Search Results (96)

This paper explores the central role of monetary governance, i.e., high politics and low politics, in protecting a currency’s exchange rate and reducing its volatility during periods of global crisis. Using annual panel data from 15 developed and emerging economies between 2001 and 2023, and applying a panel ARDL approach, the study assesses the effectiveness of high politics—captured through governance indicators—and low politics—captured through economic indicators—as a shield against external shocks, such as the 2008 financial crisis, the COVID-19 pandemic, and the Russo–Ukrainian conflict. The findings demonstrate that strong monetary governance significantly strengthens the Real Effective Exchange Rate (REER) and dampens its volatility in the long-term. In contrast, macroeconomic variables such as inflation, public spending, and trade openness exert destabilizing effects. The results highlight the strategic importance of governance as a long-term anchor of exchange rate resilience, suggesting that countries with robust institutional frameworks are better equipped to withstand global disruptions. These insights offer crucial policy implications for reinforcing monetary governance, especially in emerging economies vulnerable to financial and geopolitical turbulence. Full article

This study examines the impact of personal remittances on housing prices in European Union (EU) countries, while also accounting for a broader set of macroeconomic, demographic, and structural variables. Using annual data for 27 EU countries from 2007 to 2022, we employ a comprehensive panel econometric approach, including cross-sectional dependence tests, second-generation unit root tests, pooled mean group–autoregressive distributed lag (PMG-ARDL) estimation, and panel causality tests, to capture both short- and long-term dynamics. Our findings confirm that remittances significantly and positively influence long-term housing price levels, underscoring their relevance as a demand-side driver. Other key variables such as net migration, GDP, travel credit to GDP, economic freedom, and real effective exchange rates also contribute to housing price movements, while supply-side indicators, including production in construction and building permits, exert moderating effects. Moreover, real interest rates are shown to have a significant long-term negative effect on property prices. The analysis reveals key causal links from remittances, FDI, and net migration to housing prices, highlighting their structural and predictive roles. Bidirectional causality between economic freedom, housing output, and prices indicates reinforcing feedback effects. These findings position remittances as both a development tool and a key indicator of real estate dynamics. The study highlights complex interactions between international financial flows, demographic pressures, and domestic economic conditions and the need for policymakers to consider remittances and migrant investments in real estate strategies. These findings offer important implications for policymakers seeking to balance housing affordability, investment, and economic resilience in the EU context and key insights into the complexity of economic factors and real estate prices. Importantly, the analysis identifies several causal relationships, notably from remittances, FDI, and net migration toward housing prices, underscoring their predictive and structural importance. Bidirectional causality between economic freedom and house prices, as well as between housing output and pricing, reflects feedback mechanisms that further reinforce market dynamics. These results position remittances not only as a developmental instrument but also as a key signal for real estate market performance in recipient economies. Full article

This study aims to evaluate how key financial, educational, technological, and institutional drivers shape resource efficiency (RCE), a critical pillar of sustainable development—across major economies. Enhancing RCE is vital for ensuring long-term ecological and economic stability while meeting global sustainability targets. Using panel data from 2000 to 2022 for G20 countries, this research examines the dynamic effects of natural resources (NRSs), educational quality (EDQ), financial inclusion (FIN), green innovation (GRI), and economic complexity (ECC) on RCE. The Cross-Sectional Autoregressive Distributed Lag (CS-ARDL) model is applied to capture both short- and long-term relationships and is validated by robustness checks using the Augmented Mean Group (AMG) and Common Correlated Effects Mean Group (CCEMG) estimators. The results show that EDQ and FIN exert a negative influence on RCE, suggesting that governance inefficiencies occur when aligning education systems and financial mechanisms with sustainability goals. In contrast, NRS, GRI, and ECC significantly enhance RCE, underscoring the value of resource stewardship, innovation-driven transitions, and complex economic structures in promoting efficiency. These findings have governance implications, emphasizing the need for institutional reforms that integrate sustainability into the education and financial sectors while supporting green innovation and economic diversification. Policymakers in G20 economies are urged to implement coherent strategies that redirect educational and financial frameworks toward inclusive, resilient, and resource-efficient development pathways, thereby advancing the United Nations Sustainable Development Goals (SDGs). Full article

