RESOURCE DEPENDENCE, INSTITUTIONAL QUALITY, AND ECONOMIC GROWTH DYNAMICS: A SYSTEM GMM ANALYSIS FOR SUB-SAHARAN AFRICA

24 International Journal of Social and Educational Innovation Vol. 12, Issue 24, 2025 ISSN (print): 2392 – 6252 eISSN (online): 2393 – 0373 DOI: 10.5281/zenodo.17278578 RESOURCE DEPENDENCE, INSTITUTIONAL QUALITY, AND ECONOMIC GROWTH DYNAMICS: A SYSTEM GMM ANALYSIS FOR SUB-SAHARAN AFRICA Emmanuel Imuede OYASOR Department of Accounting Science Walter Sisulu University, Mthatha, South Africa [email protected] Abstract This study investigates the dynamic relationship between natural resource dependence, institutional quality, and economic growth in Sub-Saharan Africa (SSA) over the period 1990– 2023. Using a dynamic panel data model estimated through System Generalized Method of Moments (System GMM), the analysis addresses endogeneity concerns while capturing the temporal persistence of growth. Results reveal that higher natural resource dependence, measured through natural resource rents and export-based proxies, significantly hampers GDP per capita growth, which is consistent with the resource curse hypothesis. However, strong institutional quality mitigates this negative effect, with institutional improvements emerging as a key enabler of sustainable growth. Additionally, gross capital formation, trade openness, and labor force participation positively influence growth dynamics. Sensitivity analyses and robustness checks confirm the stability of the results across alternative specifications and subsamples. Policy implications emphasize the need for institutional reforms, economic diversification, and regional trade integration to unlock SSA’s growth potential. The findings contribute to a nuanced understanding of how governance and structural factors condition the developmental outcomes of resource-rich economies in Africa. Keywords: Natural Resource Dependence, Institutional Quality, Economic Growth, SubSaharan Africa, System GMM, Resource Curse. International Journal of Social and Educational Innovation (IJSEIro) Volume 12/ Issue 24/ 2025 25 1. Introduction The relationship between natural resource dependence and economic growth in Sub-Saharan Africa (SSA) has remained a subject of extensive academic inquiry and policy debate over the past three decades. On the one hand, natural resources are seen as a potential catalyst for economic transformation through export earnings, government revenues, and foreign investment (Sachs & Warner, 2001). On the other hand, the so-called “resource curse” hypothesis posits that resource-rich countries often experience slower growth, governance challenges, and greater macroeconomic volatility (Van der Ploeg, 2011). The experience of many SSA countries underscores the complexity of this nexus, as abundant resource endowments have not consistently translated into sustained economic progress (Bhattacharyya & Hodler, 2010). Given the region’s continued reliance on primary commodities and the growing importance of resource-based revenues, it is crucial to re-examine the dynamics of resource dependence and economic growth using robust empirical methods. Much of the literature on this topic remains inconclusive, partly due to methodological limitations and variations in how resource dependence is measured. While early studies largely relied on cross-sectional or time-series data, more recent contributions have employed panel data approaches that allow for greater heterogeneity and improved inference (Havranek et al., 2016). However, many existing panel studies still face challenges related to non-stationarity, omitted variable bias, and reverse causality. Addressing these methodological issues is essential to establish credible causal relationships between natural resource dependence and economic growth in SSA (Badeeb, Lean, & Clark, 2017). Moreover, given the diversity of SSA economies in terms of resource endowments, institutional quality, and policy frameworks, a careful sensitivity analysis using alternative proxies and estimation techniques is warranted. The empirical strategy in this study combines panel unit root and panel cointegration tests with generalized method of moments (GMM) estimations to address endogeneity and dynamic effects. By first establishing the time-series properties of the data, we mitigate concerns of spurious regression that often plague growth-resource studies (Pedroni, 2004). Next, panel cointegration techniques are applied to test for long-run equilibrium relationships between resource dependence and economic growth, accounting for cross-sectional dependence and heterogeneity (Phillips & Moon, 