Improving Export Competitiveness Through Free Trade: The Case of Africa

doi:10.21203/rs.3.rs-248203/v1

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Improving Export Competitiveness Through Free Trade: The Case of Africa

https://doi.org/10.21203/rs.3.rs-248203/v1

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In this study, a sample of the largest economies in Africa is used to investigate the impact of free trade on export competitiveness, using panel data econometric techniques on data covering 2000 through 2018. Results from the Pooled Ordinary Least Squares regression and reinforced by the Fixed Effect Model show that the significant positive determinants of export competitiveness are openness, exchange rate, ICT-related infrastructure and the rule of law, whereas corruption and foreign direct investment are significant constraints. Although tariff was found to be positively related to export competitiveness, it is not a significant driver. It is recommended that African countries should initiate and promote policies that enhance the quality and quantity of infrastructure, its institutional environment (encompassing the rule of law and the capacity to address corruption), including attracting the right kind of foreign direct investment that facilitates the utilization of its vast natural resources and transfers suitable technology.

JEL Classification Codes: F10, F15, R10

Health Economics & Outcomes Research

Export Competitiveness

economies in Africa

Pooled Ordinary Least Squares

In several countries, export competitiveness is at the heart of policy discussions. Competitiveness is “the degree to which, under free and fair market conditions, a country can produce goods and services which meet the test of foreign competition while simultaneously maintaining and expanding the real income of its people” (OECD 1992). What this implies is that competitiveness relates both to a country’s trade performance in terms of how internationally competitive it is as well as to the economic welfare of its people.

Export competitiveness has several benefits. Through specialization and integration, it enhances a country’s productivity by promoting the expansion of the domestic market through demand channels, thus improving production, employment and wages. Consequently, specialization and economies of scale are encouraged, while the spillover effects of technical progress help surmount constraints in external growth (Grossman and Helpman 1991).

Export competitiveness can result from free trade as it leverages countries to exploit economies of scale, arising from specialization due to comparative advantages, thereby improving productivity and growth. In light of this, it promotes the development of new products, arising from structural transformation through the transfer of knowledge and technology (International Monetary Fund 2016).

Africa lags behind other regions in virtually all the global competitiveness rankings, underscored on several factors. Essentially, the continent experienced slow growth from late 1970s to early 1980s, after which many of the countries began to implement sound macroeconomic policies in order to improve growth and investment. However, this hardly led to the desired outcome. In particular, the 1990s has been called the “lost decade”. The scenario however began to change in the 2000s, underpinned on low inflation rates, high economic growth rates and improved current account positions, although not without worsening unemployment and poverty rates.

According to the World Economic Forum (2015), majority of African countries are among the least competitive in the world and has rather remained stagnant, despite strong growth in the continent for 15 years. For instance, of all the countries assessed in the Global Competitive Index for 2015, 15 out of the 20 least competitive economies are from Africa. The reasons for the poor outcome include weak institutions, persistent infrastructure deficit, low levels of health and education. Within Africa, some countries were identified to be relatively more competitive, including Mauritius, Rwanda, South Africa, Botswana and Morocco. Although Africa lags other regions in the instituting the basic requirements for competitiveness, it was reported that it does comparatively well in the GCI assessment of efficiency in terms of goods, labour, and financial market.

From the foregoing, the paper investigates the impact of free trade on export competitiveness in Africa, with the following specifics:

To investigate the relationship between free trade and export competitiveness in Africa.
To examine the impact of free trade on export competitiveness in Africa.
To identify the determinants of export competitiveness in Africa.

Following the introduction, the paper is structured as follows. Section two reviews the relevant literature. The methodology is covered in section three. Section four comprises the presentation and discussion of results, while the paper is concluded in section five.

2.1 Conceptual literature

2.1.1 The concept of export competitiveness

The concept of competitiveness appears to be nebulous in the economic literature. Consequently, economists are divided on what it means. Based on the ever changing economic environment, what have been considered to be the various kernels of competiveness (such as specialization, productivity, growth and the like), it is not difficult to see why export competitiveness is conceptually elusive.

According to Krugman (1991, 1996) competitiveness is a largely meaningless notion, when he contends that in applying it to firms within national economies, what separates success from failures in international export markets is the ability to sell goods and secure the bottom line. Several economists including Eifert, Gleb and Ramachanran (2005), Bigsten and Soderbom (2006), and Porter, Ketels and Delgado (2008) have challenged this view.

