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Foreign Aid and the Dutch Disease: Evidence from Sierra Leone (For Presentation at the CSAE Conference 2014: Economic Development in Africa, Center for the Study of African Economies, University of Oxford, Oxford, UK) By Kelfala M. Kallon Department of Economics University of Northern Colorado Greeley, CO 80639 (970) 351-2134 Email: [email protected] Abstract: This paper investigated the long-run relationship between foreign aid, the real exchange rate, the trade balance, and economic growth in Sierra Leone. It found no support for the Dutch Disease hypothesis of an inverse relationship between foreign aid and economic growth in aid-recipient countries. Supporting the Balassa-Samuelson hypothesis, it also found a positive long-run relationship between labor productivity growth, the real exchange rate, the trade balance, and economic growth. A key implication of these findings is that even though foreign-aid is associated with long-run economic growth in Sierra Leone, its negative impact on the real exchange rate lowers the real income of cash-crop farmers, which raises the level of poverty and income inequality in the country. To reverse this outcome (of economic growth and increased poverty and income inequality), Sierra Leonean authorities should be using foreign aid resources and mineral rents to invest in the nation’s human capital stock and infrastructure, thereby leading to improvements in labor productivity. Labor productivity growth would lead to a real appreciation of the leone and economic growth. The stronger leone would then raise producer incomes, thereby reducing the level of rural poverty and income inequality. KEYWORDS: Foreign Aid; Dutch Disease; Balassa-Samuelson Hypothesis; Real Exchange Rates; Sierra Leone JEL CLASSIFICATIONS: F31, F35, O55. 1 I. Introduction The Dutch Disease hypothesis holds that when foreign aid is spent, even partially, on nontraded goods, the currency of the aid-recipient country appreciates in real terms. This then makes its exports less competitive on world markets. As a result, exports fall and imports increase, thus worsening the trade balance. The result is a fall in aggregate demand and, consequently, equilibrium income (Van Wijnbergen, 1984, 1985).1 Additionally, as imports become relatively less expensive following the real appreciation of the exchange rate, they displace domestically produced import-competing goods, which can lead to deindustrialization. Even if foreign aid causes a real appreciation of the recipient country’s currency, as suggested by the Dutch Disease hypothesis, the conclusion that this adversely impacts its export sector might not be true for all small open economies. Firstly, such economies are price takers on world markets. Secondly, world market prices of primary commodities are set in the major international currencies, not in those of the small open economies. Hence, the real exchange rate does not impact the foreign-currency prices of their exports. For example, if the world-market price of coffee is $500 per ton, Starbucks will pay $500 per ton for Sierra Leonean coffee regardless of the leone-dollar real exchange rate. Therefore, the leone-dollar real exchange rate will have no impact on Starbuck’s decision-making about how much Sierra Leonean coffee it purchases. Real currency appreciations however raise the real income of exporters and lower the relative costs of imported inputs. This creates incentives for increased exports. For instance, at any world market price of coffee, coffee farmers in Sierra Leone would receive more imported 1 In general, the negative impact on a country’s economy of anything that causes a huge inflow of foreign currency can cause the Dutch Disease phenomenon. Thus, in addition to foreign aid, worker remittances and natural resource exploitation can also inflict the Dutch Disease on a country. 2 goods per ton of coffee following a real appreciation of the leone. This exchange-rate-induced real income effect would then create incentives for more coffee exports, not less. Furthermore, on the cost side, a real exchange rate appreciation lowers the relative prices of imported inputs (imported crude oil, fertilizer, and agricultural implements, for instance), which consequently lowers production costs and increases per-unit profit. The reduced cost of imported inputs could actually give the domestic import-competing industry a cost advantage, thereby increasing production in the domestic import-competing sector. Therefore, contrary to the Dutch Disease hypothesis, real exchange rate appreciations could actually improve the trade balance of a small open economy. However, small open economies that are dependent on foreign direct investment (FDI) could be adversely affected by real exchange rate appreciations. This is because an appreciation of the host country’s currency raises the relative price of domestic inputs, thereby making the host country less attractive for foreign investment. Thus, if the supply elasticity of the FDIintensive export sector is greater than that of the small-farmer-produced export crops, which is typically the case, a real exchange appreciation could reduce FDI flows, cause the trade balance to deteriorate, and lower real output. Finally, if the foreign-aid resources are expended on export-capacity expansion, the resultant export-led boost to aggregate supply would lower the recipient country’s price level and raise its real output. At the existing world export prices, the consequent increase in export volume would increase export revenues and cause the domestic currency to appreciate. Domestic deflation, on the contrary, would cause a real exchange rate depreciation. Finally, increases in domestic real income would raise import demand and also cause a real depreciation of the domestic currency. 