Search Results (77)

This study examines selected factors influencing white maize price movements in South Africa over the period 1994–2024. Given the importance of white maize for food security, understanding the drivers of producer price dynamics is essential for effective policy formulation and managing price stability. Annual time-series data are analysed using an Autoregressive Distributed Lag (ARDL) modelling framework, complemented by bounds testing, an error-correction model, Toda–Yamamoto causality and structural break tests. The bounds test confirms the existence of a stable long-run cointegrating relationship between maize prices and the selected explanatory variables. In the short run, imports and fuel prices exert significant upward pressure on maize producer prices, while lagged fuel prices and rainfall reduce prices. In the long run, imports and fuel prices remain statistically significant determinants, whereas maize production, exports, the exchange rate, and rainfall are insignificant. Complemented with the structural break tests that identify regime shifts in the early 2000s, 2012, and 2021, causality results indicate that imports, rainfall and fuel prices lead to Granger causality in maize producer prices. Collectively the findings reinforce the conclusion that white maize prices in South Africa are governed by long-run structural relationships, while short-run price movements reflect temporary adjustments rather than permanent shifts in market fundamentals. An integrated, long-horizon analysis that jointly incorporates climatic, trade, and macroeconomic determinants within an ARDL framework is provided by the study. Therefore, the findings have important implications for climate-risk management, transport cost containment, trade and price-stabilisation policies. Full article

Decoupling between CO₂ emissions and economic growth is critical to reversing climate change. The OECD plays a crucial role in this regard, given its considerable share of global CO₂ emissions and GDP. This study examines the decoupling performance and the roles of renewable energy transition, as well as specific eco-innovations on climate change mitigation and environmental technology development across the OECD economies. The preliminary tests on a large panel of OECD countries identify cross-sectional dependence, structural breaks and heterogeneity. For robustness, the study proposes Fourier-CS-ARDL, Fourier-AMG, and Fourier–Dumitrescu–Hurlin methods as generalizations of their linear counterparts. After identifying cointegration and its singularity with Fourier-bootstrapping bounds and Fourier–Johansen tests, the modeling stage suggested a positive, but significantly inelastic long- and short-run elasticity of emissions to economic growth. Most of these effects are reversed by renewable energy transition in the long run and partially reversed in the short run. These CO₂ mitigation effects are also evident across different eco-innovations with varying temporal impacts. Novel Fourier causality tests identify feedback loops between CO₂ and CO₂-mitigating factors, as well as unidirectional causality from growth to all mitigating factors, confirming the indirect effect of growth on CO₂ mitigation. Overall, these results clearly suggest “relative” decoupling in OECD accompanied by CO₂e mitigation effects from eco-innovations and energy transition, and highlight the potential for green growth following the successful adaptation of energy transition and eco-innovations. Policymakers in OECD are encouraged to leverage the identified feedback mechanisms and establish international technology transfer policies to homogenously curb CO₂ emissions. Full article