1999). Finally, the GMM estimator, which is particularly suited for dynamic panel models with endogenous regressors, is used to quantify the shortand long-run impacts of resource dependence on growth while controlling for institutional and macroeconomic factors (Arellano & Bover, 1995; Blundell & Bond, 1998). International Journal of Social and Educational Innovation (IJSEIro) Volume 12/ Issue 24/ 2025 26 Another significant contribution of this study lies in its sensitivity analysis. Recognizing that resource dependence can be proxied in multiple ways—including resource exports as a share of GDP, resource rents, and resource production indices (World Bank, 2023)—we employ several alternative indicators to assess the robustness of our findings. Likewise, we compare results across different estimation methods, including fixed effects, difference GMM, and system GMM, to ensure that the core results are not driven by methodological choices. Such triangulation is essential for providing policymakers with reliable insights and for contributing to the broader academic debate (Brunnschweiler & Bulte, 2008). The time frame of 1990 to 2023 is particularly pertinent for SSA, as it captures key periods of structural adjustment, democratization, commodity price cycles, and the recent disruptions related to the COVID-19 pandemic and global energy transitions. The extended panel allows us to explore not only the average long-run effects but also potential structural breaks and nonlinearities in the resource-growth relationship (Collier & Goderis, 2009). Moreover, this period coincides with the increasing emphasis on sustainable development goals (SDGs), which highlight the need to transform resource wealth into broader economic and social wellbeing. This study seeks to advance the understanding of how natural resource dependence influences economic growth in SSA by adopting a comprehensive empirical approach that addresses key methodological challenges and rigorously tests the robustness of the results. The findings will have significant implications for resource governance and growth strategies in SSA, especially as many countries grapple with questions of economic diversification and resilience in an increasingly uncertain global environment. 2. Materials 2.1 Theoretical Review The relationship between natural resource dependence and economic growth has been extensively theorized in the development economics and resource economics literature. A central pillar of this discourse is the resource curse hypothesis, which posits that countries rich in natural resources often experience slower or more volatile economic growth than their resource-poor counterparts (Sachs & Warner, 2001). Early formulations of this theory primarily drew on neoclassical growth models, highlighting mechanisms such as Dutch disease, rent-seeking behavior, and macroeconomic instability as key transmission channels (Corden & Neary, 1982; Auty, 1993). International Journal of Social and Educational Innovation (IJSEIro) Volume 12/ Issue 24/ 2025 27 One prominent theoretical strand underscores the role of institutional quality in mediating the effects of resource dependence. According to Mehlum, Moene, and Torvik’s (2006) seminal framework, resource wealth can either support or undermine growth depending on whether institutions are of a "grabber-friendly" or "producer-friendly" nature. Subsequent studies have elaborated on this premise, emphasizing that the presence of strong institutions can help resource revenues foster public investment and diversification (Boschini, Pettersson, & Roine, 2013). Empirical extensions of this theory in the African context suggest that institutional heterogeneity across Sub-Saharan countries critically shapes the growth-resource dynamic (Bhattacharyya & Collier, 2014; Di John, 2015). Complementing the institutional lens, another theoretical perspective centers on the structural transformation hypothesis. Natural resource dependence is argued to influence the composition of economic activity, often skewing it towards primary sectors at the expense of manufacturing and services (Rodrik, 2016). This path dependency can inhibit productivity growth and technological upgrading, key drivers of sustained economic development. Recent dynamic general equilibrium models show that resource booms can crowd out skill-intensive sectors, thereby slowing human capital accumulation and long-term growth (Gollin, Jedwab, & Vollrath, 2016). These findings are particularly salient for SSA, where premature deindustrialization remains a pressing concern (Newfarmer, Page, & Tarp, 2019). A third theoretical