Annual Trends and Outlook Report 20 14 BEYOND A MIDDLE INCOME AFRICA: Transforming African Economies for Sustained Growth with Rising Employment and Incomes Edited by Ousmane Badiane Tsitsi Makombe Regional Strategic Analysis and Knowledge Support System CHAPTER 5 Economic Recovery in Africa and Its Determinants About ReSAKSS | www.resakss.org Established in 2006 under the Comprehensive Africa Agriculture Development Programme (CAADP), the Regional Strategic Analysis and Knowledge Support System (ReSAKSS) supports efforts to promote evidence and outcome-based policy planning and implementation. In particular, ReSAKSS provides data and related analytical and knowledge products to facilitate CAADP benchmarking, review, and mutual learning processes. The International Food Policy Research Institute (IFPRI) facilitates the overall work of ReSAKSS in partnership with the African Union Commission, the NEPAD Planning and Coordinating Agency (NPCA), leading regional economic communities (RECs), and Africa-based CGIAR centers. The Africa-based CGIAR centers and the RECs include: the International Institute of Tropical Agriculture (IITA) and the Economic Community of West African States (ECOWAS) for ReSAKSS–WA; the International Livestock Research Institute (ILRI) and the Common Market for Eastern and Southern Africa (COMESA) for ReSAKSS–ECA; and the International Water Management Institute (IWMI) and the Southern African Development Community (SADC) for ReSAKSS–SA. ReSAKSS is funded by the United States Agency for International Development (USAID), the Bill and Melinda Gates Foundation, the International Fund for Agricultural Development (IFAD), and the Ministry of Foreign Affairs of Netherlands (MFAN). Earlier, ReSAKSS also received funding from the UK Department for International Development (DFID) and the Swedish International Development Cooperation Agency (SIDA). Editors Ousmane Badiane and Tsitsi Makombe DOI: http://dx.doi.org/10.2499/9780896298927 ISBN: 978-0-89629-892-7 Citation Badiane, O. and Makombe, T. (Eds). 2015. Beyond a Middle Income Africa: Transforming African Economies for Sustained Growth with Rising Employment and Incomes. ReSAKSS Annual Trends and Outlook Report 2014. International Food Policy Research Institute (IFPRI). Copyright Except where otherwise noted, this work is licensed under a Creative Commons Attribution 3.0 License (http://creativecommons.org/licenses/by/3.0). Chapter 5 Contributors: Ousmane Badiane, Director for Africa, IFPRI Julia Collins, Research Analyst, West and Central Africa Office, IFPRI Xinshen Diao, Deputy Director, Development Strategy and Governance Division, IFPRI John Ulimwengu, Senior Research Fellow, West and Central Africa Office, IFPRI http://www.resakss.org 2014 ReSAKSS Annual Trends and Outlook Report 1 CHAPTER 5 Economic Recovery in Africa and Its Determinants Ousmane Badiane, Julia Collins, Xinshen Diao, and John Ulimwengu 2 resakss.org Introduction After years of stagnation and decline, the last two decades have seen an un- precedented agricultural and overall economic recovery in Africa. Although the scope of the recovery is noticeable, the drivers and the sustainability of the continent’s current improved performance are less well understood. Some argue that the growth recovery is largely the result of rising commod- ity prices (for example, Lipton 2012), with concurrent negative effects on other sectors and risks of decline following future price drops. While the impact of natural resources remains undeniably important, there have been periods of global commodity booms in the past, and they did not generate similar growth outcomes. At best, a limited number of countries benefited from such positive global trends, and often only briefly. Never have African economies been able to respond so broadly and so sustainably to improving global economic conditions. Hence, the real story is not what happened in global markets and outside Africa, but what happened within Africa to enable economies to respond so strongly and positively to global market changes. Africa’s relatively healthy growth during the recent global food and financial crises is another testimony to the dominance of internal factors in driving the recovery process. In fact, chapter 6 by Badiane and McMillan provides evidence that domestic demand has played a much larger contribu- tion to growth than commodity exports. Any observer of economic development in Africa will have noticed that the recent decade and a half has been the only time in the continent’s history that a large majority of countries have managed to sustain high and accelerating rates of economic growth over such a long period. The explanation must involve factors that not only have affected almost every country but also have generated broad, sustained structural changes. These would include progress made in political and economic governance as well as investment in economic infrastructure. Preceding and concomitant with the economic recovery are a steady increase in the number of countries transitioning toward more open and pluralistic policy systems, a sharp reduction in the number of countries with conflict and civil unrest, a near universal move toward more private-sector-friendly economic policy regimes, and, more recently, a surge in investments in all major economic sectors. All these factors will continue to be the drivers of growth and de- terminants of its sustainability in the decades to come. They will determine whether African economies will be able to meet growth challenges and seize opportunities facing them. In this paper, we review the characteristics of Africa’s recent growth performance, discussing the drivers, future outlook, and potential risks. The roles of governance and policy reforms, investment, and the management of mining and other natural resource sectors are highlighted. In the first section, we analyze economic growth and agricultural productivity trends since independence. As economic performance by African countries has changed drastically, we assess the current performance against the long- term growth trajectory of African economies since the 1960s. Given the breadth of the recovery process, we also look for evidence of convergence among African economies as well as between African economies and the rest of the world. In section 2 we review the evolution of economic development and growth policies and strategies in Africa. We compare Africa’s reform experience with that of one of the successful emerging economies, China, to examine the factors contributing to the success of policy reforms. This evaluation is followed by an econometric analysis of the drivers of growth in section 3. The final section summarizes the evidence http://www.resakss.org 2014 ReSAKSS Annual Trends and Outlook Report 3 and provides recommendations for sustaining agricultural and economic growth and avoiding potential risks. Trends in Africa’s Past and Current Growth How Rapid Is Africa’s Current Growth Compared to Past Growth? As shown in Figure 5.1, Africa’s growth performance in the last decade and a half represents a dramatic improvement over past trends. For 36 countries in Africa south of the Sahara (SSA) with readily available data, not including South Africa, the average annual gross domestic product (GDP) per capita growth rate in 2000–2012 reached 3.2 percent, the highest rate of growth in five decades, and an important departure from previous decades of negative per capita growth rates. The growth rates of the nine fastest-growing countries in SSA are shown on the left of the graph; these countries represented 31 percent of SSA’s total GDP and 48 percent of SSA’s total population in 2000–2012 (World Bank 2015). Most of the countries had negative per capita GDP growth rates in the 1980s and five were still contracting in the 1990s, but their average annual growth rate in the 2000s reached 6.0 percent. FIGURE 5.1—AFRICA’S CURRENT GROWTH IS RAPID, MEASURED BY GDP PER CAPITA Source: Authors’ calculations using data from World Bank (2014a). Note: SSA-ZAF = Africa south of the Sahara, not including South Africa. -6 -4 -2 0 2 4 6 8 10 Angola Eth iopia Ghana Nigeria Rwanda Ta nza nia Uganda SSA-Z AF Average Annual GDP per capita growth rates (%) 1980-1989 1990-1999 2000-2012 9 co untri es Chad M oza m biq ue 4 resakss.org4 resakss.org Changes in labor productivity are particularly important in relation to efforts to reduce poverty. Here too, recent growth has been impressive and has far outstripped growth in the previous decades (Figure 5.2). The average annual labor productivity growth for the 21 countries in SSA included in the Conference Board’s 2015 Total Economy Database1 (not including South Africa) was 3.2 percent during the 2000–2013 period, a marked increase over the negative growth rates of previous decades. Most of the fast-growing countries shown in Figure 5.2 had positive growth rates in the 1960s that turned sharply negative in the 1970s and became positive again only in the 1990s. Similar growth trends are seen in labor productivity in agriculture, the livelihood of most of the region’s poor (Figure 5.3). For 39 countries in SSA, not including South Africa, the annual average agricultural labor productivity growth of 1.2 percent in the 2000s was a historical high and surpassed its level of the 1960s of 1.0 percent. Productivity growth was negative during the 1970s, at -2.0 percent. Has Africa Made Up for Its Lost Decades? Africa’s recent rapid growth should be viewed in light of the preceding decades of stagnation and even deep decline. Benin et al.’s (2011) analysis of Africa’s agricultural total factor productivity showed that the rapid agricultural productivity growth since the 1980s simply allowed the continent to catch up with its total factor productivity levels of the 1960s. Indeed, Africa’s recent economic growth may not have been sufficient to put the continent back on its growth path of the early post-independence years, FIGURE 5.2—AFRICA’S CURRENT GROWTH IS RAPID, MEASURED BY GDP PER CAPITA Source: Authors’ calculations using data from Conference Board (2015). Note: SSA-ZAF = Africa south of the Sahara, not including South Africa. -10 -8 -6 -4 -2 0 2 4 6 8 10 Average Annual Labor Productivity Growth Rate (%) Angola Eth iopia Nigeria Ta nza nia Uganda SSA-Z AF 1980-1989 1990-1999 2000-2013 Ghana M oza m biq ue 1960-1969 1970-1979 1 The Total Economy Database includes annual data on GDP, population, employment, and productivity. Available from https://hcexchange.conference-board.org/data/economydatabase/ index.cfm?id=27762. http://www.resakss.org 2014 ReSAKSS Annual Trends and Outlook Report 5 when many analysts predicted that Africa would grow more rapidly than Asia (Easterly and Levine 1997). In this subsection, we evaluate whether Africa’s recent growth represents a full recovery from the lost decades of economic decline, in the sense that the growth has allowed African countries to reach the growth trajectories they began during the 1960s. To the extent that current levels of GDP and productivity remain below the levels that would have been achieved if countries had maintained their earlier growth rates, African countries are still facing the consequences of the lost decades in terms of lower standards of living, and stronger efforts to accelerate the recovery are needed. Figure 5.4 shows the per capita GDP trajectory for 27 SSA countries with data available from the 1960s. Actual per capita GDP levels are graphed in red, as well as projected levels up to 2025 based on the growth rates of the 2000s. The dotted line shows the GDP per capita levels that would have been obtained if the countries had maintained their growth rates of the 1960–1977 period. If this group of countries had continued growing at 2.0 percent per year, their average annual rate during 1960–1977, GDP would have reached a level of US$1,428 (in 2005 dollars) per capita by 2012, almost double the actual level. Instead, after reaching $694 in 1977, GDP per capita for this group of countries declined steadily over the next two decades, reaching a low of $511 in 1995 before rising again.2 The group’s GDP per capita did not surpass its 1977 level until 2010. FIGURE 5.3—AFRICA’S CURRENT GROWTH IS FASTER, MEASURED BY AGRICULTURAL OUTPUT PER WORKER Source: Authors’ calculations using data from Nin-Pratt (2015). Note: SSA-ZAF = Africa south of the Sahara, not including South Africa. -8 -6 -4 -2 0 2 4 6 8 10 Angola Chad Eth iopia Ghana Nigeria Rwanda Ta nza nia Uganda SSA-Z AF Average Annual Growth Rates in Agricultural Output per worker (%) 9 co untri es M oza m biq ue 1980-1989 1990-1999 2000-2011 1961-1969 1970-1979 2 All dollar figures throughout are US dollars. 