=100) 139.8 114.4 −.038 183.1 −.084 Current account (% GDP) −5.9 −5.7 .056 −5.9 −.083 Trade Trade (% GDP) 70.1 75.4 −.034 58.8 .084 Exports (% GDP) 30.2 31.6 −.028 26.7 .078 Imports (% GDP) 41.0 43.1 .077 32.1 .089 Terms of trade (2000=100) 111.1 102.5 .065 114.4 −.176 Aid ODA (% GDP) 13.9 13.6 .054 11.9 −.217 ODA per capita (US$) 57.0 68.3 −.107 41.5 .168 Policies, Institutions, and Governance CPIA (scale 1=low to 6=high) 3.17 3.19 .065 2.77 −.206 Voice and accountability (−2.5 to +2.5, low to high) −0.65 −.46 .168 −1.07 −.209 Political stability (−2.5 to +2.5) −0.47 −.46 .051 −1.06 −.200 Government effectiveness (−2.5 to +2.5) −0.65 −.59 .100 −1.01 −.203 Regulatory quality (−2.5 to +2.5) −0.61 −.46 .129 −.94 −.176 Rule of law (−2.5 to +2.5) −0.62 −.66 .037 −1.11 −.227 Control of corruption (−2.5 to +2.5) −0.55 −.57 .025 −1.11 −.182 Minor conflict (frequency) 0.09 .08 −.046 0.15 .082 Major conflict (frequency) 0.12 .05 −.070 0.07 −.044 Human Development Outcomes Life expectancy (years) 50.8 51.3 .062 48.1 −.136 Dependency ratio 0.93 .91 −.067 .93 .053 Under 5 mortality (per 1,000) 150.4 145.8 −.108 187.1 .237 Infant mortality (per 1,000 live births) 86.2 84.3 −.108 113.2 .277 Primary completion rate (% of relevant age group) 53.2 52.5 .049 41.4 −.178

Source: Arbache and Page (2007).

10 John Page

Policies and institutions differ between good, normal, and (especially) bad times. The World Bank’s Country Performance and Institutional Assessment (CPIA) score, a broad measure of policy and institutional performance, is lower during decelerations, but does not differ significantly between accelerations and normal times.11 Governance indicators—political stability, government effectiveness, rule of law, and control of corruption—are lower during growth decelerations.12 Voice and accountability scores are higher during growth accelerations. Minor conflicts are more frequent during bad economic times.

Growth variability also affects a number of important human development indicators. Life expectancy is substantially lower in countries experiencing growth decelerations than in countries experiencing normal times. Mortality for children under age 5 and infant mortality are substantially higher during growth decelerations than in normal times, but these indicators do not improve during growth accelerations. The primary completion rate is substantially lower in countries during growth declines.

III. Good Policy or Good Luck?

Africa’s growth since 1995 largely reflects a substantial reduction in the frequency and severity of growth collapses and an increase in the frequency and country coverage of growth accelerations (table 5). Table 5: Frequency (Country-Years) of Growth Acceleration and Deceleration, by Country Category, 1995–2005 versus 1975–2005


Country category Likelihood 1975–2005

Likelihood 1995–2005



All countries’ mean 0.25 0.42 0.22 0.12 Coastal 0.26 0.44 0.22 0.12 Landlocked 0.23 0.34 0.22 0.14 Coastal without resources 0.24 0.38 0.23 0.14 Landlocked without resources 0.22 0.34 0.22 0.14 Oil exporters 0.29 0.49 0.23 0.12 Nonoil exporters 0.24 0.40 0.22 0.12 Resource countries 0.30 0.55 0.21 0.08 Nonresource countries 0.23 0.36 0.23 0.14 Major conflict 0.16 0.35 0.17 0.06 Minor conflict 0.19 0.32 0.32 0.13 Source: Arbache and Page (2009).

11 The CPIA measures country performance in 16 policy and institutional areas, grouped into four clusters: economic management, structural policies, policies for social inclusion and equity, and public sector management and institutions. 12 Governance indicators are available for the following years: 1996, 1998, 2000, 2003, 2004, and 2005.


These trends have coincided with a period of rapid expansion of the global economy and rising commodity prices. External shocks have historically been important determinants of growth in Africa (see, for example, Collier and Dehn 2001). Oil exporters and resource‐rich countries have experienced more growth accelerations than any other country type. To what extent are the shifts in growth performance observed in the last 10 years simply a reflection of a commodity price boom, rather than improvements in economic management?

