the operational rate of foreign direct investment in …...fagbemi, f. & oladejo, b. 2019. the...

International Journal of Economics & Business ISSN: 2717-3151, Volume 3, Issue 1, page 26 - 41

Zambrut

Zambrut.com. Publication date: March 6, 2019.

Fagbemi, F. & Oladejo, B. 2019. The Operational Rate of Foreign Direct Investment in ............ 26

The Operational Rate of

Foreign Direct Investment in

West Africa: Does Human

Capital Matter?

Fisayo Fagbemi1 & Babafemi Oladejo

2

Fisayo Fagbemi1 & Babafemi Oladejo

2

Department of Economics, Obafemi Awolowo University

Ile – Ife, Nigeria

Abstract: In view of the rising precariousness of the business environment and the state of human

capital development in West African sub – region, the study assesses in particular the interaction

effect of human capital and FDI on economic growth in 13 West African countries between 2005 and

2016. The empirical analysis involves the use of panel analysis and the dynamic one – step system

GMM. With vast empirical evidence, the findings reveal that human capital is significantly relevant to

economic growth, underlining the salient linkage between human capital and economic performance,

while the low level of human capital is found to restrict West African growth space. Further evidence

indicates that FDI inflows in West Africa are found to adversely affect growth in the sub – region,

underscoring the intuition that FDI inflows undermine economic performance in countries that rely

heavily on primary commodity exports. With regard to the joint effect of FDI inflows and human

capital on the economic growth, although human capital has a positive mediating effect on FDI –

growth nexus, findings posit that binding constraints posed by the low level of human capital harmed

FDI – enhanced productivity in West Africa. Accordingly, the inefficiency such constraints generate is

the main cause of FDI inflows to West Africa atrophying. This implies that managing FDI inflows in

the sub – region in a way that improves and maximizes spillovers might require a dramatic

melioration of the investment climate and improved human capital. Thus, the study suggests that

promoting consensus for shared commitment, deepening structural reforms and standards for

securing efficient operational rate of FDI inflows through better and more education vital for human

capital enhancement could reinforce FDI – enhanced productivity.

Keywords: Foreign Direct Investment, Human Capital, Economic Growth, West Africa.

https://zambrut.com/


Zambrut



1. Introduction

With the considerable expansion in the coverage of global value chains (GVCs), foreign direct

investment (FDI) is becoming a prerequisite catalyst for jumpstarting industrialization and trade in

developing countries. As a crucial element of the global investment frontier, FDI often helps, through the

proliferation of global capital flows, leverage investment to diversify and upgrade industrial structures of

recipient countries (Chen, Geiger & Fu, 2015). The crucial role of FDI in economic development process

is typically reflected by a significant improvement in the share of employment and by the rising share of

national output in the host economies. Thus, at the macroeconomic level, the integration of these

economies into the world economy and the entry of foreign firms, partly due to the necessity of keeping up

with foreign investors and exiting worst performance, can result in more competition in their respective

local markets, leading to lower prices, increased efficient allocation, higher aggregate productivity,

increased foreign exchange, and more tax revenues (Farole & Winkler, 2014). In view of these plausible

gains from FDI, in addition to being a vital source of long-term capital for investment in critical

infrastructure, inward FDI inflows have been instrumental in African developmental initiatives (Asiedu,

2002; Anyanwu; 2006, Abor et al., 2008; Inekwe, 2013). However, FDI performance (operational rate) is

viewed to be conditional on investment climate factors — absorptive capacity and host country

characteristics (Borensztein et al., 1998; Li & Liu, 2005; Noormamode, 2008). Owing to the inefficiency

such constraints generate (unconducive investment climate across countries), the pervasive factor and

investment activities distortions are more likely to thwart the yielding potential of FDI spillover effects in

the recipient economy.

In Africa, statistical evidence indicates that the overall rate of return of FDI has been above 9% since

2006, higher than the developing country average of 8.1% and world average of 7.5% (UNCTAD World

Investment Report, 2015). Although compared to other regions of the world, in terms of FDI inflows, the

continent is not a major recipient, FDI inflows not only unevenly distributed across sub – regions in Africa

but has recorded a dramatic increase in a number of West African countries1. Between 2005 and 2014,

West African average share FDI inflows was at 26%, only behind North Africa with 35% (UNCTAD

World Investment Report, 2015). Recently, West African sub-region experienced a decline in FDI inflows

due to Ebola outbreak, regional conflicts and the contraction of commodity prices. However, with the

exception of North Africa, inward FDI inflows in West Africa are still far above other sub – regions in the

continent. In spite of this significant position, West African growth rate has been relatively paltry. For

instance, the sub – region’s growth rate stood at 0.5% in 2016 and 2.5% in 2017, while those of the world

were 3.1% and 3.5% respectively (AFDB West African Economic Outlook, 2018). Since increasing the

operational effectiveness of FDI is crucial for the enhancement of African growth potential, various

binding constraints (such as dearth of human capital2, production input and high technological gaps) in

most West African countries could be accounted for this gloomy performance (Chen, Geiger & Fu, 2015).

Hence, managing FDI inflows in the sub – region in a way that improves and maximizes spillovers might

require a dramatic melioration of the investment climate.

1 The sub – region of West Africa includes fifteen (15) countries — five (5) Anglophone countries (Ghana, Liberia, Nigeria Sierra Leone and the Gambia), nine

(9) francophone countries (Benin, Burkina Faso, Cabo Verde, Cote d’Ivoire, Guinea, Mali, Niger, Senegal and Togo) and one Portuguese speaking countries (Guinea Bissau).

Nigeria accounts for over 70% of regional GDP, and if Ghana, Côte d’Ivoire, and Senegal get included, in total, it will amount to 90% (AFDB West African

Economic Outlook, 2018). 2 Skills, knowledge, and know-how are collectively regarded as human capital (World Bank Blogs/Human Capital (2018).


Zambrut



Fig. 1: West African and World — GDP per Capita average growth rate between 2005 and 2016;

Source: Authors' estimates based on data from World Development Indicator (WDI), 2018.

Table 1

Foreign direct investment, net inflows (% of GDP) in West African Countries (2005-2016)

Country 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

Benin -0.18 -0.24 2.33 0.67 -0.26 0.77 2.06 3.45 3.93 4.17 1.81 1.87

Burkina Faso 0.59 1.43 0.32 0.39 0.67 0.43 1.34 2.95 4.11 2.88 1.50 2.64

Cabo Verde 8.28 11.88 12.67 11.79 7.42 6.98 5.48 7.36 4.83 9.70 6.10 7.37

Cote d'lvoire 2.04 1.97 2.18 1.93 1.63 1.44 1.19 1.22 1.30 1.24 1.31 1.32

Gambia 8.60 12.55 9.78 8.14 4.38 3.92 4.02 4.53 7.60 2.76 -0.18 -0.2

Ghana 1.35 3.12 5.59 9.52 9.13 7.86 8.21 7.86 6.75 8.71 8.50 8.16

Guinea 3.57 4.26 9.33 8.46 3.06 2.14 18.87 10.68 0.002 -0.84 -0.61 18.43

Guinea Bissau 1.48 3.02 2.70 0.77 2.29 3.10 2.26 0.67 1.91 2.60 1.74 1.68

Liberia 15.05 17.86 17.81 33.36 11.06 34.99 84.95 37.26 35.98 35.77 35.45 21.57

Mali 2.57 2.15 2.53 2.73 6.35 3.48 4.29 3.20 2.40 1.03 1.20 0.89

Niger 1.46 1.10 2.31 5.22 11.70 13.92 16.63 12.26 9.38 9.97 7.35 3.89

Nigeria 4.44 3.34 3.63 3.94 5.05 1.63 2.15 1.53 1.08 0.82 0.65 1.10

Senegal 1.93 3.09 3.11 3.38 2.58 2.10 2.35 1.94 2.10 2.63 2.54 2.68

Sierra Leone 5.57 3.12 4.42 2.12 4.43 9.11 32.30 19.00 8.73 7.48 5.94 13.81

Togo 4.54 4.15 2.47 1.60 1.46 3.94 19.38 3.14 4.50 1.20 6.31 5.79

Source: Author’s estimates based on data from World Development Indicator (WDI), 2018.

