Search Results (807)

Background: This study revisits whether oil revenue windfalls translate into higher socio-economic welfare in oil-exporting economies and explains why oil price booms often fail to generate sustained gains in real GDP per capita. Methods: Using annual data for ten oil-exporting countries over 1990–2024, we estimate country-specific ARDL/ECM models under a unified specification. The dependent variable is log real GDP per capita, explained by log real oil prices, the log share of government expenditure in GDP, population growth, and world GDP growth, with political and devaluation dummies where relevant. Results: Cointegration and significant error correction terms hold for most exporters, but adjustment speeds differ sharply. Long-run oil price elasticities are heterogeneous: strongly positive in Qatar, weak or insignificant in several cases (including Azerbaijan), and negative in a post-rentier pattern (UAE/Oman). Fiscal and demographic channels emerge as systematic constraints: government expenditure shares are often negatively associated with long-run welfare, and population growth typically reduces GDP per capita. World GDP growth is generally positive but uneven in significance. Conclusions: Resource use is conditional: welfare outcomes depend on fiscal regimes, demographic pressures, and structural transformation rather than windfall size alone. Full article

The objective of this research is to analyze the impact of consumer price index, exchange rate, broad money supply, and export on tax revenue in Cambodia. The short-run effects from the ARDL cointegration model suggest that inflation negatively influences tax revenue. Changes in the exchange rate also had a negative effect on tax revenue, although the power of this influence was large. On the other hand, an increase in money supply was realized to improve tax revenue performance as revealed by a positive and statistically significant coefficient of broad money. The empirical results also indicate that the impact of exports on tax revenue was insignificant. The error correction term indicates that the flow adjustment was fast, in that about 83.76% of short-run deviations were corrected in one period, thus enabling the quick restoration to the long-run equilibrium after transient disturbances. In the long-run, only exchange rate and broad money were found to be statistically significant determinants of tax revenue. The relationship was found to be negative for exchange, but positive for broad money. Full article

This study analyzed how both environmental sustainability and energy efficiency influence economic growth in Romania. The analysis in the research is based on sustainable development goals such as SDG8, SDG11 and SDG13, and several key indicators in the area of sustainability are analyzed for the period 2000–2022, such as: municipal waste recycling rate (RRMW), energy productivity (EP), greenhouse gas emissions (GHG) and renewable energy share (RENE). In this regard, the Autoregressive Distributed Lag (ARDL) model was used to capture both short-term and long-term effects. The results obtained show that energy productivity has a positive and significant impact on economic growth. This confirms the important role of energy efficiency in strengthening a sustainable economy. It has also been observed that greenhouse gas emissions are positively correlated with GDP in the short term, and the waste recycling rate has a negative effect. Regarding renewable energy, the long-term influence is not statistically significant, indicating the need for more effective policies to accelerate the energy transition. The analysis highlights the significance of a comprehensive strategy in the field of environmental and energy policies to promote stable and sustainable economic development, while providing valuable guidance for Romania’s strategic alignment with the European Union’s sustainable development goals. Full article

South Africa’s shift to renewable energy has been characterised by significant structural changes, primarily through the Renewable Energy Independent Power Producer Procurement Programme (REIPPPP), which achieved considerable capacity by 2016. Although this green transition aligns with environmental and economic goals, gender inequities persist in labour market outcomes, particularly in technical and leadership positions. This study examines the short- and long-term impacts of renewable energy investments and important socioeconomic elements on female labour force participation (FLFP) in South Africa. Applying a bounds testing approach based on a semi-annual autoregressive distributed lag (ARDL) model, this analysis utilises data from 2003 to 2022. It includes factors such as renewable energy investments, the share of green jobs, GDP per capita, and access to modern energy services. The results indicate a statistically significant long-term equilibrium relationship. Increased renewable energy investments align with increases in FLFP, and the growth of green jobs further boosts women’s workforce participation. GDP per capita additionally has a positive impact, highlighting the macroeconomic advantages of inclusive growth. On the contrary, access to existing energy services shows a statistically insignificant negative relationship with FLFP, suggesting that merely expanding infrastructure may not effectively tackle gendered labour disparities. This study adds to the field of energy economics by providing a gender-segregated empirical evaluation and by suggesting policy actions to foster a more inclusive and fair energy transition in South Africa. Full article

