Search Results (498)

The finance–environment nexus in Sub-Saharan Africa remains complex, particularly in nations where institutional quality and fiscal policies are in an early stage. To address this, the study evaluates the impact of financial development on environmental sustainability in Sub-Saharan Africa, emphasising the moderating roles of environmental taxes and regulatory quality. Using a balanced panel methodology across 11 SSA nations from 2006 to 2023, the study employs a multi-estimation model (fixed effects (FE), Fully Modified Ordinary Least Squares (FMOLS) and Autoregressive Distributed Lag (ARDL)) to capture both short- and long-run relationships. From the analysis, the FE and FMOLS estimates indicate that financial development significantly increases ecological footprints, while foreign direct investment and government expenditure are associated with lower environmental footprints. However, the ARDL estimates reveal that environmental taxes and regulatory quality significantly reduce the ecological footprint, motivating a policy shift. Most importantly, the moderation estimation reveals that environmental taxes condition the finance–environment nexus in SSA. This depicts that while financial development worsens environmental outcomes, its adverse effects are nullified and reversed under a stronger environmental tax framework. These findings are relevant to the Environmental Kuznets Curve theory and draw insights from the institutional and financial intermediation theory. The study provides evidence that financial development, when integrated with effective environmental taxation and institutional quality, promotes environmental sustainability in SSA. Policymakers are therefore urged to strengthen environmental tax frameworks, integrate green financial intermediation and intensify regulatory institutions to achieve a sustainable finance–environment model and support SDG 13 in SSA. Full article

This study examines the long- and short-run determinants of green employment in Saudi Arabia over the period 1990–2024 using an Autoregressive Distributed Lag (ARDL) bounds testing framework within an error-correction model. Six macroeconomic and structural variables are analyzed: renewable energy capacity, GDP growth, domestic credit, urbanization, foreign direct investment, and the Vision 2030 policy regime shift. Supplementary analyses test the Environmental Kuznets Curve (EKC) hypothesis and map causal relationships using pairwise Granger causality tests. The bounds test indicates long-run cointegration among the variables (F = 8.45, exceeding the 5% I(1) critical bound of 3.61). The model explains 89% of the variation in log green employment (R² = 0.89) and passes standard diagnostic tests for serial correlation, heteroskedasticity, normality, and parameter stability. Three correlates of long-run green employment are identified. The post-2016 dummy used to capture the Vision 2030 regime shift is associated with the largest coefficient in the long-run equation (θ = 1.75, p = 0.008), although this estimate should be interpreted with caution because the dummy absorbs all post-2016 changes, including policy effects, the rapid expansion of renewable capacity, broader institutional reforms, and possibly changes in measurement practices. Renewable energy capacity is the primary continuously measurable driver (θ = 0.145, p = 0.018), with Toda–Yamamoto modified Wald tests indicating a bidirectional predictive relationship between investment and employment. Urbanization exerts a significant positive long-run effect (θ = 0.098, p = 0.001). The error correction term (δ = −0.520, p < 0.001) implies equilibrium reversion with a half-life of approximately one year. The EKC hypothesis is not supported in the Saudi context, suggesting that active decarbonization policy—rather than income-driven structural change alone—is needed for environmental improvement. The findings carry implications for Vision 2030 implementation and for other resource-dependent economies undertaking structural green transitions. Full article

Achieving sustainable development requires decoupling economic growth from environmental degradation. In this context, this study examines the effects of tourism arrivals on CO₂ intensity and energy intensity, two key indicators of environmental sustainability aligned with SDGs 7 and 13. Panel autoregressive distributed lag (ARDL) and nonlinear ARDL models are employed using a balanced panel of 54 countries over the period 1996–2023. In addition, Wald tests for long-run asymmetry, dynamic multiplier analysis, and Dumitrescu–Hurlin causality tests are applied. The results confirm the existence of stable long-run relationships between tourism arrivals and both CO₂ intensity and energy intensity. In the symmetric framework, tourism growth is associated with significant long-run reductions in CO₂ and energy intensity, while short-run effects are negative and significant only for CO₂ intensity. In the asymmetric framework, positive tourism shocks generate stronger and more persistent reductions in both intensity measures, whereas negative shocks lead to weaker environmental efficiency gains. Moreover, the Wald test shows the existence of long-run asymmetry between positive and negative tourism shocks. In addition, the dynamic multiplier analysis confirms that environmental intensity adjusts gradually over time following tourism shocks. Finally, Dumitrescu–Hurlin causality tests indicate bidirectional Granger causality relationships between tourism arrivals and environmental intensity indicators. The findings are robust to dynamic endogeneity, the COVID-19 shock, and country heterogeneity. Overall, the findings indicate that tourism arrivals contribute to lowering long-term environmental intensity, consistent with relative decoupling and the goals of sustainable tourism development. Full article

