Generally, natural resources among sub-Sahara African countries have been a subject of concern in Africa and across the world. As a means of capital accumulation in developing countries, natural resources have been considered as catalysts for economic growth. Almost all of the sub Saharan countries are developing countries, and natural resources are the main source of economic growth in these countries. This study assesses the evidence of resource curse in sub-Saharan African countries and the study uses secondary annual data. In order to realize the research purpose, resource dependence measured by the share of total export to GDP and resource rents were used, and identified its effect on real GDP. The paper focuses on answering these three questions: whether resource rents have retarded growth in SSA, which is the effect of dependence on natural resources and can resource curse exist in sub-Saharan African countries despite endowment in natural resources? The result showed that merchandized exports at current values, coefficient value of 0.14 and natural resource rents at current values, coefficient value of 0.08, are positively significant with real GDP. However, the lagged value of natural resource rents, coefficient value of ﹣0.06, is negatively significant with real GDP. It was found that there is no evidence of Dutch disease and rent seeking at current values, but it is evident at past values. It implies that there is no evidence of resource curse at the current period, however it was largely surfaced in the proceeding period. The non-inclusion of other SSA countries that are not endowed with natural resources made the study limited to few SSA countries. The study tends to support the notion that resource-rich SSA countries are better off in short-run than in long-run.
Natural resources among sub-Sahara African countries (SSA) have been a subject of concern in Africa and across the world. The question is whether natural resource translates to economic growth or not. Natural resources are believed to be catalyst for economic growth if manage appropriately. It serves as means for capital accumulation for developing countries to position their economy at the steady rate of growth. Although, there seems to be two different perspectives on natural resources and economic growth relationship. Some studies followed the Benign perspective that posited that natural resource would assist the developing countries to transit from the stage of underdevelopment to that of industrial “take-off”, as obtained in such countries as Britain, United States of America, Russia, and Australia (Baghebo, [
Although some studies argued that African showed resource curse based on the parameters that was investigated, others have contrary view of a blessing rather than a curse. Resource curse can be attributed to the high degree of ethnic fragmentation that is inherent in the continent. Collier and Gunning [
Some comparable evidence showed that some resource-endowed countries have robust economy as a result of endowment in natural resources, while some countries’ growth rate retard. About three decades ago, Indonesia and Nigeria were heavily dependent on oil revenue, and Nigeria had comparable higher per capita incomes than Indonesia. However, in recent times Indonesia’s per capita income is two times that of Nigeria’s. Nigeria’s per capita income in real value has shown a slow growth trend over the years unlike Indonesia (World Development Indicators, 2014). Although Indonesia is not among SSA countries, but it compared with Nigeria showed that another resource-rich country from a different region cannot be characterized with low growth rate in its per capita income. Both Central Africa Republic and Botswana are rich in diamonds. Botswana has had an average growth rate of 4.2 percent between 1981 and 2012, but Central Africa Republic has plunged into civil strife over control of its diamond and national wealth.
Despite having substantial natural resources that can spur economic development, many resource-rich countries in Sub-Saharan Africa (SSA) are faced with slow pace of economic growth and development. This is consequent on what have been referred to in the literature as a “resource cure” hypothesis (Sachs & Warner, [
There are numerous reasons that natural resource endowment has not translated into economic growth in SSA countries which also can be applicable to other regions in the world. Among them are: Dutch disease, rent seeking and patronage, non-implementation of capital and social projects and government non-productive spending. Importantly, these obstacles have been evident in different dimensions and with different faces in respective countries, regions and communities. Many reasons have been advanced for this negative relation that exist between resource endowment and economic growth but little emphasis whether it visible at current periods or at latter periods. Therefore, it is important to explain the relation between natural resource and economic growth by examining the dynamic nature of factors such as resource rents and dependence on export of natural resources.