6 resakss.org Sustaining SSA’s current growth rate of 3.2 percent will not be enough to allow the group of countries to reach the level of their 1960–1977 growth path by 2025: the projected 2025 GDP per capita value of $1,147, if current growth rates are maintained, represents only 62 percent of the projected value of $1,841 that would have been achieved if GDP per capita had grown continuously at the 1960–1977 rate. Reaching this level by 2025 would require more than doubling current growth rates, to an annual rate of 7.0 percent, as shown by the dashed line. This is unlikely to be accomplished, as only five African countries achieved a per capita GDP growth rate of over 5 percent during the 2000s. If growth continues at current rates, the group of countries will reach their 1960–1977 growth path only in 2066. Table 5.1 lists the maximum levels of per capita GDP achieved in 33 SSA countries during the 1960–1977 period and the 2000–2012 period. For 12 countries, the maximum recent level of GDP per capita is still lower than the maximum level of the 1960s and 1970s, indicating that not only have these countries not reached their projected levels had they remained on the post-independence growth path, they have not even matched the absolute levels achieved in the past. While some of these countries are close to meeting their past GDP per capita levels, several are very far off: the Democratic Republic of the Congo’s, Gabon’s, Liberia’s, and Niger’s maximum GDP per capita levels of the 2000s are only about half their maximum levels of the 1960s and 1970s, or less. Trends in labor productivity are just as striking. Of the 21 SSA countries with available data, 9 have not surpassed their labor productivity levels of earlier decades (Table 5.2). As is to be expected, there is significant overlap between the lists of countries that lag behind their past levels of GDP per capita and of those that lag behind their past labor productivity levels. As in the previous table, the Democratic Republic of the Congo and Nigeria show current levels of labor productivity that are far below the levels of the 1960s. FIGURE 5.4—AFRICA HAS NOT RECOVERED THE GROUND LOST IN EARLIER DECADES Source: Authors’ calculations using data from World Bank (2014a). Note: SSA = Africa south of the Sahara. 400 600 800 1000 1200 1400 1600 1800 2000 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 Per capita GDP (2005 constant $US, 27 SSA countries average) Actual and 2000s trend for the future 1960-1977 growth path Catching-up scenario 60-77, 1.97% annual growth rate 3.2% annual growth rate 7.0% annual growth rate $694 $1,147 $1,841 http://www.resakss.org 2014 ReSAKSS Annual Trends and Outlook Report 7 Max in 1960–1977 Max in 2000–2012 Level of annual per capita GDP in 2000–2012 is higher than in the past Benin 451 568 Yes Botswana 1,440 6,684 Yes Burkina Faso 244 495 Yes Burundi 203 153 Cameroon 838 964 Yes Central African Republic 499 472 Chad 565 738 Yes Congo, Dem. Rep. 485 165 Congo, Rep. 1,379 1,944 Yes Côte d’Ivoire 1,659 1,014 Gabon 12,452 6,709 Gambia 444 467 Yes Ghana 512 724 Yes Guinea-Bissau 438 436 Kenya 495 595 Yes Lesotho 393 929 Yes Liberia 728 276 Madagascar 501 302 Malawi 220 250 Yes Mali 372 498 Yes Mauritania 821 835 Yes Mauritius 2,012 6,496 Yes Niger 560 290 Nigeria 876 1,072 Yes Max in 1960–1977 Max in 2000–2012 Level of annual per capita GDP in 2000–2012 is higher than in the past Rwanda 228 390 Yes Senegal 874 800 Sierra Leone 432 435 Yes South Africa 5,136 6,003 Yes Sudan 565 837 Yes Swaziland 1,196 2,451 Yes Togo 478 413 Yes Zambia 1,085 798 Zimbabwe 733 681 Source: Authors’ calculations using data from World Bank (2014a). TABLE 5.1—COMPARISON OF MAXIMUM-LEVEL ANNUAL PER CAPITA GDP (constant 2005 USD) IN THE PAST AND PRESENT 8 resakss.org TABLE 5.2—COMPARISON OF MAXIMUM-LEVEL ANNUAL LABOR PRODUCTIVITY IN THE PAST AND PRESENT (1990 USD) Max in 1960s Max in 1970s Max in 1980s Max in 1990s Max in 2000–2014 2000s is higher than the past Angola 4,353 4,793 2,618 2,506 4,896 Yes Burkina Faso 1,744 1,852 2,277 2,522 3,838 Yes Cameroon 2,329 2,901 4,668 3,385 3,060 Congo, Dem. Rep. 4,510 5,551 5,653 3,791 3,408 Côte d’Ivoire 2,266 2,406 1,813 1,617 957 Ethiopia 1,483 1,582 1,512 1,305 2,305 Yes Ghana 4,080 4,061 2,719 3,264 4,976 Yes Kenya 2,522 3,087 3,417 3,448 3,397 Madagascar 2,759 2,900 2,512 1,952 1,785 Malawi 1,166 1,689 1,517 1,486 1,829 Yes Mali 1,855 2,821 2,557 2,795 3,545 Yes Mozambique 3,944 4,416 2,958 3,735 8,128 Yes Niger 2,658 2,514 2,416 1,680 1,764 Nigeria 2,254 3,651 3,491 3,468 6,620 Yes Senegal 6,418 6,190 4,701 4,166 4,710 South Africa 11,563 14,798 16,086 13,158 17,110 Yes Sudan 4,479 5,078 4,131 4,166 6,782 Yes Tanzania 1,351 1,468 1,397 1,497 2,380 Yes Uganda 2,394 2,384 1,757 2,180 3,632 Yes Zambia 3,688 3,553 3,071 2,723 3,565 Zimbabwe 3,404 4,532 4,396 4,040 3,856 Source: Authors’ calculations using data from Conference Board (2015). Note: Data are in 1990 US dollars, converted at Geary-Khamis purchasing power parities. http://www.resakss.org 2014 ReSAKSS Annual Trends and Outlook Report 9 We also assess the quality of growth in agriculture, which is the largest sector in terms of employment in most African countries and still accounts for the largest share of GDP in some countries. Sustaining rapid agricultural growth is the most effective way to reduce poverty, and agricultural growth plays an important role in stimulating growth in the wider economy (Diao et al. 2012). Recent agricultural labor productivity growth has also not made up for the ground lost in previous decades. The group of 38 countries with available data shown in Figure 5.5 exhibit trends similar to the per capita GDP growth trends shown in Figure 5.4: substantial agricultural labor productivity growth during the years after independence was followed by steady declines that more than erased the gains made during the 1960s. The turning point where agricultural labor productivity turned positive again occurred in the mid-1980s, a decade earlier than the lowest GDP per capita level registered by the group of countries shown in Figure 5.4. This suggests that, in Africa, agricultural growth may have affected overall economic growth with a lag. If agricultural labor productivity continues to grow at its average rate of the 2000s, 1.2 percent, the projected labor productivity level of $790 in 2025 will still be more than 40 percent lower than it would have been if African countries had been able to maintain their 1960s growth rate of 1.1 percent throughout the following decades. Reaching the 1960s growth path by 2025 would require sustaining annual average growth rates of 3.8 percent; however, only seven African countries achieved or surpassed this growth rate during the 2000s. If the current growth rate of 1.2 percent is maintained, it will take more than six centuries to reach the 1960s growth path. This reality highlights 400 500 600 700 800 900 1,000 1,100 1961 1964 1967 1970 1973 1976 1979 1982 1985 1988 1991 1994 1997 2000 2003 2006 2009 2012 2015 2018 2021 2024 A gr ic ul tu ra l O ut p ut P er W or ke r ( 20 04 -0 6 co ns ta nt $ ) Level of Africa's agricultural labor productivity Ag output per worker actual, SSA-ZAF 1960s growth path $612 $790 $1,135 1.1% annual growth rate 1.2% annual growth rate 3.8% annual growth rate $930 FIGURE 5.5—AFRICA’S AGRICULTURAL PRODUCTIVITY GROWTH HAS NOT MADE UP FOR LOST DECADES Source: Authors’ calculations using data from Nin-Pratt (2015) (the original data are from the Food and Agriculture Organization of the United Nations). Note: SSA-ZAF = Africa south of the Sahara, not including South Africa. 10 resakss.org the imperative of significantly increasing efforts to boost agricultural sector productivity by successfully implementing the Comprehensive Africa Agriculture Development Programme (CAADP) agenda and achieving the key Malabo targets. One factor contributing to the challenge of increasing agricultural labor productivity growth is the higher growth rate of the rural population and hence of the agricultural labor force, which has averaged 2.2 percent per year from 2000 to 2011, compared to 1.9 percent during the 1960s. As Nin-Pratt and Yu (2008) point out, total factor productivity growth in SSA is primarily a result of catching up to the frontier; as a result, agricultural growth is likely to slow in the future unless African countries pursue aggressive strategies to accelerate innovation along the agricultural value chain. Significantly increasing the labor productivity growth rate seems unlikely without moving more labor out of agriculture: South Africa was able to achieve a 3.0 percent annual agricultural productivity growth rate from 1961 to 2011, but its agricultural labor force fell by 1.2 percent yearly throughout the period. The paper by Badiane and McMillan analyzes sectoral employment dynamics since the early 2000s and shows that labor migration has started to move in a direction that is growth enhancing. The paper also shows that much needs to be done within and outside the agricultural sector to accelerate and deepen the growth- enhancing structural transformation that is currently ongoing. Additional efforts to improve agricultural productivity must include increasing access to improved inputs, information, finance, and markets, among other factors. China’s experience, where fairly flat growth in the 1960s and 1970s gave way to extremely rapid and sustained growth in later decades, stands in sharp contrast to Africa’s. More than that of any other developing country or region, the example of China demonstrates that it is possible to manage the develop- ment process such as to achieve dramatic improvements in living standards and reductions in poverty in the space of a generation. We will explore some of the reasons for the contrast between China’s and Africa’s experiences later in the chapter. Here we compare Africa’s failure to fully recover from decades FIGURE 5.6—CHINA’S PER CAPITA GDP GROWTH Source: Authors’ calculations based on World Bank (2015). $3,583 $421 0 500 1000 1500 2000 2500 3000 3500 4000 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 China per capita GDP (2005 US$) Actual 1960s growth path 2.8% annual growth rate 7.4% average annual growth rate http://www.resakss.org 2014 ReSAKSS Annual Trends and Outlook Report 11 of economic decline with China’s success. Figure 5.6 shows that China’s economic performance of the 1980s, 1990s, and 2000s was a marked shift away from stagnant per capita GDP rates to vigorous and dynamic growth. As a result, China’s GDP per capita in 2012 rose to more than eight times the level that would have been reached had the country continued growing at 1960s rates. The