Export Diversification and Financing of Industrialization of Sub-Sahara African Countries


Scientific Essay, 2020

26 Pages


Excerpt

Table of contents

Abstract

1 Introduction

2 Literature Review

3 Methodology

4 Research Results

5 Result discussion and conclusion

6 References

Abstract

The contraction of foreign direct invest inflows (FDI) obliges the Sub-Sahara African (SSA) countries to adopt a sustainable strategy of financing the diversification of its exports and the industrialization of its economy. Exports (EXP) is used as mediator variable and gross domestic product (GDP) is used as dependent variable. Net official development assistance received (DA), International Monetary Fund credit (IMFC), and FDI are tested as an independent variables. The purpose of this study is to investigate direct and indirect effect of FDI, DA, and IMFC to find the most influential in increasing EXP. The purpose of this study is to investigate direct and indirect effect of FDI, DA, and IMFC to find the most influential in increasing EXP. The analysis was performed using Baron and Kenny method, and bootstrap resampling procedure. To test the significance of indirect effect, Sobel test and value accounted for were used. The results of the analysis indicate EXP fully mediates the relationship between GDP and FDI, and GDP and IMFC. EXP carries a partial mediation in the relation between GDP and DA. IMFC was found to have higher direct and indirect effects than FDI and DA. This implies SSA countries could engage in contracting a long-term credit to promote exports diversification and industrialization by converting IMFC Programme assistance in credit at a preferential lending interest rate.

Key Words: Official development aids, Foreign direct investment, Export, Diversification, Sub-Sahara Africa, International Monetary Fund credit.

1 Introduction

The new coronavirus (COVID-19) will have social and economic impact in the world. Many persons died, all economic sectors like tourism, agriculture, manufacturing, and trade are negatively affected putting people’s jobs and livelihoods at risk. This may have dramatic impact on Africa in general. Economically speaking, developed countries may neglect Africa while focusing on their own problem. The money received by Africa under different form will imperatively decrease such foreign direct investment (FDI), development assistance, remittances, international credit, etc. This is the time for Africa to find new ways of financing its economic growth by defining clear objectives and ways to achieve them. The United Nations Conference on Trade and Development (2020) projected a bleak future regarding FDI flows in the world. Investment flows in Africa will decrease 25% to 40% in 2020, with investment flows for developing countries in Asia decreasing to 45% in 2020. It is therefore, essential for these countries to find adequate sustainable ways and means to ensure the financing of the necessary investments capable of boosting exports.

The economies of Sub-Sahara African (SSA) countries have since relied on foreign direct investment (FDI) to finance economic development. However, the evaluation of the level of development provided by FDI is not at all satisfactory; because more than half of the countries live into poverty. SSA is considered to have significant problems on the one hand, and great potential on the other. Poverty is pervasive with low human development, and with not inclusive growth. There is enormous infrastructure gap with the investment climate and regulatory environment relatively poor. Weaknesses in governance and institutional capacity are still observed (European Investment Bank, 2013).

SSA is considered as rich in the natural resource, but is not able to exploit efficiently the resources available (Interministerial Committee for International Cooperation and Development, 2008). The natural resources available in SSA would constitute a comparative advantage endowment (Charles, Scott & Lance, 2015). The Heckscher-Ohlin Samuelson (HOS) model of international trade, recommend that countries should specialize in producing those goods in which they have a comparative advantages (Kazuhiro & Naoki, 2016). Exports-oriented strategy is able to boost economic growth (United Nations, 2001). However, the SSA baking system is not able to finance the whole economic sectors in SSA. Various reports propose to SSA to make diversification of the exports, increasing industrialization. For instance Vera and Deborah (2012) found that export diversification of products and markets increased value added and labor productivity. Louis, Abena and Bernardin (2015) found that export diversification is positively and significantly effect on economic growth in SSA. Kwami (2019) concluded the manufacturing sector through its value added has a positive impact on economic growth in SSA countries. Eric, Isabel and Edem (n.d.) indicated industrialization has on its own boosted economic growth in Africa, while trade openness augmented the effect of industrialization on economic growth.

