Exports and Economic Growth in Sub-Saharan Africa: Is There a Connection?

Exports and Economic Growth in Sub-Saharan Africa: Is There a Connection? Ousmanou Njikam Faculty of Economics & Management. University of Yaounde II P.O.Box 1063 Yaounde, Cameroon. Tel: (237) 231 11 90 (R)742 38 78 (Cell). Fax: (237) 222 18 73. E-mail: onjikam2002@yahoo.fronjikam@uycdc.uninet.cm Abstract: Are exports and economic growth correlated in Sub-Saharan Africa? If yes, what is the direction of this causation? Is this direction reversed with the change of these countries from import-substitution (IS) to export promotion (EP) strategies? Based on a sample of 21 SSA countries these questions are addressed using Hsiao's Granger-causality. The results are the following. During the IS period, economic growth unidirectionally causes total exports in five countries, manufactured exports unidirectionally cause economic growth in one country, bidirectional causality exists between economic growth and total exports in three countries, bidirectional causality exists between economic growth and agricultural exports in one country and bidirectional causality exists between economic growth and manufactured exports in three countries. During the EP period, agricultural exports unidirectionally cause economic growth in nine countries, manufactured exports unidirectionally cause economic growth in three countries, economic growth unidirectionally causes agricultural exports in five countries, economic growth unidirectionally causes manufactured exports in six countries and a bidirectional causality exists between economic growth and agricultural exports in three countries. JEL Classification: F13; O47; C52; O55 Keywords: Exports, economic growth, causality, Sub-Saharan Africa. November 2003

1 1. Introduction For most of the Sub-Saharan Africa (SSA) countries the 1980s were a decade of slow or negative growth in per capita Gross Domestic Product (GDP), worsening balance of payments, debt and financial crises and declining competitiveness (Devarajan and de Melo, 1991). Among the factors advanced to explain this economic downturn, reference was made to inappropriate domestic policies (increasing opaque and distortionary restrictions to foreign trade) and increased marginalization of SSA. For this and other reasons, outward-orientation became the new orthodoxy for these countries. As a pre-condition for the success of this strategy almost all SSA countries initiated economic reforms. The export-led growth (ELG) hypothesis implies not only that exports and economic growth are highly correlated, but that the former unidirectionally causes the latter. Past studies conducted in finding this evidence used correlation, OLS regressions or production function methodology. 1 However, the results obtained were very sensitive to the choice of sample and estimating techniques. Moreover, the assumption of similar production functions across countries was grossly inappropriate. It is difficult or even impossible to determine the direction of causality from regression and correlation analysis. Also, the structure of exports that tends to reflect the patterns of domestic production was not taken into account by these studies. There is increasing doubt that growth is as simple as it appears in the ELG arguments. Renewed emphasis is now placed on the role of internal factors or basic characteristics of an economy, especially entrepreneurship, infrastructure, human capital and institutions. 2 Therefore, causation may potentially flow from economic growth to exports. This is consistent with the internally generated growth (IGG) hypothesis. In this connection, a test of the ELG hypothesis should focus not on mere correlation, but rather on the direction of causation between exports and economic growth. The objective of this paper is threefold. First, examine whether indeed there is a causal relationship between exports (agricultural and manufactured) and economic growth. Second, determine the direction of this causation. Finally, examine whether this direction is reversed 1 See Tyler (1971), Michalopoulos and Jay (1973), Michealy (1977), Balassa (1978), Kavoussi (1984) and Moschos (1989) among others. 2 See among others Ukpolo (1994), Sharma and Dharmendra (1994) and Keller (1996).

2 with the change of SSA countries from the import-substitution (IS) to export promotion (EP) strategies. The study is based on 21 SSA countries (see the Appendix Table D for the list of these countries). These countries are chosen because of the availability of data. The structure of the paper is as follows. In section 2 the model used to test and find the direction of causation is developed. The results are presented in section 3 and in section 4 the conclusion and policy implications of the findings are presented. 2. Model In order to clarify whether agricultural (x 1 ) and manufactured (x 2 ) exports cause economic growth (y) or vice versa, autoregressive models are developed. Hsiao's (1979) version known as the stepwise Granger-causality technique is used to assess the direction of causation. 3 In order to avoid instantaneous causation all the variables are stationarized using the restricted and unrestricted vector autoregressive models (1) and (2). t 2 ( 1 L) logz = α + α (1 L) log + ν (1) 2 t 0 1 Z t 1 2 2 ( 1 L) log Z = α + α t + α (1 L) log Z + α (1 L) log Z + ω (2) 0 1 2 2 t 1 3 t 1 where Z is either real GDP, real total exports (agricultural and manufactured); L is a lag operator such that LY t = Y t 1, ν t and ωt are error terms with zero mean and constant covariance matrix (iid). The biggest practical challenge in autoregressive modelling is the choice of the optimum lag length of the autoregressive process. In this regard, the minimum final prediction errors (FPE) and Schwarz-Bayesian (SBT) criteria are used to determine the optimum lag length of past information. FPE and SBT criteria are specified as follows, FPE = [(T + K)(T - K)] * [SSRT] (3) (KT) SBT = (SSRT)* T (4) where T is the number of observations, K the number of parameters to be estimated, and SSR the sum of squares residuals. The direction of causation is located as follows. If p is the optimum lag length of the controlled variable y (real GDP) with the autoregressive process specified as follows, t t 3 See Ghartey (1993) and Gordon (1995) from which our model is derived.

y 3 p = α i yt -i ut (5) t + i = 1 Calculate FPE y (p,0) where superscript y denotes the dependent variable. Then using the autoregressive process of y add unit lags of the manipulated variable x (real agricultural and manufactured exports) cumulatively in sequence to equation (3). After each additional lag of x the FPE is calculated. Assuming that n is the optimal lag length of real exports x (specific value of n that minimises FPE) with autoregressive process specified as follows, y p n = t t -i j + i = 1 j =1 α i y + β xt - j vt (6) Calculate FPE y (p, n) and compare it with FPE y y y (p, 0). If FPE ( p, n) FPE ( p,0) where n p then exports cause economic growth. This is denoted by x y. The roles of exports and economic growth are then interchanged and the exercise is repeated. If in the final analysis, y x and x y, then a bidirectional causation denoted by y x exists between economic growth and exports. However, if exports (x) cause economic growth (y) but economic growth does not cause exports, then a unidirectional causation exists between the exports and economic growth. The roles of the variables are reversed and the exercise is repeated to test for all possible causal relationships. Similar exercises are repeated with the SBT criteria to identify and select the autoregressive models. Finally, in order to validate the causal direction, the Wald test (WT) and the likelihood ratio test (LRT) are used to test the significant levels of the restricted coefficients. These tests are specified as follows: WT = [(T - K)q]* [(S SR - SSR )] ( SSR LRT = - 2 ( SSRR SSRUR ) ) R UR UR (7) ln (8) where T is the number of observations, K the number of estimated parameters of the unrestricted equation including the intercept, q the number of the restricted parameters, and SSR R and SSR UR the restricted and unrestricted sum of squares residual. 3. Empirical Results As indicated in the introduction, the objective of this paper is threefold. First, establish the causal relationship between total exports (agricultural and manufactured) and economic growth. Second, if such a relationship exists, find the direction of the causation. Finally,