This paper examines how remittances-to-GDP are conditionally associated with GDP growth upswings and downturns in four lower-middle-income countries (LMICs) in mainland Southeast Asia—Cambodia, Laos, Myanmar, and Vietnam (CLMV)—over 2000–2021, conditional on other external inflows including foreign direct investment (FDI), official development assistance (ODA), and trade openness. Employing a nonlinear Autoregressive Distributed Lag (N-ARDL) model with a Dynamic Fixed Effects (DFE) estimator, this study estimates short- and long-run regime-differentiated associations between GDP growth regimes and remittances to GDP, controlling for foreign direct investment (FDI), official development assistance (ODA), and trade openness. GDP growth is decomposed into above- and below-median regimes, allowing the model to examine whether remittance dynamics differ across growth upswings and downturns. Panel estimates are complemented with dynamic multipliers that trace conditional adjustment paths over different horizons. The results reveal a high-growth-driven regime pattern rather than formal statistical evidence of unequal high- and low-growth coefficients. In the long run, above-median growth significantly reduces remittances to GDP (${\widehat{\theta }}_1=-0.130$, very strong evidence), consistent with the household insurance motive; below-median growth has no significant long-run association (${\widehat{\theta }}_2=-0.127$, no evidence). In the short run, above-median growth is positively associated with remittances (${\widehat{\tilde{\beta }}}_1^{+}=0.033$, very strong evidence), while below-median growth again shows no significant short-run response (${\widehat{\tilde{\beta }}}_1^{-}=0.051$, no evidence). Formal Wald tests do not reject equality between the high- and low-growth coefficients in either horizon; therefore, the findings should be interpreted as a regime-differentiated significance pattern within a nonlinear specification, not as formal proof of coefficient asymmetry. Taken together, these responses are consistent with a one-sided counter-cyclical interpretation of remittances: remittances to GDP decline when domestic growth is above the median, while no significant adjustment is observed during below-median growth episodes. The pattern documented here is therefore driven by the high-growth regime and should not be read as evidence of an active counter-cyclical surge during downturns. Trade openness and ODA exhibit significant positive short-run co-movement with remittances, whereas FDI shows a strong positive long-run association with remittances to GDP. The novelty of this study lies in providing new panel evidence on regime-differentiated remittance–growth associations for CLMV within a nonlinear N-ARDL and dynamic multiplier framework, while transparently reporting that formal Wald tests do not reject equality between high- and low-growth coefficients. Policy implications center on facilitating reliable remittance channels—reducing transfer costs and expanding financial inclusion—without assuming that remittance inflows automatically rise during downturns. Full article

This study investigates the short-term and long-term impacts of gross domestic product (GDP), inflation, foreign capital flows, trade balance and interest rate on stock market performance in Saudi Arabia for the period 1990–2023. The autoregressive distributed lag (ARDL) approach and error correction model (ECM) are employed to empirically examine the short-run and long-run relationships. The ARDL-ECM technique is effective for analyzing cointegration and assessing adjustment processes. Additionally, impulse response function (IRF) analysis based on the vector autoregression (VAR) model, estimated using these macroeconomic indicators, is applied in this paper. This study provides novel insights and addresses emerging gaps in the literature concerning Saudi Arabia as a developing economy. The long-term relationship in the bounds test results confirms its existence. In the long run, inflation and interest rate exert a statistically significant negative effect on stock market performance, while the trade balance has a significant positive impact. GDP and foreign capital inflows do not exhibit statistically significant long-run effects. Short-run dynamics indicate persistence in stock market performance along with significant effects from inflation and interest rate changes, while GDP and foreign capital inflows remain statistically insignificant in the long-run scenario. Forecast error variance decomposition (FEVD) results show that approximately 68.5% of the variation in market performance is explained by its own shocks, followed by foreign capital flows (16.3%) and inflation (8.4%). While foreign capital flow does not exhibit statistical significance in the ARDL long-run estimates, its contribution in variance decomposition highlights its role as an important source of external shocks. These findings are relevant to various stakeholders, including investors and policymakers. Additionally, policy emphasis should be placed on controlling inflation and maintaining stable interest rates while improving trade balance conditions. Although foreign capital flow does not show a direct long-run effect, its role in influencing market variability suggests the need for a stable and well-regulated investment environment. Full article

