Resources Policy最新文献

Governments in Asian economies are under immense pressure from an ecological perspective and are trying to increase compliance with environmental policies by institutions and households, which have the objective of reducing environmental pollution. This is because the Asian region contributes two-thirds of the global growth. However, because of the conventional manufacturing facilities and infrastructure, the Asian region had to rely on the consumption of the Natural Resource (NTR) for their economic development; thus,the environment is being harshly affected, eventually affecting the quality of life of every dweller. Therefore, this research revisits the Asian economies due to their global significance in financial, environmental and sustainable development. Moreover, the present study evaluates the role of Fintech (FNT), Green Finance (GFN) and Natural Resource (NTR), in diluting the disparity betweeneconomic and ecological sustainability. The current study explores these relationships through the help of an advanced and recent estimation technique named “Cross-section augmented autoregressive distributed lags (CS-ARDL)”. Through the generated outcome from CS-ARDL, FNT, NTR, and GFN are found to support the Economic Growth (ECG). From the environmental perspective, the role of FNT and GFN was found to be satisfying as they lead to reduced environmental pollution. However, the role of NTR was found to destroy ecological health, which is the validation of the earlier studies but does require careful attention from the concerned authorities. In light of these findings, the Asian governments will be in a better position to identify, devise and select appropriate strategies and policies that will assist in alleviating environmental pollution and strengthening economic development.

With the increasing attention to environmental degradation and sustainable development goals, the low-carbon energy transition has emerged as a focal point in both academic and political realms. This research examines, under the framework of the Environmental Kuznets Curve, the impact of low-carbon energy transition, natural resource rents, and economic growth on environmental performance. Additionally, it delves into the regulatory role of green finance and transition finance in the nexus between low-carbon energy transition and environmental performance. The research findings reveal that the influence of low-carbon energy transition, economic growth, and natural resource rents on environmental performance exhibits distinct regional heterogeneity. The research also verifies the premise that the Environmental Kuznets Curve exists exclusively in the eastern area of China. Further investigation indicates that sustainable finance plays a crucial regulatory role in the relationship between low-carbon energy transition and environmental performance. According to these results, the paper suggests that provinces should establish dual environmental and economic goals and optimize financial policy design. Moreover, governments and enterprises should achieve sustainable development goals through means such as technological innovation, regulatory frameworks, and market mechanisms.

This study assesses how resource rent affects sustainable common prosperity in Asian regions from 2000 to 2019. Results indicate that a 1% increase in resource rent correlates with a decrease in sustainable common prosperity by 0.15% in Eastern Asia, 0.26% in Western Asia, and 0.465% in Central Asia, highlighting the complexities of managing resource revenues. Negative coefficients for state healthcare expenditure across all regions underscore challenges in healthcare effectiveness. Unemployment adversely impacts sustainable prosperity due to income loss and strains on public resources. Economic growth positively impacts Eastern Asia but negatively affects Western and Central Asia due to resource dependency and governance issues. Good governance promotes social cohesion and equitable development. To promote sustainable common prosperity, policies should focus on transparent resource management, fostering green growth, and engaging the private sector in sustainable job creation through partnerships and skills development.

This study investigates the potential of corporate digitalization to drive advancements in green technology, emphasizing the mediating role of mineral resource endowments. The research addresses the urgent need for sustainable development amid growing environmental challenges and highlights the critical role of corporate digitalization in fostering green technology innovations. The objectives are to analyze the impact of digitalization on green technology advancements among 2341 Chinese A-listed firms from 2010 to 2022 and to explore how mineral resource endowments influence this relationship. Our findings reveal that firms with higher levels of digitalization significantly improve their adoption and innovation of green technology. Additionally, mineral resource endowments amplify the positive effects of digitalization on green tech advancements, serving as a vital mediating factor. The results indicate that firms in regions with abundant mineral resources are better positioned to utilize digital technologies for green innovations. Furthermore, our analysis shows that digitalization promotes greater collaboration and knowledge sharing, accelerating green technology development. The policy implications suggest that encouraging corporate digitalization and optimizing the use of mineral resources can significantly advance sustainable development goals. This underscores the need for integrated policies that support both digital and green transformations.

The objective of this study is to evaluate the effectiveness of Sustainable Management Practices (SMPs) in achieving Carbon Neutrality (CN) within the natural resource extraction sector, specifically in the context of the Ukraine-Russia war. The study also aims to investigate the moderating role of Policy Robustness (PR) in enhancing the impact of SMPs on CN. Data were collected from 702 employees across 234 firms in the steel, iron-ore, and aluminum sectors, from China and India. We employed SEM based methodology, combining confirmatory factor analysis and regression methodologies within Ordinary Least Squares framework to analyze the framework of the study. Key findings reveal that SMPs have a significant positive impact on CN in both India and China. Moreover, the robustness of policies plays a crucial role in reinforcing the effectiveness of SMPs in achieving CN. Interestingly, while the interaction between SMPs and PR significantly impacts CN in China, it is not as prominent in India. Additionally, the study finds that factors such as firm age and employee experience do not significantly influence CN, contrary to conventional expectations. One major contribution of this study is the identification of the synergetic effect of combining SMPs with robust policies (PR) to enhance CN, particularly in the face of geopolitical challenges like the Ukraine-Russia war.

