Q42 - Alternative Energy SourcesNávrat zpět

Green finance strategies have been established to direct funding towards green energy initiatives and promote the advancement of green technology for ecological sustainability. Moreover, the progress in green technology has played a significant role in the growth of green energy infrastructure in China. Nevertheless, there have been no prior investigations undertaken in China that specifically examine the impact of green financing and green technology on green energy within an asymmetric quantile framework. Thus, in the current study, a multivariate quantile-on-quantile regression (m-QQR) methodology is used to experimentally examine the link between green energy usage and green financing in China controlling the environmental sustainability index, green technology and economic progress utilizing data from 2000 to 2022. Results of this study confirm that China benefits in terms of rising green energy consumption only at the mid-levels of green investment projects, if more high-cost projects are added beyond this mid-level, the potential of the active projects diminishes and consumption of green energy declines. This study confirms the conservation hypothesis. A reverse relationship emerges between the consumption of green energy and environmental sustainability. Finally, green technology innovation is coupled with green financing for green energy transition. This study posits that the Chinese economy has the potential to experience significant benefits from the adoption of green energy, mostly driven by breakthroughs and the integration of green technology.

This study aims to investigate whether clean energy exchange traded funds (ETFs) exhibit long-term memory properties and whether the efficient market hypothesis is valid for these assets. The results of the model established to test the dual long memory indicate the existence of long memory in both return and volatility of the ICLN, PBD, PBW series, while the long memory feature is found only in the volatility of the other variables. The results reveal that the selected clean energy ETFs do not exhibit weak efficient market characteristics and volatility has a predictable structure. These results mean that by using the past price movements of clean energy ETFs, future price movements can be predicted and thus above-normal returns can be obtained. In addition, it can be said that risks and uncertainties are effective on the price movements of clean energy ETFs. These results are important for portfolio managers, hedgers and individual and institutional investors aiming to direct their investments to the renewable energy market, as well as for policymakers.

The energy transition process might face cognitive bankruptcy because of prevailing gender bias in the energy sector. Policy reorientation is needed to ensure diminishing of gender bias in the transition process. The political risk persisting within the economy, as well as among its international counterparts, also needs to be internalized within this framework. Existing regulatory infrastructure might possibly have an impact on shaping the dimensions of this association. The present study aims at analysing the effect of energy transition on gender inequality in the USA in light of political risk and regulations. Moderation effects are captured using marginal impact analysis. The estimation results show that although energy transition increases gender inequality, it is reduced in the presence of moderation. The policy framework developed in the study is aimed at attaining the objectives of Sustainable Development Goals (SDG) 5 and 7.

Exploring the political economy of clean energy development, this study appraises how political (de)stabilization influences the clean energy transition process in selected South Asian countries. Using yearly data spanning from 1998 to 2021, the results show that political stabilization facilitates the clean energy transition process by raising the share of renewables in the final energy consumption profiles of the concerned South Asian nations. Contrarily, political destabilization is found to inhibit the transition process. In addition, political stabilization is witnessed to partially offset the clean energy transition-inhibiting impact of rising carbon dioxide emissions across South Asia. Furthermore, the results endorse that financial development and receipts of international remittance contribute to the clean energy transition process while incoming foreign direct investments exert no impact in this regard. Accordingly, a couple of policies are recommended for the concerned South Asian nations.

The urgent need to address climate change and the depletion of natural resources has led governments worldwide to allocate significant resources towards research and development in clean energy technologies and energy efficiency. This study evaluates the effectiveness of renewable energy and energy efficiency initiatives in reducing CO₂ emissions, taking into account the influences of natural resource availability and political risk. Using data from France spanning from 1985 to 2021, we employ the kernel-based regularized least squares (KRLS) methodology, complemented by quantile regression (QR), to analyse these relationships. Our findings indicate that policies promoting energy efficiency and green energy have a positive impact on reducing CO₂ emissions. However, the availability of natural resources and political risk exacerbate environmental challenges by increasing CO₂ emissions. Thus, our study underscores the importance of continued support from policymakers for renewable energy development and energy efficiency research to effectively pursue Sustainable Development Goals (SDGs). Additionally, as the world prepares for COP28, our findings emphasize the urgency of these initiatives in meeting global climate targets.

