Introduction

The blooming growth in the scientific and technological areas of human civilization has been overwhelming in recent years, resulting in greater resource exploitation, economic expansion, and detrimental environmental effects. In fact, the whole world, and particularly the African continent, includes a panoply of natural resources that possess remained unexploited for a long time and have been the origin of numerous conflicts among nations. It is worth noting that the exploitation of these resources began during the colonial years, increased after independence and continued to progress thanks to the means of extraction’s modernization. Through their extraction and exploitation, these resources have strongly contributed to the creation of wealth and the degradation of the environment quality.

The debate on environmental sustainability has largely concentrated on analyzing the connections between economic growth, corruption, green energy, foreign direct investment, and CO2 emissions over time (Alam, 2022; Sultana et al., 2022). According to a report from the International Energy Agency (IEA, 2021), total CO2 emissions hit an all-time height of 36.3 gigatons in 2021, despite worldwide efforts to decrease them.

The state of art works on the link between income and environmental degradation postulate the existence of an inverted U-shaped relationship. This corresponds to the premise behind Kuznets’ concept of the environmental curve (1955). Thus, several studies use it as a conceptual basis for the Kuznets environmental curve (KEC) hypothesis (Grossman & Krueger, 1995; Shafik & Bandyopadhyay, 1992; Yilanci & Pata, 2020). This curve shape suggests the presence of a long-term non-linear relationship between economic growth and environmental quality. While these theoretical predictions seem to be clear, the conclusions of the empirical literature on the EKC are by no means unanimous.

Indeed, numerous studies have attempted to account for EKC empirically, with rather mixed results. While some authors have demonstrated the EKC in their research works of Ben Jebli et al. (2016), others have revealed an increasingly monotonic connection between economic growth and environmental quality from Saidi et al. (2017).

As poor countries are getting developed and as the living standard of individuals is getting enhanced, the interest in the EKC lies in the fact that it postulates the possibility for poor countries to promote environmental quality. Various authors have offered a review of empirical investigation on the link between detailed economic growth and environmental quality of Dinda (2004) and Nourry (2007).

From a theoretical perspective, the discussion on the impact of foreign direct investment (FDI) upon CO2 emissions follows the Kuznets environmental curve by Dinda (2004). High levels of pollution are ascribed to significant FDI inflows, as depicted by some authors (Li et al. 2021, Ohajionu et al., 2022). Capital inflows into a country can exert a significant impact on the environment, subject to environmental protection regulations of Panait et al. (2023).

The search for solutions that reconcile growth and preservation of the environment has become a priority. The strategy for combating environmental degradation is carried out on an international scale, mainly through awareness campaigns at summits, which are sources of proposals.

The environmental Kuznets curve was introduced by Shafik (1994), Grossman and Krueger (1995), List and Gallet (1999), and Sharma (2011). The link between economic development and CO2 emissions constitutes a crucial issue for economists (Sulaiman et al., 2013; Danish, 2017, Akhbari et al., 2019; Liang and Yang, 2019). Prior studies have explored this relationship investing various econometric methods and fund that growth is an intrinsic determinant of carbon dioxide emissions (Saidi & Hammami, 2015; Asongu et al., 2016; Aziz et al., 2020).

Over the past years, the corruption role and the correlation between economic income and environmental quality have drawn the widest attention. Corruption affects CO2 emissions, which contributes to pollution (Wang et al., 2020). The issue of corruption and CO2 emissions degradation has become a hot area of research in recent years. Extensive corruption has led to massive exploitation of natural resources and environmental degradation.

Yet, corruption can lead distortion in the design of applying environmental regulations, as well as in the process of enforcing and verifying environmental legislation (Damania et al., 2003; Fredriksson et al. 2016). Corruption is an international problem that affects all countries and all sectors of activity.

Moreover, theoretical research and empirical studies indicated that corruption is a substantial source of environmental destruction by mitigating the severity of environmental policies (Lopez & Mitra, 2000). Ganda (2020) used two indicators, namely the index corruption and corruption rankings, to reveal that corrupt behaviour deteriorates environmental sustainability in 16 Southern African countries.

In 2022, the African region ranked the lowest region at the level of perceived corruption index (CPI), with a score amounting to 32 against 43 globally, on a scale of 100. Between 2004 and 2022, CPI statistics equally indicated that on average 4 to 5 African countries account among the 10 countries regarded to be the most corrupt in the world.

