Regional integration and growth: New empirical evidence from WAEMU

Abstract

This study provides a pioneer analysis of the growth effect of WAEMU integration at the econometric level, unlike the extant literature that relied on descriptive analysis of the sub-region’s trade statistics. The study used robust instrumental variables system GMM regression in the framework of a cross-country growth model and annual panel data for the period 2000 to 2015. Contrary to the widely held view that regional economic integration fosters economic growth of the participating countries, we did not find any empirical support for a positive growth impact of WAEMU integration in West Africa, which may be due to a variety of factors that mainly point to the characteristics of the WAEMU economies. However, the results indicate that foreign direct investment (FDI), institutional quality, capital, labour and the initial real per capita GDP are important drivers of growth in the sub-region. Interestingly, the results further indicate that FDI and institutional quality are the channels through which WAEMU integration may impact on growth in West Africa. The study therefore concludes that policy reforms towards improved institutions and increased FDIs will enhance economic growth in West Africa.

Keywords

Economic integration economic growth GMM regression West Africa

I Introduction

The West African Economic and Monetary Union (WAEMU) was established by seven founding members that signed a treaty in Dakar, Senegal, on 10 January 1994, namely Benin, Burkina Faso, Côte d’Ivoire, Mali, Niger, Senegal and Togo. Guinea-Bissau, a former Portuguese colony and the only non-francophone member, joined the Union on 2 May 1997. WAEMU member states use the West African CFA Franc as a common currency, which was initially pegged against the French Franc at a fixed rate. However, the West African CFA Franc is now pegged after the Euro, following the adoption of the latter by France. The Central Bank of West African States is the central bank serving the eight WAEMU member states. Other countries in West Africa which are non-WAEMU member states include Cape Verde, Gambia, Ghana, Guinea, Liberia, Mauritania, Nigeria and Sierra Leone (Combey, 2017; International Monetary Fund [IMF], 2018).

Historically, the idea to establish WAEMU can be traced to the desire of the member states to expand the goals of the West African Monetary Association (WAMA), a monetary cooperation established in 1963. WAEMU was therefore established not only to integrate monetary cooperation but also to achieve overall economic integration. Accordingly, the Dakar Treaty of 10 January 1994 identified the main goals of WAEMU, namely: to create a common market of member countries to ease the free movement of persons, goods, services and capital; to strengthen the economic and financial competitiveness of member countries through an open and competitive market along with the rationalization and harmonization of the legal environment; the convergence of macroeconomic policies and indicators by instituting multilateral monitoring procedures; coordination of sectoral policies; and harmonization of fiscal policies through establishment of a common external tariff and a common trade policy (Ndiaye and Xu, 2016).

The above goals of WAEMU indicate that policymakers and leaders across the region view regional integration as an essential development strategy, which is vital not only in achieving economic growth and development but also in promoting shared prosperity and regional stability. According to Olomola (2000), the basic motivation has been the desire to offset the seeming political, social and economic weakness of individual countries. Specifically, the thinness of the economy of individual countries in the region is seen as growth retarding, while a well-designed and managed regional integration could bring opportunities for greater economic growth and development (Fielding et al., 2012). The opportunities that integration could offer include spillover of technological innovations and specialization, which in turn could foster productivity growth; economies of scale in production and trade, which could generate lower costs of production and enable the region to compete favourably in globalized markets; and integration of the region into the world economy (Diop et al., 2008; Salisu and Ademuyiwa, 2013; UNCTAD, 2007).

Indeed, economic justifications for regional integration such as WAEMU are well established in the literature. Such integration opens the region and increases intra-regional trade by eliminating national trade barriers (Danquah et al., 2013; Mohanty and Pohit, 2007; Salisu and Ademuyiwa, 2013; Umulisa, 2016). The adoption of common economic policies and ultimately a customs union serves as a catalyst for the expansion of trade within the region and with other countries outside the region (Agbodji, 2008). According to Shuaibu (2015), the intra-regional trade benefits of integration, amongst others, include enlarged regional markets, high capital flows and increased growth. Overall, it is seen that trade and economic integration can drive economic diversification, structural transformation, economies of scale, improved competitiveness of the region, sharing of new technologies and products among cooperating countries and effective integration and participation in the global economy (Salisu and Ademuyiwa, 2013; Umulisa, 2016). Therefore, the overriding goal of WAEMU integration is to stimulate rapid economic growth and development within the region, and ultimately achieve macroeconomic convergence of member states (Aryeetey, 2001).

Figure 1.

Source: Authors’ computation with data from World Development Indicators.

In spite of regional integration efforts for over two decades, economic growth in most WAEMU member states has generally not been impressive. For instance, from 2005 to 2015, the average annual GDP per capita growth was 1.13 per cent in Benin, 1.80 per cent in Côte d’Ivoire, 0.91 per cent in Guinea-Bissau, 1.09 per cent in Mali, 1.67 per cent in Niger, 1.03 per cent in Senegal, and 1.09 per cent in Togo. Indeed, Figure 1 indicates that the growth performance of WAEMU countries in terms of real GDP per capita growth has been generally poor compared to that of non- WAEMU countries in West Africa. Between 1995 and 2015, the average real GDP per capita growth for WAEMU countries stood at 1.19 per cent, whereas that of non-WAEMU countries was 2.62 per cent. These GDP per capita growth rates are quite low, and consistent with the United Nations’ classification of six out of eight WAEMU member states among the most impoverished countries in the world (UNCTAD, 2011).¹ This raises the question of whether the WAEMU regional integration process is significantly engendering growth in West Africa. Accordingly, the specific goals of this study include: (a) to determine if WAEMU integration is a significant driver of growth in West Africa sub-region, (b) to determine the channels through which WAEMU integration influences growth in West Africa and (c) to determine other significant drivers of growth in West Africa sub-region. Overall, this study is aimed at providing econometric evidence that will guide policy formulation towards increased growth in West Africa, unlike the extant literature that are based on the descriptive analysis of the sub-region’s trade statistics (Aryeetey, 2001; Hailu, 2014; Kayizzi-Mugerwa et al., 2014; Page and Bilal, 2001; Shams, 2005; Tuluy, 2017).

