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    How does technological innovation affect the ecological footprint? Evidence from E-7 countries in the background of the SDGs
    (ELSEVIER SCI LTD, 125 London Wall, London EC2Y 5AS, ENGLAND, 2024) Dam, Mehmet Metin; Kaya, Funda; Bekun, Festus Victor
    Although technological innovation plays a critical role in promoting sustainable development and environmental sustainability, there are few studies in the existing literature that address this relationship. This study aimed to investigate the relationship between technological innovation (TI), renewable energy consumption (REC), natural resource rent (NRR) and ecological footprint (EF) of E-7 countries (i.e. Brazil, China, India, Indonesia, Mexico, Russia and Turkiye) from 1992 to 2018 in order to ensure environmental sustainability in the context of the Sustainable Development Goals (SDGs). Analysis was performed using the ARDL estimator, robustness test and Dumitrescu-Hurlin panel causality (DHC) test. Long-term empirical estimates from the PMG-ARDL technique have shown that a 1 % increase in TI and REC reduces EF by 0.064 % and 0.234 %, respectively, i.e. increases environmental sustainability. At this point, it is possible to say that TI and REC contribute to the achievement of SDG-7 and 13 in E-7 countries while NRR and real income (GDP) were found to impede the achievement of SDG7 and 13 in E-7 countries through an increase in EF. The results were confirmed using robustness techniques. In the DHC test results, while there is a unidirectional causality from TI to EF, from EF to NRR and trade openness, a bidirectional causality was found between GDP and EF. This study suggests that policymakers should focus on introducing environmentally friendly equipment to reduce environmental degradation, increase the share of RECs and focus on sustainable development within the framework of the SDGs.
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    The role of green growth and institutional quality on environmental sustainability: A comparison of CO 2 emissions, ecological footprint and inverted load capacity factor for OECD countries
    (Academic Press Ltd- Elsevier Science Ltd, 2024) Dam, Mehmet Metin; Durmaz, Ayse; Bekun, Festus Victor; Tiwari, Aviral Kumar
    Green growth is of great importance in terms of solving environmental problems and achieving sustainable development goals. However, the existing literature has not investigated how green growth affects environmental degradation and environmental sustainability variables. In light of this gap, this study aims to analyse the impact of green growth and institutional quality on CO 2 emissions, ecological footprint and inverse load capacity factor in OECD countries by constructing three different models. The results of the analysis indicate that (i) green growth exerts a significant mitigating and differentiating effect on CO 2 , ecological footprint and inverted load capacity factor in the long run. This is evidenced by a 1% increase in green growth reducing CO 2 , ecological footprint and inverted load capacity factor by 0.563%, 0.373% and 0.198%, respectively. (i) The impact of green growth on CO 2 and inverted load capacity factor in the long run is negative and statistically significant; (ii) the impact of green growth on CO 2 and inverted load capacity factor in the short run is negative and statistically significant; (iii) the impact of institutional quality on deterioration is positive and significant in the long run; (iv) the impact of population on deterioration and sustainability is significant and mixed. The findings indicate that decision-makers in OECD countries should review green energy policies when setting the sustainable development goals, as environmental sustainability is more challenging than reducing pollution.
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    The dynamic connectedness between oil price shocks and emerging market economies stock markets: Evidence from new approaches
    (ELSEVIER, RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS, 2025) Tiwari, Aviral Kumar; Dam, Mehmet Metin; Altıntaş, Halil; Bekun, Festus Victor
    This paper uses the dynamic connectedness framework to investigate the interrelationship between the decomposed oil supply, demand and risk shocks that Ready (2018) developed and the stock market returns of emerging market economies. For this purpose, we use daily data from 11 October 2001 to 5 April 2021. Novel empirical methodologies, including wavelet quantile correlation (WQC), cross-quantilogram analysis, nonparametric causality-in-quantile approaches, contemporaneous R2 connectedness approach and generalized R2 connectedness approaches, are employed. The results show that oil price fluctuations significantly impact the economic performance of emerging market economies, reflecting historical events. Demand price shocks are regarded as net transmitters within the system, whereas supply and risk price shocks are net receivers of spillovers. Concurrently, our findings indicate a considerable degree of dynamic connectedness among the stock markets of emerging market economies. In particular, the stock markets of Brazil, Mexico, and Argentina have been identified as net transmitters of spillovers. In contrast, the stock markets of Turkey, South Korea, Malaysia, Indonesia and India are classified as net receivers of spillovers. Furthermore, we examine and document the advantages of diversified portfolios that include all sector indices, including oil price shocks and emerging market economy stock markets, in terms of portfolio performance. The insights offered here are valuable for investors and policymakers striving to enhance their strategic approaches in today’s interconnected global financial context. The results show that oil price fluctuations significantly impact the economic performance of emerging market economies and reflect historical events. Demand shocks affecting the stock market indices of Brazil, Argentina and Mexico tend to act as net spillover transmitters. In contrast, supply shocks affecting the stock market indices of Indonesia, South Korea, India, Turkey and Malaysia mainly act as net spillover receivers. Net pairwise interconnectedness analysis reveals that, except for crisis periods, interactions between financial markets or macroeconomic indicators are evenly distributed. Thus, systemic risk is lower, and markets act independently. Empirical findings obtained using WQC generally show the presence of negative correlations at long-time scales and low quantiles, which is considered an indicator of the safe-haven feature associated with the asset in question. The hedge feature is observed to be evident only at long time scales. The results of the crossquantilogram analysis show mixed evidence of correlation in all stock indices, especially in the weekly lag structure, compared to daily and monthly lags. Finally, non-parametric Granger causality test results show that stock returns are insensitive to oil price fluctuations, making these markets attractive for investors seeking diversification strategies. These findings provide valuable recommendations for investors seeking sustainable equities in a volatile oil market.