This result is more limited in that it highlights the institutional fiasco that may not only reduce growth and income levels in these economies (Yang et al., 2022), but also reinforce the degradation of their natural capital. It basically corresponds to the very foundation of any sustainable development process (Perrings & Pearce, 1994).

The very high level of corruption in Africa goes in tandem with the poor performance in terms of sustainable development. This can be accounted for in terms of the fact that corruption has the influence of mitigating environmental protection requirements through introducing biases in the adoption and application of these measures of implementing or enforcing them (Habib et al. 2020; Usman et al. 2021). In an environment characterized by corruption, government authorities are inclined to serve their own interests by adopting lax environmental regulations entailing severe environmental degradation (Li & Haneklaus, 2021; Wilson & Damania, 2005; Zhou & Li, 2019). These policies urge companies to adopt severe environmental measures of developed economies. Their central target based on increasing their profits urges them to move their production activities to nations with more lax environmental rules. The relationship between corruption and carbon dioxide has been the crux of several empirical studies, such as those conducted by Sekrafi and Sghaier (2018).

The fossil fuel consumption increase proportionally rises CO2 emissions into the atmosphere (Khan et al., 2020). Pollution brought about by carbon dioxide from various causes exerts a negative impact on human health and largely leads to increase death rate (Nathaniel and Adeleye 2021). The high level of dying in Africa makes the situation even worse and more threatening (Nathaniel & Iheonu, 2019). This is the reason for which the use of renewable energy has become a prevailing tendency owing to these global issues (Fang et al., 2020). In order to secure a green future, we need to shift from non-renewable energy sources to clean energy (Zhang, Yang, et al., 2021). Several works have corroborated that economic progress is essential to combat environmental pollution through the production of renewable energy (Xu et al., 2020). The literature on this issue encourages African economies to promote clean and renewable energy sources, boost environmental quality, and minimize emissions.

Other research works examine the effect of corruption and institutional quality on the transition to renewable energy (Saadaoui, 2022; Saadaoui & Chtourou, 2023). Renewable energy is viewed as a viable solution to a variety of the world’s socio-economic and environmental problems (Rahman & Alam, 2022).

From this perspective, the causes of environmental degradation are not reduced to a single factor, namely corruption, but other factors such as FDI, which also intervene into play.

Danmaraya and Danlami (2021) identified FDI as the driving factor for CO2 emissions, which displays different impacts on environmental quality through compositional, technical scale effects.

It is worth noting that our sample involves such West African nations, with data from 1990 to 2020. It is a limited period for reasons of data availability. Moreover, the aim for opting for these nations resides in the fact that they exhibit the same economic characteristics, the same historical background (colonization and sub-regional integration), and the same monetary policy regime. Owing to data availability, the study centers around nine of these nations uniquely.

The economies of West Africa share much in common with countries in the region that are committed to implementing green investment and financing strategies as well as promoting the investment of new green technologies as well as clean energy so as to foster the environmental condition.

Environmental sustainability is a major concern in West Africa, where the last decade has witnessed a global rise in CO2 emissions. These have increased from 103.76 megatonnes of CO2 (MtCO2) in 2000 to 186.55 Mt CO2 in 2020.

Given all these constraints identified in the above literature, and in order to better explore the effect of the different variables on environmental quality, this research work tends to bridge the gaps by answering the following question: What drives the environmental sustainability in the West African economies? In other words, what is the impact of corruption, FDI, and green energy consumption on the deterioration of environmental quality?

This research enacts original contributions, which can be summarized as follows.

Opting for West Africa as an economic nation is an essential diagnostic tool that is often neglected in the study of the environmental quality at the regional level.

The adopted analytical framework permits to test the validity or not of the Kuznets curve hypothesis in the African context especially in the West Africa region. Since it has been tackled in the literature, the EKC has arisen as a hot topic raising a continuous debate, especially in the recent years. Many researchers have examined its validity for different countries and regions. However, the question of its empirical validity remains ambiguous. Our results contradict the interpretation of the EKC as a basis for formulating environmental policy, implying that the environment deteriorates with economic growth.

Furthermore, there are limited studies conducted in the case of West African countries. To our knowledge, our study is the pioneer to empirically estimate the dynamic relationship among corruption, renewable energy, CO2 emissions, and economic growth using PMG ARDL and to test the pairwise Dumitrescu Hurlin causality.