This research examined the long-run effect of climate change on food security in Malawi, Madagascar, Mozambique and Zimbabwe using the Autoregressive Distributed Lag (ARDL) model. The study used nine variables for quantitative analysis using data for the four countries from the World Bank spanning from 2000 to 2023, using two models. The results were validated using the pooled mean group (PMG) estimator. The results from model 1 show that environmental temperature, fertiliser consumption, credit access, age dependency ratio, urbanisation and land size significantly affect the percentage of crop yields. The model 2 results show that all the aforementioned factors, including cereal temperature and yields, have an effect on the prevalence of malnutrition, which was a proxy for food security in this study. Furthermore, the study used the Granger causality test to indicate a unidirectional causality direction from both models’ independent variables to dependent variables. From the econometric analysis conducted, the findings highlight the urgent need for targeted interventions, such as promoting climate-resilient agriculture, expanding access to credit and social protection policies, to enhance nutritional well-being and improve resilience to climate shocks. Full article

China’s export-oriented economic expansion has substantially influenced transport-sector CO₂ emissions, raising critical concerns about the environmental impacts of sustained industrial growth and global trade integration. Understanding the interplay between macroeconomic dynamics, trade composition, and industrial structure is essential for aligning economic development with climate mitigation objectives. This study examines transport-related CO₂ emissions in China over the period 1990–2023, employing a hybrid methodological framework that combines econometric modeling—including Autoregressive Distributed Lag (ARDL) bounds testing, Fully Modified Ordinary Least Squares (FMOLS), and Dynamic Ordinary Least Squares (DOLS)—with machine-learning techniques using Extreme Gradient Boosting (XGBoost) interpreted through SHapley Additive exPlanations (SHAP). The analysis confirms a long-run cointegration relationship between transport emissions and the selected macroeconomic variables. Short-run dynamics indicate a strong sensitivity of emissions to GDP growth, while long-run estimates reveal that higher export-to-GDP ratios and industrial value added contribute to reducing transport emissions, reflecting the efficiency gains from industrial upgrading and cleaner trade practices. By contrast, the expansion of medium- and high-technology exports increases emissions due to the energy- and logistics-intensive nature of high-value goods. The XGBoost model achieves high predictive performance, with an out-of-sample R² of 0.9975 and a Root Mean Square Error (RMSE) of 87.16, confirming the dominant contribution of medium- and high-technology exports to transport-sector emissions. The results underscore the critical role of aligning trade structure, industrial productivity, and low-carbon logistics within China’s policy agenda. Implementing strategies that enhance industrial energy efficiency and develop sustainable transport infrastructure can substantially reduce the environmental impacts associated with export-driven economic expansion. Full article

This study aimed to identify changes in beef trade between the European Union and South American countries and to assess the potential economic impact of implementing the EU–Mercosur agreement on the beef market. The research problem asked: How might trade liberalisation under the EU–Mercosur agreement affect the volume, structure, and competitiveness of the beef market between the EU and Mercosur countries? The research used data on beef production, import, export, and consumption in the European Union and South America. The detailed analysis covered the years 2010–2024. In addition, based on USDA data, a forecast of beef production in the EU and Mercosur countries up to 2030 was prepared. The analyses employed descriptive and indicator methods, Spearman’s rank correlation analysis, and the ARDL (Autoregressive Distributed Lags) model. The results indicate that beef production is increasing in the Mercosur countries and declining in the European Union. The ARDL models showed that beef trade depends on previous production and demand, and imports to the EU respond to changes in these areas with a delay. Increasing the tariff quota for beef imports from the Mercosur countries to the EU at a reduced customs rate may increase the share of this meat in the EU market. Preferential trade conditions raise concerns among EU producers, who must comply with stricter environmental standards and higher production costs, while less restrictive practices are applied in Mercosur countries. As a result, European agriculture, especially in Poland, may become less competitive, which calls for support mechanisms and further negotiations on sustainable production. Full article

This study applies a multiple threshold nonlinear autoregressive distributed lag (MTNARDL) model to examine the asymmetric impact of real exchange rate volatility on Vietnam’s exports and imports with its three leading trading partners: China, the United States, and South Korea. By allowing trade responses to vary across different volatility regimes, the MTNARDL framework provides a flexible approach to capturing potential nonlinear adjustment dynamics that cannot be addressed by single-threshold models. Moreover, using bilateral import and export data helps reduce aggregation bias. The results indicate the presence of asymmetric long-run adjustment dynamics in the relationship between real exchange rate volatility and bilateral trade flows, while short-run effects are generally weak and less consistent across trading partners. These findings provide valuable insights into the complex effects of exchange rate volatility, enabling policymakers to more effectively design and manage policies to mitigate its impact. Full article

