Economic growth through global value chains; new insight from exchange rate effects on the African economy

Abstract

The study investigated GVC and exchange rate comovements from 1990 to 2018. The study employed a continuous wavelet coherence procedure to investigate the time-frequency dependence of global value chain (GVC) participation and exchange rates relationship in Africa. We find from the study that there is interdependency between exchange rates and global value chain participation only in the very short term for all selected countries. The study finds interdependent and well-governed networks continue to experience muted effects of exchange rate effects on GVC participation while independent firms in countries participating in GVC forward integration are negatively impacted.

Impact statement

The use of continuous wavelet coherence technique to monitor global value chain (GVC) participation levels amidst extreme market volatility offers unprecedented insights for both countries and firms. By enabling the measurement of interdependency between exchange rates and African economies’ participation in GVCs, this approach facilitates informed decision-making and risk management strategies. It empowers stakeholders to gauge the impact of macroeconomic variables, particularly exchange rates, on GVC involvement, thereby fostering adaptability and resilience in an ever-changing economic landscape. Ultimately, this innovation enhances the ability of nations and businesses to navigate volatile market conditions and optimize their engagement in global value chains.

Keywords:

• Economic growth
• macroeconomic mechanisms
• Africa
• global value chains (GVCs)
• exchange rate
• continuous wavelet transformation

REVIEWING EDITOR:

• Goodness Aye University of Agriculture, Makurdi Benue State, Nigeria

SUBJECT:

• Development studies
• Economics and Development
• Economics
• Finance

JEL CLASSIFICATION:

• F15
• F31
• F40

1. Introduction

Exchange rates greatly impact shaping macroeconomic and financial cycles and are the most quoted indices in international economics and finance. They measure competitiveness by quantifying the sensitive nature of a country’s output demand as a function of global prices (Adusei & Gyapong, 2017; Antwi et al., 2020; Chinn & Ito, 2006; Obstfeld & Rogoff, 2005). As such central banks devote time, effort, and resources to computing and analyzing their effect on determinants of investment decisions towards economic growth (Avdjiev et al., 2019; Kearns & Patel, 2016; Patel et al., 2019). In Africa, the reality of exchange rate pressures in the determination of investments, trade, development, and economic growth cannot be overemphasized. Many African countries depend on a narrow range of commodities for foreign exchange, thus, a fall in the global demand for these goods leads to a drop in the value of their currencies as foreign income falls. Notwithstanding, African countries operating exchange rates under flexible exchange rate regimes have criticized it for negatively impacting international trade along the global value chain (Auboin & Ruta, 2013).

Over the past 20 years global trade has changed tremendously influencing major parts of international trade for societal development and growth (Sato & Zhang, 2019). However, with global trade tensions placing strain on global economic and financial systems, the impact of exchange rates on global value chains has attracted wide attention. In Africa, the level of production fragmentation indicates that intermediate goods cross borders multiple times along the value chain often more than once. However, in the case of emerging and frontier African markets, most studies have assumed that these countries export only primary or final goods produced without the use of imported intermediate goods and that a single representative production line characterizes each country. The pitfall associated with these assumptions is that they fail to account for several activities that occur in line with the production-differentiated products across multiple production countries and characterize the level of participation in GVCs per country. For example, suppose that fish products (fish feed) sourced from Nigeria as a raw material for fish farming in Morocco help in the production of the final product of canned fish for Ghanaian consumers. This assumption that Nigeria exports the final good to Morocco; hence a depreciation in Nigeria’s currency hurts Morocco’s competitiveness and stands to be re-examined. In reality, however, a decline in the price of Nigeria’s fish feed could increase demand for Morocco’s output, improving Morocco’s competitiveness (Patel et al., 2019). This kind of assumption has impacted the development of coherent empirical literature on the global value chain effect on growth and development (Johnson, 2018). Consequently, documentation on Africa’s participation level in GVC has not been well documented to account for the magnitude, influence, and identification of underlying periodic trends of exchange rates, interest rates, and inflation among others in the production and sale of final products exported by emerging and frontier African markets as intermediate goods in production structures grow (Alhassan et al., 2021; Patel et al., 2019; Van Biesebroeck & Mensah, 2019; Wang et al., 2022).