Commodity Prices The better economic performance in the recent period is certainly partly due to the higher export prices for many African commodities (figure 3). Of the 40 commodity prices monitored regularly, only cotton prices have declined (from high prices during the 2003 drought year). Higher oil prices benefit 8–10 oil‐exporting countries. Gains from higher export prices for commodities such as gold, aluminum, copper, and nickel more than offset the losses from higher oil import bills in several oil‐importing countries, such as Burundi, Ghana, Guinea, Mali, Mozambique, Rwanda, Uganda, Zambia, and Zimbabwe. Overall, compared with the previous major oil price cycle during 1973–80, the aggregate terms of trade for Sub‐Saharan African countries have behaved much more favorably (figure 4).13 Figure 3: Commodity and Oil Prices (price indices, 2000=100)

50

100

150

200

250

300

350

Jan-01 Jan-02 Jan-03 Jan-04 Jan-05 Jan-06 Jan-07

Oil

Metals and minerals

Agriculture

Inde

x

Source: World Bank various years.

13 The recovery of terms of trade in non‐oil‐exporting developing countries since the late 1990s is, however, still below the peaks of the early 1980s. Data are from the World Bank’s World Development Indicators.

12 John Page

Figure 4: Terms of Trade Index in SSA 1973–80 and 1999–2006 (1973, 1999 = 100)

60

80

100

120

140

160

1999–2006

1973–1980

1974–2000

1975–2001

1976–2002

1977–2003

1978–2004

1979–2005

1980–2006

Year

Inde

x

Source: World Bank Africa Development Indicators, various years.

Despite the positive trends in commodity prices for Africa as a whole, a significant number of non‐resource‐rich countries experienced terms‐of‐trade losses driven by unfavorable changes in both oil and import prices. These countries include Benin, Burkina Faso, Cape Verde, Comoros, Eritrea, Ethiopia, The Gambia, Kenya, Lesotho, Madagascar, Mauritius, Niger, Senegal, the Seychelles, and Togo. In most cases, the additional negative shock came from prices of staple imports, such as wheat, rice, and vegetable oils. Eritrea, for example, had an estimated negative terms‐of‐trade impact of greater than 5 percent of GDP from higher food prices, while Lesotho, Mauritania, Senegal, and Togo had an estimated negative terms‐of‐trade impact in excess of 2 percent of GDP because of changes in food prices.

Policies and Institutions At the same time that commodity prices were rising, policies and institutions were also improving in Africa. The average CPIA score for Africa rose from 2.8 in 1995 to 3.2 in 2006. The number of African countries with CPIA scores equal to or greater than the threshold of 3.5 for international good performance also rose from 5 countries in 1997 to 17 in 2006.

The most striking improvement in policy is observed in macroeconomic management. The average fiscal deficit as a percentage of GDP in African countries declined from 5.7 percent during the 1980s and 1990s to 2.9 percent


during 2000–06.14 Fiscal policy in oil‐exporting countries has also improved. In contrast to the unchecked spending in the past, windfalls from oil revenue are increasingly being saved. At the start of the current oil price shock, fiscal deficits were reduced, and by 2004–06, the overall fiscal surplus averaged about 8 percent for the group. Inflation has declined dramatically since 1995 (figure 5). The regional average has been held below 10 percent since 2002.15 The number of countries able to keep inflation below 10 percent a year increased from 11–26 in the early 1990s to about 31–35 since 2000, despite the significant increase in oil prices that started in 1999.

Figure 6 suggests a correlation between better policy and institutions, as measured by the CPIA, and economic performance since 2000. The high growth rates in oil‐ and resource‐rich countries also suggest that the management of mineral resources has improved and windfalls have not been wasted to the same extent as in the past. Nineteen African countries have entered the Extractive Industries Transparency Initiative (EITI), which has the goal of verification and full publication of company and government revenues from oil, gas, and mining. Figure 5: Inflation Pattern of African Countries (number of countries by inflation range)

21 20 20 20 18 2021 22

10

17

2528 30

32 3336

32 34 31 32 33

7 7 69 11 8 5 5

4

10

2

54 2

43 9 7 12 10 9

2 41

2 0 33

5

8

3 5

23 1

5 22 3

1 2 1

2 25

2 5 2 3

3

12

34

32

2

0 10 0

1 1 1

4 3 66 4 6 7

5 6 74 2

1 3

3 3 22 1 1 1

0

5

10

15

20

25

30

35

40

45

50

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

No.

of c

ount

ries

>50%

31~50%

21~30%

11~20%

14 John Page

Figure 6: Economic Performance of African Countries by Quality of Policy, 2000–06

3.9

13.5

4.9

6.4

5.1

6.9

0

2

4

6

8

10

12

14

16

Growth (%) Inflation (%)

CPIA < 3.5

CPIA ≥ 3.5

CPIA ≥ 3.5, low incomeexcl. oil countries

Per

cent

Sources: AFRCE various years; World Bank various years.

