In a Non-Orthogonal Unicast and Multicast (NOUM) transmission system, a multicast stream intended to all the receivers is superimposed in the power domain on the unicast streams. One layer of ...Successive Interference Cancellation (SIC) is required at each receiver to remove the multicast stream before decoding its intended unicast stream. In this paper, we first show that a linearly-precoded 1-layer Rate-Splitting (RS) strategy at the transmitter can efficiently exploit this existing SIC receiver architecture. By splitting the unicast messages into common and private parts and encoding the common parts along with the multicast message into a super-common stream decoded by all users, the SIC is better reused for the dual purpose of separating the unicast and multicast streams as well as better managing the multi-user interference among the unicast streams. We further propose multi-layer transmission strategies based on the generalized RS and power-domain Non-Orthogonal Multiple Access (NOMA). Two different objectives are studied for the design of the precoders, namely, maximizing the Weighted Sum Rate (WSR) of the unicast messages and maximizing the system Energy Efficiency (EE), both subject to Quality of Service (QoS) rate requirements of all messages and a sum power constraint. A Weighted Minimum Mean Square Error (WMMSE)-based algorithm and a Successive Convex Approximation (SCA)-based algorithm are proposed to solve the WSR and EE problems, respectively. Numerical results show that the proposed RS-assisted NOUM transmission strategies are more spectrally and energy efficient than the conventional Multi-User Linear-Precoding (MU-LP), Orthogonal Multiple Access (OMA) and power-domain NOMA in a wide range of user deployments (with a diversity of channel directions, channel strengths and qualities of channel state information at the transmitter) and network loads (underloaded and overloaded regimes). It is superior for the downlink multi-antenna NOUM transmission.
Using data on 10,776 firms across 22 emerging markets, we show that both credit constraints and weak green management hold back corporate investment in green technologies embodied in new machinery, ...equipment, and vehicles. In contrast, investment in measures to explicitly reduce emissions and other pollution is mainly determined by the quality of a firm’s green management and less so by binding credit constraints. Data from the European Pollutant Release and Transfer Register reveal the environmental impact of these organizational constraints. In areas where more firms are credit constrained and weakly managed, industrial facilities systematically emit more CO 2 and pollutants. A counterfactual analysis shows that credit constraints and weak management have respectively kept CO 2 emissions 4.5% and 2.3% above the levels that would have prevailed without such constraints. This is further corroborated by our finding that in localities where banks had to deleverage more due to the global financial crisis, carbon emissions by industrial facilities remained 5.6% higher a decade later. This paper was accepted by Lukas Schmid, finance. Supplemental Material: The online appendices and data files are available at https://doi.org/10.1287/mnsc.2023.00772 .
This study investigates the effect of green-bond financing on energy efficiency investment for green economic recovery. The fuzzy Analytic Hierarchy Process (AHP) technique was used to achieve the ...research objective. The study’s findings showed that green bonds are currently the primary financing source for energy efficiency projects, enhancing economic growth by 4.9% and potentially increasing green economic recovery by approximately 17% per annum. The fuzzy analysis technique and alternative models of fuzzy modeling were applied in this study. An alternative to project-based financing is energy performance contracts (EPCs). Green bonds also invest in public and private funds for energy efficiency and economic growth. Alternatively, such bonds may finance environmental initiatives or companies. Testing energy-efficiency projects with low payback rates may be expensive. Expanding the green economy through green bonds is essential for financing to successfully promote energy efficiency finance and green growth. This study also has policy implications for stakeholders.
Non-orthogonal multiple access (NOMA) is considered as a promising technology for improving the spectral efficiency in fifth-generation systems. In this correspondence, we study the benefit of NOMA ...in enhancing energy efficiency (EE) for a multiuser downlink transmission, wherein the EE is defined as the ratio of the achievable sum rate of the users to the total power consumption. Our goal is to maximize EE subject to a minimum required data rate for each user, which leads to a nonconvex fractional programming problem. To solve it, we first establish the feasible range of the transmitting power that is able to support each user's data rate requirement. Then, we propose an EE-optimal power allocation strategy that maximizes EE. Our numerical results show that NOMA has superior EE performance in comparison with conventional orthogonal multiple access.
Green development is critical for China's economic transformation. Enhancing green total factor energy efficiency (hereafter GTFEE) is vital to emission reduction and to win-win industrial ...development. This study uses the panel data of 30 Chinese provinces for the period 2005–2016 to investigate the relationship between environmental regulation and China's GTFEE. The spatial Durbin model is employed to control for the possible spatial spillover effect. A dynamic threshold panel model that can effectively address the endogeneity problem and regional heterogeneity is utilized to examine the potential non-linear relationship between environmental regulation and GTFEE under different conditions of environmental decentralization. The estimation results indicate that there is a significant U-shaped relationship between environmental regulation and China's GTFEE. With the further expansion of environmental decentralization, the local government's autonomous choice of pollution control is improved. The improvement of environmental decentralization can lead to negative moderating effect of environmental regulation on GTFEE. Additionally, the regression results of dynamic threshold model show that environmental decentralization can increase the negative influences of environmental regulation on GTFEE. Interestingly, the non-linear impact of environmental regulation on GTFEE is dependent on the specific type of environmental decentralization. Higher degree of environmental decentralization can lead to an increase in the restraining effect of environmental regulation on GTFEE. However, an improvement in the decentralization of environmental supervision and environmental monitoring can increase the negative influences of environmental regulation on GTFEE.