All those researches did not address the question related to how to finance exports diversification and industrialization in SSA. Additionally, in front the trend in reduction of FDI and banking system weaknesses in SSA, at the best of the author’s knowledge, there is no study that shows alternatives to financing exports and industrialization in SSA. No study has shown how increase in FDI leads to increasing exports (EXP), in return EXP increases gross domestic product (GDP), for instance. No study has analyzed how increase in development assistance (DA) or in credit from international banks can increase EXP, in return EXP increases gross domestic product (GDP), for instance.

The purpose of this study is to investigate direct and indirect effect of FDI, DA, and IMFC to find the most influential in increasing EXP. Specifically, the study aims to propose to SSA leaders a new way of financing exports diversification and industrialization. This paper aims to answer the following research questions:

R.Q. 1: To what extent exports mediate the relationship between foreign direct investment and gross domestic product?

R.Q.2. To what extent exports mediate the relationship between IMF credit and gross domestic product?

R.Q.3. To what extent exports mediate the relationship between net official development assistance received and gross domestic product?

2 Literature Review

The World Bank (2020) provides indicators and defines each indicator. The following variables are defined according to World Bank. Gross domestic product (GDP) (constant 2010 US$): GDP at purchaser's prices is the sum of gross value added by all resident producers in the economy plus any product taxes and reducing possible subsidies not included in the value of the products. It is calculated without reducing depreciation of produced assets or for depletion and degradation of natural resources. Foreign direct investment net inflows (current US$) (FDI): is the sum of equity capital, reinvestment of earnings, and other capital. Direct investment refers to a category of cross-border investment linked with a resident in one economy, having control or a significant degree of influence on the management of an enterprise that is resident in another economy. Having at least 10 percent of the ordinary shares of voting stock is the criterion for determining the existence of a direct investment relationship.

Exports of goods, and services (current US$) (EXP) is the value of all goods, and other market services provided to the rest of the world. They do not consider the value of merchandise, freight, insurance, transport, travel, royalties, license fees, and other services, such as communication, construction, financial, information, business, personal, and the government services. Compensation of employees and investment income and transfer payments are excluded. Net official development assistance received (current US$) (DA) refers to disbursements of loans made on concessional terms (net of repayments of principal) and grants by official agencies of the partners of the Development Assistance Committee (DAC), by multilateral institutions, and by non-DAC countries to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. It contains loans with a grant element of at least 25 percent with the rate of discount of 10 percent. Under the use of IMF credit (current US$), there are IMF trust fund operations under the enhanced structural adjustment facility, extended fund facility, poverty reduction and growth facility, and structural adjustment facility are presented together with all the IMF’s special facilities (buffer stock, supplemental reserve, compensatory and contingency facilities, oil facilities, and other facilities).

The dependence of sub-Saharan African countries on exports of raw materials with little added value, coupled to the fact that the price of those exports depends on fluctuations in world prices, dramatically weaken the economic health of these countries. The Interministerial Committee for International Cooperation and Development (CICID) (2008) indicated that SSA is considered to have a significant proportion of global reserves: 30 percent of bauxite, 60 percent of manganese, 75 percent of phosphates, 85 percent of platinum, 80 percent of chrome, 60 percent of cobalt, 30 percent of titanium, 75 percent of diamonds and nearly 40 percent of gold. Sub-Saharan Africa produces 7 percent of global oil production and known reserves are of a similar magnitude. The endowment of the SSA countries in abundant and diversified natural resources, combined with the existence of a young workforce should constitute a comparative advantage according to the theory factor endowment (Charles, Scott & Lance, 2015).