growth performance has been less dramatic in the agricultural sector, but here too the experience is in stark contrast to what has been observed among African countries. As shown in Figure 5.7, growth in Chinese agricultural productivity, proxied by agricultural value-added divided by rural population, did falter slightly in the 1970s compared to the previous decade, but the country’s later strong growth put it back onto the 1960s growth path. Actual agricultural productivity in 2012 ($608) barely differs from the level on the 1960 trajectory ($614). Is There Evidence of Convergence in Africa’s Recent Growth Recovery? We have shown that although growth in Africa is rapid, it has not made up for the stagnation of earlier decades: incomes and agricultural pro- ductivity remain far below the levels they would have achieved if African countries had remained on their 1960s growth paths. In this subsection, we analyze whether lower-income economies have been catching up with higher-income economies. We also compare convergence dynamics in Africa with the rest of the world. Convergence is a process through which lower-income countries catch up to higher-income countries by achieving faster growth rates. In the third section, we will examine the factors af- fecting the pace and extent of convergence across countries.3 We look for signs of convergence in order to evaluate the quality of growth in terms of poverty reduction: growth without convergence fails to increase the living standards of people in the poorest countries (relative to wealthier coun- tries) as quickly as growth with convergence. FIGURE 5.7—CHINA’S AGRICULTURAL PRODUCTIVITY GROWTH Source: Authors’ calculations based on World Bank (2015). $608 $614 0 200 400 600 800 1960 1963 1966 1969 1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005 2008 2011 China agricultural value added (2005 US$) / rural population Actual 1960s growth path 4.2% annual growth rate 3.8% average annual growth rate 3 For a discussion of the analysis of convergence and its determinants, see Barro and Sala-i-Martin (2004). 12 resakss.org Figure 5.8a illustrates convergence dynamics in terms of overall economic growth. The x-axis shows the log of GDP per worker in 1960 and the y-axis shows the average annual growth rate in GDP per worker for the 1960s. Figure 5.8b repeats the analysis for the 2000s. All countries with available data are included; African countries are represented by squares, and non-African countries are represented by circles. A trend line for all countries is shown by the dotted line. A process of convergence, in which poorer countries grow faster than richer countries and thus gradually close the gap between the two groups, would imply that countries with lower initial GDP levels (countries closer to the origin on the x-axis) would have higher growth rates, placing them higher or further away from the origin on the y-axis. It appears from Figure 5.8a that there was no such tendency toward convergence in the 1960s; indeed, countries that started the decade with lower levels of GDP per worker do not show higher rates of GDP growth than those that started off with higher levels of GDP.4 In contrast, Figure 5.8b shows that countries that began the decade of the 2000s with 4 Analyses of GDP levels and growth in the following decades (not shown) also reveal no signs of convergence between countries prior to the 2000s. FIGURE 5.8a—GROWTH WITH NO TENDENCY TOWARD CONVERGENCE IN THE 1960s Source: Authors’ calculations using data from Conference Board (2015). 1960s All countries Africa 2000-2014 All countries Africa y = 0.0879x + 2.7871 R² = 0.00032 -4.0 -2.0 0.0 2.0 4.0 6.0 8.0 10.0 2.5 3.0 3.5 4.0 4.5 5.0 A nn ua l G D P p er w or ke r, gr ow th ra te , 19 60 s Log of GDP per worker, 1960 y = -2.1673x + 11.199 R² = 0.17412 -4.0 -2.0 0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 2.5 3.0 3.5 4.0 4.5 5.0 A nn ua l G D P p er w or ke r, gr ow th ra te , 20 00 –2 01 4 Log of GDP per worker, 2000 http://www.resakss.org 2014 ReSAKSS Annual Trends and Outlook Report 13 lower levels of GDP per worker did tend to grow faster. The coefficient of the associated trend line is –2.2, indicating a clear negative relationship between initial GDP levels and subsequent growth. Several other trends are apparent from Figures 5.8a and 5.8b. During the 1960s, Africa’s position was not markedly different from that of other developing regions, as demonstrated by the number of non-African countries with levels of initial GDP per worker and rates of growth that were similar to those of African countries. However, by the 2000s, the distance between Africa and the rest of the world had increased, meaning that many African countries failed to move as far along the x-axis from the 1960s to the 2000s as did countries outside the continent. The lagging progress reflects the consequences of the economic stagnation and decline of the first three or four decades after independence. The ultimate impact is that, despite converging growth in the 2000s, GDP per worker in Africa has remained low compared to the rest of the world, which has experienced steadier growth over the entire five decades. FIGURE 5.8b—GROWTH SEEMS TO HAVE A TENDENCY TOWARD CONVERGENCE IN RECENT YEARS Source: Authors’ calculations using data from Conference Board (2015). 1960s All countries Africa 2000-2014 All countries Africa y = 0.0879x + 2.7871 R² = 0.00032 -4.0 -2.0 0.0 2.0 4.0 6.0 8.0 10.0 2.5 3.0 3.5 4.0 4.5 5.0 A nn ua l G D P p er w or ke r, gr ow th ra te , 19 60 s Log of GDP per worker, 1960 y = -2.1673x + 11.199 R² = 0.17412 -4.0 -2.0 0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 2.5 3.0 3.5 4.0 4.5 5.0 A nn ua l G D P p er w or ke r, gr ow th ra te , 20 00 –2 01 4 Log of GDP per worker, 2000 14 resakss.org Has There Been Convergence in Agricultural Growth? As agricultural labor productivity in Africa began its recovery before that of overall economic growth, it may be that convergence in the agricultural sector preceded convergence in the broader economy. The comparison of Africa’s agricultural productivity growth with that of other countries suggests that this is not the case. Figures 5.9a and 5.9b plot initial levels of log agricultural output per worker against average annual growth rates for the 1960s and 2000s, respectively. The figures indicate that there has been no apparent convergence in agricultural labor productivity, either in the 1960s or in the 2000s. In fact, countries with higher initial levels of labor productivity grew faster than those with lower productivity, as evidenced by the positive coefficients on the trend lines for both decades. Thus, gaps between labor productivity levels of different countries widened rather than narrowed. This widening of the productivity gap is the opposite of the convergence in the formal manufacturing sector documented by Rodrik (2013b). The non-convergence in agriculture is reflective of the extremely slow catch-up growth observed among African countries, as discussed in the preceding subsection. It may also be an additional reason for the lack of overall economic convergence observed across countries until the 2000s. The Evolution of Sector Governance and Economic Growth We have seen that Africa is still recovering from the economic decline of its lost decades, and in fact still has a long way to go even if current growth is maintained. The continent’s recent performance, while truly encouraging, is far from sufficient. Accelerating and sustaining the current growth recovery is a strategic imperative. This requires a better understanding of the drivers of recent growth, which in turn calls for an examination of the ways in which FIGURE 5.9a—AGRICULTURAL GROWTH WITH NO TENDENCY FOR CONVERGENCE IN THE 1960S Source: Authors’ calculations using data from Nin-Pratt (2015) (the original data are from the Food and Agriculture Organization of the United Nations). y = 2.2021x - 4.3347 R² = 0.18392 -10 -5 0 5 10 15 2 2.5 3 3.5 4 4.5 5 Log of agricultural output per worker, 1960 1960s All countries Africa y = 0.7242x + 0.1731 R² = 0.05991 -4 -2 0 2 4 6 8 10 2 2.5 3 3.5 4 4.5 5 A g ou tp ut / w or ke r a nn ua l g ro w th ra te , 2 00 0s Log of agricultural output per worker, 2000 2000s All countries Africa A g ou tp ut / w or ke r a nn ua l g ro w th ra te , 1 96 0s http://www.resakss.org 2014 ReSAKSS Annual Trends and Outlook Report 15 Africa has managed its growth process throughout the decades and the role played by key factors over time. Africa, unlike any other developing region, has struggled for decades to find the proper strategic approach and direction for economic policy design and sector governance. At the time when most countries gained independence, the economic development profession itself had an incomplete understanding of the growth process and hence of its proper management. Inadequate policy regimes in many African countries, based on still-forming development theory at the time and implemented by newly formed and underequipped bureaucracies, led to decades of widely shifting externally driven strategies. Economic growth and sector governance lacked the quality, consistency, and coherence necessary for successful outcomes. To highlight this fact, we compare the evolution of reforms and strategies pursued by African countries over the past six decades with the successful pacing and sequencing of reforms by China from the late 1970s to the present. As will be shown, the largely externally driven and hence rather volatile strategy regimes in Africa contrast starkly with regimes in China, where major policy reforms were primarily based on pragmatic domestic experimentation and carried out with a focus and gradualism that made adequate learning and timely course adaptation possible. The greatest challenge faced by African governments in managing the growth process was finding the right balance between agriculture and industry as the main drivers of growth, and between government and the private sector as key actors in regulating economic activity. Badiane and Makombe (2015) conceptualize these choices with the help of the diagram shown in Figure 5.10, where the x-axis represents the relative sector emphasis of strategy regimes between agriculture and industry and the y-axis the emphasis on government versus private-sector roles. The changing development paradigms and the strategies pursued by African and Chinese leaders can be placed on the diagram according to their emphasis along these two FIGURE 5.9b—AGRICULTURAL GROWTH WITH NO TENDENCY FOR CONVERGENCE IN 2000–2011 Source: Authors’ calculations using data from Nin-Pratt (2015) (the original data are from the Food and Agriculture Organization of the United Nations). y = 2.2021x - 4.3347 R² = 0.18392 -10 -5 0 5 10 15 2 2.5 3 3.5 4 4.5 5 Log of agricultural output per worker, 1960 1960s All countries Africa y = 0.7242x + 0.1731 R² = 0.05991 -4 -2 0 2 4 6 8 10 2 2.5 3 3.5 4 4.5 5 A g ou tp ut / w or ke r a nn ua l g ro w th ra te , 2 00 0s Log of agricultural output per worker, 2000 2000s All countries Africa A g ou tp ut / w or ke r a nn ua l g ro w th ra te , 1 96 0s 16 resakss.org dimensions. The point labeled “M” describes a strategy exhibiting no bias toward either the public or private sector nor toward industry or agriculture. Africa’s Shifting Development Strategies For each decade, the position of the main strategic thrust in the four quadrants of Figure 5.10 describes the relative biases of strategy choices along the agriculture versus industry axis and the government versus private sector axis. During the first decade of post-independence development, from the 1950s to the 1960s, many governments pursued industry-led, import-substitution-based