This study examines the short-run dynamics and long-run determinants of bilateral trade between Saudi Arabia (KSA) and Jordan during the period of 1995–2024 using the autoregressive distributed lag (ARDL) bounds testing approach. Employing a country-pair time series framework, the analysis examines how economic growth, foreign direct investment (FDI), inflation differentials, and crude oil prices affect trade volume between the two countries over time. The ARDL bound test confirms the presence of long run cointegration among the variables. The Long-run results suggest that crude oil prices, inflation differential, and FDI exert positive and statistically significant effects on bilateral trade, while Saudi economic growth and FDI show negative long-run effects, suggesting that Saudi’s economy structural characteristic and domestic absorption may decrease the demand for Jordanian’s products in the long-run. The short-run results reveal a negative and statistically significant error-correction term, confirming convergence toward long-run equilibrium with approximately 32.16% of deviations corrected each year, implying a moderate speed of adjustment following economic shocks. In the short-run, economic growth, FDI, Inflations differentials, and oil prices exert significant but mixed effect on trade volume, with oil prices emerging as the most influential determinant. Several variables displayed lagged responses due to adjustment costs, production constraints, and contractual rigidities between the two countries. Overall, the findings contribute new time-series evidence on the macroeconomic drivers of bilateral trade between an oil-exporting economy such as Saudi Arabia and a neighboring non-oil-exporting partner like Jordan, offering policy insights for strengthening trade integration and economic cooperation. 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 research experimentally investigates the association between multidimensional risk factors and economic growth, quantified by GDP as a partial indicator of advancement towards economically relevant Sustainable Development Goals (SDGs). This research experimentally investigates the correlation between multidimensional risk variables and economic growth, quantified by GDP as a partial indicator of advancement towards economically relevant Sustainable Development Goals (SDGs) in Saudi Arabia, particularly in alignment with the objectives of Saudi Vision 2030. This study utilizes annual data from 1990 to 2024 and employs the Autoregressive Distributed Lag (ARDL) bounds testing approach to examine the short-run and long-run relationships between economic growth, as measured by GDP, and five key risk dimensions: governance effectiveness, financial development, environmental pressure, human capital, and oil price volatility, which act as proxies for risk dimensions. The main contribution of this study is the integration of these governance, financial, environmental, human capital, and oil price risk factors into a single ARDL framework for Saudi Arabia from 1990 to 2024, using GDP growth as a proxy for progress toward SDGs within the Saudi Vision 2030 context, addressing gaps in prior studies that focus on individual determinants. The empirical evidence indicates a long-term cointegration relationship among the variables. Our findings indicate that government effectiveness and investment in human capital are important positive factors associated with long-term economic growth, thereby validating the importance of institutional improvements and educational expenditures. In contrast, fluctuations in oil prices and environmental pressures are linked to adverse association, highlighting issues related to resource dependency and ecological degradation. Financial development exhibits a negative long-run association, indicating potential inefficiencies or diminishing returns in loan distribution. The study offers essential policy recommendations, such as expediting digital governance reforms, allocating financial resources to non-oil SMEs (SDG 8), aligning educational curricula with labor market demands, and implementing stricter environmental regulations to separate economic growth from emissions. Full article

In this paper, we analyze the impacts of financial innovation and financial deepening on the economic growth of 14 sub-Saharan African (SSA) countries from 1995 to 2023. The autoregressive distributed lag (ARDL) approach and error correction model (ECM) were used to assess short- and long-run effects. The findings indicate that mobile cellular subscriptions and government spending are the main contributors to national economic growth and that money supply has a positive impact. However, the strong negative effect of capital formation on economic growth is contrary to expectations. Conversely, the findings confirm that gross capital formation has a strong positive effect on gross domestic product (GDP) growth in the long run. Bounds testing reveals varying degrees of cointegration across countries. Long-run relationships were confirmed in Senegal, Côte d’Ivoire, Ethiopia, and Zimbabwe, all of which showed evidence of strong cointegration. These findings support policy recommendations aimed at promoting sustainable economic growth in SSA economies through targeted policies that increase domestic credit in the private sector and attract foreign direct investment (FDI). Full article

Using the Autoregressive Distributed Lag (ARDL) model cointegration framework, this paper examines the long- and short-run impact of domestic financial investment and natural resource rents on economic growth in Niger within the period 1990–2021. The Bounds test confirms a long-run relationship among variables: F = 4.646 > 3.79 at 5%. Long-run results indicate that increasing domestic investment by 1% raises real Gross Domestic Product (GDP) per capita by approximately 0.30%, whereas 1% increase in natural resource rents leads to a reduction in growth by approximately 0.06%. At the same time, exports have a positive but very small effect, while imports and labor have negative long-run influences. Short-run dynamics further support a significant positive impact of domestic investment, at p = 0.0007, and a lagged effect of natural resources at p = 0.0308. The error-correction term is negative and significant, at −0.75, showing rapid adjustment toward equilibrium. Diagnostic tests confirm an absence of serial correlation and heteroskedasticity, while stability is confirmed by CUSUM and CUSUMSQ tests. The findings reveal a dualism in the growth path of Niger in that domestic financial investments favor sustainable expansion, whereas resource-based revenues undermine the growth process in the long run and call for financial market deepening and improved governance of resource revenues. Full article