•The impact of environmental regulation on green total factor energy efficiency (GTFEE) is examined.•Environmental decentralization is introduced as moderating variables.•Spatial econometric methods and dynamic threshold models are used for empirical estimations.•There exists a significant U-shaped relationship between environmental regulation and China's GTFEE.•Environmental decentralization increases the restraining effect of environmental regulation on GTFEE.
Information and communication technology supported by the internet has become an important driving force that promotes the intelligent development of environmental governance in China. Using Chinese ...provincial panel data for the period 2006–2017, this study investigates whether the internet has improved China's green total factor energy efficiency (GTFEE) using a dynamic spatial Durbin model, mediation effect model and dynamic threshold panel model. The empirical results indicate that the GTFEE has a significant positive spatial correlation. Internet development can not only directly improve local GTFEE but also improve GTFEE in neighboring regions. After accounting for potential endogeneity, this conclusion is still valid. Meanwhile, internet development can indirectly improve regional GTFEE by reducing the degree of resource mismatch while enhancing GTFEE by improving regional innovation capabilities and promoting industrial structure upgrades. In addition, the regression results of the dynamic threshold model show that there is a nonlinear relationship between the influence of the internet development and GTFEE. Specifically, due to an increase in the degree of labor resource mismatch and capital resource mismatch, the impact of the internet on GTFEE has gradually decreased, and this effect has gradually increased with the improvement of regional innovation capabilities and the industrial structure.
•Green total factor energy efficiency (GTFEE) of 30 provinces in China is estimated.•Influence of internet development on GTFEE efficiency is quantitatively investigated.•A spatial-Durbin model that accounts for potential spatial spillover effects is employed.•Internet development can significantly improve GTFEE, but the relationship is nonlinear.•Resource mismatch, technological innovation and industrial upgrading may affect GTFEE.
A more efficient use of China’s coal resources is key to rapidly promoting the growth of the country’s industrializing economy. As such, it is essential that an effective approach for measuring and ...evaluating the current efficiency of coal resources is developed. This paper measures the efficiency of coal resources in 30 provinces in China from 2000 to 2015 using an improved DEA model of Bootstrap, and it uses Tobit regression to analyze the influencing factors on the efficiency of coal resources. The results illustrate that: 1) The proposed approach could significantly improve upon the accuracy of the measurement of the traditional DEA model. 2) The efficiency of coal resources shows an uptrend of fluctuation for the research period. With respect to the influential factors, total coal consumption has the least influence on the efficiency of coal resources. In contrast, local financial science and technology expenditures have greatest influence on the efficiency of coal resources. Among all the influential factors, local financial science and technology expenditures have the greatest negative impact on energy efficiency of coal resources and it is very critical that the government increases investment in scientific and technological investment in the mining industry.
•This paper uses Bootstrap-DEA to calculate the ECR of 30 provinces in China.•The finding that FST has negative impact on ECR is the most serious, particularly for 14 provinces in China.•GDP, IPC and SEC have negative impacts on ECR in 8 provinces.•COC has negative impact on ECR in 6 provinces.•TER and RPY have negative impacts on ECR including in 11 provinces and 9 provinces respectively.
The traditional estimation methods tend to result in biased energy efficiency estimates due to the exclusion of heterogeneous production technology. Taking this factor into account, this study uses ...the metafrontier method combined with the stochastic frontier analysis (SFA) to analyze energy efficiency performance of the industrial sectors in China’s 30 provinces during 1997–2016. This study measures energy efficiency by considering the technological gap that can be regarded as a discrete source of energy inefficiency. Different from the traditional classification of different regions in China, we divide regions into three groups by using the cluster analysis based on the indicator of energy intensity. The empirical results are summarized as follows: first, the traditional pooled estimation method, which ignores the technological gap of the industrial sectors among different regions, tends to overestimate energy efficiency performance; second, energy efficiency and technological gap ratios (TGRs) of the industrial sectors are distinct among China’s regions; and the industrial sectors of the eastern region maintained higher energy efficiency and TGRs due to more advanced production technology; third, in general, the average score of industrial energy efficiency of China was only 0.4396, implying that there’s still plenty of room for energy efficiency improvement.
•Applying SFA method with metafrontier to analyze industrial energy efficiency.•Considering technological heterogeneity in energy efficiency measurement.•The traditional pooled estimation tends to overestimate energy efficiency.•Regional differences exist in industrial energy efficiency and TGRs.
The household sector is one of the most energy-intensive sectors in Europe, and thus a focal point for reducing greenhouse gas emissions associated with energy consumption. Energy efficiency is ...considered a key measure to reduce household energy consumption, but several factors could lead to an underinvestment in energy efficiency. This is the so-called energy efficiency gap or paradox. The factors in question are grouped under market failures (including informational failures), behavioural failures and other factors. Various policies can be used to address these failures and promote the adoption of energy-efficient technologies, including energy standards and codes, economic incentives and information instruments. This paper reviews the empirical evidence to date on energy efficiency policies and discusses their effectiveness. On the one hand, command and control instruments seem to be effective policies, but they have to overcome several barriers. In the case of price instruments, subsidies and taxes do not seem to be effective while rebates present mixed results as they sometimes are effective and in other cases, they could present significant shortcomings. Finally, the effectiveness of informational policies is not always ensured as they depend on the country, sector and product category. Information feedback tools also seem to be effective as they work as a constant reminder of energy-efficient behaviour. Some limitations of energy efficiency policies are also identified, such as the difficulties of implementing codes and standards given that a minimum level need to be achieved, differences in the effectiveness of rebate programmes and non-conclusive results in regard to the effectiveness of monetary energy efficiency labels.
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