In another context, Porter, Ketels and Delgado (2008) consider the definition of competitiveness as a zero-sum game, with the result that in competing for share in the international market, an expansion by a country of its share of global markets implies a contraction by another country. Thus, competitiveness is taken to mean a country’s share of the world market. However, this consideration has been faulted because what may lead to an increase in a country’s share in the international market may come from sources that are non-sustainable even though favourable. A good example is exchange rate management in which there is an undervalued currency, so that the competitiveness inherent in such a policy does not reflect the real economy. Moreover, such a condition is merely transient and is not sustainable. Furthermore, it does not enhance the prosperity of citizens due to the preponderance of artificially low wages.

The notion that competitiveness is “the set of institutions, policies and factors that determine the level of productivity of a country” (World Economic Forum 2010, p.4) is helpful in the understanding of the microeconomic and macroeconomic fundamentals. The argument of Porter, Ketels and Delgado (2008, p.2) is persuasive in this regard: “Competitiveness is the fundamental underpinning of prosperity [and] prosperity is determined by the productivity of an economy…Productivity supports high wages, a strong currency, and attractive returns to capital – and with them a high standard of living. Productivity is the goal, not exports per se.”

When applied to a firm, sector or economy, “competitiveness” connotes different things. In terms of a firm, competitiveness means meeting customers’ needs more efficiently and more effectively than other firms do (Edmonds, Jarvis and McGinness 2000). In the context of an industrial sector, competitiveness relates to the maintenance and improvement of its position in the international market (Balkyte and Tvaronaviciene 2010). This is consistent with Sharples and Milham (1990) who consider competitiveness as the ability to provide goods and services in time, at a place and in form needed by foreign buyers at a price equal to or better than that of other potential sellers while earning at least the opportunity cost of the resources used.

Overall, what determine the export competitiveness of an industry or a sector includes the capacity to sell products internationally in terms of quantity, quality, price and time (International Trade Centre 2016). In light of this, several variables affect the capacity to be export competitive.

2.1.2 The concept of free trade

Despite its popularity in the literature, free trade does not seem to have clear and unambiguous definition. This lack of clear definition is partly a result of scholars who seem to assume that “free trade” is obvious (Esty 1994). Although there are several phrases describing what trade should be free of, such as “trade barriers,” “trade restrictions,” and “protectionism,” they generally add to the vagueness of the concept.

The concept of free trade is as old as the economics profession, dating back to Smith (1776) and Ricardo (1817), whose theories merely articulated the reasons for free trade, without actually defining it (Sykes1998). While the former argued that harm would be done to both the country intending to protect its producers via ban or imposition of high import tariffs, as well as the country producing the taxed or banned goods, the latter argued that free trade would engender comparative advantage which would allow each country to produce goods for which it is best suited, leading to a rise in global output and reduce costs.

GATT in its article III describes “free trade,” as trade free of discrimination against foreign goods (Jackson 1992). Although GATT lacks a definition of discrimination, this implies focusing on reduction of tariff, taxes and eliminating rules and regulations that discriminate between foreign and domestic goods. In this study, free trade is conceptualized as the extent to which the flow of goods and services across international boundaries are constrained.

2.2 Empirical literature

The effects and impact of free trade on export competitiveness has been investigated in the economic literature. What can be surmised from the empirics is that various free trade proxies (such as trade liberalization, economic integration, trade openness and trade agreements) are predominantly used while for export competitiveness, concepts such as export performance and export growth are used. Consequently, studies explicitly dealing with free trade and export competitiveness are rare in the empirical literature. The main concerns have been how free trade and its allied concepts benefit member countries, the determining factors and its consequences (Che et al. 2015). The relevant literature for this study is therefore related to trade openness, economic integration, trade agreements and trade liberalization and its impact or influence on exports, export competitiveness or export growth.

Trade Openness: Pillinkiene (2016) used correlation analysis, granger causality and Vector Autoregressive (VAR) econometric method to examine the effects of trade openness on the growth and competitiveness of 11 countries in Central and Eastern Europe from 2000 to 2014. The result confirmed the interdependency of the three variables that is, economic growth, trade competitiveness and trade openness. This implies that economic growth leads to improvement on trade openness and competitiveness of export in this region enhance economic growth. The results of the causality test and the estimated VAR model revealed that economic growth impacts trade openness in the long run, while the effect of competitiveness indicators on GDP per capita is long-lasting.

Economic integration: In a study by Beyene (2014), on Sub-Saharan Africa and, Latin America and the Caribbean, in terms of the exports in five merchandise subsectors covering 1995 to 2010, it was reported that the trade share and economic integration are very low, notwithstanding the progress observed.