Moreover, host country characteristics and absorptive capacity are critically instrumental in

determining the scale and nature of FDI spillovers. Thus, strengthening institutional framework, improving

human capital through better and more education and bridging the technological gap through key

infrastructure development could mitigate the aforementioned binding constraints. Given the importance of


Zambrut



the mediating link in FDI – growth relationship, a substantial body of empirical research encompasses

various channels that serve as crucial conduits for FDI – enhanced productivity potential (Borensztein et

al., 1998; Kamara, 2013; Farole & Winkler, 2014). The bulk of contemporary empirical postulations seems

to be skewed towards the role of governance in FDI – growth nexus (Raheem & Oyinlola, 2013; Hayat,

2016; Ajide et al., 2014; Adeleke; 2014), while other potential channels, particularly human capital

development, have been largely unheeded. Although much evidence has been built up in recent decades on

the existence and nature of human capital in Africa3, the uncertainty of findings coupled with the paucity

of research on the mediating role of human capital development in FDI – growth linkage, especially

regarding West Africa, have led to emerging agitation and skepticism about the extent to which human

capital can navigate the relationship between FDI and growth in West African sub - region. As such, some

critical questions raised are: With the exclusion of other sub – regions, will the same result hold in case of

West Africa in view of her peculiar characteristics? Is the inward FDI performance linked to the level of

human capital in the sub – region? And what is the interaction effect of human capital development and

FDI on growth in West Africa?

The main argument here is that, exclusively, in West Africa, human capital could determine or

mediate the direction and extent of the growth effect of inward FDI inflows. Given the state of human

capital development in the sub – region4, and as a consequence, the immiserization of growth that could

occur, the study’s key objective is to examine the interaction effect of human capital and FDI on West

African economic growth. For effective policymaking process, this study offers a basis for addressing

emerging issues and projected future growth trends, and suggesting standards for securing efficient

operational rate of FDI inflows through better and more education. In addition, promoting consensus for

shared commitment and the adoption of best practices vital for human capital enhancement that could

improve the investment climate across West African countries, and thus help developing guidelines for sub

– regional convergence on the mitigation of binding constraints and sustainable management of FDI

inflows are germane. More importantly, as the strand of empirical literature on the role of human capital in

FDI – growth space is still scant and budding, the study further contributes to a better understanding of this

role by focusing on West Africa, hence addressing the existing knowledge gap.

The rest of this study is segmented as follows: Section two follows the introductory section, which is

the review of relevant literature. The methodological approach employed is presented in section three.

Section four contains the results and discussion, and finally the concluding remarks are stated with policy

implications and recommendations in the last section.

2. Literature Review

2.1 Conceptual and theoretical issues

Various viewpoints on the concept of human capital5 are developed subsequent upon the assertion

that increasing division of labour could spur improved economic performance (Adam Smith in 1776). The

first theoretical stand is based on individual aspects. Schultz (1961) views human capital as ―something

akin to property‖ which negates the concept of labor force in the classical perspective, although the author

advocates that human capital is crucial for attaining both national and regional economic growth and

development. The second viewpoint centers on human capital itself and its accumulation process. This

perspective accentuates on knowledge and skills obtained throughout educational activities, suggesting the

aggregation of investment in such areas as education, health, on-the-job-training, and migration (Sharpe,

2001). The last concept is closely linked to the production-oriented perspective of human capital. It

3 According to UNESCO estimates, in terms of human capital, sub-Saharan Africa (SSA) still lags behind. For instance, 130 million girls between the age of 6 and 17 are out of school, and 15 million girls of primary-school age – half of them in SSA – will never enter a classroom. Across SSA, as described by Heads of

State in the region, terrorism, the strain on national budgets, insecurity, the influx of refugee children who are in need of education, and the cultural bias against

educating girls are the main challenges plaguing human capital development (World Bank Blogs/Human Capital (2018). 4 For example, only Ghana (the first country in SSA) met the Millennium Development Goal (MDG1) target of halving extreme poverty by 2015 in West Africa.

A share of the population living in poverty decreased from 52% in 1991 to 24% in 2012 (World Bank Blogs/Human Capital (2018). 5 The concept can mean different things to different stakeholders, as it is multi – dimensional. For detailed information on this conceptual diversity, one may consult World Bank report on human capital index (2015).


Zambrut



stresses on the initiative that affects the value of a worker's marginal product (Frank & Bemanke (2007).

Consequently, human capital simultaneously covers both the instrumental concept to create certain values

and the ―endogenous‖ meaning to self-generate it. While ignoring other potential determinants, generally it

is evident that even at the conceptual level, a lot of emphasis has been placed on the role of education and

healthcare services in human capital attainment (Dae-Bong, 2009; Didenko, 2007). Lucas’s (1988)

perspective on human capital development approach underlines that human capital development is an

engine of economic growth, implying that the incentives for human capital development should be high in

order to promote economic growth.

Theoretically, two main school of thought confirmed to be the basis of empirical studies on the link

between FDI and growth: the traditional school (modernization and dependency theory) and the integrative

school (the eclectic paradigm). The modernization school posits that countries will rise to what is viewed

as higher developmental levels by following a designed natural order. They assert that through

industrialization and trade openness and by keeping up with developed countries’ development path,

developing countries could overcome endogenously induced barriers. The capacity to overcome these

barriers is determined by both human and physical capital endowments (Wilhelms, 1998). This theory rests

on new growth theory6 (Mengistu & Adams, 2007; Adams, 2009b). It provides strong support for the

argument that FDI could be a potent instrument and factor in promoting growth. However, the

exploitation of this plausible potential requires a viable and conducive economic climate. Where such an

economic climate is absent (like pervasive dearth of human capital and good institutions), FDI may be

ineffective and counterproductive; it may undermine rather than stimulate growth, while exerting little

influence on social rates of return in the recipient economy, it may serve to induce the private rate of return

to investment by foreign firms.

Dependency theory asserts that domestic reliance on foreign investment is inimical to economic

growth and exacerbates income inequality problem in the long run. The dependence school advocates

equal distribution of wealth, income and power by being self - reliant and through collective actions of

developing countries. To the proponents of dependence theory, the primary cause of underdevelopment is

the exploitation from the industrialized nations, although it is admitted that in the short run, higher

investment and consumption are attained following increases in FDI, thereby creating direct and

immediate economic growth. Nonetheless, as FDI builds up and foreign projects take the center stage,

there will be effects detrimental to the rest of the economy which undermine economic performance (Tsai,

1994; Adams, 2009b). The last school — the eclectic paradigm — in defining its own framework,

integrates the concepts embedded in the modernization school and dependency school. It provides a

framework that groups micro – and macro – level determinants in order to explain why and where

multinational companies (MNCs) invest abroad (Dunning, 1977). The framework stresses that firms

invests abroad to look for three types of advantages: Ownership (O), Location (L), and Internalization (I)

advantages; hence it is regarded as OLI framework.