This study investigates the relationship between energy indicators and human development in South Africa over the period 1980–2023, employing a quantitative research design. Using secondary annual time-series data, the study examines the effects of electricity generation, per capita energy consumption, Oil-related fiscal revenue share as a share of total government revenue, and total energy consumption on the Human Development Index. The Autoregressive Distributed Lag (ARDL) bounds testing approach is employed to assess long-run and short-run relationships, complemented by Error Correction Models (ECM) to capture dynamic adjustments. Unit root and stability tests, including CUSUM and CUSUMSQ, ensure the robustness of the estimations, while Granger causality tests explore predictive linkages among variables. The findings reveal a positive long-run relationship between electricity generation and total energy consumption with human development, highlighting the importance of reliable and broad-based energy utilisation for enhancing welfare outcomes. In contrast, per capita energy consumption and Oil-related fiscal revenue share exhibit negative long-run effects, suggesting inefficiencies in energy use and the fiscal risks associated with reliance on oil-related government revenue. Short-run dynamics indicate that temporary adjustments, such as infrastructure expansion and transitional fiscal spending, can produce immediate but contrasting effects on human development. Granger causality analysis identifies unidirectional predictive relationships from electricity generation and Oil-related fiscal revenue share to human development, while total energy consumption exhibits weak bidirectional causality. Diagnostic tests confirm the model’s reliability and parameter stability over the study period. The results imply that energy policies in South Africa should prioritise efficient and inclusive energy use, ensure effective allocation of energy-related fiscal resources, and complement energy system improvements with broader socio-economic interventions. This study contributes to the understanding of the energy–development nexus in emerging economies, offering evidence-based insights for policymakers seeking sustainable human development. Future research could extend the analysis to provincial or sectoral levels, consider emerging energy technologies, and explore alternative development proxies to capture more nuanced socio-economic dynamics. Full article

Proof-of-Work (PoW) cryptocurrency mining is conventionally characterised as an energy competition, yet this paper provides evidence that the primary competitive margin has shifted from electricity procurement to semiconductor acquisition. Using Bitcoin (BTC) and Bitcoin Cash (BCH)—two SHA-256 networks sharing identical hardware but differing in scale and governance—as a natural comparative setting, we apply the Autoregressive Distributed Lag (ARDL) bounds testing approach to 112 weekly observations (January 2019–March 2021). Mining reward exhibits near-unity long-run elasticity with respect to both hash rate and energy consumption (0.773–1.009), confirming miners’ price-taking behaviour. Critically, the shutdown threshold—an efficiency-based cost floor derived from ASIC hardware generations—dominates all cost-side regressors with elasticities of $-1.941$ to $-2.156$, substantially exceeding electricity price effects in both magnitude and significance. VAR analysis provides evidence consistent with a centralisation paradox: rising chip efficiency Granger-predicts increased mining pool concentration for BTC (${\chi }^2=33.64$, $p<0.001$) via a revenue-redistribution mechanism, while electricity costs carry no equivalent structural consequence. Zivot–Andrews tests confirm that China’s 2021 mining ban produced a significant transient disruption but no permanent structural break in BTC’s hash rate trajectory, consistent with the geographic mobility of capital-intensive hardware. These findings imply that standard energy-price policies address the wrong margin; effective governance of PoW sustainability requires redirecting regulatory attention toward the semiconductor supply chain—a conclusion with direct relevance to SDG 7 and SDG 13. Full article