Shobande (2019) investigated the effects of economic integration on agricultural export performance in selected West African countries, using gravity model on annual time series data covering the period from1970 to 2016. The empirical evidence was based on pooled regression and fixed effects estimation. The study found that economic integration, measured by trade openness and weighted tariff, is a strong predictor of export performance in the region, and the study recommended among others, the adoption of common currency to boost trade competitiveness. In similar vein, Olayiwola and Ola-David (2013) examined the interaction between economic integration and trade facilitation in ECOWAS countries and the effects of regional blocs in promoting export. Using descriptive statistics for annual data covering the period 1995 to 2009, their findings is in support of regional economic integration. Evidence from their study revealed that sustained growth can be achieved with export growth.

In contrast to the aforementioned studies, a group of studies observed that there seems to be a negative relationship between economic integration or liberalization potential and export performance. This group of studies observed empirically the negative effect of trade liberalization on welfare and internal policy as well as survival of local firms (Panagariya 2003; Baldwin 2006; Jenkins 1997).

Trade agreements: Panagariya (2003), debating on the extent to which optimal conditions are satisfied, argued that Regional Trade Agreements (RTAs) are essential discriminatory policies, given that optimal condition are satisfied. His results showed that the basis of negotiation on regional trade has its welfare effect on the objectives such arrangement seeks to achieve.

Jenkins (1997) in a study on the effects of trade liberalization on resource allocation, productivity growth and export performance, discussed the theoretical arguments which underlined such a policy and the main neo-structuralist criticisms and suggested that the results of trade liberalization have been disappointing. This, according to the study, has given rise to some skepticism concerning the advantages of a wholesale policy of trade liberalisation in a low-income country such as Bolivia.

Nin-pratt, Xinshen and Yonas (2009) investigated the potentials of a Free Trade Agreement (FTA) on the economy of 14 Southern African countries, using bilateral trade data at the four-digit Standard International Trade Classification (SITC). Their findings revealed that the overall effects of an FTA would be positive but insignificant in most countries, indicating that the largest benefits or significant impact would be to the advantages of countries with a regional comparative advantage for export product, while they may still remain inefficient producers of the commodities traded in the region.

Trade liberalization: Several studies regarding whether trade liberalization impacts export growth and performance have been carried out in the literature, using different data set, econometric techniques, in both developed and developing countries and the results are generally mixed. The studies include Coyle et al. (1998), Nin-pratt, Xinshen and Yonas (2009), Cestepe, Yildirima and Bahtiyar (2015), Edmund (2016) and, Bakari and Mabrouki (2018).

The findings of some studies indicated a positive effect (Hoque and Yusop 2012; Hadjiyiannis, Heracleous and Tabakis 2016; Potelwa, Lubinga and Ntshangase 2017; Shobande 2019), while others reported an insignificant or even negative relationship (Greenaway, Morgan and Wright 1999; Jenkins 1997). There are also studies that used single country with their specific effects and others using cross countries with various organizations fostering economic liberalization.

Coyle et al. (1998), using a modified version of the gravity model to analyze the role of different forces underlying the compositional changes in the world trade in the last fifteen years, with specific focus on the supply and demand factors as well as change in transport cost and policy changes found that transport cost and related factors are important determinants in explaining the shift in global trade. Edmund (2016) examined the impact of EU trade liberalization on export competitiveness of ECOWAS countries using gravity model, fixed effects and random effects as well as Hausman tests in a panel data of 15 ECOWAS and EU countries, covering the period from 1995 to 2014. The study captured trade liberalization with import tariff in the EU markets and export competiveness by export value of ECOWAS countries. Their findings reveal that trade liberalization impacts export competitiveness positively. It was reported that a 1% reduction in import tariffs in the EU countries is associated with an increase of 0.487% in export value of ECOWAS countries.

Hoque and Yusop (2012), using the autoregressive distributed lag (ARDL) testing approach for Bangladesh on the impacts of trade liberalisation on export performance from 1972 to 2005, found that trade openness enhances export growth but growth in GDP plays a very significant role in export growth. Likewise, Potelwa et al. (2017), employing a gravity model to investigate trade flow and the factors determining South Africa's export to its cardinal destination between 2001 and 2014, found that increase in gross domestic product (GDP) caused an increase in the country's export.

Cestepe, Yildirima, and Bahtiyar (2015) used fixed effects Least Squares and Generalized Method of Moments estimation technique imbedded in a panel gravity model to investigate the export effects of trade liberalization on 13 Middle East and North African (MENA) countries to 30 trading partners in the Organization for Economic Cooperation and Development (OECD). Trade liberalisation was found to be a useful policy in export promotion. Using fixed effects and generalized method of moments as well as heterogeneous panels with time series and cross section estimation technique based on dynamic panel data models, Santos-Paulino (2002) investigated the dynamic effects of trade liberalisation on export performance in 22 developing countries. Trade liberalization was reported to exert a strong positive impact on export performance, although its impact differed from country to country.