3 Table 1: Net ODA As a Percentage of Period As a Percentage of GDP Government Expenditures 1975-1979 3.1234 36.4956 1980-1989 8.7236 117.3996 1990-1999 18.2476 170.9770 2000-2005 34.6575 228.1825 1974-2005 15.5124 139.7453 Source: Author’s Calculations based on the World Development Indicators Dataset. It should be clear from the above that the impact of foreign aid on the recipient country’s real exchange rate of a small open economy and the effect of the latter on the trade balance and real output cannot be determined a priori. Furthermore, because poverty reduction is a key objective of foreign aid, the latter’s impact on the levels of poverty and income inequality is also germane to the usefulness or lack thereof of foreign aid. Accordingly, this paper uses data from Sierra Leone to empirically investigate the impact of foreign aid on the real exchange rate, the trade balance, and real GDP growth. The implications of its findings on the levels of poverty and income inequality in that country are also discussed. The choice of Sierra Leone is justified by its historic dependence on foreign aid, which is demonstrated in Table 1, which shows net ODA rising from a low 3.12 percent of GDP per year between 1974 and 1979 to a high of 34.66 percent per year in the 2000-2005 period. For the entire 1974-2005 period, net ODA constituted approximately 15.5 percent of GDP per year. Data on net ODA as a percentage of government expenditures demonstrate the country’s aid dependence even more glaringly. Constituting nearly 36.5 percent of government spending per year in the 1974-1979 period, foreign aid as a percentage of government expenditures skyrocketed to approximately 117.4 percent, 180 percent, and 228.2 percent in the 1980-1989, 4 1990-1999, and 2000-2005 periods respectively. For the entire 1974-2005 period, net ODA accounted for approximately 139.75 percent of government spending per year. The rest of the paper is organized as follows. The empirical literature on the Dutch Disease phenomenon is surveyed in Section II. A model of the relationship between the real exchange rate, the trade balance, and real output in small open economies is developed in Section III and estimated in Section IV using Johansen’s maximum-likelihood procedure. Key findings of the study and their policy implications are then presented in Section V. II. A Survey of the Literature While there have been several empirical studies on the determinants of the real exchange rate in developing countries, those on the Dutch Disease in SSA have been scanty and have produced mixed results. For example, Harvey (1992) found that Botswana’s diamond export boom did not cause the Dutch Disease phenomenon in that country. However, Falck (1997) found evidence of the phenomenon in Tanzania. This was contradicted by Nyoni (1998) and Li and Rowe (2007). In West Africa, Sackey (2002) and Sanusi (2011) found support for the phenomenon in Ghana while Ogun (1995) found no such effect in Nigeria. In a cross-country study of twelve CFA Franc countries,2 Ouattara and Strobl (2008) found no support for the phenomenon. In contrast, Adenauer and Vagassky (1998), Elbadawi (1999), Elbadawi, Kaltani, and Soto (2009), and Fielding and Gibson (2012) found support for it among a cross-section of SSA countries. Fielding and Gibson (2012) also found that “hard” fixed exchange rate regimes have larger Dutch Disease effects than flexible exchange rate regimes. In Asia, White and Wignaraja (1992) found that increases in aid and remittances caused a real appreciation of the Sri Lankan currency. And on the general issue of private capital flows, 2 The CFA franc is a currency used by 12 formerly French colonies in West and Central Africa, whose value was previously fixed against the French franc but is now fixed against the euro. 5 which is more important than foreign aid to Asia and Latin America, Athukorala and Rajapatirana (2003) found increases in FDI associated with a depreciation of the real exchange rate while other capital flows have the opposite effect. Meanwhile, Rajan and Subramanian (2011) found support the Dutch Disease in a cross-section of developing countries. Finally, worker remittances were shown to have Dutch Disease effects in Cape Verde (Falck and Bourdet, 2006), Guatemala (Fuentes and Herrera, 2007), and Latin America in general (Lopez, Molina, and Bussolo, 2007). Like the empirical literature on the Dutch Disease, the empirical literature on the relationship between foreign aid and real GDP growth is also quite mixed and unsettled. For instance, in a meta-analysis of the existing literature at the time, Tsikata (1998) concluded that, though contentious, the plurality of the evidence suggests an insignificant relationship between aid and economic growth. Hansen and Tarp (2001) contrarily found the literature increasingly being supportive of a positive relationship between the variables. Doucouliagos and Paldam (2008) countered with a meta-analysis that again suggested the insignificance of the aideconomic growth relationship. Additionally, they concluded that the aid-economic growth relationship becomes positive only when Asian countries are included in the sample. This suggests that regional differences also matter. However, after reviewing the same studies in Doucouliagos and Paldam (2008), Mekasha, and F. Tarp (2013) reported a positive relationship between aid and economic growth. They further claimed that the insignificant findings by Doucouliagos and Paldam (2008) had been based on the methodological error of assuming fixed effects in the panel studies when the heterogeneity of recipient country characteristics make the random effects assumption more appropriate. 