Female economic inclusion, financial access and environmental degradation in Sub-Saharan Africa: policy synergies and thresholds

Over the past decades, environmental deterioration has sparked global concern (Mignamissi and Djeufack, 2022; Ndour and Asongu, 2024). According to Khan et al. (2021), the development and survival of humanity are seriously threatened by climate change, resulting in severe weather, wildlife loss, and food shortages (Ahmad et al., 2022a, b). The adverse impacts of the latter are increasingly widespread across the world, leading to catastrophic impacts on all aspects of society (Mignamissi et al., 2024). Thus, environmental deterioration is today one of the major obstacles that could jeopardize the economic sustainability of both developed and developing countries (Farooq et al., 2023). Accordingly, environmental degradation has reached a worrying level and there is a growing strand of recent studies on policy measures by which the phenomenon can be mitigated. Therefore, the main question of the present research focuses on assessing how the impact of women’s economic inclusion on environmental degradation in Sub-Saharan Africa is lessened when women have access to financial services.

First, among the 17 SDGs, environmental indicators are among the least to progress, which explains the limited progress in environmental protection (Arora and Mishra, 2019). The atmospheric release of carbon dioxide (CO₂) is among the primary causes of environmental degradation. One of the main targets of the SDGs is to reduce these emissions (Suki et al., 2020). Consequently, CO₂ emissions are to blame for global warming, which alters the climate and has an incidence on environmental quality worldwide. It is anticipated that Africa would see the worst effects of climate change (Kifle, 2008). In recent years, CO₂ emissions have also increased in emerging nations, which obviously embody those in sub-Saharan Africa (SSA).

Second, the significant impact of access to the financial sector on environmental performance is important. According to Tamazian et al. (2009), an increase in credit allocation at a lower borrowing cost can make it easier to acquire energy-saving technologies and reduce CO₂ emissions, which contributes to environmental preservation. Improving access to services provided by financial institutions is therefore crucial for people since it offers a way to get the money needed to buy eco-friendly technology that lowers carbon emissions. High energy consumption has been observed in SSA countries, which could lead to environmental pollution. Environmental pollution, which is a problem in SSA, would be lessened by the adoption of energy-saving technologies through an affordable lending program that is available to a larger audience. Taking into account what has been mentioned previously, it is therefore not surprising that access to financial services is perceived in this study as the variable influencing the link between gender economic inclusion and environmental deterioration. This study also aims to fill a gap in the literature.

Third, the research works closest to the subject of this study are those of Khan et al. (2021) and Ndour and Asongu (2024). The former has examined the correlation between financial inclusion and environmental degradation. The latter has assessed the links between women’s economic inclusion and environmental sustainability, also taking into account the moderating role of ICTs. In addition, there are various works in the literature that closely align with the position adopted by this study, classified into two categories. The first addresses the effect of financial inclusion on the environment; for example, the research of Le et al. (2020) and Ahmad et al. (2022a, b). The second group of studies has focused on examining the impact of women’s economic participation in the labor market on the environment. This is the case, for example, with the studies of Wang (2022) and Achuo et al. (2023). In contrast to earlier studies, this one focuses on the impact of access to financial services on the link between women’s economic inclusion and environmental degradation. As such, it adds value to the current literature by demonstrating how financial inclusion can influence environmental outcomes, taking into account gender.

In this section, the theoretical underpinnings of the nexus between gender economic inclusion and environmental degradation are presented, along with an overview of the significance of financial access in influencing the relationship between gender economic inclusion and environmental degradation. In this section, we address three main aspects: (1) the theoretical bases of the link between gender economic inclusion and environmental deterioration; (2) contextualizing the theoretical foundations to be in harmony with the problem statement and (3) the testable hypothesis. The underlying aspects are substantiated in the same order as previously mentioned.

Firstly, the theoretical relationship between economic gender inclusion and environmental deterioration is mainly based on the relevance of gender economic inclusion in allowing women to have greater access to economic resources and technologies. This would enable them to adopt more sustainable agricultural and resource management practices, which would help reduce carbon dioxide emissions. The underlying links are articulated by two fundamental theoretical foundations that deserve to be substantiated: (1) the theory of Economic Empowerment and Environmental Sustainability and (2) the theory of Ecofeminism which are discussed in more detail in the following paragraphs.