The rest of the article is structured as follows; the second section presents the theoretical and empirical literature, while the third section is on methodology, data and descriptive statistics of the variables. The fourth section presents the empirical results of the study, while section five concludes the paper and presents some policy implications/recommendations.

II Theoretical and empirical literature

Economic theories are yet to establish a consensus on the growth effect of economic integration. Economic integration theories explaining this conclusion can be broadly categorized into traditional and new economic integration theories, each reflecting a developmental stage in the evolution of the theories. The traditional theories of economic integration explain the possible benefits of integration and are often referred to as classical theory or static analysis of economic arrangements. The new economic integration theories, which are developed to reflect changing economic conditions and trade environments, are also referred to as dynamic analysis (Hosny, 2013; Marinov, 2014).

Viner’s traditional customs unions theory, which is based on the pioneer work of Viner (1950), provides the first study of the benefits of economic integration that analyses them critically from an economic point of view. It is the first study to define specific criteria for the distinction of the advantages and disadvantages of economic integration by dividing the possible effects of economic integration into the well-known trade creation and trade diversion effects. Trade creation occurs when two or more countries enter into a trade agreement, and trade shifts from a higher cost producer to a lower cost producer among member states. Trade diversion occurs when imports are shifted from a lower price producer from a third country, which is not a part of the integration agreement, to a higher price producer from a member state. This happens when a common customs tariff applied after the integration agreement protects the higher cost supplier from a member state. According to Viner (1950), trade creation increases a country’s welfare while trade diversion reduces it. Thus, countries would have motivation to participate in economic integration when it leads to more trade creation (i.e., gains) than trade diversion (i.e., losses). Other theorists, such as Meade (1955) and Lipsey (1960), have extended Viner’s theory by addressing different issues of economic integration effects. However, all of them come to the conclusion that there is no possible direct answer to the question of whether integration increases global welfare or not.

When it became clear in the early 1960s that Viner’s static analysis of trade creation and trade diversion is not sufficient to assess the impact of integration on welfare, Balassa (1961) and Cooper and Massell (1965) introduced dynamic effects of economic integration as a better means of explaining the economic rationale behind the creation of economic integration schemes. Schiff and Winters (1998) aptly defined the dynamic effects of economic integration as anything that affects the rate of medium and long-term economic growth of the member states participating in the integration agreement. The dynamic theories of economic integration are developed together with the change in global economic conditions. Lawrence (1997) identified private sector participation, foreign direct investment (FDI) and increasing role of services, among others, as the factors behind the dynamic integration efforts. However, Marinov (2014) explained that the main pitfall of dynamic analysis is that, unlike the static one, there is no reliable method for quantitative assessment of dynamic effects. Nonetheless, dynamic effects have a larger impact on economic processes than static ones due to their deeper scope. In fact, Marinov (1999) summarized the dynamic effects of economic integration to include increase of investment expenditure, sustainable increase of demand, consolidation of production and increase of its specialization, improvement of the organization and management of production and production technology, increase of production efficiency, creation of economic growth and so on.

Even though the dynamic analysis of economic integration emerged as a result of recent changes that are shaping the global economy today, some analysts have argued that economic integration theories, especially the classical theories, may not be relevant to integration among developing countries such as the WAEMU integration. In fact, Balassa (1965) specifically explains that the theoretical literature on economic integration discusses customs unions only in industrialized countries. Thus, new theories of economic integration adjusted to the special needs of developing countries have emerged following the pioneer work of Viner. These include the training ground theory and the package approach, among others.² The training ground theory favours protection for the sake of stimulating industrial development in economic integration schemes of developing countries. According to Inotai (1991), this theory explains that during the first phase of integration between developing countries, international competitiveness of these countries can be gradually improved by relying on the regional market in the first phase of industrialization. Free trade among member states and the usually high common external tariff on imports from the outside world should provide temporary protection for infant industries as well as a sufficiently large market for future industrial development. This process, called import-substituting industrialization, will secure sufficient time for the development of the industrial sectors of the member developing countries so that openness to world markets may then come at a later stage after the developing countries have reached a reasonable degree of efficiency and technical development. Thus, economic integration among developing countries may be considered as a stepping stone (or training ground) towards open competition with the outside world after a short period of learning (or training). Critics of this theory have argued, among others, that developing regional markets in many cases are not large enough to enable industrial development in terms of economies of scale so that eventually, protection measures rather than being temporary may actually become permanent (Hosny, 2013).

The package approach is a means of implementing integration among developing economies. It facilitates the integration process and enhances its stability by assuring that each member state is responsible for the implementation of a single integration project within a common package of such projects (Balassa and Stoutjesdijk, 1975). Such a typical package of projects could include transport, communication, public goods, education, science, agriculture, mining, industry and so on. This approach is considered appropriate for developing countries because it aims at increasing their levels of economic growth and development as well as their levels of regional trade. However, comprehensive information regarding the distribution of benefits and costs of each project on each member country should be available so that no member state feels cheated in the integration process. Challenges of financing, monitoring and controlling could potentially hamper the application of this approach.

