SOURCES OF ECONOMIC GROWTH IN THE SOUTHERN AFRICAN DEVELOPMENT COMMUNITY (SADC)

Sources Asian-African of Economic Journal Growth of Economics in the Southern and Econometrics, African Development Vol. 14, No. Community 2, 2014: 185-193 (SADC) 185 SOURCES OF ECONOMIC GROWTH IN THE SOUTHERN AFRICAN DEVELOPMENT COMMUNITY (SADC) Christopher Mupimpila * * Department of Economics, University of Botswana, Private Bag 0022, Gaborone, Botswana, E-mail: mupimpi@mopipi.ub.bw ABSTRACT This study analyzes the sources of economic growth in the Southern African Development Community (SADC) using panel data for the period 1990 to 2011. The study finds that economic growth in SADC is positively and significantly determined by labour, physical capital, exports, human capital, and infrastructure. Properly conceived, these factors can induce structural change and enhanced regional integration in SADC.The negative but significant determinants of economic growth in SADC are: inflation and total debt service on external debt. Therefore, economic growth in SADC requires a stable macroeconomic environment in which countries are net creditors. For higher and sustained economic growth, it is necessary to have structural change in SADC. JEL Codes:C23, O41, O47. Key words: SADC, economic growth, Dutch disease, export promotion, human capital, and macroeconomic stability. I. INTRODUCTION What are the causes of economic growth? Denison (1967) studied the United States of America and eight European countries, and found labour to be significant for economic growth. His study was restricted to sources of growth in developed countries for the period 1950 to 1962. By contrast, Robinson (1971) analyzed the economic growth of thirty-nine developing countries for the period 1958 to 1966, and found labour to be insignificant for growth in these countries. However, Hagen and Hawrylyshyn (1969), and Chenery et al. (1970) studied both developed and developing countries, and found structural variables to be significant for growth in developing countries only. Elias (1992) examined the sources of economic growth of seven Latin American countries from 1940 to 1985, and found capital to be the major source of growth for these countries. Clearly, empirical evidence shows that the sources of growth vary across time and space. The determinants of economic growth vary over time and across countries. Therefore, for different times and regions, the question is: what causes economic growth? Furthermore, in the context of regional integration, studying the sources of growth generates information that enhances regional integration. As Mills and Sidiropoulos (2001) have argued, economic growth deepens regional integration.

186 Christopher Mupimpila The present study examines the sources of economic growth in the Southern African Development Community (SADC). The SADC member countries are: Angola, Botswana, the Democratic Republic of Congo, Lesotho, Madagascar, Malawi, Mauritius, Mozambique, Namibia, the Seychelles, South Africa, Swaziland, Zambia, and Zimbabwe. As is the case of other regional blocs, the aim of SADC is to promote economic integration among member countries. This study uses panel data analysis to determine the sources of economic growth in SADC for the period 1990 to 2011. Section 2 of this paper describes the methodology and data. Section 3 discusses the empirical findings, and this is followed by a summary and conclusions in section 4. II. METHODOLOGY AND DATA Based on Solow (1957), the sources-of-growth approach specifies the aggregate production function: Q t = A t F(K t, L t ) (1) Where Q t is output, A t is technological progress, K t is capital stock, L t is labour, and t is time. Taking time derivatives of equation (1), and with further manipulation, yields: Q K L A (2) K Where Q, K, L, and A are the proportional growth rates of Q, K, L, and A respectively, K is the elasticity of output with respect to K, and L is the elasticity of output with respect to L. The Solow growth model assumes exogenous technology with positive but diminishing marginal product of capital. However, it has been argued, under such conditions, sustained economic growth is not possible in the long-run. As a result, other researchers have employed endogenous growth models in which technological change arises from the accumulation of new knowledge generated by research and development (Romer 1986, 1990; Lucas, 1988; Mankiw et.el.,1992). In these models, there are two forms of