2.2 Empirical review

With vast literature on the link between foreign direct investment and economic growth, there has

been dearth of any consistent conclusion. The general empirical discourse on FDI – growth nexus has been

predominantly contentious and marginally inconclusive7. The channels through which FDI affect growth

is the crux of the spurting contention. In essence, with emphasis on the spillover effects of FDI on

economic growth of the recipient economy, the dominant view underscores the conditionality of such

indirect effects on additional factors (Busse & Groizard, 2006; Balasubramanyam, Salisu & Sapsford,

1996; Borensztein, De Gregorio & Lee, 1998; Carkovic & Levine, 2003; Kamara, 2013). More

specifically, the existing stock of human capital and technological changes are viewed to be central

6 Balasubramanyan et al. (1996) provide a detailed discussion of key theories of FDI – growth nexus and thematic research notes for a better understanding of

rules modeled it. 7 SSA, in particular, in spite of its improvements and reforms such as institutions, policies infrastructure and liberalization, compared to other regions, in terms of FDI performance, the region is viewed to still trail behind (see Odenthal, 2001; Asiedu, 2003).


Zambrut



determinants of spillover effects of FDI in the host economy, suggesting the complementarity between FDI

and human capital in the development path of any country (De Jager, 2004; Ray, 2012). Besides

complementarity concerns, there have been ensuing research efforts on the reliability of the influence of

FDI on growth. Empirical studies underlining the specific features of FDI are Johnson (2006); Basu &

Guariglia (2007); Li & Liu (2005); Sunde (2017); among others. They all argue that FDI positively affects

economic growth. In contrast, another strand of literature stresses that FDI may undermine economic

growth, as it can cause the distortion in the development path of FDI-recipient economy (Fry, 1993;

Bornschier et al., 1978; De Backer & Sieuwaegen, 2003), while some other studies posit that there is no

direct relationship between FDI and growth (Alfaro et al., 2002; Durham, 2004; Herzer et al., 2008).

Basically, empirical elucidations on the divergent propositions have pointed to different methodological

issues (Carkovic, Levin, Moven, Grahma & Blomstrom, 2005) and absorptive capacity of FDI – recipient

economy (Blomstrom & Kokko, 2003).

Reflecting on the instrumentality of human capital and its stimulating effect on economic growth

rates, based on a sample of sixty developing countries during 1965-87, World Bank (1991) reveals that

countries with high levels of both education and macroeconomic stability and openness tend to experience

high growth rates. Also, Thomas & Wang (1997), with analysis of a sample of 1265 World Bank projects,

countries with both a more educated labour force and a more open economy are found to be three

percentage points higher in terms of the rate of return than countries with only one or the other.

Essentially, it is empirically noteworthy that in achieving inclusive growth and development, human

capital is posited to be a polar principal (Sen, 2013; Asadullah, Savoia, & Mahmud, 2014; Joshi, Hughes,

& Sisk, 2015). In addition, Sen (1999) argues that as people’s capabilities are enhanced through education

and health care, easy distribution of wealth is promoted, which in turn induces reduced inequality. This

elucidates the instrumental role of human capital in economic development process8, and thus buttresses

the assertion that there is a correlation between human capital and economic growth.

It is also notable to delve into the previous explicit discussion on the absorptive capacity of the FDI –

recipient economy and the interaction between human capital and FDI. While advocating for a substantial

improvement in human capital, Noormamode (2008) underlines that the social and economic situation of

the host economy matters in order to benefit from positive effects of FDI. With the test of the effect of FDI

on economic growth in cross-country regression framework specifically for 69 developing countries,

Borensztein et al. (1998) posit that FDI is instrumental and served as the central component of the transfer

of technology, and thus positively influences development of the host country. Moreover, the contributive

role of FDI to economic growth outstrips that of domestic investment. Given the threshold computed for

the secondary school attainment of 0.52, further findings indicate that the higher the benefit from spillover

effects of FDI applies to the higher threshold stock of human capital. In another study, Li & Liu (2005),

using a panel analysis for 84 countries between 1970 and 1999, underscore that human capital is a vital

vehicle for absorptive capacity of the effect of FDI. They also argue that if the technology gap between the

source and the receiving country is high, the host country’s benefit from FDI will be low. Analogously,

Bengoa et al. (2003), based on panel data analysis for 18 Latin American countries (1970-99), show that

economic stability and liberalized capital markets of the recipient country determines the extent to which

host economy will be beneficial from the positive spillover effects of FDI. More importantly, the host

country, especially any developing country, must accord investment in education and infrastructure

considerable attention, and that development of human capital should precede technological influences

(Nelson & Phelps, 1996).

Some researchers have also centered their studies on the direct and indirect role of institutional

quality in economic development process through the channel of FDI. These include; Raheem & Oyinlola

(2013); Hayat (2016); Ajide et al. (2014); Adeleke (2014); among others. In all, it is posited that

institutional factors mediate between FDI – growth nexus in modern economies. Apart from institutions,

8 In addition, the spillover effects of research and development and human capital accumulation are considered as the essential ingredient of improved economic

performance (see Meyer, 2003).


Zambrut



empirical research is somewhat seemed to be converged on the proposition that the effect of FDI on

growth is conditional on certain factors such as open trade regime (Balasubramanyan et al., 1996), sectoral

patterns (Dutt, 1997), the level of complementarity and substitution between FDI and domestic investment

(de Mello, 1999) and financial market development (Durham, 2004). In addition, a number of studies

validate that FDI spillovers9 are larger in countries that are more open to trade (Lesher & Miroudot 2008;

Meyer & Sinani 2009; Havranek & Irsova 2011).

As the preceding review bears out that for the realization of FDI spillovers, the host country policy

measures and absorptive capacity are the indispensable ingredient. Accordingly, although studies have

examined the role of host country characteristics (such as the stock of existing human capital and local

financial markets) and institutional context for FDI – enhanced productivity spillovers, research efforts are

limited to cross – sectional studies of developing and developed economies as a whole. Fewer studies

center on MENA, OECD, SSA and time series studies of countries, while no known study has focused

mainly on West African sub – region regarding the mediating effect of human capital on FDI – growth

nexus. Aside offering better and more comprehensive coverage of FDI inflows to West Africa, considering

that there are significant sub – regional differences in terms of income, infrastructure and human capital

endowments in Africa, a sub – regional study, especially for West Africa, could embed best practices

(policy measures member states could adopt in light of their respective contexts) for human capital

development and for having sufficient absorptive capacity. Hence, reflecting on human capital as a vital

vehicle for FDI – led productivity spillovers, this study addresses the gap in the literature by focusing on

West African sub – region.

3. Data and Methodology

3.1 Data

Aligning with the crux of the main objective, the study covers thirteen (13) West African countries10

between 2005 and 2016. Given possible missing observations in the sample and the uncertainty on the

systematic form for missing observations, the study period is based on the availability of data on the main

variables of interest across countries in the sub – region. Essentially, the number of countries selected is

adequate to have holistic and sufficient expositions of the empirical analysis. Following Borensztein et al.