Explaining Good Times and Bad Tables 6 and 7 summarize the results of efforts to understand what economic and institutional variables are associated with growth accelerations and decelerations. These regressions represent a further search for stylized facts about acceleration and deceleration episodes.16 Table 6 shows the conditional probabilities of a growth acceleration or deceleration based on OLS estimates. Table 7 shows fixed‐effect logit models that give the probability of a growth acceleration or deceleration taking place at the country level.17

The first and most striking result of the econometric exercises is the extent to which the results provide greater insight into the determinants of growth decelerations than growth accelerations. In both econometric models the fit of the model to the data and the precision of the estimated coefficients are higher in the case of growth declines. The number of variables showing statistically significant correlations with the probability of a growth decline is also larger.

16 No causality is inferred from the relationships, and no attempt has been made to control for endogeneity of some of the right‐hand‐side variables. 17 Random‐effects models, including dummies for oil‐producing countries, and landlocked and resource‐rich countries returned statistically insignificant results. Hausmann tests suggest that fixed‐effects estimates are preferable to random effects.


Tab

le 6

: Con

ditio

nal p

roba

bilit

y of

gro

wth

acc

eler

atio

n an

d de

cele

ratio

n at

the

aggr

egat

e le

vel

Varia

ble

Dep

ende

nt v

aria

ble:

fr

eque

ncy

of g

row

th

acce

lera

tion

per c

ount

ry

Dep

ende

nt v

aria

ble:

freq

uenc

y of

gro

wth

dec

eler

atio

n pe

r cou

ntry

M

odel

1

Mod

el 2

M

odel

3

Mod

el 4

M

odel

5

Mod

el 6

M

odel

7

Mod

el 8

M

odel

9

Mod

el 1

0 M

odel

11

Mod

el 1

2

Ln in

vest

men

t .1

10

(1.7

0)

.047

(.7

2)

−.

253

(−3.

23)

−.

233

(−1.

97)

Voi

ce (g

over

nanc

e in

dica

tor)

.056

(1

.87)

.061

(1

.98)

R

esou

rce

rich

coun

try

.082

(1

.77)

.0

82

(1.7

3)

Ln O

DA

per c

apita

−.

078

(−2.

17)

−.03

6 (−

.84)

Ln im

ports

−.

145

(−2.

40)

.020

(.21

)P

oliti

cal s

tabi

lity

(gov

erna

nce

indi

cato

r)

−.

068

(−2.

08)

Gov

ernm

ent

effe

ctiv

enne

ss

(gov

erna

nce

indi

cato

r)

−.12

7 (−

2.63

)

Rul

e of

law

(g

over

nanc

e in

dica

tor)

−.11

5 (−

2.60

)

C

ontro

l of c

orru

ptio

n (g

over

nanc

e in

dica

tor)

−.

132

(−2.

68)

R

2 .0

6 .0

8 .0

6 .1

6 .1

0 .1

9 .1

2 .0

9 .1

4 .1

4 .1

5 .2

1 N

45

44

45

44

45

45

45

44

44

44

44

44

Sou

rce:

Arb

ache

and

Pag

e (2

007)

. N

ote:

t-te

st in

par

enth

eses

.

16 John Page

Table 7: Predicting Growth Acceleration and Deceleration—Panel Data Dep. variable: dummy of

growth acceleration Dep. variable: dummy of

growth deceleration Variable Odds ratio p-value Odds ratio p-value

Savings 1.152 .000 .929 .000 Investment in fixed capital .956 .062 FDI net flow 1.146 .000 .811 .000 GDP deflator 1.010 .016 Consumption 1.051 .004 Government consumption .904 .000 Trade .980 .008 Minor conflict 1.744 .045 Major conflict .435 .064 LR (chi2) 127.6 .000 97.4 .000 N 825 647

Source: Arbache and Page (2007). Note: Fixed effect logit regression.

