This article aims to investigate the explanatory factors of FDI attractiveness in the Economic Community of West African States (ECOWAS) through panel data modelling and estimation over the period 1985-2015. The findings show that stabilization of the macroeconomic environment, government consumption expenditures, domestic credit to the private sector, interest rate, gross fixed capital formation, exchange rate, economic freedom index, as well as natural resources and market size are the main FDI driving factors in ECOWAS.
The ability to attract foreign direct investment (FDI) is considered a major component of development policy. Due to insufficient available resources to finance long-term development of Africa and the growing difficulty in poverty reduction, new economic strategies at national, regional and international levels are now putting more emphasis on FDIs.
The experience of a small number of newly industrialized economies (NIEs) of East Asia experiencing rapid growth and, more recently China, helped to support the idea that FDIs have played an essential role to address the lack of resources in low-income countries and avoid an increase in debt while directly addressing the causes of poverty.
According to the United Nations Conference on Trade and Development [
The objective of this article is to determine the factors explaining the attraction of FDIs in the Economic Community of West African States (ECOWAS). To this end, the paper presents recent developments in terms of FDIs in ECOWAS member countries and FDI attractiveness policy in the region before turning in the literature review, to theoretical and empirical foundations of the analysis of FDI flows. Section 4 presents the model and model specifications, followed by estimation results. The last section deals with policy recommendations related to FDI inflows and concludes.
According to the Balance of Payments and International Investment Position Manual (BPM6) of the International Monetary Fund (IMF) [
Another aspect often considered to qualify a transfer of FDI capital is the share of participation in the company’s capital. Thus, the Organization for Economic Cooperation and Development (OECD) proposes to consider as direct investment when the share of capital held by foreign investor is at least 10% of the capital of the resident enterprise. Therefore, any investment whose amount is below this threshold has to be classified in another type called portfolio investment.
The World Bank defines foreign direct investment as: “Foreign direct investment are the net inflows of investment to acquire a lasting management interest (10 percent or more of voting stock) in an enterprise operating in an economy other than that of the investor. It is the sum of equity capital, reinvestment of earnings, other long-term capital, and short-term capital as shown in the balance of payments.” [
FDIs include mainly two types of operations. On the one hand, there are operations made from internal growth within the same transnational company between the parent company and its various institutions established abroad (subsidiaries, representative offices, etc.); ex nihilo creation of new units, expansion of production capacity of existing units, financial flows between institutions (increase in capital, loans and cash advances by the parent, etc.), local reinvestment of profits.
On the other hand, there are those made through acquisitions, provided they attain at least 10% of the coveted foreign company’s capital. Nowadays, this threshold is internationally recognized to distinguish FDI from “portfolio investment”, the latter being by definition much more volatile and corresponding to participation less than 10% of a company’s capital. In this case, the investment is considered by the company as a form of international portfolio diversification [
FDI inflows to Africa have been rising during the recent years. However, economic growth remains slow compared with other developing regions, and Africa receives only 5% of total FDI inflows to developing countries. However, the amounts involved are much higher than the average level during the first half of the 1990s.
Furthermore, the situation varies considerably from one country to another, because investors are beginning to realize the potential of many African countries. The main FDI recipients in Africa are Nigeria, Egypt, South Africa, Angola, Equatorial Guinea, etc. Countries, such as Ethiopia, Mozambique and Uganda also show their capacity to attract FDIs which are mainly directed towards the manufacturing sector and services.
To explain why some countries receive more FDIs than others, it is essential to understand the factors which influence the choice of transnational companies to invest abroad.
Three major types of factors are involved here: recipient country policies (including applicable regulation to FDIs), measures adopted by countries to encourage and facilitate investments and finally general economic characteristics.
Being made up of countries with very different characteristics, most of which are poor and heavily indebted, with weak domestic savings in an international development financing context which is increasingly selective, ECOWAS member countries adopted a strategy of attracting foreign capital and particularly FDI.