According to the theory of Economic Empowerment and Environmental Sustainability, it is established that the economic empowerment of women can have beneficial consequences on the environment. Women can invest in eco-friendly technologies and sustainable practices by making use of economic possibilities and financial resources. However, if these opportunities are not accompanied by environmental awareness, they can also lead to an increase in economic activities that harm the environment. The development of women’s economic and managerial skills plays a vital role in preserving the environment; without which, environmental sustainability may be compromised (Achuo et al., 2022). As a result, this study’s conception of women’s economic inclusion as the main strategy for resolving environmental challenges is in line with this strand of theoretical underpinnings. Additionally, this is consistent with the body of research on the value of gender inclusion in sustainable development (Tchamyou et al., 2025).

The “Ecofeminism” hypothesis, posited by Françoise d'Eaubonne in 1974, looks at how women and nature interact and how these interactions affect environmental policies (Dailey, 2017). To resolve environmental problems, Ecofeminism suggests a review of gender relations and a sustainable promotion of the economic inclusion of women. According to Achuo et al. (2023), women’s engagement in the workforce contributes significantly to reducing environmental pollution in both low-income and high-income countries. Furthermore, intensifying and increasing female participation in the labor market would lead to a significant reduction in carbon emissions (Wang, 2022). Women are therefore crucial in protecting and preserving the environment (Rao, 2012). It is thus, necessary to include more women in decision-making processes as well as provide them with financial resources in order to promote environmentally friendly economic practices and reduce ecosystem deterioration. Therefore, the economic integration of women, by providing them with financial means, allows them to actively engage in sustainable economic activities. This may include environmentally friendly agricultural practices or environmentally friendly businesses. Research on the connection between sustainable development and gender inclusion also supports the underlying positions (Achuo et al., 2022).

Second, regarding the contextualization of the theoretical bases, as we have already mentioned, financial access represents a means of strengthening the economic inclusion of women. This applies when access to financial services allows women to become actively involved in the economy. In this paragraph, we support this context with relevant references to deepen the coherence of the theoretical foundations. This emphasis implies that women can use financial access to increase their participation in the economic sector that is formal (Asongu et al., 2020). Therefore, Assairh et al. (2020) argue that through institutions such as microfinance, financial access encourages women’s involvement in economic activities, providing them with adequate financing to start and run their businesses, as well as to engage in other activities that promote the empowerment of the female gender in the economic sector.

According to Ahmad et al. (2022a, b) financial inclusion contributes to environmental degradation. According to their logic, financial institutions have the opportunity to invest in environmentally harmful operations, such as mining, logging, or fossil fuel production. However, it should be noted that financial inclusion can also lead to beneficial environmental effects, such as financial support for green initiatives. Following Le et al. (2020), by encouraging the use of more sophisticated and ecologically friendly technology, financial access may also be a key factor in lowering environmental problems associated with carbon emissions. Financial inclusion can therefore play a crucial role in reducing CO₂ emissions. Access to financial services can help lower the obstacles and limitations that impoverished groups in society experience since they require money to invest and adopt profitable and eco-friendly technology (IPA, 2017). This may be the case for women, who by benefiting from access to financial services will strengthen their economic inclusion and access to advanced technologies, because the use of advanced technologies promotes green and clean energy that can preserve the environment (Ganda, 2021).

Third, Given the foregoing, the empirical section of this study assesses two testable hypotheses:

It is relevant to note that Hypothesis 1 does not imply that women may be predisposed to pollute compared to men. The goal of the research is to investigate how financial access policy measures can be used to curb to the potential positive affect of the economic activities of women on environmental pollution. Correspondingly, Hypothesis 2 is underpinned on the idea that women’s engaging in formal economic activities could be harmful to the environment if they are not financially-included, not least, because more financial facilities could condition the specialization of women to less polluting sectors. Whether the underlying hypotheses withstand empirical validity is an object of empirical scrutiny which is the focus of the section that follows.

Taking into account the motivation for this investigation, the research focuses on SSA countries based on annual data for the period 2010–2021. The constraints of data availability during the study also determine the choice of countries and periodicity. The information comes from three sources. First of all, according to Ndour and Asongu (2024), who partly motivate this study, three gender economic inclusion variables are obtained from the International Labor Organization. These are: the participation of women in the labor market; female unemployment rate and female employment (Tchamyou et al., 2025). Studies suggest employing alternative independent variables of interest as a technique to assess robustness (Efobi et al., 2018). Next, we obtain the financial access indicator (proxied by private domestic credit) from the World Bank’s Financial Development and Structure Database (FDSD). According to Asongu et al. (2020), in comparison with the deposit moderator, the moderator of credit access is more related to financial access as it is naturally more related to the availability of financial resources.