The study therefore addresses whether resource rents has retard growth in SSA, what are the effect of dependence on natural resources and can resource curse exist in sub-Saharan African countries despite endowment in natural resources? In attempt to address these questions, the study attempt to examine the effect of resource export on economic growth in sub-Saharan African countries, identify the effect of resource rents on SSA economic growth and assess the evidence of resource curse in sub-Saharan African countries;
The scope of study concentrates on 12 resource-rich Sub-Saharan African Countries that data are available and covers the period of 1981 to 2013. We have Time (T) = 33, observations covering 12 countries (N) and total observations, n = 396 (that is, n = T multiply by N). A list of SSA countries is provided in Appendix 1.
Most economists believed that trade is generally seen as a fulcrum of growth and has been given much emphasis. In the 17th century, a group of merchants, government officials and philosophers who advocated on economic philosophy known as mercantilism started the notion that international trade brings economic growth and increases the welfare of a nation. It is believed that a nation to become powerful, it export is expected to be more than it import, where the resulting export surplus is used to purchase precious other valuables. Adam Smith propounded the classical theory of international trade based on his concept of absolute advantage idea. According to him, the true wealth of a nation are stock of human, man-made and natural resource rather than stock of precious metals, and he went further to argued that the wealth of a nation can be increased if the government would increase their volume of exports that give them absolute advantage. In addition, he showed the gains of trade that it is possible to make a nation better off without making another worse off (Debel, [
Comparative advantage model propounded by David Ricardo to replace the principle of absolute advantage, provided a strong basis for trade among countries. According to this model, a country will specialize in the production and exportation of commodity of which it has comparative advantage over other countries. That is the commodity that it can produce at the lowest relative cost. The principle of reciprocal demand developed by J.S. Mill and later developed by Edgeworth and Marshall explained both demand and supply conditions which determine the terms of trade and hence trade between countries. The factor endowment theory of Eli Hecksher & Berti Ohlin (H-O) of external trade posited that different relative proportions of countries have different endowments of factors of production later replaced the comparative advantage. Some countries have large amounts of capital (capital intensive) while others have little capital and much labour (labour intensive). This theory argued that each country has a comparative advantage in the commodity which uses the country’s abundant factor. Capital intensive countries should specialize in the production and export of capital-intensive goods while labour intensive countries should specialize in the production and export of labour-intensive commodities. This theory encouraged third world countries to focus on their labour and land intensive primary product exports. However, it was argued that by exchanging these primary products for manufactured goods of the developed countries, third world nations could realize enormous benefits obtained from trade with the richer nations [
The notion of natural resource leading to economic growth and development is a conventional perspective that existed before the late 80 s ( [
The poor performance of most resource-endowed countries in the 1980s experiencing low economic growth and development is hampered due to the ‘resource curse’ phenomenon [
The general argument is anchored on the fact that revenues from natural resources are very volatile, as they are driven by sharp and significant fluctuations in prices over relatively short periods of time [
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Many prominent researchers have supported the view that resource-poor countries have better economic growth and development indicators than resource-rich countries. [
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Carmignani and Chowdhury [
This study adopted the Benign perspective as the theoretical framework. As identified in the literature, this perspective has the view that natural resources had positive effect on economic growth [
The model employed in this study is multiple regression panel data models. Presenting a Long-run output growth functional relationship:
where GDP is real Gross Domestic Product (GDP), mex is Merchandized Export, nrr is Natural resource rents and f is functional notation. For the purpose of statistical test, the log linear representation of (12) a is thus:
where lngdpit is the natural log of real GDP per capita over period t in generic country i, lnmexit is the natural log of Merchandized Export per capita, Innrrit is the natural log of Natural resource rents per capita over the cross countries and time periods. With
If the variables are cointegrated, then the error term is I(0) for all i. The ARDL (1,1,1) dynamic panel specification of (3.2) of the study is
The error correction reparameterization of (3.3) is
where
The error-correction speed of adjustment parameter,
The study employed Autoregressive Distributed Lag (ARDL) Dynamic Panel Data (DPD) model for their estimations. The dynamic fixed effects (FE) estimation approach is used in which the time-series data for each group are pooled and only the intercepts are allowed to differ across groups. The traditional dynamic fixed effect using stata command, xtreg, is be used to estimate the autoregressive distributed lag (ADRL) dynamic panel data model (Blackburne & Frank, [
It is important to make sure that there is no mixture of I(0), I(1) and I(2) variables so that we make sensible interpretation of the long-run relationships. Therefore panel unit roots tests is of very importance
The implication of these results suggest that co-integration test must be carried out to ascertained whether there is long-run relationship that exist between the dependent variable (real GDP per capita) and the independent variables (natural resource rents per capita and total merchandized exports per capita). Also, Error Correction Model to return to long-run equilibrium which corrects the error associated in short-run across countries.