Export-oriented strategies have been recognized to be an engine for boosting economic growth. International publications and empirical results support the theory that exports contribute to the increase in economic growth. The report of the United Nations (2001) indicated that exports may promote economic growth by generating a greater capacity utilization; taking advantage of economies of scale; bringing about technological progress; creating employment and increasing labour productivity; improving allocation of scarce resources throughout the economy; relaxing the current account pressures for foreign capital goods by increasing the country’s external earnings and attracting foreign investment; and by increasing the well-being of the country. Ndambiri (2012) analyzed a panel data of 19 SSA from 1982 to 2000. Using Generalized Method of Moments (GMM) found a physical capital formation; a vibrant export sector and human capital formation contribute significantly to the economic growth among SSA countries. Pam (2016) indicated that a trade threshold existed below which greater trade openness had beneficial effects on economic growth, and above which the trade effect on growth declined.

The existing literature shows the incapacity of baking sector in SSA countries to provide credit to all borrowers to finance economic activity. The World Trade Organization (2016) indicated that significant gaps exist in credit provision, and many companies don’t have access the financial tools that they need. Moreover, without adequate trade finance, opportunities for growth and development are not exploited; businesses are deprived of the fuel they need to trade and expand. According to the European Investment Bank (2013), SSA’s financial and banking systems remain underdeveloped. The banking systems in the region are highly concentrated and generally inefficient at a financial intermediation; with small size and low intermediation, and despite little barriers to entry and exit, and limited competition. As consequence, access to finance in sub-Saharan Africa is among the lowest in the world, presenting one of the key obstacles to the activity, and growth of enterprises. This in turn constitutes a constraint to the region to achieve its full growth potential. According to the United Nations Conference on Trade and Development (UNCTAD) (2007), accessing to finance shall be considered as a critical catalyst of trade expansion and economic development, especially in developing countries. Many participants in dynamic industries as fisheries, renewable energy and electronics depend on credit to improve their operations and achieve sustainable livelihoods. Additionally, where credit is constrained or very dear, producers and other actors in the value chain are unable to meet a market demand, and integrate effectively into local, regional, and international supply chains leading to miss opportunities for growth, and chronic incapacity to increase participation in global trade. There is a need for SSA to find a new way of supporting its exports diversification and industrialization.

3 Methodology

The methodology used follows that one presented by Baron and Kenny (1986). The method is based on successive regression analysis, as indicated in the equation. The analysis, gives a better understanding of the relationship between the independent and dependent variables when the variables appear not to have a definite connection (Omokri, Agbedey and Nwajei, 2018). Moreover, two main methods are generally used in mediation analysis: Baron and Kenny method, and bootstrap resampling procedure. Marie and Jingjing (2016) explained the equation of statistical relationship in mediation analysis according to Barron and Kenny (1986) as follows:

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DV is the dependent variable; IV is the independent variable; M is the mediating variable and εl, l = 1, …, 3, are the error terms. Equation (1) shows the relationship between variable IV and DP ignoring the mediating variable M. The coefficient must be significant. Equation (2) shows the relationship between IV and the mediating variable M. The coefficient a must be significant. Equation (3) represents the relationship between IV and DV controlling for account the mediating variable M. The coefficient c in equation (1) represents the total effect, while the coefficient c ′ in equation (3) indicates the direct effect, and the product of coefficients ab is known as the indirect effect. As consequence, the total effect should be equal to the sum of the direct and indirect effects, that is, c = ab + c ′. There is mediation when c’ is less than c of the question 1.The calculation can be done without using specific package.

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Bootstrap method can be used, and it does not rely on the assumption of normality, and can fit for smaller sample sizes (Hadi, Abdullah & Sentosa, 2016). Omokri, Agbedey and Nwajei, (2018) added that bootstrap resampling procedure is more performing than Baron and Kenny method. The results from Baron and Kenny method and bootstrap method are not different. The study combines both methods. Baron and Kenny method allows getting coefficients a, b, ab and c, but does not shows to what degree indirect effect ab is significant. Bootstrap method shows indirect effect ab with the probability value.