strategies in which development of the industrial sector was to be driven by an active public sector and promoted through state enterprises operating behind import barriers and other forms of protection. Agriculture was seen as a source of resources to support industrialization. This was very much in line with the prevailing thinking of development theory around the time of independence. The bias toward industry emanated from the recognition that potential rates of growth were substantially higher in industry than in agriculture. Not well understood either in theory or practice at the time was the fact that industrial growth was only possible when fueled by faster agricultural growth.5 Import- substitution industrialization was consequently characterized by strong biases against agriculture and the private sector. Even in the agricultural sector, government was highly involved through parastatal organizations controlling the buying and selling of crops, including to foreign export markets, and the procurement and distribution of modern inputs: seeds, fertilizers, and pesticides. The parastatals also determined and enforced the prices of individual crops, which required the prohibition or heavy restriction of the selling, buying, or transportation of agricultural commodities by private- sector operators. Consequently, agriculture was subjected to heavy taxation, implicitly and explicitly, and considerable regulatory disruption, which survived the import-substitution industrialization strategy era and played a significant part in the poor performance of the sector and in the broader economic decline and stagnation referred to earlier.6 The import-substitution industrialization strategy’s emphasis on industry as the main source of growth and the very limited role accorded to the private sector place this stage in the upper right of the diagram in Figure 5.10. As would be discovered later, import-substitution industrialization strategies did not result in improved economic performance. Both agricultural growth and overall economic growth lagged badly in the ensuing decade. Rural-urban inequality increased as agriculture failed to grow, create wealth, and change living conditions in the rural areas, while the bias toward industry favored urban centers. In response to these developments, multilateral and bilateral development agencies, which had major influence on growth and development strategy choices, began to shift focus in the 1970s. Alarmed African governments also sought to boost agricultural production, particularly of food crops, in pursuit of the goal of food self-sufficiency. Import-substitution industrialization therefore gave way to integrated rural development projects, which aimed to improve rural 5 Johnston and Mellor (1961) had just published their pioneering work. 6 See Oyejide (1986), Tshibaka (1986), and Badiane and Kinteh (1994) for discussions of the negative effects of policy and trade regimes on agriculture in Nigeria, Zaire, and selected African countries, respectively. http://www.resakss.org 2014 ReSAKSS Annual Trends and Outlook Report 17 livelihoods by raising agricultural productivity as well as increasing access to education and health services among rural communities. Linked to integrated rural development is the basic human needs approach, which emphasized increasing incomes, ensuring access to social services, and increasing stakeholder participation in the planning of development programs. This translated into a heavy shift to the upper left quadrant of the diagram in Figure 5.10, with the focus moving away from industry toward agriculture. However, the role of government as the central development actor remained nearly intact. Many of the agricultural development projects pursued during the 1970s did not succeed due to their high costs, and education and health indicators did not improve despite the basic human needs approach. During the 1980s and 1990s, African develop- ment strategies underwent another major shift through the Structural Adjustment Programs (SAPs) promoted by the International Monetary Fund (IMF) and the World Bank. SAPs intended to accord a stronger role to markets and the private sector in regulating and operating economic activity. By seeking to correct the public-sector bias and its associated implicit and explicit taxation of agriculture, SAPs de facto tended to tilt the balance from industry and more in favor of agriculture. Agricultural policies promoted through SAPs included reducing the role of marketing boards and parastatals, liberalizing input and output markets by reducing fertilizer subsidies, limiting price intervention, and reducing overvalued exchange rates. These changes resulted in rising outputs of FIGURE 5.10—GROWTH AND POVERTY REDUCTION STRATEGIES IN AFRICA: CONSTANTLY CHANGING PARADIGMS Source: Badiane and Makombe (2015). Note: CAADP = Comprehensive Africa Agriculture Development Programme; PRSP = Poverty Reduction Strategy Paper; SAPs = Structural Adjustment Programs. 18 resakss.org export crops in some countries, but in many others the supply response was smaller than anticipated. Because of heavy cuts in government expenditures, complementary investments in agricultural technology, infrastructure, and market institutions were not made at that time. It could also be that economies needed more time to respond to the far-reaching changes along with the complex ramifications that emerged. At any rate, it was clear that the reforms that were carried out did not result, as hoped for, in overall improved economic growth and poverty reduction in the 1980s and early 1990s.7 The failure to make progress in reducing poverty and recognition of the lack of country participation in the SAPs led in the late 1990s to another major qualitative shift, to the Poverty Reduction Strategy Paper (PRSP) approach. Under the PRSPs, countries set out the policy reforms they intended to implement to promote growth and reduce poverty in a participatory process involving domestic civil society organizations as well as the World Bank and IMF. Unlike the SAPs, the PRSPs put social sectors clearly, either by design or de facto, at the fore. The PRSPs maintained the SAPs’ emphasis on the private sector and markets but shifted the focus of development strategies further toward the rural sector, recognizing agriculture as a key sector to lead broad-based growth and poverty reduction. However, this recognition did not initially lead to increased investments in agriculture. Moreover, many of the SAP agricultural policies were maintained in PRSPs, and country participation was more limited in general than intended. By the end of the millennium, the four decades of searching for effective development strategies that would produce decent growth and generate real economic and social progress had failed to meet the hopes and aspirations of people in Africa. Despite good, and in some cases better, prospects than other developing regions at the time of independence, Africa was now lagging behind badly in nearly all measures of economic and human development. The costs and controversies associated with SAPs and the limited success of PRSPs severely curtailed the propensity of global development organizations, multilateral as well as bilateral, to venture into major agenda-setting efforts. The time also coincided with important leadership changes at the continental level. Presidents Thabo Mbeki of South Africa, Olusegun Obasanjo of Nigeria, Abdoulaye Wade of Senegal, and Abdelaziz Bouteflika of Algeria all came to power around that time with an ambitious pan- African agenda. They launched a continent-wide initiative under the leadership of the African Union Commission (AUC) called the New Partnership for Africa’s Development (NEPAD). Through it, they sought to reform the relationship between the global development community and Africa and put African countries in a stronger leadership position in deciding the continent’s future development agenda. A centerpiece of their efforts was the demand for greater commitment to and accountability for improved political and economic governance on the part of African governments (AUC 2001). Under NEPAD, African countries initiated, in 2003, the Comprehensive Africa Agriculture Development Programme (CAADP), which shifted the emphasis further toward agriculture. Because of the relevance of China’s experience for the implementation of this program, we will return to the discussion of CAADP after the review of Chinese reforms in the agricultural sector in the next subsection. 7 The fact that the reforms called for were not fully implemented in many countries makes the assessment of SAPs in general a rather difficult exercise (Jayne et al. 2002). http://www.resakss.org 2014 ReSAKSS Annual Trends and Outlook Report 19 Reforming Agricultural and Rural Development Strategies: The Chinese Experience To see what a more consistent and coherent approach toward policy and strategy development for economic transformation in general and agricul- tural and rural-sector growth in particular might have accomplished, we examine the China example. In the 1960s and 1970s, China had far lower GDP per capita and much higher poverty than Africa. Like Africa, it faced a daunting reform agenda. But the reform process in China proceeded much differently from that in Africa, and had far different impacts. China’s reform process was characterized by gradualism, country ownership and leader- ship, and the use of evidence to guide policies (Chen, Hsu, and Fan 2014). Reforms followed a careful trial-and-error process in which successful local experiments were scaled up and unsuccessful initiatives were abandoned. Political support and ownership of reforms were bolstered by the gradual- ism of the process and the use of evidence. The reform process followed an agriculture-based “firing from the bottom” approach, in which a focus on agriculture preceded reforms in manufacturing and later services. The initial emphasis on agriculture helped enable the large-scale poverty reduction that accompanied growth. Four stages in China’s reform process can be distinguished based on the analysis by Chen, Hsu, and Fan (2014). In the first stage, from 1978 to 1984, agricultural reforms were implemented that greatly increased incentives for producers. Government procurement prices were increased, central control of some production decisions was relaxed, and, perhaps most importantly, agriculture was decollectivized with the implementation of the household responsibility system, under which individual households were given more control over land and production. The government also invested in agricultural research and development and the development and dissemination of improved seed varieties, which contributed to agricultural growth, poverty reduction, and rising rural incomes. This stage of reform was strongly focused on agriculture and retained a major role for the government, placing it in the upper left of the diagram in Figure 5.11: although market forces were given a larger role in influencing production and resource allocation decisions, the environment was still heavily controlled by the government. The second stage of reform, from 1985 to 1993, included further liberalization of agricultural output markets, with a shift from procurement quotas to contracts, as well as fertilizer market liberalization. Rural incomes continued to grow, and the increased availability of labor and capital resources resulted in a rapid expansion of the rural nonfarm sector. Township and village enterprises flourished. This stage of reform represents a shift downward and to the right in the diagram: reforms constituted a step toward more market-based systems, but government maintained its role as the main economic player. The proliferation of township and village enterprises represented a widening of focus to the nonfarm economy, but agriculture remained the central area of policy reforms. During the third stage of reform, from 1994 to 2001, the government maintained control in strategic sectors while liberalizing others. Special Economic Zones were created and foreign direct investment (FDI) was liberalized. Nonstate enterprises were permitted to play a larger role in agricultural trade. Increasingly open trade policies and decreased protectionism led to a major expansion of trade and an increase in the contribution of trade to GDP (Fan, Gulati, and Dalafi 2007). These changes moved the systems further toward greater private-sector participation. 