The co-integration test result reported in
Variables | IPS Test | Remark | |
---|---|---|---|
I(0) | I(1) | ||
Real GDP per capita | −0.6031 | −4.514*** | stationary at first difference |
Natural Resource Rents per capita | −0.9099 | −5.180*** | stationary at first difference |
Total Merchandized Exportsper capita | −1.0524 | −5.826*** | stationary at first difference |
Source: Author’s calculation, 2015. Note: significant at *10%, **5% and ***1% levels for all statistics. Critical value for IPS unit root tests for 10%, 5% and 1% respectively are, −1.810, −1.900 and −2.040.
statistics of which 6 is adopted and the Kao residual based co-integration test.
In the results in
The Hausman test is consistent and efficient for Fixed and inconsistent for Random Effect. This invariable suggest that fixed effect estimator is consistent and preferred in ADRL Dynamic Panel Data long-run estimation. The advantage of fixed effect over random effect can be as a result of the correlation between the unobserved heterogeneity of individual SSA countries captured by the error term, μi and the explanatory variables. Fixed effect estimator corrects the serial correlation in the models, when E(Xjit vi) ≠ 0.
From the results estimated in
The results implied that a positive change in mex at current time, real GDP will respond proportionally by 14%, while a proportional increase in nrr will increase real GDP by 8%. On the basis of regressing current values
Statistic | Value | Significance level |
---|---|---|
Panel rho | −1.757** | 5% |
Panel PP | −7.328*** | 1% |
Panel ADF | −7.209*** | 1% |
Group rho | −0.480 | Not significant |
Group PP | −8.714*** | 1% |
Group ADF | −8.027*** | 1% |
Kao | 1.97** | 5% |
Source: Author’s calculation, 2015.
Log of real GDP as dependent variable | Coefficient | Standard Error |
---|---|---|
Constant | 0.957*** | 0.182 |
Log of merchandised exports per capita | 0.139*** | 0.018 |
Log of natural resource rents per capita | 0.081*** | 0.015 |
Log of lagged value of natural resource rents per capita | −0.060*** | 0 .015 |
Log of lagged value of merchandised exports per capita | 0.002 | 0.020 |
log of lagged value of real GDP per capita) | 0.740*** | 0.036 |
R2 = 0.93; F-statistics = 270*** |
Source: Author’s calculation, 2015. Significant at *10%, **5% and ***1% levels for all statistics; standard error in parenthesis.
of natural resource rents on the current value of real GDP, the assertion of resource curse by [
The dynamic factor of all models showed a positive relationship with real GDP and significant at 5% level. The inclusion of lagged of log of real GDP per capita into the models is to account for the dynamism of the model. That is, how the dependent variable are been affected by its past values. The coefficients of lagged value of real GDP, 0.74, indicated 74% proportional increase response by real GDP when it’s previous values rise. This suggests that past aggregate output level has a big positive impact on the current aggregate output.
Acknowledging the non-stationary of the variables at their lag specifications, and their stationarity at first difference and establishing panel co-integration in all models, the Panel Error Correction Model (PECM) can be estimated. As identified earlier, the purpose of the PECM is to correct the error associated in short-run across countries. The coefficients of lagged value of errors must be negative to cause a return to long-run equilibrium.