The Sobel test was used to test the existence of significant of indirect effect. This test analyzes the hypothesis there is no statistical difference between the total effect of FDI/IMFC/DA on GDP and the direct effect after taking into account the potential influence of EXP. In other word, EXP does not significantly mediate the relationship between FDI/IMFC/DA and GDP. To confirm the result, variance accounted for (VAF) indicating the share of the indirect effect in the total effect will be calculated. If VAF is less than 20%, the indirect effect is insignificant; therefore, there is no mediation. If VAF is between 20% and 80%, there is partial mediation. A VAF value of greater than 80% implies full mediation (Hadi, Abdullah & Sentosa, 2016).

Collected data for SSA, are related to 2018. The data were retrieved in World Development Indicators 2018. All variables are expressed in US dollars. Central, normality and dispersion of collected data will be tested. R environment is used. Mediation, processR packages are used to analyze mediation. Regressions will be performed to get a coefficient of the mentioned equations. Multicollinearity is analyzed to detect high inter-correlations among the independent variables. Variance inflation factor (or VIF), that measures how much the variance of a regression coefficient is inflated due to multicollinearity in the model was analyzed with car package.

Countries included in the sample are 37: Burundi, Congo Democratic Republic, Central African Republic, Benin, Botswana, Burkina Faso, Cabo Verde, Cameroon, Chad, Comoros, Congo Republic, Cote d'Ivoire, Guinea, Eswatini, Ethiopia, Gabon, Gambia, Ghana, Guinea-Bissau, Kenya, Lesotho, Liberia, Madagascar, Mali, Mauritania, Mauritius, Mozambique, Nigeria, Niger, Rwanda, Senegal, Sierra Leone, South Africa, Togo, Uganda, Zambia, Zimbabwe.

4 Research Results

4.1. Descriptive statistics

Data are collected to investigate to what extent exports mediate the relationship between foreign direct investment and gross domestic product; to examine to what extent exports mediate the relationship between IMF credit and gross domestic product; and to identify to what extent exports mediate the relationship between net official development assistance received and gross domestic product. Before mediation analysis, the study begins by performing descriptive analysis.

4.1. Descriptive statistics

Table 1: Descriptive analysis

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The result of the statistical summary indicates a big difference between the mean and the median of the variables, with high standard variation. The analysis of the minimum value, and the maximum value shows a big difference in the country according to the variable considered. The skewness analysis shows there is no symmetry in the data, as the result of the test gives value greater than zero. This could indicate a lack of normal distribution in the data. Probality value of Jarque-Bera, Shapiro, and Kolmogorov-Smirnov normality test for GDP, FDI, DA, and IMFC are less than 0.05 indicating that data are not normally distributed. Consequently, there is a strong evidence to reject the null hypothesis that data are normally distributed. The lack of normality implies the use bootstrap which is nonparametric method, and does not care about normality.

4.2. Mediation Analysis

The mediation analysis consists of verifying the conditions of Baron and Kenny procedures. According to Pardo & Román (2013), there is mediation when following conditions are respected:

1) X and Y must be related, (total effect / coefficient C);
2) X and M must be related (coefficient a different to zero);
3) M and Y must be related once the effect of X is controlled, (coefficient b must be different to zero);
4) The relationship between X and Y must be significantly reduced when controlling the effect of M. (coefficient c’, must be smaller than coefficient c). If one of these conditions is not respected, there is no mediation. The significance level for the analysis is 5%.

Table 2: Mediation analysis of foreign direct investment (FDI)

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Table 3: Mediation analysis of IMF credit (IMFC)

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Details

Title
Export Diversification and Financing of Industrialization of Sub-Sahara African Countries
Author
Year
2020
Pages
26
Catalog Number
V903756
ISBN (eBook)
9783346199904
ISBN (Book)
9783346199911
Language
English
Tags
african, countries, diversification, export, financing, industrialization, sub-sahara
Quote paper
Antoine Niyungeko (Author), 2020, Export Diversification and Financing of Industrialization of Sub-Sahara African Countries, Munich, GRIN Verlag, https://www.grin.com/document/903756

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