4 examine whether the direction of this causation is reversed when countries under study changed from IS to EP strategies. The analysis is based on 21 SSA countries. Annual timeseries data on real agricultural (x 1 ) and manufactured (x 2 ) exports and real GDP (y) from these countries over IS and EP sub-periods are employed. The data are from World Bank World Tables and World Development Indicators. Because of the use of time-series data and autoregressive models, and in order to avoid instantaneous causation, data on total exports and real GDP were tested for stationarity using (un)restricted autoregressive models. The results of the WT and ADF test are reported in Appendix Table A. During the IS period, and in Benin, Burkina-Faso, Sudan, DRC, Cameroon, Gabon, Côte-d Ivoire, Senegal, Ghana and Nigeria, the stationary real GDP is expressed in logarithmic level form. In Niger, Kenya, Madagascar, Malawi and Republic of Congo, the first-difference of real GDP after the logarithmic transformation yielded a stationary series while in Central African Republic (CAR), Togo, Mali, Tanzania and Sierra- Leone, the second-difference of real GDP after the logarithmic transformation yielded a stationary series. In Togo, Cameroon, Gabon, Côte-d Ivoire, Senegal, Ghana and Nigeria, the logarithmic level form of real agricultural exports is stationary. The first-difference of real agricultural exports after the logarithmic transformation is stationary in CAR, Burkina-Faso, Niger, Mali, Kenya, Sudan, Tanzania, Madagascar, DRC, Malawi, Sierra-Leone and Zambia while the second-difference of real agricultural exports after the logarithmic transformation is stationary in Benin and Republic of Congo. Concerning the manufactured exports, the second-difference after the logarithmic transformation is stationary in Benin, Togo, Kenya, Sierra-Leone, and Republic of Congo while the first-difference after the logarithmic transformation is stationary in CAR, Burkina-Faso, Niger, Sudan, Tanzania, Malawi, Zambia, Cameroon, Gabon, Côte-d Ivoire, Senegal, Ghana and Nigeria. Finally, the logarithmic level form of real manufactured exports is stationary in Mali, Madagascar and DRC. During the EP period, the logarithmic level form of real GDP and real total exports are stationary in all countries, except in Ghana where the first-difference of total exports after the logarithmic transformation yielded stationary series and in Benin and Nigeria where the first-difference of manufactured exports after the logarithmic transformation is stationary. After stationarizing the variables, the number of the optimal lag length of each variable is determined using the FPE and SBT procedures. The results are reported in Appendix Table B. During the IS period, the optimum lag length of real GDP is 2 in CAR,

5 Niger and Senegal, 4 in Malawi, 3 in Côte-d Ivoire, 6 in Cameroon and one in the rest of countries under study. The optimum lag length of real agricultural exports is 3 in CAR, Togo, Sierra-Leone and Nigeria, 2 in Benin, Mali and Madagascar, 4 in Côte-d Ivoire and one in the rest of countries under study. For the manufactured exports, the optimum lag length is 2 in Togo, Mali, Kenya, Sudan, Malawi, Sierra-Leone, Côte-d Ivoire and Senegal while unit lag length is the optimum in the rest of countries under study. According to the SBT criteria, the optimum lag length of manufactured exports is 3 and 4 in Côte-d Ivoire and Senegal respectively. During the EP period, the optimum lag length of real GDP is 2 in Madagascar, Republic of Congo and Ghana while unit lag length is the optimum for real GDP in the rest of countries under study. For the agricultural exports, 5 and 4 are the optimum lag length according to FPE and SBT criteria in Niger, 3 is the optimum lag length in CAR, Togo, Sierra-Leone and Nigeria, 2 is the optimum lag length in Benin, Mali and Madagascar while unit lag length is the optimum for real agricultural exports in the rest of countries under study. For the manufactured exports, 2 is the optimal lag length in Togo, Mali, Kenya, Sudan, Malawi, Sierra-Leone, Côte-d Ivoire and Senegal while the unit lag length is the optimum in the rest of countries under study. But, according to the SBT criteria, 3 and 4 are the optimum lag lengths of real manufactured exports in Côte-d Ivoire and Senegal respectively. Using the procedure outlined in section 2, the results of the Granger-causality test in all countries under study and for all variables are reported in Appendix Table C. The optimum lag length of each variable is placed within parentheses. The analysis consists in determining the direction of causation (column 5) by comparing the results of FPE and SBT criteria of univariate autoregressive models (columns 3 and 8) with the results of FPE and SBT criteria of bivariate autoregressive models (columns 4 and 9). This causality is validated or not by the WT and LRT (columns 6, 7, 11 and 12). The results are further examined by discussing the autoregressive estimates, which are not reported in the text. 4 During the IS period, the results are the following. In Cameroon, Côte-d Ivoire, Senegal, Ghana, Benin, Burkina-Faso, Mali, Sudan and Madagascar, the FPE and SBT results of the univariate model of real agricultural exports are greater than the FPE and SBT results of the bivariate model of real agricultural exports. This means that in these countries, economic growth causes agricultural exports. Except in Benin and Burkina-Faso, the WT and 4 For interested readers these results are available. They are not reported herein to keep focus the objective of this research.