6 From the experience of both post-World War II Europe and South Korea, we know that foreign aid can foster economic growth if the capacity to use it effectively exists in the recipient country or region. This suggests that cross-country studies of countries with different aid-using capacities are bound to provoke more disagreement than agreement in view of the fact that they lump together countries with different policies, histories, and capacities. Thus, individual country studies are perhaps more appropriate because they are not polluted by the inclusion of countries with disparate characteristics in the same sample. The aid economic growth relationship also suffers from an endogeneity problem because if poverty alleviation is a key objective of foreign aid, slow-growth countries would receive more foreign aid than their high-growth counterparts. Also, the more an open economy, the more foreign investment it is likely to attract. With foreign investment comes technology transfers, which increase labor productivity, the real exchange rate, the trade balance, and real output. Hence, the single-equation estimation techniques that have been used in previous studies suffer from simultaneity bias. This calls for a multi-equation estimation in order to avoid that bias. Finally, although Sierra Leone is hugely aid-dependent, I know of only one study (Kargbo, 2012) that has investigated the aid-economic-growth relationship in that country. That study found a positive long-run relationship between foreign aid and economic growth in Sierra Leone. Given the dependence of Sierra Leone on foreign aid, this study will be a valuable addition to this virtually non-existent literature on a subject that is very crucial to the Sierra Leonean economy. III. The Empirical Model A. The Long-Run Real Exchange Rate The existing literature holds that the long run real exchange rate in developing economies 7 depends mainly on real variables—the terms-of-trade, the level and composition of real government expenditures, trade and foreign-exchange controls, technical progress, market access and institutional quality (De Gregorio and Wolf, 1994; Edwards, 1988; Li and Francis, 2007; Elbadawi, 1994; Elbadawi and Soto, 1997; and Wong, 2009). The Dutch Disease hypothesis adds foreign aid to that mix. Because how foreign aid impacts the real exchange rate has already been discussed, the rest of this section will focus on its other determinants. 1. Labor Productivity Balassa (1964) and Samuelson (1964) demonstrated that labor productivity growth causes the domestic currency to appreciate in real terms. Starting in the traded goods sector, labor productivity growth initially causes a wage increase in that sector. Eventually, wages will increase in the non-traded-goods sector also in order to equilibrate the aggregate labor market. This increases production costs and the domestic price level. Consequently, the domestic currency appreciates in real terms. Labor productivity growth could also cause a real depreciation of the currency of a small open economy if its citizens spend most of their productivity-induced income increases on imported goods. Therefore, under the small-country assumption, labor productivity growth would have an ambiguous effect on the real exchange rate. 2. Trade Openness A positive relationship supposedly exists between trade openness, total factor productivity growth, and economic growth (Barro, 1997; Dollar, 1992; Edwards, 1993 and 1998; Harrison, 1996; Mankiw, Romer, and Weil, 1992; and Yanikkaya, 2003). The resultant domestic prosperity leads to increased imports, which then causes the domestic currency to depreciate in both nominal and real terms. 8 Free trade involves exporting commodities in which a country’s firms have comparative advantage and importing those in which they have a comparative disadvantage. Therefore, trade openness should increase both imports and exports, thereby having an ambiguous effect on the real exchange rate. Trade openness also enhances a country’s export and/or import-substitution capacity through technology transfers by multinational companies (MNCs). Under the small-country assumption, the resultant export expansion and/or import reduction should cause an appreciation of the domestic currency. The bottom line, therefore, is that the net effect of trade openness on the real exchange rate of small open economies cannot be determined a priori. 3. Foreign Incomes Foreign income growth increases the demand for the domestic-economy’s exports, thereby leading to a real appreciation of its currency. Additionally, economic prosperity in the developed countries creates a favorable political climate for foreign aid and private capital flows to the developing countries. Consequently, the increased demand for the domestic economy’s exports and increased capital inflows should cause a real appreciation of the domestic currency. 