The constant flow of global trade through African firms and countries influences exchange rates and global value chain production, which remains contested in literature. Various studies have attributed the variation in GVC participation levels of African countries to the type of measure used be it the level of participation in product processing, classification, and firm-level activities as they do not converge in the same direction, methodological differences and issues in examining credible and consistent data. Thus, any measure employed in the examination of the effect of macroeconomic variables (for example, exchange rate, inflation, and interest rates) on GVC participation levels requires a clear measurement technique that can measure the direction, magnitude, and relationship. By considering the different types of participation levels when discussing African economies, a clear understanding of the impact of macroeconomic varies on global value chains can be provided. Notwithstanding taking cognizance of exchange rate shocks and effects on global value chain participation in policy and literature, there has been no methodical review of the relationship effect on global trade, growth, and development in Africa. Researchers in other jurisdictions have paid little attention to how global value chain production participation is impacted during exchange shocks. We employ continuous wavelet coherence to contribute and bring focus and understanding to the relation. Therefore, we address the relationship between exchange rates and GVC participation level by quantifying the level of participation of African countries. The study selected four African countries from the Regional Economic Communities (RECs) with high participation levels based on the availability of data, market size, entry, and trade barriers, exchange rate volatility, production input and output levels, and trade volumes (Ghana, Nigeria, Morocco, South Africa). We thereby address the relationship through the lens of statistical models, by capturing GVC participation and volatilities in exchange rates within the selected African markets from 1990 to 2018 in this paper. We contribute to the literature on global value chains, growth, and development effects by concentrating on African exchange rate variability by leveraging new development and big data on GVC participation in the production process using macroeconomic series (exchange rates) that capture the various changes and waves that directly influence African markets’ global value chain participation at any point in time for each country considering their market condition (Patel et al., 2019).

Foreshadowing our study, we posit that the exchange rate effect on GVC participation in the selected African countries from the heat maps shows low levels of interdependence in the medium and long term, for Ghana, Nigeria, South Africa, and Morocco. The study found that trade does not significantly impact the GVC participation levels in Ghana and Nigeria, moderate effect in South Africa, and high levels of interdependence in Morocco. GVC participation is highly influenced by GDP per capita and no impact from inflation on GVC participation for all the selected countries.

The remainder of the paper is structured as follows: Section 2 presents the theoretical and empirical review of exchange rates and global value chains; Section 3 presents the methodology employed. In section 4 we present the main empirical results; Section 5 presents the discussion and section 6 presents the conclusion.

2. Review of literature

The global value chain (GVC) and exchange rates relationship has received minute scholarly consideration. In literature, the theory on GVC was built on ‘commodity’ to only standardized products although the theory covered differentiated products (Gereffi et al., 2001). GVC theory has since then focused on organizational disintegration and geographical dispersal of value chain activities for production, highlighting the part lead firms play in establishing GVC networks. Lead firms select the role they play in GVC networks based on the location, allocation, and distribution of value-added resources and activities in production structures Gereffi (1999). Participation in cross-border production has fundamentally reshaped global economic activity in international trade. In light of this, the flow of goods from one organization to the other has advanced economic growth and development. However, under GVC theory the flow of trade is often guarded and does not allow for dispersed interdependencies (Benito et al., 2019). For example, the flow of oil products from an oil mining firm to retailers under the concentrated GVC theory does not allow retailers to adjust transportation routes which could lead to lowering the cost of the product (prices) upon delivery or against any unforeseen circumstances. Consequently, organizations displaying a vertical specialty in global value chains production structures when high import intensity exists their export could experience a decline in response to import prices as and when exchange rate volatility occurs (Hagemejer et al., 2022). For instance, if an oil firm in Nigeria imports intermediate goods, the production of goods for exports could change Nigeria’s exchange rate, which will affect its export price as imported intermediate goods rise. Again, retailers of the final good cannot change or adjust the price of the final good or make changes to any part of the production process due to their lack of independence. Thus, a depreciation (appreciation) in exchange rates positively (negatively) may affect the profitability of exports even as the cost of intermediate goods (inputs) may increase (decrease). During such periods to maintain the level of foreign currency income from the export destination, the firm may adjust the prices of their products in the country of origin’s currency (Niara) to ensure that markups remain stable. Therefore, firms operating under the GVC theory will operate a higher pass-through effect to the local currency while a lower pass-through effect is operated at the destination currency import prices for its exports. The GVC theory strengthens the exchange rate pass-through effect depending on the level of backward GVC participation of suppliers (De Soyres et al., 2018; Georgiadis et al., 2020). The internationalization theory on the other hand is concerned with inter-firm relations in world economies which is based on transaction cost economies (De Marchi et al., 2014; Humphrey, 2014; Narula & Wahed, 2016). The theory seeks out efficiency, building on economic actors’ desire for autonomy by selecting firms with efficient independent governance structures to carry out their business activities in ways that minimize their cost exposure. The internationalization theory seeks to reduce production costs by considering location, technology, production scale, governance of how and who organizes the level of involvement, and the remuneration of economic actors. Countries or firms operating under internationalization theory are not able to effectively deal with changing dynamics along the international production lines due to its flexible style of operation and the independence of firms or countries, which leads to low levels of integration due to a lack of access to relevant information (Petersen et al., 2010). Firms under the internationalization theory are continuously faced with instability, unreliability, and inefficiency issues as more complex situations emerge, with network partners unable to make their adjustments along the value chain for production and distribution as and when changes occur at the macroeconomic level of the originating firm (Contractor et al., 2010; Petersen et al., 2010).