6 LRT validate this direction of causation at the 1% and 5% levels respectively. Additionally, the autoregressive coefficients of real agricultural exports bivariate models show that the real GDP is positively and significantly correlated with agricultural exports in these economies. In the rest of the SSA countries under study however, the FPE and SBT results of the bivariate model of real agricultural exports are greater than the FPE and SBT results of the univariate models of real agricultural exports. Therefore, economic growth does not cause agricultural exports and the WT and LRT validate this lack of causation in most cases. Concerning the manufactured exports and still over the IS period, the results are the following. There is a strong and positive correlation between manufactured exports and economic growth in Cameroon, Côte-d Ivoire, CAR, Benin, Burkina-Faso, Niger, Mali, Kenya, Madagascar, DRC and Sierra-Leone. The FPE and SBT results of the univariate model of real manufactured exports are greater than the FPE and SBT results of the bivariate model in all these countries. Therefore, the direction of the previous strong positive correlation is from economic growth to manufactured exports. From the Wt and LRT results, it is clear that real GDP causes manufactured exports at the 1% and 5% levels respectively. Moreover, the autoregressive estimates of manufactured exports reveal that real GDP coefficient is positive and significant in most of these countries. In the remaining countries under study, the FPE and SBT results of the one-dimensional autoregressive process of real manufactured exports are smaller than the two-dimensional autoregressive process of real manufactured exports. Therefore, real GDP does not cause manufactured exports in these countries. The results in Appendix Table C show that the WT and LRT validate this lack of causation in almost all of these countries. By interchanging the role of variables and still during the IS period, the results are as follows. In Cameroon, Côte-d Ivoire, Ghana, Benin and Niger the FPE and SBT results of the bivariate model of real GDP are smaller than the FPE and SBT univariate model results of real GDP. Therefore, agricultural exports cause economic growth in these five countries. The WT and LRT confirm at the 1% and 5% levels respectively this causation. The coefficients of autoregressive models show that agricultural exports are positively associated with real GDP but are not significant in all five countries. For the manufactured exports and in Cameroon, Côte-d Ivoire, Nigeria, CAR, Benin, Sudan, Madagascar, DRC and Sierra-Leone, the FPE and SBT results of the two-dimensional real GDP model are smaller than the FPE and SBT results of the one-dimensional autoregressive process of real GDP. Therefore, manufactured

7 exports cause economic growth in these nine countries. The WT and LRT results validate this causation in all these countries. The autoregressive estimates also indicate that manufactured exports are positively and significantly correlated with economic growth, except in CAR and Sudan. The final analysis of the IS period results is recapitulated in Table 1. More specifically, Table 1 gives the list of countries where we found significant causation between economic growth and total exports. Table 1: Summary of the IS period results analysis Country Variables Direction of causation Real GDP (y) Manufactures exports (x 1 ) Agricultural exports (x 2 ) Benin Y X 1 X 2 y x, y x, x y x y 1 2 1, 2 Burkina-Faso Y X 1 X 2 y x, y x 1 2 Cameroon Y X 1 X 2 y x, y x, x y x y 1 2 1, 2 CAR Y X 1 X 2 x2 y, y x2 Côte-d Ivoire Y X 1 X 2 y x, y x, x y x y 1 2 1, 2 DRC Y X 1 X 2 x2 y, y x2 Ghana Y X 1 X 2 x1 y, y x1 Kenya Y X 1 X 2 y x2 Madagascar Y X 1 X 2 y x, y x x y 1 2, 2 Mali Y X 1 X 2 y x, x 1 2 Nigeria Y X 1 X 2 x 2 y Niger Y X 1 X 2 x1 y, y x2 Senegal Y X 1 X 2 y x1 Sierra-Leone Y X 1 X 2 y x x y 2, 2 Sudan Y X 1 X 2 y x x y 1, 2 In the final analysis, the results of the IS period in Table 1 clearly show a bidirectional causation between economic growth and total exports (agricultural and manufactured) in Cameroon, Côte-d Ivoire and Benin. This implies that in these three countries real GDP growth and total exports are mutually interdependent in the IS development process i.e.

8 expansion in exports promotes the growth of Cameroonian, Ivorian and Benin national incomes and the structural transformation of these economies reinforce expansion in total exports. The results in Table 1 also show a unidirectional causation from real GDP to agricultural exports in Senegal, Burkina-Faso, Mali, Sudan and Madagascar and from real GDP to manufactured exports in Burkina-Faso, Mali, CAR, Niger and Kenya. These results imply that the development of national economies was a prerequisite to the development of agricultural exports in Senegal, Burkina-Faso, Mali, Sudan and Madagascar while the development of national economies was a prerequisite to the development of manufactured exports in Burkina-Faso, Mali, CAR, Niger and Kenya. It then appears that in the early stages of the development process, internal factors played an important role in fostering agricultural and manufactured exports in these SSA countries. From the results in Table 1, there is bidirectional causation between economic growth and agricultural exports in Ghana and between economic growth and manufactured exports in Madagascar, DRC and Sierra-Leone. The ELG and the IGG hypotheses are therefore appropriate in these countries. In this regard, the economic growth and the agricultural exports are mutually beneficial and reinforce each other in Ghana while the manufactured exports and the real GDP are mutually beneficial and reinforce each other in Madagascar, DRC and Sierra-Leone. In Sudan, there is a unidirectional causation from manufactured exports to economic growth. Thus, the ELG hypothesis is appropriate in the Sudanese context. Finally, the finding that total exports have no effect on economic growth and vice versa in 14 of 21 SSA countries under study during the IS period implies that such a strategy distorted these economies because of the underlying protective measures. Since the exports sector also benefited from such protection, the exports growth further increased the extent of distortions, thus retarding or at best not contributing to economic growth. On the other hand, the development of national economies of these SSA countries during the IS strategy did not reach the level capable to significantly affect the development of exports. This result also implies that the inward-looking strategy penalised the development of exports in these countries. Over the EP period, the results are the following. In Cameroon, Côte-d Ivoire, Ghana, Burkina-Faso, DRC, Madagascar, Malawi, Zambia and Gabon and concerning the agricultural exports, the FPE and SBT results of bivariate models of real GDP are smaller than the FPE and SBT results of univariate models of real GDP. So, agricultural exports cause economic growth in these nine countries. The WT and LRT further validate this result at the 1% and 5%

9 levels respectively in all the nine economies except in Côte-d Ivoire where the WT and LRT are insignificant. The agricultural exports coefficients in the real GDP autoregressive models are positively and significantly associated with real GDP in all the nine countries. Concerning the manufactured exports, the FPE and SBT results of bivariate models of real GDP are smaller than the FPE and SBT results of univariate models of real GDP in Cameroon, Mali and Malawi. This implies that in these three countries, manufactured exports cause economic growth during the EP period. The WT and LRT validate at a 5% level this causation. The autoregressive coefficient of manufactured exports in these three countries show that the manufactured exports are positively and significantly associated with real GDP. By interchanging the role of variables and for Senegal, Nigeria, Burkina-Faso, DRC, Mali, Kenya, Tanzania and Madagascar, the FPE and SBT results of the bivariate models of agricultural exports are smaller than the FPE and SBT results of univariate models of agricultural exports. Therefore, in 8 of 21 SSA countries under study, economic growth causes agricultural exports performance over the EP era. The WT and LRT validate this unidirectional causation at the 1% and 5% levels respectively. The autoregressive estimates further show that real GDP is positive and significant at a 5% level in the explanation of the agricultural exports performance. By considering the real GDP as exogenous in the manufactured exports autoregressive model, the FPE and SBT results for Côte-d Ivoire, Ghana, Nigeria, Benin, Togo, Madagascar and Gabon are smaller than the FPE and SBT results of manufactured exports univariate models. The results of the WT and LRT and the autoregressive coefficients validate at the 1% and 5% respectively these results. A summary of all significant causation during the EP period is reported in Table 2. Table 2: Summary of the EP period results analysis Country Variables Direction of causation Real GDP (y) Manufactures exports (x 1 ) Agricultural exports (x 2 ) Benin Y X 1 X 2 y x2 Burkina-Faso Y X 1 X 2 y x x y 1, 1 Cameroon Y X 1 X 2 x y x y 1, 2 Côte-d Ivoire Y X 1 X 2 x1 y, y x2 DRC Y X 1 X 2 x1 y, y x1