Overall, it is obvious that the rationale behind economic integration among developing countries, particularly the growth effect of such integration, could not be defined and explained just by the static and dynamic effects that determine integration among developed economies. Thus, the application of the theories presented here to the real-world case of regional economic integration efforts in Africa is still a subject of research. Accordingly, this study contributes towards a more comprehensive understanding of the growth effect of regional economic integration in Africa by providing a pioneer analysis of the growth effect of WAEMU integration at the econometric level. This is unlike the extant literature on the growth effect of WAEMU integration, which is based on the descriptive analysis of the sub-region’s trade statistics.

Empirical literature

Empirical studies have also investigated the interactions between regional economic integration, economic growth and welfare, but the findings are widely divided on the nature of the relationships existing between them. Deme and Ndrianasy (2017) used a gravity model to estimate welfare effects of regional integration. The results indicate that Economic Community of West African States (ECOWAS) has robust trade creation and thus a positive welfare effect on its member countries as a group. Similar results have also been found in Iran and its northern neighbours—that regional economic integration through trade link has positive impact on growth and welfare (Naveh et al., 2012). Nguyen (2015) predicts that trade liberalization reduces poverty and inequality and increases per capita GDP in the low- and middle-income countries. Combining endogenous growth models and economic geography in the study of the impact of regional economic integration on the member and non-member countries of a regional union, Dion (2004) established that regional economic integration impacts growth through inter-regional technology diffusion as knowledge spillovers originating from leading countries spread to lagging partners. Other studies indicating that economic integration is growth enhancing include Henrekson et al. (1997), Coulibaly (2004), Amurgo-Pacheo and Pierola (2007), Jong-Wha et al. (2008) and Nwosu et al. (2013).

Contrary to the foregoing paragraph, some recent studies indicate that economic integration can have negative or no effect on economic growth. Tumwebaze and Ijjo (2015) examined the contribution of COMESA integration to economic growth in the region using a 1980–2010 annual panel dataset and instrumental variables generalized method of moments (GMM) regression in the framework of a cross-country growth model. The results indicate no significant empirical support for a positive growth impact on the region from the integration. The findings of Vamvakidis (1999) also indicate that economic integration impacts negatively on growth, which may be due to the fact that such integrations are usually among small, poor, and very similar economies. Similarly, Golit and Adamu (2014) argued that intra-African trade has not been effective in fostering growth. They noted that wrong policies, such as preferential trade liberalization schemes, encourage African countries to concentrate on trade among themselves and therefore reflect trade diverting effect. They stressed that such policies are no longer tenable because most African countries export the same or similar commodities and maintain the same pattern of trade, which clearly demonstrates the lack of both absolute and comparative advantage that characterize these countries, reflecting in the low volume of intra-regional exports. They finally submitted that regional integration dominated by trade plays a less crucial role in spurring economic growth and recommend that African countries should redefine the goal of regional integration towards ensuring the provision of critical infrastructure, building human capacities and stock of physical capital. Similar work by Baldwin (2003), Bolaky and Freund (2004), Winters (2004), and Chang et al. (2005) support the idea of combining other policy measures, such as investing in infrastructure and building a quality institution, in order to robustly inspire economic growth. Other studies that have also contributed towards a more comprehensive understanding of the growth effect of integration in Africa, especially in West Africa, include Aryeetey (2001), Page and Bilal (2001), Shams (2005), Hailu (2014), Kayizzi-Mugerwa et al. (2014), Tuluy (2017) and the references therein. However, these studies are generally based on the descriptive analysis of Africa’s trade statistics. In other words, they are devoid of econometric work.

In sum, the foregoing review of the empirical literature indicates that even though several studies have examined the relationship between regional economic integration and economic growth, none of the recent studies has specifically focused on the growth effect of WAEMU integration based on econometric analysis. Indeed, the extant literature on the growth effect of regional integration in West Africa has thus far dwelt on the descriptive analysis of the region’s trade statistics. It is the goal of this study to fill this gap in the literature. This is quite important given that WAEMU countries have made considerable efforts in opening their economies to regional trade partners, but there is little or no econometric evidence to show if those regional efforts have delivered on their ultimate goal of engendering and sustaining economic growth in West Africa.

III Methodology

Theoretical framework

The new growth theory indicates that the growth of labour supply and growth of labour productivity are important factors in the economic growth process because they usually lead to an increase in a country’s domestic production and hence economic growth. Growth in labour productivity generally emanates from growth in human capital (i.e., accumulation of skills and knowledge), growth in investment (i.e., accumulation of physical capital) and technical progress (i.e. use of new and better production techniques). Following Tumwebaze and Ijjo (2015), we assume a Cobb-Douglas production function combining capital and labour with constant returns to scale so that aggregate output can be expressed as follows:

Y = A K^{α} L^{1 - α}

(1)

where Y = real economic output, measured in this study as real per capita GDP in constant 2010 US$; A = technical progress; K = capital stock (or investment), measured as domestic credit to private sector in percentage of GDP and L = labour force (or human capital), measured as adult population aged 15–64 years in percentage of total population. The annual real per capita GDP growth is obtained from equation (1) as:

y = a + α k + (1 - α) l

(2)

where a, y, k and l denote the growth rates of A, Y, K and L, respectively.

