Sürdürülebilir Kalkınma Amaçları
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- MakaleAçık Erişim2025Analyzing the impact of economic growth and FDI on sustainable development goals in China: insights from ecological footprints and load capacity factors
Güler, Ilkay; Naimoglu, Mustafa; Simsek, Orhan; Adali, Zafer; Özbek, Sefa
This study investigates the impact of economic growth and foreign direct investment (FDI) on China's sustainable development goals (SDGs), specifically Zero Hunger (SDG 2), Life Below Water (SDG 14), and Life on Land (SDG 15). It examines ecological footprints and load capacity factors (LCFs) in cropland, fishing, forest, and grazing land using Fourier bootstrap autoregressive distributed lag (ARDL) cointegration analysis and fully modified ordinary least squares (FMOLS) estimators. The study covers the period from 1979 to 2022. Key findings reveal that while GDP and FDI often exacerbate environmental degradation, urbanization and value-added agriculture, forestry, and fishing (FAFGDP) improve sustainability in some areas. The study confirms the pollution haven hypothesis for most models, suggesting that China's legal and regulatory frameworks may inadequately mitigate FDI's adverse environmental effects. The Environmental Kuznets Curve (EKC) hypothesis is not supported as GDP growth generally increases ecological footprints. However, trade openness and urbanization show positive influences on environmental sustainability. Policy recommendations include enhancing energy efficiency, promoting renewable energy, implementing green technologies in agriculture and urban development, and revising FDI policies to incentivize environmentally friendly practices. These strategies are crucial for achieving China's sustainable development goals and mitigating the pressures of human activities on natural resources.
- MakaleYalnız künye2025Ecological footprint components and agricultural productivity: Insights from MENA countries
Recepoğlu, Mürşit; Hayaloğlu, Pınar; Cakir, Sümeyra Cay; Artan, Seyfettin; Cakir, Mehmet Ali
The surge in the global population over the past century has highlighted the importance of agricultural production, leading to many studies to boost productivity. Unlike previous studies that primarily explore agricultural productivity growth, this study investigates how the subcomponents of the ecological footprint affect agricultural productivity in MENA countries between 1992 and 2021, identifying which types of environmental pollution have the most significant impact. Driscoll and Kraay (1998) method results show that ecological footprint has a major negative impact on agricultural productivity. Similarly, all ecological footprint components have a negative impact on agricultural productivity. The forest footprint has the highest coefficient magnitude, followed by crop land footprint, carbon footprint, fishing grounds footprint and grazing land footprint. The results have been tested for robustness using the Half-Panel Jackknife test to avoid biased results, and parallel results have been obtained. Finally, the causality between agricultural productivity and explanatory variables has been tested using Dumitrescu and Hurlin (2012) panel causality test. The findings suggest that policymakers may find it more effective to eliminate pollution rather than using additional resources to increase agricultural productivity. This approach allows for the reallocation of resources used in agricultural production to other areas.
- MakaleAçık Erişim2025Future of Clean Cooking Energy Access in Emerging Economies by 2030
Cakir, Mehmet Ali; Unlu, Ramazan; Cakir, Sümeyra Cay; Xanthopoulos, Petros
This study assesses the future of clean energy and technology access for cooking in emerging economic blocs—BRICS, MINT, ASEAN, and MENA—through 2030. Cooking contributes 3% of global greenhouse gas emissions, with over half of household emissions coming from cooking. Therefore, clean cooking energy is critical for sustainability and human health. The study aims to evaluate the likelihood of achieving the UN Sustainable Development Goal of universal clean cooking energy access by 2030 and the 2050 net-zero emissions target. Machine learning techniques, such as support vector regression, gradient boosting, and linear regression, alongside an ensemble approach, provide forecasts for these regions. The findings show a varied outlook. Within ASEAN, two countries are expected to reach 100% clean energy access for cooking by 2030, while two are likely to experience a decline. The MENA region shows stronger progress, with eight countries expected to meet the 2030 target. Among BRICS countries, only India is projected to reach full accessibility, while Russia faces a decline. The MINT countries face challenges, with none expected to meet the target, and Nigeria is projected to experience a decrease in clean energy access. The study concludes that the current trajectory makes achieving the 2030 Sustainable Development Goals and the 2050 net-zero emissions target unlikely for these regions. Policymakers must reassess their strategies and learn from successful countries to improve outcomes.