approach highlights the role of macroeconomic volatility as a transmission channel. Commodity price cycles introduce external shocks that disproportionately affect resource-dependent economies (Cashin, Mohaddes, & Raissi, 2019). In theoretical terms, volatility exacerbates uncertainty, discouraging long-term investment and fostering procyclical fiscal behavior (Arezki & Brückner, 2015). Recent stochastic growth models also illustrate how repeated boom-bust cycles can result in lower average growth, particularly in countries with limited fiscal buffers (Bleaney & Halland, 2021). For SSA nations, which are heavily reliant on commodities such as oil, metals, and agricultural products, this volatilitygrowth nexus remains highly relevant. More recently, the sustainable development framework has expanded the theoretical discourse beyond traditional macroeconomic outcomes to encompass broader developmental dimensions. Theoretical contributions in this vein posit that sustainable management of natural resource wealth requires integrating economic, social, and environmental objectives (Barbier & Hochard, 2018). Resource dependence, if not managed with a long-term sustainability perspective, risks undermining intergenerational equity and environmental resilience (Cust & International Journal of Social and Educational Innovation (IJSEIro) Volume 12/ Issue 24/ 2025 28 Mihalyi, 2017). For SSA countries facing the dual challenges of poverty alleviation and climate change adaptation, this broadened theoretical lens is increasingly pertinent (UNDP, 2021). 2.2 Empirical Review Empirical investigations into the nexus between natural resource dependence and economic growth in Sub-Saharan Africa (SSA) have employed diverse methodologies such as panel cointegration, dynamic GMM, and threshold regressions. The empirical strands underscore four key insights: first, dynamic GMM remains the preeminent technique to address endogeneity and persistence in panels; second, long-run relationships exist but are typically characterized by cointegration with endogenous adjustment; third, nonlinearities and threshold effects are pervasive, with institutional quality and trade openness as critical mediators; and fourth, micro-level evidence reveals localized growth benefits that may not translate into sustained national growth without supportive policy frameworks. Odhiambo (2020) uses system GMM to demonstrate how financial development mediates resource-growth linkages, emphasizing the method’s ability to address endogeneity and sustain robust inference in panels. Oguzie et al. (2023) apply system GMM on mineral rents and growth across 13 SSA countries to correct for simultaneity, measurement error, and unobserved heterogeneity. Panel cointegration studies further substantiate long-run equilibria between resource indicators and GDP per capita. A notable example is a 2015 dynamic panel analysis across multiple African countries, which identifies significant cointegration relationships and error-correction dynamics, suggesting that deviations in resource dependence and income levels adjust toward long-run steady states. Such findings contrast with studies like Katoka & Dostal (2022), which utilize threshold regressions to account for nonlinearities in commodity-price channels, revealing that the impact of resource income on growth varies depending on price regimes. A growing body of research examines the resource curse paradox using multi-method comparisons. Brunnschweiler-Bulte-style meta-analyses (2016–2022) report mixed results: approximately 40 % of studies find adverse growth effects, 40 % no significant effects, and 20 % positive effects, largely depending on context, model, and proxy used. Newer empirical contributions echo this heterogeneity. For example, a 2024 study utilizing data from 46 SSA nations (2000–2022) applies system GMM and confirms that while natural resource rents generally stimulate GDP, the effect diminishes or reverses at higher levels of dependence. International Journal of Social and Educational Innovation (IJSEIro) Volume 12/ Issue 24/ 2025 29 Several studies enrich the analysis by controlling for institutional quality and environmental outcomes. An MDPI (2023) investigation links natural resource income, institutional variables, and environmental degradation, reporting that resource rents increase emissions but that stronger institutions attenuate this effect when using GMM estimations. Similarly, research into wood-fuel economies (2019) shows how resource use interplays with growth and carbon impacts across SSA using macro-panel GMM, while cross-sector panel VARs (2021) reveal that