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Ritsumeikan International Affairs Vol.7 (2009) The Impacts of Vertical and Horizontal Export Diversification on Growth: An Empirical Study on Factors Explaining the Gap between Sub-Saharan Africa and East Asia’s Performances YOKOYAMA, Kenji & ALEMU, Aye Mengistu © Institute of International Relations and Area Studies, Ritsumeikan University The Impacts of Vertical and Horizontal Export Diversification on Growth: An Empirical Study on Factors Explaining the Gap between Sub-Saharan Africa and East Asia’s Performances YOKOYAMA, Kenji* & ALEMU, Aye Mengistu** Abstract This paper empirically investigates the separates effects of vertical and horizontal export diversification on economic growth based on a panel data of 41 countries from Sub-Saharan Africa (SSA) and East Asia. First, the study revealed that East Asian countries have been successful to diversify their exports both vertically and horizontally; whereas SSA’s diversification attempt was too minimal and its contribution for growth and structural change on the economy was insignificant. Secondly, the study confirms that, though horizontal diversification is positively correlated with growth, its contribution was found to be not impressive compared to vertical diversification for growth. The possible explanation is that, unlike vertical diversification which is mainly growth-oriented and having a dynamic spillover effects on the economy, horizontal diversification is mainly stability-oriented and less-growth oriented. This paper, therefore, calls into question the policy advices of some researchers that proposed Africa’s emphasis should be on horizontal diversification through increasing the number of priRITSUMEIKAN INTERNATIONAL AFFAIRS Vol.7, pp.49-90 (2009). *Yokoyama Kenji is a Professor at Ritsumeikan Asia Pacific University, 1-1, Jumonjibaru, Beppu-shi, Oita-ken 874-8577, Tel: 977-78-1000 Fax: 977-78-1001, E-mail: [email protected] **Alemu Aye Mengistu is a PhD Candidate, Graduate School of Asia Pacific Studies, Ritsumeikan Asia Pacific University, Beppu-shi, Oita-ken, Japan Postal Address:Kannawa-Miyuki, 5 Kumi, AP Matsumi (Room 106), Beppu-shi, Oita-ken, 8740045 Phone number: +81 8033601404, E-mail: [email protected] 50 RITSUMEIKAN INTERNATIONAL AFFAIRS 【Vol. 7 mary export products. This paper argues that SSA should give more emphasize for vertical diversification by means of valueadded ventures and forward and backward production linkages. In doing so, countries in SSA must create sufficient levels of human and physical capital, infrastructure, appropriate policies and strong institutions. Keywords: Export Diversification, Vertical Diversification, Horizontal Diversification, Economic Growth, Sub-Saharan Africa, and East Asia I. INTRODUCTION “When the sun began to set on Europe’s foreign empires, and former colonies across the globe began in the 1960s to prepare themselves for independence, no body was that worried about Africa. The anxiety was all for Asia. After all, Africa was a place of great mineral riches and vast agricultural fecundity. Asia, by contrast, seemed to have only problems and population” (Commission for Africa, 2005:16). It was not with out reason that, we started the itroduction with the above remark. At the time of their independence in the 1960s, income per capita in most SSA was fairly comparable with that of East Asia. In fact, in the 1960s, much of the expectation was from SSA to perform more economic achievement than East Asia because of its large endowments of natural resources. However, starting from quite similar per capita income in the early 1960s, Sub-Saharan Africa (SSA) and East Asia experienced a divergent development path and outcome for the last three/ four decades. The annual growth in Real GDP per capita of SSA averaged about 0.44% over the period 1975-2004, compared to about 4.1% for East Asian economies during the same period. Table 1 shows income comparisons between the years 1965 and 2000 for selected East Asian and SSA countries. In 1965, for instance, Korea Republic and Thailand had income per capita of $130 and $140 respective- 2009】 The Impacts of Vertical and Horizontal Export Diversification on Growth(YOKOYAMA & ALEMU) 51 ly; which had been lower than some SSA Countries such as Congo DR, Ghana, Congo Republic, Cote d’Ivoire and Niger. By year 2000, Korea and Thailand have registered a per capita income of $ 9,010 and $2,020 respectively. In the same time span, however, Ghana, Congo Republic, Cote d’Ivoire have managed to increase their per capita income from $230, $170 and $200 only to $330, $590 and $680, respectively. In the same token, South Africa which is regarded as the best economy in Africa and Singapore in East Asia had exactly equal income per capita of $ 540 each in 1965. In year 2000, however, South Africa registered a per capita income of $3,060 where as Singapore achieved a per capita income of $ 23,350 which was almost 7.6 times the performance of South Africa. Figure 1 also indicates how SSA and East Asia diverged in income per capita since the 1970s after having more or less the same beginning in the 1960s. Table 1: Per Capita Income in 1965 and 2000 (in current US$) Country Sub-Saharan Africa Cameroon Congo, Rep. Congo, DR Cote D’Ivoire Ghana Niger Nigeria Sierra Leone South Africa East Asia Japan Korea, Rep. Hong Kong, China Singapore China Malaysia Thailand 1965 2000 2000/1965 140 170 330 200 230 180 120 160 540 580 590 90 680 330 180 260 130 3,060 4.1 1.7 0.3 3.4 1.4 1.0 2.2 0.8 5.7 910 130 690 540 100 330 140 35,420 9.010 26,410 23,350 840 3,250 2,020 38.9 69.3 38.3 43.2 8.4 9.8 14.4 Data Source: WDI Database 52 RITSUMEIKAN INTERNATIONAL AFFAIRS 【Vol. 7 Figure 1 : Income per capita in Sub-Saharan Africa and East Asia, 1975 and 2004 Income per capita of SSA and East Asia 35000 Income per capita (in PPP) 30000 25000 20000 2004 1975 15000 10000 5000 B C ur ki na fa am so er C oo on n go C DR on go E R. th io pi a G ha na K en M ya au r it iu N s ig er S ia .A fr ic U a ga Z nd im a ba bw e C In hin do a ne K sia or ea M R al . a P ys hi ia lip p S ine in s ga po T re ha ila nd 0 Country Unlike East Asia, Africa hardly benefited from the boom in manufactured exports. According to UNCTAD (2003), Africa’s share in world merchandise exports fell from 6.3 per cent in 1980 to 2.5 per cent in 2000 in value terms. Similarly, Africa’s share of total developing-country merchandise exports fell to almost 8 per cent in 2000 from its value of 1980. In contrast, East Asia’s share of global merchandise exports increased from 18 per cent in 1980 to 22 per cent in 2000, while its share of total developing-country merchandise exports increased from almost 60 to 72 per cent over the same period. Similarly, its share in global manufactures trade increased threefold, reaching 21.5 per cent in 2000. The value of East Asia’s total exports recorded 7 per cent average annual growth over the period under review, compared to a mere 1 per cent for Africa (table 2). Similarly, SSA’s share in world imports fell from 3.1 % in 1980 to 1.4% in 2002, while East Asia again increased its world import share from 13.1% to 20.8% in the same time span (UNCTAD, 2003). Table 2 : Export Structure of Africa and East Asia, 1980 and 2000 Region 1980 2000 a All Merchandise Africa share in: Global exports Developing Countries East Asia share in: Global exports Developing Countries b Manufactures All Merchandise Manufactures 6.3 20.3 0.8 7.8 2.5 7.9 0.8 3.0 18.1 58.5 7.1 66.9 22.4 72.0 21.5 79.0 Source: UNCTAD (2003) ‘a’ refers Standard International Trade Classification (SITC) 0–9 & ‘b’ refers SITC 5–8, less 68. 2009】 The Impacts of Vertical and Horizontal Export Diversification on Growth(YOKOYAMA & ALEMU) 53 SSA countries are heavily dependent on a narrow base of few agricultural and mineral exports for foreign exchange earnings (Table 3) and have had to endure the consequences of all problems resulting from the fluctuation of commodity prices in world markets. About 17 of the 20 most important export items of Africa are primary commodities and resource-based semimanufactures. On average, world trade in these products has been growing much less rapidly than manufactures. In fact, world trade in other primary commodities that account for an important proportion of total exports of Africa such as coffee, cocoa, cotton and sugar, has been sluggish, with the average growth of trade in such products in the past two decades barely reaching one-third of the growth rate of world trade in all products (UNCTAD, 2003). For instance, world prices for many of the commodities that Africa exports declined between 1990 and 2000: Cocoa, Cotton, sugar and copper by over 25%, coffee by 9% and minerals overall declined by 14% (WTO, 2001). As noted in Ng and Yeats (2002), one-half of traditional products in SSA experience average price changes of 50 % or more during the 1990’s. Table 3 Main Exports of Selected Sub Saharan Africa Countries COUNTRY Benin Burkina Faso Burundi Chad Congo, Dem. Rep Ethiopia Gabon Kenya Mali Mauritius Niger Nigeria Rwanda South Africa Sudan Zambia EXPORTS Cotton, Palm oil Cotton, Animal Products, Gold Coffee, Tea, Sugar, Cotton, Hides Cotton, Oil, Livestock, Textiles Diamonds, Copper, Coffee, Cobalt, Crude oil Coffee, Hides, Oil seeds, Beeswax, Sugarcane Crude Oil, Timber, Manganese, Uranium Tea, Coffee, Horticultural products, Petroleum products Cotton, Gold, Livestock Sugar, Clothing, Tea, Jewellery Uranium, Livestock products Petroleum, Petroleum products, Cocoa, Rubber Coffee, Tea, Hides, Tin ore Gold, Diamonds, Metals & Minerals, Cars, Machinery Oil, Cotton, Sesame, Livestock & Hides, Gum Arabic Copper, Minerals, Tobacco Source: Osakwe (2007) 54 RITSUMEIKAN INTERNATIONAL AFFAIRS 【Vol. 7 Theoretical analysis suggests that agricultural commodity prices fall relative to manufacturing products because of relatively inelastic demand and because of the lack of differentiation among producers. On the demand side, the development of synthetic substitutes further