Better macro economic management, higher investment and savings, better

governance, and greater openness to trade appear to reduce the odds of a growth decline. Higher investment, higher ODA per capita, increased imports, and better governance indicators are significantly associated with fewer growth decelerations in the OLS regressions. In the multinomial logit analysis increases in savings, investment, FDI, and trade reduce the probability of a growth deceleration. Inflation and minor conflicts increase the odds of bad times. Better governance indicators reduce the likelihood of growth decelerations in the OLS results. Avoiding conflict also helps to avoid bad economic times.

The picture is less clear with respect to good times. Higher savings and investment are less strongly associated with an increased probability of growth accelerations, although FDI appears to play a positive role. Increases in savings, FDI, and consumption increase the probability of good times in the logit regressions, whereas higher government consumption and major conflicts reduce the odds. Voice and resource endowment raise the probability of growth accelerations in the OLS regressions. Interestingly, better governance indicators are not associated with more frequent accelerations.

Better Policies and Some Luck Africa’s recent growth appears have had more to do with good policy—learning how to avoid economic mistakes—than to good luck—favorable movements in the terms of trade. There were clearly some important policy and institutional improvements that underpin the fall in the frequency of economic declines. While the terms of trade have improved on average, their impact has been far from uniform, and changes in the terms of trade are not correlated with increased probabilities of growth accelerations or declines. Indeed, the terms of trade were less favorable during growth acceleration episodes.


These findings are consistent with other research. Hausmann, Pritchett, and Rodrik (2005) conclude that positive external shocks are strongly correlated only with short‐term economic expansions, not with sustained growth episodes. The IMF (2007) finds that most growth spells in Africa during the recent expansion are taking place during negative terms‐of‐trade shocks, and concludes that other factors have been more important in boosting growth. Raddatz (2008) finds that although external shocks have become relatively more important as sources of output instability in Africa in the past 15 years, output variability in general is declining. The relative increase is the result of a decline in the variance of internal shocks, including policy failures or conflicts.

IV. Is Growth Sustainable?

Avoiding the mistakes leading to growth declines has made an important contribution to Africa’s economic outlook, but sustaining growth for more than a decade will require that its economies achieve and maintain levels of economic fundamentals—savings, investment, and productivity growth—that are similar to well performing economies in other regions. Table 8 compares key economic variables for Africa with those of other developing regions in 1995–2005. Savings and investment rates were well below those of other regions, and private investment lagged badly. Both private consumption and government consumption were higher than those of other regions. The contrast in savings, investment, and consumption with East and South Asia was particularly striking. Inflation, FDI, and trade are comparable to other regions. Table 8: Differences between Simple Sample Average by Regions, Weighted Data, 1995–2005

Variable

Sub-Saharan Africa

East Asia & Pacific

Latin America

& Caribbean

Middle East & North Africa

South Asia

All Low & middle income

Per capita GDP growth 1.34 6.75 1.13 2.23 4.27 3.89 Savings (% GDP) 17.47 38.45 21.04 23.85 22.39 26.01 Investments (% GDP) 17.69 32.77 19.17 22.49 22.88 23.65 Private sector investment (% GDP) 13.11 19.27 16.39 13.92 16.36 16.83 FDI net flow (% GDP) 2.60 3.22 3.24 1.16 0.79 2.73 Consumption (% GDP) 84.10 68.03 80.85 75.64 80.54 76.23 Trade (% GDP) 62.31 66.85 42.72 57.38 31.90 55.43 Exports (% GDP) 30.62 35.04 21.47 28.15 14.81 27.95 Imports (% GDP) 31.68 31.78 21.25 29.22 17.09 27.47 Terms of trade (2000=100) 101.89 90.89 101.50 NA 104.10 96.28 GDP deflator (%) 7.16 4.91 6.17 5.20 5.67 6.48 Government consumption (% GDP) 16.00 13.47 14.52 15.04 10.83 14.34 Source: Arbache and Page (2009). Note: The sample averages refer to all years between 1995 and 2005.

18 John Page

Tabl

e 9:

Diff

eren

ces

of M

eans

of E

cono

mic

Fun

dam

enta

ls B

efor

e an

d A

fter 1

995

A

ll co

untr

ies

Non

-res

ourc

e ric

h R

esou

rce

rich

Varia

ble

1995

–200

5

1985

–94

t-tes

t 19

95–2

005

1985

–94

t-tes

t 19

95–2

005

1985

–94

t-tes

t

Sa

ving

s (%

GD

P)

12.0

5 10

.47

* 10

.88

10.8

14.8

5 9.