(1998) and Anyanwu (2012), accordingly, two human capital measures were used: Gross enrolment ratio

at secondary school (SCH) and life expectancy (LEXP). This measure of education attainment has been

regarded as most significantly related with growth (Barro and Lee, 1994), while gross FDI inflows is

viewed to be positively and significantly influenced by population health (life expectancy) in low- and

middle-income countries (Alsan et al., 2006).

Moreover, other variables used are foreign direct investment (FDI), real GDP per capita, trade

openness and the institutional indicator (government effectiveness). FDI is the direct investment equity

flows in the reporting economy. It is the sum of equity capital, reinvestment of earnings, and other capital

as indicated in the balance of payments. Real GDP per capita is used as a proxy for economic growth. It is

the sum of gross value added by all resident producers in the economy plus any product taxes and minus

any subsidies not included in the value of the products. Trade openness is measured by the sum of exports

and imports of goods and services as a share of gross domestic product. It is included to reflect the level of

integration of West African economies into the world economy. Data are in constant 2010 U.S. dollars.

Through the application of institutional and regulatory instruments, government can influence and navigate

the economic direction; hence government effectiveness is taken as institutional and governance tool

employed in the FDI – receiving economy. It is the one of the six institutional indicators proposed by

Kaufmann et al. (2010)11

which captures perceptions of the quality of the civil service, the quality of public

9 For a detailed discussion on various recipient country policy and institutional factors that can mediate the direction and extent of FDI spillovers one may

consult the work of Farole & Winkler (2014). 10 In the study, out of fifteen countries in the sub – region, only Cote d’Ivoire and Guinea Bissau are excluded (not selected) due to extremely missing

observations and unavailability of data on school enrollment, secondary (% gross) for the two countries. 11 Based on the work of Kaufmann et al. (2010), the governance measure (i.e. government effectiveness), ranging from -2.5 to 2.5, was taken. Higher values of these indexes indicate a higher level of institutional quality, while lower levels imply weak institutions.


Zambrut



services, and the degree of its independence from political pressures, the quality of policy formulation and

implementation, and the credibility of the government’s commitment to such policies. Trade openness and

government effectiveness are used as control variables. Theoretically, human capital, FDI and government

effectiveness are expected to have direct correlation with economic growth, while the expected impact of

trade openness depends on the nature and state of the economy. Apart from data on institutional quality

that were obtained from World Governance Indicators (2017 Edition), all others were sourced from the

World Bank’s World Development Indicators (2017 Edition).

3.2 Methodology

The theoretical framework adopts an augmented growth accounting model, and based on Solow

(1956), FDI is incorporated. This is in line with the work of Borensztein et al. (1998) and De Mello (1999).

Accordingly, the model is specified as follows:

( )

Where represents the level of output (the growth of the economy) for country in year determined by human capital ( ), physical capital ( ), FDI inflows ( ), and the exogenous state of the

economic environment ( ). The state of the economic environment encompasses various control and

policy variables affecting the level of productivity in the economy. FDI, based on new growth theory, is

regarded as additional source of resources or capital injection (inflows) into the host country with peculiar

characteristics. Recent empirical evidence suggests that such foreign capital inflows will have an indirect

impact on the FDI – recipient country through the influence of the absorptive capacity of the reporting

economy in terms of, for instance12

, new and good governance institutions, the level of human capital,

infrastructural development, and the level of financial development.

Hence, the present study tests the hypothesis that human capital development significantly triggers

FDI – enhanced productivity spillovers while accounting for other contingent economic growth

determinants. With the introduction of the interaction term, the empirical model specification follows

Borensztein et al. (1998) and Balasubramanyam et al. (1999), and states in the following pattern:

( )

Where indicates the interaction term between FDI and human capital. is a vector of

control variables — trade openness ( ) and government effectiveness ( ). is the constant while

represent the estimated coefficients. indicates the idiosyncratic error term. The country - specific

effect is represented by , which is assumed to be time unvarying. remains as previously defined.

Omitted variable bias, simultaneity bias, sample heterogeneity (cross-section and temporal

heteroscedasticity) are usually associated with panel data analysis, a number of different models and

estimation techniques will give better and reliable estimates. As a result, this study also estimates dynamic

growth model to examine human capital channel through which FDI may contribute to economic growth in

West Africa. This approach usually addresses the simultaneity issue. Thus, Eq. (2) is rewritten as follows:

( )

For the possible change common to all, is taken as period - specific effect, while

represents the growth rate of West African economies. The estimation method requires taking the first

differences of Eq. (3) to get rid of the country-specific effects, as they do not vary with time. This results

to:

( ) ( )

12 For details, one may consult the work of Adjasi, Abor, Osei, & Nyavor-Foli (2012); Agbloyor, Abor, Adjasi, & Yawson (2014); Alfaro et al. (2004);

Morrissey & Udomkerdmongkol (2012); Elkomy et al. (2016); World Bank; (2001), Azman-Saini, Baharumshah, & Law, (2010); Omran & Bolbol (2003); Balasubramanyan et al. (1996); Borensztein et al. (1998).


Zambrut



Given that the first lag of the explanatory variables in is potentially correlated with the in , however Eq. (4) poses some new estimation problems. Theoretically, it is vital to control for the

endogeneity issue, time and country - specific effect (Arellano & Bover, 1995). Hence, the estimation is

performed using lagged levels of the series as instruments for the equation in first differences. Nonetheless,

Arellano & Bover (1995) and Blundell & Bond (1998) observed that large finite sample bias might occur

with the first-difference GMM estimator when the series are quite persistent, as this could result to weak

instruments. In terms of finite sample bias and estimation precision, they posit that the system-GMM

performs much better than the difference-GMM. As such, in most economic applications studies, system-

GMM estimator has been made the choice, since it provides consistent and efficient estimates. It is

particularly suited for this study, as time periods (T) is less than the number of Cross-section (N)

(Roodman, 2009). Specifically, in this study, in addition to System – GMM, different panel data

techniques (Pooled OLS, Random Effects, Fixed Effects and Panel-Corrected Standard Error’ (PCSE)

estimation13

) are also used, as they are most advantageous for being indicative and for the provision of

robustness check.

4. Results and Discussion

The empirical analysis starts with the summary statistics of the variables used in the model. Table 2

displays the essential attributes of the variables based on the computed overall mean values, whereas

standard deviation, minimum and maximum values are given with their respective overall, between and

within values. The overall mean value of GDP is the highest, and also for standard deviation at all levels

(overall, between and within) followed by trade openness, while those of the government effectiveness is

the lowest, suggesting a pervasive poor institutional environment in West African sub-region. However, in

terms of minimum value, FDI is the lowest under the within category. Based on the overall standard

deviation of the two measures of human capital — school enrollment, secondary (% gross) and life

expectancy at birth, total (years), it is observed that there is a 19.04% range of fluctuations in school

enrollment and a 5.86% range of fluctuations in life expectancy in West Africa during the study period. In

the same period, FDI is also fluctuated within the range of 9.92%.