By assuming non-diminishing returns to the accumulation of both human capital and physical capital, the new growth theory is able to predict the long-term growth effects of economic integration. Indeed, the dynamic theories of economic integration have identified private sector participation, FDI and the increasing role of services as some of the channels through which economic integration, such as the WAEMU integration, may impact on real per capita GDP growth. For instance, such economic integration could grant the participating member states access to a larger regional market through the removal of trade barriers, enhance their ability to attract FDI through the provision of critical infrastructure and improve their institutional quality through increased competition and human capacity development. These may in turn spur economic growth. In what follows, we will rely on this growth framework to specify the model for this study, which will address the following null hypotheses: (a) WAEMU integration is not a significant driver of growth in West Africa sub-region, (b) FDI, institutional quality and trade are not significant channels through which WAEMU integration influences growth in West Africa and (c) other macroeconomic factors such as the initial level of real per capita GDP, the level of human capital and physical capital are not significant drivers of growth in West Africa sub-region.

Model specification

To model the growth effect of WAEMU integration, we extend the cross-country economic growth function in equation (2) by including the variables that capture the foregoing hypotheses. These variables include: initial real per capita GDP, FDI, trade openness and institutional quality. Thus, we express the econometric model in its implicit form as follows:

\begin{matrix} P G D P_{i, t} = f (P G D P_{i, t - 1}, C A P_{i, t}, L A B_{i, t}, \\ F D I_{i, t}, T R A D E_{i, t}, I N S T, \\ W A E M U) \end{matrix}

(3)

where PGDP_i,t is the growth rate of real per capita GDP of West African countries; PGDP_i,t_-1 is the growth rate of real per capita GDP of West African countries lagged by 1 to capture the initial level of real per capita GDP growth; CAP_i,t is the growth rate of capital stock; LAB_i,t is the growth rate of human capital; FDI_i,t is foreign direct investment; TRADE_i,t is (Exports + Imports)/GDP expressed in percentage (i.e., trade in % of GDP), which is a measure of trade openness; INST is the institutional quality dummy variable; and WAEMU is a dummy variable = 1, if the country participates in WAEMU and 0, otherwise. In the case of the institutional quality variable, we follow Alexiou et al. (2014) and use the data from Freedom House, which monitors political freedom in each country on an annual basis using two criteria, political rights (i.e., freedom to participate in the political process) and civil liberties (i.e., rights to free expression, to organize or demonstrate, and to freedom of religion, education, travel and other individual rights). For each country, the INST dummy variable takes the value of 2 for the classification free, 1 for partly free and 0 for not free. We find that the dummy index ranged between 0 and 1 for Burkina Faso, Cote D’Ivoire, Gambia, Guinea, Guinea-Bissau, Liberia, Mauritania, Nigeria, and Togo. For Benin, Cape Verde, Ghana, Mali, Senegal and Sierra Leone, the dummy index ranged between 0 and 2.

For the econometric analysis and following Tumwebaze and Ijjo (2015), we express equation (3) as a log-linear regression, where lowercase variables denote the natural log of the respective uppercase variables:

\begin{matrix} p g d p_{i, t} = α_{0} + α_{1} p g d p_{i, t - 1} + α_{2} c a p_{​} \\ + α_{3} l a b_{i, t} + α_{4} F D I_{i, t} \\ + α_{5} t r a d e_{i, t} + α_{6} I N S T \\ + α_{7} W A E M U + ε_{i, t} \end{matrix}

(4)

where α₀ is the constant term; α₁, α₂, α₃ and α₅ denote the elasticities of real per capita GDP growth relative to the respective variables; and ε_i,t is the stochastic error term. We did not log the FDI variable because some of the values are negative.

This study used a robust instrumental variables system GMM to estimate the coefficients of the variables in equation (4). Among others, the choice of this method is based on the following important features: (a) economic growth is a dynamic phenomenon and system GMM corrects for unobserved country heterogeneity, omitted variable bias and potential endogeneity that frequently affect growth estimations, (b) if heteroscedasticity is present, the GMM estimator is more efficient than the simple instrumental variable (IV) estimator, but if heteroscedasticity is not present, the GMM estimator is no worse asymptotically than the IV estimator and (c) the use of robust estimator ensures that the standard errors are consistent in the presence of any pattern of heteroscedasticity and autocorrelation within panels, that is, the method works to eliminate serial correlation and heteroscedasticity (Blundell and Bond, 1998; Bond et al., 2001). In what follows, we provide an explanation on how each variable in equation (4) is expected to influence real per capita GDP growth.

The convergence hypothesis advanced by the neoclassical growth models suggest that the lower the initial real per capita income, the higher the growth rate in per capita output. In other words, the models predict a negative relationship between initial real per capita GDP growth and long-run growth rate of real per capita GDP so that in the long-run, all countries will have the common growth rate dictated by the common technical knowledge (Barro, 1997; Mankiw et al., 1992; Solow, 1957; Swan, 1965; Tumwebaze and Ijjo, 2015). Hence, the initial level of per capita GDP growth is expected to have a negative effect on economic growth.

Capital accumulation increases the amount of physical capital per worker and hence the overall productive capacity of the economy. Economic growth theories have generally stressed the importance of physical capital accumulation as the most robust source of growth (Artelaris et al., 2007; Jorgenson, 1963). Hence, the coefficient of capital stock is expected be positive. Labour is also expected to stimulate growth based on the neoclassical production and the Solows growth model (Barro, 1997; Iheonu et al., 2017).