Furthermore, internationalization theory does not consider governance interdependencies across borders as the GVC theory does (Benito et al., 2019). The inflexible nature of power asymmetries and standardization of products under the GVC theory leads to low investment inflows, high coordination, and cost control as firms seek to lower their specific transaction cost along the chain while increasing or maintaining their foreign exchange income (Gereffi et al., 2005). Additionally, when exchange rate prices appreciate or depreciate in the production or receiving country, retailers (distributors) cannot adjust prices without managerial consent from the originating production firm. By this, the lead organizations can suppress any possible practical predispositions amongst the GVC participatory organizations for the good of the entire production structure which firms under internationalization theory cannot do (Kano, 2018). Moreover, economies and firms operating GVC networks under internationalization theory provide a platform for competitive forces over time, which drives out inefficient production methods due to uncompetitive and unstable production from disinterested actors (Benito et al., 2019). On the other hand, where economic actors are heavily invested in the GVC networks, it ensures reliability, quality, and efficiency, leading to competitive and stable production among participating firms or countries (Benito et al., 2013; Petersen et al., 2010). Organizations and countries under the internationalization theory seek flexible arrangements focusing on market (prices), hybrid (tacit information and transaction-specific investments), and hierarchy (firm strategies on ownership and location decisions). GVCs operating by this theory are more concerned with their internal structures, while GVCs under the GVC theory are focused on consolidating power through externalization (Humphrey, 2014; Sako & Zylberberg, 2017; Strange & Newton, 2006).

Exchange rates pass through import prices to affect global value chains, as Auer’s (2015) work on government-controlled appreciation of the Yuan against the US dollar depicts. Consequently, the US producer price rose for imported inputs from China from the exchange rate pass-through effect. Additionally, regional-level producer prices have been documented to strongly influence import input prices for the Asia-Pacific region as the cost of intermediates increases (Auer & Mehrotra, 2014). Nevertheless, the use of the US dollar as the major trading currency in global trade invoicing coupled with high trade prices impacts expenditure switching through exports in the short-term, impacting growth in emerging and frontier economies (Bayoumi et al., 2018; Borin & Mancini, 2019; Boz et al., 2019; Leigh et al., 2017). Exchange rate changes influence long-term growth through trade channels, specifically for export-led growth channels. Developed economies’ trade response to exchange rates leads to an increase in market entry and exported products. Technological upgrades and high-skill production must boost export diversification to achieve growth during currency depreciation (Goya, 2020).