68

* In

vest

men

ts (%

GD

P)

20.2

6 19

.4

18

.93

18.7

8

23.4

20

.92

**

Priv

ate

sect

or in

vest

men

t (%

GD

P)

12.5

1 11

.46

**

11.2

3 10

.6

15

.43

13.4

7

Fore

ign

dire

ct in

vest

men

ts n

et fl

ow (%

GD

P)

4.95

1.

50

* 3.

63

1.41

*

8.23

1.

75

* C

onsu

mpt

ion

(% G

DP)

91

.12

92.0

9

95.8

5 95

.24

79

.9

84.1

5 *

Trad

e (%

GD

P)

76.5

8 68

.43

* 72

.73

66.1

1 *

85.7

7 74

.1

* E

xpor

ts (%

GD

P)

32.2

7 28

.06

* 28

.86

25.6

7 *

40.3

2 33

.92

* Im

ports

(% G

DP

) 44

.27

40.3

6 *

43.8

6 40

.44

* 45

.25

40.1

8 *

Sou

rce:

Arb

ache

and

Pag

e (2

008a

). N

otes

: (*

) t-te

st th

at m

eans

are

not

equ

al s

igni

fican

t at t

he 5

% le

vel.

(**)

t-te

st th

at m

eans

are

not

equ

al s

igni

fican

t at t

he 1

0% le

vel.


Table 9 compares economic fundamentals during 1995–2005 with 1985–94.18 For Africa as a whole savings were higher than in the previous decade, but aggregate investment did not change significantly. Savings and investment in resource–rich countries showed substantial increases (by about 5 percent of GDP) in 1995–2005, but savings and investment were not significantly different in the two periods for non‐resource‐rich economies. Private investment and FDI went up. Overall there was a small increase of about one percent of GDP in the private investment rate. Resource‐rich countries had higher rates of private investment than resource poor countries, both before and after 1995. FDI increased threefold in the period 1995–2005, to 5 percent from 1.5 percent in the previous decade. Most of this increase was due to a sharp rise in FDI in resource rich economies to 8.2 percent of GDP from 1.8 percent, reflecting the fact that most FDI flows to Africa are concentrated in the mineral sectors.

Investment rates for top performers in Africa are still below those of the high‐performing Asian countries (table 10). Although Ghana and Mozambique, are on par with India, none of the better performing countries in Africa invest a share of their GDP equal to China or Vietnam. The aggregate efficiency of investment among top performers in Africa, as reflected by incremental capital‐output ratios, is equal to that found in many Asian countries. Incremental capital output ratios (ICORs) in Africa, however, are less stable and are easily affected by output variation caused by drought (Rwanda in 2003), flood (Mozambique in 2000), or other factors. Table 10: GDP Growth, Investment Rates, and ICOR (select countries in Asia and Africa, 2000–06)

GDP growth Investment rate ICOR Top Asian performers China 9.5 39.7 4.2 Cambodia 9.2 19.0 2.2 Vietnam 7.5 33.4 4.5 India 6.9 27.8 4.7 Lao PDR 6.4 25.1 4.0

Top African performers (excluding middle-income, oil- and resource-intensive countries) Mozambique 7.6 26.4 3.1 (5.1*) Tanzania 6.3 20.2 3.3 Ethiopia 6.2 18.4 3.0 Burkina Faso 6.1 18.5 3.3 Uganda 5.6 20.7 3.8 Rwanda 5.5 19.4 3.7 (5.8*) Ghana 5.0 25.7 5.2 Source: World Bank WDI and authors’ estimates.

18 So that the subsets’ sample sizes are consistent, oil‐exporting countries are not accessed separately.

20 John Page

The improvement in the volume and productivity of investment among Africa’s top performers has not translated into a generalized increase in investment rates or capital productivity. Physical capital per worker has grown less than 0.5 percent a year, half the world average. The overall ICOR is still high at 5.5, and a major source of Africa’s disappointing growth, low total factor productivity (TFP), has not improved. TFP growth has been negative since the 1960s. It averaged −0.4 percent between 1990 and 2003 (Bosworth and Collins, 2003).19

V. Toward a Strategy for Sustained Growth.

Growth has been higher, more likely, and more widespread since 1995. It was spurred by better commodity prices and better policy, but there is no strong evidence that it was accompanied by higher accumulation of human or physical capital, and higher productivity. Avoiding economic collapses will continue to depend on good policy, leadership, and aid, but the growth bonus that Africa can realize by further reducing the frequency of economic declines has diminished substantially. To sustain and accelerate growth the region will have to tackle several constraints to greater productivity and investment.