Findings by Baldwin and Gu (2004) on Canadian manufacturing sector indicate that between trade liberalisation and export growth, a positive relationship exists. It was concluded that a reduction in tariff barriers to trade attracts more Canadian firms to enter the export market. Kassim (2013) deployed panel data econometric methodologies to explore the impact of trade liberalisation on the growth of exports and imports in 28 Sub-Saharan African countries from 1981 to 2010. It was found trade liberalisation enhances the growth of exports but the growth of import is faster. The study also revealed that trade liberalization has a significant impact in increasing the price elasticity of demand for exports and imports. In the same way, Greenaway, Morgan and Wright (1999) investigated the effects of the composition of export on economic growth of 69 countries using a dynamic model. The study found out that a strong positive relationship exists between exports and economic growth.

Notwithstanding the findings, majority of the studies are in line with economic principles and theories and also support trade liberalization and why it should be encouraged, other studies have contrary findings. This includes Ratnaike (2012) who considered a panel data approach and a Generalized Method of Moments methodology for 28 OECD countries for the years ranging from 1980 to 2010. The conclusion is that trade liberalisation is largely an insignificant determinants of export performance and that local competitiveness and global demand are more consistent drivers of export performance. Bergés (2007) using long run time series data of market prices of total exports from 1905 to 2000 and free trade zone exports from 1976 to 2000 to investigate trade liberalisation and export growth performance of the Dominican economy finds that trade liberalization does not guarantee export growth unless it is accompanied with improved market access in the destination market.

In relation to econometric techniques, some studies that have applied the gravity model seem to be consistent in their results. For example, in a study carried out by Sohn (2005) on South Korea's bilateral trade flows and practical trade policy applications, it was shown that South Korea's trade followed a Heckscher-Ohlin model, implying that South Korea has a large, unrealized trade potential with Japan and China, which is an indication that the two countries are desirable partners for an FTA. Invariably, North-South Korean trade will increase remarkably, if bilateral relations normalize and North Korea participates in Asia Pacific Economic Cooperation (APEC). Comparably, Bhattacharyya and Banerjee (2006), utilizing the core gravity model reported that around 43% of the fluctuations in India's direction of trade in the period is explained by the technique, as India's trade responds less than proportionately to size and more than proportionately to distance.

From the literature reviewed, it can be observed that results on what factors are critical to export competitiveness are not conclusive and therefore remain an empirical question. Additionally, very little has been done in terms of investigating the case of Africa from the point of view of Africa’s export competitiveness. Importantly, the empirical literature is clear about the role of trade on growth. Its role on export competitiveness is not clearly understood. This study fills that gap.

2.3 Theoretical framework

According to Zhang (2015), being export competitive involves a lot of cost and risks, necessitating huge investment in infrastructure, research and development, interface between firms and research institutes and advanced technology. In light of this, several factors have been found to influence the capacity of a country’s export competitiveness.

The quantity and quality of infrastructure are critical in accessing and participating in the international market (Limao and Venables 2001). Access to and use of Information and Communications Technology (ICT), and electricity, considered as aspects of a country’s infrastructural architecture, are increasingly being noted as critical to trade (see Yoshino 2008; Eifert, Gleb and Ramachanran 2005).

The role of R&D in innovations and new products is emphasized in the empirical literature and help improve the share of export market, which in turn boost R&D efforts (Guarascio, Pianta and Bogliacino 2015). At the international stage, the most successful economies have emphasized the creation of new advantages in complex products, largely determined by new skills and technologies (Lall and Urata 2003), both of which reinforce the need for R&D and high-tech products in a country’s manufacturing exports mix.

FDI can either create or replace trade and therefore may make or mar export competitiveness. For the former, FDI enhances the opening of access to new markets by facilitating exports from the home to the recipient country, through the establishment of marketing and distribution channels. FDI can lead to trade diversion when it becomes a substitute channel of supplying. In this case, domestic production is either displaced by exports of final products from the home country, or foreign affiliate’s exports replace previous home country exports to third countries, as observed by Rivera-Batiz and Oliva (2003). FDI may also result in damaging local and indigenous firms (Nachum, Dunning and Jones 2000), transfer technologies that are not suited for a country’s resources or factor proportions, all of which may constrain the country’s overall comparative advantage (Zhang 2015).

Theoretically, a decline in real exchange rate enhances exports and reduces the impact of external constraints. In light of this, a fall in the relative price of tradables in terms of nontradables goods tends to benefit a country’s export capacity and competitiveness. Devaluation therefore provides a means of promoting international competitiveness (Boltho 1998).