FDI is generally expected to promote growth in the host country through the provision of direct capital financing, creation of competition, adoption of new production methods and other positive externalities such as technology transfer (Aurangzeb and Haq, 2012; Kalu and Mgbemena, 2015). However, empirical studies like Iheonu (2016) have observed that FDI crowds out domestic investment in sub-Saharan Africa, which might not be good for its growth prospects. Besides, other studies, such as Dutt (1997) and Saltz (1992) have also found a negative relationship between FDI and growth. Thus, the coefficient of FDI is expected to be positive or negative.

The trade-led growth hypothesis posits that trade acts as an engine for economic growth. However, empirical evidence on the relationship between trade openness and economic growth in developing countries extensively yielded mixed and inconclusive results. While some studies find that trade openness may be detrimental to economic growth (Iheonu et al., 2017; Keho, 2017), others find that trade can promote growth through exposure to competition, efficiency in resource allocation, provision of access to goods and services, among others (Tumwebaze and Ijjo, 2015). Hence, the coefficient of trade openness is expected to be either positive or negative.

The institutional-quality hypothesis explains that the institutional framework within which economic agents interact with each other in an economy affects economic growth and development. This hypothesis further posits that what matters most are the “rules of the game” in a society, which include the prevailing behavioural norms and their ability to create appropriate incentives for desirable economic behaviour (Alexiou et al., 2014; Rodrik and Subramanian, 2003). Most empirical studies in the literature have provided evidence suggesting a positive relationship between institutions that promote economic freedom and economic performance (Acemoglu et al., 2003; Adkins and Savvides, 2002; Dawson, 2003; Easterly et al., 2004; Osman et al., 2012; Rodrik et al., 2004). Therefore, the coefficient of institutional quality is expected to be positive.

Recall that the WAEMU dummy variable takes a value of 1 if a West African country participates in WAEMU and zero otherwise, thereby capturing the effect of WAEMU integration on economic growth in West African sub-region. This regional economic integration is expected to promote growth through market expansion and increased competition (Tumwebaze and Ijjo, 2015). This is because WAEMU has a broad objective that seeks to create opportunities for even the smaller members in a single market for goods and services as well as in the delivery of public goods. In fact, one of the best known initiatives of WAEMU aimed at achieving this broad objective is the adoption of common external tariff rates for all member countries in January 2000. By default, this initiative imposed a higher tariff on goods from all non-WAEMU countries (Aryeetey, 2001). However, it is interesting that there is currently no econometric evidence on the growth effect of this regional integration effort. If the coefficient of the WAEMU dummy variable is found to be positive and statistically significant, it means that WAEMU integration has been growth enhancing. However, if the coefficient is found to be negative and statistically significant, then it means that this integration has not been engendering growth in the sub-region.

Data and preliminary descriptive data analysis

This study used annual panel data for 15 West African countries over the period 2000 to 2015. The choice of this period is informed by the need to account for the developments following the adoption of common external tariff rates by all WAEMU member countries. The countries included in the study are Benin, Burkina Faso, Cape Verde, Côte d’Ivoire, Gambia, Ghana, Guinea, Guinea-Bissau, Liberia, Mali, Mauritania, Nigeria, Senegal, Sierra Leone and Togo. Out of the fifteen countries studied, seven are WAEMU member countries, namely Benin, Burkina Faso, Cote d’Ivoire, Guinea-Bissau, Mali, Senegal and Togo. Niger, which is a WAEMU country, is excluded due to lack of data for some variables. The entire data were taken from the world development indicators database of the World Bank, except for the institutional quality data. The data for the institutional quality variable were compiled from Freedom House database.

Table 1 summarizes the descriptive statistics of the variables. First, let us consider Panel 1, which reports the statistics for the WAEMU countries. We find that Cote d’Ivoire recorded the highest real per capita GDP of US$1469.73 in 2015, while Burkina Faso recorded the lowest real per capita GDP of US$434.76 in 2000. The average real per capita GDP is US$747.04. Togo received the highest FDI inflow of 19.38 per cent in 2011, while Benin recorded the least FDI inflow of −0.90 per cent in 2004. The average FDI inflow is 2.15 per cent of GDP. Togo recorded the highest trade openness value of 125.03 per cent in 2013, while Burkina Faso had the least value of 30.73 per cent in 2003. The average trade is 65.79 per cent of GDP.

Table 1.