Gabon Y X 1 X 2 x 1 y Ghana Y X 1 X 2 x1 y, y x2 Kenya Y X 1 X 2 y x1 Madagascar Y X 1 X 2 x y, y x1, y x2 Malawi Y X 1 X 2 x2 y, y x1 Mali Y X 1 X 2 x2 y, y x1 Nigeria Y X 1 X 2 y x, x 1 2 Senegal Y X 1 X 2 y x1 Tanzania Y X 1 X 2 y x1 Togo Y X 1 X 2 y x2 Zambia Y X 1 X 2 x 1 y 10 In sum, and concerning the EP period, there is a unidirectional causation from agricultural exports to economic growth in 9 of 21 countries under study. Therefore, the performance of agricultural exports substantially contributed to these countries economic growth during the outward orientation period. From this result we can deduce that countries like Cameroon, Côte-d Ivoire, Ghana, Burkina-Faso, DRC, Madagascar, Malawi, Zambia and Gabon can use exports of agricultural products as engine of their economic growth. Given the considerable comparative advantage of these countries in the production of primary products the increase capacity of producing the agricultural primary products would significantly stimulate growth. However, some authors (Fosu, 1990 for instance) argue that this strategy would obviously lead to the deterioration of poor countries' terms of trade (tot). The manufactured exports unidirectionally cause economic growth only in 3 in 21 countries under study, either 14.3% of the sample. Thus Cameroon, Malawi and Mali can promote the growth of their respective economies by relying on the development of manufactured exports. However, in the majority of SSA countries where there is no causality from manufactured exports to economic growth, alternative strategies rather than the promotion of manufactured exports may be applied in order to structurally transform these economies. Therefore, the existence of a critical level of development is crucial in achieving economic growth through the adoption of EP policies of manufactured products. It would consequently be very difficult for most SSA countries to promote the exports of manufactured

11 goods at a level that can significantly affect their economic growth. In Burkina-Faso, DRC and Madagascar, there is bidirectional causation between agricultural exports and economic growth. This result suggests that these countries followed the path of ELG and at the same time domestic market conditions had a significant impact on the growth process of these countries, with agricultural exports playing a reactive role. The unidirectional causation from real GDP to agricultural exports in Mali, Senegal, Nigeria, Kenya and Tanzania and from real GDP to manufactured exports in Côte-d Ivoire, Ghana, Madagascar, Gabon, Benin and Togo implies that in these countries economic growth was sufficient during the EP period to generate growth of agricultural exports in the first group of countries and of manufactured exports in the second group. 4. Conclusion This study firstly tested the causal relationship that may exist between exports (agricultural and manufactured) and economic growth. Secondly, in the case such relationship exists, the study determined the direction of this causation. Finally, the study examined whether this direction is reversed when the countries studied change from import-substitution (IS) to export promotion (EP) strategies. The analysis is based on 21 SSA countries. The countries are chosen because of the availability of data. The results of the Wald test (WT) and MacKinnon's Augmented Dickey-Fuller (ADF) indicated that during the IS period, During the IS period, and in 10 countries, the stationary real GDP is expressed in logarithmic level form. In 5 countries the first-difference of real GDP after the logarithmic transformation yielded a stationary series while in 5 other countries, the second-difference of real GDP after the logarithmic transformation yielded a stationary series. In 7 countries, the logarithmic level form of real agricultural exports is stationary. The first-difference of real agricultural exports after the logarithmic transformation is stationary in 12 countries while the second-difference of real agricultural exports after the logarithmic transformation is stationary in 2 countries. Concerning the manufactured exports, the second-difference after the logarithmic transformation is stationary in 5 countries while the first-difference after the logarithmic transformation is stationary in 13 countries. Finally, the logarithmic level form of real manufactured exports is stationary in 3 countries. During the EP period, the logarithmic level form of real GDP and real total exports are stationary in

12 all countries, except in one country where the first-difference of total exports after the logarithmic transformation yielded stationary series and in 2 countries where the firstdifference of manufactured exports after the logarithmic transformation is stationary. After stationarizing the variables, the number of the optimal lag length of each variable is determined using the FPE and SBT procedures. During the IS period, the optimum lag length of real GDP is 2 in 3 countries, 4 in one country, 3 in one country, 6 in one country and one in the rest of countries under study. The optimum lag length of real agricultural exports is 3 in 4 countries, 2 in 3 countries, 4 in one country and one in the rest of countries under study. For the manufactured exports, the optimum lag length is 2 in 8 countries while unit lag length is the optimum in the rest of countries under study. According to the SBT criteria, the optimum lag length of manufactured exports is 3 and 4 in one and 2 countries respectively. During the EP period, the optimum lag length of real GDP is 2 in 3 countries while unit lag length is the optimum for real GDP in the rest of countries under study. For the agricultural exports, 5 and 4 are the optimum lag length according to FPE and SBT criteria in one country, 3 is the optimum lag length in 4 countries, 2 is the optimum lag length in 3 countries while unit lag length is the optimum for real agricultural exports in the rest of countries under study. For the manufactured exports, 2 is the optimal lag length in 8 countries while the unit lag length is the optimum in the rest of countries under study. But, according to the SBT criteria, 3 and 4 are the optimum lag lengths of real manufactured exports in 2 countries. Hsiao's (1979) version of Granger-causality, which goes beyond mere correlation, is used to address the issue of the direction of causation. The WT and Likelihood ratio test (LRT) were used as criteria to jointly test the restrictions imposed on the variables and validate the direction of causation. Concerning the IS period, the results show bidirectional causation between real GDP and total exports (agricultural and manufactured) in Cameroon, Côte-d Ivoire and Benin. In these countries therefore, the economic growth and total exports were complementary i.e. reinforced each other. The unidirectional causation from real GDP to agricultural exports in Senegal, Burkina-Faso, Mali, Sudan and Madagascar and from real GDP to manufactured exports in Burkina-Faso, Mali, CAR, Niger and Kenya implies that the development of national economies was a prerequisite for these countries to expand their agricultural and manufactured exports respectively. The bidirectional causation between economic growth and agricultural exports in Ghana and between economic growth and manufactured exports in