The literature is replete with the growth potential of trade. The experience in several countries, including East Asia and Latin America reinforce the imperative of trade as a critical factor of growth. Considering the World Bank’s framework on export competitiveness encompassing three complementary fundamentals, i.e. the incentive framework, reducing trade related costs and addressing government and market failures, it is clear that trade is facilitated when costs associated with the movement of goods across borders are reduced to the barest minimum (the second framework). In this context, costs encompass a wide range of elements including tariff and non tariff barriers and those relating to the business and institutional environment (such as costs associated with transportation, energy, ICT, transparency, bureaucracy, administration, among others).

Finally, institutions have been implicated in the empirical literature linking lower South to North exports than those relating to factor endowments (see Anderson and Marcouiller 2002). Other institutional factors such as rule of law and corruption have been found significantly impact exports (e.g. Elbadwi, Mengistae and Zeufack 2006).

From the foregoing, an empirical framework and strategy that adequately capture the determinants of export competitiveness is germane.

3.1 Data Sources and definition of variables

The paper utilized panel data covering (2000 to 2017), on 9 countries in Africa, namely Nigeria, South Africa, Egypt, Algeria, Morocco, Kenya, Angola, Ghana and Tanzania. These countries were selected because they are the 10 biggest economies in Africa by GDP in 2019. The choice of period is underpinned on availability of data. Ethiopia was omitted due to non-availability of data for most of the variables. Where there were missing data (for some years), 3-year moving average values were used.

Although differences exist on how export competitiveness’ is conceptualized and operationalized in the economic literature, the paper uses the Revealed Comparative Advantage (RCA), considered as a standard measure of a country’s export competitiveness. RCA index is defined as the ratio of a country’s exports in a particular category of a commodity to its contribution in total merchandise exports (Balassa and Noland 1989). The use of export comparison is better than that of cost in assessing a country’s comparative advantage (Buckley, Pass and Prescott 1988). Thus, RCA helps us determine the progress made by a country in terms of expanding the commodities in which it possesses a trade potential. The RCA index ranges between 0 and +∞. If it is less than 1, the country is not specialized in exporting the product, and if greater than 1, the country is specialized in exporting the product. We concentrate on products in which the sample countries have shown relative export competitiveness. This approach is better than “grossing” or lumping countries together, since competitiveness is not uniform across or even within countries.

Although the literature emphasizes that “what a country exports matters” (Hausman, Hwang and Rodrik 2007), data on high-tech exports in manufacturing exports are not available for most of the countries. The same is true about R&D. Consequently, the two variables were omitted in the study.

We have used three indicators of free trade, namely tariffs, openness and exchange rate. Two measures of infrastructure were adopted in the study, viz gross fixed capital formation and mobile-cellular telephone subscriptions. For the institutional indices, two proxies were employed, i.e. rule of law and corruption. The paper also controls for foreign direct investment, which is indicative of macroeconomic environment. The variables used and their sources are presented in table 1.

Table 1 Variables and their description

Variable	Proxy	Source^*
Export competitiveness	Revealed Comparative Advantage	UNCTAD Database
Free trade	Tariff rate, applied, weighted mean, all products (%)	World Bank
	Openness (Trade/GDP)	World Bank
	Exchange rate	World Bank
Control variables
Infrastructure	Gross fixed capital formation (% of GDP)	ITU
	Mobile-cellular telephone subscriptions	ITU
Institutional Factors	Rule of Law	www.govindicators.org.
	Control of corruption	www.govindicators.org.
Macroeconomic environment	FDI	World Bank

^*Note: World Bank (2020), International Telecommunications Union (2020), UNCTAD (2020).

3.2 Model specification and estimation techniques

Analyzing export competitiveness can be undertaken at the micro (firm), meso (sector), and macro (nation) levels. At the macro level (which is the focus of the intended study), export competitiveness is influenced largely by government actions including a coherent policy framework that attracts FDI, suitable taxation, trade facilitation and reduction of tariff and non-tariff barriers, trade liberalization, and measures to improve institutional quality.

Following the extant literature, a model is specified which relates export competitiveness to free trade, infrastructural, institutional and other key determinants. The empirical model is presented as follows:

where y represents export competitiveness, Xit is a vector of free trade variables, while Zit is a vector of institutional and other control variables, as previously defined. α and the βs denote the intercept term and the parameters to be estimated respectively. The subscript denotes country i to j

(in line with panel data framework), while µ_t is the white noise disturbance term.