displaces agricultural commodities as intermediate inputs, reducing at least the growth in demand. This drastic decrease of the SSA presence in world trade was not only the result of the deterioration of the terms of trades (due to low income elasticity of demand) in primary commodities, but also of the loss of competitiveness in manufactures. Ironically, SSA’s manufacturing sector grew significantly in the 1960’s; more than 8% annual average growth rate of manufacturing value added was substantially higher than the corresponding GDP growth rate, although the base of the manufacturing sector from which this growth derived was quite small. This growth performance, however, could not be sustained. It decelerated sharply in the 1970’s and was virtually stagnant in the 1980’s. By the mid 1980’s, the capacity utilization rates in manufacturing was well below 35% in many SSA countries (World Bank, 1993). The question is, therefore, why countries in East Asia achieved breakthrough in economic development in the past 3-4 decades while countries in Sub-Saharan Africa did not? Sachs et al. (2004) identified the main characteristics of SSA weak economic performance and poverty traps as: (i) the level of capital (human & physical) so small that it falls below the threshold needed to start modern production processes; (ii) very low levels of savings, which make the capital accumulation impossible; (iii) high rates of population growth from the rural poor who see young children as an economic asset and (iv) a very slow diffusion of technology from abroad. On the other hand, the major characteristics of economic growth in East Asian countries are: (1) rapid accumulation of savings and high rates of investment, (2) high level of foreign direct investment (FDI) and it was appropriately used as an alternative source of foreign currency and a big factor in capital formation, (3) high investment on basic infrastructure including marketing information system, (4) rapid increases in levels of schooling, (5) rapid growth of manufactured exports, and (6) stable macroeconomic and institutional environment have been instrumentals in creating confidence in policy makers. Moreover, one of the most remarkable features of growth in East Asian countries is that, it was accompanied by rising economic equality 2009】 The Impacts of Vertical and Horizontal Export Diversification on Growth(YOKOYAMA & ALEMU) 55 (Gerber, 2005). Hence, the East Asian experience has called into question the idea that economic growth in developing countries follows a “Kuznet’s curve,” in which equality first declines and then rises. Although the conditions that led to greater income equality were rooted in the unique historical experiences of each country, it is also evident that each of the East Asian countries had a similar set of highly visible wealth-sharing mechanisms such as land reform, free public education, free basic health care, and significant investments in rural infrastructure. These policies didn’t equalize income by themselves, but they provided people with the tools they needed to raise their individual incomes and gave hope for the future. Table 4 shows that for all regions, it is Africa where income is most unequal as shown by the Gini coefficient of 0.51. Table 4 : Income Inequality Measures by World Regions Region Africa East Asia and Pacific South Asia Latin America Industrialized Countries Gini Coefficient Share of top 20 % Share of Middle Class Bottom 20 % 0.51 0.38 0.32 0.49 0.34 50.6 44.3 39.9 52.9 39.8 34.4 37.5 38.4 33.8 41.8 5.2 6.8 8.8 4.5 6.3 Source: Deininger and Squire (1996) The success of East Asian countries to shift from producing a low productive primary commodities to producing a more productive manufactured products reflects even latecomers are able to specialize in high growth areas if some of the pre-conditions are fulfilled. Thus, as Masuyama and Vandenbrink (2001) pointed it out, “unless a country diversifies critical supporting industries, the development of few industries alone will not produce growth in the economy.” At this point it is necessary to make a distinction between vertical and horizontal diversification. While horizontal diversification entails broadening of the primary export mix in order to stabilize the volatility of global commodity prices, vertical diversification involves a radical change in export structure and further uses of existing and new innovative export products by means of value-added ventures such as processing and marketing. While both horizontal and vertical diversifications are expected to positively induce economic growth, the requirements for the two could 56 RITSUMEIKAN INTERNATIONAL AFFAIRS 【Vol. 7 vary considerably in terms of technological, managerial and marketing skills. Accordingly, it is vertical integration that may require more advanced technology, skills and initial capital than horizontal diversification. Vertical diversification can also be more linked with higher learning possibilities that, in turn, may produce greater dynamic externalities than that of horizontal diversification. For-example, vertical diversification takes place by moving up the value chain to produce manufactured products as in Korea, China, and Malaysia. Horizontal diversification is achieved by producing non traditional dynamic exports such as cut flowers as it has been started recently in Kenya, Uganda and Ethiopia to supplement or partially replace the traditional exports like coffee and tea. It should be stressed that diversification is not a phenomena that contradicts the notion of comparative advantage especially in the case of developing countries. Rather, it a process of broadening comparative advantages into new sectors. Moreover, diversification should be seen as a dynamic process, not as a static one. A country’s export pattern is a good predicator of future growth (Hausmann and Klinger, 2007). Volume of total exports in turn is determined by the three main factors: the world demand for exports of the given commodity, competitiveness of the given product and the degree of export diversification of that country (Athukorala, 1991). For instance, in the 1960s, agricultural export performance was similar among Indonesia, the Philippines and Thailand, both in nominal and real value terms. But in the decades since then, the three countries have shown different performances in agricultural exports. The main important factor resulting in the differences is the ability of diversification and adjustment of agricultural exports when the market conditions changed (Hirohisa, 2003). As Pinaud and Wegner (2004) put it, African economies still lack proper “shockabsorbers” to withstand internal (e.g. drought, floods, and political instability) and external (e.g. volatility of commodity prices and exchange rates) shocks alike. Thus, the capacity of smoothing shocks highly depends on the ability of African policy makers to diversify their economies. The case in point in this paper is, therefore, to assess the separate effects of vertical and horizontal export diversification for economic growth. Although diversification can’t be expected to become the only panacea for SSA economic problems, it is one of the key measures for structural solutions (De Ferranti et al, 2002). That is why the economic report on Africa 2009】 The Impacts of Vertical and Horizontal Export Diversification on Growth(YOKOYAMA & ALEMU) 57 (2007) presents the theme of diversification as a new paradigm for Africa’s development and the report argues that diversification is a prerequisite to achieving positive development in the continent. II. OBJECTIVE OF THE STUDY, RESEARCH QUESTIONS AND PROPOSITIONS Objective of the Study The overall objective of this study is to identify and measure the effects of vertical and horizontal export diversification on economic growth, both in SSA and East Asia. The overall assumption is that the East Asian experiences could provide valuable lessons that policy-makers in sub-Saharan Africa could adapt to their own contexts. Meanwhile, the study is expected to fill the gaps by closely looking diversification from its vertical and horizontal dimensions and thus recommend which one may contribute more to growth. Therefore, an attempt has been made to answer the following key policy questions. Research Questions 1. If diversification can have a positive impact on a country’s growth and development prospects, what are the policy options available to support that process? 2. Which areas of export diversification (vertical or horizontal) may be considered priorities in Africa and why? 3. What other factors cause the differences in income per capita growth over time and across countries? 