Africa is highly diverse, and any attempt to offer a strategic approach to growth for the region as a whole runs the risk of excessive simplification. South Africa for example dominates the regional economy of Sub‐Saharan Africa. Its output is 35 percent of the total regional GDP. But, most studies of regional economic prospects for Africa—including this one—tend to exclude or marginalize South Africa. In many ways this is appropriate: South Africa’s economic structure is more closely aligned to middle‐income countries in other regions than to the economies of its smaller regional neighbors, and it is more integrated into the global than the regional economy. For these reasons South Africa’s problems and prospects differ fundamentally from those of the rest of Africa. As the region’s leading economy, however, its success or failure will strongly influence both economic thinking and performance in Africa. Box 1 addresses what is, perhaps, the most pressing problem faced by South Africa, the task of job creation.

For the remaining countries in the region the empirical findings of this paper and the experience of a number of successfully growing economies suggest four major themes that are relevant to achieving a sustained economic expansion. These are: using natural resource rents well, creating an export push, building the African private sector, and investing in skills.

19 Devarajan, Easterly, and Pack (2003) make the argument that the low and volatile productivity of capital constrains growth in Africa more than the region’s low investment rate.


Box 1: South Africa: It’s Jobs... Since independence in 1995 economic performance in South Africa has been a modest success. Early fears of massive capital flight were not realized, macroeconomic management has been sound, and the economy grew at 3.5 percent per year between 1995 and 2006. At the same time, however, South Africa had one of the highest rates of unemployment in the world. Unemployment rose from about 15–30 percent of the labor force in 1995 to 30–40 percent in 2003, depending on the definition used (Kingdon and Knight, 2007). Lack of employment opportunities has contributed to poverty and crime, raising the specter of a vicious circle in which increasing social insecurity reduces business confidence and investment, leading to slower economic growth and lower job creation. Developments in the labor market may well hold the key to South Africa’s long-term economic success.

In the simplest terms job creation since 1995 has failed to keep pace with very rapid growth in the labor force. Between 1995 and 2003 the labor force grew at 4.2–4.8 percent per year (depending on the definition used)—an extremely rapid rate internationally—while wage employment grew at only 1.8 percent. The result was an increase in unemployment of more than 9 percent per year (Kingdon and Knight, 2007). Ironically, the rapid growth of the labor force to a large degree reflected the new opportunities offered to majority South Africans following independence: growth of labor force participation by African men and women led the growth of the labor force.

The behavior of the demand side of the labor market in the face of this rapid increase in labor supply reveals the sharp dualism that characterizes South Africa’s labor market. Real earnings in the formal, unionized sector of the economy remained largely unchanged while earnings in small enterprises, informal employment, and self-employment declined. In the absence of downward adjustment in real wages the full burden of job creation in the formal sector fell on growth of output and hence labor demand. Economic growth was simply not sufficient to generate robust job growth in the formal economy. In the informal sector, despite downward pressure on real wages and earnings, barriers to entry—arising for example from access to credit, crime, access to infrastructure, and the risk of “formalization”—appear to have restricted the formation and growth of dynamic small and micro enterprises.

The policy solutions to the employment problem in South Africa need to recognize the interconnected roles of economic growth and regulatory reform. South Africa’s labor market dualism arises from its regulatory regime: wage and employment regulations restrict flexibility in the formal sector. Most econometric evidence, however, suggests that complete deregulation of the labor market in the absence of more robust, sustained growth would not be sufficient to absorb all of the unemployed into the formal sector (Fields et al., 1999). On the other hand labor market regulation—in particular the “extension provision” that requires collective bargaining agreements to be extended to all firms in an industry, regardless of size—is very likely one of the factors inhibiting investment and growth, especially in small enterprises that globally provide the bulk of employment in middle- and high-income countries (World Bank, 2007c). Thus policy makers need to work on two fronts: identifying and implementing policies to grow the economy and pursuing regulatory reforms to reduce the degree of dualism in the labor market.

Using Natural Resource Rents Well Resource‐based rents (the excess of revenues over all costs) are widespread and growing due to new discoveries and favorable prices. Between 2000 and 2010, more than $200 billion in oil revenue will accrue to African governments, dwarfing the levels of official development assistance to the region.