Due to the relatively short time for which data are available (2000-2018), the study utilizes the Pooled Ordinary Least Squares (POLS), Fixed Effect (FE) and Random Effect (RE) models, and the best models were selected on the basis of the Breusch-Pagan (LM) and Hausman (1978) tests respectively. Consequently, the dynamics of the panel series were not explored.

4.1 Results

The descriptive statistics and correlation matrix of the variables used in the study are presented in the appendix and are not elaborated due to space constraint.

As earlier stated, three models were estimated and the relevant test statistics implemented to determine the most appropriate model for analysis. The F-stat (1.41646) of the joint significance of differing group means is statistically significant (with p-value of 0.2139521), indicating that the null hypothesis that the pooled OLS model is adequate is not rejected in favor of the fixed effects alternative.

The Breusch-Pagan test statistic (LM is 0.000893429 and p-value is 0.976155) indicates that the null hypothesis that the pooled OLS model is adequate, in favor of the random effects alternative is not rejected. In light of this, the POLS regression results are analyzed in this study and the Fixed Effect model is used for robustness checks. To conserve space, the REM is not reported.

Table 2 Determinants of Export Competitiveness in Africa

	Dependent Variable: Export Competitiveness
	*Variables*	*Coefficient*	*Std. Error*	*t-Statistic*
	Intercept term	-11.98541^*	3.201491	-3.743696
	Tariff	0.262788	0.333395	0.788218
	Openness	1.012832^**	0.508784	1.990691
	Exchange rate	0.134903^***	0.082359	1.637983
	Gross fixed capital formation	0.245757	0.477263	0.514931
	Mobile-cellular telephone subscriptions	0.840078^*	0.126333	6.649716
	Rule of law	1.457494^*	0.516358	2.822641
	Corruption	-1.976714^*	0.560521	-3.526563
	Foreign direct investment	-0.786436^*	0.134566	-5.844248
	Lagged export competitiveness	0.257574^*	0.072704	3.542757
	R²	0.527436
	Adjusted R²	0.491994
	F-statistic	14.88154
	Prob(F-statistic)	0.000000
Diagnostics: Residual variance: 160.374/(130 - 18) = 1.43191; Joint significance of differing group means: F(8, 112) = 1.41646 with p-value 0.2139521 Breusch-Pagan test statistic: LM = 0.000893429 with p-value = prob(chi-square = 0.976155 RESET specification test statistic: F = 0.321491, with p-value = 0.726

Source: Authors’ computations

Results in Table 2 suggest that tariff has a direct relationship with export competitiveness, although it is not statistically significant. This is not consistent with the prediction of theory. Higher tariffs tend to harm trade and consequently the relative ability to compete in the global market place. Thus, tariff does not significantly promote Africa’s export competitiveness,

The coefficient of openness has a direct relationship with export competitiveness and is statistically significant at 5%, implying that less barriers to trade (exemplified by greater trade in exports and imports) is associated with improved export competitiveness. 1% rise in openness (i.e. a rise in total trade relative to GDP) is associated with an increase in its comparative advantage by about 1.01%. Thus, export competitiveness in Africa can be improved if its total trade is given the required impetus.

Another free trade liberalization variable (exchange rate) is directly related to export competitiveness and is statistically significant at 10%. The result indicates that improved competitiveness is due to a regime of floating exchange rate determined by market forces. Statistically, 1% rise in exchange rate (implying depreciation) is associated with an increase in competitiveness by about 0.13%.

The competitiveness indicator and infrastructural variables are directly related. Consequently, gross fixed capital formation and mobile-cellular telephone subscriptions are positively related to export competitiveness and between them, mobile-cellular telephone subscriptions coefficient is statistically significant at 1%. In this context, infrastructure matters for export competitiveness in Africa. On the average, a 1% rise in mobile-cellular telephone subscriptions is associated an increase in export competitiveness by about 0.84%.

As institutional variables (rule of law and corruption) are both statistically significant determinants of export competitiveness. While rule of law shows a direct relationship with export competitiveness, corruption exerts an indirect effect. Both results are consistent with the prediction of theory and are statistically significant at 1%. The results suggest that whiel the rule of law promotes competitiveness, corruption hinders it.

The coefficient of foreign direct investment (FDI) has an inverse relationship with export competitiveness and is statistically significant. 1% rise in FDI is associated with a decline in competitiveness by about 0.79%. Thus, FDI tends to undermine Africa’s competitive potential.

Lastly, the estimated results indicate that export competitiveness is self-reinforcing as shown by its lagged coefficient. Thus past levels and efforts at being competitive are critical towards current drive to compete at the transnational stage.