Additionally, the current study can be regarded as original in terms of analysing the impact of corruption on CO2 emissions, given that it is a constraint to progress in Africa, which corresponds to the most affected region by corruption. Consequently, the introduction of environmental laws and anti-corruption measures can help enhance support for environmental rights, leading to greener and more inclusive economic growth.

The rest of the current research paper is structured as follows: The section 2 is allocated to a literature review that summarizes the main works dedicated to the question of the relationship between economic growth, corruption, FDI, renewable energy, and CO2 emissions. Section 3 tackles the invested data and the applied econometric methods. Section 4 presents the descriptive analysis of data and displays and discusses the work’s findings. Section 5 displays the major conclusions and offers some outstanding recommendations for other research directions.

Literature Review

The environmental debate has given rise to a large amount of research into the factors accounting for the environmental degradation. Research into the existing empirical literature reveals inconclusive results. For this reason, we attempt to address, in this section, the links between renewable energy, income, corruption, and foreign direct investment (FDI) on the environmental quality.

Nexus Between Economic Growth and Environmental Quality

A large corpus of literary works have handled the relationship between CO2 emissions and economic growth applying a variety of methodologies for multiple times periods (Kirikkaleli, 2020; Rahman et al., 2020; Jebabli et al., 2023).

Referring to Grossman and Krueger (1991; 1995), the debate on economic growth and CO2 emissions takes place with the EKC hypothesis. The empirical results with regard to the EKC hypothesis are mixed and the validity of this hypothesis has been the subject of controversy.

In fact, this hypothesis was largely validated (Acheampong et al., 2019; Salari et al., 2021; Bouyghrissi et al., 2022; Hossain et al., 2023; Omri & Saadaoui, 2023). However, the EKC hypothesis has not been validated by panoply of studies (Boufateh, 2019; Pata and Caglar (2021); Massagony and Budiono, 2023).

Different analyses were undertaken for the case of uniquely one country. For instance, Amri et al. (2019) revealed that the EKC hypothesis was not confirmed in Tunisia. Yet, Ghazouani (2021) validated it in Tunisia. The consequences for China have also been softened; Pata and Caglar (2021) rejected the EKC assumption but Zhang and Zhang (2018) validated it. In developed economies, Salari et al. (2021) validated this hypothesis in the USA. Meanwhile, Shahbaz et al. (2017) verified the presence of the EKC hypothesis.

Azam et al. (2016) tackled the relationship between economic growth and CO2 emissions for a panel of economies with high CO2 emissions, demonstrated that there is a positive link between economic growth, and corroborated the deterioration of environmental quality in the United States and Japan. This positive relationship has been validated in other empirical studies and in different contexts. For example, Yousefi-Sahzabi et al. (2011) confirmed that there is a strong positive correlation between economic growth and deterioration in the quality of environment in Iran.

Furthermore, in South Asian countries, Wei et al. (2021) proved the positive relationship between economic growth and CO2 emissions. Omri and Saadaoui (2023) argued that income positively reduces the quality of environment in France. In addition, Onofrei et al. (2022) explored the dynamics of the link between economic growth and CO2 emissions in a sample of 27 European Union Member States. Using dynamic ordinary least squares (DOLS), authors inferred that there is a long-term cointegrating relationship between growth and CO2 emissions.

Furthermore, Goodness and Prosper (2017) addressed the relation between economic growth and carbon dioxide emissions in a sample of developing nation. Adopting the dynamic panel model, they argued that there is a negative relationship between both variables. Shoaib et al. (2020) asserted that, for both developing and developed economies, economic growth reduced environmental quality. In the same vein, other studies have yielded different results regarding this relationship. For instance, Ibrahiem (2020) verified the existence of bidirectional causality. On the other side, Tahir et al. (2021) claimed the existing unidirectional causality between economic growth and environmental quality. Utilizing an econometric panel method, Alaganthiran and Anaba (2022) illustrated that economic growth affects the quality of environment in sub-Saharan African economies.