capital: physical capital and human capital; with the latter being a function of new knowledge. Romer (1990) observes that there is increasing marginal productivity of knowledge, and this can sufficiently override the decreasing marginal productivity of physical capital, resulting in increasing marginal productivity of total capital. He then concludes that sustained long-run economic growth is possible under endogenous technology and increasing returns to knowledge. Thus, for empirical purposes, equation (2) is augmented by other variables, besides labour and capital (Mankiw et. al., 1990; Chenery et. al., 1986). In the present study, the estimated equation is: it i it i it it Y X Z (3) Where i = 1, 2,..., cross-sections, the SADC countries, observed over periods t = 1,2,...,T, 1990 to 2011; Y is real gross domestic product, X represents the conventional factors of production, labour and capital. In this study, LFTOT denotes the total labour force, and GFCF represents gross fixed capital formation, the proxy for physical capital. In equation (3), Z is a vector of other sources of economic growth, besides labour and capital. These L

Sources of Economic Growth in the Southern African Development Community (SADC) 187 variables are as follows. IMPT and EXPT denote real imports and exports respectively, while FDI is foreign direct investment, and DEBT is the total debt service on the external debt. The variable INF is the annual rate of inflation as measured by the consumer price index. SESEC is the total secondary school enrolment as a percentage of the total population of official secondary school age. This is the human capital variable in this study. The variable INFRA denotes infrastructure and is proxied by telephone lines per 100 people. In the model, the error term is. The data for this study is from the World Development Indicators published by the World Bank. All the variables are in United States Dollars, except for inflation, secondary school enrolment, and telephone lines per 100 people. The data for all the variables is for the period 1990 to 2011. III. EMPIRICAL FINDINGS Table 1 shows the results of the panel unit root tests. The tests used in this study are the Levin, Lin, and Chu (LCC) test, and the Augmented Dickey Fuller-Fisher (ADF-Fisher) test. Both tests present the null hypothesis that unit root is present while the alternative is that there is no unit root (Baltagi, 2005). Both tests also allow for an unbalanced panel. However, the LLC test assumes that there is a common unit root process across cross-sections, but the ADF-Fisher test assumes individual unit root processes across cross-sections. The results in table 1 show that the variables are nonstationary, except inflation (INF), and secondary school enrolment (SRSEC), which are stationary at levels. However, the nonstationary variables become stationary after the first difference, except total labour force (LFTOT), which becomes stationary after the second difference. The Hausman test was used to determine the choice between the random and fixed effects model. As a result, the fixed effects model was adopted for this study. Table 2 shows the empirical findings using the fixed effects model. Both the R-squared and the adjusted R-squared are significant, suggesting high explanatory power of the model. In table 2, it is clear that the conventional neoclassical variables, labour and capital, are positively significant for economic growth in SADC. In particular, physical capital, as proxied by gross fixed capital formation (GFCF), is by far the most significant source of economic growth in SADC. This is understandable because of the role of mining in SADC. Several SADC countries are mineral-based economies. As exports, minerals require solid and welldeveloped infrastructure such as roads and railways. This is an advantage of mining, besides the fact that it is a significant source of foreign exchange earnings and government revenue (James et. al., 1987). Nonetheless, there are several disadvantages of mining. These are well-documented by Auty (1993), who studied four mineral economies in South America: Bolivia, Chile, Jamaica, and Peru; one in Sub-Saharan Africa, Zambia; and the other in Asia, Papua New Guinea. The underlying theme of his study is the resource curse thesis, the idea that the abundant resources some countries possess may be curse because these countries may actually perform worse than the less well-endowed countries, (Auty, 1993:1).