13 Madagascar, DRC and Sierra-Leone implies that during the IS period strategy these countries concentrated in applying policies that foster economic growth through the exports of agricultural and manufactured products and also applied policies that increase the level of development in an effort to generate growth through primary agricultural and manufactured products. In Sudan, the results show a unidirectional causation from manufactured exports to economic growth. Thus, ELG hypothesis is appropriate and manufactured exports could be considered as engine of Sudanese economic growth. The fact that total exports have no effect on economic growth and vice versa in 14 of 21 SSA countries under study during the IS period implies that the inward oriented strategy further distorted these economies, thus penalising exports growth. Also, the development of these economies during the IS period did not reach the level capable to significantly affect the development of total exports. Therefore, if these countries would like to perform well in exporting primary agricultural and manufactured exports the domestic production structures should be developed or modified. During the EP period, the agricultural exports unidirectionally cause economic growth in 9 of 21 countries under study (Cameroon, Côte-d Ivoire, Ghana, Burkina-Faso, DRC, Madagascar, Malawi, Zambia and Gabon). This result implies that during the outward orientation strategy the primary agricultural exports were the engine of growth of these countries. Given the considerable comparative advantage of these countries in the production of primary products the increase capacity of producing the agricultural primary products would significantly stimulate growth. However, it seems that such a strategy would lead to the deterioration of terms of trade. The manufactured exports unidirectionally caused real GDP growth only in 3 countries, namely Cameroon, Mali and Malawi. Thus, these countries can promote the growth of their respective economies by developing the exports of manufactured products. However, this result brings into question the effectiveness of the EP policies in the majority of SSA countries where the emphasis is also placed on the promotion of manufactured goods. A such emphasis is problematic in the extent that it may probably not lead to the structural transformation of these economies and then may not have significant impact on their economic development. Still during the EP period, the results show bidirectional causation between economic growth and agricultural exports in Burkina-Faso, DRC and Madagascar. Therefore, the ILG and ELG hypotheses are credible in these countries. Finally, the unidirectional causation from real GDP to agricultural exports in Mali, Senegal, Nigeria, Kenya and Tanzania, and from real GDP to manufactured exports in Côte-

14 d Ivoire, Ghana, Madagascar, Gabon, Benin and Togo implies that the expansion of total exports is dependent on the structural transformation of these economies. The problem however with this study is that the analysis is limited to few variables such as GDP and total exports (agricultural and manufactured). A more appropriate approach would be to incorporate variables such as real exchange rate, human capital, infrastructures, institutional environment, etc. in the analysis. These variables may have played very important and different roles in the process of economic growth of SSA countries during the inward and outward orientations strategy. References Balassa, B. (1978). Exports and Economic Growth: Further Evidence. Journal of Development Economics 5, 181-89. Darrat, A. (1987). Are Exports an Engine of Growth? Another Look at the Evidence. Applied Economics, 19, 277-83. Devarajan, S. and J. de Melo (1987). Evaluating Participation in African Monetary Unions: A Statistical Analysis of the CFA Zones. World Development, vol. 15, No. 4, 483-96.... (1991). Membership in the CFA Zone: Odyssean Journey or Trojan Horse? in Chibber, Ajay and Stanley Fisher (eds.), Economic Reform in Sub- Saharan African, World Bank. Elbadawi, I and N. Majd (1996). Adjustment and Economic Performance Under a Fixed Exchange Rate: A Comparative Analysis of the CFA Zone. World Development, vol. 24, No. 5, 939-51. Fosu, A. K. (1990). Export Composition and the Impact of Export on Economic Growth of Developing Economies. Economics Letters 34, 67-71. Ghartey, E.E. (1993). Causal Relationship Between Exports and Economic Growth: Some Empirical Evidence in Taiwan, Japan and the US. Applied Economics, 25, 1145-52. Gorden, D.V. (1995). Optimal Lag Length in Estimating Dickey-Fuller Statistics: An Empirical Note. Applied Economics Letter, 2, 188-90.

15 Granger, C.W.J. (1969). Investigating Causal Relations by Econometrics Models and Cross-Spectral Methods. Econometrica, 37, 424-38. Guillaumont, P., S. Guillaumont and P. Plane (1988). Participating in African Monetary Unions: An Alternative Evaluation. World Development, vol.6, No. 5, 569-76. Hsiao, C. (1979). Autoregressive Modelling of Canadian Money and Income Data. Journal of American Statistical Association, 74, 553-60. Jung, W.S. and P.J. Marshall (1985). Exports, Growth and Causality in Developing Countries. Journal of Development Economics 18, 1-12. Kavoussi, R.M. (1984). Exports Expansion and Economic Growth: Further Empirical Evidence. Journal of Development Economics 14, 241-50. Michalopoulos, C. and K. Jay (1973). Growth of Exports and Income in the Developing World: A neoclassical View, A.I.D. Discussion Paper No. 28, Washington, DC. Michael, M. (1977). Exports and Growth: An Empirical Investigation. Journal of Development Economics, 4, No. 1, 49-53. Moschos, D. (1989). Export Expansion, Growth and the Level of Economic Development. Journal of Development Economics, 16, 99-102. Pindyck, R.S. and D.L. Rubinfeld (1991). Econometric Models and Economic Forecasts. McGraw-Hill, Inc. Third Edition. Salvatore, D. and T. Hatcher (1991). Inward Oriented and Outward Oriented Trade Strategies. The Journal of Development Studies, vol. 27, No. 3, 7-25. Sharma, S.C. and D. Dharmendra (1994). Causal Analyses Between Exports and Economic Growth in Developing Countries. Applied Economics, vol. 26, 1145-57. Tyler, W.G. (1981). Growth and Export Expansion in Developing Countries: Some Empirical Evidence. Journal of Development Economics, 9, No.1, 121-30. Ukpolo, V. (1994). Export Composition and Growth of Selected Low-Income African Countries: Evidence from Time-Series data. Applied Economics, vol.26, 445-49.