This study investigates the role of fossil fuel energy efficiency (FFE) in shaping environmental sustainability in Türkiye, with particular emphasis on the moderating effect of trade openness (TO) over the period 1982–2023. Environmental sustainability is proxied by the Load Capacity Factor (LCF), which integrates ecological footprint and biocapacity within the Load Capacity Curve (LCC) framework. Long-run relationships are examined using the Fourier ARDL bounds testing approach to account for structural breaks, while coefficient robustness is ensured through Fully Modified Ordinary Least Squares (FMOLS) and Canonical Cointegrating Regression (CCR) estimators. The empirical findings indicate that improvements in energy efficiency contribute positively to environmental sustainability, and this effect is significantly strengthened when energy efficiency interacts with trade openness (FFE × TO). This suggests that trade openness enhances the environmental gains of energy efficiency through technological spillovers. In addition, the results reveal an inverted-N-shaped nonlinear relationship between economic growth and environmental sustainability, indicating varying environmental pressures across different income levels. Overall, the findings highlight the importance of integrating trade policies with energy efficiency-oriented green technology strategies to achieve sustainable environmental outcomes in Türkiye. Full article

While extensive research has explored the determinants of foreign direct investment (FDI) and foreign portfolio investment (FPI) in BRICS nations, there remains a notable gap in understanding the influence of intangible factors, particularly soft power and nation branding. Historically, academic discourse has underemphasized the role of nation branding as a crucial emotional and perceptual component in investment decision-making processes. Consequently, governments in BRICS countries must enhance their national branding efforts to attract both capital and portfolio investment flows. The principal aim of this study was to jointly analyse the tangible and intangible determinants influencing FDI and FPI in BRICS from 1994 to 2024. Employing advanced econometric techniques, specifically the Autoregressive Distributed Lag (ARDL) bounds testing approach for cointegration and Vector Error Correction Models (VECM) for estimation. This study makes a unique contribution to existing literature by examining the nexus between nation branding, FDI and FPI, thereby introducing a novel perspective on the factors driving investment in the BRICS context with an emphasis on non-tangible determinants. The findings indicate that nation branding, along with exchange rate stability, property rights, and financial market development, are significant positive determinants of FPI in these countries. Conversely, capital openness demonstrated a negative relationship with FPI. Moreover, the positive impact of nation branding on FDI within BRICS nations was reaffirmed. This study substantiates the critical role of nation branding as a pivotal driver for both FDI and FPI, emphasising its strategic importance in the economic landscape of BRICS countries. Full article

This study investigates the dynamic relationship between key macroeconomic indicators, specifically inflation (CPI), the Federal Funds Rate, GDP growth, unemployment, and money supply, and U.S. stock market returns, represented by the S&P 500 index, over the period January 2015 to June 2025. The objective is to understand how inflation and monetary policy affect market performance in both the short and long run. Using an Autoregressive Distributed Lag (ARDL) modeling framework and Error Correction Model (ECM), the study examines monthly S&P 500 returns alongside macroeconomic variables, accounting for lagged effects and potential cointegration. The model captures both immediate and delayed impacts, employing the Bounds Testing approach to confirm long-run equilibrium relationships. Results show significant mean-reversion in stock returns, a delayed negative impact of inflation and interest rate increases, and a positive contemporaneous response to GDP growth. Unemployment exhibits a counterintuitive positive effect on returns, suggesting forward-looking investor expectations. The money supply also positively influences equity prices, supporting liquidity-based asset pricing theories. This paper provides updated empirical evidence on macro-finance linkages and highlights the complex interplay of monetary policy, inflation, and market expectations in shaping U.S. equity returns. Full article

This study examines links between global financial stress and cryptocurrency returns from 1 January 2017 to 31 January 2025, while explicitly accounting for commodity markets. We use an econometric toolkit: unit-root and cointegration testing, ARDL bounds, Toda–Yamamoto causality, and a two-state Markov Switching model to trace long-run equilibrium and transmission mechanisms across cryptocurrencies (BGCI), systemic stress (OFR-FSI), volatility measures (VIX, VVIX, VSTOXX, VVSTOXX, MOVE), major equities and bonds, and three commodities (gold, oil, copper). Results show robust long-run cointegration between BGCI and several financial variables, including S&P/ASX 200 and the Bloomberg Barclays Bond Index; models that include commodities continue to support these long-term links. Toda–Yamamoto tests reveal that stress and volatility indices unidirectionally transmit shocks to cryptocurrencies and commodities, while gold displays a bidirectional relationship with BGCI, indicating a conditional safe haven interaction. Markov Switching estimates show amplified co-movement among BGCI, gold and bonds in stress regimes, with the model predominantly remaining in a normal state. Overall, cryptocurrencies are embedded within the broader financial system; commodities, especially gold, are used to moderate the stress crypto transmission and offer conditional diversification value during turmoil. Full article