Nexus Between Foreign Direct Investment (FDI) and CO2 Emissions

The link between CO2 emissions and FDI is referred to in literature as the “pollution haven hypothesis” (PHH). From this perspective, FDI can exert a favourable or an unfavourable effect on the environment, which corroborates either the pollution halo hypothesis or the pollution haven hypothesis (Shinwari et al., 2022; Saadaoui & Chtourou, 2023). For instance, FDI can focus on renewable energy as well as technology transfer and skills development, leading to improved environmental sustainability.

On the other side, FDI can deplete/or reduce environmental sources and increase greenhouse gas emissions (Abdouli and Hammami, 2017; Wang et al., 2023). In particular, Hou et al. (2021) claimed that the pollution haven hypothesis is validated. This result verifies that there is a positive relationship between FDI and environmental quality degradation. Within the same framework, Wang et al. (2023) proved that FDI can reinforce environmental deterioration in a sample of developing countries belonging to the European Union. This result is equally verified by Pata et al. (2022) in the context of developed countries.

On the other side, empirical studies run by Xie et al. (2020); Pata and Samour (2022); and Saadaoui and Chtourou (2023) unveiled that FDI can help reduce pollutant concentrations. This can be ascribed to the fact that FDI attracts high-level production models, which improves environmental quality. Concerning the case of Turkey, Haug and Ucal (2019) found no statistically remarkable relationship between FDI and per capita carbon emissions. This result is also verified by the studies conducted by Danish and Ulucak (2022).

Nexus Between Corruption and Environmental Quality

The corruption threat can have an effect on environment quality (Ganda, 2020; Usman, 2022; Wang et al., 2020). This impact can be direct through reducing the strict environmental regulations, destroying the quality of environment with the rise of CO2 emissions (Yahaya et al., 2020).

In his empirical studies tackling the link between corruption and carbon dioxide emissions, and using a dynamic ARDL approach, Usman et al. (2022) addressed the link between corruption and environmental quality in Nigeria. He proved that corruption lessened environmental degradation. By applying a panel threshold model, Akhbari and Nejati (2019) examined the relation between corruption and environmental quality in developed and developing countries. The result revealed that corruption increases the carbon emission in developing countries but it has no effect at the level of CO2 emissions in developed countries.

Within China’s context, using statistical methods, Wang et al. (2020) revealed that corruption exerts a negative effect on ecological efficiency. According to Bakare and Ozegbe (2022), corruption is likely to impede economic quality and reduce environmental quality. Wang et al. (2018) handled the impact of corruption on environmental quality on BRICS countries. The results proved that CO2 emissions decrease when corruption is controlled.

In Nigeria, Nkemdilim et al. (2023) corroborated that corruption displays a negative and important impact on environmental quality. For a panel of Commonwealth of Independent States countries, Hwang et al. (2023) tackled the influence of corruption on environmental quality using a generalized least squares panel model. The results indicated that corruption directly increases CO2 emissions.

Nexus Between Renewable Energy and Environmental Quality

Several studies considered that renewable energy wields an effect on CO2 emissions (Musah et al., 2023; Usman et al., 2022). Negative relationships have been identified in studies conducted on the effect of RE on the environmental quality. For example, in coastal Mediterranean economies, Sharma et al. (2021) found that RE reduced the carbon footprint in a sample of Asian developing countries.

For 36 developed counties, Sahoo and Sethi (2021) claimed that RE exhibits a positive effect on environmental quality using the FMOLS and DOLS models. Naeem et al. (2023) confirmed the impact of clean energy on reducing CO2 emissions in 29 OECD countries through the use of a cross-sectional autoregressive distributed lags technique.

Fakher et al. (2023) handled the effect of renewable energy consumption on CO2 emissions. They inferred that RE ameliorates environmental quality on Organization of the Petroleum Exporting countries. Using dynamic seemingly unrelated regression equations, they demonstrated the importance of renewable energy in terms of promoting environmental sustainability.

In the same line with these findings, in a South Asian Association for Regional Cooperation (SAARC) region, Khalid et al. (2021) empirically confirmed that renewable energy consumption helps mitigate environmental problems using spatial heterogeneous panel data approach.

Furthermore, using the DOLS approach, Raihan and Tuspekova (2023) confirmed that an increase in green energy in Thailand can entail a reduction in pollutant emissions. This finding goes in good conformity with the study carried out by Mukhtarov et al. (2022) in Azerbaijan.

Furthermore, using the moments quantile regression approach, Liao et al. (2023) suggested that clean energy consumption can promote environmental sustainability in OECD countries.