This study examines the associations of land temperature anomalies and energy-related CO₂ emissions per hectare with wheat and maize yields in Romania and Serbia during 1992–2023. Energy-related CO₂ emissions per hectare are used as a scale-adjusted proxy for energy-use intensity and emissions associated with agricultural energy consumption, rather than as an indicator of climate intensity. The study contributes to the literature by applying a comparative ARDL framework to Romania and Serbia, two Central and Southeast European agricultural systems with different institutional contexts, integrating climate variability, nitrogen fertilizer use and energy-use-related emissions into a unified crop-specific analysis. Using the Autoregressive Distributed Lag (ARDL) framework, we estimate long-run equilibrium relationships and short-run dynamics between cereal yields and the selected explanatory variables. The results partially support the proposed hypotheses by indicating heterogeneous country- and crop-specific relationships. In Romania, nitrogen fertilizer use is positively associated with wheat and maize yields, while rising land temperature anomalies are negatively associated with maize productivity. In Serbia, energy-related CO₂ emissions per hectare show a statistically significant negative long-run relationship with maize yields, whereas no statistically robust long-run relationships are identified for wheat. The findings highlight the importance of energy efficiency, input optimization and country-specific decarbonization strategies for sustainable cereal production. Full article

This study examines the determinants of energy consumption in South Africa over the period 1980–2023 using a multivariate time-series framework. Unlike conventional studies that focus primarily on the energy–growth nexus, this analysis incorporates financial development, industrialization, and population growth to provide a more comprehensive understanding of energy demand dynamics. The Autoregressive Distributed Lag (ARDL) approach is employed to estimate both short-run and long-run relationships. Unit root tests confirm that all variables are integrated of order one, justifying the application of the ARDL bounds testing approach. The results reveal the existence of a stable long-run relationship between energy consumption and its determinants. Industrialization and population growth emerge as the most significant drivers of energy demand in both the short and long run, reflecting South Africa’s energy-intensive economic structure and rising demographic pressures. Financial development is found to have a positive and statistically significant effect, suggesting that improved access to credit stimulates energy consumption through increased investment and economic activity. In contrast, economic growth exhibits a positive but statistically insignificant long-run effect, indicating partial decoupling between output growth and energy demand. The error correction term is negative and statistically significant, confirming convergence to long-run equilibrium. Causality analysis further indicates that energy consumption is primarily driven by macroeconomic factors rather than acting as a leading indicator. The findings underscore the importance of industrial energy efficiency, population-responsive energy planning, and targeted financial support for sustainable energy investment. This study contributes to the literature by providing a comprehensive, country-specific analysis and offers policy-relevant insights for enhancing energy security and supporting sustainable economic development in South Africa. Full article

This study examines the dynamic impact of geopolitical risk (GPR) and renewable energy consumption (RENE) on energy security in Egypt from 2000 to 2023. Given the increasing regional instability and Egypt’s strategic pivot toward a green economy, this research employs the Autoregressive Distributed Lag (ARDL) bounds testing approach, which is robust for small sample sizes and mixed integration levels. The empirical results provide preliminary evidence of a long-run negative relationship between geopolitical risk and energy security (coefficient: −11.92), suggesting that external political shocks may act as a deterrent to energy stability. Conversely, renewable energy is found to exert an indicative positive influence (coefficient: +1.17) on the energy security index. Notably, these long-run coefficients are significant at the 10% level, implying that while these variables represent emerging structural trends, they remain sensitive to high regional volatility and the evolving nature of the Egyptian energy sector. Diagnostic tests, including Jarque–Bera (0.92) and Breusch–Pagan–Godfrey (0.94) tests, support the model’s reliability, while CUSUM and CUSUMSQ tests indicate general parameter stability. The study suggests that while renewable energy integration shows potential for enhancing resilience, its current scale may not yet be sufficient to fully counterbalance the potential pressures of geopolitical shocks. Policy implications point toward the strategic value of “geopolitical hedging” through continued green investment, the expansion of strategic reserves, and the adoption of de-risking financial instruments like Green Sukuk to support long-term energy sovereignty as a precautionary measure. Full article