188 Christopher Mupimpila Table 1 Panel Unit Root Test Results Variable Levin, Lin and Chu s test ADF-Fisher s Chi-square test Levels 1 st difference Levels 1 st difference GDP -0.44855-5.25553 18.9261 78.0288 (0.3269) (0.0000)* (0.9415) (0.0000)* FDI -3.30054-8.67385 39.2175 153.080 (0.3819) (0.0000)* (0.1209) (0.0000)* IMPT 1.16489-7.12833 22.6329 87.4176 (0.8780) (0.0000)* (0.5415) (0.0000)* GFCF 1.81961-3.84552 21.2265 54.5317 (0.9656) (0.0001)* (0.5068) (0.0001)* LFTOT -0.81326 0.42631 29.3820 25.9908 (0.2080) (0.3349) (0.3933) (0.5736) EXPT 0.74702-3.71865 24.0685 51.8518 (0.7725) (0.0001)* (0.4577) (0.0008)* DEBT -1.16442-5.46615) 41.5660 92.6746 (0.1221) (0.0000)* (0.0476)** (0.0000)* INF -4.09462 - - - - - - - 69.6107 - - - - - - - (0.0000)* (0.0001)* SESEC -2.41500 - - - - - - - 31.7528 - - - - - - - (0.0079)** (0.0001)*** INFRA 1.34105-0.47718 20.2055 55.8845 (0.9100) (0.3166) (0.9111) (0.0028)* Notes: *, **, and *** denotes that a variable is stationary at 1%, 5% and 10%level respectively; P-values are in parenthesis. There are several reasons mineral economies may under-perform compared to other developing countries. First, mining is by nature capital-intensive, and therefore it employs only a very small segment of the total labour force. Secondly, mining tends to be an enclave with minimal linkages to the local industries. Rather, the fiscal linkage, through taxes, is by far the dominant contribution of mining to the local economy (Auty, 1993). Thirdly, because it is capital-intensive, mining depends on foreign capital investment. Therefore, mining has low revenue retention, because a significant portion of the export earnings are repatriated abroad to the owners of the foreign capital (Ibid.). Furthermore, mining can have adverse effects on other sectors of the economy, particularly agriculture and manufacturing. This is because of what is known as the Dutch disease (Auty, 1993; James et. al., 1987). Stated by Auty (1993: 15): Dutch disease manifests itself in the premature shrinkage of the agricultural sector compared with the non-mineral economies at a similar stage of development and also the under-development, or extreme protection of the manufacturing sector. It is especially damaging in the case of mining, as opposed to most soft commodities, because during mineral booms agriculture as well as manufacturing can become uncompetitive and dependent on import substitution. In the case of Zambia, Auty found that the mineral boom distorted market signals in agriculture and manufacturing, and also retarded economic diversification (Ibid.). These observations may be true for other mineral-based economies in SADC.

Sources of Economic Growth in the Southern African Development Community (SADC) 189 In table 2, the structural variables that have a positive and significant impact on economic growth in SADC are: exports (EXPT), human capital (SESEC) and infrastructure (INFRA). These results are as expected, after all SADC has, among its members, the most industrialized country in Africa: South Africa. Through the years, South Africa has undergone structural change with the growth of manufacturing. A key factor in the liberalization of the South African economy is the Growth, Equity and Redistribution (GEAR) strategy adopted in 1996 (Chipeta and Schade, 2007). GEAR seeks to expand trade and foreign direct investment in SADC, because of the critical role of these factors in economic growth. We learn this from the experience of Asian countries. According to James et. al. (1987), all the Asian countries that have successfully industrialized since the 1960s have moved away from import substitution to export promotion strategies. Four of these countries are now classified as the newly industrializing countries (NICs), namely; Hong Kong, Singapore, South Korea, and Taiwan. Besides export promotion, the NICs depended on skilled labour for enhanced economic growth (Yang, 2008; James et. al., 1987). As Romer (1986) argues, sustained long-run economic growth is possible under conditions of increasing marginal productivity of knowledge which sufficiently overrides the decreasing marginal productivity of physical capital, thereby resulting in increasing marginal productivity of total capital. Knowledge is part of human capital, and it consists of such activities as formal education and on-the-job training (Romer, 1990). More precisely, increase in human capital raises technological progress, which, in turn, raises economic growth. Table 2 Sources of Economic Growth in SADC Explanatory variables Coefficient t-statistic Constant -0.198811-0.281238 Log of total labour force (InIftot) 8.951858 2.279213** Log of gross fixed capital formation (Ingfcf) 0.735557 12.82679* Log of real exports (Inexpt) 0.356588 5.421812* Log of real imports (Inimpt) -0.464904-1.368445 Log of lagged real gross domestic product (Ingdp (-1)) -10.47483-8.331365* Lagged foreign direct investment (fdi (-1)) 2.0111111 0.830779 Log of total debt service on external debt (Indebt) -0.220178-2.031388** Inflation rate (inf) -3.711111-3.138086* Log of secondary school enrolment as % of gross (Insesec) 1.261574 1.564554*** Log of telephone lines per 100 people (Ininfra) 0.513717 3.610375* R-squared 0.969797 Adjusted R-squared 0.955894 D-W Statistic 1.363533 F-statistic 69.75508 Prob(F-statistic) 0.000000 Cross-sections included 9 Periods included 20 Total panel (unbalanced) observations 93 Notes: *, **, *** denotes that a variable is significant at 1%, 5%, and 10% level respectively.