These results agree well with those found by Aziz et al. (2020) in MINT (Mexico, Indonesia, Nigeria, Turkey) economies by using moment of quantile regression measures. They equally go in good consistency with the findings of Leitão (2021) who used different econometric approaches, panel dynamic least squares (DOLS) (panel fully modified least squares (FMOLS), fixed effects (FE), and panel quantile regression) for BRICS. Likewise, Li and Haneklaus (2022) used the ARDL model for China. In the same regard, Jahanger et al. (2023) performed empirical studies and revealed that renewable energy exerts a negative impact on environmental degradation in Pakistani economies.

However, using a dynamic panel, Çakmak and Acar (2022) clarified that renewable energy consumption did not influence environmental quality in the case of the United States, Canada, China and India, Saudi Arabia, Kuwait, Russia, China, Nigeria, and Brazil. Furthermore, using the generalized quantile regression, Pata and Samour (2022) emphasized that renewable energy does not affect environmental indicators in the case of France. While Farhani and Shahbaz (2014) reported that the increasing use of renewable energy rises CO2 emissions in MENA countries, Xue et al. (2022) highlighted that renewable and clean energy do not significantly reduce environmental impact.

In addition, Ben Jebli and Ben Youssef (2017) recorded that the use of renewable energy, in the long term, increases CO2 emissions for the North African country. Farhani and Shahbaz (2014) stated that the increasing use of renewable energy rises CO2 emissions in MENA countries.

Data Analysis and Methodology

Data

The data established stands for a panel of nine West Africa economies, namely Gambi, Ivory Coast, Mali, Burkina Faso, Sierra Leone, Ghana, Niger, Senegal, and Togo for a period from 1990 to 2020. The selected data have been provided by the World Bank (WDI, 2021), and International Country Risk Guide (ICRG). Table 1 outlines all data invested in the model.

Table 1 Data description, measurements, and sources
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Table 2 illustrates the descriptive statistics for the used variables with respect to a set of 09 West African economies from 1990 to 2020. As previously stated with the data source, all the used variables are transformed into natural logarithm, except FDI.

Table 2 Descriptive statistics of variables
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Methodology

In the current study, balanced panel data of nine West African economies are used.

Cross-Sectional Dependence (CD) and Panel Heterogeneity

According to Pesaran (2007), the cross-sectional dependence (CD) among the variables used may take place. Thus, the finding of the previous data can entail biased outcomes. Referring to earlier works of literature, it is confirmed that evidence from panel models should present a significant cross-sectional dependence in the error. The main target for the cross correlation of errors is assigned to multiple factors such as omitted typical effects and spatial effects as well as unobserved components (Pesaran, 2004a, 2004b). To check the cross-sectional dependence among the variables and in order to further elaborate our empirical analysis, we applied Pesaran (2004a, 2004b) and Breusch and Pagan (1980) cross-sectional dependence tests.

Stationarity

The next step corresponds to confirming the stationarity after tackling the cross-sectional dependence within the modeling of panel data. Multiple unit root tests have been undertaken in the state of art works, such as first-generation and second-generation tests. The most widely used of the first-generation tests are the Levin and Lin (1992, 1993) and Im et al. (2003) whereas Maddala and Wu (1999) tests are motivated by the Dickey and Fuller (1979) tests. These tests rely on the assumption of independence between the panel components. The frequently used second-generation tests are the augmented Dickey-Fuller test (CADF) and the cross-sectional IPS test (CIPS), considering heterogeneous panels (Pesaran, 2007). The second-generation assessments tend to confirm the independence assumption through assuming interdependence among individuals. The validation of this hypothesis is perceived as an advantage to better determine the properties of panels.

Cointegration Tests

The current research work adopts the cointegration test of Pedroni (2004). It considers country heterogeneity referring to the accurate parameters of each country in the sample.

This heterogeneity can be presented in terms of cointegrating relationships, in addition to the level of short-term dynamics. Hence, under the alternative hypothesis, a cointegration link can take place for each country, which may differ from one country to another.

Taking heterogeneity into account is an undeniable advantage, as in practice it is almost rare for the cointegration vector to be the same for every country in the panel.