This paper examines the relationship between macroeconomic scale, the structure of energy consumption, and carbon dioxide emissions in Poland over the period 2000–2023, against the background of the country’s energy transition under European Union (EU) climate policy. The study aims to identify the extent to which gross domestic product (GDP), hard coal consumption, natural gas consumption, and electricity generation from renewable energy sources (RES) explain the level of CO₂ emissions in a coal-dependent economy undergoing gradual structural change. The empirical analysis is based on annual data from Statistics Poland and applies two complementary econometric approaches: an Ordinary Least Squares (OLS) model to capture the baseline relationships and an Autoregressive Distributed Lag (ARDL) model to examine short-run dynamics and lagged effects. The OLS results show that the model explains a substantial share of emission variability and that coal consumption is the only statistically significant determinant of CO₂ emissions, with a strong positive coefficient. GDP, natural gas consumption, and RES production do not exhibit statistically significant effects in the baseline specification. The ARDL results indicate that coal has the strongest contemporaneous statistical association with emissions, while also suggesting weak autoregressive properties of the emission system and the absence of statistically significant short-run associations for GDP, gas, and renewables. Sensitivity analysis further shows that coal remains the variable most strongly associated with emission levels, whereas the estimated associations for GDP, gas, and RES are comparatively weak. The findings suggest that, in Poland, emission dynamics are more closely linked to the carbon intensity of the energy mix than to the scale of economic activity itself. The study suggests that effective decarbonization is likely to be associated with a structural reduction in coal dependence, while the emission-reduction potential of renewable energy expansion may become more visible over a longer time horizon. These results have important implications for the design of Poland’s energy and climate policy, suggesting that the success of the transition is closely linked to changes in the structure of energy carriers in a way consistent with economic and infrastructural constraints. Full article

Purpose: This study examines the asymmetric effects of economic growth, energy consumption, renewable energy, trade openness, and innovation on CO₂ emissions in China and India. It aims to determine whether positive and negative shocks in these variables generate different environmental responses across economies undergoing energy transition. Design/methodology/approach: The analysis employs a Nonlinear Autoregressive Distributed Lag (NARDL) model using annual data from 1990 to 2023. The framework decomposes explanatory variables into positive and negative partial sums to estimate asymmetric long-run and short-run effects. Dynamic multipliers are used to trace adjustment paths, while a symmetric ARDL model serves as a robustness check. Findings: The results reveal strong and persistent asymmetries in China, particularly in energy use, renewable energy, and innovation. Positive energy shocks significantly increase emissions, while reductions produce limited environmental gains, reflecting structural rigidities. Renewable energy reduces emissions asymmetrically, and innovation exhibits direction-dependent effects. In contrast, India shows weaker and more selective asymmetries, with emissions primarily driven by short-run energy demand and limited long-run structural effects. The symmetric model fails to capture these dynamics, confirming the importance of nonlinear modeling. Conclusion: The findings demonstrate that emissions dynamics are nonlinear and country-specific. Asymmetry is more pronounced in structurally advanced economies undergoing energy transition, while developing economies remain demand-driven. These results highlight the need for differentiated and context-specific environmental policies. Full article

Saudi Arabia has consistently had low insurance penetration (around 0.89% of GDP over the previous three decades), which is far lower than the worldwide average and the goals set by Vision 2030. This research examines the factors influencing insurance penetration (INSP) in Saudi Arabia from 1990 to 2024, primarily testing the demand-following hypothesis which posits that sustainable economic growth acts as a key determinant of insurance demand. The Kingdom intends to diversify its economy as part of Vision 2030 by lowering its dependence on oil, boosting the use of renewable energy, expanding financial markets, and strengthening resilience. The insurance industry is becoming more and more important for managing risk, making green investments, and allocating long-term capital. The analysis employs annual data and the Autoregressive Distributed Lag (ARDL) bounds testing methodology to investigate both short- and long-term relationships between insurance penetration and five critical variables: sustainable economic growth (SD, indicated by GDP per capita growth), financial development (FD, domestic credit to the private sector as a percentage of GDP), renewable energy consumption (REC, percentage of total final energy consumption), trade openness (TO), and urbanization (URB). The main results show that the insurance industry is very route dependent. In the long term, sustainable economic growth, financial development, and the use of renewable energy all have big beneficial effects on insurance penetration. This shows how important they are for extending the insurable base and supporting green investments. Urbanization has a little negative but statistically weak long-term impact (coefficient −0.0056, p < 0.10), while trade openness does not have any effect at all. In the near term, using renewable energy is the biggest positive driver (coefficient 0.096, p < 0.01). This shows how important insurance is in paying for and reducing the risk of energy transition. These findings are resilient to CUSUM and CUSUMSQ stability assessments. This study makes a unique contribution to the field by presenting the first single-country cointegration analysis of an oil-rich economy undergoing structural transformation, directly correlating the adoption of renewable energy with insurance demand, supported by data extending to 2024. The results show that making insurance markets work with the Saudi Green Initiative through green insurance products, mandated coverage for private finance, and digital/micro-insurance aimed at city dwellers can help Vision 2030 targets be reached faster. Policy suggestions stress the need to combine insurance with changes in the financial and renewable energy sectors in order to reach greater penetration goals (which have recently been raised to 3.6–4.5% levels) and build a more diverse, strong, and low-carbon economy. Full article