4. What would be the lessons from East Asia to SSA with regard to diversification in particular and economic growth in general? Propositions (a) Although vertical and horizontal diversifications are expected to stimulate economic growth, it is vertical integration that has a dynamic spillover effect on the economy and contribute more to economic growth; (b) Higher value of investment (domestic and foreign) raises the steady-state level of output per effective worker; the growth rate; (c) Human capital is expected to be one of the key determinant for eco- 58 RITSUMEIKAN INTERNATIONAL AFFAIRS 【Vol. 7 nomic growth based on endogenous growth theory and the Solow neo-classical exogenous theory; (d) Since the levels of human capital and FDI are below the threshold level in SSA, thus their contribution to economic growth may not be satisfactory in SSA compared to East Asia; (e) Since the theory of ‘absolute convergence’ predicts poorer countries typically grow faster in income per capita, ‘initial GDP/capita’ is inversely related with growth- rate; (f) Flexible exchange-rate system and openness in a given country may create favorable conditions for export growth and thereby to economic growth; (g) Political Instability is inversely related with export diversification and growth due to the fact that rate of saving and investment tends to be low in countries with frequent wars. III. Conceptual Framework for Export Diversification Three quarters of developing country exports in early 1980s were primary commodities, but now around 80% of developing countries are manufactures. However, Africa has not been part of this transformation. Processed products in Africa account only for less than 10% of the total exports from the continent. There are different views why Africa concentrated only on the export of primary products. On one hand, as Wood and Mayer (2001) noted, the concentration of Africa’s export on unprocessed primary products is largely caused by the region’s combination of low levels of education and abundant natural resources. On the other hand, Collier (2002) argues that Africa’s current comparative advantage in primary commodities is often due, not to its intrinsic endowments or location, but to a poor investment climate that is policy oriented. It is a common knowledge that the most dynamic developing area in the world economy in terms of growth and transformation during the period under review was East Asia. While at the beginning of this period the industrial base of the economies in this region was small, they transformed into industrialized countries within a relatively short period of time. What accounts, then, for the growth miracles in East Asia? Some economists argue that their rapid growth is explained by their ability to 2009】 The Impacts of Vertical and Horizontal Export Diversification on Growth(YOKOYAMA & ALEMU) 59 imitate foreign technologies. By adopting technology developed abroad, these countries managed to improve their production function substantially in a short period of time. In other words, these countries achieved a very rapid growth in total factor productivity (TFP). On the other hand, recent studies revealed that East Asia’s exceptional growth can be traced to large increases in measured factor inputs: increases in labor-force participation, increases in the capital stock, and increases in educational attainment (Mankiw, 2003). Moreover, Japan’s role in the development of the East Asian production structure over the past thirty or so years should be also taken into account. This has occurred through provision of Japanese war reparations, aid, and investment leading to high levels of intra and inter-regional trade, through the creation of a web of production networks based around Japanese firms. For instance, in the 1991-1993 periods, Japanese FDI in East Asia totaled 16.6 percent, while FDI from USA and European countries had been 10 percent and 3.6 percent, respectively (Kelly, 2002). By the same token, in 1993, Japan was the largest trading partner of China, Thailand, Malaysia and Indonesia, and the second largest trading partner (after the US) of South Korea, Taiwan, Singapore and the Philippines. Of the total $11.2 billion Japanese ODA in 1993, Asia’s share was about 59.5 %, and within Asia itself, China was the major recipient. Japan’s financial aids to East Asian countries in comparison with other regions are shown in table 5. Table 5 : Regional Distribution of Japan’s Bilateral ODA (%) Region Asia (northeast) (southeast) Middle east Africa Latin America Europe Oceania Unclassifiable 1970 98.3 Source: Kelly (2002) 3.3 2.3 -4 -0.2 0 0.3 1980 70.6 4.2 43.9 2.5 18.9 6.0 0.2 0.5 1.2 1985 67.7 15.3 37.6 1.7 15.0 8.8 1.1 0.9 4.8 1990 59.3 12.0 34.3 1.5 15.4 8.1 6.9 1.6 7.1 1993 59.5 17.7 29.9 2.2 15.9 9.0 1.7 1.7 10.0 1995 54.4 15.2 24.6 6.8 12.6 10.8 1.5 1.5 12.3 1997 46.5 8.0 21.4 7.8 12.1 10.8 2.0 2.4 18.3 60 RITSUMEIKAN INTERNATIONAL AFFAIRS 【Vol. 7 East Asian countries have benefited from Japan not only in development aid, but also more importantly they benefited from technological transfer through FDI and exports. Furuoka (2005) used Kaname Akamatsu’s ‘Flying Geese’ model to analyze Japan’s role in East Asian economic development. In the initial stage of the formation of the second gaggle of flying geese, Japan (the leading goose) exported manufactured goods to the second-tier geese, i.e., South Korea, Taiwan, Hong Kong and Singapore. All those countries later came to be known as Asian Newly Industrializing Economies (NIEs). Once local demand for imported goods in NIEs had reached a certain threshold, Japan proceeded to establish production bases there. In the next stage, Asian NIEs became able to produce internationally competitive products, while Japan assisted the NIEs’ efforts of industrialization by providing them foreign aid. Eventually, Asian NIEs themselves became exporters of manufactured goods to other countries (third-tier geese), such as China and three ASEAN countries, namely Thailand, Malaysia and Indonesia. Besides exports, NIEs, following a pattern that had been established by Japan, were bringing investments to those countries. All the while, as had been the case with Asian NIEs, Japan assisted the third-tier geese’s efforts to industrialize and modernize their economies by supplying them vast amounts of money as foreign aid. Unfortunately, Africa lacks a ‘leading goose’ similar to Japan that may lead the flocks in the continent. Perhaps, South Africa can emerge as a leading economic power and contribute to Africa at large and the Southern African Development Community (SADC) region in particular in terms of FDI and technological transfer. In the same token, North African countries have a geographical proximity advantage with Europe and if they properly utilized it, the wide European market can be used as a stimulant for export growth, production diversification and technological transfer. However, it should be noted that the most enduring cause of the poor performance of African economy was not only due to lack of ‘economic power’ in the continent, but also the nature of African institutions and the quality of political regimes and that of the leadership are also partially responsible for the low performance in economic development at large, and insignificant export diversification and structural changes in particular. As Mkandawire and Soludo (1999) noted, the state in Africa has failed signally in its developmental mission because of various interrelated factors: 2009】 The Impacts of Vertical and Horizontal Export Diversification on Growth(YOKOYAMA & ALEMU) 61 (i) its “excessive” and “counterproductive” intervention in domestic economic process; (ii) its over bureaucratization and bloated size; (iii) its over centralization of development, which discourages local (private) initiatives and the rural (productive) sector. On the other hand, there are also cases to associate the economic development performance of Africa since early 1980s with its experience related to the most criticized ‘structural adjustment program that was sponsored by the World Bank and IMF. According to Collier and Gunning (1997), GDP per capita declined by 1.3 % per annum during the 1980s, a full 5 percentage points below the average for all low-income developing countries. This deterioration was even worse during 1990-94, at 1.8% per annum, further widening the gap with other developing countries to 6.2 percentage points. Likewise, the external debt of SSA has more than doubled over the adjustment period, without any increase in economic growth to sustain its servicing in the future. For instance, the indebtedness of Nigeria has increased over the adjustment period. The debt stock, which was only $18.9 billion before the SAP period, had risen to $33.2 billion by 1991. Inflation which averaged 18 percent between 1980 and 1985, rose to an average of 24 percent between 1986 and 1991; by the end of 1992 it was over 46 percent and remained in that high range through 1993. (Ake, 1996). Africa’s infrastructural base and human capital formation, which were deemed to be fragile at the beginning of adjustment, have deteriorated even further. Africa’s capacity to manage the crisis has been further eroded through massive brain-drain and demoralization of the civil service, caused by sharply declining real wages and massive retrenchments (Mkandawire and Soludo, 1999). Human development indicators-life expectancy, infant mortality, and school enrollment-have worsened. In a study by Ali (1998), which used data from IFAD and classified countries according to the WB categories, 10 SSA countries were classified as “ intensively adjusting” (Ghana, Kenya, Malawi, Tanzania, and Zambia), “other adjusting” (Gabon, Gambia and Mali), or “ non-adjusting” (Ethiopia and Lesotho). Accordingly, for the intensively adjusting countries, it was found that the index of rural poverty had increased from 56.6% in 1965 to 62.4% in 1988. Similarly, for the other adjusting countries, the index of rural poverty increased from 45.1% in 1965 to 60.7% in 1988. In contrast, the head-count ratio for the non-adjusting group decreased from 65.8% in 62 RITSUMEIKAN INTERNATIONAL AFFAIRS 【Vol. 7 1965 to 43.6% in 1988 (Ali, 1998; Mkandawire and Soludo, 1999). Generally table 6 shows how poverty in Africa was intensified, since the implementation of SAP in many of the African countries. Thus, SAP aggravated the already existing problems in SSA.. Table 6 : SAPs and poverty in SSA, 1985 and 1990 Country Cote d’ Ivoire Ghana Kenya Mauritania Rwanda Senegal Tanzania Uganda Zambia Zimbabwe Head-count ratio (%) Change in poverty Change in macroeconomic 1985 1990 (% points) policy (score) 40.31 29.00 53.17 32.17 31.59 49.65 53.53 37.10 48.53 56.71 45.93 33.49 58.83 35.52 37.94 54.75 59.79 44.69 52.54 67.26 5.62 4.49 5.66 3.35 6.35 5.10 6.26 7.59 4.01 10.55 -1.3 2.2 0.5 0.5 -0.2 0.5 1.5 0.2 -0.3 1.0 Source: Ali (1998) While African policy makers felt that a fundamental cause of Africa’s structural problem was precisely its over specialization in primary production; on the contrary, the World Bank report entitled “ Accelerated Development in Sub-Saharan Africa: An agenda for Action ” (1981) which became the classic perspective of the Breton Woods institutions was recommending Africa to concentrate on primary production, particularly agricultural products. As a result, except