PMG Regression

The basic advantage of the pooled mean group (PMG) panel cointegration approach, reported by Pesaran (1997) and Pesaran et al. (1999), lies in the fact that the PMG approach considers the time series characteristics of the panel data variables. According to Pesaran et al. (1999), the distinguished approach of the PMG estimator is to take account for panel heterogeneity and endogeneity of series and to supply mixed-stationary. Besides, it is possible to disentangle short- and long-term effects, differences in error variances, and intercepts using the underlying autoregressive distribution lag (ARDL) model. In comparison with different panel estimation methodologies, the PMG approach displays certain additional merits, namely robustness to the outliers and lag orders. To perform the Pesaran et al. (1999) PMG estimation, the ARDL (p, q) models are ascertained in the following manner:

$$\textrm{CO}{2}_{it}=\sum_{j=1}^P{\theta}_{ij}\ \textrm{CO}{2}_{i,t-j}+\sum_{j=1}^{p-1}\Delta {X}_{i,t-j}+{\gamma}_i+{\varepsilon}_{it}$$

where CO2 is the dependent variable and X is the vector of explicatives variables.

Empirical Analysis

The Results of the Cross-Dependency Test

In order to tackle the possible correlation between units, both cross-sectional dependency tests of Breusch and Pagan (1980) and Pesaran (2004a, 2004b) are invested. The findings of both tests are exhibited in Table 3.

Table 3 Cross-sectional dependence results
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The results reveal that the null hypothesis of the existence of cross-sectional dependence is statistically refuted by both tests at the various threshold levels. This finding can be assigned to the likelihood of a shock that may exist in one of these African countries and propagates to the others.

Unit Root Tests Analysis

This stage relies on specifying the stochastic characteristics of the various model variables: Breitung (2000), and the second-generation CADF (cross augmented Dickey-Fuller). The CADF test considers the cross-sectional dependence determined in the earlier estimation phase. The results of the first- and second-generation stationarity tests are displayed in Table 4. According to the outcomes of the LLC unit root test, all variables are I(1) with the exception of the corruption variable, which is stationary at level. In the same respect, the Breitung test predicts that only the variables corruption and CO2 emissions are stationary at level, and the rest of the variables are I (1). Furthermore, applying the CADF test, all variables are integrated of I(1) order, with the exception of the variable CO2.

Table 4 Unit root tests
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The conclusion derived from the stationarity analysis demonstrates that all series are integrated of order I(0) or I(1), and that there is no order I(2).

Cointegration Results

Table 5 summarizes the cointegration test results of Pedroni (1999) and Pedrouni (2004). The results are suggestive of the existence of a long-term cointegration, since the probabilities assigned to the intra-dimensional and inter-dimensional tests validate the rejection of the null hypothesis of no cointegration in each panel.

Table 5 Pedroni cointegration results
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Long-Term and Short-Term Relationships

Table 6 outlines short- and long-term model estimates using the ARDL-PMG approach. The results corroborate the validity of the model grounded on the “ECT” coefficient, which is obviously negative and outstanding at all threshold significance levels.

Table 6 Long- and short-run analyses
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In what follows, the influences of corruption, foreign direct investment, and renewable energy on environmental quality are recorded, while testing the Kuznet curve (lnGDP and LnGDP2).

The coefficients related to the impact of lnGDP are positive and significant at 1% threshold level, indicating that a 1% increase in the economic level in West African countries elevates the level of CO2 emissions. However, in this case, the Kuznet curve is not validated regarding the impacts of both Ln GDP and lnGDP2. In fact, the lnGDP2 is negative but non-significant, supplying a strong evidence of the non-validation of the EKC hypothesis. The non-validation of the Kuznet curve goes in good accordance with studies in the case of African countries, for example Zoundi (2017), Amri et al. (2019), and Boukhelkhal (2022).

In recent years, West African countries have achieved great improvements in their economic growth rates. However, these countries have ambitious goals in terms of boosting the pace of economic growth in order to fix the problems of poverty. This situation will conversely influence the environmental quality in this region.

Moreover, the positive influence of the GDP on CO2 emissions is verified by Mongo et al. (2021) for 15 European countries, Belaïd and Zrelli (2019) for 9 Mediterranean countries, Wen et al. (2021) for Asian countries, and Omri and Saadaoui (2022) for the case of France.