Faced with the challenges of the third millennium, economic and social development of ECOWAS member countries should rely more on accelerating the ongoing integration process, including through the effective implementation of sectoral policies, thus completing the achievement of the Customs Union and the convergence of economic policies.
FDI inflows could help ECOWAS member countries to better realize their new development strategy which attaches great importance to private investment, especially FDI.
If developing countries want to have the greatest possible attractiveness to transnational corporations, it is because they want to make the most profit from FDIs, that is to say, to maximize their positive contribution to development and minimize their negative effects. As well as development, transnational corporation experience the consequences of the growing importance of intensive-knowledge production, rapid technological change, contraction of economic activities and increasingly openness of the countries.
For example, today most of the developing countries consider FDI as an important factor of development. Public policy has a role to play, but the instruments of government policy had evolved to adapt to the new situation, without the fact that governments must review their objectives to meet new needs.
Regarding transnational corporations, the new situation is reflected both by new opportunities as well as new constraints. They developed rapidly, their number has increased sharply and they have changed their strategies, which not only had an influence on the determinants of their investments abroad but also changed the way their activities affect the economies of recipient countries.
Traditionally, the contribution and the expected impact of transnational corporations was to supplement domestic savings by foreign savings, and thus to increase supply of usable financial resources for development. Today, as many developing countries have liberalized access to financial markets and various other modes of funding, governments compare the contribution of FDIs and other financial flows to development.
Since the development capacity of a country depends increasingly on its ability to cope with technological change and to be integrated into the global economy, technology development, acquisition of management skills and techniques and export competitiveness have become for developing countries much more important.
Meanwhile, the countries pledged to carry out sustainable development, protect the environment and ensure the sustainability of resources for future generations. Transnational corporations are well placed to contribute to development because they play a key role in these areas.
In fact, since FDIs cover a range of assets they can have an impact which is more sensitive than their various components taken individually, and contribute to the restructuration of entire sectors or even to strengthen the competitiveness of the whole economy. They can also have negative consequences for developing countries, i.e. oust local investors or cancel some of their advantages through transfer pricing.
Given the fact that developing countries are looking increasingly not only to attract FDIs but also to benefit from them, many authors have dedicated their work to the extent to which FDIs can contribute to the various key sectors of economic development and on the question relative to how to ensure that this contribution be even more strengthened.
From the perspective of the recipient countries, FDIs are a catalyst for economic development, particularly through their contribution to the increase in private investment, job creation, growth in domestic supply, deepening technology transfer, training and improving human capital and increase the productivity of enterprise production factors. FDI development also entails greater integration of countries in international trade and should have the effect of facilitating access of developing countries to international markets [
There is in the literature a concept of technology transfert through the multinational firms, according to which technology of the subsidiary would spread to local companies through positive externalities (or “spillovers” in the terminology [
Macdougall [
Caves [
The first studies were conducted by Caves who studies the manufacturing sector in Australia, by Globerman [
However, there are studies showing that external effects are not significant. This is the case of Haddad and Harrison [
Furthermore, the endogenous growth theory considers FDIs as a key enabler in the process of economic development thanks to the positive externalities they generate in the recipient economy. The impact of FDIs on economic growth could result mainly in their direct effects on private capital stock, stimulating local investment in complementary activities of multinational firms [
In recent works, the analysis of the determinants of private capital flows is usually done by distinguishing between internal factors that can be influenced by the recipient economy “pull factors”, external factors associated with economic conditions in the source countries, which are beyond the control of recipient economies “push factors”.
Despite the growing importance of investment flows, there is no unified theoretical framework for understanding FDI determinants.
Traditional theories of international trade highlight the differences in factor endowments to explain trade and factor mobility and in particular the relocation of firms [
However, these theories are in a context of perfect competition very restrictive to the extent that the majority of multinational firms operate in markets with imperfect competition. Because of this market imperfection firms may have specific advantages and are encouraged to take the risk of investing abroad.