Rapid urbanization and infrastructure expansion in Ghana have intensified demand for concrete, yet reliable, context-specific forecasting tools to support long-term infrastructure planning and resource management remain limited. Existing demand models are largely developed for advanced economies or focused on cement production rather than final concrete consumption, limiting the applicability to rapid urbanizing developing countries. This study addresses this gap by developing an integrated forecasting framework to quantify and project concrete demand in Ghana. Using time-series data spanning 2000–2025, the study employs a modelling approach that combines the Autoregressive Distributed Lag (ARDL) model and Error Correction Model (ECM) to examine both short- and long-run relationships between concrete consumption and key macroeconomic indicators, including GDP, population, GDP growth, concrete prices, housing loan interest rates, lending rates, and exchange rates. Forecast results for 2025–2030 indicated a sustained upward trend in concrete consumption, increasing from 39,278.52 m³ in 2026 to 99,430.53 m³ in 2030, with an average annual growth rate of 26.3% and a mean projected demand of 67,730.83 m³. Model evaluation metrics demonstrated high predictive accuracy, confirming the robustness of the proposed framework. The study contributes to the literature on construction demand forecasting by providing a context-specific, empirically validated model of concrete consumption in a developing economy. The findings offer actionable insights for policymakers, urban planners, and construction managers, underscoring the need to proactively scale local production capacity, strengthen supply-chain logistics, and promote sustainable material sourcing to support infrastructure development. Full article

This study examines the determinants of profitability for 21 Bulgarian commercial banks over the period from the first quarter of 2007 to the first quarter of 2025, using financial statement data. Bank profitability is measured by return on assets (ROA) and return on equity (ROE) and modeled within a panel autoregressive distributed lag (PMG-ARDL) framework. The empirical specification combines bank-specific and macroeconomic variables, allowing for the identification of both long-run equilibrium relationships and short-run bank-level dynamics. The long-term results indicate that the net interest margin (NIM), net fee and commission margin (NFM), government bond yields, the growth of the gross domestic product (GDP), and the loan-to-deposit ratio (LDR) positively affect profitability. On the other hand, higher unemployment, rising housing prices, increased loan loss impairments, and the ratio of cash holdings to total assets reduce profitability. The findings provide policy-relevant insights for bank management, regulators, and macroprudential authorities regarding efficiency, income diversification, and credit risk management. The findings facilitate a more comprehensive assessment of banking sector resilience and provide a foundation for the development and refinement of macroprudential and supervisory policy measures. Full article

This study analyses the long-run relationship between governance quality and renewable energy development using a global panel of 174 countries over the period 2000–2023. The objective is to assess whether institutional quality systematically influences renewable energy deployment across heterogeneous development contexts. The empirical analysis employs a panel autoregressive distributed lag (PMG-ARDL) framework, which accommodates mixed integration orders and allows for heterogeneous short-run dynamics while imposing homogeneity on long-run coefficients. Renewable energy consumption, measured as the share of renewable energy in total final energy consumption, is modelled as a function of governance quality indicators, economic development, and environmental pressure, with trade openness and foreign direct investment included as control variables. Panel unit root tests indicate a mixture of I(0) and I(1) variables, supporting the use of the ARDL framework, while panel cointegration tests provide strong evidence of a stable long-run relationship in the estimated model. The results reveal a statistically significant long-run association between governance quality and renewable energy development, although the magnitude and direction of the effects vary across governance dimensions and development levels. In contrast, short-run effects are generally weak, suggesting that governance primarily shapes renewable energy outcomes through gradual, structural channels. These findings highlight the importance of institutional quality for long-term energy transition processes and provide empirically grounded insights for the design of energy and governance policies. The analysis reveals significant heterogeneity across development contexts: governance improvements yield positive effects on renewable energy adoption in low-income countries (β = +3.77), where institutional deficits constitute binding constraints, whilst the effect becomes negative in high-income economies (β = −11.87), reflecting diminishing returns and infrastructure lock-in. These findings suggest that developing countries should prioritise governance reforms—particularly Regulatory Quality and Political Stability—to accelerate energy transitions, whereas advanced economies should shift policy attention toward grid modernisation and market design. International organisations should adopt differentiated climate finance strategies matching institutional support to the development stage. Full article