growth effects are contingent upon trade openness and institutional quality. Threshold models and heterogeneity-aware approaches further nuance the analysis. A 2022 threshold-regime study identifies distinct regimes in the FDI–resource–growth relationship, indicating that FDI’s growth-enhancing effect is mediated by the level of resource dependence. Concurrently, panel heterogeneity frameworks (e.g., Pesaran et al., 2019; Aghion & Howitt, 2021) underscore the importance of accounting for cross-sectional dependencies and parameter heterogeneity in dynamic panels. Local-level studies also contribute valuable micro-empirical insights. Provenzano & Bull (2021), using satellite-data and difference-in-difference, report that while mining boosts local urbanization, these gains are temporary and heavily conditioned by political regimes, echoing the broader dynamic and contingent nature of resource-led growth. 2.3. Hypotheses Development H₁: Natural resource dependence negatively affects economic growth (resource curse) The negative relationship between natural resource dependence and economic growth is widely theorized through mechanisms like Dutch disease, rent-seeking, and volatility. Sachs and Warner (2001) documented that high natural resource reliance tends to crowd out manufacturing, generating net negative growth effects. Van der Ploeg (2011) further explicated the macroeconomic and institutional pathways that may invert expected growth benefits from resource wealth. Meta-analytical reviews (Badeeb, Lean, & Clark, 2017) point to persistent negative associations, particularly in dynamic panels, reinforcing the resource curse hypothesis. Empirical evidence employing GMM and cointegration techniques in SSA supports this negative dynamic. Studies have documented that resource rent dependence shifts productive activity away from higher-value sectors (Acosta et al., 2022) resulting in slower growth. For instance, recent panel-dynamic GMM estimations (Epo & Faha, 2020; Asiamah et al., 2022) reveal consistent negative coefficients for resource rents on GDP per capita growth. A 2022 International Journal of Social and Educational Innovation (IJSEIro) Volume 12/ Issue 24/ 2025 30 multi-country analysis using dynamic GMM also found that regions heavily reliant on fuel and mineral exports face constrained growth trajectories (Natural Resource Dependence and Institutional Quality, 2022). This convergence across methodologies and time frames underscores the robustness of the adverse growth effect associated with resource dependence in SSA economies. H₂: Institutional quality mitigates the negative impact of resource dependence on economic growth Theoretical frameworks (Mehlum, Moene, & Torvik, 2006; Acemoglu & Robinson, 2012) posit that institutions determine whether resource abundance becomes a blessing or curse. Better governance, property rights, and regulatory frameworks are theorized to channel revenues into productive investment, preventing rent-seeking and Dutch disease effects. Recent theory goes further by differentiating institutional components such as rule of law, accountability, and regulatory quality, each offering nuanced mitigation potential (Torvik, 2017). A growing empirical literature supports the moderating role of institutions in SSA. System GMM estimations (Asiamah et al., 2022; Sibanda et al., 2023) reveal that resource rents negatively affect growth primarily where governance is weaker. In contrast, in high-institution regimes, the adverse coefficient is attenuated or becomes insignificant. A recent IV-GMM study on property rights across African oil economies (2024) shows that improved property institutions can convert resource curse dynamics into growth avenues. Likewise, a 2025 crosscountry examination confirmed that macro-institution indicators such as regulatory quality and control of corruption significantly reduce resource-dependence drag on growth (Does Governance Matter…, 2025). H₃: Investment, trade openness, and labor force participation positively influence economic growth, particularly in conjunction with sound governance Key elements of neoclassical growth theory-capital accumulation, human capital, trade—are widely held to be growth-enhancing. Berg et al. (2012) stressed capital formation as critical in capital-scarce SSA countries. Trade openness is theorized to boost growth by facilitating technology transfer, specialization, and efficiency (Frankel & Romer, 1999). Labor force participation ensures the productive use of human capital, while sound governance is argued to amplify these synergies (Dollar & Kraay, 2003). International Journal of Social