The PECM estimate is of great importance because it shows the short-run relationships of variables. The coefficients of the error term have negative slopes and are significant at 1% level. This suggests that the error associated in short-run across countries has been corrected, and there is a return to long-run equilibrium (
The PECM results showed that all the independent variables are significant though with different signs. The negative slope of the lagged value of natural resource rents an evidence of resource curse on past value in the short-run. However, at current values of both merchandised exports and natural resource rents, they are positively related to real GDP in short-run.
It was empirically found that in the long-run relationship, the evidence of resource curse could not be established when economic growth depends on the current values of merchandized export and natural resource rents. However, the inclusion of lagged values of natural resource rents established the evidence of resource curse. These findings showed that in the absence of strong socio-political institutions and good policy-driven economic growth, the once-a-blessing resource will later become a curse. The only SSA country exception that has been able to solve substantial macroeconomic problems associated resource is Botswana. For five decades, Botswana has had virtually uninterrupted rapid growth which has lifted them from one of the world’s most impoverished
Δ (lgdpit) | Coefficient | Standard Error |
---|---|---|
Constant | 0.019** | 0.009 |
Δ (log of merchandised exports per capita) | 0.051*** | 0.013 |
Δ (log of natural resource rents per capita) | 0.058*** | 0.011 |
Δ (log of lagged value of natural resource rents per capita) | −0.038*** | 0.011 |
Δ (log of lagged value of merchandised exports per capita) | 0.027** | 0.014 |
Δ (log of lagged value of real GDP per capita) | 0.267*** | 0.071 |
Error correction term at lag 1 | −0.189*** | 0.055 |
R2 = 0.1811 | ||
F-statistics = 11.39*** |
Source: Author’s calculation. Notes: Δ (real GDP) is dependent variable. Significant at *10%, **5% and ***1% levels for all statistics; standard error in parenthesis.
countries into the ranks of the upper-middle-income nations. This has accredited to their ability to formulate policy and prudently managing its mineral wealth that enable them to avoid the resource curse (Lundgren, Alun and York [
The following recommendations are suggested.
1) Resource endowed SSA countries should utilized all available natural resources and propel to growth through diversification of their economy where agriculture, agro-allied industries and the entire manufacturing sector would continue to contribute to their economy.
2) Resource endowed SSA countries should formulate policy that will in turn accelerate the economic growth and good management of natural resources in SSA countries.
3) Resource-endowed SSA countries’ agenda should be to drive their macroeconomic policy towards a supporting sustained and broad-based development.
4) On the other hand, resource endowed SSA countries’ policymakers should address managing natural resource wealth on how much of the resource wealth to consume now and how much to consume later to place them on balanced growth path. Botswana has earned a reputation for good governance and prudent macroeconomic policies. They pursued ‘inclusive institutions’ policy which has helped them drive economic performance over the last decades.
5) The volatility of resource prices should make resource endowed SSA countries’ government cautious when choosing between investments in physical or financial assets because physical assets cannot be liquidified immediately to address sudden drops in resource revenue.
6) Establishing institutional mechanisms or policy to reduce the adverse effects of volatile prices is therefore essential.
Daniel Chibueze Onyejiuwa, (2016) Resource Rents and Dependence in Sub-Saharan African Countries Economies. Open Access Library Journal,03,1-11. doi: 10.4236/oalib.1102378
The below table shows the Sub-Sahara African Countries selected for this study, and their basis of selection depends availability of data for all variables.
Sub-Saharan African Countries Resource Dependence Ratio
Source: Author’s compilation. Note: *the value is calculated as the ratio of resource export to total export with data source, World Development Indicators, 2014.
HAUSMAN TEST
b = consistent under Ho and Ha; obtained from xtreg B = inconsistent under Ha, efficient under Ho; obtained from xtreg Test: Ho: difference in coefficients not systematic chi2(5) = (b-B)’[(V_b-V_B)^(-1)](b-B) = 47.78 Prob > chi2 = 0.0000