Energy remains fundamental to economic growth and national development, yet Egypt faces a persistent challenge in expanding energy supply without deepening dependence on conventional sources. Although earlier studies examined the determinants of energy use, limited evidence exists on whether macroeconomic and environmental factors differently affect renewable energy consumption (REC) and non-renewable energy consumption (NREC) in the Egyptian context. This study addresses this problem by examining the roles of economic growth, financial development, the ecological footprint, and economic globalization in shaping REC and NREC in Egypt over the period 1970 to 2024. To achieve this objective, the study employs the Autoregressive Distributed Lag (ARDL) approach, which is suitable for estimating short-run dynamics and long-run relationships among variables with mixed orders of integration. The results indicate that across the REC models, economic growth increases renewable consumption, while the ecological footprint reduces it, indicating that environmental pressure has not translated into stronger REC. Financial development exhibits as a negative in the long run, suggesting finance has not been consistently directed toward renewables. Although economic globalization is insignificant, trade and financial globalization reduce REC in the long run. For the NREC models in the long run, GDP, financial development, and ecological footprint increase NREC. Economic, trade, and financial globalization effects are mostly insignificant for NREC, implying that domestic fundamentals drive conventional energy use. Thus, the findings suggest that Egypt’s energy structure is still driven more by domestic growth and financial conditions than by external integration. However, these results should be interpreted as evidence of association within the ARDL framework rather than proof of causality. The study therefore highlights the need for policies that align economic growth with renewable energy expansion, improve the direction of finance toward green investment, and strengthen the institutional conditions necessary to support a more sustainable energy transition Full article

This research explores how livelihood capital endowments affect the growth of Non-Wood Forest Products (NWFPs) in rural communities in the Koyten Dag region of Turkmenistan. This study is grounded in the Sustainable Livelihoods Framework. It draws on the Capability Approach, Institutional Theory, and Human Capital Theory, which are considered to have a strong influence on NWFP development within the exclusive post-Soviet socio-ecological environment. This study also uses annual time-series data from 2001 to 2024. It applies the ARDL bounds testing method to examine the short- and long-run associations among livelihood assets and NWFP production. The results confirm strong long-run co-integration, indicating that the five capitals have a significant impact on NWFP development. Emerging as the ultimate drivers in both the short and long term, education, skills, health, and digital connectivity become especially important. Financial and social capital reflect long-term contributions, while natural capital highlights the significance of the availability of ecological resources and governance systems. The correction error term indicates a rapid rate of adjustment, suggesting that the livelihood system is robust and can return to equilibrium quickly in response to temporary shocks. This research uses the Autoregressive Distributed Lag (ARDL) method of co-integration, which is effective for small-sample analyses of long-run relationships. The empirical analysis is conducted in a systematic process, which is the unit root tests based on augmented Dickey–Fuller (ADF) and Phillips–Perron (PP) techniques, in order to establish the order of integration of variables. The Akaike Information Criterion (AIC) is used to determine the appropriate lag length for the ARDL model to achieve the best model specification. In the robustness analysis, we perform fully modified OLS (FMOLS) and dynamic OLS (DOLS) estimation. Sub-period analysis was performed to test structural breaks. The variance inflation factor (VIF) test was used to detect multicollinearity. This paper has significant theoretical and practical implications, including the need for policies that are integrative and, at the same time, enhance human capabilities, digital infrastructure, institutional quality, and resource governance. This knowledge can be used to promote the sustainable development of rural areas and as an efficient approach to the NWFP sector in Turkmenistan. Full article