Impact of Energy Price Distortion on Green TFP Based on Spatial Econometric Model

With environmental regulation as the intermediary, this paper studies the influence mechanism and mediating effect of energy price distortion on green total factor productivity. On the basis of the panel data of 30 provinces in China (except Tibet, Hong Kong, Macao, and Taiwan), the research results from the study of panel and spatial metrology show that energy price distortion has a significant negative effect on the improvement of green total factor productivity. Different environmental regulation tools have different impacts, and the impact effect of fiscal energy conservation and environmental protection expenditure is better than that of pollution punishment. The transmission effect of energy price on environmental regulation policies is different when environmental regulation is the intermediary. The increase of the degree of energy price distortion will increase the financial expenditure of energy conservation and environmental protection, while the energy factor price will increase the green total factor productivity with the increase of pollution punishment.

European energy risks persist despite fall in prices

Headline EUROPE: Energy price risks will persist

The Influence of Energy Price Distortion on Region Energy Efficiency in China’s Energy-Intensive Industries from the Perspectives of Urban Heterogeneity

As typical representatives of China’s industrial sectors, energy intensive industries are the focus of energy conservation. This study constructs a trans-log production function and stochastic frontier analysis model to analyze the impact of energy price distortion on total factor energy efficiency in energy intensive industries on the city level. The results reveal that the phenomenon of energy price distortion existed in all cities from 2003 to 2019, with an average degree of −0.175; and the total factor energy efficiency in China’s energy intensive sectors showed an upward trend, with an average efficiency of 0.729. Further deep analysis of affecting mechanisms concluded that the price distortion showed a significant restraining effect on improving energy efficiency, while the improvement of urban agglomeration systems had an opposite effect. In addition, energy consumption structure, foreign trade, and infrastructure construction are positively correlated with energy efficiency. Therefore, promoting the market-oriented reform of China’s energy market is of great significance to improve city energy efficiency and build a resource-conserving society.

Urban Household Energy Consumption Forecasting Based on Energy Price Impact Mechanism

The energy price influence system is one of the key mechanisms in the study of energy consumption. China’s household energy consumption has obvious regional differences, and rising income levels and urbanisation have changed the willingness and ability of households to make energy consumption choices. Based on the linear price effect of household energy consumption, this paper explores the scenario characteristics of energy prices affecting energy consumption, taking electricity and natural gas consumption as examples. Based on household energy consumption statistics from 2005 to 2018 in 36 major cities across China, the accuracy and change trends of household energy consumption forecasts are investigated through the decision tree-support vector machine (DT-SVR) non-linear forecasting technique. The study shows that the non-linear forecasting technique accurately portrays the predicted trends of changes in total urban household electricity and natural gas consumption. Within the less developed regions of economic development, income levels are still the main constraint on changes in urban household energy consumption, and the stimulating effect of income levels on household energy consumption has not been seen in the process of economic development in these less developed regions. Urbanisation as an important factor in examining household energy consumption, different development patterns and development processes will gradually be reflected in scenario aspects such as the choice of urban household energy consumption and changes in total consumption.

Energy price modelling in Sub-Saharan Africa: a systematic literature review

The energy market in Sub-Saharan Africa (SSA) is not meeting the demands of the region’s growing population. Energy access remains a significant challenge, with most people on the continent still reliant on biomass and other traditional forms of energy. Paradoxically, research has found that the African continent has the highest potential for renewable energy generation. For this energy to be commercialized effectively, there is a need to understand energy price modelling in the SSA context. Our initial review of Literature showed that energy price modelling has received little attention in SSA. This paper, therefore, fills this gap by using a systematic literature review to consolidate knowledge on how energy price modelling has been applied in the SSA context. The systematic literature review results reveal four commonly used models: time series, Artificial Neural Network, Hybrid Iterative Reactive Adaptive (HIRA), and Hybrid models. Across the 46 SSA countries, governments have applied these models to price electricity and petroleum at the national level. However, these models have not been applied to renewable energy markets. Neither have they been applied at the household level. In the discussion, we hypothesize that price modelling can be used at the household level to improve energy decision-making. For this to work, price modelling should be simplified, user-friendly, and accessible to households. In conclusion, we recommend that SSA governments develop a more holistic view of energy price modelling to better harness the potential of renewables. They can do this through effective stakeholder engagement that includes the needs of small businesses and households. The main lessons drawn from this review include the possibility of using energy price modelling technology as a pathway to encouraging energy transitions to renewable energy in informal settlements in Africa. Using technology to bring the price modelling closer to the people is also an important element in facilitating effective transition to renewable energy. Finally, including the members of the community in pricing through creation of awareness on the models used and popularizing technology that can help in predictive pricing will help in creating better and faster energy transitions.

How to Encourage Energy Savings Behaviours? The Most Effective Incentives from the Perspective of European Consumers

Ongoing climate change and increasing energy consumption are becoming a serious threat to international development efforts. To ensure a secure and sustainable future, local, national and regional authorities, as well as energy companies, need to be involved in improving energy efficiency and promoting rational energy use. The consumer is always at the centre of interest of policy and energy reduction strategies makers. It is their behaviour, motives and beliefs that can lead to optimised and economical energy management. This paper responds to the need to identify the individual preferences of energy consumers. The presented research fills an existing gap in the literature by analysing the strength of the influence of different types of instruments and external stimuli shaping pro-environmental attitudes of consumers of different behavioural types. The analysis presented in this paper is the result of the next stage of the authors’ research on energy consumers modelling, their segmentation and comprehensive characteristics. The analysis was conducted on a representative sample of N = 4332 respondents from 8 European countries (Czech Republic, France, Greece, Spain, Germany, Poland, Romania, and the United Kingdom). The study used multivariate statistical methods, such as: Correspondence Analysis, Factor Analysis and Kruskal-Wallis test. These methods are adequate to the assumptions of the research procedure and allowed for the identification of 4 latent factors that link the incentives into groups, where the motivation to save energy is based on: information (“Information and Knowledge”), social norms (“Social Influence”), investment funding (“Investments”) and energy price changes (“Energy Price”). In addition, the level of effectiveness of the studied incentives and motivators depends on the behavioural type of energy consumers and increases with rising levels of their intrinsic pro-environmental motivation.

Evaluation of Energy Price Liberalization in Electricity Industry: A Data-Driven Study on Energy Economics

This study aims to evaluate the effects of price liberalization on energy consumption intensity, because price liberalization leads to improved productivity, energy consumption management, and consumption reform. Although the energy consumption of large-scale factories and industries has increased dramatically, and the energies losses have an increment in the power transmission lines, this policy can result in decreasing the energy consumption intensity due to the changes in consumption patterns. If there is a correlation between two variables, the price can be a valid variable to control cost and increase consumption efficiency. The augmented Dickey–Fuller (ADF) and the Chi-squared tests are also employed to investigate the maneuverability of these variables in the first-order contrast. In this case study, the energy consumption intensity response to price changes using the data gathered between 1988–2020, has gained a confidence interval of these reactions at 95%. The proposed vector autoregressive (VAR) model has forecasted the action and reaction of the end-user, to investigate the future shocks between 2020–2050, considering a new price shock, in the Iranian energy market for the first time. The research findings have shown that energy price liberalization leads to the energy intensity improvement, however, the end-user (shocking) reactions should be investigated to implement a more sustainable policy that eases the new energy price rises.