20 resakss.org In the fourth stage of reform, from 2002 to the present, the procurement system was ended and grain markets were completely liberalized. Agricultural taxes were progressively reduced and income transfers to farmers were initiated. Land reforms were enacted to further increase tenure security. Protectionist trade policies continued to be eased (Fan, Gulati, and Dalafi 2007). Infrastructure expansions were financed by both public and private investments. Both the third and fourth stages saw the focus of policy reforms shift even more strongly toward markets and the private sector. The Chinese reform process has been characterized by gradualism and the sequencing of reforms, resulting in a coherent shift in focus that has unfolded over decades. Subsequent reforms built on the accomplishments of previous reforms. This approach was permitted by a reliance on smaller-scale experimentation to produce the evidence needed for the decision to scale up to the national level. The country needed nearly three decades to gradually transition toward a more open, private-sector-led, and market-based system. The process was accompanied by careful sequencing and targeting of institutional reforms and public investments. As reflected in Figures 5.12a and 5.12b, institutional reforms provided the largest boost to growth and poverty reduction in the earlier period. When the strongest effects of the reforms were largely played out, rising government investments in the subsequent period deepened the initial responses and extended their impact further (Fan, Zhang, and Zhang 2004). The Chinese experience therefore represents a major contrast with Africa’s multiple abrupt changes of focus. However, Africa seems to have found a more successful approach during the FIGURE 5.11—POLICY AND STRATEGY COHERENCE AND CONSISTENCY: CHINA Source: Badiane and Makombe (2015). Note: CAADP = Comprehensive Africa Agriculture Development Programme; PRSP = Poverty Reduction Strategy Paper; SAPs = Structural Adjustment Programs. http://www.resakss.org 2014 ReSAKSS Annual Trends and Outlook Report 21 current period. After decades of shifting priorities based on externally driven policies, in the early 2000s African countries seized the leadership role in for- mulating the continent’s development strategies. As indicated earlier, African leaders, in 2003, adopted CAADP as the main framework for agriculture-led development and poverty reduction. Unlike previous strategies, CAADP is a homegrown initiative that emphasizes broad-based participation of stake- holders from the public and private sectors, farmers’ groups, civil society, and donors in policy planning, implementation, and review (NEPAD 2003). The CAADP’s emphasis on regular review and mutual accountability and the use of evidence and analysis to guide policymaking represent important improvements over past development initiatives. CAADP acknowledges the central role of the private sector in agricultural develop- ment but advocates a strong role for governments to play in increasing agricultural investment and creating an enabling environment for agri- cultural growth and private-sector involvement. The current approach to development strategy places agriculture at the center, recognizing the special importance of agricultural growth in poverty reduction as well as its contribution to overall economic growth, but it also calls for much greater balance between government and private-sector roles than earlier strategies. More than ten years after the launch of CAADP, the focus on agricultural production and investments and the principles of inclusivity and mutual accountability seem to be showing the staying power needed to bring results FIGURE 5.12a—SOURCES OF CHINA’S AGRICULTURAL GROWTH Source: Authors’ construction based on data from Fan, Zhang, and Zhang (2004). Fan, Zhang, and Zhang (2004) estimated the effects of different categories of public investments on poverty and growth at the provincial level, using a simultaneous equations approach to account for the endogeneity of the variables affecting economic outcomes. Year dummies were used to proxy the year-specific effects of institutional reforms. -10 0 20 40 60 Institutional reforms Public investment Other Percent 1978-1984 1985-2000 -20 0 80 60 100 Percent 40 20 Institutional reforms Public investment Other 1978-1984 1985-2000 80 FIGURE 5.12b—SOURCES OF CHINA’S POVERTY REDUCTION Source: Authors’ construction based on data from Fan, Zhang, and Zhang (2004). Fan, Zhang, and Zhang (2004) estimated the effects of different categories of public investments on poverty and growth at the provincial level, using a simultaneous equations approach to account for the endogeneity of the variables affecting economic outcomes. Year dummies were used to proxy the year-specific effects of institutional reforms. Note: The estimated impacts of reforms on poverty reduction are those arising from increased agricultural productivity; other possible avenues are not included. -10 0 20 40 60 Institutional reforms Public investment Other Percent 1978-1984 1985-2000 -20 0 80 60 100 Percent 40 20 Institutional reforms Public investment Other 1978-1984 1985-2000 80 22 resakss.org on the ground. The renewed Malabo commitments and the next ten years of CAADP will be at the center of efforts to sustain and accelerate the recovery and further improve growth and poverty outcomes. Empirical Analysis of Drivers of Growth in Africa In the preceding sections, we have seen that Africa’s growth recovery, although impressive, has still not been sufficient to put the continent back onto its growth trajectory of the 1960s. Signs of convergence between Africa and the rest of the world only begin to appear in the 2000s. It is clear that the recent growth recovery should be seen in relative terms; it is a welcome departure from the stagnation and decline of the preceding period, but in order to fully recover from its lost decades Africa must sustain and even accelerate growth. In this section, we investigate the role of policy-related variables and other drivers of Africa’s recent growth in order to identify the factors that governments should take into consideration when planning future growth strategies. We empirically test for the existence of growth convergence, both at the global level and among African countries. Evidence of convergence within Africa would indicate that the continent experienced broad, high- quality growth with a positive effect on poverty. We apply the convergence model developed by Barro and Sala-i-Martin (2004), with the log of GDP per capita as the dependent variable. Using 1990 as the initial period, we compare Africa’s experience to that of Latin America and the Caribbean and East Asia and the Pacific, as well as the world as a whole. The estimation captures how relative per capita GDP growth across countries in later years is affected by the initial level of per capita GDP in 1990, as well as other relevant variables. A positive and significant coefficient on the initial GDP per capita variable would indicate that countries with lower initial incomes experienced faster growth over the period than countries with higher initial incomes, and therefore that convergence took place. The other variables selected are those likely to affect economic growth and the pace of convergence. The variables and data sources are detailed in Table 5.3. Relatively low and stable inflation is an important element of macroeconomic stability and represents an important pathway for macroeconomic reforms to positively affect growth. Data on inflation are from the IMF’s World Economic Outlook database (IMF 2015) and show year-on-year percentage changes in average consumer prices. Savings, FDI, and official development assistance (ODA) are included to reflect the effects of the availability of financing for investment from these sources. Data on FDI and savings are from the World Bank’s World Development Indicators (WDI) and are expressed as shares of GDP (World Bank 2015). Data on ODA are from the Organization for Economic Co-operation and Development (OECD) Creditor Reporting System and show gross disbursements of ODA to each recipient country in constant 2013 million US dollars (OECD 2015). We include three types of ODA, classified by sector. ODA 100 refers to ODA for “social infrastructure and services,” including education, health, water and sanitation, and government and civil society. ODA 200 refers to ODA for “economic infrastructure and services,” including transport and storage, communications, energy, banking and financial services, and business services. ODA 300 refers to ODA for “production sectors,” including agriculture, industry, mining, construction, and trade. These three types of ODA represent 51.4 percent of the total ODA received by African countries during the period of analysis. We do not include other types of ODA, such as humanitarian aid, assistance to refugees in donor countries, administrative http://www.resakss.org 2014 ReSAKSS Annual Trends and Outlook Report 23 costs of donors, general program assistance, and so on. Variables from the World Bank’s Worldwide Governance Indicators (WGI) are added in order to examine how changes in different aspects of governance and institutional quality have affected growth. The WGI are expressed in standard normal units, with most values falling between -2.5 and 2.5 and higher values indicating better outcomes. Each indicator is constructed from multiple data sources and expresses the perceptions of households, firms, and other organizations regarding different areas of governance. The WGI we include are as follows: • Voice and Accountability (VA) represents “perceptions of the extent to which a country’s citizens are able to participate in selecting their government, as well as freedom of expression, freedom of associa- tion, and a free media.” • Government Effectiveness (GE) represents “perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pres- sures, the quality of policy formulation and implementation, and the credibility of the government’s commitment to such policies.” TABLE 5.3—VARIABLES INCLUDED IN THE ECONOMETRIC MODEL Variable Description Source Log GDP per capita Log of GDP per capita, constant 2005 USD World Bank (2015) Log GDP per capita, 1990 Log of 1990 GDP per capita, constant 2005 USD World Bank (2015) Inflation Inflation, average consumer prices, percent change IMF (2015) Savings Gross domestic savings, percent of GDP World Bank (2015) FDI Net inflows of foreign direct investment, percent of GDP World Bank (2015) ODA 100 ODA for social infrastructure and services (health, education, etc.), gross disbursements, million 2013 USD OECD (2015) ODA 200 ODA for economic infrastructure and services (transport and storage, communications, energy, etc.), gross disbursements, million 2013 USD OECD (2015) ODA 300 ODA for production sectors (agriculture, industry, mining, etc.), gross disbursements, million 2013 USD OECD (2015) Voice and Accountability (VA) Perceptions of participation and freedom of expression and association, standard normal units World Bank (2014b) Government Effectiveness (GE) Perceptions of the quality of public services and policymaking, standard normal units World Bank (2014b) Regulatory Quality (RQ) Perceptions of the quality of regulations for private-sector development, standard normal units World Bank (2014b) Rule of Law (RL) Perceptions of the quality of law enforcement and likelihood of crime, standard normal units World Bank (2014b) Control of Corruption (CC) Perceptions of the absence of large- and small-scale corruption, standard normal units World Bank (2014b) Life expectancy Life expectancy at birth World Bank (2015) Schooling Average total years of schooling, population age 15 and over Barro and Lee (2014) Rain Annual rainfall, mm CRU and Harris (2014) Natural resource export share Share of fuel, ore, and mineral exports in total merchandise exports (percent) World Bank (2015) Manufacturing export share Share of manufacturing exports in total merchandise exports (percent) World Bank (2015) Source: Authors. Note: CRU = University of East Anglia Climatic Research Unit; FDI = foreign direct investment; IMF = International Monetary Fund; ODA = official development assistance; OECD = Organization for Economic Co-operation and Development. 