some diversification attempts by few countries, many of SSA economies remain un-diversified. According to Collier (2004), commodity-dependent SSA countries have two options: diversifying away from primary commodities, or learning how to live with commodity dependency better. For many SSA countries diversification is quite feasible, but in doing so, they have to develop the required pooled skilled labor and attract the necessary capital investments in order to move first into agro processing and then into light and capital intensive manufacturing, One of the most influential theories that explain why the comparative advantage of many developing countries has shifted from the export of pri- 2009】 The Impacts of Vertical and Horizontal Export Diversification on Growth(YOKOYAMA & ALEMU) 63 mary products to manufactured products is that of the “product cycle” theory. The product life cycle theory by Raymond Vernon (1966) argued that, for manufactured goods, comparative advantage may shift over time from one country to another. This happens because these goods go through a product life cycle. Once the product is invented, then overt time becomes more standardized as consumers and producers gain familiarity with its features. Standardized manufacturing routines are increasingly common, using low-skilled and semi-skilled labor in assembly type operations. Accordingly, an increasing share of the world’s output is moving to developing countries where abundant unskilled and semi-skilled labors keep labor costs low. Secondly, the product cycle theory emphasizes that commercial successes of consumer durables depend on product development mainly based on cost-cutting mass production and the use of known technology, rather than on technological breakthroughs. The neoclassical economic theory predicts that, when a relatively poor country starts accumulating capital and enters the cone of diversification, the Rybczynski effect occurs and the share of the capital-intensive aggregate should go up. This in turn would reduce industrial concentration and increase diversification. On the other hand, the endogenous growth model states that greater diversifications of exports occur through learning-bydoing and learning-by-exporting and through imitation of developed countries (Pineres and Ferrantino, 1997:376). In the same token, what appears to be crucial is also creating an environment that creates competition and thus to acquire new skills and this can be performed through exports. Without the pressure from outside competitive forces, acquisition of human capital, and thus overall economic growth, may be slow (Husted and Melvin, 2007). So far we have seen the importance of export diversification mainly on the supply side. However, diversification may also result more endogenously from a growing demand for a variety of goods as a country’s income increases (Imbs and Wacziarg, 2003). In other words, production patterns respond to changes in the structure of demand and then generate increasing sectoral diversification through the “Engel effect”. The most influential research on diversification by Imbs and Wacziarg (2003) has identified two stages of diversification in the process of economic development. First, poor countries tend to diversify as their incomes rise; then, the level of diversification will reach to a turning point and later begin to become 64 RITSUMEIKAN INTERNATIONAL AFFAIRS 【Vol. 7 more specialized. In this case, the diversification of an economy could be related to its development level, measured by GDP per capita, through an inverted-U shaped relation. Therefore, a country ought to undertake investment in such a way that this turning point occurs as a result of attaining deep diversification. Because, it is only after the attainment of deep diversification that countries can shift to the second stage that tends towards specialization. Hence, almost all developed countries and some high income developing countries today are in the stage of re-concentration after they successfully passed the diversification stage in the past. Concentration Diversification Re-Concentration Thus, the stages of diversification will follow the following steps: Thus, the question is that if countries get back to re-concentration, why should they need to diversify? The point is that, there is a fundamental difference between countries that are in the first stage of concentration and countries that come-back to re-concentration. The main difference is that the former specializes largely in primary products whose relative prices are falling from time to time; where as the latter specializes in high value added and knowledge intensive products whose relative prices are on a rise from time to time. Both standard neoclassical growth theory and the more recent endogenous growth theories pointed out those technological differences across nations were the primary explanation of long-term growth differences as well as of wealth and income inequality around the world (Romer, 1990). Neoclassical theory, however, considers technology as both universally available and applicable, and explains technological differences as variations in the endowments of production factors and infrastructure (Stokke, 2004). In contrast, endogenous growth theory drops two central assumptions of the Solow model, (i) that technological change is exogenous, and (ii) that the same technological opportunities are available in all countries. It considers that technology differences and the limited capability of developing countries to absorb new knowledge are the main reasons for persistent low productivity, and therefore for poverty (Lucas, 1990). Combining the findings of new trade and endogenous growth theory suggests that the interplay of economies of scale, externalities and national or 2009】 The Impacts of Vertical and Horizontal Export Diversification on Growth(YOKOYAMA & ALEMU) 65 international spillovers of knowledge and technology can be crucial for the diversification experience of “late-comers.” Generally, there are about five important channels of how diversification may influence growth or income: 1. Diversification may be considered as an input (a production factor) that increases the productivity of the other factors of production (Romer, 1990) ; 2. The second route is that diversification may increase income by expanding the possibilities to spread investment risks over a wider portfolio of economic sectors (Acemoglu and Zilibotti 1997) ; 3. Diversification is expected to have a positive contribution to Total Factor Productivity (TFP) growth, and by extension, to economic growth; 4. Diversification may also have a positive effect to growth because of the existence of economies of scope in production. Economies of scope exist when the same inputs generate greater per unit profits when spread across multiple outputs than dedicated to any one output; and 5. Through forward and backward linkages, production of a diversified export structure is also likely to provide stimulus for the creation of new industries and expansion of existing industries elsewhere in the economy (Hirschman, 1958). Similarly, Gylfason (2002) has clearly explained the interaction of diversification and economic growth along other variables as shown in the diagram below. Six Determinants of Growth Investment Trade Education Growth Stability Diversification Democracy 66 RITSUMEIKAN INTERNATIONAL AFFAIRS 【Vol. 7 The above diagram explains that there are about six different kinds of producible capital that are needed to sustain economic growth. First, saving and investment are obviously necessary to build up physical capital. Second, education is needed to build up human capital. Third, macroeconomic stability encourages the accumulation of financial capital, i.e. financial depth, which helps lubricate the wheels of production and thus increases economic efficiency and growth. Fourth, increased trade with the rest of the world helps to technology transfer as well as to strengthen the capital base of domestic activity. Fifth, increased democracy can be viewed as an investment in social capital by which is meant the infrastructural glue that hold society together and keeps it working harmoniously. Sixth, diversification is expected to increase income by expanding the possibilities to spread investment risks over a wider portfolio of economic sectors. As a whole, the model indicates that factors that are good for growth also encourage economic diversification. Therefore, it is important to investigate in details how vertical and horizontal exportdiversification, along other institutional and policy variables may affect a country’s growth in income per capita. The following section is dealing with this issues. IV. Determinants of Economic Growth Based on economic theories and previous empirical studies, the following independent variables have been indentified: (a) Vertical and Horizontal Diversification There is a positive relationship between export diversification (vertical and horizontal) and economic growth due to the roles it contributes in increasing returns to scale and dynamic spillover effects and (De Ferranti et al., 2002; Al-Marhubi, 2000; Hausmann, et al., 2006; Matthee and Naude, 2007; Funke and Ruhwedel, 2005). (b) Domestic Investment According to Solow model’s prediction, the investment rate is a key determinant of whether a country is rich or poor. Investment, in turn, depended on high saving rates. The neoclassical growth models of Solow-Swan and Ramsey also predict that, an exogenously higher value of I/Y raises the steady-state level of output per effective worker; the growth rate. 2009】 The Impacts of Vertical and Horizontal Export Diversification on Growth(YOKOYAMA & ALEMU) 67 (c) FDI Inflow FDI can increase competition, making domestic companies more efficient and stimulates sectoral and product diversification. In line with this, FDI would have a positive impact on industrialization as well as economic growth at large, since it adds to the domestic accumulation of