This study investigates the interactive link between bank performance and financial innovation in Tunisian banking using a mixed-methods research framework that combines econometric approaches and institutional factors. The empirical analysis uses a panel data of 11 commercial banks from the period of 2000–2024 and employs an Autoregressive distributed lag (ARDL) model to estimate short- and long-run impacts of innovation on return on equity (ROE). A composite indicator of Fintech investment, digital service adoption, and innovation productivity characterizes financial innovation. Governance factors like the presence of risk management departments and executive compensation are taken into account. The results reveal a robust positive impact of financial innovation on bank performance in the long run, especially in more concentrated market settings. Risk management supports performance, while inefficient executive compensation is negatively associated with profitability. These findings are confirmed by robustness tests with HAC standard errors. This research contributes to the literature by situating financial innovation in the context of an emerging North African market and produces practitioner-relevant information for policymakers and bank executives interested in ensuring that performance results are consistent with innovation strategy. Full article

Saudi Arabia implements a wide range of non-tariff measures on imports and exports. Different research articles have quantified the effect of non-tariff measures on trade, but their effect on Saudi Arabia has not been quantified. The major objective of this paper is to quantify the effect of non-tariff measures on the imports of Saudi Arabia. Panel data from 2000 to 2022 for four major regions trading with Saudi Arabia are used to estimate the panel ARDL gravity model. The results of the bound test confirm the presence of a long-run association between the model variables. In the long-run, the per capita income of Saudi Arabia is the main determinant of imports. In contrast, in the short-run the per capita income has no influence, and the non-tariff measures have a negative effect on import value. At the cross-sectional level, the results confirm the negative effect of non-tariff measures on the selected trade partners with varying degrees. The results ascertain the detrimental effect of the application of technical and non-technical measures on Saudi Arabia’s imports. We recommend policymakers in Saudi Arabia adopt a more transparent policy of NTMs application that leads to a sustainable supply of goods and services and ensures sustainable trade. Full article

This study examines the effects of artificial intelligence investments, green financing, government stability, and institutional quality on renewable energy consumption from a multidimensional perspective. Using panel data for the period 2014–2023, 15 leading countries in the field of green financing were included in the analysis. The Cross-Sectionally Augmented Autoregressive Distributed Lag (CS-ARDL) method was preferred in the empirical analysis; robustness tests were conducted with Fully Modified OLS (FMOLS) and Dynamic OLS (DOLS) estimators to assess the reliability of the findings. According to the findings, artificial intelligence investments have a significant and positive impact on renewable energy consumption in both the short and long term. Similarly, green financing contributes strongly and statistically significantly by enhancing the feasibility of clean energy projects. Furthermore, stable governments and the effective functioning of institutional structures support this process; both factors are observed to have a positive effect on renewable energy consumption. This study offers concrete policy recommendations in line with the United Nations sustainable development goals (SDGs) 7, 9, 13, and 16. Full article

The transition to sustainable, innovation-driven economies has become a global imperative, particularly for resource-dependent regions like the Middle East, where environmental challenges, fossil fuel reliance, and economic diversification pressures intersect. In this context, green innovation plays a pivotal role in mitigating environmental degradation while supporting long-term economic growth. This study examines the short-term and long-term drivers of green innovation across 13 Middle Eastern countries from 1990 to 2023, with a focus on environmental governance, environmental pollution, economic growth, and natural resource abundance. Using a balanced panel dataset, this study applies Frees, Friedman, and Pesaran CSD tests to address cross-sectional dependency and second-generation unit root tests for data stationarity. Both first- and second-generation cointegration tests confirm long-run relationships among variables. The empirical analysis employs the cross-sectional autoregressive distributed lag (CS-ARDL) model, alongside Pooled Mean Group (PMG-ARDL), Average Mean Group (AMG), and Common Correlated Effects CCEMG estimators, ensuring robustness. The findings indicate that, in the long term, environmental governance, economic growth, population size, and natural resource abundance significantly promote green innovation, with respective coefficients of 0.3, 0.01, 0.02, and 0.4. Conversely, human development and environmental pollution exert a negative influence on green innovation, particularly over the long term. These results suggest that, while economic and governance factors drive innovation, human capital development may prioritize immediate growth over sustainability, and pollution may hinder long-term innovation. Enhancing environmental governance, accelerating renewables, using strategic resource revenue for green projects, integrating green growth, and regional collaboration can position Middle Eastern economies as green innovation leaders. Full article