From empirical literature, we find that exchange rate appreciation (depreciation) has a negative (positive) effect on exports under international trade which underscores economic uncertainties and volatilities underlying exchange rates (Auboin & Ruta, 2013; Mayer & Steingress, 2020). Other studies found that aggregation bias negatively affects exchange rate and trade (Bussiire et al., 2016; Mayer & Steingress, 2020; Sato et al., 2016). Again, Bahmani-Oskooee and Gelan (2018) found that exchange rates have a long-term effect on exports. In their study, they examine twelve (12) African economies’ trade and exchange rate relationships. From their studies, the exchange rate volatility effect on exports and imports is inconsistent in the short term on domestic production. Furthermore, exporting firms and countries (manufacturing industry) experience growth decline when exchange rate appreciation mechanisms are implemented (Prasad et al., 2007). For such economies, exchange rate depreciation has been found to increase the manufacturing sector’s (industry) share of GDP and employment as the share of agriculture declines (Caglayan & Demir, 2014). In the Middle East and North African (MENA) countries’ exchange rates have been found to have a positive effect on trade through export demands Louati et al. (2022) while Elsherif and Mohieldin (2020) found exchange rates to affect international trade negatively. Other studies on exchange rate transmission channels continue to focus on the direct and indirect relationship with production structures, investment, and national policies (Broda & Weinstein, 2006; De Backer & Flaig, 2017; Marcolin et al., 2016). From the above works, we find that consideration for the role of GVC participation is not captured in the examination of the transmission channels.

On the other hand, few studies have considered the global value chains and exchange rates relationship. In studies where they have been examined a positive relationship with import prices for small open economies was found and not with other trading partners in the global value chain. Again, strategic placement of complementarities was found to exist when examining GVC networks without investigating the participation levels concerning exchange rates (Casas, 2020; Casas et al., 2017). In studies where global value chains are considered economies were found to be susceptible to exchange rate uncertainties, and exchange rate elasticity lowered when GVC participation increased for exports, this is however disputed (Ahmed et al., 2016; Leigh et al., 2017; Sato & Zhang, 2017; Tang, 2014). In this regard, we seek to investigate the effect on the exchange rate GVC participation relation with a focus on Africa.

3. Methodology

This study employed a quantitative approach using secondary data to examine the relationship between global value chain participation and African exchange rates. The study used data from the World Development Indicator database [WDI] and UNCTAD-Eora Global Value Chain (GVC). The study employed yearly time series for global value chain participation[GVC] and exchange rate[EXC], Gross Domestic Product per capita[GDPpc], Trade (% of GDP) [TR], Inflation, consumer prices (annual %) [INF] from 1990 to 2018, (Casella et al., 2019; World Bank Development Indicators, 2022). The series is based on the availability of data and takes into consideration the discrepancies in exchange rates a vital variable for the analysis. We certify reliability and uniformity, using five (5) macroeconomic datasets, which are annual for GVC participation and gross domestic product per capita [gdppc], inflation consumer prices [inf], trade as a percentage of GDP, real exchange rates [exc] for four (4) African countries, namely, Ghana, Nigeria, Morocco, South Africa. We selected trade, inflation, and gross domestic product per capita as comparative references for examining the direct relationship between GVC and exchange rates. We sought to understand the direct impact of GVC participation on the economy. The countries are grouped based on their level of participation in global value chain activities in Africa subject to data availability. The countries were selected, respectively, based on the highest and second-highest participating economies in GVC structures in their African regional economic communities (ECOWAS, AMU, SADC). We dropped Egypt and Kenya based on the missingness of data for exchange rates. This study tests the association between global value chain participation and African exchange rates. We employ data transformation techniques (for example, cleaning, filtering, and aggregating data) and apply statistical procedures in transforming the selected data to a usable state to examine the relationship between the variables. We employed Continuous Wavelet Transformation (CWT) to identify and isolate periodic signals for the variables of interest. CWT provides stability for the localized time frequency to improve the trade-off between crests, gaps, detected waves, and extraction in the data (Aloui et al., 2018; Wu et al., 2020). The extension of wavelet transformations is used in macroeconomic analysis to manage problems of nonstationary time series. We find CWT as a suitable technique for examining the varying characteristics of nonstationary variables across time and domain space. We decompose the selected time series using the wavelet function to ensure a localized time-frequency space and zero means. We obtained information about the local neighborhood using the decomposed series. We examine the frequency and time-space behavior of the data using a morlet wavelet.

4. Results and interpretation

We examine and present the summarized measures of the relationship between global value chain participation and exchange rates for four (4) African economies. We present the descriptive statistics in Table 1 for the selected data sample from 1990 to 2018, with 29 observations based on data availability for the dependent variable global value chain participation. We observed values for skewness (asymmetry) and kurtosis between −2 and +2 and 7 to +7 as acceptable while large standard deviation values indicate how far the variables are from the mean for GVC participation and exchange rates (Byrne, 2013; Hair & Black, 2010).