Vernon [
Kindleberger [
The international trade theories developed in the 1990s, including those of Brainard [
The benefits of localization constitute a necessary and sufficient condition for FDIs. In this regard, Dunning [
A comprehensive approach to these explanatory factors of FDIs was attempted by Dunning [
Venables et al. [
Smith [
While relocation or vertical FDIs occur when firms are part of a perspective of international division of production process, multinational corporations spread their activities across countries depending on the different comparative advantages (different countries in size and factor endowments, low workforce costs) [
Also, Agnieszka and Young [
Asiedu [
The literature on FDI identifies a number of intrinsic factors that make a country a preferred destination or not for FDIs (Theory of “pull-factor”). These conditions include the quality of socio-economic infrastructure, market size, level of human capital development, distance between the country and key international markets, labor cost, openness to international trade, foreign exchange policy, fiscal and non-fiscal incentives, political stability, monetary policy and degree of financial liberalization [
In addition to these socio-economic variables, Akinkube [
In addition to the intrinsic characteristics of recipient economies, there are also external factors (“push factors”) that affect FDI inflows through different channels. These factors explain to what extent the economic conditions of the country of origin influence the direction of capital flows to developing countries. These include the growth rate of developed countries and interest rates.
According to Reinhart [
The change in international interest rates also has an impact on the financing of FDI flows. A study by the World Bank found that over the period 2003-2007, the low level of international interest rate and the subsequent decline in borrowing costs contributed to over 70% increase in capital inflows to developing countries [
In the empirical analysis, we focus on some studies on FDI determinants from the perspective of the recipient country, particularly in developing countries. Various empirical studies have considered a wide range of variables (qualitative and quantitative) that influence FDI. Some papers have put emphasis on economic and financial factors [
In his study on the determinants of FDI in Africa, Morisset [
Asiedu rejects the role of economic openness on FDI inflows to African countries, considering that African trade reforms would be deemed not credible by foreign investors. The author also shows that some factors, traditionally accepted as relevant determinants of FDI are not validated in the case of African economies, namely the return on capital and infrastructure development.
In the same vein, Kamaly [
For Morisset improvement of the business climate through aggressive trade liberalization can fuel the interest of foreign investors to a particular country. Although for many observers, the ability of African countries to attract FDI has mainly depended on their natural resources endowment and the size of their markets, the implementation by a number of countries (Singapore, Ireland) of proactive policies may be an indication of the improvement the attractiveness of the country.
Many studies, including those of Tsai [
Among factors considered logically meaningful in researches, market size is unanimously accepted as an important factor in attracting FDIs. The theory, especially important for FDIs, motivated by the recipient country market, argues that a country with a larger market will have a greater capacity to absorb production due to FDI inflows and thus be more attractive to potential investments.
Dupuch and Milan [
Several empirical studies have shown the existence of a positive relationship between FDIs and growth, if recipient countries have favorable initial conditions, including a minimum level of economic development or the existence of local capacity for wealth creation including a sufficiently high level of education.
Borensztein, De Gregorio and Lee, Bengoa and Sanchez-Robles [
By studying three regional economic groups in North and Central America, Blomstrom and Kokko [
Other studies including Hess [
Thus, Singh and Jun find that political risk is an important determinant for countries that attracted the largest amount of FDI inflows. For others that have attracted less, socio-political instability (approximated by the number of working days lost) had a negative impact on investments. Similarly, Kamaly finding a positive impact of democracy on FDI, concludes that democratic countries have an effective advantage over autocracies about the relative attractiveness to FDI.
Analyzing the data from the survey conducted in the Southern African Development Community (SADC) member countries, Hess identifies five main obstacles to FDI, common to these countries: the unstable political and economic environment, inefficient administration, corruption, lack of transparency and the high tax burden. Ngowi concludes that the lack of attractiveness of African countries is explained by their lack of political and institutional stability and predictability.