The diagnostic statistics for the POLS model are satisfactory. On the average, about 49% of the total variations in export competitiveness are explained by changes in free trade, infrastructural, institutional and other associated variables. The F-statistic points to joint significance of the regressors in determining the variations in export competitiveness. Additionally, the model does not suffer from incorrect specification as indicated by the RESET statistic.

For robustness checks, the estimated FEM results are presented in table 4.

Table 3 Robustness checks

Dependent Variable: Export Competitiveness

*Variable*	*Coefficient*	*Std. Error*	*t-ratio*
Intercept	−13.1432^*	3.47877	−3.7781
Tariff	0.822118^**	0.392823	2.0928
Openness	1.4079^**	0.666417	2.1126
Exchange rate	0.183402^**	0.082668	2.2185
Gross fixed capital formation	0.711709	0.659358	1.0794
Mobile-cellular telephone subscriptions	0.457488^*	0.108174	4.2292
Rule of law	−0.20367	0.787112	−0.2588
Corruption	−1.31698^**	0.51765	2.5441
Foreign direct investment	−0.297786^**	0.13807	−2.1568

Note: ^*, ^**and ^*** represent 1%, 5% and 10% level of significance respectively.

Source: Authors’ computations

The results of the Fixed Effect Model in table 3 are comparatively similar to the Pooled OLS, except for the rule of law coefficient which is negative but statistically not significant in the REM. Thus the results reported in the POLS regression are robust to alternative framework.

4.2 Discussion of Results

The discussion of results proceeds along the estimated model which relates export competitiveness to free trade, infrastructural, institutional and the macroeconomic environment. All of these are anchored on the three objectives of the study and consequently linked to the empirical literature.

Free trade and export competitiveness: Tariff was found to have a positive relationship with export competitiveness and it is not a statistically significant determinant of export competitiveness in Africa. This suggests that a rise in tariffs would have no significant impact on Africa’s export competitiveness. This is plausible, given Africa’s export composition which is mostly made up of primary products with high income elasticity. This is consistent with the view that free trade in the form of trade liberalisation by way of tariffs is an insignificant determinants of export performance (Kassim 2013). There is no guarantee that by reducing tariff, Africa’s exports and competitiveness will improve, given the various difficulties in accessing destination markets, in line with Bergés (2007), who found trade liberalization does not guarantee export growth unless there is improved market access in the destination market. Given Africa’s export portfolio, import tariffs in foreign markets can be argued to be more relevant in the context of its export competitiveness, consistent with the findings by Edmund (2016).

Moreover, openness was found to positively and significantly impact export competitiveness. This is in line with previous findings by Pillinkiene (2016) which indicated that there is interdependency among openness, economic growth and trade competitiveness. There is no doubt that higher growth improves a country’s capacity to trade and that openness is critical in that context, and with improved growth comes more capacity to compete. By opening up the economy, export performance can be enhanced which consequently facilitates the ability to penetrate foreign markets, although domestic factors including GDP are crucial, in line with Hoque and Yusop (2012).

It was found that exchange rate has a direct and significant impact on export competitiveness. This is consistent with the prediction of theory. It is argued that a fall in the relative price of tradables in terms of nontradables (i.e. devaluation) boosts exports and reduces the impact of external constraints and competitiveness (Boltho, 1998).

Infrastructure and export competitiveness: The infrastructural indicators in the study were found to have a direct relationship with export competitiveness. Importantly, the influence of ICT embodied in mobile-cellular telephone subscriptions has a statistically significant impact on export competitiveness. Previous findings have emphasized the role that increased access to and use of Information and Communications Technology (ICT), and have on trade (Yoshino 2008; Eifert, Gleb and Ramachanran 2005). In light of this the quantity and quality of infrastructure are emphasized, as they facilitate both the access and participation in the international market (Canning and Bennathan 2000; Limao and Venables 2001).

Institutions and export competitiveness: The institutional variables proxied by the rule of law and corruption were found to significantly impact export competitiveness. While rule of law exerts a direct impact, that of corruption is indirect. Both results are consistent with the prediction of theory. Empirically, the results are consistent with previous findings linking rule of law and corruption to exports (Elbadwi, Mengistae and Zeufack 2006). It is evident that poor and inefficient institutions encumber trade and that better quality of formal institutions coincides with more trade flows (Anderson and Marcouiller 2002). In the light of this, the quality of contracting institutions (embodied in the rule of law and the capacity to deal with corruption) are co-determinants of trade, aside technology and natural endowments (Nunn and Trefler 2015).