Table 2

Summary Statistics

Variable Mean Standard deviation Minimum Maximum

(overall) overall Between Within overall between within overall between within

GDP 986.84 841.07 864.18 116.56 279.10 335.57 373.52 3452.94 3252.71 1290.06

FDI 7.01 9.92 7.90 6.37 -0.84 1.61 -13.68 84.95 31.76 60.10

Schooling (SCH) 43.10 19.04 17.39 6.02 9.90 14.09 25.94 94.25 85.68 56.01 Life Exp (LEXP) 58.28 5.86 5.79 1.79 43.60 48.19 53.69 72.43 71.92 61.50

Trade openness(TRPE) 77.52 38.23 31.92 22.53 21.12 48.13 19.89 311.36 167.84 221.03

Government effect (GOV) -0.76 0.45 0.46 0.10 -1.54 -1.36 -1.06 0.35 0.09 -0.48

The pairwise correlation coefficients, in Table 3, indicate that, contrary to most theoretical

postulations, FDI is adversely related with GDP in the sub – region, and with insignificant correlation with

human capital indicators. Also, there is significant negative correlation between FDI and government

effectiveness. Nonetheless, the two measures of human capital used are significantly correlated with

economic growth, suggesting that they have a significant positive influence on West African economies.

The relevance of institutional characteristics in any economy is supported by the significant direct relation

between government effectiveness and GDP in the model. In contrast, both human capital measures are

correlated with FDI but not significant.

13 With PCSE, in the existence of both serial and contemporaneous correlation as a result of possible disturbances, efficient and reliable estimates are provided.

In addition, unlike Parks’ Feasible Generalized Least Squares (FGLS) estimator, it is mostly applicable for cases where cross- sectional observations are more than the time period. For detailed elucidation and discussion, see Parks (1967).


Zambrut



Table 3

Pairwise correlation coefficient

Variable GDP FDI SCH LEXP TRPE GOV

GDP 1.00

FDI -0.13 1.00

(SCH) 0.73* 0.05 1.00 (LEXP) 0.49* 0.10 0.68* 1.00

(TRPE) -0.05 0.46* 0.32* 0.27* 1.00

GOV 0.55* -0.21* 0.45* 0.67* -0.18* 1.00

* represents correlation coefficients significant at the 5% level or better.

Table 4 reports the regression results in two different specifications. Model (i) represents the

estimation for secondary school enrollment as the indicator of human capital, whereas model (ii)

encompasses the estimation for life expectancy as the measure of human capital. In the first model, random

effects is employed, since Hausman specification test confirms that the country-specific effects is

uncorrelated with the other covariates of the model, indicating that random effects will be unbiased and

most appropriate for the model. However, in the second model, the test rejects this assumption, under this

condition, random effects will be biased and inappropriate for the model. Hence, fixed effect is used as the

correct estimation procedure for model (ii). Foremost, in all, the panel analysis, the results indicate that

that FDI has a negative influence on economic growth14

, and only significant in model (ii) under the

pooled OLS and fixed effects at 5% and 10% level of significance respectively, jettisoning the findings of

a positive effect (Johnson, 2006; Basu & Guariglia, 2007; Li & Liu, 2005; Sunde, 2017). This imply that

FDI could cause distortions in the development path of West African sub-region, which aligns with studies

of Fry (1993); Bornschier et al. (1978); De Backer & Sieuwaegen (2003). In contrast, a positive

association is found between schooling (SCH) and growth in model (i) for pooled OLS and random effects,

whereas in model (ii), life expectancy (LEXP) adversely affects economic growth (pooled OLS) but is

positive and significant for fixed effects. One plausible justification for these results is that low quality and

inadequate higher education which could hamper enhanced skills and performance incentives of the labour

force may be the major contributing factor. Overall, this corroborates the view that human capital is

instrumental to economic development process (Sen, 2013; Asadullah, Savoia, & Mahmud, 2014; Joshi,

Hughes, & Sisk, 2015). Deepening structural reforms and positive changes in current education

architecture, in general, will stimulate growth.

The interaction term with human capital measures is positive, but only significant in model (ii) —

pooled OLS. This suggest that human capital is critical to improving the yielding or growth - enhanced

potential of FDI in West Africa, which is in line with the conclusion of Noormamode (2008); Borensztein

et al. (1998); Li & Liu (2005). Regarding the control variables, Government effectiveness (GOV) has a

significant positive impact on growth in the two specifications under pooled OLS but negative and

insignificant in both random effects and fixed effects specifications, reflecting the feeble nature of

institutions across countries. Trade openness (TRPE) is found to be only positive in the second model

(pooled OLS and fixed effects estimation), and exclusively significant in the first model (pooled OLS).

This type of relationship does not appear that trade affects economic growth in any significant way. Since

the magnitude of the effect of trade depends on the level of the content of manufacture of any economy,

these results reaffirm the low manufactured content of West African exports.

14 Borensztein et al., 1998 assert that in countries with a low level of human capital, FDI inflows make a negative contribution to the growth of the economy.


Zambrut



Table 4

Panel Analysis for Interaction Models

GDP (log) Pooled OLS Random Effects Fixed Effects

Model (i) Model (ii) Model (i) Model (ii)

FDI -0.06 [-0.98]

-0.77** [-2.56]

-0.01 [-0.69]

-0.08* [-1.80]

Trade openness(TRPE)log -0.54***

[-3.72]

0.03

[0.16]

-0.03

[-0.97]

0.02

[0.88] Government effectiveness (GOV) 0.52***

[5.57]

0.71***

[4.92]

-0.04

[-0.59]

-0.04

[-0.95]

Schooling (SCH) log 0.82*** [6.16]

0.32*** [8.56]

Life Exp (LEXP)log -0.56 [-0.59]

1.94*** 12.02

FDI*Schooling 0.01

[0.87]

0.002

[0.66]

FDI*Life Exp 0.19**

[2.52]

0.02

[1.80]

Constant 0.44***

[10.45]

0.40**

[2.68]

0.60***

[23.71]

0.41**

[3.10]

R2 0.64 0.39 0.45 0.60

Observations 118 152 118 152

No. of countires 13 13 13 13

Hausman test 10.42 (0.06) 11.76 (0.04)

Pesaran CD (P-value) 0.21 0.32

Figures in parentheses are t-values. (***), (**) & (*) indicate significance at 1%, 5% and 10% respectively.

Model (i) indicates the inclusion of school enrollment, secondary (% gross) as human capital measure, whereas model

(ii) explains the inclusion of life expectancy at birth, total (years) as human capital measure — in the estimated model

In order to check the veracity of the panel analysis results, Panel-Corrected Standard Error’ (PCSE)

regression is carried out on the two specifications, indicating the robustness test for the obtained results.

Table 5 presents the results of the robustness test. Essentially, the results are somewhat analogous to those

obtained in the pooled OLS, random and fixed effects models. FDI still maintains its negative signs in both

models. However, as revealed earlier, the test substantiates that the human capital indicators are relevant to

the growth of GDP per capita. Following this, the interaction term coefficients are positive, but just

significant in the first model. This also buttresses the assertion of the previous findings that the stock of

existing human capital in the host economy does shape the growth effect of FDI. In general, it is germane

to know that the inconsistence in signs of the estimated coefficients is mostly common in panel data

analysis owing to the potential simultaneity and considerable attenuation bias and country-specific effects

resulting from the possible existence of measurement error and persistent explanatory variables bias

(Deaton, 1995).

Analogously, due to the dynamic nature of the economic behavior, the dynamic one – step system

GMM is also reported in Table 5. In addition, in view of the potential endogeneity bias and serial

correlation of the error term, the panel regression analysis could result to inconsistent parameter estimates.