Africa’s resource‐rich economies will have the ability to finance their development needs substantially from their own resources. But, if the economic history of resource‐rich, poor countries—especially in Africa—is any guide, rather than bringing prosperity, oil and other minerals may drive new producers

22 John Page

into what Paul Collier in his influential book The Bottom Billion terms the “Natural Resources Trap.” Collier and Goderis (2007) find that while favorable commodity price movements account for short‐run increases in GDP, commodity booms have long‐run negative effects on the rate of growth of low‐income, resource‐rich economies. African countries dependent on oil, gas, and mining have weaker political institutions, higher rates of poverty, and higher inequality than non‐mineral‐dependent economies at similar levels of income. Africa’s mineral‐dependent economies also tend to do worse with respect to social indicators than non‐mineral countries at the same income level; they have higher poverty rates, greater income inequality, less spending on health care, higher prevalence of child malnutrition, and lower literacy and school enrollments.

But geology is not destiny. Natural resource wealth can be an effective driver of growth and poverty reduction. Chile, which has been the fastest‐growing Latin American country for the past 15 years, has relied almost entirely on exports of natural resource products, accompanied by openness to trade and FDI to boost its growth. Botswana has been among the world’s fastest‐growing economies for the last 30 years. Indonesia and Malaysia have used their natural resource wealth to diversify and grow their economies, and equally importantly, to allow the poor to participate in and benefit from that growth. Indonesia successfully pursued a 25‐year policy of using a share of its petroleum revenues to increase the productivity of smallholder agriculture, through targeted fertilizer subsidies and massive investments in rural infrastructure (roads, irrigation, market infrastructure, and water systems). Labor‐intensive public works made jobs available to unskilled workers willing to work at local market wages. Malaysia used its natural wealth to upgrade infrastructure, improve education, and diversify the economy.

The symptoms of the natural resources trap are reasonably common across countries: weak public institutions, corruption, boom‐to‐bust macroeconomic management, stagnant long‐run economic growth, and inefficient public expenditures. Its causes are complex and not easily diagnosed or remedied at the country level. The large literature on the political economy of natural resources exporters in Africa agrees that that politics and institutions matter.20 Natural resource revenues accrue primarily to the state, and public sector decision making directly influences their allocation. In Africa political, social, and ethnic factors combine in many resource‐rich countries to encourage clientelism in fiscal policies and to undermine the effectiveness of institutions designed to limit discretionary behavior in public financial management. Politicians—democratic or autocratic—much of the literature argues, simply find it easier to compete for

20 Commodity windfalls have been associated with the prevalence of conflict (Collier and Hoffler 2005) and rent‐seeking behavior. (Bates 1983; Sklar 1991) According to the prevailing wisdom, the concentration of fiscal resources also tends to encourage excessive, imprudent investment and corruption. (Gelb 1988; Auty 1998; Eifert, Gelb, and Tallroth 2003).


power on the basis of patronage than to promote growth and deliver public services.

But some countries in Africa—notably Botswana—have dealt successfully with these pressures. The key to their success appears in large measure to be the creation and maintenance of checks and balances that limit the ability of politicians (and governments) to buy support through the distribution of resource rents. A common theme in successful resource‐rich economies—whether democratic or autocratic—is that political leaders are held accountable for and derive their legitimacy from delivering economic and social outcomes valued by their societies.

How might Africa’s commodity exporters strengthen accountability in the use of their prospective revenues? One way might be to attempt to forge a national consensus—crossing ethnic, regional, and political boundaries—to use oil revenues to underpin a “shared growth” strategy, similar to those pursued by the first‐generation high‐performing Asian economies—Hong Kong, China; Indonesia; the Republic of Korea; Malaysia; Singapore; Taiwan, China; and Thailand.21 These strategies had two common elements: fostering growth by encouraging high savings, long‐term investments, and continuous improvements in organization, technology, and management, and investing in highly visible wealth‐sharing mechanisms, such as universal primary education, rural development, and basic health care. Unlike populist redistribution schemes, such as food or fuel subsidies or public employment in nonproductive activities, these strategies were designed to increase people’s capacity to participate in and benefit from the process of economic change. They were broad‐based investments with visible outcomes that could be monitored, and Asian politicians—even in the resource‐rich economies—were held accountable by their societies for results. With the basic vision of development broadly shared, political competition centered on who was best able to deliver.