16 Appendix Table A. Results of unit roots test. Wald Test * ADF Test * IS period EP period IS period EP period Benin Real GDP 44.9332 7.774-13.48-70.663 Agricultural exports 3.6719 6.331-3.87-2.925 Manufactured exports 2.1031 2.456-3.687-14.813 Burkina-Faso Real GDP 94.6124 2.201-3.809-18.796 Agricultural exports 3.8491 1.98-3.664-3.278 Manufactured exports 18.3243 3.453-3.674-2.478 Cameroon Real GDP 94.83 54.13-2.71-3.07 Agricultural exports 73.32 31.33-11.49-9.55 Manufactured exports 57.67 67.58-9.15-12.01 Central African Republic Real GDP 11.216 5.5104-5.206-3.3132 Agricultural exports 7.0026 11.228-5.11-2.895 Manufactured exports 18.737 15.998-3.258-4.1122 Côte-d'Ivoire Real GDP 13.21 12.31-5.65-7.14 Agricultural exports 51.61 65.11-15.45-2.505 Manufactured exports 86.31 96.03-28.46-10.581 Democratic Republic of Congo (DRC) Real GDP 2.3819 45.451-3.754-9.049 Agricultural exports 4.3914 22.33-4.039-3.439 Manufactured exports 5.4198 15.156-3.62-4.53 Gabon Real GDP 27.48 31.48-6.00-8.486 Agricultural exports 34.82 24.62-19.31-2.652 Manufactured exports 16.44 17.14-3.90-5.837 Ghana Real GDP 240.75 242.87-2.31-3.569 Agricultural exports 258.46 256.61-15.92-34.563 Manufactured exports 19.43 21.43-2.98-11.686 Kenya Real GDP 2.48 4.882-3.496-30.659 Agricultural exports 1.3579 5.125-3.777-4.412 Manufactured exports 1.2755 6.6625-3.971-4.517 Madagascar Real GDP 14.704 2.2055-3.822-26.535 Agricultural exports 12.532 3.456-2.119-4.866 Manufactured exports 11.9685 5.432-3.608-4.031 Malawi Real GDP 3.8647 12.123-3.756-24.954 Agricultural exports 5.993 13.325-4.799-6.251 Manufactured exports 2.6474 14.596-3.7-2.024 Mali Real GDP 1.6699 9.4521-3.824-7.226 Agricultural exports 2.0854 8.5523-3.584-3.211 Manufactured exports 19.156 7.7514-3.406-2.661 Nigeria Real GDP 384.03 35.405-3.30-40.259 Agricultural exports 24.32 22.36-8.86-9.15 Manufactured exports 168.33 58.234-4.21-77.605

17 Niger Real GDP 3.0243 4.445-3.837-6.694 Agricultural exports 2.1059 5.442-3.433-3.905 Manufactured exports 1.974 2.368-3.54-4.242 Republic of Congo Real GDP 11.45 6.061-4.105-11.606 Agricultural exports 8.32 4.036-3.392-3.604 Manufactured exports 5.44 7.093-3.607-3.709 Senegal Real GDP 33.61 8.9602-2.55-208.096 Agricultural exports 57.18 3.445-2.34-3.441 Manufactured exports 791.55 8.222-4.69-3.382 Sierra-Leone Real GDP 1.672 1.5544-3.684-3.697 Agricultural exports 17.4191 2.367-3.792-4.523 Manufactured exports 5.7866 3.698-5.095-5.554 Sudan Real GDP 16.07 7.663-3.982-4.45 Agricultural exports 4.8068 6.84-3.266-4.06 Manufactured exports 2.384 8.345-4.384-5.162 Tanzania Real GDP 1.5 3.045-4.18-90.114 Agricultural exports 2.023 6.658-3.593-4.63 Manufactured exports 1.303 2.1515-3.651-2.141 Togo Real GDP 7.185 1.998-4.26-16.655 Agricultural exports 0.232 3.657-3.932-2.795 Manufactured exports 6.7103 4.568-4.437-8.983 Zambia Real GDP 1.382 6.288-3.868-26.17 Agricultural exports 0.1375 7.14-4.459-3.28 Manufactured exports 3.6914 7.62-5.183-3.363 * The critical values of the WT at the 1 and 5% are respectively 9.31, 6.73 and 5.6 for a sample of 50. They are the usual t-values generated by Dickey and Fuller (see Pindyck et Rubinfeld, 1991:461). The Mackinon values for the ADF at 1, 5, and 10 percent are respectively -4.0673, -3.462, and -3.157.

Table B. FPE and SBT of a one-dimensional autoregressive process of real GDP, real Agricultural and manufactured exports, for SSA countries during the IS and EP periods Lag Order FPE y *10-2 SBT y *10-2 FPE x1 *10-2 SBT x1 *10-2 FPE x2 *10-2 SBT x2 *10-2 IS period EP period IS period EP period IS period EP period IS period EP period IS period EP period IS period EP period (1) Benin 1 2.46 11.02 2.71 12.10 34.01 13.34 37.51 14.64 15.51 29.03 17.11 32.37 2 2.78 13.48 3.22 15.35 29.89 7.23 34.49 8.24 17.63 34.12 20.34 39.91 3 3.07 16.09 3.65 18.76 31.12 9.26 37.34 10.79 18.53 45.05 26.16 54.60 4 3.92 20.18 3.66 23.40 36.78 9.48 45.35 10.87 24.70 46.35 28.13 58.93 5 4.69 22.17 7.22 24.12 46.50 9.86 57.64 10.99 25.98 49.11 29.80 58.98 6 6.22 40.23 8.28 35.58 48.58 12.96 64.76 11.46 30.73 85.20 34.75 60.58 (2) Burkina-Faso 1 0.76 4.99 0.84 5.47 6.56 4.75 7.24 5.21 11.38 13.71 12.56 14.99 2 0.80 5.57 0.93 6.35 6.83 5.50 7.89 6.27 13.28 16.24 15.35 18.35 3 0.92 6.82 1.11 7.95 7.13 6.88 8.60 8.02 15.89 17.39 19.18 18.59 4 0.95 8.01 1.65 9.29 8.28 9.26 10.31 10.74 16.99 18.01 21.16 20.09 5 1.06 8.81 1.83 9.59 10.15 9.56 12.85 16.11 20.12 27.54 25.47 27.41 6 1.57 9.52 2.73 10.46 10.47 9.63 12.93 17.09 28.47 26.12 25.56 42.23 (3) Cameroon 1 30.24 41.75 33.08 45.82 43.20 50.93 47.26 55.89 22.79 40.12 23.84 44.02 2 28.25 43.57 32.74 49.62 43.88 57.43 50.84 65.41 24.65 43.80 26.97 49.89 3 25.53 44.52 30.97 49.66 44.24 58.36 53.67 65.70 26.54 51.97 30.76 52.79 4 26.25 48.81 30.64 54.42 44.47 76.68 56.19 79.35 28.64 54.78 34.75 55.55 5 26.88 69.00 30.58 75.10 44.65 90.27 57.84 81.17 31.15 67.07 39.36 57.69 6 29.48 111.00 29.63 100.20 45.36 105.21 58.43 94.11 33.68 69.58 44.62 58.47 (4) CAR 1 2.99 2.00 3.30 3.33 8.61 7.49 9.50 10.29 10.51 12.36 11.60 12.11 2 2.73 2.11 3.15 3.45 3.74 7.50 4.32 10.69 12.19 14.56 14.10 12.52 3 3.21 2.22 3.84 3.65 3.18 7.58 3.84 11.05 12.29 15.69 14.61 12.63 4 3.58 2.32 4.41 3.66 3.97 7.68 4.95 11.25 13.02 16.66 16.22 12.76 5 4.7 2.35 5.83 3.68 4.78 7.88 6.06 12.88 16.17 17.66 20.47 12.87 6 5.10 2.38 6.09 3.69 5.97 7.98 7.45 13.87 19.80 18.62 24.70 13.88 (5) Côte-d Ivoire 1 24.53 8.56 26.83 9.39 77.22 2.36 84.48 2.59 21.40 12.53 23.41 13.75 2 22.00 10.38 25.49 11.83 76.46 2.21 90.92 2.52 20.72 15.81 24.01 18.01 3 18.99 12.59 23.04 14.68 76.16 2.79 92.04 3.25 29.87 18.96 24.11 22.10 4 19.74 15.85 23.15 18.38 76.06 2.84 94.58 3.29 38.11 22.51 22.88 26.10 5 20.32 18.30 23.30 19.91 78.27 3.47 94.66 3.77 46.53 27.35 21.90 29.75 6 23.32 141.67 28.37 125.30 78.91 5.16 95.70 4.56 55.54 73.67 21.43 65.16 (6) DRC