More importantly, given the asymptotic standard errors, compared to the two – step system GMM, one –

step system GMM15

is virtually efficient and unbiased. Accordingly, the consistency of the estimates are

checked through two specification tests — the Sargan/ Hansen over-identifying restrictions and a serial

correlation test in the disturbances (Arrelano & Bond, 1991). The Hansen test is basically for the overall

validity of instruments; and it confirms that the instruments are valid. Moreover, the absence of second

order serial correlation indicates that the models are correctly specified. As such, they provide efficient and

reliable estimates. In all, the number of observations are more than the number of instruments. This thus

satisfies the rule of thumb. In line with previous estimations, FDI has a negative impact on growth in all

the models. Regarding the effect of human capital development on growth, both measures (Schooling and

Life expectancy) are strongly significant, but the positivity vanishes irrespective of the model, contrary to

15 The asymptotic standard errors associated with two-step System GMM which have been proved to be critically inefficient and unbiased downward can lead to a type II error (see Windmeijer 2005)


Zambrut



the earlier positive effect. Although, they are significantly crucial for explaining the growth of West

African economies, their negative signs may be puzzling, regarding the theoretical assertion that human

capital should serve as a veritable engine of growth (Lucas, 1988). Conversely, the prevailing complex

system and limited management capacity are inimical to the effective orientation of all parts of an

education system towards modern learning and acquisition of relevant skills. On the other hand, With

respect to life expectancy, its significance shows that it is highly relevant in economic development

process while the negative sign could be attributed to some pervasive factors in the sub – region. For

instance, in West Africa, a large chunk of the population (especially old people) are illiterate, and they

mostly engage in ―black economy‖ (economic activities not reflected in their national accounts) or

informal economic activities with poor quality jobs and meager income. These seem to be a major

constraint on the demographic dividend undermining competitiveness and productivity. With adult

population dominance, public sector is also awash with poor service delivery coupled with striking

fungibility issue, which makes external funds less truly additional. By and large, there is lack of enhanced

skills and performance incentives. The level of financial linkages is a striking and steep case in point

(AFDB’s Human Capital Development Strategy, 2016). The interaction of FDI with two human capital

measures has positive (model (i) and (ii)) and significant (model (i)) productivity effect in the system

GMM estimation16

, validating the positive role of human capital development for FDI spillovers17

(Nelson

& Phelps, 1996; Bengoa et al., 2003; Adams, 2009b). Furthermore, the results show that governance

positively influences GDP per capita with only weak significant in the second model, confirming the low

level of institutional quality across countries (Ajide et al., 2014; Adeleke, 2014). Trade openness is also

found to have a positive impact on growth but only significant in model (i), reasserting the claim of

(Mengistu & Adams, 2007; Farole & Winkler, 2014).

Table 5

Estimated results based on Panel – Corrected (PCSE) and Dynamic One – Step System GMM

GDP (log) Panel – corrected (PCSE) System GMM estimation

Model (i) Model (ii) Model (i) Model (ii)

GDP (lag) 1.01*** [54.82]

1.01*** [57.19]

FDI -0.04**

[-2.23]

-0.11

[-1.13]

-0.02**

[-2.38]

-0.006

[-0.21 Trade openness(TRPE)log -0.17**

[-2.79]

-0.14

[-1.19]

0.02

[0.95]

0.04**

[2.53]

Government effectiveness (Gov) 0.41*** [6.15]

0.43*** [4.03]

0.02 [1.16]

0.04* [1.70]

Schooling (SCH) log 0.52***

[7.92]

-0.05**

[-2.03]

Life Exp (LEXP)log 1.61***

[3.44]

-0.28**

[-2.42] FDI*Schooling 0.01**

[2.13]

0.004**

[2.47]

FDI*Life Exp 0.03 [1.12]

0.001 [0.23]

Constant 0.77***

[5.78]

0.20

[0.56]

0.11

[0.80]

0.96**

[2.43] R2 0.69 0.64

Observations 118 152 109 139

No. of countires 13 13 13 13

No. of instruments 44 44

A – Bond AR(1) test p-value 2.41 (0.02) 3.89 (0.00)

A – Bond AR(2) test p-value 0.93 (0.35) 2.52 (0.21)

Sargan test 20.87 (0.23) 43.23 (0.22)

Figures in parentheses are t-values. (***), (**) & (*) indicate significance at 1%, 5% and 10% respectively.

Model (i) indicates the inclusion of school enrollment, secondary (% gross) as human capital measure, whereas model

(ii) explains the inclusion of life expectancy at birth, total (years) as human capital measure — in the estimated model.

16 In this paper, the findings from other techniques used serve as complementary evidence, while the main conclusion rests on the results of One Step System –

GMM. 17 Borensztein, et al. (1998) asserts that ―the higher the productivity, if FDI holds, only when the host country has a minimum threshold stock of human capital.‖


Zambrut



In sum, the persistence of the adverse effect of FDI on GDP per capita in all the analysis may result

from heavy reliance on primary commodity exports, natural resource dependency and insufficient

secondary education in West African sub – region, especially the dependence of some large West African

economies on natural resource exports as the contemporary trend (AFDB West African Economic

Outlook, 2018). Empirically, the low level of human capital coupled with the growing precariousness of

the business environment could be the main cause of FDI inflows to West Africa atrophying. Hence, this

particular case warrants the empirical findings of the study that FDI negatively contribute to economic

growth. The results also corroborate the intuition that human capital development is instrumental in

economic development process. By and large, the findings confirm the positive mediating role of human

capital development in FDI – growth nexus in the sub – region, suggesting that the operational

effectiveness of FDI inflows to West Africa could be enhanced through a dramatic melioration of the

investment climate and educational system across countries.

5. Concluding remarks

Exclusively, in West Africa, human capital could shape the direction and extent of the growth effect

of FDI inflows. Also, in view of the rising precariousness of the business environment and the state of

human capital development in the sub – region, the study assesses in particular the interaction effect of

human capital and FDI on economic growth in 13 West African countries between 2005 and 2016. The

countries include; Ghana, Liberia, Nigeria, Sierra Leone, the Gambia, Benin, Burkina Faso, Cabo Verde,

Guinea, Mali, Niger, Senegal, and Togo. The empirical analysis involves the use of panel data techniques

(Pooled OLS, Fixed Effect and Panel-Corrected Standard Error’ (PCSE)) and the dynamic one – step

system GMM.

With vast empirical evidence, on the whole, the findings reveal that human capital is significantly

relevant to economic growth, underlining the salient linkage between human capital and economic

performance, since human capital development is instrumental in economic development process.

Conversely, the low level of human of capital is found to restrict West African growth space, as the

empirical evidence suggests that the prevailing complex system and limited management capacity are

inimical to the effective orientation of all parts of an education system towards modern learning and the

acquisition of relevant skills for enhancing growth. Hence, the melioration of current education

architecture will stimulate growth. FDI inflows to West Africa are widely found to adversely affect growth

in the sub – region, underscoring the conjecture that FDI inflows undermine economic performance in

countries that rely heavily on primary commodity exports. Natural resource dependency is the

contemporary trend in some large West African economies. In another finding, reflecting the feeble and

poor nature of institutions across West African countries, governance is insignificant but positively

enhances the sub – region’s growth, suggesting that, in addition to trade openness, institutions offer

prudential guide for keeping up with developed countries’ development path.