FDI’s effect on CO2 over the long term is positive, highlighting the destructive role of foreign investment on environmental situation over the long term. In the long term, West African countries tend to invest more in polluting industries through FDI. In multiple cases, FDI is considered as a catalyst for CO2 emissions in developing countries. Indeed, these flows may be tempted to relocate polluting industries in developing countries, where environmental regulations are less stringent.

In this regard, it is worth noting that developing countries lure more FDI to boost the economic activity, which may also entail an increase in the use of energy. Therefore, it can significantly decrease the environmental quality. In this case, our results support the haven hypothesis, according to which foreign investment accelerates polluting emissions in West African countries. This outcome is validated by Shahbaz et al. (2019), Demena and Afesorgbor (2020), Danmaraya and Danlami (2022), and Balsalobre-Lorente et al. (2022).

Renewable energy corresponds to a powerful instrument for limiting CO2 emissions in the short and long terms. In fact, it reduces CO2 levels by 2.044 and 1.291, respectively, in the short and long terms. This result calls for the diversification of West Africa’s energy sources, and for taking advantage of its renewable energy potential, especially solar energy. The negative impact of the green energy on CO2 emissions is corroborated in numerous studies such as Saadaoui and Chtourou (2023) who validated the contribution of hydroelectricity generation on reducing CO2 emissions on Turkey. Moreover, Zoundi (2017), Inglesi-Lotz and Dogan (2018), Njoh (2021), and Namahoro et al. (2021) advocated the role of renewable energy on the CO2 emissions within African countries context.

Within the same respect, an improvement in corruption levels in these countries will help stimulate an amelioration of the environmental quality. As far as this study is concerned, the impact of 1% improvement in corruption will reduce CO2 levels to 0.252% at a significant level of 5%. In fact, a corruption prevention mechanism can encourage investment in renewable and green energies that will push the economy towards a sustainable development path (Saadaoui, 2022; Uzar, 2020). In this respect, political decision-makers can direct funds towards this type of investment, which can boost the transition to a low-carbon economy. Basically, anti-corruption measures can help control the use of funds and resources in a responsible and feasible way, which can have a significant impact on reducing polluting emissions.

This impact is emphasized by Sadiq et al. (2023). On the other side, this influence is considered different to other studies such as Leitão (2021), Lv and Gao (2021), and Rahman and Alam (2022).

The short-run analysis confirms only the renewable energy impact on CO2 emissions. However, foreign direct investment reveals a negative impact, which implies that in the short run this investment helps reduce the level of CO2 emissions. As for the GDP capita and the corruption index, they indicate that there are no significant influences in the short term.

The Pairwise Dumitrescu Hurlin Causality

Table 7 outlines the results of the Dumitrescu and Hurlin (2012) causality test, which explores the causal links between GDP per capita, corruption, foreign investment, the proportion of renewable energies in the energy mix, and pollutant emissions in West African countries. Causality results disclose that the relationship between CO2 and corruption is unidirectional, emphasizing the direct effect of climate change on the institutional climate indicated by corruption in West African countries. This result is opposite from the one reported by Sadiq et al. (2023) who discovered a unidirectional causality between both variables.

Table 7 The pairwise Dumitrescu Hurlin causality results.
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In addition, environmental quality causes GDP per capita, and the opposite direction of causality has not been validated. The GDP can directly exert an effect on CO2 emissions, which was confirmed by Dogan and Seker (2016), but inconsistent with what was found by Awan and Azam (2022).

Concerning the relationship between FDI and CO2, the causality analysis indicates that there exist a single causal link running from the FDI variable to CO2 emissions. This outcome differs from the findings of Seker et al. (2015), Tang and Tan (2015), To et al. (2019), and Qamruzzaman (2021).

However, the CO2 and green energy support the hypothesis of neutrality. This link is corroborated by Saidi and Omri (2020). This obtained result is inconsistent with the one reported by Perone (2024) who considered that biofuel, geothermal and biomass, solar, and wind have a unidirectional causality with CO2 emissions. However, there exists a bidirectional causality between hydropower and CO2 for a panel composed of 27 OECD countries. Moreover, Bergougui (2024) argued that RE and CO2 emissions have a unidirectional causality in Algeria.

Conclusion

The present study addressed the dynamic relationship between income, renewable energy, FDI, corruption, and CO2 emissions for West African countries over the period 1990–2020. The ARDL PMG and the pairwise Dumitrescu Hurlin causality are invested to identify both long-run cointegration and causality analysis.