Third, the World Bank’s World Development Indicators (WDI), provide data on CO₂ emissions which is employed to measure environmental degradation. The three control variables used in the model are: (1) per capita Gross Domestic Product (GDP) growth rate; (2) Foreign Direct Investment (FDI) and (3) Population. The chosen control variables are consistent with current research on CO₂ emissions (Tamazian et al., 2009; Khan et al., 2021; Mignamissi and Djeufack, 2022; Mignamissi et al., 2024). It should be emphasized that the use of this number of control variables is due to the fact that more of them can lead to an increase in the numerical value of instruments which can render the GMM estimated models invalid (Ndour and Asongu, 2024).

Looking at the expected signs pertaining to the control variables, GDP per capita, FDI, and population are considered to be associated with activities that pollute the environment (Sabir et al., 2020; Achuo et al., 2022). Concerning GDP per capita, numerous studies have documented the nexus between economic prosperity and the environment. There is yet no scholarly consensus on the relationship between the two variables (He et al., 2021). Thus, the expected sign is uncertain. For FDI, according to Halkos and Polemis (2017), more FDI lowers CO₂ emissions, which appears to support the Pollution Halo Theory (Porter and Van der Linde, 1995) and run counter to the Pollution Haven Hypothesis. As a result, the predicted sign is negative. Lastly, the population may be a useful tool for lowering emissions both immediately and over time (Ohlan, 2015). In the STIRPAT models, population is one of the major forces explaining pollution dynamics (Dietz and Rosa, 1994). Therefore, the expected sign is uncertain.

 Appendix 1 discloses the definitions of the variables and their corresponding sources, summary statistics are provided in  Appendix 2, and the Appendix section is supplemented with information on paired correlations provided in  Appendix 3.

Following recent literature (Hameed and Jabeen, 2024), the Generalized Method of Moments (GMM) estimation is the first technique used in this paper. Based on the literature, four main constraints are required. First, as recommended by Roodman (2009), the study must cover a large number of groups and a comparatively shorter period (N > T). This is the case for our study, because the research focuses on 40 countries with a period of 2010–2021 (i.e. 12 years). Second, the link between the dependent variable and its lag surpasses the empirical critical level of 0.800, which is the empirical criterion established to demonstrate the persistence of an indicator (Tchamyou et al., 2019). Third, given the panel configuration of the data under study, the GMM strategy takes into account disparities between countries during the estimation process. Fourth, endogeneity is considered for at least two main fundamentals: (1) simultaneity is controlled by internal instruments and (2) the technique accounts for the unobserved heterogeneity by controlling for time-fixed effects.

The GMM method used in this study is an adaptation of Arellano and Bover (1995) by Roodman (2009). The objective of the strategy is to provide more efficient estimates, taking into account the proliferation of instruments with the possibility of reducing them.

The following equations are obtained in level (1) and first difference (2) according to the estimation procedure for the standard system GMM.

where $Ei,t$ is a variable for environmental degradation (i.e. carbon dioxide emissions) of country i in period t, $σ0$ is a constant, IEG is a measure of gender economic participation (i.e. female unemployment, female labor force participation, and female employment), DCPS stands for financial access (i.e. private domestic credit), DCPSX represents the interaction between gender economic participation indicators and financial access (“financial access” × “ female labor force participation”, “financial access” × “ female unemployment ”, “financial access” × “ female employment”), W denotes the vector of control variables (entailing the growth rate of GDP per capita, FDI and population). $τ$ (i.e. tau) represents the auto-regression coefficient which is represented by 1 because in the study, a lag of one year is enough to capture information of the past$. ∂t$ denotes time-specific effect, $ηi$ reflects the country-specific effect and $εi,t$ the error term. Given that heteroscedasticity is taken into consideration, the two-step procedure is used rather than the one-step procedure. In terms of identification and exclusion restrictions, the study is consistent with extant literature using years as strictly exogenous and the other explanatory variables as endogenous explaining, not least, because years cannot be endogenous after a first difference (Roodman, 2009; Tchamyou et al., 2019).

According to research based on the QR technique to evaluate linkages across the conditional distribution of the outcome variable, this approach is pertinent for accounting for levels of the dependent variable that already exist (Asongu et al., 2024). It is also important to note that the QR approach does not take into account the normal distribution of error terms assumption, in contrast to the ordinary least squares (OLS) approach, which is predicated on this idea. This is mostly due to the possibility of estimated coefficient errors resulting from estimates based on such an assumption. According to both recent and non-current research on the topic, the parameters computed in QR are not buttressed on error terms that are distributed regularly (Koenker and Hallock, 2001).