and Educational Innovation (IJSEIro) Volume 12/ Issue 24/ 2025 31 Recent empirical assessments confirm these theoretical claims within SSA. Dynamic GMM studies find that gross capital formation exerts strong positive, and statistically significant growth effects (Namahoro, Wu, & Su, 2023; Green Growth Dynamics, 2025). Trade openness contributes positively in panel settings, particularly under robust governance regimes (Emilie Kinfack & Bonga-Bonga, 2023; Trade Openness, Institutions, and Inclusive Growth, 2022). Labor participation also shows significant albeit smaller effects, consistent with demographiceconomic models (Tarver, 2021; Kouassi et al., 2022). Additionally, hybrid studies combining trade and financial openness emphasize that strong governance enhances the growth impact of both capital inflows and trade integration (Fankem & Oumarou, 2020), highlighting the pivotal role of governance quality in leveraging growth determinants. 3. Methodology The relationship between natural resource dependence and economic growth in Sub-Saharan Africa can be understood through several interrelated theoretical perspectives, each offering insights into different mechanisms at play. Classical and neoclassical growth models provide the foundational structure, while institutional and political economic theories elucidate how resource dependence may condition growth outcomes. The neoclassical Solow-Swan growth model (Solow, 1956) serves as a starting point for conceptualising long-run growth dynamics. In its basic form, output 𝑌 is produced using capital 𝐾, labour 𝐿, and a technology factor 𝐴. The aggregate production function is given by: 𝑌(𝑡) = 𝐴(𝑡)𝐾(𝑡)𝛼𝐿(𝑡)1−𝛼 (1) where 0 < 𝛼 < 1 reflects the elasticity of output with respect to capital. In this framework, long-run per capita growth is driven by technological progress, whereas factor accumulation exhibits diminishing returns. Natural resource wealth, if treated as an exogenous income source, may initially boost capital accumulation but cannot sustain long-run growth unless reinvested in productivity-enhancing activities (Sachs & Warner, 2001). Extending this model to explicitly incorporate natural resources, many scholars adopt an augmented production function that includes resource rents 𝑅 as an input (Brunnschweiler & Bulte, 2008; van der Ploeg & Poelhekke, 2017). This yields the following form: 𝑌(𝑡) = 𝐴(𝑡)𝐾(𝑡)𝛼𝐿(𝑡)𝛽𝑅(𝑡)𝛾 (2) where 𝛾 represents the elasticity of output with respect to natural resources. While such a formulation allows resources to contribute directly to output, it also highlights potential pitfalls. Excessive reliance on resource rents may distort incentives and foster a rent-seeking economy International Journal of Social and Educational Innovation (IJSEIro) Volume 12/ Issue 24/ 2025 32 (Mehlum, Moene, & Torvik, 2006). Moreover, resource windfalls often lead to appreciation of the real exchange rate, reducing competitiveness in tradable sectors, a phenomenon known as Dutch Disease (Corden & Neary, 1982). In mathematical terms, an increase in resource revenues 𝑅 can be linked to an appreciation of the real exchange rate 𝑞 through: Δ𝑞 = 𝜙Δ𝑅 (3) where 𝜙 > 0 captures the sensitivity of the exchange rate to resource inflows. As 𝑞 appreciates, manufacturing and agricultural exports may contract, impeding structural transformation and long-term growth (Harding & Venables, 2013). Another theoretical stream emphasises the role of institutions in mediating the resource-growth relationship. According to the institutional resource curse hypothesis (Acemoglu & Robinson, 2012), resource rents provide opportunities for elite capture and weaken public accountability. This dynamic can be formalised in a political economy model where the probability 𝜋 of rent capture by elites is an increasing function of resource wealth 𝑅 and a decreasing function of institutional quality 𝜃: 𝜋 = 𝑓(𝑅, 𝜃), ∂𝜋 ∂𝑅 > 0, ∂𝜋 ∂𝜃 < 0 (4) Higher 𝜋 is associated with suboptimal public investment and corruption, both of which impair economic performance (Collier & Goderis, 2012). Therefore, the growth effects of resource wealth are not uniform but contingent on institutional settings. Dynamic empirical growth models incorporating these theoretical insights often adopt panel data specifications that account for both short-run dynamics and long-run equilibrium relationships. A typical dynamic panel model used in empirical analyses of the resource-growth nexus takes the following form (Arellano & Bond, 1991; Blundell & Bond, 1998): Δ𝑦𝑖𝑡 = 𝛼Δ𝑦𝑖𝑡−1 + 𝛽Δ𝑋𝑖𝑡 + 𝜇𝑖+ 𝜀𝑖𝑡 (5) where 𝑦𝑖𝑡 is the log of GDP per capita for country 𝑖 at time 𝑡, 𝑋𝑖𝑡 is a vector of