However, Noukpo and Fotie [
Political stability is often seen as a factor favorable to FDI in the world. But this is not always true with investments in the extractive industry [
Infrastructure is also an important factor in the investment decision of firms abroad. Guisinger cited by Groh and Wich [
Al Nasser [
Basu and Srinivasan [
Koukpo [
DJE [
This study makes use of the following variables:
ü Government expenditures are often expenditures of general interest to improve the social conditions of the country. They may be expenditures relative to infrastructure construction.
ü GDP per capita and household consumption which are indicators often used as proxies for material well-being.
ü GDP growth rate reflects the country’s wealth creation dynamic and tells whether the economy is doing well or not. It is also a macroeconomic indicator that allows, among others, to compare and possibly to choose between a set of countries for an investment decision. It is expected to have a positive impact on FDI flows into a country or a given zone.
ü Exchange rate has an impact on imports and exports of a given country. Investors wishing to export their products may find this rate incompatible with their investment choices.
ü Gross fixed capital formation refers to the acquisition or stock of durable production goods. It is a proxy for investment. It can have a positive impact on FDI flows.
ü Domestic credit to the private sector allows an investor to have an idea of the local financing capacity, and this can be a source of funds to the investor in the case of need. Thus, it is normal that the domestic credit impact positively FDI flows in a given country.
ü Debt and debt service, the amount of that debt, which is often public may influence the choice of FDI, by the fact that face to a situation of payment obligation, there could be a reduction in investment, especially public investment.
ü Degree of openness, economies that are most open are assumed to have a better chance of capturing FDI inflows.
ü Gross primary school enrollment, and gross secondary school enrollment: these are
variables taken as proxies of human capital. In addition to cheap labor, investors look for a more skilled population because it fits more to the new technologies and has more innovative capacity.
ü Economic Freedom Index2: these two variables reflect the global ranking of countries in terms of political rights and freedom to undertake economic and political actions, they can be taken as proxies of good governance.
ü Nominal and real interest rates.
ü Rents from natural resources are the sum of oil rents, natural gas rents, coal rents (hard and soft), mineral rents, and forest rents.
ü Primary energy production3: includes the production of a set of resources such as oil, natural gas, coal, biofuels, etc. necessary for energy production. This variable can be considered a proxy of the natural resources of the country because some resources that go into the composition of this aggregate such as plants for the production of nuclear energy, does not exist in ECOWAS member countries. Thus, this variable could be composed primarily of natural resources for these countries.
ü The population due to the size of the market which is an important element of attractiveness for FDIs.
It is assumed that FDI inflows are explained by a set of variables X that are taken in two dimensions, temporal and individual, Xit with i for the individual dimension and t the time. The relationship is written as:
With Xk the set of explanatory variables measured on individuals at different dates, the exponent k refers to the kth variable, μi refers to the individual effects, and
The explanatory variables are lagged and this is justified by the fact that to invest in a country in a given year, investors will analyze the macroeconomic behavior of various indicators in the earlier periods. This choice also has the advantage of avoiding bi-di- rectional impact between FDI inflows and the explanatory variables when they are taken in the same year that can create a simultaneity bias in the estimations.
Two data sources were used in this study. The first is collected from the World Bank [
The analysis of stationarity is a necessary step in any econometric modelling using time series in order to avoid a spurious regression. Regarding panel data, the stationarity test used is Levin Lin and Chu test. It is the extension of the presence of unit root test proposed by Dickey and Fuller for time series. The test is based on the existence or not of a deterministic trend for a given series under the assumption of the presence of unit root.