The study investigates the dual transitions of digitalization and renewable energy in Thailand to see if digital expansion facilitates the transition to renewable energy sources and greenhouse gas (GHG) mitigation. The study utilized data from the World Bank between 2000 and 2023 to reconstruct models for autoregressive distributed lag (ARDL) analysis for short-run and long-run dynamics under ecological modernization and technology diffusion theories. Contrary to expected synergies, empirical results revealed that a developing economy would find an ‘investment trade-off’ instead. Digitalization showed no significant immediate impact on renewable energy production; however, it exerted a significant negative lagged effect (coefficient = −0.593), suggesting that digital and energy infrastructures compete for limited financial resources. It was found that there is a 6.3% increase in greenhouse gas emissions for every 1% increase in internet usage. Thus, these results challenge the belief that increased internet usage will help improve the environment. Absent proper supportive policies about both digitalization and green transitions, such as investing in plants and machinery towards digitalization rather than green technology, the pacing effects of digitalization will affect the goals of converting to clean energy. This requires a policy coordination approach to ensure that funds earmarked for green infrastructure are safeguarded. Full article

This study analyzes the determinants of gross saving in Jordan over the period 1991–2023, with particular attention paid to the role of macroeconomic and demographic factors in shaping saving behavior. The empirical analysis employs the Autoregressive Distributed Lag (ARDL) bounds testing approach to examine both short-run and long-run relationships between gross saving, the age dependency ratio, real per capita GDP growth, real interest rates, and unemployment. The results indicate rapid short-run adjustment dynamics in saving behavior and a stable long-run association between saving and its key determinants. In contrast to standard theoretical predictions, a higher dependency ratio is found to increase gross saving. This outcome appears to reflect Jordan’s socio-demographic context, precautionary saving motives, family-based support mechanisms, limited social security coverage, and the role of remittances. Income growth has a positive effect on saving, while unemployment exerts a negative effect. The real interest rate exhibits limited and transitory short-run effects, while remaining insignificant in the long-run. From a policy perspective, the findings underscore the importance of job creation, sustained income growth, and the development of broader saving instruments. Full article

Achieving sustainable economic growth by addressing structural and environmental issues has become a top priority for decision-makers worldwide. This study investigates the impacts of renewable energy use, export diversification, and agricultural growth on sustainable economic development among G-20 economies. The analysis employs panel data from 1990 to 2021 with second-generation panel econometric methods, such as the PMG-ARDL test and dynamic panel estimation techniques, to elucidate both short- and long-term relationships. To examine the stationarity of the data series and identify cross-sectional dependence, this study applies some panel unit root tests, including the Cross-Sectionally Augmented Im and Pesaran test, the cross-sectional dependence (CSD) test, the Cross-Sectional Augmented Dickey–Fuller (CADF) test, and the Im, Pesaran, and Shin (IPS) test. The Westerlund co-integration test is employed to explore long-term relationships among the variables. To assess the prolonged impact of these factors, this study adopts the Pooled Mean Group–Autoregressive Distributed Lag (PMG-ARDL) approach. Findings reveal a statistically significant and persistent relationship between the variables, indicating that agricultural growth, renewable energy utilisation, and export diversification negatively affect economic growth. All insights highlight critical implications for G-20 policymakers; countries can develop a more resilient and sustainable economic pathway by addressing obstacles in agriculture, clean energy, and trade diversification. Full article

This research examines how financial development, energy efficiency and energy inefficiency, green technology, and research and development (R&D) affect environmental conditions and ecological footprint in the Group of Seven (G7) countries. The study combines two theoretical models, including the Environmental Kuznets Curve (EKC) and the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT), within a unified framework. This study addresses a key gap in the literature by examining whether financial development follows a distinct nonlinear environmental pathway beyond the traditional income-based EKC framework. Using annual data from 1994 to 2023, the analysis applies the Cross-Sectional Autoregressive Distributed Lag (CS-ARDL) approach to account for cross-sectional dependence and long-run heterogeneity among G7 economies. The findings indicate that the G7 does not support the traditional EKC hypothesis, although a U-shaped relationship between environmental degradation and financial development exists. Energy-related factors play a central role in shaping environmental outcomes, with energy efficiency and green technology significantly alleviating environmental pressure, and green technology proving to be the most influential among them. While energy inefficiency is associated with greater environmental stress, its effect remains statistically insignificant, suggesting that efficiency improvements are more decisive than reductions in inefficiency. Beyond energy dynamics, financial development and R&D investment also contribute significantly to environmental improvement, highlighting the complementary role of technological progress and financial systems in promoting environmental sustainability. The robustness results confirm the main findings. Overall, the study underscores the critical role of technological innovation and energy efficiency in promoting sustainability and challenges the applicability of the traditional EKC framework in advanced economies. The findings contribute to a deeper understanding of the multifaceted relationships between financial development, energy efficiency and inefficiency, green technology, and R&D, and their implications for sustainable development. Full article