4. Government Expenditures Government expenditures are by nature skewed toward the non-traded goods sector. Hence, they initially raise wages and prices in that sector. The resultant reallocation of resources away from the traded-goods to the non-traded-goods sector causes a reduction in exports, which causes a real currency depreciation. Additionally, government spending is usually financed by monetary expansion in much of Sub-Saharan Africa, which causes lower domestic interest rates, increased capital outflows, and a real depreciation of the domestic currency. However, regardless of how it is financed, government spending also raises aggregate demand and, consequently, the price 9 level and the interest rate. The resultant domestic inflation and capital inflows then causes a real appreciation of the domestic currency. In other words, the net impact of government expenditures on the real exchange rate cannot also be determined a priori. 5. The Terms of Trade Improvements in the terms of trade raise producer incomes in small open economies. This incentivizes them to allocate productive resources to the export sector. Under the small-country assumption, the increase in exports should cause a real appreciation of the domestic currency. However, if domestic residents have a substantial taste bias for imported goods, improvements in the terms of trade could disproportionately increase import demand, thereby causing a real depreciation of the domestic currency. Consequently, the net impact of an improvement in the terms of trade on the real exchange rate depends on the relative magnitudes of its supply-side impact on export expansion and demand-side impact on imports. Based on the above, the following is the long-run equilibrium behavioral equation for the real exchange rate (R):3 ? ? ? + ? ? ? R = R NODA, LPROD, OPEN, GOV, YF, TOT, Z ; (1) where NODA = net foreign aid flows; LPROD = labor productivity; OPEN = trade openness; YF = foreign income; GOV = share of government expenditures in GDP, TOT = the terms of trade, and Z = all other factors that impact the real exchange rate.4 3 A question mark above a variable denotes that its expected impact on the real exchange rate is ambiguous while the plus denotes a positive impact. 4 This is a proxy for such things as the absence of tariffs against the country’s exports, the quality of its institutions, its regulatory framework, the level and quality of its infrastructure, and the knowledge and skill base of its workers. 10 B. The Trade Balance Neoclassical economics assumes the trade balance being positively related to foreign incomes (YF) and inversely related to the real exchange rate (R) and domestic income (Y). The above discussion however suggests that this may not hold for small open economies. On the one hand, real exchange rate appreciations raise the per-unit profit of domestic producers by increasing export revenues and lowering the domestic currency prices of imported inputs. This should lead to export growth and an improvement in the trade balance. On the other hand, real currency appreciations raise production costs in FDI-intensive activities, thereby making the country relatively uncompetitive as a host for FDI. As a result, its exports suffer. Moreover, imports become relatively cheaper when a country’s currency appreciates in reals terms. Resultantly, imports increase, thereby putting downward pressure of the trade balance. Finally, real currency appreciations also lower the domestic-currency prices of imported inputs, which gives domestic producers of import-competing goods a cost advantage, thereby lowering imports. Thus, the real exchange rate’s impact on the trade balance of small open economies is ambiguous. Hence, the determinants of the former would also ambiguously impact the trade balance, as suggested below in Equation (2): ? ? ? ? ? ? − ? ? − ? TB = F R, YF, Y = F NODA, LPROD, OPEN, GOV, TOT, Z, YF, Y ; (2) C. Real Output In the Harrod-Domar growth model (Harrod, 1939; and Domar 1946), economic growth in the developing countries is assumed to be inhibited by low savings, which limits investment in both physical and human capital. Thus, foreign resources (in the form of aid, foreign investment and loans) are necessary to close the savings gap. Solow’s growth model (Solow, 1956), on the other hand, gave prominence to technical progress as the key driver of long-run economic 11 growth. However, technical progress was assumed to be exogenous. Therefore, regardless of their domestic savings rates, developing countries could get new technology through multinational corporations (MNCs)—which invest in the developing countries in order to take advantage of their relatively higher rates of return on capital. Thus, even if foreign aid is not available, economic growth would continue and convergence in living standards would occur if free trade and free capital movements are allowed. Finally, the endogenous growth model identified investment in knowledge, skills, and infrastructure as the key determinants of technical progress, something that the Solow model considered as exogenous. Thus, countries that invest in knowledge, infrastructure, and physical capital grow faster than those that can’t or won’t. And because of low domestic savings, developing countries can only adequately invest in these assets through foreign resources (aid, technical assistance, loans and investment). This links foreign aid directly to economic growth in the developing countries. Rebelo’s AK model (Rebelo, 1991) best describes the aid-growth relationship in the spirit of the endogenous growth model:5 Y = AK; (3) where A = total factor productivity and K = capital stock. Assuming that investment in a developing country is mostly financed with foreign resources (foreign aid and foreign private capital flows)—because of low or non-existent domestic saving—creates a direct relationship between foreign resources and economic growth in developing countries. Furthermore, because real exchange rate appreciations raise the cost of foreign investment in the host country, foreign private capital flows are assumed to be inversely related to it. In sum, therefore, a developing 5 The AK model is a special class of the Cobb-Douglas production function in which the elasticities of output are respectively 1 and zero for capital and labor. 