In Appendix 1, for each variable two tests were conducted (one with trend and one without trend) using the Levin Lin and Chutest. These tests are performed on the lagged variables (all variables in
Levin Lin and Chu Unit root test: 5% significance level | |||||
---|---|---|---|---|---|
With trend | Without trend | Order of intégration | |||
Variables | Yes/No4 | P-value | Yes/No | P-value | |
ConsGouv | Yes | 0.9940 | Yes | 1.0000 | I(1) |
PIB_habitant | Yes | 0.3729 | Yes | 1.0000 | I(1) |
Taux_change | Yes | 0.4020 | Yes | 0.9636 | I(1) |
FBCF | Yes | 0.3788 | Yes | 1.0000 | I(1) |
CreditauPrive | Yes | 1.0000 | Yes | 1.0000 | I(1) |
Croissance_PIB | No | 0.0000 | No | 0.0000 | I(0) |
Dette | Yes | 0.4245 | Yes | 0.9742 | I(1) |
Inflation | No | 0.0000 | No | 0.0000 | I(0) |
Termes_Echange | No | 0.0001 | No | 0.0172 | I(0) |
Service_Dette | Yes | 0.0909 | Yes | 0.0957 | I(1) |
Degre_Ouverture | Yes | 1.0000 | Yes | 1.0000 | I(2) |
TbsPrimaire | Yes | 0.5957 | Yes | 0.2992 | I(1) |
TbsSecondaire | Yes | 0.2007 | Yes | 1.0000 | I(1) |
FDI | No | 0.0017 | No | 0.0241 | I(0) |
IndiceLibrEco | No | 0.0342 | Yes | 0.9272 | I(0) |
TauxInteret | No | 0.0000 | No | 0.0001 | I(0) |
TauxIntereReel | No | 0.0000 | No | 0.0000 | I(0) |
ResourcesRents | No | 0.0057 | No | 0.0478 | I(0) |
PrEnergiePrimair | Yes | 1.0000 | Yes | 0.8801 | I(1) |
Population | No | 0.0000 | Yes | 1.0000 | I(0) |
ConsMen | No | 0.9983 | Yes | 1.0000 | I(1) |
Source: Author’s computation.
their original names). For example, the variable government consumption expenditure (ConsGouv) was lagged of one year (renamed LConsGouvin the appendix).
The first two boxes of the table correspond to the Levin Lin and Chu test with trend and without trend on the lagged variable LConsGouv.
These results are summarized in
Then we made stationary the variables that were not. The order of integration for each variable is presented in the last column of
For the modeling, the lagged variables are used as regressors. The reasons that the variables are being lagged are exposed in Part 2 which is relative to the specification of
YEAR | 2000 | 2010 | 2015 | |||
---|---|---|---|---|---|---|
West Africa | 32,864 | % | 92,384 | % | 152,075 | % |
Benin | 213 | 0.65% | 604 | 0.65% | 1666 | 1.10% |
Burkina Faso | 28 | 0.09% | 354 | 0.38% | 1682 | 1.11% |
Cape Verde | 192 | 0.58% | 1252 | 1.36% | 1486 | 0.98% |
Côte d'Ivoire | 2483 | 7.56% | 6978 | 7.55% | 7318 | 4.81% |
The Gambia | 216 | 0.66% | 323 | 0.35% | 350 | 0.23% |
Ghana | 1554 | 4.73% | 10,080 | 10.91% | 26,397 | 17.36% |
Guinea | 263 | 0.80% | 486 | 0.53% | 2171 | 1.43% |
Guinea-Bissau | 38 | 0.12% | 63 | 0.07% | 134 | 0.09% |
Liberia | 3247 | 9.88% | 4956 | 5.36% | 7056 | 4.64% |
Mali | 132 | 0.40% | 1964 | 2.13% | 2893 | 1.90% |
Niger | 45 | 0.14% | 2251 | 2.44% | 5161 | 3.39% |
Nigeria | 23,786 | 72.38% | 60,327 | 65.30% | 89,735 | 59.01% |
Senegal | 295 | 0.90% | 1699 | 1.84% | 2808 | 1.85% |
Sierra Leone | 284 | 0.86% | 482 | 0.52% | 1848 | 1.22% |
Togo | 87 | 0.26% | 565 | 0.61% | 1367 | 0.90% |
TOTAL (en %) | 100.00% | 100.00% | 100.00% |
Source: UNCTAD, World Investment report, 2016 and author’s computation.
the econometric model.