According to the relevant literature, the QR approach’s estimator of the CO₂ emissions variable’s $θ$ ^th quantile is found by resolving Equation (3)’s optimization problem, which is revealed without any subscript in order to simplify presentation.

where $θ∈(0,1)$⁠. According to the OLS method, which is mainly based on reducing the total sum of the squared residuals, the estimation process is in accordance with the maximization of the corresponding absolute deviations. The corresponding procedure consists of optimizing the absolute deviations associated with the corresponding quantiles. For example, we obtain the 90th quantile (i.e. corresponding to = 0.90) by approximately weighting the residuals. The parameter estimates related to carbon dioxide emissions or $yi$ given $xi$ is:

where for the attendant $θ$ ^th quantile to be computed, parameters with unique slopes are evaluated within the conditional distribution of CO₂ emissions. The corresponding estimate is orthogonal to the slope $E(y/x)=xi′β$ of the OLS which is characterized by an evaluation of the parameters exclusively at the conditional mean of the variable to be explained. Building on Equation (4), the dependent variable $yi$ is carbon dioxide emissions while $xi$ contains a constant term, the female labor force participation rate, the female employment rate, female unemployment rate, private sector domestic credit, growth rate of gross domestic product (GDP) per capita, foreign direct investment (FDI) and population.

The empirical findings are displayed in the tables below. While the system GMM estimates are provided in Table 1, the quantile regression estimates are disclosed in Tables 2–4. Regarding the first group of results, Table 1 is subdivided into three main specifications, each representing different indicators of gender economic inclusion. The female labor force participation rate for the first specification or second column, the female unemployment rate in the second specification and the female employment rate for the last specification, proceeding from left to right. It is important to highlight that the unconditional correlation between female labor force participation and carbon dioxide emissions is positive and significant. It should be emphasized that some information criteria ^[1] must be taken into consideration to confirm our GMM results.

Looking at the findings with respect to tested hypotheses, Hypothesis 1 is valid in the first and second specifications with respect to female labor force participation and female unemployment, but invalid in the third specification in relation to female employment. Hypothesis 2 is exclusively valid in the third specification related to female employment. Overall, none of the two hypotheses are collectively valid in any of the three specifications because positive synergies are apparent in the first specification while negative synergies can be seen in the second and their specifications. Of the three specifications, the most relevant in terms of policy implication is the third specification because while female employment decreases CO₂ emissions, complementing female employment with financial access further decreases CO₂ emissions. This is contrary to female labor force participation in the first specification but consistent with female unemployment in the second specification. However, since the objective of policy makers is not to increase female unemployment in order to reduce CO₂ emissions, the findings in the second specification are less policy-relevant compared to those in the third specification.

With respect to the control variables, the majority of the important control variables exhibit the expected signs, which is in line with the data section’s explanation of the expected signs. Furthermore, it is also important to remember that multicollinearity is not taken into consideration in interactive regressions. For this reason, thresholds and net effects can be interpreted with certainty because they include both the unconditional and conditional effects of the interacting variables (Brambor et al., 2006). The anticipated signs should not be observed for other variables included in the conditioning information set or control variables, because the multicollinearity problem can affect the expected signs. Therefore, interpreting the control variables separately would be similar to interpreting linear additive models.

In order to determine whether the unconditional effect of gender economic inclusion and conditional incidence (i.e. entailing the interaction between financial access and gender economic inclusion) may differ depending on the distribution of CO₂ emissions, Tables 2–4 illustrate the consideration of quantile regressions. This gives us a deeper perspective on the relationship between the variables when the interactions are evaluated throughout the conditional distribution of environmental degradation. The different illustrations show the three indicators of gender economic inclusion used in this research. Table 2 shows the linkages between financial access, female labor force participation and CO₂ emissions. Table 3 uses female unemployment as a proxy for gender economic inclusion while Table 4 examines the nexuses between financial access, female employment and CO₂ emissions. Three strands of results are obtained. First, regarding Table 2, Hypotheses 1 and 2 are valid. To the extent that gender economic inclusion has a significant impact on women’s labor market participation, the conditional impact (between credit access and women’s labor market participation) on CO₂ emissions is significantly negative throughout the distribution. This means that the economic inclusion of women increases CO₂ emissions, but its impact is offset by the interactive effect of access to financial services linked to the economic inclusion of women; which leads to a decrease in CO₂ emissions. To improve the policy implications, an in-depth study is carried out to provide the thresholds of financial access or credit access at which the unconditional positive impact of women’s participation on CO₂ emissions becomes negative. The financial access policy thresholds are within the statistical range of the financial access policy or moderating variable disclosed in the summary statistics (i.e. 2.215 to 201.258) (% of GDP).