24 resakss.org • Regulatory Quality (RQ) shows “perceptions of the ability of the gov- ernment to formulate and implement sound policies and regulations that permit and promote private sector development.” • Rule of Law (RL) shows “perceptions of the extent to which agents have confidence in and abide by the rules of society, and in particular the quality of contract enforcement, property rights, the police, and the courts, as well as the likelihood of crime and violence.” • Control of Corruption (CC) shows “perceptions of the extent to which public power is exercised for private gain, including both petty and grand forms of corruption, as well as ‘capture’ of the state by elites and private interests.” (Kaufmann, Kraay, and Mastruzzi 2010, 4)8 We include variables representing human capital, with average life expectancy proxying general improvements in health, and average years of schooling capturing improvements in educa- tional attainment. Data on these two indicators are from the World Bank WDI and from the Barro and Lee Educational Attainment dataset, respectively. To examine the possible roles of exports and export composition in growth, and to explore the effects of reliance on natural resources, we use data from the World Bank WDI on natural resource exports (including oil and mining exports) as a share of merchandise exports and manufacturing exports as a share of merchandise exports. We also interact the natural resource export share with inflation to capture the effects of inflation associ- ated with rapid rises in natural resource exports. 8 We do not include the “political stability and absence of violence/terrorism” indicator, as this indicator expresses perceptions of likelihood of violence but does not accurately correspond to actual violence and instability. FIGURE 5.13—CONSUMER PRICE INFLATION, 1970–2013 Source: Authors’ calculations using data from World Bank (2015). Note: Includes 24 countries with data for most years in the period. Two outliers with very high inflation in the mid-1990s, the Democratic Republic of the Congo and Angola, are excluded. 0 5 10 15 20 25 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 http://www.resakss.org 2014 ReSAKSS Annual Trends and Outlook Report 25 FIGURE 5.14—SAVINGS AND FOREIGN DIRECT INVESTMENT (FDI) AS A PERCENTAGE OF GDP, 1990–2013 Source: Authors’ calculations using data from World Bank (2015). Note: Savings as a percentage of GDP is shown on the left axis; FDI as a percentage of GDP is shown on the right axis. 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 0 5 10 15 20 25 30 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Savings FDI FIGURE 5.15—OFFICIAL DEVELOPMENT ASSISTANCE (ODA) DISBURSEMENTS TO AFRICA, 2002–2013 Source: Authors’ calculations using data from OECD (2015). Note: ODA 100 refers to ODA for social infrastructure and services, ODA 200 is for economic infrastructure and services, and ODA 300 is for productions sectors. 0 5000 10000 15000 20000 25000 30000 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 ODA 100 ODA 200 ODA 300 Finally, we include data on rainfall from the University of East Anglia Climatic Research Unit (CRU), in recognition of the important role that climate can play in growth, particularly in econo- mies where agriculture plays a prominent role. Trends in Key Variables Affecting Growth A look at the variables used shows that many factors have improved over time to boost the pace of growth among African economies. Inflation and other indicators of macroeconomic stabil- ity have improved markedly in the past several decades (Figure 5.13). This may be partially or largely the result of the reforms first implemented through the SAPs in the 1980s and 1990s. As far as financing is concerned, Figure 5.14 shows that savings as a share of GDP (measured on the left axis) declined during most of the 1990s but rose thereafter, albeit unevenly. The share of FDI in GDP (measured on the right axis) rose sharply throughout the 1990s and most of the 2000s, from less than 0.5 percent in 1990 to nearly 4 percent in 2007. Recently the FDI share has declined again in the aftermath of the global financial and commodity market crises, reaching 2.1 percent in 2013. ODA also rose significantly during the 2000s (Figure 5.15). Of the three types of ODA we examine, ODA for social 26 resakss.org infrastructure and services started at the highest level in 2002 (the first year for which data are avail- able) and more than doubled, to almost $25 billion by 2013. The other two types of ODA also increased considerably, more than tripling in the case of economic infrastructure and services. A final indicator of the additional revenues available to African countries during the recovery period is the share of natural resource exports in GDP (Figure 5.16). This share also increased sharply during the 2000s, rising from an average of 9 percent in 1997 to almost 20 percent in 2008. Governance indica- tors improved, but not markedly, over the late 1990s and 2000s (Figure 5.17). The Government Effectiveness (GE) and Control of Corruption (CC) indicators fell slightly over the period. The Rule of Law (RL) and particularly the Voice and Accountability (VA) indicators ended the period at higher values than initially, but rose and fell slightly several times. The Regulatory Quality (RQ) indicator also rose and fell several times and ended the period at a level similar to the initial level. Empirical Findings The results of our analysis are presented in Table 5.4. They indicate that significant convergence took place when the role of policy-related and other variables is taken into consideration. FIGURE 5.17—CHANGE IN GOVERNANCE INDICATORS, 1996–2013 Source: World Bank (2014b). Note: Values represent average for African countries, weighted by population. CC = Control of Corruption; GE = Government Effectiveness; RL = Rule of Law; RQ = Regulatory Quality; VA = Voice and Accountability. -0.95 -0.9 -0.85 -0.8 -0.75 -0.7 -0.65 -0.6 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 VA GE RQ RL CC FIGURE 5.16—NATURAL RESOURCE EXPORTS AS A SHARE OF GDP, 1997–2008 Source: Authors’ calculations based on data from World Bank (2014a). 0 5 10 15 20 25 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 http://www.resakss.org 2014 ReSAKSS Annual Trends and Outlook Report 27 Africa LAC EAP SA World Variables Dependent variable: Log GDP per capita (1990–2013) Log GDP per capita, 1990 –0.00516*** –0.01842*** –0.01500 –0.00289 –0.00935*** (0.00168) (0.00403) (0.02005) (0.00540) (0.00143) Inflation –0.00011*** –0.00011* 0.00045** –0.00020 –0.00003 (0.00004) (0.00005) (0.00017) (0.00018) (0.00003) Savings 0.00005* 0.00019*** 0.00025*** 0.00054** 0.00012*** (0.00003) (0.00005) (0.00008) (0.00023) (0.00003) ODA 100 (Social) 0.00501*** 0.00099 –0.00085 0.00691*** 0.00459*** (0.00152) (0.00328) (0.00233) (0.00164) (0.00113) ODA 200 (Economic) 0.01285*** –0.00558* –0.00048 0.01400*** 0.00286*** (0.00205) (0.00379) (0.00172) (0.00340) (0.00092) ODA 300 (Production) 0.00514** 0.00049 –0.02004*** –0.01933*** –0.00200 (0.00247) (0.00427) (0.00716) (0.00534) (0.00248) FDI 0.00009** 0.00019** 0.00031** 0.00004 0.00010** (0.00004) (0.00010) (0.00018) (0.00073) (0.00005) VA –0.00084 0.00370 0.00363** 0.00523 –0.00094 (0.00098) (0.00202) (0.00263) (0.00323) (0.00097) GE 0.00024 0.00073 0.00623 0.01056* 0.00378*** (0.00151) (0.00188) (0.00371) (0.00618) (0.00129) RQ 0.00051 0.00190 0.00103 0.00169 0.00278** (0.00123) (0.00148) (0.00332) (0.00454) (0.00109) RL 0.00296** 0.00100 0.00603*** –0.01317*** –0.00178 (0.00138) (0.00184) (0.00302) (0.00452) (0.00115) CC 0.00373*** 0.00128 –0.00038 0.01025*** 0.00172* (0.00111) (0.00159) (0.00257) (0.00359) (0.00101) Africa LAC EAP SA World Variables Dependent variable: Log GDP per capita (1990–2013) Life expectancy 0.00022** 0.00395*** 0.01195*** 0.00383*** 0.00078*** (0.00009) (0.00034) (0.00092) (0.00079) (0.00010) Schooling 0.00269*** 0.00157** –0.00362*** –0.00268 0.00374*** (0.00040) (0.00061) (0.00094) (0.00195) (0.00034) Rain –1.41E-06 –1.44E-06** 1.27E-06 –9.94E-07 –1.30E-06* (1.37E-06) (7.07E-07) (1.84E-06) (1.29E-06) (7.12E-07) Resource export share 3.74E-06 –0.00003 –0.00020*** –0.00071* 0.00003* (0.00002) (0.00003) (0.00010) (0.00040) (0.00002) Inflation* resource share 3.68E-06** 3.91E-06** –1.79E-06 0.00005 3.80E-07 (1.46E-06) (1.58E-06) (5.02E-06) (3.01E-05) (8.99E-07) Manufacturing export share 7.39E-07 5.19E-06 0.00012 –0.00018 –0.00002 (0.00002) (0.00002) (0.00006) (0.00013) (0.00002) Constant 0.01538 –0.14140*** –0.68895*** –0.19496*** –0.00055 (0.01156) (0.03528) (0.15296) (0.06188) (0.01189) Observations 331 235 94 51 830.0 χ2 (18) 443.1 992.7 640.6 895.0 1056.6 Log likelihood 1420.9 209.3 387.7 237.2 3261.1 Source: Authors’ estimation results. Notes: *** significant at 0.01 level; ** significant at 0.05 level; * significant at 0.10 level. Standard errors given in parentheses. CC = Control of Corruption; EAP = East Asia and the Pacific; FDI = foreign direct investment; GE = Government Effectiveness; LAC = Latin America and the Caribbean; ODA = official development assistance; RL = Rule of Law; RQ = Regulatory Quality; SA = South Asia; VA = Voice and Accountability. TABLE 5.4— ESTIMATION RESULTS 28 resakss.org Countries with lower initial levels of per capita GDP grew faster, indicating that lagging economies began to catch up with leading economies. The growth recovery in Africa has therefore been effective at raising incomes in the poorest countries. Evidence of convergence was also found in the world as a whole and in Latin America and the Caribbean, but at faster rates than in Africa: 5.1 percent, 6.0 percent, and 4.7 percent for the world, Latin America and the Caribbean, and Africa, respectively. This estimation analyzes convergence over the 1990–2013 period. Results using 2000 as the starting year are similar (not shown). As shown in the table, convergence is affected by a host of variables, in addition to the initial level of GDP per capita. Inflation, for instance, was found to negatively affect per capita GDP growth in Africa, while ODA and the shares of FDI and savings as a percentage of GDP had a positive effect. The more moderate levels of inflation and overall improved