Saudi Arabia’s Vision 2030 is closely tied to CO₂ emissions and energy consumption issues. This initiative aims to modernize the country’s economy, diversify its energy sources, and enhance sustainability. This paper examines the relationships among CO₂ emissions, Renewable Energy Consumption (REC), and Non-Renewable Energy Consumption (NREC) in Saudi Arabia, from 1990 to 2019. To assess the stationarity of the panel time-series data, the Augmented Dickey–Fuller (ADF) and Phillips–Perron (PP) tests were initially used. Given that the data exhibited a mixed order of integration, the Autoregressive Distributed Lag (ARDL) framework was employed. Three different lag selection criteria were applied for cointegration, using CO₂ emissions as the dependent variable. Additionally, the direction and significance of causality were analyzed within the ARDL framework. Robust tests were conducted to evaluate the generalizability of the study’s findings. We demonstrated a significant long-term relationship between climate change and both REC and NREC in Saudi Arabia. The findings indicate that in the long run, a 1% increase in REC leads to a 0.21% decrease in CO₂ emissions. Furthermore, a 1% increase in NREC corresponds to a substantial 53.4% reduction in CO₂ emissions. Finally, policy recommendations were proposed in alignment with Saudi Arabia’s Vision 2030. Full article

In recent years, the importance of developing the tourism sector and diversifying income sources has grown in the Gulf Cooperation Council (GCC) countries. This paper estimates the impact of tourism industry development on income equality in the GCC region from the first quarter of 2014 to the fourth quarter of 2023. Furthermore, this paper evaluates the existence of the Kuznets curve and its implications for income distribution. To achieve these objectives, this study employs panel cointegration tests and the cross-sectionally augmented autoregressive distributed lag (CS-ARDL) model. The dataset combines quarterly data from the World Bank and national statistical agencies, including indicators such as tourism revenue, international arrivals, government effectiveness, and education expenditure (used as a proxy for income equality). The results indicate that tourism revenue (TOU) has a significant and positive long-run effect on income equality (0.14%). In the short run, the squared term of tourism revenue (TOU2) becomes significant and positive (0.01%), but the findings do not support the Kuznets curve hypothesis. Furthermore, the number of international travelers (TRAV) has a negative and significant effect in the long run, while government effectiveness (GE) is negative and significant in both the long and short run. A key limitation of the study lies in the use of education expenditure as a proxy for income equality, due to the unavailability of consistent inequality metrics across the GCC countries. Full article

Using a panel Autoregressive Distributed Lag (ARDL) model, this study examines the effects of the adoption of Application Programming Interfaces (APIs) on the digital economy of Saudi Arabia, using monthly data from 2015 to 2024 from the World Development Indicators and Bloomberg. The results show that API Adoption Rate (APIAR) has a positive long-term influence on the Digital Economy Index (DEI), highlighting APIs as a transformative tool that foster innovation, increase scalability within enterprises, and enhance digital transactions in line with SDG 9: Industry, Innovation, and Infrastructure. The findings also indicate that the Number of Active APIs (NAAPIs) exerts a significant and positive effect on DEI in both short- and long-term, which aligns with SDG 8: Decent Work and Economic Growth by fostering accelerated digital transformation and new innovation-driven job opportunities in addition to entrepreneurship via API-driven platforms. API Investment (APII) exhibits a beneficial short-term effect on DEI; nevertheless, it is not significant in the long run, indicating the need for strategic and continuous investment. This finding resonates with SDG 17: Partnerships for the Goals, highlighting the significant role of public–private collaboration in enhancing digital infrastructure and enabling AI solutions. Building on these results, there is an urgent need to improve consistent API ecosystems, enhance collaborative partnerships, and align API strategies to national aspirations for driving Saudi Arabia’s digital economic growth and supporting Vision 2030 and the UN’s SDGs. Full article

Achieving environmental sustainability in the G20 requires aligning economic growth with effective policy interventions. This study examines the role of financial technology (FNT), environmental legislation (ENL), and institutional quality (INQ) in reducing the ecological footprint (EF), while also assessing the adverse impacts of natural resource extractions (NRS) and economic expansion. Using CS-ARDL on panel data from 2000 to 2022, the study confirms cross-sectional interdependence and long-term cointegration through CIPS, CADF, and Westerlund tests. The findings reveal that FNT, ENL, and INQ significantly mitigate EF, whereas NRS and economic growth exacerbate it. Robustness is validated through the AMG and CCEMG methods, with ANN models reinforcing the results. The Dumitrescu–Hurlin test establishes a bidirectional link between NRS, economic growth, and EF, while FNT, ENL, and INQ exert a unidirectional influence on sustainability. These insights underscore the need for stronger regulatory frameworks, green fintech integration, and governance reforms to drive sustainable economic transitions in G20 economies. Full article