Both tests allow us to see what estimation method should be adopted for estimating the parameters of our model.
Specification tests for deciding whether to estimate the theoretical model by assuming that the coefficients are identical for all countries in the sample or, conversely, the equation must be estimated for each individual country. Three tests are to be performed.
The first line of the table shows the results of testing the hypothesis of a perfectly homogeneous structure (pooled model), that is to say the constants and coefficients of the variables are the same for all countries. It shows that this hypothesis is rejected with a p-value well below 5%. It is therefore concluded that there is heterogeneity from either coefficients or constants. So we run the second test to see whether the heterogeneity can be attributed to the coefficients associated to the variables of the model. From this test, it emerges that the null hypothesis of homogeneity of coefficients is accepted
Tests for the presence of individual effects at 5% significance level | ||
---|---|---|
Null hypothesis | Statistic | P-value |
4.5790 | 2.182e−18 | |
1.3016 | 0.0502 | |
55.45339 | 2.879e−83 |
Source: Author’s computation.
by comparing the p-value at 5%. It appears therefore to perform on the constants a third test to confirm or refute the findings made in the first test. The results confirm the findings of the first test and show the heterogeneity from the constants at the 5% level. Therefore, there are individual effects to be taken into account in estimating the model.
The test is to see if we are in the presence of fixed effects or random effects. This is actually to test the presence of a possible correlation between the individual effects and the explanatory variables (
The test rejects the existence of a correlation between the individual effects and the explanatory variables at the 5% level. Thus the model to be estimated is with random effects (Appendix 2).
These tests relate to the assumptions made about the residuals of the model with random effects and are used to learn about their veracity.
These tests are relative to two homoscedasticity tests; the first being Breush and Pagan test for testing the hypothesis of global homoscedasticity of the model, that is to say, the variance of the error term is the same for all countries, regardless the date. The second test relative to the specificity of panels (inter-individual heteroscedasticity test) is then to perform when there is heteroscedasticity.
By performing both tests, we note that there is the presence of heteroscedasticity (Appendix 3 and Appendix 4). It is therefore appropriate to correct it.
The tests to be performed at this stage are inter-individual autocorrelation test and intra-individual autocorrelation test. The test results show that there is only the presence of an intra-individual autocorrelation (Appendix 5). A correction of this autocorrelation is necessary.
Hausman test: fixed effects versus random effect at 5% | ||
---|---|---|
Null hypothesis | Statistic | P-value |
Random effects | chi2 = 51.56 | Prob > chi2 = 0.0000 |
Source: Author’s computation.
FDI | Coefficients | z | P > |z| |
---|---|---|---|
ConsGouv | 0.0243368 | 0.02 | 0.986 |
ConsMen | 1.647798 | 1.67 | 0.096 |
PIB_habitant | 1.18e+07 | 3.01 | 0.003 |
CreditauPrive | 0.0105764 | 5.22 | 0.000 |
Dette | 0.5367067 | 0.67 | 0.502 |
Taux_change | 3785462 | 1.02 | 0.306 |
FBCF | 1.325459 | 0.72 | 0.474 |
Termes_Echange | −2.49e+07 | −3.01 | 0.003 |
Service_Dette | −7.828796 | −0.84 | 0.399 |
Degre_Ouverture | −8,179,375 | −1.66 | 0.096 |
Croissance_PIB | 6.03e+09 | 2.44 | 0.015 |
TbsSecondaire | −4.43e+07 | −1.16 | 0.245 |
TbsPrimaire | 3.04e+07 | 1.39 | 0.164 |
Indicedelibertconomique | 1.29e+08 | 4.92 | 0.000 |
TauxInteretReel | 9,056,738 | 1.60 | 0.110 |
TauxInteret | −1.37e+08 | −2.95 | 0.003 |
InflationAnnuelle | 1.10e+07 | 1.02 | 0.308 |
ResourcesRents | −2.64e+07 | −0.68 | 0.495 |
PrEnergiePrimair | 0.000083 | 5.35 | 0.000 |
Population | 1308.806 | 8.79 | 0.000 |
Source: Author’s computation.