Table 1. Descriptive statistics.

	GHANA						SOUTH AFRICA
	GVC	GDPpc	Exc	Trade	Inf	GVC	GDPpc	Exc	Trade	Inf
Mean	1.21E + 06	9.08E + 02	1.00E + 02	7.52E + 01	2.05E + 01	3.42E + 07	5.16E + 03	1.00E + 02	2.17E + 01	6.92E + 00
Maximum	2.89E + 06	2.28E + 03	1.44E + 02	1.16E + 02	5.95E + 01	6.75E + 07	8.74E + 03	1.34E + 02	4.43E + 01	1.53E + 01
Minimum	1.84E + 05	2.53E + 02	6.82E + 01	4.25E + 01	4.87E + 00	7.52E + 06	2.71E + 03	7.07E + 01	1.30E + 00	−6.92E-01
Std. dev.	9.62E + 05	6.85E + 02	1.97E + 01	1.90E + 01	13.2298	2.20E + 07	1.86E + 03	1.89E + 01	1.28E + 01	3.50E + 00
Skewness	0.49495	0.69403	0.453625	0.261056	1.267	0.24315	0.27722	0.26291	−0.1338	0.59707
Kurtosis	−1.4681	−1.13089	−0.49405	−0.67373	0.81506	−1.7231	−1.4291	−1.1807	−0.9902	0.42732
	NIGERIA						MOROCCO
	GVC	GDPpc	Exc	Trade	Inf	GVC	GDPpc	Exc	Trade	Inf
Mean	8.16E + 06	1.36E + 03	1.07E + 02	3.74E + 01	1.85E + 01	6.57E + 06	2.15E + 03	1.04E + 02	6.42E + 01	2.57E + 00
Maximum	1.63E + 09	3.20E + 03	2.73E + 02	5.33E + 01	7.28E + 01	1.27E + 07	3.49E + 03	1.15E + 02	8.57E + 01	7.99E + 00
Minimum	1.84E + 06	2.70E + 02	4.97E + 01	2.07E + 01	5.39E + 00	1.37E + 06	1.22E + 03	9.54E + 01	4.71E + 01	4.42E-01
Std. dev.	5.60E + 06	9.50E + 02	5.18E + 01	8.68E + 00	1.71E + 01	4.37E + 06	8.18E + 02	5.61E + 00	1.24E + 01	2.08E + 00
Skewness	0.25139	0.40267	1.756703	−0.07905	1.916	1.86E-01	0.28095	0.23423	0.19874	1.09181
Kurtosis	−1.7496	−1.42703	2.589091	−0.71335	2.50697	−1.72396	−1.6765	−1.3142	−1.3875	−0.02924

GVC: Global Value Chain participation; GDPpc: Gross Domestic Product per capita; Exc: Exchange Rate.

We employ continuous wavelet coherence to examine the influence of selected macroeconomic variables on GVC participation for the four (4) largest GVC participating economies. The pairwise wavelet coherence (W.C.) plots aid in evaluating the strength of interdependence among the selected variables and GVC participation. The study presents the CWT plots for GVC participation, GDP per capita, exchange rates, and trade. The plots display results for Ghana, South Africa, Nigeria, and Morocco. The exchange rate is selected as the covariate series. The bivariate inquiry is aimed to establish whether the selected macroeconomic variables influence the level of participation of economies in GVC activities. Figures 1–4 indicate the wavelet coherence with phase difference and COI for pairs of data. The horizontal axis shows time while the vertical axis shows the frequency band ranging from low-frequency (high-scale) to high-frequency (low-scale). The COI is displayed as a bell shape, with the area of edge effect beyond which the coherence estimates are spurious. The statistically significant coherence level is set at 5% within the bounded region with a grey contour. The phase arrows indicate the directionality of the coherence while the color bars show the degree and movement of coherence, as movement from the blue areas (weaker coherence) to yellow and red areas (strong coherence), shows the rise in interdependency among the selected variables. In all plots global value chains are used as the first series while exchange rates, gross domestic product per capita, trade, and inflation take the second slot. The morlet continuous wavelet is used to convert the time series for analysis in the time-frequency domain, where 0–4 years represents the short-term, the scale of 4–8 years represents the medium-term, and the scale of more than 8 years represents the long-term. The movement on the graph from the top to the bottom indicates the movement from short-term to medium and long-term horizons.