1 57.70 52.49 63.70 57.60 6.61 18.29 7.29 20.07 40.43 27.24 44.63 29.89 2 66.52 53.12 77.02 58.32 7.01 14.65 8.11 16.69 42.36 33.27 49.05 37.89 3 77.00 60.19 93.14 62.22 8.08 10.66 9.76 12.42 45.56 39.89 55.12 46.50 4 90.29 60.87 113.32 70.10 8.89 12.74 11.08 14.77 47.02 42.21 59.01 48.95 5 102.78 60.94 132.14 70.55 10.60 14.79 13.42 16.09 58.01 52.40 74.58 57.00 6 198.83 90.18 127.18 70.65 12.00 17.37 14.96 16.52 75.93 62.19 97.70 59.41 (7) Gabon 1 45.18 12.91 49.43 14.16 27.83 14.36 29.76 15.76 21.05 10.39 22.02 11.40 2 42.74 13.49 49.53 15.37 29.00 17.02 33.61 19.39 22.80 13.77 24.94 15.68 3 39.96 13.92 48.48 16.23 31.28 17.67 37.94 20.59 24.55 13.86 28.45 15.87 4 36.89 15.43 46.61 17.90 34.03 17.11 43.00 24.84 26.50 13.88 32.15 16.10 5 25.91 19.65 34.33 21.37 36.62 22.98 48.53 29.45 28.84 96.12 36.44 16.21 6 29.11 187.00 40.15 21.65 39.64 93.05 54.68 82.23 31.18 98.46 41.31 16.31 (8) Ghana 1 2.16 4.11 2.36 4.23 29.43 5.75 32.20 6.29 23.54 31.20 25.75 21.77 2 1.94 3.34 2.25 3.80 29.16 7.25 31.37 8.19 25.34 31.52 29.36 27.41 3 1.83 3.78 2.22 4.41 29.16 7.47 30.98 9.54 27.35 36.11 33.18 27.55 4 1.88 3.87 2.37 5.22 29.54 6.75 30.33 10.75 29.76 36.67 37.61 34.67 5 1.90 3.95 2.42 6.10 29.89 10.68 30.15 10.83 32.18 36.95 42.63 113.92 6 1.97 4.85 2.51 7.52 30.30 18.02 37.86 12.43 34.98 37.95 48.26 170.12 (9) Kenya 1 0.06 5.84 0.07 6.41 4.74 2.16 5.23 2.38 4.70 3.30 5.19 3.62 2 0.07 6.94 0.08 7.90 4.93 2.00 5.70 2.28 4.67 3.41 5.39 3.89 3 0.08 8.51 0.09 9.92 5.70 0.96 6.88 1.12 4.87 3.81 5.84 4.44 4 0.09 10.58 0.12 12.27 7.03 1.30 8.75 1.51 5.54 4.88 6.83 5.66 5 1.12 12.23 0.14 13.31 8.80 1.63 11.14 1.78 6.45 6.34 7.43 6.90 6 1.18 90.67 0.15 80.19 10.70 1.71 13.34 2.33 6.53 7.36 8.42 6.93 (10) Madagascar 1 0.04 2.10 0.52 2.30 2.95 7.32 3.26 8.04 10.96 2.02 12.10 2.21 2 0.05 1.59 0.63 1.82 2.90 8.15 3.19 9.28 11.74 1.97 13.59 2.24 3 0.53 1.75 0.64 2.05 3.52 9.52 4.25 11.10 11.84 2.19 14.33 2.55 4 0.63 1.84 0.79 2.91 4.29 11.59 5.35 13.44 14.28 2.53 17.93 2.93 5 0.76 2.06 0.96 3.22 4.77 13.89 6.04 15.11 16.31 2.49 20.97 3.93 6 0.97 2.31 1.21 5.04 6.04 25.20 7.53 22.29 20.65 3.92 26.57 3.96 (11) Malawi 1 0.19 14.82 0.20 16.26 2.11 2.83 2.33 3.10 8.98 3.01 9.91 3.30 2 0.18 17.56 0.20 19.99 2.48 2.80 2.87 3.19 7.64 3.80 8.84 4.33 19