12 country’s capital stock should depend positively on net foreign aid flows (NODA), negatively on the real exchange rate, and positively on other exogenous factors (Z): + − + (4) K = K(NODA, R, Z). Substituting R in Equation (4) with the right-hand-side expression in Equation (1) yields the following relationship between real output and its determinants: − + ? ? ? + ? + + ? Y = AK NODA, R, Z = AK NODA, LPROD, OPEN, GOV, YF, TOT, Z . (5) Equations (1), (2), and (5) can be restated in the following reduced-form long-run equilibrium equations: β11 R t -β12 NODAt -β13 LPRODt -β14 OPENt -β15 GOVt -β16 TOTt -β17 YFt -β18 Zt 06 β21 TBt -β22 NODAt -β23 LPRODt -β24 OPENt -β25 GOVt -β26 TOTt -β27 YFt -β28 Zt 0.7 β31 Yt -β32 NODAt -β33 LPRODt -β34 OPENt -β35 GOVt -β36 TOTt -β37 YFt -β38 Zt 0.8 The above equations represent a structural VAR model in which β11, β21, β31 are restricted to 1 and the coefficients of Rt, TBt, and Yt are restricted to zero in each other’s equation. If the variables are cointegrated, the rank of their cointegrating matrix should be 3. In other words, each βij in the last n-3 equations is assumed to be zero. Finally, under the Dutch Disease hypothesis, β12 should be positive while β22 and β32 are negative. Additionally, the sign of each βij in the real exchange rate equation should be the opposite of its corresponding coefficient in the other two equations. Because labor productivity starts in the traded goods sector under the Balassa-Sameulson hypothesis, it should also have a positive impact on net exports (the trade balance) and equilibrium output in countries like Sierra Leone whose traded-goods activities are purely export oriented. In other words, β13, β23, and β33 should be positive. However, under the 13 neoclassical assumptions of the Dutch Disease hypothesis, if β13 is positive, β23, and β33 should be negative, and vice versa. Thus, the two hypotheses are mutually exclusive. IV. Data, Estimation, and Results A. Data Annual data spanning 1974 and 2005 are used in the empirical analysis. The World Bank’s World Development Indicators dataset is the source of net foreign aid flows as a proportion of GDP. Data on labor productivity are from The Extended Penn World Tables (Marquetti, 2012). Because there are no continuous data on Sierra Leone’s terms-of-trade for the entire sample period, the terms of trade index for the Sub-Saharan Africa6 was used as a proxy. Meanwhile, the index of industrial production for advanced economies was used as a proxy for foreign income. Because of the lack of continuous time series on Z for Sierra Leone, it was not included in the VAR. Finally, the January 2014 issue of the International Monetary Fund’s International Financial Statistics is the source of data for the trade balance,7 unit values of SSA exports and imports, government expenditures, real GDP, and the index of industrial production for advanced economies. Finally, Darvas (2012) is the source of the data on the real effective exchange rate.8 In order to account for the impact of the civil war on the dependent variables, a war dummy (WAR, which is equal to 1 for the 1991-2002 period and zero otherwise) was added to the model 6 This was calculated as the ratio of the unit value of SSA exports to the unit value of its imports) 7 Sierra Leone mostly ran trade deficits (interspersed with a handful of years of trade surpluses) during the sample period. Therefore, the ratio of exports to imports was used as a proxy for the trade balance. Hence, the difference of its log is the rate of growth of the trade deficit. 8 The real effective exchange rate was calculated as follows: w ij pe R i = ∏ i ij ; where j=1 p j t n pi and pj denote Country I’s and Country J’s respective price levels; eij is the bilateral spot exchange rate (defined as the units of Country J’s currency that can be exchanged for a unit of Country I’s); and wij is the ratio of the bilateral trade between the two countries. Therefore, an increase in Ri denotes a real appreciation of Country I’s currency. 14 as a deterministic term. It is expected that its impact on the dependent variables will be negative. Finally, all the variables were expressed in natural logarithms. B. Estimation Equations (6), (7), and (8) are best estimated by Johansen’s maximum-likelihood procedure for cointegrated VAR models (Johansen, 1988) because it assumes that the variables are endogenous. However, as Cheung and Lai (1993), Haug, (1996), Gredenhoff and Jacobson (2001), and Toda (1995) have shown, the Johansen trace test suffers from small-sample bias. As a remedy, Johansen (2002) developed a small-sample Bartlett correction. This has been shown to improve the robustness of the Johansen procedure in small samples (Kurita, 2013). Version 2 of Cointegration Analysis of Times Series (CATS), which is used in this study, has the Barlett correction.9 Additionally, CATS has a multivariate stationarity test which is based on the deterministic terms in the cointegrating relations. This makes it superior to the traditional univariate unit-root tests. 