In moving from vision to implementation, the experience of other resource‐rich countries suggests that the elements of a successful strategy for mineral revenue management include the following:

Getting a fair price for the resource. Contracts for Africa’s natural resources in the past have too frequently provided too few rents and too many risks to host governments. Auctions have been infrequently used, yet in the presence of genuine competition, they offer an efficient means to allocate rents fairly between host governments and extractive industry investors.

Being transparent in accounting for revenues. Accountability needs transparency, but many African mineral producers continue to keep revenues from public scrutiny. The Extractive Industries Transparency

21 The term is due to World Bank (1993). A fuller exposition of the concept is provided in Campos and Root (1996).

24 John Page

Initiative (EITI) has begun to make inroads in Africa, but only six mineral‐rich countries have actually published EITI reports.

Saving in good times to anticipate bad times. This can be accomplished by the consistent application of fiscal rules or by the creation of various stabilization mechanisms, but neither practice is widespread in Africa.

Strengthening public financial management and accountability. Building the capacity of public expenditure systems to identify, prioritize, and evaluate expenditures is essential. One of the keys to Botswana’s and Chile’s successful use of natural resources has been the application of systematic cost benefit analysis to development projects.

Monitoring and evaluating outcomes and reporting on results. In addition to ex ante evaluations of public expenditures ex post monitoring and evaluation need to take place, and the results need to be publicly disclosed.

Creating an Export Push For economies without substantial natural resources rapid growth and diversification of nontraditional exports offers two important ways to boost growth through greater integration into the global economy. The first channel is simply via an enlarged market, which permits more rapid growth in exporting firms and sectors, and in some cases, the realization of economies of scale.

The second, and more controversial channel, is through “learning by exporting.” There is a large body of empirical literature that indicates that firms engaged in export production have higher levels of total factor productivity than those producing exclusively for the domestic market. This empirical regularity holds for the few African economies for which sufficient microeconomic data are available to permit rigorous statistical analysis. Soderbom and Teal (2003), Milner and Tandrayen (2004), and Mengistae and Pattillo (2004), using panel data for manufacturing firms in three countries (Ethiopia, Ghana, and Kenya) find significantly higher levels of productivity in exporting firms, relative to firms selling only domestically. If the higher productivity levels of exporting firms are the result of their export activities—as might be the case for example in supplier–buyer relationships that involve the transfer of tacit technological or production knowledge—increasing the share of exports in GDP will generate higher levels of economy wide total factor productivity and more rapid growth.

The alternative explanation for the higher productivity of exporting firms is self‐selection. More efficient firms are able to export while those with lower productivity confine themselves to the local market. Both hypotheses are plausible, and indeed, need not be independent of each other. More efficient firms can more easily access international markets, but they may still learn from exporting. The most recent econometric evidence available suggests that the learning by exporting hypothesis is defensible and, indeed, was a major factor in the success of East (and now South) Asia’s rapidly growing economies. The


literature also suggests however that learning by exporting is more likely to take place in smaller economies and in new, modern manufacturing and service exports, rather than in traditional, commodity exports. Given this evidence, a key strategic initiative to raise productivity in Africa ought to be to push the development of nontraditional exports, including both manufacturing and modern services.

Compared to Latin America, the Middle East and North Africa, and South Asia, Africa has always had a relatively high share of trade in its national income and a high ratio of exports to GDP. However, African exports, particularly nonoil exports, are growing slowly (figure 7), and in sharp contrast to the case of China and Asia’s other top‐performing countries, exports are not growing as a share region’s output. Of perhaps even greater concern, they are declining in importance for Africa’s fastest‐growing economies. Africa’s share of world trade is falling, and its exports remain heavily concentrated in a few traditional commodities (figure 8).

To generate new dynamism in nontraditional exports Africa will need to put together an “export push” strategy, similar to those undertaken by East and more recently South Asian economies. These strategies are characterized by coordinated pro‐export commercial and exchange rate policies, effective export promotion institutions, and efficient trade‐related infrastructure. While Africa has made some progress in each of these areas, it has not made sufficient progress in all three to create an environment conducive to the rapid growth of nontraditional exports. Figure 7: Non-Oil Exports as Percent of GDP (SSA versus other regions)

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East Asia andPacific

Eastern Europeand Former

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) 1983–85 1993–95 2003–05

Region Source: World Bank various years. Note: Expo

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