5% level are GDP per capita, domestic credit to the private sector, growth rate, interest rate, terms of trade, primary energy production considered here as natural resources (refer to IV.1), population and finally economic freedom index, and their coefficients have the expected signs. The coefficients of the variables cannot be directly compared to comment on the magnitude of the impact of a variable on FDI inflows in relation to another variable. This is justified by the fact that all the variables are not in the same order of magnitude, for e.g. household consumption expenditures and growth rate.
Growth rate positively affects FDI inflows to the countries. Growth rate is one of the macroeconomic indicators to understand the dynamics of the economy. A sustained increase in economic growth for a country may reflect an economy that is doing well and so this may encourage foreign investors.
The domestic credit to the private sector positively impacts FDI inflows. However it should be noted that the magnitude of the impact is relatively low (0.01). Domestic credit amount is often determined by domestic saving which is often low, this could justify this magnitude.
GDP per capita and population have a positive impact on FDI inflows (1.18e+07 and 1308.806, respectively). They can be seen as variables representing market size and capacity of the recipient countries to face the supply of new goods. Thus investors will have a higher propensity to choose a country with a high population or a population with high living standards for their activities. Another variable relative to the market which positively influences FDI inflows but at the 10% level of significance is household consumption which corresponds, in any way, to demand. We note that an increase in interest rates leads to a decrease in FDI inflows. Interest rate being part of indicators to assess the financial situation of a country, its increase discourages investment decisions as it increases the cost of borrowing.
Primary energy production seen as a proxy of natural resources affects positively FDI inflows. This may be a production cost minimization strategy in approaching primary resources needed for production.
Economic Freedom Index whose maximal value is 1000 is a criterion which impacts significantly FDI inflows. The freedom to undertake economic activities could be among the necessary conditions for a country to attract FDI.
The coefficient associated with the terms of trade has a negative sign and therefore, here, the influence of this variable on FDI inflows is unexpected.
This study allows identifying the determinants of FDI inflows to ECOWAS member countries and measuring their relative importance. Using panel data, the article shows that FDI attractiveness is a major asset for ECOWAS member countries.
We found that among the identified factors, stabilization of the macroeconomic environment, natural resources endowment, and market size were the most determinants. Exchange rate and the index of economic freedom have a relatively small impact compared to these three factors.
Given these results, the ECOWAS member countries could strengthen, through the implementation of various economic policies, their position in international capital flows. The attractiveness policies of the ECOWAS countries should be based on these main factors.
For the macroeconomic environment, West African governments should continue to reduce the gap between best practices in many major dimensions of ease of doing business, including improving domestic credit to the private sector, ensure that they have competitive interest rates, promote economic freedoms and the development of human capital in a perspective of exploiting the natural resources of ECOWAS, including oil and gas recently discovered in Senegal.
Trade openness is also a major determinant of the attractiveness of the ECOWAS countries. Regional integration agreements offer to the countries, especially those with limited market size, a gateway into the world economy with less exposure to risks related to the free movement of goods, services and production factors. Besides the decrease or elimination of tariff barriers, regional integration agreements generally include specific measures to facilitate the movement of capital between member countries and the entry of foreign capital in the region. The ECOWAS member countries are encouraged to pursue economic integration established with the entry into force of the Common External Tariff (CET) since 1st January, 2015 and the prospect of the advent of the single currency in 2020.
Investment rates (global or public), are, in the light of the results of the study, another major determinant of FDI in ECOWAS. To increase FDI inflows to the region, it is necessary to increase public investment, particularly in socio-economic infrastructures.
Sane, M. (2016) Determinants of Foreign Direct Investment Inflows to ECOWAS Member Countries: Panel Data Modelling and Estimation. Modern Economy, 7, 1517-1542. http://dx.doi.org/10.4236/me.2016.712137
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