1. Rank Determination When individual graphs of the variables were examined, some, but not all, of them show trends. However, when they are graphed together, they resemble random-walk processes with drifts. Therefore, if their linear combination is stationary, it is not likely to have a common trend. Consequently, only a constant was assumed in the cointegrating space. Finally, based on the Likelihood Ratio test, the Final Prediction Error Criterion, the Schwarz Criterion, and HannanQuinn Information Criterion, a one-period lag was chosen as optimal.10 9 CATS is a procedure in Estima’s Regression Analysis of Time Series (RATS). 10 In contrast, the Akaike Information Criterion identified 3. Monte Carlo simulations have shown that the use of the likelihood ratio test together with information-criteria tests increase the chances of correctly choosing the optimal lag (Hatemi-J and Kacker, 2009). This and the small sample size informed the decision on one lag. 15 Table 2: Rank Determination Statistics NullHypothesis r=0 Eigenvalue 0.9419 Uncorrected Trace Trace P-Value 281.5073 0.0000 Corrected Trace Trace P-Value 240.6473 0.0000 r=1 0.8569 193.3147 0.0000 170.1331 0.0008 r=2 0.7773 133.0337 0.0011 120.3208 0.0122 r=3 0.7111 86.4677 0.0245 80.2252 0.0704 r=4 0.5357 47.9792 0.2340 45.5837 0.3199 r=5 0.3922 24.1955 0.4528 23.4971 0.4949 r=6 0.2462 8.7615 0.5605 8.6816 0.5683 Table 2 reports the trace statistics for the cointegrating matrix. The corrected statistics are smaller than their uncorrected counterparts. This is expected because the Bartlett Correction imposes a penalty on small samples. The uncorrected trace test identified a rank of 4 at the 0.05 level while the corrected version identified 3. Consequently, a rank of 3 was chosen, meaning that there are three long-run equilibrium relations between the endogenous variables, as suggested by the structural model. 2. The Estimated Long-Run Equilibrium Relationships The estimated cointegrating vectors (β′) were normalized in terms of the dependent variables in the structural equations (R, TB, and Y). Identifying restrictions were then placed on the estimated cointegrating relations in consonance with the structural model. The estimated coefficients and the absolute values of their t-statistics (in parenthesis), which are reported in Table 3, show that the estimated coefficients of the trade openness variable are quite insignificant in both the trade balance and real income equations. A zero-value restriction was therefore placed on its coefficient in those equations. With a Chi-Square statistic of 0.1288 and 2 degrees of freedom, the null hypothesis could not be rejected. Thus the model was re-estimated 16 Table 3: Estimated Cointegrating Vectors (Unrestricted Model) R Equation TB Equation Y Equation Coefficient t-Statistic Coefficient t-Statistic Coefficient t-Statistic 1.000 -- -- -- -- -- TB -- -- 1.0000 -- -- -- Y -- -- -- -- 1.0000 -- Constant 31.9954 5.5477a -71.4266 7.5874a -16.8093 21.7400a NODA 0.9415 8.3604a -1.9774 10.7578a -0.1641 10.8728a LPROD -1.1859 -4.0282a -0.7269 1.5127 -0.3300 8.3601a OPEN 1.0650 7.3042a -0.0961 0.4036 -0.0128 0.6546 GOV -0.0954 -1.3141 0.3537 2.9839a 0.0131 1.3413 a 0.2166 1.7909 R YF -3.5402 -3.9237a 9.1191 6.1921 TOT -2.3615 -3.1849a 8.0448 6.6471a 0.6123 6.1593a WAR -0.6764 -4.7586a 2.0020 8.6288a 0.2947 15.4659a a=significant at the 0.01 level. Table 4: Estimated Cointegrating Vectors (Restricted Model) R TB Y Coefficient t-Statistic Coefficient t-Statistic Coefficient t-Statistic 1.000 -- -- -- -- -- TB -- -- 1.0000 -- -- -- Y -- -- -- -- 1.0000 -- Constant 32.6598 5.9474a -71.9253 8.2502a -16.8853 23.3760a NODA 0.9476 8.5347a -1.9672 10.8974a -0.1630 10.8954a LPROD -1.2083 4.1964a -0.7134 1.5320 -0.3278 8.4961a OPEN 1.0125 11.2584a -- -- -- -- GOV -0.1068 1.5345 0.3729 3.3617a 0.0156 1.7001 YF -3.6698 4.2410a 9.2821 6.7221a 0.2390 2.0889b TOT -2.3664 3.2594a 8.0198 6.8251a 0.6098 6.2631a WAR -0.7074 5.3700a 2.0374 9.9450a 0.2996 17.6495a R Chi-Square (2) = 0.1288; a=significant at the 0.01 level; b = significant at the 0.05 level. 17 Table 5: Residual Analysis Test Statistic D.O.F P-Value LM(1) 62.2028 49 0.0975 LM(2) 49.5208 49 0.4523 Normality 22.3307 14 0.0721 LM(1) 835.9955 784 0.0965 LM(2) 1,604.1139 1,568 0.2572 Serial Correlation ARCH Figure 1: Actual and Fitted Dependent Variables R TB 5.8 Y 0.5 15.4 5.6 0.0 15.3 5.4 -0.5 5.2 -1.0 5.0 -1.5 4.8 -2.0 4.6 -2.5 4.4 1975 -3.0 1975 15.2 15.1 1980 1985 1990 Actual 1995 Fitted 2000 2005 15.0 14.9 1980 1985 1990 Actual 1995 2000 2005 14.8 1975 1980 1985 Fitted 1990 Actual 1995 2000 2005 Fitted with the restrictions and the results are reported in Table 4. Although the magnitude of the coefficients remained relatively unchanged, as expected, the t-statistics improved moderately. In spite of this, the coefficient of labor productivity in the trade balance equation (β23) and those of government expenditures in the real exchange rate and the real GDP equations (β15 and β35, respectively) remained insignificant. Moreover, all the variables in the restricted model retained their original signs. Finally, graphs of the estimated cointegrating relations are reported in the appendix as Figures A1, A2, and A3. They show that the relations are stationary. 