Special Issue "Economic Analysis on Energy and Environmental Issues and Policy"

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "Energy Economics and Policy".

Deadline for manuscript submissions: 1 May 2021.

Special Issue Editor

Prof. Dr. Ken'ichi Matsumoto
Website
Guest Editor
Nagasaki University, Nagasaki, Japan
Interests: Climate change and policy; Global environmental issues; CGE model; Econometric analysis; Agent-based mode; Energy security

Special Issue Information

Dear Colleagues,

The current economic system highly depends on energy and natural resources. As a result, economic activities cause various environmental issues, including climate change, pollution, environmental degradation, loss of biodiversity and ecosystem services, waste, and resource depletion. These environmental issues eventually affect our economy, such as industrial activities, agriculture/forestry and land use, disasters, and human health. The global society is now aiming to achieve circular economy as well as a low-carbon, sustainable society. To solve environmental issues and achieve this society, various policy measures have been or will be implemented throughout the world at various levels (global, regional, national, and local). Therefore, it is indispensable to understand the economic aspects of environmental and energy issues and policy (i.e., how environmental and energy issues and policy affect the economy).

This Special Issue aims to gather state-of-the-art research findings and knowledge in all aspects of economic analysis on energy and environmental issues and policy (both empirical and scenario analysis). We also welcome studies with various approaches, from quantitative to qualitative.

Prof. Dr. Ken'ichi Matsumoto
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • economic system
  • environmental system
  • energy system
  • sustainable development goals (SDGs)
  • low-carbon society
  • circular economy
  • economy–environment interactions
  • economic modeling
  • statistical analysis
  • policy analysis

Published Papers (5 papers)