3 0.15 21.63 0.18 25.21 2.86 2.71 3.45 3.15 9.16 4.74 11.06 5.53 4 0.13 25.19 0.16 29.20 2.97 3.21 3.51 3.72 9.83 4.76 11.08 5.65 5 0.19 29.22 0.24 31.79 3.72 8.53 3.55 9.28 10.56 4.85 19.57 5.78 6 0.21 43.07 0.32 38.10 3.89 9.15 6.09 9.41 11.11 4.91 21.65 6.43 (12) Mali 1 0.50 0.54 0.56 0.60 6.22 1.93 6.86 2.12 66.72 68.45 73.66 75.10 2 0.55 0.55 0.64 0.63 4.72 0.53 5.39 0.60 65.85 74.38 76.24 84.72 3 0.56 0.59 0.67 0.67 5.44 0.61 6.57 0.71 68.98 91.98 83.44 107.21 4 0.67 0.60 0.83 0.69 6.44 0.68 8.02 0.79 72.12 108.46 90.52 125.77 5 0.87 0.65 1.08 0.70 8.13 0.98 10.29 1.06 90.57 162.19 116.64 176.43 6 0.88 0.67 1.09 0.75 9.63 1.16 12.01 1.27 94.97 261.30 122.21 231.11 (13) Nigeria 1 26.01 12.48 28.46 13.70 49.56 14.52 54.22 15.93 25.11 145.80 27.47 51.46 2 24.23 15.26 28.08 17.38 52.20 15.31 60.48 17.44 27.04 180.84 31.33 52.35 3 22.34 19.30 28.10 22.49 56.35 12.57 68.11 17.46 29.16 228.94 35.78 68.16 4 23.23 23.74 28.83 27.53 61.09 41.54 77.19 17.48 31.64 297.41 39.98 68.69 5 29.94 27.50 29.42 29.64 65.98 42.28 87.42 20.03 34.20 398.11 45.32 96.57 6 32.67 175.67 35.75 155.37 70.06 43.25 96.64 22.65 37.12 552.32 51.20 106.29 (14) Niger 1 1.38 7.47 1.52 8.19 12.92 1.06 14.26 1.16 32.60 32.47 35.97 35.63 2 1.36 8.79 1.58 10.02 14.38 1.05 16.63 1.10 35.29 35.89 40.81 40.87 3 1.63 10.86 1.97 12.66 15.43 0.89 18.62 1.04 36.67 42.71 44.27 49.78 4 1.79 13.47 2.22 15.62 17.89 0.81 22.29 0.94 36.68 43.50 44.33 56.96 5 2.24 15.86 2.83 17.25 21.89 1.16 27.72 1.26 43.79 45.15 46.78 66.16 6 2.67 41.93 3.34 37.09 25.09 3.98 31.30 3.53 43.90 48.13 52.91 71.12 (15) Rep. of Congo 1 0.93 12.51 1.02 13.73 8.57 54.98 9.46 60.32 15.47 17.98 17.06 19.73 2 0.98 12.13 1.14 13.02 8.84 53.10 10.20 60.08 16.11 18.92 18.59 21.55 3 1.09 14.47 1.31 16.87 9.85 9.39 11.82 10.94 17.46 20.13 22.55 21.80 4 1.33 17.34 1.66 20.11 10.83 11.95 13.36 13.86 22.51 23.19 25.43 25.29 5 1.40 18.84 1.77 20.49 12.12 13.91 15.02 15.13 28.18 28.33 30.14 29.94 6 1.82 24.93 2.26 22.05 16.19 62.05 19.33 54.88 36.38 29.13 37.62 32.58 (16) Senegal 1 18.23 7.61 19.94 8.35 31.73 9.36 34.71 10.27 14.38 1.83 14.74 2.00 2 17.20 9.16 19.92 10.43 33.20 10.30 38.47 11.73 14.28 2.23 14.59 2.55 3 16.11 11.37 19.95 13.25 34.73 19.87 42.14 11.89 14.44 2.28 14.52 2.66 4 14.97 14.30 20.92 16.59 36.49 27.19 46.10 18.33 14.66 2.42 13.52 2.81 20

5 07.45 16.34 21.87 17.77 37.91 35.44 50.23 25.92 15.17 2.71 17.45 2.94 6 12.25 16.86 22.89 26.06 39.22 38.56 54.09 27.57 16.81 4.24 18.91 3.75 (17) Sierra-Leone 1 1.04 1.51 1.15 0.77 16.92 1.51 18.67 10.05 20.95 21.32 23.11 13.65 2 1.13 1.56 1.30 0.88 14.12 2.52 16.33 10.11 20.58 21.33 23.76 13.69 3 1.28 1.62 1.54 0.89 12.05 3.33 14.54 10.15 23.22 21.42 27.87 14.08 4 1.52 2.07 1.88 0.91 13.38 4.00 16.66 10.77 28.78 21.56 33.16 14.85 5 1.57 2.11 1.98 1.01 16.97 4.11 21.49 10.88 28.79 22.66 39.17 14.88 6 1.72 2.13 2.38 1.12 21.40 4.74 26.69 12.58 28.67 24.07 40.36 15.66 (18) Sudan 1 0.84 0.11 0.93 1.15 3.47 4.44 3.82 2.01 64.45 44.25 71.13 66.66 2 0.94 0.15 1.08 1.25 3.96 4.51 4.58 2.08 55.77 44.36 64.49 66.68 3 0.95 0.61 1.16 1.35 4.76 4.62 5.54 2.09 63.67 44.51 76.86 66.89 4 1.09 0.66 1.23 1.36 4.82 4.75 5.88 2.55 69.48 44.55 86.56 67.52 5 1.71 0.88 1.91 1.38 5.13 4.76 6.49 2.68 78.82 45.65 99.79 67.95 6 1.91 1.22 2.74 1.40 5.70 4.85 7.11 3.78 102.00 45.79 127.22 68.05 (19) Tanzania 1 0.07 43.95 0.07 48.22 2.75 2.77 3.04 3.04 13.01 22.32 14.36 24.49 2 0.08 52.90 0.08 60.25 3.01 2.88 3.48 3.28 15.06 23.98 17.42 27.31 3 0.09 62.94 0.73 73.37 3.28 3.22 3.96 3.26 18.28 28.76 22.06 33.52 4 0.76 75.53 0.93 87.59 3.34 3.30 4.16 3.34 20.39 38.07 25.41 44.14 5 0.94 87.53 1.16 95.22 4.34 3.43 5.49 3.47 23.75 51.48 30.07 56.00 6 1.23 105.38 1.47 104.76 4.37 4.30 5.67 3.52 30.56 57.59 38.12 50.94 (20) Togo 1 1.46 8.97 1.61 9.84 9.37 3.99 10.35 4.38 39.79 12.89 44.89 14.15 2 1.50 10.99 1.73 12.52 6.73 5.04 7.80 5.74 33.81 6.28 40.55 7.15 3 1.58 12.45 1.89 14.51 6.40 6.54 7.74 7.62 35.19 7.24 44.79 8.44 4 1.97 16.03 2.43 18.59 7.84 8.82 9.83 10.22 33.47 9.28 45.02 10.76 5 2.41 17.65 2.99 19.20 9.56 12.62 12.29 13.73 38.21 9.51 53.82 18.17 6 3.12 34.00 3.72 30.07 14.27 21.92 13.46 19.39 45.35 10.32 56.29 20.28 (21) Zambia 1 1.56 42.24 1.72 46.34 30.50 11.95 33.66 13.12 91.04 9.83 100.47 10.79 2 1.85 43.18 2.14 49.19 30.67 14.55 35.46 16.57 95.65 10.85 110.61 12.36 3 2.11 52.79 2.55 61.53 36.23 14.65 43.69 16.58 106.65 11.07 128.59 12.90 4 2.40 62.88 2.99 72.92 41.17 14.86 51.29 16.65 122.91 12.90 153.13 14.95 5 2.58 71.40 3.94 77.67 45.75 14.94 57.92 16.85 122.94 20.06 154.57 20.95 6 2.60 76.23 4.32 78.55 46.43 15.35 60.42 17.03 131.43 21.32 163.91 21.17 21