3. Model Diagnosis The Johansen maximum likelihood procedure used in this analysis assumes that the residuals are NIID. Table 5 reports the results of the Breusch-Godfrey LM test for serial 18 correlation, the normality test, and the ARCH test for heteroskedasticity. They show that the null hypotheses of the absence of serial correlation, normality, and homoscedasticity could not be rejected at the 0.05 level. Hence, the residuals are NIID as assumed. Also, CATS’ multivariate stationarity test rejected the null hypothesis of stationarity of all the endogenous variables at the chosen rank of 3. The Augmented Dickey-Fuller (ADF) and Phillip-Perron (PP) unit root tests also identified two of the endogenous variables (real GDP and labor productivity) to be I(2) while the rest are I(1). However, only two endogenous variables need to be integrated in the same order for cointegration to exist between a group of nonstationary endogenous variables (Dennis, 2006: 4). Therefore, together, these results confirm that the endogenous variables are candidates for cointegration.11 Finally, how well a model predicts the endogenous variables is an important test of its performance. Accordingly, actual and fitted values of the dependent variables from the restricted model are graphed in Figure 1. They show the fitted values tracking their actual values very closely. 12 This suggests that the estimated equilibrium relations from the restricted model are quite robust. 3. Interpretation of the Results Contrary to the Dutch Disease hypothesis, the evidence shows foreign aid being associated with a real depreciation of Sierra Leone’s currency (the leone), an improvement in its trade balance, and economic growth. Thus, like Kargbo (2012), this study also concludes that foreign aid promotes economic growth in Sierra Leone. Specifically, a percentage increase in foreign aid 11 The stationarity and unit root test results are available upon request. 12 Graphs of the other endogenous variables and their fitted values, which also show a remarkable fit, are available from the author. 19 flows is associated with a 0.95 percent real depreciation of the leone, a 1.97 percent improvement in the trade balance, and a 0.16 percent real GDP growth. That real exchange rate has a positive long-run relationship with both the trade balance and real output is supportive of the neoclassical view that real exchange rate depreciations increase exports and decrease imports, thereby resulting in an improvement in the trade balance and economic growth. This appears at face value to contradict the argument that the income effect of real exchange rate changes on cash-crop exports in countries like Sierra Leone should cause the trade balance to deteriorate following real currency depreciations. However, because coffee and cocoa, the country’s major export crops are tree crops, which do not bear seeds for at least 5 years after they are planted, the response of farmers to real exchange rate changes is likely to be relatively smaller than that of the FDI-intensive sector. Consequently, an aid-induced real depreciation of the leone is likely to have lowered cash-crop exports by less than it increased FDI-intensive exports. As a result, aggregate exports increased, causing economic growth and an improvement in the trade balance. Labor productivity growth is positively associated with the three dependent variables, as suggested by the Balassa-Samuelson hypothesis. It is however not significant in the trade balance equation. This suggests a taste bias for imported goods by workers in the FDI-intensive sector. Therefore, as their incomes rise as a result of their increased productivity, their demand for imports rises proportionately with the supply of FDI-intensive exports. As a result, the trade balance remains unaffected. Finally, that labor productivity growth has a positive and significant long-run relationship with real GDP, in spite of its lack of impact on the trade balance, suggests that even though productivity growth might start initially in the traded-goods sector, it eventually filters through the economy thereby leading to economy-wide output growth. 20 Trade openness was significant (negatively) in only the real exchange rate equation and not the other two. As noted already, increased trade openness raises both exports and imports. It is therefore not surprising that it had no significant impact on net exports and, consequently, equilibrium income. The two effects might just have canceled each other out. That, in spite of this, trade openness caused a real depreciation of the leone could be explained by movements in the capital account following the reforms that made the economy more open. Specifically, the abolition of controls on foreign exchange and capital flows might have caused net capital outflows from Sierra Leone, consequently causing a real depreciation of the leone. Like Kargbo (2012), no significant long-run relationship was found between government spending and either the real exchange rate or the rate of economic growth. It was, however, found to be negatively associated with the trade balance in the long run. This might be explained by the fact that government spending is generally skewed in favor of the non-traded-goods sector. The resultant reallocation of productive resources to that sector (away from the tradedgoods sector) might have caused the deterioration in the trade balance. Foreign economic growth, meanwhile, was found to be positively related to the real exchange rate and negatively to both the trade balance and real GDP. This is in congruence with neoclassical theory, which holds that foreign economic growth increases exports. Without any direct impact on imports, this should lead to an appreciation of the domestic currency. However, if there is a significant consumption bias in favor of imported goods, the trade balance could deteriorate if the foreign-income-induced increase in exports is outweighed by the exchange-rate induced increase in imports. In that case, foreign income growth could also lead to a reduction in domestic output. This seems to have been the case in Sierra Leone. 