resources. (d) Human Capital “If you plan for a year, plant a seed. If for ten years, plant a tree. If for a hundred years, teach the people. When you sow a seed once, you will reap a single harvest. When you teach the people, you will reap a hundred harvests” (K’uan-tzu, 551-470BC). It is also widely accepted that growth theory has considered human capital as the major determinant of economic growth. The stock of human capital has been proxied by the level of secondary school educational attainment. However, it should be noted that developing domestic human resources through education and training is along-term process to increase the innovative capacity of an economy. (e) Initial GDP per Capita The Solow-Swan and Ramsey hypothesis of ‘absolute convergence’ predicts that, poorer countries typically grow faster in income per capita in order to catch up to the richer countries. The Solow model, however, emphasized that economies may converge depending on why they differed in the first place. If two economies with the same steady state happened by historical accident to start off with different capital stocks, then we should expect them to converge. The economy with the smaller capital stock will naturally grow more quickly like exhibited in the case of Japan and Germany after the World War II. On the other hand, if two economies have different rates of saving, then we should not expect convergence. Instead each economy will approach its own steady state. (f) Population Growth The Solow model predicts that economies with higher rates of population growth will have lower levels of capital per worker and therefore lower incomes. The population variable is mainly used to see the scale effects. On the other hand, endogenous growth theory hypothesized that, larger economies would perform better. Thus, the effect of population growth on economic growth is ambiguous. (g) Exchange Rate In theory, the depreciation of the local currency exchange rate against the 68 RITSUMEIKAN INTERNATIONAL AFFAIRS 【Vol. 7 US$ should represent a window of opportunity for exports to be boosted. But, sometimes agricultural exports do not respond as expected, mainly due to lack of trade finance caused by the inefficient domestic banking system, the excessive dependence on imported inputs, which may be more expensive in local currency terms, and a decline in terms of trade during economic crises. When trade volumes do not respond to exchange-rate changes, the trade balance moves in the “wrong” direction: depreciation makes the country’s trade deficits rise in the short run, but it becomes rising to surpluses again; and this phenomenon is called the J-curve effect (Ito, 2001). Generally, it has been hypothesized that exchange rate has a positive link with economic growth. (h) Openness The degree of openness of a given country has been assumed to be one of the necessary stimulants to export and economic growth. For instance, until 1858, Japan was almost entirely isolated from world trade. In that year, the Japanese government ended self-imposed trade restrictions and began trading with the rest of the world. Once trade began, Japan specialized in three commodities: silk, silkworm eggs, and tea. Within 12 years after markets were opened, foreign trade had increased by 7,000 percent. Generally, the combination of improved terms of trade as well as the gains from adopting improved technologies from abroad may have accounted for as much as 65% rise in real national income (Huber, 1971; Husted and Melvin, 2007). (i) Political Instability Political Instability is inversely related with export diversification and economic growth due to the fact that rate of saving and investment tends to be low in countries with frequent wars, revolutions, and coups (Mankiw, 2003). (j) Rule of Law The links between rule of law and economic growth has been given due attention in recent days. It has been assumed that rule of law in a given country is positively and significantly related to growth. Thus, the independent variables and their expected relationships with economic growth have been summarized in table 7. 2009】 The Impacts of Vertical and Horizontal Export Diversification on Growth(YOKOYAMA & ALEMU) 69 Table 7 :- Independent variables, their expected signs and data sources Variable Indicator Vertical The Ratio of Manufactured Diversification Exports to Total Exports Horizontal Number of Export Products. Diversification +/- Data Sources + Own calculation based on data from World Bank and UNCTAD databases. + UNCTAD Database based on SITCs three-digit products classification Domestic Capital Ratio of GFCF to GDP + WDI Database FDI Ratio of net FDI to GDP + WDI Database Secondary School + Human Capital Initial GDP/C Barro-Lee (2000) and supplemented Enrollment Ratio to total by data from WDI for some countries population with age 15 and and for years beyond 2ooo for all above. countries in the sample. Real per capita GDP (initial) + IMF Database Population Growth Annual growth in population + Summer et al (2006) Penn World Table Exchange Rate Summer et al (2006) Penn World Exchange rate of local + currency with that of US$ Openness Degree of openness based on Table Version 6.2 + Sachs and Warner (1995) Political Instability Collier and Hoeffler’s (2004) Summer et al (2006) Penn World Table Version 6.2 - ‘War dummies’ for countries Collier and Hoeffler (2004) war index tables suffered from war. Rule of Law Civil Liberty Index + World Freedom House V. The Data and stylized Facts This study has made an intensive empirical analysis for a panel of 41 countries (32 from SSA and 9 from East Asia) 1975 to 2004. Panel data are better able to identify and measure effects that are simply not detectable in pure-cross sections or pure time series data. Inline with this, annual data should be avoided in growth studies since the results might be affected by short-run business cycle effects (Folster and Henrekson, 2001). Thus, the averages over five-year periods are used instead of annual observations resulting in a six- five year periods covering the 1975 to 2004 time span. Hence, except initial GDP per capita and initial human capitals which were only measured at the beginning of each five-year peri- 70 RITSUMEIKAN INTERNATIONAL AFFAIRS 【Vol. 7 ods, the remaining explanatory variables are measured in their averages over a five-year period. Although ‘school enrollment’ has been taken as a proxy for education (human capital), ‘education-square’ has also been included to capture diminishing or increasing effects on the dependent variable (GDP/Capita growth). It is widely known that quadratic functions are used quite often in applied economics to capture decreasing or increasing marginal effects. Accordingly, when the coefficient on education is positive and the coefficient on education-square is negative, the quadratic has a parabolic shape. On the other hand, when the coefficient on education is negative and the coefficient on education-square is positive, the quadratic has a U-shape with the implication of increasing marginal effects (Wooldridge, 2006:201). This implies that, at lower value of education (school enrollment ratio), there is no as such significant effect on GDP/C growth. At some point, however, the effect becomes positive and very significant. In practice, it is important to know where this turning point is. Accordingly, the turning point (minimum or maximum) of the function is always achieved at the coefficient on education (school enrollment ratio) over the absolute value of the coefficient on education-square: X* = | b1 / (2 b2 ) | , where, b1 and b2 are the coefficients of the education and education-square variables, respectively. VI. RESEARCH METHODOLOGY AND ESTIMATION Measuring Diversification An increasing export orientation of the manufacturing sector, accompanied by a rising share of manufactures in total exports, is part of the “normal” pattern of structural change in the growth process of developing countries. Since vertical diversification (VDIV) mainly implies out of primary into manufactured exports, it can be measured by the share of manufactured exports to total exports [Elbadawi, 1999; Hood and Mayer, 2001; Munemo, 2007; and others] VDIV = (TMX) / (TX) (1) Where, VDIV is the index of vertical diversification, TMX is value of total manufactured exports, and TX is value of total exports. Similar to the works of Herzer and Nowak-Lehmann (2006), horizon- The Impacts of Vertical and Horizontal Export Diversification on Growth(YOKOYAMA & ALEMU) 71 2009】 tal diversification (HDIV) in this study has been proxied by the number of export sectors classified by the Standard International Trade Classification (SITC) at the three-digit level. Thus, the maximum value of the index is 239 (the number of individual three-digit products in SITC revision 2), and its minimum (theoretical) value is zero, for a country with no exports. UNCTAD annually present the number of products exported (or imported) at the three-digit SITC, with those products that are greater than $100,000 or more than 0.3 per cent of the country total exports (or imports). Hence, the vertical and horizontal diversification of SSA and East Asia countries have been estimated and presented in fig 2 & 3 below. Figure 2 : Vertical Export Diversification in SSA and East Asia, 1975 and 2004 Vertical Diversification in SSA and East Asia 200 180 160 VDIV Index 140 120 2004 100 1975 80 60 40 20 C B ur ki na fa am so er oo C on n go D C R on go R . E th io pi a G ha na Ke ny M a au r it iu s N ig er ia S .A fr i ca U ga Zi nd a m ba bw e C h In ina do ne s Ko ia re a R M . al P ays hi i a lip pi ne S s in ga po r Th e ai la nd 0 Country Figure 3 : Horizontal Export Diversification in SSA and East Asia, 1975 and 2004 Horizontal Diversification in SSA and East Asia 500 450 400 350 HDIV 300 2004 250 1975 200 150 100 50 ki ur B C na fa am so er C oo on n go C DR on go E R. th io pi G a ha na Ke ny M a au rit iu N s ig er S . A ia fr i c U a ga Zi n m da ba bw e C hi n In do a ne Ko sia re a M R. al ay P hi sia