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Research

Open AccessArticle
Forecasting Volatility of Energy Commodities: Comparison of GARCH Models with Support Vector Regression
Energies 2021, 14(1), 6; https://doi.org/10.3390/en14010006 - 22 Dec 2020
Abstract
We compare the forecasting performance of the generalized autoregressive conditional heteroscedasticity (GARCH) -type models with support vector regression (SVR) for futures contracts of selected energy commodities: Crude oil, natural gas, heating oil, gasoil and gasoline. The GARCH models are commonly used in volatility [...] Read more.
We compare the forecasting performance of the generalized autoregressive conditional heteroscedasticity (GARCH) -type models with support vector regression (SVR) for futures contracts of selected energy commodities: Crude oil, natural gas, heating oil, gasoil and gasoline. The GARCH models are commonly used in volatility analysis, while SVR is one of machine learning methods, which have gained attention and interest in recent years. We show that the accuracy of volatility forecasts depends substantially on the applied proxy of volatility. Our study confirms that SVR with properly determined hyperparameters can lead to lower forecasting errors than the GARCH models when the squared daily return is used as the proxy of volatility in an evaluation. Meanwhile, if we apply the Parkinson estimator which is a more accurate approximation of volatility, the results usually favor the GARCH models. Moreover, it is difficult to choose the best model among the GARCH models for all analyzed commodities, however, forecasts based on the asymmetric GARCH models are often the most accurate. While, in the class of the SVR models, the results indicate the forecasting superiority of the SVR model with the linear kernel and 15 lags, which has the lowest mean square error (MSE) and mean absolute error (MAE) among the SVR models in 92% cases. Full article
(This article belongs to the Special Issue Economic Analysis on Energy and Environmental Issues and Policy)
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Open AccessArticle
Energy Prices and COVID-Immunity: The Case of Crude Oil and Natural Gas Prices in the US and Japan
Energies 2020, 13(23), 6300; https://doi.org/10.3390/en13236300 - 29 Nov 2020
Abstract
The COVID-19 pandemic storm has struck the world economies and energy markets with extreme strength. The goal of our study is to assess how the pandemic has influenced oil and gas prices, using energy market reactions in the United States and Japan. To [...] Read more.
The COVID-19 pandemic storm has struck the world economies and energy markets with extreme strength. The goal of our study is to assess how the pandemic has influenced oil and gas prices, using energy market reactions in the United States and Japan. To investigate the impact of the COVID-19 cases on the crude oil and natural gas markets, we applied the Auto-Regressive Distributive Lag (ARDL) approach to the number of the US and Japanese COVID-19 cases and energy prices. Our study period is from 21 January 2020 to 2 June 2020, and uses the latest data available at the time of model calibration and captures the so-called “first pandemic wave”. In the US, the COVID-19 pandemic had a statistically negative impact on the crude oil price while it positively affected the gas price. In Japan, this negative impact was only apparent in the crude oil market with a two-day lag. Possible explanations of the results may include differences in pandemic development in the US and Japan, and the diverse roles both countries have in energy markets. Full article
(This article belongs to the Special Issue Economic Analysis on Energy and Environmental Issues and Policy)
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Open AccessArticle
On the Acceptability of Electricity Demand Side Management by Time of Day
Energies 2020, 13(14), 3665; https://doi.org/10.3390/en13143665 - 16 Jul 2020
Cited by 1
Abstract
Advances in the introduction of fluctuating renewable energies, such as photovoltaics (PV), have caused power-system destabilization. However, stability can be improved if consumers change the way they use power, moving to time slots when the PV output in an area is high. In [...] Read more.
Advances in the introduction of fluctuating renewable energies, such as photovoltaics (PV), have caused power-system destabilization. However, stability can be improved if consumers change the way they use power, moving to time slots when the PV output in an area is high. In large cities in developed countries, where the types of distributed energy resources are varied, demand side management (DSM) in which consumers share power supplies and adjust the demand has received considerable attention. Under effective DSM that uses the latest information and communication technology to maximize the use of renewable energy, we believe that sparing use of appliances is not the only solution to address global warming. If behavioral change shifts the use of domestic appliances from one time slot to other time slots, we do not have to abandon the use of these appliances. The aim of this study is to determine the possibility of such behavioral changes in people in order to provide basic information for operating an effective DSM. To that end, we conducted a questionnaire-based survey of 10,000 households in Japan. We investigated the proportion of people responding to a request for a demand response (DR) under the given presented reward in time slots when DSM by DR is required. We also analyzed the factors influencing people’s response to a request for a DR. Furthermore, based on the rewards likely to be achieved in the adjustable power market, we estimated how much adjustable power would be realized. Full article
(This article belongs to the Special Issue Economic Analysis on Energy and Environmental Issues and Policy)
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Open AccessArticle
The Role of Low Temperature Waste Heat Recovery in Achieving 2050 Goals: A Policy Positioning Paper
Energies 2020, 13(8), 2107; https://doi.org/10.3390/en13082107 - 23 Apr 2020
Cited by 4
Abstract
Urban waste heat recovery, in which low temperature heat from urban sources is recovered for use in a district heat network, has a great deal of potential in helping to achieve 2050 climate goals. For example, heat from data centres, metro systems, public [...] Read more.
Urban waste heat recovery, in which low temperature heat from urban sources is recovered for use in a district heat network, has a great deal of potential in helping to achieve 2050 climate goals. For example, heat from data centres, metro systems, public sector buildings and waste water treatment plants could be used to supply 10% of Europe’s heat demand. Despite this, at present, urban waste heat recovery is not widespread and is an immature technology. Based on interviews with urban waste heat stakeholders, investors interested in green investments, and experience from demonstrator projects, a number of recommendations are made. It is suggested that policy raising awareness of waste heat recovery, encouraging investment and creating a legal framework should be implemented. It is also recommended that pilot projects should be promoted to help demonstrate technical and economic feasibility. A pilot credit facility is suggested aimed at bridging the gap between potential investors and heat recovery projects. Full article
(This article belongs to the Special Issue Economic Analysis on Energy and Environmental Issues and Policy)
Open AccessArticle
The Impacts of Air Pollution on Health and Economy in Southeast Asia
Energies 2020, 13(7), 1812; https://doi.org/10.3390/en13071812 - 09 Apr 2020
Cited by 6
Abstract
The accessibility of cheap fossil fuels, due to large government subsidies, promotes the accelerated gross domestic product (GDP) per capita growth in Southeast Asia. However, the ambient air pollution from fossil fuel combustion has a latent cost, which is the public health issues [...] Read more.
The accessibility of cheap fossil fuels, due to large government subsidies, promotes the accelerated gross domestic product (GDP) per capita growth in Southeast Asia. However, the ambient air pollution from fossil fuel combustion has a latent cost, which is the public health issues such as respiratory diseases, lung cancer, labor loss, and economic burden in the long-run. In Southeast Asia, lung cancer is the leading and second leading cause of cancer-related death in men, and women, respectively. This nexus study employs the panel vector error correction model (VECM) and panel generalized method of moments (GMM) using data from ten Southeast Asian countries from the period (2000–2016) to explore the possible association between emissions, lung cancer, and the economy. The results confirm that CO2 and PM2.5 are major risk factors for lung cancer in the region. Additionally, the increasing use of renewable energy and higher healthcare expenditure per capita tend to reduce the lung cancer prevalence. Governments specially in low oil price era, have to transfer subsidies from fossil fuels to renewable energy to create a healthy environment. Furthermore, cost creation for fossil fuel consumption through carbon taxation, especially in the power generation sector, is important to induce private sector investment in green energy projects. Full article
(This article belongs to the Special Issue Economic Analysis on Energy and Environmental Issues and Policy)
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Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Title: Does Carbon Pricing Improve a Company’s Carbon Management Using an Internal Carbon Price? Empirical Evidence from Korean Companies under the Korean Emission Trading Scheme