This study investigates the short- and long-run drivers of natural gas consumption in the European Union using an ARDL bounds testing approach. The analysis incorporates GDP per capita, liquid fuel use, and solid fuel use as explanatory variables. Augmented Dickey–Fuller tests confirm mixed integration orders, allowing valid ARDL estimation. The results reveal a statistically significant long-run relationship (cointegration) between gas consumption and the energy–economic system. In the short run, the use of liquid fuel exerts a strong positive influence on gas demand, while the effects of GDP materialise only after a two-year lag. Solid fuels show a delayed substitutive impact, reflecting the ongoing transition from coal. An error correction model confirms rapid convergence to equilibrium, with 77% of deviations corrected within one period. Recursive residual and CUSUM tests indicate structural stability over time. These findings highlight the responsiveness of EU gas demand to both economic and policy signals, offering valuable insights for energy modelling and strategic planning under the European Green Deal. Full article

In this study, the relationship between economic growth and carbon emissions for the period 1968–2022 in Turkey was evaluated within the framework of the EKC (Environmental Kuznets Curve) hypothesis. In addition, the impacts of renewable energy consumption and agricultural value added on carbon emissions were analyzed using the ARDL bounds testing approach. The validity of the results was also tested using the FMOLS and DOLS methods. The findings confirmed the existence of a cointegration relationship between carbon emissions and per capita income, renewable energy consumption, and agricultural value added. Long-term analyses indicate that renewable energy consumption reduces carbon emissions, whereas growth in agricultural value added leads to an increase in emissions. In addition, it has been determined that the EKC hypothesis is valid in both the long and short terms and that increases in per capita income raise emissions up to a certain threshold and have a mitigating effect when this threshold is exceeded. The results of the short-term analysis showed that the effects of renewable energy consumption vary across periods, and that agricultural value added increases emissions in the short term. This study provides empirical evidence for Turkey by incorporating sectoral variables within the EKC framework and offers meaningful insights for policymakers regarding the environmental impacts of agricultural value added and renewable energy use in the context of a developing country. Accordingly, fiscal policy instruments such as green taxation, carbon credit trading mechanisms, and financial and agricultural subsidies should be more effectively utilized in Turkey to support structural transformation in agriculture and promote the use of clean energy, in line with the findings that suggest the need for targeted agricultural and energy policies aligned with Turkey’s SDG commitments. Full article

The Australian agriculture sector currently relies on imported fertilizers, which poses risks to price stability and increases the potential for supply chain disruptions. This study aims to investigate the trends and factors affecting fertilizer consumption in Australia, considering the moderating effects of agricultural GDP and agri R&D expenditure. The econometric models, including ARDL bound tests, Granger causality tests, and FMOLS, were used to analyze quarterly data from 2000 to 2023. The findings confirm that a significant long-run relationship exists among the variables of crop production, agricultural export–import ratio, and agricultural R&D expenditure. The moderating effects of agricultural GDP and agricultural R&D expenditure on fertilizer consumption were also found to be significant. The Granger causality test results indicate that bidirectional causality exists between agricultural GDP and fertilizer consumption, arable land and fertilizer consumption, employment and fertilizer consumption, and the export–import ratio and fertilizer consumption. The findings from the robustness checks confirm that most of the variables are co-integrated with fertilizer consumption, except agri GDP and employment. Thus, policymakers are advised to prioritize investment in agricultural R&D to promote sustainable fertilizer consumption and enhance agricultural value addition in Australia. Full article

This study examines the relationship between banking sector development (credit and deposits) and economic growth in Ecuador, using quarterly data for the period 2000–2022. An ARDL approach with Bound Test cointegration is employed, incorporating structural breaks using the Bai–Perron test and controlling for macroeconomic shocks. In addition, time transformation methodologies are applied to harmonize the frequency of the series: the monthlyization of GDP is performed using the Chow-Lin method, and the imputation of missing unemployment data using the Kalman filter. The results reveal a significant long-run elasticity between bank deposits and GDP (0.45%), while credits do not present a statistically significant effect, possibly due to high delinquency and institutional weakness. Granger causality tests confirm a unidirectional relationship between banking variables to economic growth. These findings highlight the importance of strengthening financial supervision and improving institutional quality to enhance the effect of bank intermediation. The study provides robust and contextualized empirical evidence relevant to resource-dependent economies with concentrated financial systems, contributing to the debate on the relationship between finance and growth in developing countries. Full article