Descriptive statistics of the variables

Panel 1: WAEMU Countries
	PGDP	CAP	LAB	FDI	TRADE	INST	WAEMU
Mean	747.0355	15.9321	52.7024	2.1457	65.7858	1	1
Minimum	434.7633	0.4104	49.4544	−0.9002	30.7325	0	1
Maximum	1469.7300	37.6766	55.4294	19.3757	125.0334	2	1
Std Dev.	264.2363	7.7255	1.6712	2.1974	19.6153	0.6873	0
Panel 2: Non-WAEMU Countries
	PGDP	CAP	LAB	FDI	TRADE	INST	WAEMU
Mean	1158.6430	17.5068	54.3629	8.9646	83.3360	1	0
Minimum	271.0221	1.6203	51.0442	−0.8390	21.1244	0	0
Maximum	3405.7820	65.7418	64.3621	89.4760	311.3553	2	0
Std Dev.	895.0215	14.9925	2.5478	13.1304	46.4587	0.7039	0
Panel 3: All Countries
	PGDP	CAP	LAB	FDI	TRADE	INST	WAEMU
Mean	966.5596	16.7719	53.5880	5.7825	75.1459	1	0.5
Minimum	271.0221	0.4104	49.4544	−0.9002	21.1244	0	0
Maximum	3405.7820	65.7418	64.3621	89.4760	311.3553	2	1
Std Dev.	707.4181	12.1565	2.3315	10.2703	37.4515	0.6991	0.4999
Panel 4: Correlation Matrix of the Variables
	FDI	INST	LAB	PGDP	CAP	TRADE	WAEMU
FDI	1.0000	−0.0811	0.1586	−0.0758	0.0613	0.4003	−0.3319
INST	−0.0811	1.0000	0.1551	0.3000	0.3293	−0.0117	0.1109
LAB	0.1586	0.1551	1.0000	0.6151	0.5939	0.3331	−0.3561
PGDP	−0.0758	0.3000	0.6151	1.0000	0.7360	0.0693	−0.2909
CAP	0.0613	0.3293	0.5939	0.7360	1.0000	0.2533	−0.0648
TRADE	0.4003	−0.0117	0.3331	0.0693	0.2533	1.0000	−0.2343
WAEMU	−0.3319	0.1109	−0.3561	−0.2909	−0.0648	−0.2343	1.0000

Source: The authors.

Note: Notations for the variables relate to the model in equation (3).

Panel 2 of Table 1 reports the statistics for non-WAEMU countries. Here, we find that Cape Verde recorded the highest real per capita GDP of US$3405.78 in 2011, while Liberia recorded the lowest real per capita GDP of US$271.02 in 2003. The average real per capita GDP is US$1158.64. Liberia received the highest FDI inflow of 89.48 per cent in 2003, while Guinea recorded the least FDI inflow of −0.84 per cent in 2014. The average FDI inflow is 8.96 per cent of the GDP. Liberia recorded the highest trade openness value of 311.36 per cent in 2007, while Nigeria had the least value of 21.12 per cent in 2015. The average trade is 83.34 per cent of GDP.

On a comparative basis, we find that on the average, non-WAEMU countries recorded higher real per capita GDP, FDI inflow in percentage of GDP and trade in percentage of GDP. This underlines the important question that motivated this study, namely is the WAEMU integration contributing significantly to economic growth in West Africa? In fact, the statistics in Panels 1 and 2 are consistent with the plots of average real GDP per capita growth earlier shown in Figure 1. However, the statistics did not show any remarkable difference between the WAEMU and non- WAEMU countries in terms of institutional quality. In West Africa as a whole, Panel 3 indicates an average per capita GDP of US$966.56, while the corresponding values for FDI inflow in percentage of GDP and trade in percentage of GDP are 5.78 per cent and 75.15 per cent, respectively. A closer observation reveals that these values are all higher than the corresponding values for the WAEMU countries in Panel 1. The standard deviation indicates that most of the variables witnessed substantial variations. The correlation matrix of the variables is reported in Panel 4, and it shows that collinearity is not a problem in this study.

Empirical results and discussion

This study used a dynamic panel data approach in the estimation of equation (4) in order to avoid the problems of heteroscedasticity, serial correlation, reverse causality and potential endogeneity of the regressors, and to correct for unobserved country heterogeneity and omitted variable bias. This involved the application of robust instrumental variable system GMM procedure, which produces consistent estimates of the parameters of interest and their asymptotic variance-covariance (Arellano and Bond, 1991; Arellano and Bover, 1995; Blundell and Bond, 1998; Bond et al., 2001).

The results of the estimations are reported in Table 2. Panel A excludes the WAEMU variable as well as all the interaction terms. Panel B includes the WAEMU variable, but excludes all the interaction terms. Panel C includes all the variables in the study, plus the interaction terms, while Panel D excludes the WAEMU-Trade interaction term, whose coefficient is not statistically significant in Panel C. In all, we find that the results qualitatively follow similar patterns.

The results in Table 2 indicate that the effect of initial per capita GDP growth is positive and statistically significant at the 5 per cent level. This result suggests that the initial per capita GDP impacts significantly on the economic growth of West African countries, contrary to Tumwebaze and Ijjo (2015), but consistent with Levine and Renelt (1992). In a study of 101 countries from 1960 to 1989, Levine and Renelt (1992) found that the initial level of real GDP per capita, the growth rate of international trade and the rate of investment were important drivers of GDP per capita growth. The results also indicate that capital and labour force have positive and significant effect on economic growth. These findings are consistent with theoretical expectations as well as recent empirical findings on the drivers of growth in West Africa such as Iheonu et al. (2017).

Table 2.

Estimation results (dependent variable: real per capita GDP growth)