Figure 1. The Wave coherence and phase difference plots for Ghana.

Figure 2. The Wave coherence and phase difference plots for Nigeria.

Figure 3. The Wave coherence and phase difference plots for South Africa.

Figure 4. The Wave coherence and phase difference plots in Morocco.

From Figure 1 we find interdependency in the short-term horizon from 2006 to 2012, low interdependency in the medium-term horizon, from 1996 to 1999 between global value chains and exchange rates with no interdependency in the long term. We observe an island of strong coherence in the short term between global value chains and gross domestic product per capita with zero phases. In the medium term, we observe strong coherence with right and up arrows indicating the lagging of global value chains over gross domestic product per capita from 2004 to 2011. In the long term, we observe no interdependency between the variables. For the trade and inflation plot, we find moderate levels of interdependency in the short-term and medium-term horizons with no interdependency between global value chains and trade. There however no interdependency between global value chains and inflation in the short and medium term while a moderate interdependency relation is found in the long term from 2002 to 2007. The findings confirm the positive relationship found by Casas et al. (2017) and Casas (2020) during the implementation of production structures for GVC participation and exchange rates.

GHANA.

From Figure 2, for Nigeria we observe strong coherence in the short-term on the scale of 0–4 years from 1999 to 2001 and a moderate coherence from 2009 to 2010. In the medium term, we observe no interdependency between global value chains and exchange rates, which is displayed by the blue color (weak coherence). In the long-term within the COI from 2002 to 2006 the presence of a strong coherence with zero phase is observed. In the case of global value chains and gross domestic product per capita, there is strong coherence from 1995 to 1999 with the global value chain lagging and from 2004 to 2014 in the short-term. There is interdependency found in the medium and long term at moderate levels from 1997 to 2014. The level of coherence in the short term is moderate with low interdependency between global value chains and trade from 2008 to 2013 and strong coherence from 2005 to 2010. In the long term, we find strong coherence from 2004 to 2008. The coherence level between global value chains and inflation is moderate in the short-term; in the medium-term, we observe weak coherence and no interdependency from 1996 to 2012; long-term moderate coherence with a moderate interdependency relationship from 2004 to 2006.

South Africa from Figure 3, we observe strong coherence in the short-term from 2006 to 2009 indicating the presence of interdependency relationship between global value chains and exchange rate. We further observe no interdependency and weak coherence within the COI for the medium and long-term horizons. There is an interdependency relationship between global value chains and gross domestic product per capita and strong coherence from 1995 to 1998. We observe a right and up arrow indicating the lagging of the global value chains against gross domestic product per capita. For global value chain and trade, we observe an island in the short-term with a strong coherence and left and down arrows indicating an out-of-phase with global value chains lagging trade from 2005 to 2012. We observe that from 1995 to 1997 there was a strong coherence in the short term. The relationship between global value chains and inflation in the short term is weak. In the medium to long-term, we observe a movement from blue to red colours indicating the rising level of intensity of the wavelet coherence from 2006 to 2012.

From Figure 4, we observe an island in the short term from 2005 to 2008 with strong coherence with out-of-phase arrows indicating global value chains leading. From 2005 to 2010 we observe movement from blue to red colours indicating a strong coherence presence and no interdependency in the long term among the variables. There is interdependency between global value chains and gross domestic product per capita and a strong coherence from 2005 to 2013 with zero phase; 1995 to 1998 short-term displays a strong coherence in phase with global value chains lagging. In the long-term, we observe strong coherence with right and down with global value chains leading gross domestic product per capita in phase. Furthermore, we observe an interdependency relationship between global value chains and trade with in-phase arrows indicating the lag of global value chains from 2000 to 2010 from the short to medium term. In the long term, we observe moderate coherence and interdependency between the series with zero phases. The interdependency between global value chains and inflation is strong as the plot displays strong coherence and in-phase arrows. This indicates that global value chains lag inflation from 2004 to 2010. We observe a weak coherence and zero phase from the medium to long-term within the COI from 1995 to 2010.