190 Christopher Mupimpila The results of this study confirm that human capital has a positive and significant effect on economic growth, as other studies elsewhere also show (Oketch, 2006; Krueger and Lindahl, 2001; Bills and Klenow, 2000; Benhabib and Spiegel, 1994; Mankiw et. al., 1992; Lucas, 1988). In the case of SADC, single and cross-country studies find a positive and significant relationship between human capital and economic growth (Mupimpila and Funjika, 2010; Mupimpila, 2009, 2007a, 2007b; Siphambe, 2000, Ncube, 1999). It is therefore necessary that SADC countries should sustain the investment in human capital. The question then is: what are the factors which have a negative impact of economic in SADC? There are two variables that have a significant but negative impact on economic growth in SADC: total debt service on the external debt (DEBT) and inflation (INF). The results in table 2 support the findings of Mupimpila and Funjika (2010). The authors suggest that hyperinflation in one country can lead to macroeconomic instability which is transmitted to other countries in the region. This has been the case with Zimbabwe, which in January 2007 had a record inflation rate of 1,593 % (Mupimpila and Funjika, 2010: 164). In other words, regional blocks are adversely affected by the contagion effect of macroeconomic instability in one member country (Cleary, 2001). However, external debt service negatively affects economic growth because of the export earnings that are spent on the debt. External debt siphons the export earnings of debtor countries. This is one way in African countries export more capital than they import (Rampel, 1992). Another way this happens can be deduced from the negative correlation between imports and economic growth in table 2. Since imports are considered to be a stimulus to growth, why should we expect a negative relationship between imports and economic growth in SADC? The answer has been provided by Lane and Milesi-Ferretti (2001, 2007) and Pogoda (2012). In their earlier study, Lane and Milesi-Farretti (2001) examined the foreign assets and liabilities of 67 developed and developing countries for the period 1970 to 1998. They used balance of payments data to evaluate the net external assets (NFA) of each country as a ratio of GDP. Overall, developed countries had positive net foreign assets during the period, in contrast to developing countries, which had negative aggregate NFA. The findings suggest that developed countries were net creditors while developing countries were debtors; thereby supporting the hypothesis that there is a positive relationship between NFA and the level of development. In a follow up study, Lane and Milesi-Ferretti (2007), increases both the sample size and the period of study; they now had 145 countries for the period 1970 to 2004. According to their findings, Hong Kong, Singapore, and Taiwan increased their net foreign assets to GDP ratio between 1996 and 2004. By contrast, African and Latin American countries had decreases in NFA as a ratio of GDP, implying that these countries were exporting capital (Lane and Milesi-Ferretti, 2007). Commenting on these results, Pogoda (2012: 37) says: This suggests that [African and Latin American countries] import more goods and services than they export and therefore they export more capital than they import. This is why we can expect a negative relationship between imports and economic growth in SADC. Besides, table 2 shows that the lagged value of GDP has a negative and significant impact on economic growth in SADC; implying that it isnecessary to have structural change in the region.