lip p S in in es ga po Th re ai la nd 0 Country 72 RITSUMEIKAN INTERNATIONAL AFFAIRS 【Vol. 7 The Growth Model The augmented Solow-Swan Model based on Mankiw, Romer, Weil (1992) for growth has assumed the following augmented Cobb-Douglas production function with three inputs: Y = K a Hl (AL) 1-a-l (2) Where Y is output, K is physical capital, H is human capital, A is the level of technology, and L is labor. The parameters a and l are positive, and a+l< 1. Yit=b0+b1HUMCAPit +b2 DOMINVit+b3 FDIit+b4 VDIVit+b5 HDIVit b6 Zit+eit (3) Where i indexes the countries under study, t denotes the year, and Zitrepresents the set of additional control variables including macroeconomic policy variables as mentioned in Table 9 of section 3 of this paper, and eit is the idiosyncratic errors. Thus, the model takes both the crosssection dimension and the time-series dimensions into consideration. There is a reverse causation from diversification to growth, and again from growth to diversification as noted by Imbs and Wacziarg (2003). Similarly, there is a reverse causation from growth to investment, in addition to the causation from investment to growth like noted by Blomstrom, Lipsey, and Zejan (1993) ; Barro and Sala-i-Martin (1998). In other words, not only investment causes economic growth, but also economic growth influences the propensity to invest. In doing so, one should decide whether it is necessary to use an instrumental variable, i.e., whether a set of estimates are consistent or not. Davidson and Mackinnon (1993) suggest an augmented regression test called Durbin-Wu-Hausman (DWH test) test for endogeneity, which can easily be carried out for the residuals of each endogenous right-hand side variable, as a function of all exogenous variables. Accordingly, the Durbin-Wu-Hausman test for the suspected endogenous variables and the test-statistic results are displayed in table 8 below. 2009】 The Impacts of Vertical and Horizontal Export Diversification on Growth(YOKOYAMA & ALEMU) 73 Table 8 : DWH test for Endogeneity and Results Variables Vertical Diversification Horizontal Diversification Domestic Investment Foreign Direct Investment Openness Exchange Rate GDP Initial Test for Residuals vdiv_res =0 hdiv_res =0 gfcf_res =0 fdigdp_res =0 openness_res =0 exchange_res =0 GDP initial_res =0 P-Value 0.0061*** 0.0001*** 0.0986* 0.0001*** 0.0078*** 0.0005*** 0.0000*** Hence, from table 8 we can note that, except the domestic investment variable which has become significant at 10% level, all suspected endogenous variables have become statistically significant at 1% level. In other words, the above variables are indeed endogenous and should be instrumented with appropriate instrumental variables. Therefore, if the assumption of strict exogeneity of the explanatory variables with the idiosyncratic errors fails, then, we can’t apply the common panel data analysis approaches such as random effects, fixed effects, and first differencing methods. As a result, a 3SLS with instrumental variables will be employed in addition to SUR techniques. The instruments comprise some of the original variables and lags of the other variables; lag variables are reasonable candidates as instruments because the correlation of the residuals in the growth regressions between the two periods is never substantial (Barro and Sala-i-Martin (2001). Accordingly, the average value of Vertical Diversification, Horizontal Diversification, Domestic Investment, FDI, Exchange Rare, and Degree of Openness for the preceding five years have been considered as instruments for the above variables respectively. On the other hand, School Enrollment Ratio, Population Growth, Political Instability and Rule of Law are considered as pre-determined, and they enter as their own instruments in the regressions. In line with this, test for heteroscedasticity was conducted using Breusch-Pagan test, White test, and Cook-Weisberg (Score) test and as a result the null-hypothesis of homoskedasticity was rejected at 1%, 1%, and 10% significance levels, respectively. This implies that there is evidence of heteroskedasticity in which the error variance is not constant. Hence, corrective measures were taken and the standard errors have been adjusted 74 RITSUMEIKAN INTERNATIONAL AFFAIRS 【Vol. 7 accordingly. Likewise, test for serial correlation for the error terms was conducted using Wooldridge test for autocorrelation in panel data and the result yields a p-value of 0.2641, that implies there is no evidence of serial correlation (first order autocorrelation) and hence the error terms are not correlated. Moreover, though stationary test for panel data is a recent phenomenon, this study employed the Levin-Lin-Chu for stationarity test and as a result the null-hypothesis of non-stationarity was rejected at 1% significance level; i.e. the growth dependent variable is stable with constant mean, variance and standard error. VII. EMPIRICAL RESULTS AND MAIN FINDINGS Descriptive Statistics The average growth in income per capita for the full sample (table 9) was about 1.2 % with a minimum growth rate of -12 percent and a maximum growth rate of 11 percent. Looking the same statistics from the subsamples of SSA and East Asia will confirm that the average growth in income per capita in SSA was only 0.21 percent, while that of East Asia was 4.64 percent in the same period of time. What is astonishing most is also the wide variation recorded in income per capita growth that ranges from -12 percent (minimum) to about 11 percent (maximum). This implies that SSA countries themselves are characterized by wide variation in economic performance due to various institutional and country specific macroeconomic policy constraints. On the other hand growth in income per capita in East Asia also varies from -1.2 percent (minimum) to 9.6 percent (maximum). 2009】 The Impacts of Vertical and Horizontal Export Diversification on Growth(YOKOYAMA & ALEMU) 75 Table 9 : Descriptive Statistics for the Full-Sample Variable Observation Mean Std. Dev. Minimum maximum GDP/Capita Growth 246 1.180 3.648 -12 11 Vertical Diversification 246 24.914 28.962 0.001 96.4 Horizontal Diversification 246 94.001 76.024 4.8 233 Domestic Investment 246 19.999 8.236 3.6 48 Foreign Direct Investment 246 1.913 3.325 -5.4 26.36 Initial Human Capital 246 17.953 15.217 0.9 61.9 Human Capital-Square 246 552.931 804.038 0.81 3831.61 Population Growth 246 2.386 1.034 -5 6 Initial GDP (in log) 246 3.136 0.483 2.292 4.469 Exchange Rate (in log ) 246 1.58 1.802 -11.539 4.321 Openness 246 13.993 5.864 5.944 54.376 Political Instability 246 0.293 0.456 0 1 Rule of Law 246 4.675 1.447 1 7 In the same token, though the average vertical diversification index in the full-sample was only 24.9 percent, a close look at the sub-samples again confirms that SSA has recorded only 12 percent compared to East Asia’s 66 percent outstanding performance. The divergent performance of East Asia and SSA in economic activities is not only bounded with vertical diversification; but also in horizontal diversification as well. The evidences from table 10 and table 11 again imply that the average number of export goods from SSA was estimated only at 64, while it was about 202 for East Asia. Generally, the evidences show that East Asia and SSA have become more and more divergent in their diversification performances both vertically and horizontally. 76 RITSUMEIKAN INTERNATIONAL AFFAIRS 【Vol. 7 Table 10 : Descriptive Statistics for SSA Sub-Sample Variable Observation Mean Std. Dev. Minimum Maximum GDP/Capita Growth 192 0.208 3.336 -12 11 Vertical Diversification 192 13.394 15.359 0.001 74.426 Horizontal Diversification 192 63.728 53.373 4.8 233 Domestic Investment 192 17.491 7.034 3.6 48 FDI 192 1.529 2.864 -5.4 26.36 Initial Human Capital 192 13.215 11.792 0.9 57 Human Capital-Square 192 312.948 562.548 0.81 3249 Population Growth 192 2.609 0.984 -5 6 Initial GDP (in log) 192 2.995 0.373 2.292 4.180 Exchange Rate (in log ) 192 1.614 1.963 -11.539 4.321 Openness 192 14.758 6.272 5.944 54.376 Political Instability 192 0.313 0.465 0 1 Rule of Law 192 4.919 1.281 1.6 7 Table 11 : Descriptive Statistics for East Asia Sub-Sample Variable Observation Mean GDP/Capita Growth 54 4.636 Std. Dev. Minimum 2.415 -1.2 Maximum 9.6 Vertical Diversification 54 65.877 28.930 1.775 96.4 Horizontal Diversification 54 201.638 36.432 91 232.8 Domestic Investment 54 28.919 5.605 17.6 45.8 FDI 54 3.280 4.372 -0.82 17.84 Initial Human Capital 54 34.8 14.101 8.3 61.9 Human Capital-Square 54 1406.20 947.383 68.89 3831.61 Population Growth 54 1.593 0.793 0 3.2 Initial GDP (in log) 54 3.638 0.501 2.362 4.469 Exchange Rate (in log ) 54 1.474 1.056 0.185 3.958 Openness 54 11.271 2.749 6.420 17.674 Political Instability (War Dummy) 54 0.222 0.420 0 1 Rule of Law 54 3.807 1.667 1 7 Similar statistics on the other important variables in the two regions confirm similar scenarios as we exhibited it in the case of diversification performances. For instance, the average fixed capital formation as a ratio of GDP in East Asia was about 29 percent, whilst it was only 18 percent in SSA. Similarly, the average FDI ratio to GDP in East Asia was recorded at 2009】 The Impacts of Vertical and Horizontal Export Diversification on Growth(YOKOYAMA & ALEMU) 77 3.3 percent, while it was only 1.5 percent in SSA. Similar comparison of SSA and East Asia in terms of their secondary schooling attainment varies from an average of 13 percent for SSA to 35 percent for East Asia. In line with other previous studies, the descriptive statistics from the subsamples show that the average population growth in SSA was about 2.61 percent, while it was only about 1.6 percent for East Asia. Since the majority of SSA’s populations are under working age, it has been believed that the higher and fast population growth rate has also contributed for the sluggish economic growth in the continent. Regression Results and Main Findings The empirical results for the full-sample has been provided by table 12 in which the first three columns are based on SURE