macroeconomic stability clearly did contribute to Africa’s growth recovery, suggesting that SAPs may have produced positive growth effects but with a significant time lag (Badiane and Makombe 2015). The effect of savings was positive and significant. However, both the significance and the magnitude were lower in Africa than in the other regions and in the world as a whole. Africa’s average share of savings in GDP was lower than that of the other regions. The effect of FDI in Africa was larger and more significant than that of savings but was still lower than that in most other regions and the world as a whole. Despite the rapid rise in FDI in Africa over the period, average levels remained lower than those of most other regions; FDI may prove to have a larger effect on economic growth as levels increase to match those of other developing regions. The effects of FDI, as well as of ODA, also depend on other factors, including institutional quality and human capital levels in the receiving country. All three types of ODA examined have had a significant positive effect on growth, particularly the “economic infrastructure and services” category. This category includes much of what is commonly referred to as infrastructure, such as transport, storage, and communications, as well as financial and other business services. Disbursements of each type of ODA increased considerably throughout the recovery period, but the amount of ODA for social infrastructure and services (including health, education, etc.) was consistently two to three times that of ODA for economic infrastructure All types of ODA were either insignificant or significant and negative for most of the other regions. For South Asia and for the world as a whole, the first two types of ODA show a significantly positive effect on growth. Although there has been controversy over the effects of aid on economic growth, with many studies unable to find a positive relationship, the revised analysis of several previous studies performed by Clemens et al. (2012) indicates that aid does have a modest positive effect on growth on average, although effects differ by country. Our analysis suggests that Africa is a region in which aid has had, at least in the past decade, better- than-average growth impact. The governance and institutional quality variables and the human capital variables represent what Rodrik (2013a) calls “fundamental capabilities,” or characteristics that can drive sustained, but not necessarily rapid, economic growth. The human capital variables, life expectancy and average years of schooling, both positively affected growth among African countries. Both human capital variables also had a positive and significant effect on growth in every region and in the world as a whole (with the exception that schooling appears as negative and significant in the East Asia and the Pacific region, and as not significant in South Asia). http://www.resakss.org 2014 ReSAKSS Annual Trends and Outlook Report 29 Improvements in two of the governance variables, Rule of Law and Control of Corruption, positively affected growth in African countries, while three other variables, Government Effectiveness, Regulatory Quality, and Voice and Accountability, were found to have no significant impact on growth. There is a wide consensus that good governance in general and the related concepts of rule of law and control of corruption in particular are vital for economic growth (see, for example, Ugur and Dasgupta [2011] for a review of evidence on corruption and growth). It is interesting that even the limited progress that has been made in these areas appears to have had a positive effect on growth in Africa. As shown in Figure 5.17, the Rule of Law indicator improved only slightly over the period and the Control of Corruption indicator even trended downward toward the end of the period. For the world as a whole, Control of Corruption, Regulatory Quality, and Government Effectiveness were similarly positive and significant. Consequently, the deepening of reforms in the area of political governance must be a critical component of future strategies to foster long- term growth, create employment, and raise incomes. The effect of natural resource exports, as a share of total merchandise exports, is positive but insignificant. However, the effect becomes positive and significant when the natural resources export share is interacted with inflation. This growth-enhancing effect could arise through two channels. First, increased export revenues, if properly managed, have the same impact as increases in savings, FDI, or ODA, as they improve the country’s capacity to finance investments, including the importation of capital goods, which boosts productivity and growth. Second, increased export revenues, through the impact on the balance of payments and improved access to foreign exchange reserves, tend to help stabilize country exchange rates, with associated improvements in the macroeconomic environment for growth. Natural-resource-dependent economies have historically struggled to neutralize the inflation-inducing effects of surges on export revenues. The positive effect above appears to suggest that during the recovery period, the negative effects of inflation on growth were less severe in natural-resource- dependent countries than in others. Countries seem to have had greater success than in the past in adequately managing natural resource export earnings such as to avoid their destabilizing macroeconomic impacts. The negative effects of inflation in natural-resource-dependent countries may have been partially offset by other positive effects of increased export revenues on growth. Although inflationary pressures can stem from an increased influx of foreign exchange revenues during natural resource export booms, they can also stem from other factors related to fiscal and monetary management. As was seen in Figure 5.13, inflation has been lower across the continent in the 2000s than in the two preceding decades. The macroeconomic reforms enacted during the SAP era may have softened the inflationary tendencies of rising natural resource export earnings during the 1990s and 2000s. Indeed, African countries with a high natural resource value-added share (>10 percent) appear to have been effective in managing resource revenues such as to avoid their growth-reducing inflationary effects. As can be seen from Figure 5.18 (next page), relatively resource-dependent countries experienced higher inflation than others during the late 1990s, but by the mid-2000s they had brought inflation down to levels similar to those of non-resource-dependent countries. The graph begins in 1997 because Angola and the Democratic Republic of the Congo, two natural- resource-dependent countries, had extremely high inflation rates that are difficult to show on the graph. If those two countries are excluded, natural-resource-dependent countries still show higher inflation rates than 30 resakss.org non-natural-resource-dependent countries during the early and mid-1990s, and rates start to converge by the late 1990s. The successful management of natural resource revenues suggested by our results is a welcome contrast to the experiences of many resource-rich African countries during the 1970s and 1980s. A large volume of natural resource exports exposes the economy to the risk of Dutch disease, due to the shift in relative prices in favor of nontradable sectors, which in turn results in the contraction of activities in the nonresource tradable sectors, including manufacturing and agriculture. For instance, in Nigeria, the effects of oil price booms as well as government policies that were biased against agriculture helped turn the country from a major agricultural exporter in the 1960s into a large-scale food importer during the 1970s (Oyejide 1986). The volatility in public expenditures and relative prices that is associated with natural resources boom and bust cycles also creates uncertainty and thus disincentives for investment, which in turn has a negative effect on growth (Budina, Pang, and van Wijnbergen 2007). In the last decade, ever more African countries have joined the ranks of oil and mineral producers. Managing revenues prudently to harness their potential for catalyzing growth while avoiding their possible negative effects on other sectors will be a key challenge in the future management of growth. Public spending and investment may be the most effective tool the government has to counter Dutch disease effects that tend to harm agriculture and manufacturing (Scherr 1989). However, the effectiveness of public spending tends to decline at high levels of expenditure (Gelb and Grasmann 2010). Indeed, Nigeria accumulated high debts during the 1980s despite its oil revenues, in part because public investment projects were often unsuccessful and failed to generate sufficient revenues (Budina, Pang, and van Wijnbergen 2007). More recently, Ghana, in the aftermath of surging oil exports, raised domestic spending significantly, leading to serious macroeconomic problems (IFEJ 2015). Similar developments are documented by Tshibaka (1986) in the case of the Democratic Republic of the Congo. Gabon provides another example of a country where large and rising natural resources FIGURE 5.18—CONSUMER PRICE INFLATION, NATURAL-RESOURCE-DEPENDENT AND NON-RESOURCE-DEPENDENT COUNTRIES Source: Authors’ calculations based on World Bank (2015) and UNSD (2015). Note: NR = natural resource. “NR dependent” countries are those with mining and utilities value-added shares of over 10 percent, according to the United Nations Statistics Division. Inflation is weighted by GDP. 0 5 10 15 20 25 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 NR dependent Non-NR dependent http://www.resakss.org 2014 ReSAKSS Annual Trends and Outlook Report 31 revenues have failed to generate meaningful overall economic growth or tangible progress in poverty reduction in the past. Strengthening public financial management systems to enable them to handle the increased spending resulting from resource revenues will be another critical component of future strategies for growth with employment generation (IMF 2007). Processes for investment project identification, selection, and implementation will also need to be enhanced in order to improve the quality and impact of public expenditures in resource-rich countries (Budina, Pang, and van Wijnbergen 2007). As a general rule, Gelb and Grasmann (2010) recommend a cautious fiscal policy, as the negative welfare effects of overestimating future revenues and overspending far outweigh the costs of overcaution and underspending. Despite the importance of vigilance to ensure proper resource management in the years ahead, the role of natural resources in Africa’s recent growth should not be overstated. Both resource-rich and non- resource-rich countries were among the best growth performers in recent years, and both groups were also represented among slower-growing countries, as shown in the paper by Badiane and McMillan. In other words, sustaining and accelerating the current recovery process to boost employment and incomes will require improvements in all the areas discussed above: political governance, human resources, and the macroeconomic environment. Conclusions In this chapter we have reviewed Africa’s unprecedented growth recovery and examined the roles of policy-related factors and other drivers. Africa’s growth in the decade of the 2000s was the most rapid the continent has seen in the past five decades and followed several decades of stagnation and even decline in per capita GDP. Similar patterns are seen in overall labor productivity and in