With regard to the joint effect of FDI inflows and human capital on the economic growth, although

human capital has a positive mediating effect on FDI – growth nexus, evidence indicates that binding

constraints posed by the low level of human capital and prevalent investment activities distortions harmed

FDI – enhanced productivity spillovers in West Africa. Accordingly, the inefficiency such constraints

generate is the main cause of FDI inflows to West Africa atrophying. This implies that managing FDI

inflows in the sub – region in a way that improves and maximizes spillovers might require a dramatic

melioration of the investment climate and improved human capital. Thus, the study suggests that

deepening structural reforms and standards for securing efficient operational rate of FDI inflows through

better and more education could reinforce FDI – enhanced productivity growth. In addition, promoting

consensus for shared commitment and the adoption of best practices vital for human capital enhancement

that could help engendering sub – regional convergence on the mitigation of binding constraints and

sustainable management of FDI inflows across West African countries are central.


Zambrut



6. References Abor, J., Adjasi, C.K.D. & Hayford, M.-C. (2008). How Does Foreign Direct Investment Affect the Export Decisions of Firms

in Ghana? African Development Review, Vol. 20, No. 3, pp. 446–65.

Adams, S. (2009b). Foreign Direct Investment, Domestic Investment, and Economic Growth in Sub-Saharan African. Journal of

Policy Modelling, 31, 939-949.

Adeleke, I.A. (2014). Foreign Direct Investment-Growth Nexus in Africa: Does Government Matter? International Review of

Financial Analysis, 21, 81-89.

Adjasi, C., Abor, J., Osei, K.A. & Nyavor-Foli, E.E. (2012). FDI and Economic Activity in Africa: The Role of Local Financial

Markets. Thunderbird International Business Review, 54, 429– 439.

AFDB (2016). Human Capital Development Strategy — One Billion Opportunities: Building Human Capital for Inclusive

Growth in Africa.

AFDB (2018). West African Economic Outlook — Macroeconomic Developments and Poverty, Inequality, and Employment

Labor Markets and Jobs. African Development Bank Group.

Agbloyor, E.K., Abor, J.Y., Adjasi, C.K.D. & Yawson, A. (2014). Private Capital Flows and Economic Growth in Africa: The

Role of Domestic Financial Markets. Journal of International Financial Markets, Institutions and Money, 30, 137–152.

Ajide, K., Adeniyi, O. & Raheem, I. (2014). Does Government Impact on the Foreign Direct Investment – Growth Nexus in

Sub-Saharan Africa? Zagreb International Review of Economics and Business, Vol. 17, No2, pp. 71-81.

Alfaro, L., Areendam, C., Kalemli-Ozcan, S. & Sayek, S. (2004). FDI and Economic Growth: The Role of Local Financial

Markets. Journal of International Economics. 64 (1), 89–112.

Alsan, M., Bloom, D. E. & Canning, D. (2006). The Effect of Population Health on Foreign Direct Investment Inflows to Low-

and Middle-Income Countries. World Development, Vol. 34, No. 4, 613–630.

Anyanwu, J. C. (2006). Promoting of Investment in Africa. African Development Review, Vol. 18, No. 1, pp. 42–71.

Anyanwu, J. C. (2012). Why Does Foreign Direct Investment Go Where It Goes? New Evidence from African Countries.

Annals of Economics and Finance 13-2, 433-470.

Arellano, M. & Bond, S. (1991). Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to

Employment Equations. Review of Economic Studies, 58 (2), 277 – 297.

Arellano, M.; & Bover, O. (1995). Another Look at the Instrumental Variable Estimation of Error-Components Models. Journal

of Econometrics, 68, pp.29-51.

Asadullah, N. M., Savoia, A., & Mahmud, W. (2014). Paths to Development: Is there a Bangladesh Surprise? World

Development, 62: 138-154.

Asiedu, E. (2002). On the Determinants of Foreign Direct Investment to Developing Countries: Is Africa Different? World

Development, Vol. 30, No. 1, pp. 107–19.

Asiedu, E. (2003). Policy Reform and Foreign Direct Investment to Africa: Absolute Progress but Relative Decline. In Saleh

Nsouli, eds., Development Policy Review, The New Economic Partnership for Africa Development: The Key

Challenges.

Azman-Saini, W., Zubaidi, A. & Hook, S. (2010). Law, Foreign Direct Investment, Economic Freedom and Economic Growth:

International Evidence. Economic Modelling, 27, 1079–1089.

Balasubramanyam, V.N., Salisu, M. & Sapsfort, D. (1996). Foreign Direct Investment and Growth in EP and is Countries. The

Economic Journal, Vol. 106. No. 434. pp: 92 – 105.

Barro, R., & Lee, J-W. (1994). Sources of economic growth. Carnegie Rochester Conference Series on Public Policy 40, 1–46.

Basu, P. & Guariglia, A. (2007). Foreign Direct Investment, Inequality and Growth. Journal of Macroeconomics, 29. pp: 824 –

839.

Bengoa M., Sanchez-Robles, B. (2003). Does FDI Promote Economic Growth? Recent Evidence from Latin America.

Universidad de Cantabria.

Blomstrom, M. & Kokko, A. (2003). The Economics of Foreign Direct Investment Incentives. NBER, Working Paper, 9489.

Blundell, R. & Bond, S. (1998). Initial Conditions and Moment Restrictions in Dynamic Panel Data Models. Journal of

Economics, (87): 115–43.

Borensztein, E., De Gregorio, J. and Lee, J. W. (1998). How Does FDI Affect Economic Growth? Journal of International

Economics, 45: 115-135.

Borensztein, E.; Gregorio, J-De. & Lee, J.W. (1998). How does Foreign Direct Investment Affect Economic Growth? Journal of

International Economics, Vol. 45. pp: 115 – 135.

Bornschier, V., Chase-Dunn, C. & Rubinson, R. (1978). Cross-national Evidence of the Effects of Foreign Investment and Aid

on Economic Growth and Inequality: A Survey of Findings and a Reanalysis. The American Journal of Sociology.

Vol.84. No: 3. pp: 651 – 683.

Busse, M. & Groizard, J. (2006). FDI, Regulations and Growth.

Carkovic, M. & Levine, R. (2003). Does Foreign Direct Investment Accelerate Economic Growth? University of

Carvovic, M., Levine, R., Moren, T.H. Grahma, E.M., & Blomstrom, M. (2005). Does Foreign Direct Investment Promote

Development?

Dae-Bong, K. (2009) Human Capital and its Measurement. OECD World Forum, Busan, Korea.


Zambrut



De Backer, K. & Sleuwaegen, L. (2003). Does Foreign Direct Investment Crowd Out Domestic Entrepreneur. Review of

Industrial Organization, 299 (1), 67-84.

De Jager, J. (2004). Exogenous and Endogenous Growth, University of Pretoria ETD.

De Mello, L.R. (1999). Foreign Direct Investment-Led Growth: Evidence from Time Series and Panel Data. Oxford Economic

Papers. 51, 133-151.

Deaton, A. (1995). Data and econometric tools for development analysis, in Behrman J., Srinivasan T. N. (eds.), Handbook of

Development Economics, Elsevier Science B.V. Vol III.

Didenko, A. Y. (2007). Educational Reforms in Spain and Estonia and their Impact on Human Capital Growth. Master Thesis of

Comparative and International Education, Spain

Dunning, J. (1977). Trade Location of Economic Activity and the Multinational Enterprise: A Search of an Eclectic Approach.