explanatory variables including natural resource dependence and institutional quality, 𝜇𝑖 captures unobserved country-specific effects, and 𝜀𝑖𝑡 is the idiosyncratic error term. The Generalised Method of Moments (GMM) estimator is typically employed to address endogeneity concerns arising from the correlation between 𝑦𝑖𝑡−1 and 𝜇𝑖 (Roodman, 2009). Importantly, the relationship between natural resources and growth may exhibit nonlinearities. Some studies suggest that at low levels of dependence, resources can foster growth through capital accumulation and infrastructure development, but beyond a threshold, adverse institutional and macroeconomic effects dominate (Papyrakis & Gerlagh, 2004). A quadratic term in resource dependence 𝑅𝑖𝑡 is thus often included: International Journal of Social and Educational Innovation (IJSEIro) Volume 12/ Issue 24/ 2025 39 Variable NRR Model FUEX Model MINEX Model Hansen J (p-value) 0.287 0.312 0.301 Arellano-Bond AR(2) (p) 0.421 0.398 0.410 Source: Author (2025) Table 7: Post-Estimation Tests Test Statistic p-value Hansen J test (overid.) 19.427 0.287 AR(1) test -2.792 0.005 Source: Author (2025) Table 8: Robustness Check (Subsample by Institutional Quality) Variable Low INST High INST Natural Resource Rents -0.145*** -0.045 Institutional Quality 0.120 0.410*** Lagged GDPPC Growth 0.204*** 0.221*** Gross Capital Formation 0.072** 0.097*** Trade Openness 0.005 0.022** Note: Significance codes: *** p<0.01, ** p<0.05, * p<0.1 Source: Author (2025) International Journal of Social and Educational Innovation (IJSEIro) Volume 12/ Issue 24/ 2025 40 Note: Figure 1 - Residual vs fitted value; Figure 2 - Predicted vs Actual GDP Growth; Figure 3 - Dynamic effect of Lagged GDP growth overtime Source: Author (2025) 4.2 Hypotheses Evaluation and Policy Implications H₁: Natural resource dependence negatively affects economic growth (resource curse). This hypothesis is strongly confirmed by the analysis. The significant negative coefficients substantiate that higher natural resource dependence is associated with lower GDP per capita growth. These findings are consistent with the resource curse theory articulated by Sachs and Warner (2001) and extended by van der Ploeg (2011). They also align with meta-analytical evidence presented by Badeeb et al. (2017) and dynamic panel studies in the SSA context, which document persistent adverse growth effects linked to resource dependence (Epo & Faha, 2020) H₂: Institutional quality mitigates the negative impact of resource dependence on growth. This hypothesis is supported. The robustness check demonstrates that in countries with higher institutional quality, the negative association between resource dependence and growth is significantly reduced and loses statistical significance. This result is in line with the institutionalist view that effective governance can offset the detrimental effects of resource dependence (Acemoglu & Robinson, 2012). Recent empirical analyses for SSA (Asiamah et al., 2022; Gelb et al., 2023) show that institutional quality plays a pivotal moderating role, validating the hypothesis. International Journal of Social and Educational Innovation (IJSEIro) Volume 12/ Issue 24/ 2025 41 H₃: Investment, trade openness, and labor force participation positively influence economic growth, particularly in conjunction with sound governance. This hypothesis is validated. The positive and statistically significant coefficients for gross capital formation (GCF) and trade openness (TRADE) support the theoretical propositions that capital accumulation and economic integration enhance growth (Calderón & Servén, 2010; Frankel & Romer, 1999). Although the coefficient for labor participation (LAB) is smaller and marginally significant, its positive sign is consistent with demographic-economic growth theories (Hanushek & Woessmann, 2015), which emphasize the contribution of an active labor force to long-run economic performance. The evidence presented carries profound policy significance. First, the consistent resource curse effect calls for improved governance to prevent rent capture, real exchange rate misalignment, and economic stagnation. Policy efforts should prioritize transparency, independence of institutions, and quality of legal systems (Mehlum et al., 2006; Asiamah et al., 2022). Second, capital formation exhibits robust positive impacts, suggesting governments should bolster physical and human capital investment. Infrastructure, education, and technology adoption are essential to sustain productivity and buffer resource dependence. Third, trade openness is beneficial although mild; tailored trade policies can help domestic industries upgrade while maintaining exposure to global markets (Rodrik, 2001; Asongu & Odhiambo, 2023). Fourth, the moderating effect of institutions underscores the need for graduated reform: policy efforts should first strengthen institutions, even modest improvements can reduce the resource curse’s negative impact (van der Ploeg & Poelhekke, 2017). This multifaceted approach aligns with integrated resource management frameworks advocated by Sachs & Warner (2001) and Humphreys et al. (2007). 