5. Discussion

Over the years, Ghana has been over-reliant on the exploitation of natural resources, much like other resource-rich African economies with low value-added activities. Exports in these sectors are often led by multinational corporations, for which the laws of Ghana favor the repatriation of net profits and dividends, among others, at the expense of re-investment in the country. As such firms operating in Ghana are often found in upstream GVC activities for which under the GVC theory exchange rate pass-through effect is high. These laws continue to push the agenda for GVC participation in upstream trade activities rather than downstream. The participation levels of the country and firms are well governed and inflexible ensuring that foreign exchange income remains high. Thus, the net combined effect of unconditional repatriation and currency depreciation has increased investment in export-led raw materials production compared to value-added intermediate products (Nuhu & Bukari, 2021). Again, the rebasing of the national accounts brought a boost in GDP per capita, with the W.C. plot confirming the lead position of GDP per capita in the drive for higher participation in GVC activities. We find that despite this, the economic complexity and competitiveness remain low with comparative advantage only in natural resources and agriculture production networks (Baah-Boateng & Twum, 2020; Genevieve et al., 2023; World Bank, 2019). The results from Nigeria’s wavelet coherence plots confirm the work of Inyang and Effiong (2021) who find that the level of GVC participation is weakened by a low production base, import-dependent production structure, and capital due to the presence of a high number of independent firms operating along the GVC network. Nigeria’s production strength has been dominated by the production of raw inputs for exports (for example, crude oil, and natural and liquified gas, among others) signaling its strength in forward GVC participation. Nigeria has a high level of over-dependence on imported products due to production process independence leading to low investment in infrastructure to boost the production of value-added products for domestic and foreign markets which need value-added intermediate goods for production activities. The findings from the wavelet coherence plots show that in the short term global value chains interact strongly with trade, gross domestic product per capita, and weakly with exchange rates and inflation. South Africa is a major trading hub for non-resource manufactured products (for example, mining and basic metal products) with strong forward GVC participation through exports. However, their inability to convert positive factor price movements into growth, industrialization, and capitalizing is reflected in the decline of participation levels in downstream GVC activities. This confirms the GVC theory effect among firms in South Africa (Kowalski et al., 2015; Ziemann & Guérard, 2017). Our findings reflect this in the wavelet coherence plot between global value chains, trade, and gross domestic product per capita in the short term. In the case of exchange rate and inflation, we observe strong coherence in the very short term. These findings reflect the stable economy of Morocco within the study period with a stabilized exchange rate regime. This continues to spur trade growth and, consequently, GVC participation, leading to competitiveness and growth (Genevieve et al., 2023; Guechati & Chami, 2021). Although Morocco has not fully integrated global production networks, it remains a strong marginal player in Africa and globally. Despite this, Morocco’s trade, although low, is largely increasing as it takes advantage of GVC-related trade within a constantly changing environment (Louati et al., 2022).

6. Conclusion

Given that GVC production is divided into different production stages to be manufactured across multiple countries, with intermediate inputs crossing multiple borders at different times, country-level participation can be through forward or backward participation. Countries’ and firms’ level of participation in production along value chains could be impacted by exchange rate volatility which affects their trade competitiveness positively or negatively. The responsiveness of exports and imports to exchange rate volatility could offset export revenues or import payments of suppliers and buyers on the value chain.

Based on the results for the selected African economies we find that although they are factor-endowed, these countries have continued to export commodities and import intermediate inputs marking the basis for the high levels of GVC participation. Furthermore, in countries where the economy is sensitive to movements in exchange rates, a depreciation in the country’s currency below the export destination currency could lower the export stimulus (Edwards & Hlatshwayo, 2020). Though various governments, through different policies, have made concerted efforts to restructure their economies and lower dependence on imported manufactured products, this pattern of trade has remained the same with minimal value addition and over-reliance on imported products (Gyeke-Dako et al., 2017). There is a need for Africa’s open economies that rely heavily on imports, to improve value-added exports and increase competitiveness, by considering the creation of strong interdependent GVC networks (Ogunleye, 2014). In African countries, volumes of domestic producers along GVC networks use imported intermediate inputs for export production and have continued to remain independent of each other. These domestic producers remain sensitive to currency pricing, especially due to the high usage of the US dollar as the dominant trading foreign currency in global trade. The impact of exchange rate shocks and or volatility through exports is often muted while imports are not. When exchange rates appreciate or depreciate firms seek to reduce or control costs by passing the cost on to the next GVC participating firm which in most cases drives out inefficient production methods due to uncompetitive and unstable production measures (Benito et al., 2019). The exchange rate pass-through effect therefore, continues to rise for independent firms in countries participating in forward integration while interdependent and well-governed networks continue to experience muted exchange rate effects on GVC participation and global trade relationship.