The results of this research are summarized as follows: On the one hand, the findings obtained from both cross-sectional dependence tests of Breusch and Pagan (1980) and Pesaran (2004a, 2004b) revealed the existence of a cross-sectional dependence. On the other hand, unit root panel tests unveiled that all variables are integrated at level I (0) and I(1). Thirdly, the Pedroni cointegration test demonstrated that the variables utilized are cointegrated and hence possess a structural long-run link.

This study yielded valuable results that can help formulate effective procedures for environmental sustainability in West Africa. The results indicated that economic growth and FDI tend to increase CO2 emissions in the long term. On the other side, green energies and the control of corruption can reduce these emissions. The causality analysis suggested that there is a one way of causality from CO2 emissions to both corruption and economic growth, and a one direction causality from FDI to CO2. However, the relationship between renewable and CO2 is neutral.

In the same vein with the obtained empirical results, we hence recommend that, in order to promote growth in West Africa, governments need to adopt convenient energy sector transformation techniques. Particularly, investment in renewable energy has to be promoted so as to place the environment on a sustainable track while undertaking economic growth. In other words, countries need to strengthen their capacity to use renewable energy through adopting policies that facilitate the transition so as to clean energy across the region.

Certain countries have already set up energy transition programs. For instance, under the leadership of the Economic Community of West African States (ECOWAS), the 15 West African countries have elaborated National Renewable Energy Action Plans, with clearly defined targets for access and deployment of renewable energy capacity by 2030. In particular, West African countries should integrate climate change considerations into infrastructure planning and design. Clean, indigenous, and affordable renewable energy solutions offer the region the opportunity to move towards low-carbon development and build resilience, thereby achieving its economic, social, environmental, and climate goals. The massive development and sustainable use of biomass, geothermal, hydroelectric, solar, and wind power on the continent can rapidly alter the region’s current realities.

In accordance with Sustainable Development Goals 7 (SDGs), countries must guarantee that their citizens have access to affordable clean and sustainable energy. Referring to SDG 7, energy use amounts to more than 60% of global greenhouse gas emissions. While renewables are supplying around 17% of global energy consumption emissions, the IPCC foresees that global energy consumption will need to rise to around 85% by 2050 to shun the worst impacts of climate change.

Although the countries of West Africa have recently been experiencing strong economic growth, this has slowed down owing to the deterioration in terms of the environment quality in the region. Owing to their restricted financial resources, which mitigates the likelihood of enacting the massive investments needed for green development on their own, West African economies have undertaken reforms so as to lure FDI. In view of the role of FDI in development, as well as the increase in FDI flows to the nation in recent years, it is quite significant to consider their impact on the environment.

In addition, foreign direct investment has improved environmental degradation, validating the pollution haven hypothesis (PHH), which is not surprising since West African economies depend largely on foreign investment to foster economic growth. West African countries must therefore strive for clean foreign direct investment and aggressive environmental management systems in order to accomplish long-term growth. Moreover, foreign direct investment in energy development infrastructure in the region has mainly focused on power production investing polluting fuels. Governments in the region should either establish strict environmental measures for highly polluting foreign establishments, or sustain foreign companies whose activities contribute to enhancement of environmental sustainability in the region. For example, it would be worthwhile for policymakers and companies in West Africa to set up environmentally friendly policies and procedures that could help them mitigate CO2 emissions. This could be achieved through maintaining barriers to the entry of polluting industries so as to control imports of polluting products..

It is therefore highly recommended that the sub-region adopts ambitions strategies to boost the quality of its institutions. For instance, one West African country has recently embarked on a digitization procedure to promote transparency as well as accountability, and lessen on the other side corruption and needless bureaucratic activities. Multiple neighbouring countries in the sub-region can follow this example to foster their institutions and as a matter of fact maintain long-term environmental sustainability.

To this extent, we would assert that there are certain limitations to this research that need to be highlighted. These shortcomings involve the non-availability of the data for all the variables and all the economies in the region, in addition to the lack of a global regulation of environmental quality to identify the overall impact of emissions. Taking these aspects into account, future research would tend to ameliorate the quality of the presented finding. Future research would thus incorporate additional indicators of environmental quality such as the ecological footprint as an environmental measure degradation, which is a broader indicator that considers all the factors responsible for environmental degradation.