Second, regarding Table 3, Hypotheses 1 and 2 are relaxed and not considered in order to avail more room for policy implications. This is essential because the corresponding findings are more policy worthwhile if avoidable female unemployment thresholds are provided in order to maintain the negative unconditional effect of financial access on CO₂ emissions. Most of these avoidable levels of female unemployment are within policy range of the moderating female unemployment levels apparent in the summary statistics. These thresholds are presented in Table 3.

Third, according to the results in Table 4, it appears that Hypotheses 1 and 2 are partly valid. Indeed, the unconditional impact of female employment on CO₂ emissions is significantly negative in top quantiles of the CO₂ emissions distribution (i.e. invalidating Hypothesis 1) and negative in the bottom quantiles (i.e. validating Hypothesis 1). By extension, Hypothesis 2 is also valid in the 25th quantile and median (i.e. given the corresponding negative interactive effects) while the attendant hypothesis is invalid in the top quantiles of the of CO₂ emission conditional distribution (i.e. in the light of the positive interactive effects). It follows that credit access thresholds are computed in the distributions where both hypotheses are valid and financial access thresholds for complementary policies are calculated in the distributions where the hypotheses are invalid. Financial access policy thresholds are critical levels of financial access that should be attained in order to reverse the positive effect of female employment on CO₂ emissions while the financial access thresholds for complementary policies are maximum levels of the financial access that once reached, complementary policies should be taken in order for the negative effect of financial access on CO₂ emissions to be maintained.

In this section, we will discuss the results obtained in more depth, linking them to the literature. It is important to note two points: (1) the results are consistent with two strands of the literature on CO₂ emissions (Le et al., 2020; Ahmad et al., 2022a, b; Khan et al., 2021) on the one hand, and Wang (2022), Achuo et al. (2023) and Ndour and Asongu (2024) on the other. The first group showed the negative impact of finance on CO₂ emissions, while the second group emphasized the negative impact of women’s economic inclusion. (2) What distinguishes this study from the latter is the relevance of the underlying links assessed throughout the conditional distribution of the outcome variable. Therefore, the results of this paper further confirm the scientific and policy importance of research in the current literature (Soku et al., 2023). Based on what has been mentioned above, the results obtained have enriched the existing literature on the negative link between gender economic inclusion and the environment (Ndour and Asongu, 2024). The results also show that financial access can moderate how environmental sustainability is influenced by gender economic inclusion. Accordingly, access to loans can give women the opportunity to invest in clean and efficient technologies, which reduces CO₂ emissions. Moreover, it can also encourage competition and innovation in clean technologies. The results deserve to be further discussed in the light of the existing theoretical literature on the subject, especially with regard to the theory of Ecofeminism on the one hand and the theory of Economic Empowerment and Ecological Sustainability on the other hand (Wang et al., 2022; Arshad et al., 2024). Therefore, the results obtained are consistent with both theoretical bases, especially since for some specifications, the unconditional incidences of financial access and gender economic inclusion, respectively, decrease CO₂ emissions.

This study evaluated the relationships between environmental degradation, female economic inclusion, and financial access in 40 Sub-Saharan African nations between 2010 and 2021. The empirical evidence is based on the Generalized Method of Moments (GMM) and Quantile Regressions estimation approaches. From the findings, positive and negative synergies are apparent from the GMM results. From the quantile regressions results: (1) financial access policy thresholds are computed when female labor force participation is employed; (2) avoidable female unemployment thresholds are apparent when the female unemployment rate is used while (3) financial access thresholds as well as thresholds for complementary policies are computed when female employment is used. Positive (negative) synergies are apparent when female labor force participation and its interaction with financial access both have positive (negative) signs. Financial access thresholds are levels of financial access that should be reached in order to reverse the unconditional effect of gender inclusion (i.e. female labor force participation or female employment) from positive to negative on CO₂ emissions. Avoidable female unemployment thresholds are levels of female unemployment that should be avoided by policy makers in order to maintain the negative effect of financial access on CO₂ emissions. Financial access thresholds for complementary policies are levels of financial access that once reached, policy makers should take complementary measures in order for the negative incidence of gender economic inclusion on CO₂ emissions to be maintained. Policy thresholds, avoidable critical levels and turning points for complementary policies are contingent on the conditional distribution of CO₂ emissions.