estimation techniques under different scenarios, whereas, columns 4, 5, and 6 display the results based on instrumental variables estimation using simultaneous equations. Accordingly, ‘vertical export diversification’ has been found to be one of the major determinants of economic growth which is statistically significant at 1 percent level using SURE estimation techniques. Likewise, vertical diversification has become again the most important positive determinant of growth even when the variables are instrumented for endogeneity concerns. For instance, the coefficient for vertical diversification in column 1 of table 12 implies that a one percentage increase in the share of manufactured products in total exports results in a 4.4 percent increase in GDP per capita. The coefficient of this same variable has become 0.0336 when it has become instrumented, and this again implies that a one percentage increase in the share of manufactured products in total exports results in 3.4 percent increase in GDP per capita. It is however interesting to note that the importance of vertical diversification to GDP per capita growth is not similar between East Asia and SSA. For instance, column 1 of table 13 shows that a one percentage increase in the share of manufactured products in total exports may contribute in more than 5 percent increase in GDP per capita growth in East Asia. 78 RITSUMEIKAN INTERNATIONAL AFFAIRS 【Vol. 7 Table 12 : SURE & 3SLS Estimations with Instrumental Variables for the full sample GDP/C growth Vertical Diversification Horizontal Diversification Domestic SURE-I .0444*** (.0105) .0017 (.0040) .2169*** SURE-II .0415*** (.0107) .0022 (.0039) .2201*** SURE-III .0394*** (.0108) .0004 (.004) .221*** INST-I .0336** (.0132) .0084* (.005) .1157*** INST-II .0291** (.0134) .0094* (.0051) .1254*** INST-III .0285** (.0139) .0072 (.0053) .1221*** Investment FDI (.0277) .1812*** (.0594) -2.5357*** (.6531) -.0086 (.0476) .001 (.0008) .1035 (.2042) .7557* (.4129) .2621 (.0979) (.0276) .1819*** (.0592) -2.782*** (.6744) -.0103 (.0474) .001 (.001) .0857 (.2038) .8532** (.4173) .2743*** (.0993) -.2104 (.1517) (.0276) .1742*** (.0591) -2.532*** (.6488) -.003 (.0473) .0007 (.0008) .0946 (.2029) .4986 (.434) .2920*** (.0974) (.0444) .3353*** (.1001) -2.918*** (.7495) -.0124 (.0512) .0011 (.001) .0215 (.2157) .4517 (.4382) .3859*** (.1060) (.0443) .3449*** (.0997) -3.286*** (.7721) -.0183 (.051) .001 (.001) -.0103 (.2155) .5708 (.4423) .3541*** (.1074) -.2413 (.1591) (.0442) .3321*** (.1014) -2.865*** (.7455) -.0092 (.0511) .0011 (.0009) .0141 (.2140) .2621 (.484) .3806*** (.1053) -.0616* (.0339) 3.0591 (2.0116) 246 .4548 -.0485 (.0524) 4.6567** 6.8977*** 5.2681*** (2.2641) (2.6569) (2.3529) 246 246 246 .4063 .4113 .4155 Initial GDP/C Education (Initial) EducationSquare Population Growth Political Instability Foreign Exchangex Rule of Law Openness Constant No.of obs. R Square 2.0659) (1.9485 246 .4475 3.8736* (2.3378) 246 .4518 2009】 The Impacts of Vertical and Horizontal Export Diversification on Growth(YOKOYAMA & ALEMU) 79 Table 13 : SURE and 3SLS Estimations with Instrumental Variables for East Asia GDP/C growth Vertical Diversification Horizontal Diversification Domestic SURE-I 0513*** (.0163) .0075 (.0086) .1055** SURE-II .0581*** (.0159) -.0002 (.009) .0598 SURE-III .0545*** (.0171) .0069 (.0087) .1051** INST-I .0506** (.0243) .0213 (.0151) -.0479 INST-II .0554** (.0221) .0078 (.016) -.0944 INST-III .0765*** (.0253) .0112 (.0146) -.030 Investment FDI (.0512) .2581*** (.0781) -5.052*** (.7879) -.1537 (.097) .0022 (.0015) .3537 (.4025) -1.4317 (.9375) 3623 (.3793) (.0534) .1906** (.0812) -3.758*** (.9644) -.2013 (.0956) .0029** (.0014) .3296 (.3864) -1.4754 (.8996) .1963 (.3719) .4871** (.2254) (.0510) .275*** (.0836) -5.169*** (.8134) -.1612 (.0977) .0023 (.0015) .3851 (.4054) -1.2945 (.9668) .3869 (.3808) (.1422) .4736*** (.1201) -6.726*** (1.0796) -.194 (.1156) .0029* (.0017) .7017 (.5726) -2.7712 (1.6988) .9399* (.5185) (.159) .3435*** (.1456) -4.861*** (1.777) -.2229 (.1105) .0035** (.0017) .6337 (.5222) -2.8844* (1.6411) .6424 (1.6411) .5151 (.4249) (.1419) .5824*** (.1516) -7.473*** (1.2636) -.2301 (.1212) .0032* (.0018) .7507 (.6001) -1.810 (1.6031) 1.0295* (.5537) Initial GDP/C Education (Initial) EducationSquare Population Growth Political Instability Exchange Rate Rule of Law Openness Constant No.of obs.. R Square .0533 (.0956) 15.714*** 12.668*** 15.44*** 93.0867) (3.2795) (3.117) 54 54 54 .5669 .6013 .5693 .2876* (.1632) 22.05*** 18.316*** 21.476*** (4.7559) (4.2591) (4.8131) 54 54 54 .4407 .5077 .4045 Where as in SSA, except column 2 of table 14, there was no evidence that vertical diversification contributed for growth in income per capita. This is mainly because of the share of manufactured products in total exports in SSA has still been under the threshold level to make any impact on economic growth. This calls for SSA to have a strong effort to vertically diver- 80 RITSUMEIKAN INTERNATIONAL AFFAIRS 【Vol. 7 sify its exports from the existing few primary products to a large mix of value-added manufactured products; as witnessed in East Asia. On the other hand, the study confirms that, though horizontal diversification is still positively correlated with growth in income per capita, its contribution to growth was not found to be so impressive compared to vertical diversification. The empirical evidence from the regression analysis of the full-sample (table12) highlighted that it is only in some cases (column 4 &5 of table 12) that horizontal diversification is statistically significant at 10 percent level. Accordingly, the coefficients of horizontal diversification in columns 4 & 5 from the full sample imply that a one percentage increase in numbers in export sectors will increase GDP/Capita by only 0.8% and 0.9%, respectively. In fact, the analyses from the sub-samples have not confirmed any significant relationship between horizontal export diversification and growth in GDP per capita. 2009】 The Impacts of Vertical and Horizontal Export Diversification on Growth(YOKOYAMA & ALEMU) 81 Table 14 : SURE and 3SLS Estimations with Instrumental Variables for SSA GDP/C growth Vertical Diversification Horizontal Diversification Domestic Investment FDI Initial GDP/C Education (Initial) EducationSquare Population Growth Political Instability Exchange Rate Rule of Law SURE-I .0293 (.0227) -.0027 (.0065) .0012 (.0675) .5289** SURE-II .0385** (.0157) -.0035 (.0048) .1739*** (.0345) .1802** SURE-III .0268 (.0229) -.0033 (.0067) .01 (.069) .5004* INST-I .0293 (.0226) -.0026 (.0065) .0012 (.0675) .529** INST-II .01919 (.0229) -.0014 (.0062) .0301 (.0648) .4356* INST-III .0268 (.0229) -.0033 (.0068) .01 (.0694) .5004* (.2481) -.0903 -1.123 -.0659 (.0685) .0015 (.0013) .3687 (.2633) .4296 (.5729) .3933*** (.1284) (.0832) -1.4078 (.9129) -.0747 (.0594) .0019* (.0011) .3297 (.2324) -1.288*** (.4977) .2991*** (.108) -.4865** (.1889) (.2599) -.1664 -1.1295 -.064 (.0682) .0016 (.0013) .3687 (.2607) .3128 (.604) .3939 (.1273) (.248) -.0903 -1.123 -.0659 (.0685) .0015 (.0013) .3687 (.2633) .4296 (.5729) .3933*** (.1284) (.2492) -.7299 -1.0798 -.0769 (9.0658) .0017 (.0013) .3143 (.2535) .8377 (.5788) .355*** (.1233) -.5021** (.2146) (.2598) -.1664 -1.1295 -.064 (.0682) .0016 (.0013) .3687 (.2607) .3128 (.604) .3939*** (.1273) Openness Constant No.of obs.. R Square -1.8964 (2.9557) 192 .1666 1.861 (2.901) 192 .3078 -.0332 (.0632) -1.2504 (3.2251) 192 .1829 -1.8965 (2.9557) 192 .1666 2.3266 (3.2338) 192 .2267 -.0332 (.0632) -1.25 (.0632) 192 .1829 Thus, although we can’t rule out the positive impact of horizontal diversification to economic growth, it is more evident that vertical diversification is the main engine of growth, and this was exactly what East Asians’ did in the past. Eventually, what SSA has to learn from East Asia is that, policy makers in the region should give more focus on vertical diversification towards value-added products than the horizontal one. 82 RITSUMEIKAN INTERNATIONAL AFFAIRS 【Vol. 7 The study also asserts that domestic investment and FDI are strong key factors for growth in income per capita (table 12), inline with our proposition at the outset. For instance, the coefficient of ‘domestic investment’ from column 1 of table 12 indicates that a one percentage increase in the ratio of fixed capital formation to total GDP will increase GDP/capita by 21.7 percent. Similarly, the results from the instrumental variable estimation in the same table confirms that, a one percent increase in the ratio of gross fixed capital formation to GDP yields about 11.5%, 12.5%, and 12.2% increases in growth in GDP per capita as displayed in column 4, 5, and 6 of table 12, respectively. Similar to domestic investment, FDI has been found to be a very strong factor to induce growth in income per capita as shown in table 12. For instance, the instrumental variable estimations from columns 4-6 of table13 show that a one percent increase in the ratio of FDI to GDP would result in 33.5%, 34.5%, and 33.2% increase in GDP/C growth, respectively. Interestingly, the results from the full-sample analysis are more or less consistent with the results from the SSA and East Asia sub-samples (table 14 &13). Particularly, the results from East Asia sample confirmed that FDI has been one of the major factors for the regions fast growth in income per capita for the last three decades. If we single out column 6 of table 14, we can find that a one percent increase in the ratio of FDI to GDP in East Asia may bring a 58.2 percent increase in GDP/C growth. The effect of FDI to growth in GDP/C has been less significant in SSA compared to East Asia as expected. This is mainly because of FDI in SSA is too low and concentrated only in few oil producing and mineral-rich countries like Nigeria, Angola, and South Africa. The empirical evidences from the sub-samples confirm that, it was FDI more than domestic capital, which contributed to economic growth in East Asia. However, this doesn’t mean that East Asia’s high saving tradition didn’t contribute for