This study explores the dynamic relationship between economic growth, technological innovation, and $C{O}_2$ emissions in BRICS nations, integrating the Environmental Kuznets Curve (EKC) and Innovation Claudia Curve (ICC) frameworks. Using a panel ARDL approach on data from 1991 to 2023, we investigate the long-run and short-run interactions between GDP, renewable energy consumption (RENC), foreign direct investment (FDI), urbanization (URB), and patent applications (PAs) in shaping environmental outcomes. The findings confirm the EKC hypothesis, revealing an N-shaped relationship between GDP and emissions, indicating that while economic growth initially leads to higher $C{O}_2$ emissions, this trend reverses at a critical threshold before a secondary increase occurs at higher income levels. The ICC framework identifies a cubic relationship between innovation and emissions, where technological advancements initially drive higher emissions before contributing to sustainability at later stages, though an excessive scale of innovation may reintroduce environmental pressures. RENC is found to significantly mitigate emissions, while URB and FDI display dual and context-dependent effects, highlighting the multidimensionality of sustainable transitions in emerging economies. These results underscore the importance of targeted policy interventions, such as scaling renewable energy infrastructure, promoting green innovation, guiding urban expansion, and aligning FDI with environmental objectives. Full article

The role of carbon emissions in the worsening of global warming and other climate change implications has been well recognised. This study empirically investigates the effect of economic growth, urbanisation, and energy consumption on carbon emissions using panel cointegration tests and pooled mean group autoregressive distributed lag (PMG-ARDL) techniques. The research is based on panel data from Western Balkan countries spanning 2001 to 2022. Urbanisation is incorporated into the model to determine its significance in the dynamic relationship among economic growth, energy consumption, and carbon emissions. The inclusion of urbanisation in the Western Balkans context is particularly novel because of its acceleration in this region. The findings suggest that energy consumption, economic growth, and urbanisation significantly affect environmental quality in the long run. In contrast, it has been demonstrated that only economic growth significantly impacts the environment in the short run. Subsequent investigations have revealed that environmental distortion is a long-term consequence of energy consumption, urbanisation, and economic expansion in the examined nations. These countries must prioritise enhancing energy efficiency, urban planning, and pollution mitigation measures while ensuring that economic growth remains unhindered. Full article

Environmental degradation poses a significant global challenge which necessitates innovative strategies to achieve sustainability. This study investigates the impact of technological innovation (TCN), higher education (EDU), green finance (GRF), globalization (GLI), and entrepreneurship (ENT) on environmental quality (EQ) in G20 countries. The study uses panel data from 2000 to 2020 to investigate relationships between study variables. Among the various diagnostic tests conducted, the Variance Inflation Factor (VIF) confirms that multicollinearity is not present. Furthermore, the cross-sectional dependence (CSD) test identifies cross-sectional interdependence among the study variables. Moreover, the slope homogeneity (SL) test indicates heterogeneity in the data. For the stationarity check, the Cross-Sectional Augmented Im–Pesaran–Shin (CIPS) test indicates mixed results. Finally, the study uses the Cross-Sectionally Augmented Autoregressive Distributed Lag (CS-ARDL) and the Generalized Method of Moments (GMM) for the long- and short-run analysis of variables. The outcomes of CS-ARDL indicate that GLI has a significant negative impact on EQ, hence causing deterioration in G20 economies. On the other hand, TCN, EDU, GRF, and ENT show positive and significant impacts on EQ, therefore enhancing environmental outcomes. Additionally, the Dumitrescu–Hurlin causality test reveals bidirectional causality, which highlights the interconnected relationship between TCN and ENT with EQ. However, GRF, EDU, and GLI demonstrate unidirectional causality with EQ. The takeaway of the study focuses on the importance of policies in promoting green innovation, resource efficiency, and sustainable practices to advance environmental quality within G20 economies. Full article

This study expands the tourism development literature by examining how currency valuation and financial sector maturity influence the tourism–growth relationship. While prior research emphasizes direct or bidirectional causality, this study distinguishes itself by exploring the mediating and moderating roles of financial development and exchange rate stability. Using an instrumental variables approach and empirical data from Africa, we find that exchange rates and financial development partially mediate tourism’s effect on economic growth, particularly in economies with weaker currencies and more developed financial systems. Our results challenge the tourism–growth neutrality hypothesis by demonstrating that exchange rates not only influence tourism demand but also actively shape its growth effects. A panel ARDL analysis confirms bidirectional causality, which reinforces the interdependence between tourism and growth. However, unlike previous studies that view tourism as an isolated driver of growth, we demonstrate that its economic impact depends on a country’s financial maturity and exchange rate competitiveness. Policy recommendations aimed at enhancing economic growth through improved tourism and financial infrastructure are offered. Full article