In the pursuit of sustainable development, economies such as China are placing a paramount emphasis on significantly augmenting the utilization of renewable energy sources. This marks a departure from conventional research approaches that solely focused on macroeconomic determinants while investigating patterns of renewable energy consumption. Thus, this research pursues to witness the relationship between the political risk index (PRI), renewable electricity output (RELOP), public-private partnership investment in energy (PPINENR), and renewable energy consumption (RECNS) in China from 1984 to 2022. For data estimations, this study utilizes time series methods, which include DF-GLS and Johansen cointegration for unit root and long-run equilibrium with FMOLS, DOLS and CCR as primary methods. The research also employs the least squares method with break years and robust least squares as robustness check methods while for causal relationships, we deploy the Granger causality approach. The outcomes assert that variables are found stationary at differences and long-run equilibrium is confirmed among variables. The empirical estimations predict that GDP and PPINENR reduce the RECNS in China in both short and long term. Furthermore, PRI and RELOP enhance renewable energy consumption in the short as well as long run. Therefore, policymakers should mostly focus on the encouraging role of PPINENR towards renewable electricity to enhance RECNS in developing economies, particularly in China. To achieve the targets of COP27, China should increase its focus on the efficient utilization of public-private partnership investments and also manage the political risks in the economy to promote renewable energy consumption and achieve a sustainable environment. Moreover, the causality analysis unearths that PRI could be utilized along with other variables to enhance RECNS in China. The robustness check asserts similar and robust outcomes.

The article investigates the connections between the prices of biofuels and many traded commodities and other relevant assets in Europe, USA and Brazil. The analysis uses a comprehensive dataset covering price data for 32 relevant traded titles over the period 2003-2015. Main contribution of this article is a combination of minimum spanning tree and hierarchical tree approaches with expert economic understanding of biofuels market leading to identification of price connections in a complex trading system. Our analysis of mutual price connections discovers the major defining features of world leading biofuels markest over the last decade. We provide characteristics of main bioethanol and biodiesel markets with respect to technical and local features of the production and consumption of particular biofuels.

The article is focused on the total historical and future costs of supporting photovoltaic elektricity generation in the Czech Republic. The model estimation of these costs is accompanied by methodologically unified comparison with cost of the support of other renewable energy resources. We find that as long as the goals of Czech National Action Plan for Renewable Energy will be implemented, the costs on photovoltaics support will account for more than one half of all costs on renewable energy, combined production of electricity and heat and other secondary resources. The article also provides brief overview of the photovoltaic market in the Czech Republic with its past, present and possible future developments.

The interconnections within food, biofuel and fossil fuel markets are first described in the context of biofuels technologies and economic policy framework. Consequently, the econometric analysis consisting of Johansen cointegration, error correction model, vector autoregression and Granger causality is applied to price series of 12 biofuel related commodities. While a number of equilibrium relationships are found across the examined markets suggesting their interconnection, we do not obtain a persuasive confirmation of the thesis that biofuels clearly lead to food shortages via the increase in prices of basic food commodities used in the production of biofuels.

The paper analyses impacts of environmental regulation on Czech power system. We employ MESSAGE modelling platform to construct a dynamic linear optimisation energy model of the Czech power system. We analyse regulation impacts on fuel use and CO2 emission, fuel-mix and technology-mix, induced investment and fuel and other O&M costs to generate electricity over the period 2006-2030. Negative external costs attributable to endogenously determined new level of air quality pollutants are quantified to make our cost-benefit analysis more complex. Overall, effects of four policy scenarios are assessed, including subsidies for renewable energy, increase in air quality charge rates and an introduction of the EU ETS in the Czech power system. Based on our simulation, we find that prospected 10-fold increase in charging of air quality pollutant would not have any significant effect on emission and would not bring any stimuli for change in technology and fuel mixes. Subsidy to renewable energy would result in their development; however, larger effect would appear in far future and only if new nuclear power units are not allowed to build. Auctioned EUA, especially above €15 per tonne of CO2, would be the only effective instrument with significant effects on power sector. Key factor on CO2 emission is whether scenario consists of new nuclear power units or these units are banned. Our simulation results hold even if we allow the key model assumption to vary, except, the discount rate that would have effect on whether more-investment intensive technologies are used to generate electricity.

In most industrialized countries, renewable energy is supported by policy schemes burden of which is distributed among taxpayers and energy consumers. Renewable sources of energy face a major problem because of their intermittency and that has not been adequately reflected in the discussions of their subsidies in the Czech Republic and in the analysis of the related costs. The article attempts to contribute to this discussion and to the analyses of the costs of growth of wind energy supply in the Czech Republic.