GVC participation by African economies continues to remain essential to growth and development, as much of Africa’s trade activities from the various sectors are involved in forward (upstream) production feeding into the production and exports of downstream producer networks. The upstream production knowledge in Africa’s context is more evident at the beginning of the production process, with the production of raw materials leaving little room for the scope of upgrading (Foster-McGregor et al., 2015). Low production upgrades have lowered the propensity to introduce new products as an investment into research and development is relatively low, hampering African firms’ participation and integration in the value-added value chain process. There is therefore a need to upgrade production technology in countries and firms in Africa to participate and integrate fully value-added products into their trade activities. Countries such as Morocco and South Africa, which engage in value-added-related activities, mainly in upstream production networks, are a significant contributing factor to their high levels of GVC participation in Africa (Del Prete et al., 2018). In this regard, African countries need to encourage interdependent value chain participation to increase production, technology transfer, and logistic development through private and public partnerships. Again, strong financial policies are needed to upgrade and improve interdependency among GVC networks to boost growth leveraging high labor skills, industrial upgrading, and global networking, for inclusive growth (Ogunleye, 2014). Furthermore, strengthening investment vehicles and increasing opportunities for private sector participation in GVCs through value-added production will impact African trade growth, alongside a reassessment of policies towards the management and improvement of controls to improve GVC participation eventually. Governmental initiatives such as the 1D1F (One District One Factory) program piloted in Ghana could be given a second look by other African economies building on best practices to encourage firms to operate under the GVC theory to reduce possible exchange rate pass-through effect thereby increasing their participation in GVC production processes (Genevieve et al., 2023; Osei et al., 2020; Yussif et al., 2022). These initiatives backed by the implementation of strong monetary and fiscal policies and measures could boost GVC participation in economic growth and development.

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Additional information

Notes on contributors

Genevieve Gyasi

Genevieve Gyasi is a Lecturer/Researcher at the University of Energy and Natural Resources (UENR) in Ghana, with a PhD in Finance from Kwame Nkrumah University of Science and Technology, Kumasi Ghana. She worked as a graduate research fellow at the United Nations Economic Commission for Africa in Rabat, Morocco, North Africa working in the Economics and Social Affairs department from 2019 to 2021. The research fellowship covered topics in macroeconomics, trade, labor, migration, and social affairs. Her current research interest covers International Economics, Finance, and Econometrics topics in Developmental and Financial Economics in Africa. This paper which is part of a series of research projects seeks to address issues that affect the African continent in recent years.

Joseph Magnus Frimpong

Prof. Joseph Magnus Frimpong is a Professor in Finance at the School of Business, KNUST. He is also an Economist and a Business Consultant. He is a director of some successful businesses including Juaben Oil Mills Limited, Juaben-Ashanti, and Sir Magnus Hotel in Kumasi. He was appointed a member of the Governing Board of the National Development Planning Commission (NDPC) of the Republic of Ghana in 2019. Prior to his appointment to serve on the NDPC board, Prof. Magnus Frimpong functioned as a Dean of KNUST School of Business in 2007. He also served as the Head of Department, Department of Accounting and Finance, KNUST School of Business between 2007 to 2015. His wide international experience and in-depth knowledge in Mathematics, Economics, Finance, Econometrics, Research, Entrepreneurship, and Business Consulting have benefited numerous people in academia and industry alike.

Kwame Mireku

Kwame Mireku, Ph.D is an accounting and finance Senior lecturer at Kwame Nkrumah University of Science and Technology. Mireku’s research interests include Financial Literacy, SME Financing, Economic Growth and Financial Stability, Stock market dynamics, Behavioral Finance amongst others.