Regressors	Panel A	Panel B	Panel C	Panel D
Constant	−8.7599 (4.7096)***	−9.1466 (4.8652)***	−8.8413 (4.9392)***	−8.8781 (4.7476)***
Initial per capita GDP growth	1.0429 (0.4677)**	1.0287 (0.4453)**	1.0277 (0.4588)**	1.0356 (0.4794)**
Capital	0.7357 (0.2151)*	0.7064 (0.1973)*	0.7739 (0.2367)*	0.7021 (0.2012)*
Labour	6.9945 (1.1696)*	7.4633 (1.2418)*	7.3411 (1.3039)*	7.5085 (1.4898)*
FDI	0.9273 (0.1431)*	0.8242 (0.1198)*	0.8334 (0.1384)*	0.8436 (0.1411)*
Trade	−0.1355 (0.1613)	−0.0551 (0.0889)	−0.0395 (0.0416)	−0.1018 (0.0925)
Institutional quality	0.9365 (0.0925)*	0.9882 (0.0689)*	0.9768 (0.0867)*	0.9653 (0.0887)*
WAEMU		−1.4542 (0.8357)***	−1.5778 (0.8717)***	−1.4987 (0.8014)***
WAEMU*FDI			0.4392 (0.2072)**	0.4919 (0.2196)**
WAEMU*institutional quality			0.4248 (0.0822)*	0.4401 (0.0896)*
WAEMU*trade			−0.2503 (0.5108)
Observations	225	225	225	225
Number of countries	15	15	15	15
Arellano–Bond test for AR(2) in first differences [Z-value]	−1.1516	−1.0759	−1.0144	−1.073
Arellano–Bond test for AR(2) [Prob > Z]	0.2495	0.2820	0.3104	0.2833
Arellano–Bond test for AR(3) in first differences [Z-value]	1.1383	1.0208	1.0558	1.0083
Arellano–Bond test for AR(3) [Prob > Z]	0.2550	0.3073	0.2911	0.3133
Sargan Test [Chi² value]	30.4859	30.097	29.9672	30.0844
Sargan Test [Prob > Chi²]	0.1067	0.1089	0.1304	0.1096

Source: The authors.

Notes: Robust standard errors are reported in parenthesis. *, ** and *** denote significance at 1, 5 and 10 per cent, respectively.

The coefficient of FDI is positive and significant, which is consistent with theoretical prediction and generally in line with the empirical literature (Artelaris et al., 2007; Aurangzeb and Haq, 2012; Iheonu et al., 2017; Kalu and Mgbemena, 2015; Tumwebaze and Ijjo, 2015). This result stresses that investment or physical capital accumulation is an important source of growth in West Africa sub-region. It also reflects the fact that FDIs usually bring about several positive externalities, such as technology transfer, adoption of better production techniques and increased competition, which in turn enhance the productivity capacity of the domestic economies. The United Nations Conference on Trade and Development (UNCTAD) Statistics indicate that West Africa as a region has averagely received annual FDI inflows of US$13 billion since 2008 (see FDI inflows for ECOWAS in Appendix 3). This is a remarkable improvement over the average figure of US$4.5 billion that it received from 2000–2007, as well as the US$3.93 billion received in Economic and Monetary Community of Central Africa (CEMAC) from 2008 to 2017.

Contrary to the trade-led growth hypothesis that trade liberalization fosters economic growth through spillover effects, we find that trade openness impacts negatively on economic growth in the sub-region. However, its impact is not statistically significant. This finding is consistent with some studies that found that trade openness may be detrimental to economic growth in West Africa (Iheonu et al., 2017; Keho, 2017). This may be due to the fact that bilateral trade between WAEMU member countries is more in terms of trade diversion than trade creation as a result of economic distortions that encourage illegal trade, which in turn significantly reduce bilateral trade within the Union (Agbodji, 2008). Appendix 1 reports the trade flow statistics for the West African countries in 2016. The overall patterns in this statistics indicate that except for Gambia, intra- regional trade (i.e., trade with other WAEMU and non-WAEMU West African countries) did not exceed 27 per cent of each country’s total global trade. In addition, the statistics show that all the countries recorded negative trade balance, except Côte d’Ivoire and Nigeria. These are consistent with the regression results, which indicate that the role of trade is unimportant. Furthermore, Appendix 2 reports the regional trade for WAEMU and other selected regions. The patterns also indicate low trade volumes in West Africa relative to other regions like South Asia, which is also consistent with the results.

The results indicate that the coefficient of institutional quality is positive and statistically significant throughout, suggesting that institutional quality is an important growth driver in West Africa. This result is consistent with the institutional-quality hypothesis, which explains that the institutional framework within which economic agents interact with each other in an economy affects economic growth and development (Alexiou et al., 2014; Rodrik and Subramanian, 2003). Empirical studies that have found similar evidence suggesting a positive relationship between institutions and economic performance, particularly among African economies include Alexiou et al. (2014), Osman et al. (2012), Iheonu et al. (2017) and Anthony-Orji et al. (2019). Again, the data from Freedom House, which monitors political freedom in each country on annual basis using the two criteria of political rights (i.e., freedom to participate in the political process) and civil liberties (i.e., rights to free expression, to organize or demonstrate, and to freedom of religion, education, travel, and other individual rights), indicate that all the countries in this study are classified as either free or partly free since 2007, except Côte d’Ivoire, Gambia and Mauritania. This also indicates improvement relative to the periods before 2007.

Overall, the region has witnessed some improvements in institutional quality and FDI inflows in the last decade, which is consistent with the regression results that FDI and institutional quality are important drivers of growth in the region. Essentially, the regression results suggest that with further improvements in institutional quality, such as improvements in control of corruption, government effectiveness, regulatory quality and rule of law, the region should be able to attract more FDI like the developing economies in Asia that received an average of US$427.3 billion FDI inflows from 2008 to 2017. Herein lies the key policy implication of the paper, which is that policymakers and leaders in the region can drive growth through improved institutional quality and enhanced FDI inflows.