economic growth in the each country of the region. Yes, it did; but not as much as the contribution of FDI to growth. What lessons can be learned from East Asia is that, SSA countries should do their utmost efforts to attract FDI by creating a conducive atmosphere including political stability, macroeconomic stability and favorable institutions so as to minimize investment risks. The ‘Education’ variable which was proxied by the level of educational enrollment has been recognized as one of the main determinants for eco- 2009】 The Impacts of Vertical and Horizontal Export Diversification on Growth(YOKOYAMA & ALEMU) 83 nomic growth. In this study, the marginal effects of education has been analyzed by including the ‘square’ of the education variable as it has been commonly practiced by various researchers, since there is strong justification that school enrollment/attainment would have a delayed effect after a certain point. In other words, including square of ‘school enrollment ratio’ can capture whether or not education has a diminishing or increasing effects on growth in GDP/C. Accordingly, it has been found that the coefficient on school enrollment ratio is negative and the coefficient on education-square is positive, which implies that the growth model will exhibit a U-shape with the implication of increasing marginal effects. The interpretation for such kind of results is that, at lower value of school enrollment, an additional school enrollment will not have a significant effect on growth. At some point, however, the effect becomes positive and very significant. In this case, the empirical evidence from our analysis shows that the marginal effect of education has become statistically significant in the case of East Asia; rather than SSA. For instance, the marginal effect of school enrollment to growth in East Asia from table 13 was found to be 0.3 percent using instrumental variable estimations. The significance of the education variable in SSA sub-sample is even too minimal and this is mainly due to the low level of educated labor which is under the threshold level with no significant effect on growth. In practice, it is important to know where this turning point of the marginal effect of education to be positive will occur. According to Wooldridge (2002), the turning point (minimum or maximum) of the function is always achieved at the coefficient on education over the absolute value of the coefficient on education-square and roughly estimated as follows: Education* = | b1 / (2 b2 ) | Where, b 1 and b 2 are the coefficients of education and educationsquare, respectively. For instance, the coefficients of education and education-square in column 4 of table 13 of the East Asian sample have been 0.194 and 0.0029, respectively. Thus, the turning point (minimum) value of school enrolment ratio can be calculated as: Education* = | -0.194/ 2 (0.0029) | = | -0.194/0.0058| = 33.5 This implies that it is only after a school enrollment ratio of 33.5 % that the role of education will be significant to growth in GDP/C. Where as, the average school enrollment ratio estimated for SSA in the descrip- 84 RITSUMEIKAN INTERNATIONAL AFFAIRS 【Vol. 7 tive statistics (table 10) was only 13.2 % which is too low in stimulating economic growth in the region and that is why the education variable has become less significant in SSA’s sub-sample. However, it is obvious that the availability of a large pool of skilled labor force is a pre-requisite for FDI inflow as well as for a country to diversify its economy and exports. One of the most notable results from the full sample analysis is that, initial GDP per capita is found to be a strong negative determinant to growth in income per capita, which confirms the Solow-Swan- Ramsey hypothesis of absolute convergence such that poorer countries grow faster than the richer ones and thereby catch up to the richer countries. For instance, the coefficient for initial GDP/C in column 1 of table 12 for the full-sample analysis is estimated at -2.5357. This implies that convergence occurs at the rate of 2.5% per year. The results of the full-sample analysis on the effect of initial GDP/C on growth is quite consistent with the results in the East Asia’s sub-sample analysis (table 13). In fact, the rate of convergence in East Asia has been recorded much higher than the rate of growth estimated for the full samples. For instance, the coefficients of initial GDP/C in columns 4, 5, and 6 of table 13 show that convergence occurs at the rate of 6.7 %, 4.95, and 7.5%, respectively. These results appear to be much close to the realty in the ground that East Asia has started from a very low level of income per capita, and achieved a tremendous success in it, which is now more close to the developed world. However, this same variable (initial GDP/Capita) in the SSA sub-sample (table 14) was not found to be significant; regardless of its negative sign as theoretically proposed. This implies that there was no significant evidence of convergence in SSA to catch up with rich countries in the past three decades. This again confirms that SSA which was once in equal level of income per capita with East Asia had experienced a stagnated and sometimes a retarded economic growth for the past three decades. However, though it was not significant, the negative sign of the coefficient points out some indications of convergence in the region. Theoretically, the effect of population growth to economic growth is disputable. On one hand, the Solow model predicts that economies with higher rates of population growth will have lower levels of capital per worker and therefore lower incomes. On the other hand, the endogenous growth theory predicts that population has scale effects and hence larger population and larger economies perform better. Coming to the empirical 2009】 The Impacts of Vertical and Horizontal Export Diversification on Growth(YOKOYAMA & ALEMU) 85 results in our analysis both for the full-sample and the sub-samples, no evidence has been found for population growth to be a significant factor for growth in income per capita. Foreign exchange has been found to be positively and statistically significant at 1 percent level and implies that a depreciating local currency would result for stimulating production and boosting exports. For instance, column 4, 5, and 6 of the instrumental variable estimation in table 12 implies that a one percentage decease in the value of the local currency against US$ will result a 0.4% increase in GDP per capita growth. Finally, other control variables such as degree of openness, property rights have been found to be significant determinants of economic growth in the case of East Asia. Where as, political instability has been found to be a negative factor for economic growth as it is mainly noted in the case of Sub-Saharan Africa. It is evident that in countries with frequent wars and political turmoil, the rate of saving and investment tends to be low. Generally, East Asia’s success was highly attributed by their huge investment on human capital through education and the high rate of physical capital accumulation mainly driven by foreign direct investment (FDI). Quite the opposite, the level of human capital (skilled labor) and physical capital formation including the level of FDI in SSA has been under the threshold level in playing a positive role to materialize a structural change in the economy. In line with this, countries in East Asia have managed to diversify their economies and exports mainly vertically and transformed their economies from being exporters of few primary commodities in the late 1960s and early 1970s to exporter of high valued manufacturing and service products after the mid-1980s. Unfortunately, SSA’s export diversification attempt was too minimal and most of the countries in the continent are still dependent on the export of few agricultural and mineral products which are highly vulnerable for price shocks. The paper then argues that the inference that SSA can replicate the East Asian experience is largely relevant as long as countries in SSA create favorable conditions as discussed above. VIII. CONCLUSION AND POLICY RECOMMENDATIONS First of all, the empirical results confirmed that export diversification; 86 RITSUMEIKAN INTERNATIONAL AFFAIRS 【Vol. 7 especially vertical diversification played a vital role to induce economic growth in the case of East Asia. East Asia’s success was highly attributed by their huge investment on human capital through education and the high rate of physical capital accumulation mainly driven by foreign direct investment (FDI). Conversely, the level of human capital (skilled labor) and physical capital including FDI in SSA has been under the threshold level in playing a positive role to materialize significant export diversification and structural change in the economy. Secondly, the empirical results from this research have revealed that it is ‘vertical diversification’ which is more important than the horizontal one to stimulate economic growth. This, therefore, calls into question the policy advice of some researchers that proposed Africa’s emphasis should be on horizontal diversification through increasing the number of primary export products. Thirdly, diversification in general and vertical diversification in particular in SSA would not be an easy task: countries seeking to diversify must have sufficient levels of human and physical capital as well as an adequate infrastructure to support the export diversification strategies. Moreover, stronger production linkages between the particular country and the world’s leading multinational companies should be created mainly through foreign direct investment. Fourthly, the success of East Asian countries to shift from producing a low productive primary commodities to producing a more productive manufactured products reflects even latecomers are able to specialize in high growth areas if some of the pre-conditions are fulfilled. 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