agricultural labor productivity, a key factor for increasing rural incomes. The current growth recovery is promising, but the struggle to increase living standards is far from over. The recent growth acceleration has not been sufficient to put the continent back onto its growth path of the 1960s; Africa remains far below the levels of GDP per capita and agricultural labor productivity that it would have reached today had it avoided the lost decades and maintained the growth rates of the 1960s. In fact, many African countries have not yet matched the absolute levels of GDP per capita and agricultural productivity that they displayed in earlier decades. Signs of economic convergence between Africa and the rest of the world are discernable starting in the 2000s, but no such convergence appears in agricultural labor productivity, where the gap between low- productivity and high-productivity countries continues to widen. To speed up the pace of catching up and allow Africa to harness growth to maximize impact on poverty, efforts must be made to raise agricultural productivity and growth in order to sustain and even accelerate the recovery. The evolution of growth policies and strategies among African countries since independence offers valuable lessons for the future, in particular when compared with the experience of China, which was poorer than Africa during the 1960s and 1970s but which embarked on an exceptionally rapid growth trajectory starting in the late 1970s. Over the past five decades, many African countries pursued policies based on successive waves of shifting paradigms, with abrupt and frequent changes in focus between industry and agriculture and between government and the private sector. China, by 32 resakss.org contrast, followed a reform process that was carried out gradually and in incremental steps, based on evidence from small-scale experiments. This approach allowed China to sustain rapid growth for several decades and lift unprecedented numbers of people out of poverty. As much as the shifting development strategies pursued by African countries failed to result in sustained growth for decades, subsequent improvements in policies and governance paved the way for broad-based growth across the continent. Key drivers explaining Africa’s growth recovery include increases in savings, FDI, and ODA; improvements in education and life expectancy; improvements in the rule of law and control of corruption; and increasing macroeconomic stability. The results also suggest that natural-resource-dependent countries have been able to manage foreign exchange revenues adequately to prevent negative macroeconomic effects. Given the large and increasing numbers of countries in Africa now producing oil or minerals, prudent management of natural resource revenues will be essential in the coming decades if countries are to avoid repeating earlier mistakes and put revenues to work to spur more broad-based growth. The empirical analysis also shows that during the recovery period, convergence took place among African countries as well as in the world as a whole, indicating that growth was successful in raising incomes in the poorest countries. Of concern is, however, the absence of convergence in terms of agricultural labor productivity between Africa and the rest of the world. On the contrary, the productivity gap between Africa and other regions appears to be widening, which again highlights the critical importance of a continued successful implementation of CAADP. http://www.resakss.org 2014 ReSAKSS Annual Trends and Outlook Report 33 AUC (African Union Commission). 2001. The New Partnership for Africa’s Development (NEPAD). Abuja, Nigeria: African Union. Badiane, O., and S. Kinteh. 1994. Trade Pessimism and Regionalism in African Countries: The Case of Groundnut Exporters. IFPRI Research Report 97. Washington, DC: International Food Policy Research Institute. Badiane, O., and T. Makombe. 2015. “Agriculture, Growth, and Development in Africa: Theory and Practice.” In The Oxford Handbook of Africa and Economics. Vol. 2, edited by C. Monga and J. Y. Lin, 307–324. Oxford, UK: Oxford University Press. Barro, R. J., and J.-W. Lee. 2014. Barro-Lee Educational Attainment Dataset. Educational Attainment for Population Aged 15 and Over. Accessed June 2015. http://barrolee.com/. Barro, R. J., and X. Sala-i-Martin. 2004. Economic Growth, 2nd ed. Cambridge, MA, US, and London: MIT Press. Benin, S., A. Nin-Pratt, S. Wood, and Z. Guo. 2011. Trends and Spatial Patterns in Agricultural Productivity in Africa, 1961–2010. ReSAKSS Annual Trends and Outlook Report 2011. Washington, DC: International Food Policy Research Institute. Budina, N., G. Pang, and S. van Wijnbergen. 2007. Nigeria’s Growth Record: Dutch Disease or Debt Overhang? World Bank Policy Research Working Paper 4256. Washington, DC: World Bank. Chen, K. Z., C. Hsu, and S. Fan. 2014. “Steadying the Ladder: China’s Agricultural and Rural Development Engagement in Africa.” China Agricultural Economic Review (6) 1: 2–20. Clemens, M. A., S. Radelet, R. R. Bhavnani, and S. Bazzi. 2012. “Counting Chickens When They Hatch: Timing and the Effects of Aid on Growth.” Economic Journal 122 (561): 590–617. Conference Board. 2015. Total Economy Database: Output, Labor, and Labor Productivity, 1950–2015. Accessed June. https://www. conference-board.org/retrievefile.cfm?filename=TED---Output- Labor-and-Labor-Productivity-1950-2015.xlsx&type=subsite. CRU (University of East Anglia Climatic Research Unit) and I. Harris. 2014. CRU CY3.22: CRU Year-by-Year Variation of Selected Climate Variables by Country (CY) version 3.22 (Jan. 1901–Dec. 2013). NCAS British Atmospheric Data Centre. Accessed June 2015. http://dx.doi. org/10.5285/9A8A0770-D7FC-4FC4-B83F-227E1170F2EB. References http://barrolee.com/ http://dx.doi.org/10.5285/9A8A0770-D7FC-4FC4-B83F-227E1170F2EB http://dx.doi.org/10.5285/9A8A0770-D7FC-4FC4-B83F-227E1170F2EB 34 resakss.org Diao, X., J. Thurlow, S. Benin, and S. Fan, ed. 2012. Strategies and Priorities for African Agriculture: Economywide Perspectives from Country Studies. Washington, DC: International Food Policy Research Institute. Easterly, W., and R. Levine. 1997. “Africa’s Growth Tragedy: Policies and Ethnic Divisions.” The Quarterly Journal of Economics 112 (4): 1203– 1250. Fan, S., A. Gulati, and S. Dalafi. 2007. “Overview of Reforms and Development in China and India.” In The Dragon and the Elephant: Agricultural and Rural Reforms in China and India, edited by A. Gulati and S. Fan, 10–44. Baltimore: Johns Hopkins University Press for the International Food Policy Research Institute. Fan, S., L. Zhang, and X. Zhang. 2004. “Reforms, Investment, and Poverty in Rural China.” Economic Development and Cultural Change 52 (2): 395–421. Gelb, A., and S. Grasmann. 2010. How Should Oil Exporters Spend Their Rents? Center for Global Development Working Paper 221. Washington, DC: Center for Global Development. IFEJ (Institute of Financial and Economic Journalists). 2015. “CEPA Worried about Direction of Ghana’s Economy.” Accessed August 6. http://ifejghana.org/cepa-worried-about-direction-of-ghanas- economy/. IMF (International Monetary Fund). 2007. The Role of Fiscal Institutions in Managing the Oil Revenue Boom. Washington, DC: IMF. ———. 2015. World Economic Outlook database. Accessed May. http:// www.imf.org/external/pubs/ft/weo/2015/01/weodata/download.aspx. Jayne, T. S., J. Govereh, A. Mwanaumo, J. K. Nyoro, and A. Chapoto. 2002. “False Promise or False Premise? The Experience of Food and Input Market Reform in Eastern and Southern Africa.” World Development 30 (11): 1967–1985. Johnston, B. F., and J. W. Mellor. 1961. “The Role of Agriculture in Economic Development.” American Economic Review 51 (4): 566–593. Kaufmann, D., A. Kraay, and M. Mastruzzi. 2010. The Worldwide Governance Indicators: Methodology and Analytical Issues. World Bank Policy Research Working Paper 5430. Washington, DC: World Bank. References http://www.resakss.org http://ifejghana.org/cepa-worried-about-direction-of-ghanas-economy/ http://ifejghana.org/cepa-worried-about-direction-of-ghanas-economy/ http://www.imf.org/external/pubs/ft/weo/2015/01/weodata/download.aspx http://www.imf.org/external/pubs/ft/weo/2015/01/weodata/download.aspx 2014 ReSAKSS Annual Trends and Outlook Report 35 Lipton, M. 2012. “Income from Work: The Food-Population-Resource Crisis in the ‘Short Africa.’” Leontief Prize lecture, Tufts University, Medford, MA, US, April 3. NEPAD (New Partnership for Africa’s Development). 2003. Comprehensive Africa Agriculture Development Programme. Midrand, South Africa: NEPAD. Nin-Pratt, A. 2015. Agricultural Intensification in Africa: A Regional Analysis. IFPRI Discussion Paper 01433. Washington, DC: International Food Policy Research Institute. Nin-Pratt, A., and B. Yu. 2008. An Updated Look at the Recovery of Agricultural Productivity in Sub-Saharan Africa. IFPRI Discussion Paper 787. Washington, DC: International Food Policy Research Institute. OECD (Organization for Economic Co-operation and Development). 2015. Creditor Reporting System database. Accessed July. http://stats.oecd. org/index.aspx?DataSetCode=CRS1#. Oyejide, T. A. 1986. The Effects of Trade and Exchange Rate Policies on Agriculture in Nigeria. IFPRI Research Report 55. Washington, DC: International Food Policy Research Institute. Rodrik, D. 2013a. The Past, Present and Future of Economic Growth. Global Citizen Foundation Working Paper 1. Geneva: Global Citizen Foundation. ———. 2013b. “Unconditional Convergence in Manufacturing.” Quarterly Journal of Economics 128 (1): 165–204. Scherr, S. J. 1989. “Agriculture in an Export Boom Economy: A Comparative Analysis of Policy and Performance in Indonesia, Mexico and Nigeria.” World Development 17 (4): 543–560. Tshibaka, T. B. 1986. The Effects of Trade and Exchange Rate Policies on Agriculture in Zaire. IFPRI Research Report 56. Washington, DC: International Food Policy Research Institute. Ugur, M., and N. Dasgupta. 2011. Evidence on the Economic Growth Impacts of Corruption in Low-Income Countries and Beyond: A Systematic Review. London: EPPI-Centre, Social Science Research Unit, Institute of Education, University of London. UNSD (United Nations Statistics Division). 2015. National Accounts Main Aggregates Database. Accessed July. http://unstats.un.org/unsd/ snaama/introduction.asp. http://stats.oecd.org/index.aspx?DataSetCode=CRS1 http://stats.oecd.org/index.aspx?DataSetCode=CRS1 http://unstats.un.org/unsd/snaama/introduction.asp http://unstats.un.org/unsd/snaama/introduction.asp 36 resakss.org World Bank. 2014a. World Development Indicators database. Accessed January and November. http://databank.worldbank.org/data/reports. aspx?source=world-development-indicators. ———. 2014b. Worldwide Governance Indicators database. Accessed June 2015. http://info.worldbank.org/governance/wgi/index.aspx#home. ———. 2015. World Development Indicators database. Accessed June and July. http://databank.worldbank.org/data/reports.aspx?source=world- development-indicators. References http://www.resakss.org http://databank.worldbank.org/data/reports.aspx?source=world-development-indicators http://databank.worldbank.org/data/reports.aspx?source=world-development-indicators http://info.worldbank.org/governance/wgi/index.aspx#home http://databank.worldbank.org/data/reports.aspx?source=world-development-indicators http://databank.worldbank.org/data/reports.aspx?source=world-development-indicators Regional Strategic Analysis and Knowledge Support System International Food Policy Research Institute 2033 K Street, NW Washington, DC 20006-1002 USA Tel.: + 1 202.862.4662 Fax: +1 202.467.4439 Email: resakss-africa@cgiar.org www.resakss.org 978-0-89629-892-7