Abstract: Amid the growing adoption of carbon prices globally, this study examined whether it contributed to corporate carbon management, with particular attention to a company’s internal carbon price, through a case study of Korean companies under the Korean Emissions Trading Scheme. A questionnaire survey targeting mainly energy-intensive industries, i.e., petrochemical, iron & steel, paper & pulp, and on-sight interviews with executive directors of Emissions Trading Scheme division in 10 major companies were carried out. The interviews found that the companies subject to the emissions trading scheme set their own carbon prices based on the domestic carbon market price, and used such to make investment decisions and to build low-carbon funds. Meanwhile, using the data collected from 100 respondents through the survey, Korean companies’ internal carbon pricing was estimated by using a proxy of the emission allowance price at which a company decides to trade emissions in the carbon market. The multiple-bounded discrete choice format was utilized as the analysis method. Results indicate that the range of the internal carbon price varied by sector. Overall, the carbon price internalized by Korean companies under the domestic emission trading scheme corresponds to 14-17 USD/t-CO2. Econometric analysis adopting the internal carbon price as a dependent variable further shows its association with the pre-listed carbon management factors adopted by companies. It revealed that some companies with a high internal carbon price level are incentivized to abate their emissions through emission trading in order to meet their emission cap. Based on the limited resources and studies available on corporate opinions related to carbon strategies, this study revealed valuable insight on progression in corporate strategies to carbon pricing using internal carbon pricing, and further suggests obstacles in the current system to carbon management as well as requirements for the government to improve the related policy in Korea.

 

 

Title: The Introduction of Wind Power Generation in a Local Community: An Economic Analysis of Subjective Well-Being Data in Chōshi City

Abstract: In this study, we analyze the external effects of wind turbines, which are often considered detrimental to the promotion of wind power generation. Understanding these externalities is essential for reaching a consensus with residents who live near the planned site of a wind turbine. We conducted a mail survey in Chōshi City in Chiba Prefecture to examine the external effects of wind turbines, adopting a subjective well-being index to measure respondents’ well-being. Regression analysis suggests that a view of wind power turbines has a positive effect on the subjective well-being of local residents. Moreover, results indicate that such well-being increases with increasing distance from wind turbines. In other words, except for scenic elements, we found that wind turbines are not always considered desirable by residents. As such, it is important to further clarify the external influence of wind turbines as well as other facilities in the neighborhood.

 

 

Title: Forecasting Volatility of Energy Commodities: Comparison of GARCH Models with Support Vector Regression
Abstract: Energy risk has always been one of major risk factors for most firms involved in key industrial sectors in both developed and developing countries. Risk management of energy commodities is a crucial issue for majority industrial firms, as it can seriously affect its competitiveness, viability and future profitability. Global economic developments, emerging technological advances and unexpected economic, geopolitical and environmental events have caused a significant increase in volatility of energy commodities prices in the last 20 years. For these reasons, the ability to predict volatility of energy commodities is gaining more and more importance.

In the paper we compare the forecasting performance of the GARCH-type models with support vector regression (SVR) for futures contracts of selected energy commodities: crude oil, natural gas, heating oil, gasoil, gasoline. The GARCH models are a standard tool applied in the volatility literature, while SVR is one of machine learning techniques, which have been gaining huge popularity in recent years.

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