Macroeconomic environment and Export competitiveness: Foreign direct investment (FDI) was found to have an inverse relationship with export competitiveness and is statistically significant. This is in line with a priori expectation which links FDI to either a positive or negative role for export competitiveness. The result suggests that for Africa, FDI does not appear to facilitate the opening of access to new markets and could well be damaging to indigenous firms, as found in Nachum, Dunning and Jones (2000). It is arguable if FDI has aided Africa’s needed technologies not suited for its resources or factor proportions, and therefore undermine its overall comparative advantage, echoing previous findings (Zhang, 2015).

The theoretical argument that FDI via multinationals are capable of accessing new markets, improve competition in the country where hosted and contribute to the host country’s export diversification drive (Remla 2012) is not supported in the extant case. Moreover, the results question the view that FDI can augment scarce domestic capital, create new employment outlets and ensure gains from indirect spillover effects on productivity, leading to the preponderance of FDI policies in the developing world as observed by Iwamoto and Nabeshima (2012).

The results of this study differ from previous investigations in one major respect. Whereas previous studies are related to exports and export performance, those of the present study are related to export competitiveness and in particular to a country’s comparative advantage. Thus exports and export competitiveness cannot be said to be explicitly synonymous with export competitiveness, as a country can improve the quantity of its exports without necessarily being more competitive in relation to other countries. In light of this, comparing how a country’s exports fare with another provides a suitable indicator of its competitiveness, a condition captured in the Revealed Comparative Advantage used in this study.

From the foregoing discussion, what determines of export competitiveness in Africa include openness, exchange rate, ICT-related infrastructure, institutions (the rule of law and corruption) and the macroeconomic environment (in terms of foreign direct investment). While openness, exchange rate, ICT-related infrastructure, and the rule of law promote export competitiveness, corruption and foreign direct investment hinder it.

The paper examined the impact of free trade on export competitiveness in Africa, with a view to identifying the determinants of export competitiveness. Using data from secondary sources covering 2000 through 20121 on 9 major African countries and deploying the Pooled OLS and FEM panel econometric techniques, evidence was found linking improved export competitiveness to trade openness, exchange rate, ICT-related infrastructure and the rule of law. Factors found to encumber export competitiveness include corruption and foreign direct investment. Openness, exchange rate, ICT-related infrastructure and the rule of law were found to be positively related to and significantly impact export competitiveness; while corruption and foreign direct investment have a significantly indirect impact. Importantly, tariff was found to be positively related to export competitiveness but not a significant factor.

From the estimated results, the critical gaps in improving export competitiveness in Africa are in the areas of infrastructure, institutions, and the macroeconomic environment. In light of this, the following are recommended:

Policies that enhance the quality and quantity of ICT infrastructure are crucial if the goal of improved export competitiveness is to be achieved. This is pertinent given the imperative of the global environment for trade and the increasing deployment of ICT for competitive advantage.
The institutional environment in Africa should be improved with regards to the rule of law and the capacity to deal with corruption. Because Africa’s financial, goods, and labour markets function comparatively well with similar regions like Latin America, it needs to build upon its comparatively efficient markets by investing in reforms that enhance its rule of law and discourage corruption.
There is the need to enhance Africa’s capacity to attract the right kind of foreign direct investment that particularly facilitates both the exploitation of its vast natural resources as well as the transfer the required technology. Well articulated and coordinated policies are thus called for which attune the needs of the continent to global demand. To this, cautious policies that encourage investment and attract capital and technology to sectors for which the continent has comparative advantage are required.

5.1 Future Research

This study neither makes claims to exhausting the possible impacts of trade on Africa’s export competitiveness nor claims to fully capture its complexity. There are a number of shortcomings which can be addressed in future research. First, the analysis is broadly macroeconomic in nature and thus, analysis at firm level was not undertaken. Second, the focus of this study was on agriculture-related items, for which many African countries exhibit relative comparative advantage. With the kind of income elasticity for most agricultural commodities relative to manufacture, this might tend to indicate that the continent should concentrate on primary products, which should not be the case. The value of and quality of manufactures and trade in services cannot be overemphasized, considering that their contribution to the Africa’s exports has grown over 20 per cent (UNECA and AUC, 2011). Consequently, there is the need to consider the price component of export competitiveness in Africa in future research.

Authors’ contributions

All the authors contributed with respect to conceptualizing the broad objective of the study, the literature review, the econometric analysis, and analyzing the empirical findings. They read and approved the final version of the manuscript.

Funding

The authors did not receive any funding (internal or external) for this study.

Availability of data and materials

All data generated or analysed during this study are included in this published article [and its supplementary information files].

Competing interests

The authors declare that they have no competing interests.

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Improving Export Competitiveness Through Free Trade: The Case of Africa

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Abstract

1. Introduction

2. Literature Review

3. Methodology

4. Results And Discussion

5. Conclusions

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References

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