21 For its part, the terms-of-trade was found to be positively associated with a real appreciation of the leone and negatively with both the trade balance and real output. Specifically, the leone appreciated in real terms by approximately 2.37 percent for each percentage improvement in the terms of trade. The income effect of improvements in the terms of trade raises both exports and imports. Therefore, that the real exchange rate appreciated could be explained by the fact exports rose faster than imports. However, if this were true, the trade balance would have improved. The evidence, on the contrary, shows a significant negative relationship between the terms of trade and the trade balance. This again suggests a high income elasticity of demand for imports among Sierra Leoneans. As a result, increased producer incomes due to terms of trade improvements raised imports in excess of exports, thereby causing a deterioration in the trade balance and a reduction in the rate of economic growth. Finally, the war years are associated with a 0.71 percent real appreciation of the leone. This might be due to the massive wartime capital inflows due to operations by especially the United Nations and the British during the latter half of the war. The war years were also found to be negatively and significantly related to both the trade balance and economic growth. Obviously, with domestic economic activities having almost ground to a halt amidst massive imports of arms and food, this finding was expected.13 V. Conclusions and Policy Implications A key finding of this study is that the Dutch Disease hypothesis does not hold for Sierra Leone, a heavily foreign-aid dependent country. Therefore, in the case of Sierra Leone, the answer to Easterly’s question “Can Foreign Aid Buy Growth?” (Easterly, 2003) is affirmative. Even as it has promoted economic growth, has foreign aid achieved its core objectives of 13 This finding is contrary to the non-significant relationship found by Kargbo (2012) between war-time foreign aid and economic growth found. 22 poverty reduction and human development in Sierra Leone? The finding of a negative relationship between foreign aid and the real exchange rate suggests that the answer to this question is negative. As noted earlier, there is a direct relationship between the real exchange rate and the real incomes of the producers of export crops in countries like Sierra Leone. Thus, foreign-aid-induced real depreciations of the leone reduce the real incomes of Sierra Leonean cash-crop farmers, who constitute one of the poorest groups in the country. On the other hand, they raise the prices of inputs in the FDI-intensive sector, much of which accrues to urban elites and foreign owners of capital. Therefore, with over two-thirds of the Sierra Leonean population engaged in rural agriculture, aid-induced reductions in rural incomes increases the levels of poverty and income inequality in the country—even as it promotes long-run economic growth. This is consistent with the finding that at least 44 percent of real GDP growth in the postindependence Sierra Leone has accrued to the owners of capital (Kallon, 2013). Finally, the Dutch Disease hypothesis and other kindred justifications have led to policy recommendations that, like their Asian counterparts, SSA countries should forego foreign aid altogether (or be forced to do so by international donors) and rely more on FDI and loans in order to foster economic growth.14 Contrarily, this study suggests that instead of foregoing foreign aid, Sierra Leonean authorities should be investing foreign-aid resources to improve the quantity and quality of the nation’s human capital stock and infrastructure (in especially rural agriculture).15 This would raise the productivity of agricultural labor. Improvements in labor productivity would cause the leone to appreciate in real terms, thereby raising rural incomes and, thus, reducing rural poverty and income inequality. 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(2003). “Trade Openness and Economic Growth: A Cross-Country Empirical Investigation”, Journal of Development Economics, 72 (1), 57-89. 27 Figure A1: The First Cointegrating Relation Beta1'*Z1(t) 1.25 0.75 0.25 -0.25 -0.75 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 1993 1995 1997 1999 2001 2003 2005 Beta1'*R1(t) 1.00 0.75 0.50 0.25 0.00 -0.25 -0.50 -0.75 1975 1977 1979 1981 1983 1985 1987 1989 1991 Figure A2: The Second Cointegrating Relation Beta2'*Z1(t) 1.5 0.5 -0.5 -1.5 -2.5 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 1993 1995 1997 1999 2001 2003 2005 Beta2'*R1(t) 1.5 0.5 -0.5 -1.5 -2.5 1975 1977 1979 1981 1983 1985 1987 1989 1991 Figure A3: The Third Cointegrating Relation Beta3'*Z1(t) 0.3 0.2 0.1 0.0 -0.1 -0.2 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 1993 1995 1997 1999 2001 2003 2005 Beta3'*R1(t) 0.3 0.2 0.1 0.0 -0.1 -0.2 1975 1977 1979 1981 1983 1985 1987 1989 28 1991