5. Conclusion This study has examined the intricate relationship between natural resource dependence, institutional quality, and economic growth in Sub-Saharan Africa. The study reinforces the pivotal role of institutions in shaping economic outcomes. Through sustained governance reforms, strategic investment, and regional integration, SSA countries can harness their resource wealth to foster inclusive and resilient growth. Advancing this agenda requires continued scholarly attention and a deepened commitment to evidence-based policymaking. International Journal of Social and Educational Innovation (IJSEIro) Volume 12/ Issue 24/ 2025 42 The results provide robust evidence of a persistent resource curse across the region: higher dependence on natural resource rents exerts a significant negative effect on GDP per capita growth. The effect is not inevitable, its severity diminishes in the presence of strong institutional quality, underscoring the critical role of governance. Additionally, capital formation, trade openness, and, to a lesser extent, labor force participation emerged as significant positive drivers of growth. These findings are consistent with contemporary resource curse literature (Arezki et al., 2021; Gelb et al., 2023) and institutional growth theories (Acemoglu & Robinson, 2012). While this study provides important insights, several limitations must be acknowledged. First, although the use of System GMM addresses endogeneity concerns, the potential for unobserved heterogeneity remains (Roodman, 2009). Second, the reliance on aggregate country-level data may mask subnational disparities in resource governance and growth outcomes (Cust & Poelhekke, 2015). Third, the operationalization of institutional quality using broad composite indicators, though standard in cross-country studies, may not fully reflect institutional nuances in SSA contexts (Gelb et al., 2023). Finally, while this study focused on linear effects, more complex non-linear or threshold relationships between resources, institutions, and growth could exist, warranting further exploration. Several actionable recommendations arise. Policymakers in SSA should prioritize institutional reforms aimed at enhancing transparency, rule of law, and public accountability. Establishing sovereign wealth funds with clear governance structures and adopting fiscal rules can help stabilize resource revenues and mitigate procyclicality (Bova et al., 2016). Moreover, fostering economic diversification through targeted support for non-resource sectors is crucial to reducing vulnerability to commodity price shocks (Gelb et al., 2023). Investments in human capital should complement physical capital investments to enhance labor productivity and long-term growth prospects (Hanushek & Woessmann, 2015). At the regional level, deepening trade integration under frameworks like the African Continental Free Trade Area (AfCFTA) offers avenues for expanding market access and stimulating structural transformation (Asongu & Odhiambo, 2023). Future research should address the limitations highlighted. First, more granular analyses incorporating subnational data could yield richer insights into the local dynamics of resource governance and economic performance (Cust & Poelhekke, 2015). Second, future studies should explore interaction effects between resource dependence, governance quality, and other structural factors such as financial development or human capital (Mehlum et al., 2006). Third, International Journal of Social and Educational Innovation (IJSEIro) Volume 12/ Issue 24/ 2025 43 the application of machine learning techniques to identify non-linear patterns or structural breaks in the resource-growth relationship represents a promising avenue. Finally, longitudinal case studies of SSA countries that have successfully escaped the resource curse could provide valuable lessons for the region (Gelb et al., 2023). References Acemoglu, D., & Robinson, J. A. (2012). Why nations fail: The origins of power, prosperity, and poverty. Crown Business. Addisu, L. A., & Werker, E. 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