Utilities Policy最新文献

Attracting private investments to renewable energy projects is a topic of significant debate within academic circles. This study investigates the relationship between green fiscal policy and green monetary policy concerning investments in renewable energy in India, spanning from 1990 to 2021, employing the ARDL (Autoregressive Distributed Lag) technique. The findings reveal that green taxes can positively or negatively impact investments in renewable energy sources. Furthermore, green monetary policy, mainly through the provision of green loans, accelerates investment inflows into renewable energy sources in the short and long terms. Challenges hindering private investment in India's renewable energy sector include compounded risk and inflation. Nonetheless, financial development and literacy rates are crucial in expanding investment in renewable energy sources. Based on these findings, practical policy recommendations for India entail enhancing sustainable literacy through green education, promoting social inclusivity, and establishing effective monetary and fiscal policies.

This study investigates the challenges and strategies associated with successfully implementing the Koramangala-Challaghatta Valley project in Karnataka, India. This project is an innovative approach for water security in semi-arid regions by indirectly recharging groundwater using treated wastewater. Interviews with various stakeholders reveal strategies to address key challenges. An integrated wastewater management and safe reuse framework were applied to analyze the qualitative data. This study highlights the effectiveness of an integrated approach, including institutional collaboration with policies/programs to address technical, financial, and risk mitigation aspects, while community participation promotes social acceptance and ensures the long-term sustainability of wastewater reuse initiatives.

The research literature on the driving mechanisms for the clean energy transition in the Next 11 (N11) economies to accomplish their carbon-free targets is scarce. We address this research gap with an empirical analysis of the effects of renewable fuels, resource allocation, corporate governance, energy trade, economic growth, carbon taxes, and digitalization on the shift to clean energy between 1990 and 2022. Using the method of Moments Quantile Regression, the results show that all regressors enhance the shift to clean energy. Based on the study outcomes, policymakers should intensify their attempts to coordinate policies to support sustainable development goal ambitions.

This paper aims to assess container terminal (CT) efficiency with the effect of carbon neutrality. Among mechanisms to achieve carbon neutrality in CTs' operations, emission taxes are deemed the most preferred tool to internalize the external costs associated with greenhouse gas emissions by placing a financial burden on polluters. This paper first uses cluster analysis to determine the homogeneous decision-making units (DMUs), i.e., container terminals. A novel approach is proposed to determine the level of emission taxes that DMUs should be levied based on how much CO2 they discharge. Since emission taxes are an undesirable output from the operations of CT operators (CTOs), the Slacks-based Measure Data Envelopment Analysis (SBM-DEA) model is thus employed to incorporate the emission taxes into the research model and to determine the optimal emission taxes for CTOs. Finally, the CTOs in Vietnam (hereafter the VN-CTOs case) are empirically surveyed to verify the proposed model. The proposed research framework can contribute a methodological reference toward the relevant literature in achieving carbon neutrality. Further, the empirical results can provide practical information for the Vietnamese CTOs to improve their CT efficiency.

This study investigates the influence of the U.S. Energy Independence and Security Act (EISA) of 2022 on stock market volatility. Considering potential policy impacts on market dynamics, it employs a mean-reverting jump-diffusion model for volatility analysis, supported by rigorous hypothesis testing to validate empirical findings. For investor sentiment analysis, a pre-trained model (BERT-base-multilingual-uncased) is used to assess sentiment, with logistic regression and Bidirectional LSTM utilized for sentiment prediction. Contrary to conventional findings, logistic regression outperforms Bidirectional LSTM for the small dataset. Overall, the study estimates show no statistically noteworthy difference in volatility before and after implementing the EISA of 2022. This study provides valuable insights for navigating financial decisions within the intricate landscape of energy markets.

In the European Union, the transition to a circular economy has been guided by supranational regulations, subsequently transposed by Member States. In Italy, transposition occurred through Legislative Decrees 22/1997 and 152/2006, which set ambitious waste targets. To test their effectiveness in promoting the transition, we implement a Shift-and-Share analysis on data over 1997–2006 and 2007–2019. The three Italian macro-areas (North, Centre and South) shared a virtuous planning phase (specialisation) and a penalising socioeconomic context (competitiveness) in the first period. In the second period, the situation reverted in Northern and Central Italy. Southern Italy remained anchored to the linear economy model.

Developing countries should clarify the dedicated grid connection cost-sharing model when reforming electricity user price policy, which could be learned from developed countries’ experiences. We use the random forest method and monthly data from several developed countries or regions, including the United States and the United Kingdom in 2018–2020, to identify key features that influence decision-makers in choosing dedicated grid connection cost-sharing models and simulate the connection cost-sharing models suitable for various regions of China using provincial data. It provides experience and enlightenment for China and other developing countries to implement the connection price policy reform.

Our analysis aims to better understand water losses by developing a specific methodology for estimating water leak flow rates and durations. Additionally, it aims to improve asset management practices for drinking water utilities by forecasting the costs and benefits of investment and operational decisions on the network. Current utility practices are compared to a "do nothing" policy and to the potential effective asset management policies proposed by an artificial neural network (ANN) based software, PRISM. Applied to four utilities in France, our methodology provides valuable insights for enhancing water loss estimates and finding trade-off asset management policies.

This study aims to identify the strengths, weaknesses, opportunities and threats associated with renewable energy communities (RECs) in Italy. The results, obtained through an incentivised online survey and an analytic hierarchy process, showed that economic saving on energy costs is the most relevant criterion for both consumers and expert stakeholders. Also, technical barriers and energy independence emerged as relevant in developing RECs. Consumers are more sensitive to the social opportunities behind RECs, while experts focus only on the economic aspects. The economic benefits, pragmatism, and effective management of human and physical resources within RECs can help achieve sustainable development.