Sources of Economic Growth in the Southern African Development Community (SADC) 191 IV. SUMMARY AND CONCLUSIONS Empirical evidence shows that the sources of economic growth vary across countries over time. This study analyzed the sources of growth for the Southern African Development Community (SADC), which comprises: Angola, Botswana, the Democratic Republic of Congo, Lesotho, Madagascar, Malawi, Mauritius, Mozambique, Namibia, the Seychelles, South Africa, Swaziland, Zambia, and Zimbabwe. The study employed panel data for the period 1990 to 2011, and estimated economic growth as a function of labour, physical capital, and structural variables: imports, exports, foreign direct investment, debt service, inflation, human capital, and infrastructure. The empirical findings of this study show that economic growth in SADC is positively and significantly determined by labour, physical capital, exports, human capital, and infrastructure. In particular, physical capital, as represented by gross fixed capital formation, is by far the most significant source of economic growth in SADC. This is to be expected, considering that several SADC countries depend on mining for exports, foreign exchange, and government revenue. By nature, mining is capital-intensive and mineral exports require welldeveloped infrastructure. This study examined the advantages and disadvantages of mining. It also emphasized the critical role of exports and human capital in economic growth. However, inflation and total debt service on the external debt have a negative but significant impact on economic growth in SADC. The results of the present study suggest that economic growth in SADC requires a stable macroeconomic environment in which countries are net creditors. For higher and sustained economic growth, it is necessary to have structural change in SADC. Consider, for example, the experience of the newly industrializing countries: Hong Kong, Singapore, South Korea, and Taiwan. Invariably, these countries have relied on the exports of manufactured goods and skilled labour for enhanced and sustained economic growth. References Auty, R. M. (1993), Sustaining Development in Mineral Economies, The Resource Curse Thesis, London: Routledge. Baltagi, B. H. (2005), Econometric Analysis of Panel Data, Chichester, West Sussex: John Wiley & Sons. Benhabib, J. and M. Spiegel (1994), The Role of Human Capital in Economic Development: Evidence from Aggregate Cross-Country Data, Journal of Monetary Economics, 34: 143-174. Chenery, H., H. Elkington, and C. Simons (1970), A Uniform Analysis of Development Patterns, Economic Development Report 148, Harvard University Center for International Affairs, Cambridge, Massachusetts. Chenery, H., S. Robinson, and M. Syrquin (1986), Industrialization and Growth: A Comparative Study, London: Oxford University Press. Cleary, S. (2001), Variable Geometry and Varying Speed: An Operational Paradigm for SADC, In C. Clapham, G. Mills, A. Morner, and E. Sidiropoulos eds.regional Integration in Southern Africa: Comparative International Perspectives, Pretoria: South Africa Institute of International Affairs (SAIIA):87-104. Chipeta, C. and K. Schade eds. (2007), Deepening Integration in SADC, Macroeconomic Policies and Social Impact: A Comparative Analysis of 10 Country Studies and Surveys of Non-State Actors, Gaborone; Friedrich Ebert Foundation.

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Sources of Economic Growth in the Southern African Development Community (SADC) 193 Romer, P. M. (1986), Increasing Returns and Long-run Growth, The Journal of Political Economy, 94(5): 1002-1037. Romer, P. M. (1990), Endogenous Technological Change, Journal of Political Economy, 98(5): S71-S102. Yang, J (2008), Analysis of So-Called Export-led Growth, IMF Working Paper, WP/08/220, Washington, D.C.: International Monetary Fund. Krueger, A. B. and M. Lindahl (2001), Education for Growth: Why and for Whom? Journal of Economic Literature:1101-1136. Bills, M. and P. Klenow (2000), Does Education Cause Growth? American Economic Review 90: 1160-1183.