In B. Ohlin, P.O. Hesselborn and P.J. Wijkman (eds.). The international Allocation of Economic Activity, Macmillan,

London.

Durham, J.B. (2004). Absorptive Capacity and the Effects of Foreign Direct Investment and Equity Foreign Portfolio

Investment on Economic Growth. European Economic Review, 48. pp: 285 – 306.

Dutt, A. (1997). The Pattern of Direct Foreign Investment and Economic Growth. World Development, 25(11), 1925-1936.

Elkomy, S; Ingham, H; & Read, R. (2016). Economic and Political Determinants of the Effects of FDI on Growth in Transition

and Developing Countries. Thunderbird International Business Review, 1-16 DOI: 10.1002/tie.21785.

Farole, T. & WinklerMaking, D. (2014). Foreign Direct Investment Work for Sub-Saharan Africa: Local Spillovers and

Competitiveness in Global Value Chains. The World Bank.

Frank, R. H., & Bernanke, B. S. (2007). Principles of Microeconomics (3rd ed.). New York: McGraw-Hill/Irwin.

Fry, M. J. (1993). Foreign Direct Investment in a Macroeconomic Framework – Finance, Efficiency, Incentives, and Distortions.

The World Bank International Economics Department, WPS 1141.

Havranek, T., & Irsova, Z. (2011). Estimating Vertical Spillovers from FDI: Why Results Vary and What the True Effect Is.

Journal of International Economics, 85 (2): 234–44.

Hayat, A. (2016). Foreign Direct Investment, Institutional Framework and Economic Growth. Munich Personal RePEC

Archieve, No. 74563.

Herzer, D., Klasen, S. & Nowak-Lehmann, D.F. (2008). In search of FDI-led growth in developing countries: the way forward.

Economic Modelling. 25, 793-810.

Inekwe, J.N. (2013). FDI, Employment and Economic Growth in Nigeria. African Development Review, Vol. 25, No. 4, pp.421–

33.

Johnson, A. (2006). The Effects of FDI Inflows on Host Country Economic Growth. CESIS Electronic, Working Paper Series.

Paper No. 58.

Joshi, D. K., Hughes, B. B., & Sisk, T. D. (2015). Improving Governance for the Post-2015 Sustainable Development Goals:

Senario Forecasting the Next 50 years. World Development, 70: 286-302.

Kamara, Y.U. (2013). Foreign Direct Investment and Growth in Sub-Saharan Africa: What are the Channels? University of

Kansas.

Kaufmann, D., Kraay, A., & Mastruzzi, M. (2010). The Worldwide Governance Indicators: Methodology and Analytical Issues.

Available online: www.govindicators.org (accessed on 19 April 2016).

Lesher, M., & Miroudot, S. (2008). FDI Spillovers and Their Inter-relationships with Trade. OECD Trade Policy, Working

Paper 80, Organisation for Economic Co-operation and Development (OECD), Paris.

Li, X. & Liu, X. (2005). Foreign Direct Investment and Economic Growth: An Increasingly Endogenous Relationship. World

Development. Vol. 33. No: 3. pp: 393 – 407.

Lucas, R. (1988). On the Mechanics of Economic Development, Journal of Monetary Economics Vol 22, No. 1, 3-42

Mengistu, B., & Adams, S. (2007). Foreign Direct Investment, Governance and Economic Development in Developing

Countries. The Journal of Social, Political and Economic Studies, 32(2), 223-249.

Meyer, K. (2003). FDI Spillovers in Emerging Markets: A Literature Review and New Perspectives. DRC, Centre for New and

Emerging Markets, London Business School, Working Paper No. 15.

Meyer, K., & Sinani, E. (2009).When and Where Does Foreign Direct Investment Generate Positive Spillovers? A Meta-

Analysis. Journal of International Business Studies, 40 (7): 1075–94.

Morrissey, O. & Udomkerdmongkol, M. (2012). Governance, Private Investment and Foreign Direct Investment in Developing

Countries. World Development. 40(3), 437–445.

Nelson, R., & Phelps, E., (1966). Investment in Humans, Technological Diffusion, and Economic Growth. American Economic

Review, Papers and Proceedings 61, 69–75.

Noormamode, S. (2008). Impact of FDI on Economic Growth: Do Host Country Social and Economic Conditions Matter?

University of Neuchatel, Switzerland.

Odenthal, L. (2001). FDI in Sub-Saharan Africa. OECD Development Cetre, Working Paper, 173, March.

Omran, M. & Bolbol, A. (2003). Foreign Direct Investment, Financial Development and Economic Growth: Evidence from the

Arab Countries. Review of Middle East Economics and Finance. 1(3), 231–249.

Raheem, L.D. & Oyinlola, M.A. (2013). Foreign Direct Investment, Governance and Economic Growth Trilogy: New Evidence

from ECOWAS countries. Journal of Global &Science Issues, Vol 1, Issue 2.


Zambrut



Ray, S. (2012). Impact of Foreign Direct Investment on Economic Growth in India: A Co integration Analysis. Advances in

Information Technology and Management 2: 187–201.

Roodman, D. (2009). How to Do Xtabond2: An Introduction to Difference and System GMM in Stata. The Stata Journal, Vol 9,

No, 1, pp.86 – 136.

Schultz, T.W. (1961). Investment in Human Capital American Economic Review, 51, 1-17.

Sen, A. (1999). Development as Freedom: Oxford University Press.

Sen, K. (2013). The Political Dynamics of Economic Growth. World Development, 47:71-86.

Sharpe, A. (2001). The Development of Indicators for Human Capital Sustainability. Centre for the study of living standard,

Canada.

Solow, R.M. (1956). A Contribution to the Theory of Economic Growth. Quarterly Journal of Economics. 70(1), 65-94.

Sunde, T. (2017). Foreign Direct Investment and Economic Growth: ADRL and Causality Analysis for South Africa. Research

in International Business and Finance (41): 434–44.

Thomas, V. & Wang, Y. (1997). Growth and Environment: Allies or Foes? Finance and Development, 34: 22-24.

Tsai, P. (1994). Determinants of Foreign Direct Investment and Its Impact on Economic Growth. Journal of Economic

Development, 19(1), 137-163.

UNCTAD (2015). World Investment Report 2015 – Reforming International Investment Governance. UNCTAD, New York and

Geneva.

Wilhelms, S. (1998). Foreign Direct Investment and Its Determinants in Emerging Economies. African Economic Policy

Discussion, Paper, 9.

Windmeijer, F. (2005). A Finite Sample Correction for the Variance of Linear Efficient Two-Step GMM Estimators. Journal of

Econometrics, 126(1): 25-51.

World Bank (1991). World Development Report 1990: The Challenge of Development. New York: Oxford University Press.

World Bank (2001). Global Development Finance Report. World Bank, Washington, DC

World Bank (2015). Human Capital Index. World Economic Forum.

World Bank Blogs (2018). Human Capital: Working for a World Free of Poverty. IBRD.IDA.

Zambrut Journal, Link Access;

https://zambrut.com

https://zambrut.com/operational-investment/

© Copyright 2019 International Journal of Zambrut | Zambrut, Inc.


https://zambrut.com/operational-investment/


the operational rate of foreign direct investment in …...fagbemi, f. & oladejo, b. 2019. the...

Documents