The study utilizes external factors to improve the precision of predicting fluctuations in oil prices. Based on the pertinent research, the present research gathers 62 external factors from 2000 to 2021, that indicate the changes in oil need, oil supplies, oil stock, economic basics, monetary metrics, and estimations of unpredictability. The experimental findings suggest that shrinkage techniques provide better predictions for all times, the research indicates that principle component analysis (PCA) regression precisely forecasts oil price variations one month in advance. Shrinkage approaches, in contrast, surpass comparable methods when it comes to prediction for all type timeframes. Moreover, an uncontrolled learning technique known as Principal Component Analysis (PCA) demonstrates better predictive ability when oil prices are falling, while supervised learning methods such as shrinkage methods notably enhance the precision of variability estimation. These results suggest that using sophisticated regression methods will significantly improve the accuracy of oil price projections, hence supporting improved decision-making for legislators and traders.

The iron and steel (IS) industry is one of the main positions for achieving the "dual-carbon" goal, so it is significant to clarify the decoupling status (DS) of CO₂ emissions and economic growth (EG) in the IS industry and the main factors affecting the DS. This paper adopted the Tapio decoupling and the catching-up decoupling to analyze the decoupling of CO₂ emissions and EG in the IS industry in China during 2011–2021. Then, the ordered Logistic regression model was used to explore the key factors affecting the DS. The results showed: (1) CO₂ emissions and EG both showed obvious trends of rising, falling, and then rising; (2) the Tapio DS of CO₂ emissions and EG in each province continued to get better, but the catching-up DS had poorly improved; (3) R&D investment (RD), urbanization level (URB), energy consumption intensity (EI), endowment structure (ES) and environmental regulation (ER) had a significant effect on the Tapio DS, and RD and ER had a significant effect on the catching-up DS. Accordingly, the suggestions were proposed to promote the IS industry to realize the optimal decoupling of CO₂ emissions and EG.

Natural resources prices have been greatly affected by the Russian-Ukrainian war. Investors also pay special attention to the price of natural gas and oil. This paper introduces the Thermal optimal path (TOP) method and the Long Short-Term Memory (LSTM) model to investigate the dynamic lead-lag relationship between investor attention and natural resources prices for crude oil and natural gas.

We find that during the war, the ability of investor attention to lead the prices of crude oil and natural gas become significantly stronger. Adding investor attention to the model significantly improves price prediction in the full sample. In addition, after the sample period is segmented according to the TOP method, the forecasting performance is greatly improved compared to the full sample. These findings indicate that traders and companies can incorporate investor attention into price predictions to further improve their trading strategies.

The “resource curse” paradoxically impacts countries abundant in natural resources, presenting challenges despite their apparent benefits. In 20 such economies, the focus has shifted to using sustainability measures to address this curse, analyzed through Cross-Sectional Fully Modified Ordinary Least Squares. Between 1999 and 2018, sustainable education proved essential in mitigating resource curse vulnerabilities. For instance, a 1% rise in primary school enrollment correlates with a 0.16 decrease in the Resource Curse Vulnerability Index, aiding economic diversification. Similarly, a 1% increase in state education investment leads to a 0.54% reduction in the index, improving human capital and governance. However, higher inflation exacerbates vulnerability, while trade liberalization reduces dependence on resources. Increased electricity consumption and internet access may intensify risks. Effective policies should focus on increasing education investment, supporting Education for Sustainable Development, enhancing media advocacy, promoting renewable energy, and advancing sustainable digital transformation.

The advancement of eco-friendly mining is a crucial pathway for reforming and progressing China's mineral resource management system in the modern era. This approach serves as an essential response to the mining sector's distinctive resource landscape and developmental stage, aimed at promoting ecological civilization and implementing the revised orientation of land resource governance. FinTech emerges as a novel mechanism that facilitates the integration and efficient allocation of financial resources, thus catalyzing the eco-friendly transformation of mining enterprises. This study explores the effects and underlying mechanisms of FinTech on the eco-friendly transformation of mining enterprises by examining mineral enterprises listed on China's A-share market from 2013 to 2021. The analysis demonstrates that FinTech positively influences the eco-friendly transformation of these enterprises, a finding supported by rigorous robustness tests that include changes in estimation methods, substitution of explanatory variables, variations in sample size, and addressing endogeneity concerns. Moreover, a heterogeneity analysis, which examines enterprises' nature, size, and regional private finance levels, reveals that FinTech primarily enhances the eco-friendly transformation of private enterprises, with less substantial impacts on state-owned enterprises. Notably, the effectiveness of FinTech in promoting eco-friendly transformation is particularly significant in smaller mining enterprises and regions with lower levels of private finance. Mechanistic analysis further underscores FinTech's role in facilitating eco-friendly transformation through enterprise digitalization and technological upgrading.