Solar energy has become well-documented and famous globally despite high upfront costs and a lack of financing mechanisms. Solar power can keep sustainable economic growth by fulfilling the increasing worldwide demand for energy while addressing climate change and reducing emissions. On the other side, Foreign Direct Investment is a crucial source of promoting energy-efficient technology across the world. This study explores the role of solar energy consumption and the impact of Foreign Direct Investment inflows for clean environment in the top ten consuming solar energy countries for the period 1990 to 2016. The significance of this study is that it uses cubic form of income and FDI to account technique, scale and cumulative effects on CO2 emissions. The results depict N-shaped EKC between income and CO2 emissions. The Foreign Direct Investment inflows play positive role to boost the environment quality. Due to strong structure of institutions FDI inflows can be a source of solar technology promotion. However, other aspects of economy like GDP-scale that linked to the environment can’t be ignored. Thus for clean environment countries still need to implement more efficient policies for “sustainable development”
This study explores the relationship between banking efficiency and financial development in the Belt and Road Initiative (BRI) economies from 2007 to 2018. The study employs three dimensions to assess financial development: (i) depth, (ii) stability, and (iii) efficiency. In the initial stage, BRI banking efficiency is quantified using Data Envelopment Analysis (DEA). Subsequently, the Generalized Method of Moments technique is applied to identify the connection between banking efficiency and financial development. The study employs fundamental structural benchmarks to evaluate disparities between actual financial development indicators and predicted values. Banking efficiency plays a crucial role in determining the depth, stability, and efficiency of financial development within BRI economies and is pivotal in closing these gaps. Strong institutional frameworks also support the advancement of the BRI’s financial development sector. Moreover, foreign direct investment positively impacts reducing financial development gaps and promoting growth in the financial sector. The study concludes that BRI member countries should prioritize banking industry reforms to enhance the stability, depth, and efficiency of their financial sectors.
The objective of this study is to examine the impact of climate change on forestry efficiency (FRE) and total factor productivity change (TFPC) in 31 provinces of China for a study period of 2001–2020. Additionally, the study aims to evaluate the success level of governmental initiatives used to mitigate climate change. Using the DEA-SBM, this study estimates the forestry efficiency for 31 Chinese provinces and seven regions. Results indicate that the average forestry efficiency score obtained is 0.7155. After considering climatic factors, the efficiency level is 0.5412. East China demonstrates the highest average efficiency with a value of 0.9247, while the lowest score of 0.2473 is observed in Northwest China. Heilongjiang, Anhui, Yunnan, and Tibet exhibit the highest efficiency scores. Mongolia, Heilongjiang, Sichuan, Hebei, and Hunan are the five provinces most affected by climate change. This study’s findings indicate that the average total factor forestry productivity (TFPC) is 1.0480, representing an increase of 4.80%. The primary determinant for change is technology change (TC), which surpasses efficiency change (EC). Including climate variables reduces total factor productivity change (TFPC) to 1.0205, mainly driven by a decrease in TC. The region of South China exhibits the highest total factor productivity change (TFPC) with a value of 1.087, whereas both Northeast China and Central China observe falls below 1 in TFPC. The Mann–Whitney U test provides evidence of statistically significant disparities in forestry efficiency and TFPC scores when estimated with and without incorporating climate factors. Kruskal–Wallis found a statistically significant difference in FRE and TFPC among seven regions.
Trade agreements are thought to raise trade integration, but existing preferential trade agreements (PTAs) are insufficient in measuring market access of products. This study develops a product-based coverage index of PTAs using the World Trade Organization (WTO) preferential trade agreements and calculates bilateral trade measures using the EORA multi-regional input-output (MRIO) tables covering 189 countries worldwide over the period 1990–2015; the structural gravity model is employed to test how PTAs affect bilateral trade. Our findings show that countries sharing a common PTA could boost the trade volume compared to those without PTAs, supporting the trade creation effect. However, the trade promotion effect of the product-based coverage index of PTAs is significant only if the member countries are low-and middle-income countries. Further, the wide range of product liberalization brought by PTAs can promote global production networks by stimulating the trade of intermediate goods. Our results are important for understanding the market access effect of PTAs with the increasing development of trade integration and global value chains (GVCs).
The challenge of achieving sustainable economic development with a secure environmental system is a global challenge faced by both developed and developing countries. Energy Efficiency (EE) is crucial in achieving sustainable economic growth while reducing ecological impacts. This research utilizes the Slack-Based Measure Data Envelopment Analysis (SBM-DEA) and the Malmquist-Luenberger Index (MLI) method to evaluate EE and productivity changes from 1995 to 2020 across G20 countries. The study uses four different input–output bundles to gauge the impact of renewable and non-renewable energy consumption and carbon emissions on EE and productivity changes. The study results show that including renewable energy consumption improves the average EE from 0.783 to 0.8578, but energy productivity declines from 1.0064 to 0.9988. Incorporating bad output (carbon emissions) in the estimation process enhances renewable EE and productivity change, resulting in an average EE of 0.6678 and MLI of 1.0044. Technological change is identified as the primary determinant of energy productivity growth in scenarios 1 and 2, while technical efficiency determines energy productivity change in scenarios 3 and 4. The Kruskal-Wallis test reveals a significant statistical difference between the mean EE and MLI scores of G20 countries.
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