Contrary to the widely held view that regional economic integration fosters economic growth of the participating countries, the empirical results in Table 2 indicate that WAEMU integration has a negative and statistically insignificant effect on economic growth in the West African sub-region at the 5 per cent level. This finding is consistent with some empirical studies which suggest that regional economic integration among developing countries has so far failed to impact positively on economic growth (Oyejide, 2000; Shams, 2005; Tumwebaze and Ijjo, 2015; Vamvakidis, 1999). The failure of regional economic integration to foster economic growth in Africa has been attributed to a variety of factors which mainly point to the characteristics of African economies. These factors include: the dependence by most African economies on primary products and basic minerals as main exports; the export of the same or similar commodities by most African countries which shows lack of both absolute and comparative advantage; lack of full range of tools by the governments in the region to ensure sustained growth; the adoption of wrong policies such as preferential trade liberalization schemes that have been found to possess trade diverting effect; and lack of critical infrastructure, among others (Chang et al., 2005; Golit and Adamu, 2014; Hailu, 2014).

Recall that the dynamic theories of economic integration identified FDI and a host of other variables as channels through which economic integration, such as the WAEMU integration, may impact on real per capita GDP growth. Accordingly, this study investigated the roles of FDI, institutional quality and trade as likely channels through which WAEMU integration influences growth in West Africa. The results in Panels C and D indicate that only FDI and institutional quality are significant channels through which the influence of WAEMU integration may be felt, while the role of trade remained muted. This is consistent with Amadou (2013) which explained that WAEMU countries have not fulfilled all convergence criteria, protocols and conventions agreed upon by member countries so that trade openness can impact on economic growth. It is also consistent with Golit and Adamu (2014) which recommended that African countries should redefine the goal of regional integration towards ensuring the provision of critical infrastructure and building human capacities and stock of physical capital.

We subjected the estimates in Table 2 to two important specification tests, namely the Sargan tests of overidentifying restrictions and the Arellano-Bond test for error serial correlation at the second order (AR2) and at the third order (AR3). The results indicate that in all cases, the null hypothesis that the population moment conditions are correct and the null hypothesis of no autocorrelation are not rejected.

Conclusion and policy implications/recommendations

WAEMU was established not only to integrate monetary cooperation but also to achieve overall economic integration among member countries with the overriding goal of stimulating rapid and sustainable economic growth and development within the West African sub-region. Hence, the main goal of this study is to investigate if the WAEMU integration has been playing an important role in the economic growth of countries within the sub-region. To do this, the study estimated a cross-country growth model from 2000 to 2015 using instrumental variable system GMM regression. The results indicate that contrary to the widely held view that regional economic integration fosters economic growth of the participating countries, there was no evidence to suggest that WAEMU integration had a positive effect on economic growth in West Africa. However, the results indicate that the most robust drivers of growth in the sub-region are FDI, institutional quality, capital, labour and the initial real per capita GDP. The results further indicate that FDI and institutional quality are the most robust channels through which the WAEMU integration impacts on economic growth, while the role of trade openness remained negligible throughout.

In view of the above findings, we therefore recommend that there is a need for consistent policy reforms that will enhance and increase capital accumulation, human capital development and resource mobilization for higher investment. Policies that encourage FDIs should be supported and implemented to achieve this. There is also need to embark on institutional reforms and continuous improvement in the political and social environment for the WAEMU countries. This will ensure a more liberal democracy that is deeply commitment to freedom, human rights, equal citizenship, economic and socio- political inclusion. These will help West African countries maintain quality institutions that can attract more FDIs and promote sustained economic growth and development. The results also have policy implications for the structural transformation of West African economies in order to make them more attractive to prospective investors. This can be achieved through the removal of bottlenecks to private and public investments, increased investment in basic infrastructure to drive productivity, increasing government support to micro, small and medium scale enterprises, formalization of land ownership and transparency in the enforcement of property rights.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The authors received no financial support for the research, authorship and/or publication of this article.

Footnotes

Appendix

Appendix 3.

Foreign direct investment inflows measured in millions of US Dollars

Year	WAEMU	ECOWAS	CEMAC	Africa	Developing Economies in Asia
2000	513.53	2,094.68	552.64	9,651.02	142,034.11
2001	563.35	1,998.06	1,467.19	19,974.55	122,996.00
2002	622.29	2,845.93	2,028.64	14,743.89	94,954.37
2003	472.69	3,261.96	2,279.22	18,230.78	130,709.92
2004	628.06	3,252.39	1,094.17	17,725.16	175,731.63
2005	782.79	6,312.21	1,741.41	29,473.06	224,575.71
2006	854.58	6,892.88	1,063.53	34,538.97	293,523.24
2007	1,592.56	9,415.62	3,347.19	51,152.19	353,172.38
2008	1,669.12	12,014.70	2,557.21	58,131.94	378,488.88
2009	2,537.44	14,767.32	4,658.67	56,506.91	316,313.26
2010	2,281.74	11,893.75	4,558.07	46,687.09	412,870.91
2011	3,302.59	18,337.56	3,710.39	46,746.84	416,849.97
2012	2,584.60	15,485.71	1,870.55	51,984.99	405,845.43
2013	2,799.43	13,354.17	3,052.87	50,789.53	415,393.78
2014	2,651.16	11,646.69	2,929.50	52,440.50	459,970.96
2015	2,364.89	9,677.27	6,215.29	56,633.00	516,406.95
2016	2,206.44	12,423.24	5,775.50	53,189.63	475,347.43
2017	2,639.29	10,977.65	3,985.60	41,772.30	475,839.21

Source: United Nations Conference on Trade and Development, UNCTAD Statistics. Foreign direct investment: Inward and outward flows and stock, annual. http://unctadstat.unctad.org/wds/TableViewer/tableView.aspx?ReportId=96740

Notes

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