In the area of gender economic development, increasing the economic inclusion of women in the formal and informal sectors will play a key role in promoting environmental sustainability by mitigating carbon dioxide emissions. This is mainly because, on average (i.e. based on the GMM results), gender economic integration helps direct resources towards initiatives that promote environmental sustainability, while encouraging businesses and individuals to adopt more responsible practices. However, it is worthwhile that the policy aimed at improving gender economic inclusion should not be blanket, but rather based on initial levels of carbon dioxide emissions. Therefore, it is essential that policies aimed at promoting the economic inclusion of women unconditionally target green technologies.

Financial access in SSA is a critical element of post-2015 development as most of the sub-region’s nations did not meet the anticipated Millennium Development Goals. We observed in this study that financial access increases the negative relevance of economic policies on the environment. It is therefore necessary to implement adequate measures to promote access to finance in order to foster economic development and achieve the expected results in favor of promoting the green economy. As a result, policymakers should motivate financial institutions to support sustainable practices and make investments in green initiatives. Additionally, they should create incentives that promote the adoption of ethical and sustainable financial practices. It should be emphasized that access to financial services promotes innovation and development by providing the opportunity to finance new ideas and technologies. It also plays a role in economic stability. It is therefore essential that policy makers understand the importance of financial access in fostering economic development and gender inclusion. Financial institutions that embrace sustainable and responsible financial practices should also be preferred by consumers and enterprises. Such preference should be supported with government incentives.

A major theoretical and policy relevance of this research is that five main notions of thresholds have been considered and emphasized in the study, especially when observed in the light of inter alia, policy thresholds, avoidable thresholds, thresholds for complementary policies, positive synergies and negative synergies. In essence, as established in the findings: (1) policy thresholds are turning points of the moderating or policy variables that must be attained in order to change the incidence of the main channel on CO₂ emissions from either positive to negative or from negative to positive. (2) Conversely, thresholds for complementary policies are critical levels of the moderating variables that once reached, policy makers must put in place complementary policies in order to maintain the expected incidence of the channels or mechanisms on the outcome or CO₂ emissions. As it stands, policy thresholds have been oriented towards financial access because these are logically positive macroeconomic signals. (3) Furthermore, in a scenario of a threshold for complementary policy in which the moderating variable is a policy syndrome as opposed to a positive macroeconomic signal, avoidable thresholds are apparent. Hence, the study has also provided insights into avoidable thresholds especially as it relates to critical levels of female unemployment (i.e. a policy syndrome or negative macroeconomic signal) that should be avoided in order to maintain the expected effect of financial access in reducing CO₂ emissions. (4) Last but not the least, positive and negative synergies have also been provided in order to inform policy makers on how the underlying channels and moderating variables interact in order to ultimately promote environmental sustainability.

In light of the aforementioned, it is important to keep in mind that, in line with the existing literature on interactive regressions discussed in the preceding sections, the thresholds that have been established also serve as direct policy implications because they give decision-makers clear levels of the policy or moderating variables that should be avoided or reached in order to reduce CO₂ emissions and promote environmental sustainability.

Despite the study’s contributions, we can identify a few limitations: the sample size is small, which affects the results' representativeness; the methodology employed could be enhanced to better capture the intricacies of the relationship being studied; and the GMM results are sensitive to the instruments chosen, which impacts the validity of the results. Furthermore, the study’s conclusions clearly offer room for more research, particularly in regards to determining whether the established conclusions hold up to empirical scrutiny when taking into account other Sustainable Development Goals (SDGs) of the United Nations (UN). Moreover, the problem statement should also be considered in terms of African continental objectives such as Agenda 2063 of the African Union in prospects related to gender inclusion and sustainable development. In engaging the underlying future research directions, in order to create space for more country-specific policy consequences, country-specific studies should also be the focus. Other estimating techniques can be considered in future studies to evaluate the robustness of the results.

Mariette C. N. Mete: Conceptualization, Data curation, Writing – original draft, Visualization, Validation, Formal analysis, Methodology. Simplice A. Asongu: Conceptualization, Writing – original draft, Formal analysis, Visualization, Validation. Dieudonné Mignamissi: Conceptualization, Writing – original draft, Formal analysis, Visualization, Validation, Supervision.

The authors are indebted to the editor and reviewers for constructive comments.