We present a stylized microeconomic model to analyze solar panels and storage investment decisions of a representative consumer under either grid (credit regulation) or individual (price regulation) storage. We identify the conditions under which prosumers become storers. We show that solar technology must be more competitive under credit than price regulation for consumers to invest in storage. We

This study delves into the complexities of energy commodity futures and clean energy indexes, analyzing their responses to geopolitical risk. The detrended fluctuation analysis was applied, and the efficiency index was estimated to assess energy market behavior better. This approach allows the evaluation of long-range dependence and market efficiency. The findings show evolving patterns influenced

This paper investigates the connection between energy uncertainty and banking credit risk within the Eurozone. To analyze this relationship, we first apply a Bayesian time-varying VAR model to examine how shocks in energy uncertainty influence financial risk. Next, we use the impulse response function to assess how these shocks propagate through the banking sector. Further, long-run Granger causality

Considering the policies surrounding carbon trading, decarbonization plans have been regarded as imperative choices for the manufacturing industry. However, there has been little research into combining the concrete carbon quota allocation methods with the low-carbon supply chain. Still, the distinction between ordinary and low-carbon manufacturers has been scarcely investigated. To fill these gaps

Inequality in income and consumption expenditure is intricately linked to discrimination based on gender, caste, and religion in India. Using large-scale administrative survey data – the Consumer Pyramids Household Surveys (CPHS), we provide empirical evidence on Roemer's paradigm of equality of opportunity in energy consumption and its components: fuel and electricity consumption. We investigate the

In the European Union's electricity wholesale markets, energy is traded across large bidding zones, which, in most cases coincide with national borders: the so-called zonal markets. Within each market zone, energy flows are supposed to be free of transmission constraints. However, in some cases transmission constraints exist, implying an inefficient mismatch between demand and supply in different areas

This paper uses the dynamic connectedness framework to investigate the interrelationship between the decomposed oil supply, demand and risk shocks that Ready (2018) developed and the stock market returns of emerging market economies. For this purpose, we use daily data from 11 October 2001 to 5 April 2021. Novel empirical methodologies, including wavelet quantile correlation (WQC), cross-quantilogram

As a complement to previous studies related to geopolitical risk (GPRs) and renewable energy development, this study examines the impact of GPRs on renewable energy technology innovation in an attempt to reveal whether fluctuations in GPRs promote energy transition. The study finds that increased levels of GPRs will foster technological innovation in the renewable energy sector, most pronounced in

We investigate the impact of global common volatility and geopolitical risks on clean energy prices. Our study utilizes daily data from January 1, 2001, to March 18, 2024. Using a new framework based on explainable artificial intelligence (XAI) methods, our findings demonstrate that the COVOL index outperforms the geopolitical risk index in accurately predicting clean energy prices. Furthermore, the

We investigate the relationship between business strategies and corporate carbon (CO2) emissions. Using a sample of US publicly listed firms, we document that firms following a prospector-type business strategy emit significantly less CO2 than those adopting a defender-type strategy. We also find that this relationship holds for Scope 1, Scope 2, and Scope 3 emissions. This connection is more evident

This paper examines how border carbon adjustments (BCAs) may address the consequences of uncoordinated global climate action, focusing on the economic impacts for Canada. We investigate these impacts under different BCA design features and by considering a coalition of countries and regions that adopt BCAs. We find that when Canada is within a coalition of BCA-implementing countries including the United

The paper examines how women's political empowerment affects renewable energy demand, considering factors like energy costs, green technologies, and gross domestic product (GDP) growth in the panel dataset of 36 Organisation for Economic Cooperation and Development (OECD) economies from 1990 to 2022. The Least Absolute Shrinkage and Selection Operators (LASSOs) algorithms select the critical drivers

In the eighteenth and nineteenth centuries the United Kingdom transported convicts to the penal colonies of New South Wales and Van Diemen's Land. Most of the convicts who were sent to the colonies were men. Treating it as a quasi-natural experiment, we employ the gender imbalance associated with this historical event to examine how gender norms influence the adoption of photovoltaic solar panels (PVS)

This study investigates the drivers of renewable energy capacity in 25 OECD countries from 1989 to 2019, with a particular focus on the complex role of oil prices in the energy transition. Given their strong correlation with major fossil fuels like coal and gas, understanding the impact of oil price shocks is crucial for shaping effective transition strategies. We examine this impact from a climate

We combine econometric estimation with quantitative modeling to generate projections on the trade, GDP, and emissions effects of a potential trade liberalization agreement involving energy-related environmental goods (EREGs) and environmentally preferable products (EPPs). Trade liberalization can contribute to reduced emissions in two ways in our projections: (i) a reduction of import prices of goods

We develop and apply a modelling framework to estimate the micro-level employment impacts of climate policies in Aotearoa New Zealand. Our approach links an economy-wide model with a micro simulation module to calculate employment changes for different groups of the population across several dimensions (and combinations of dimensions), including sectoral, geospatial, demographic, and socio-economic

We examine how the US treasury yields are connected with traditional energy and green cryptocurrencies in higher moments. For this purpose, we first compute the US treasury yield curve's Level, Slope, and Curvature based on different maturities from October 2017 to December 2023 and then apply the TVP-VAR model on return, volatility, Skewness, and Kurtosis measures. We find that returns are the most

This paper examines the recent increase in natural gas prices, the sensitivity of inflation expectations, and the pass-through to inflation. Using a semi-structural vector autoregression, we identify a natural gas price shock in the euro area with a combination of sign and zero restrictions. We rely on market-based measures of inflation expectations. The results show that shocks to the real price of

This paper explores the interconnections among oil, artificial intelligence (AI), clean technology, and traditional markets. We apply a novel generalized quantile-on-quantile connectedness method that assesses variable cross-quantile interdependencies, analyzing data from 2018 to 2023. Our study provides a detailed examination of risk transmission dynamics between oil, AI, clean technology, and major

This study investigates the relationships between social and political trust and views on energy affordability, which are crucial for promoting sustainable energy practices. The findings indicate that social and especially political trust are negatively correlated with perceptions of energy affordability. The study also finds that the probability of being highly concerned about energy affordability

Disputes over cost allocation can present a significant barrier to investment in shared infrastructure. While it may be desirable to allocate cost in a way that corresponds to expected benefits, investments in long-lived projects are made under conditions of substantial uncertainty. In the context of electricity transmission, uncertainty combined with the inherent complexity of power systems analysis

This study aims to examine the combined effects of green energy (Sustainable Development Goal, SDG-7.2), energy efficiency (SDG-7.3), and economic productivity (SDG-8.2) in mitigating energy-driven GHG emissions. The novelty of this study is that it extends the Kaya identity to mathematically explain how the two SDG-7 goals affect energy-driven emissions, and it provides global empirical evidence from

Reliance only on economic growth fueled by fossil fuels may become unsustainable, where the negative ecological consequences of this growth path are rapidly impacting the ecosystem. To address these challenges, enhancing supply chain digitalization, increasing business enterprise R&D expenditure, and boosting government budget allocations for R&D are essential. Additionally, improving fossil fuel energy

Geopolitical risk, as a key determinant of energy supply, greatly influences the vulnerability of energy markets. This study develops a novel energy market vulnerability index—which measures the level and dynamics in vulnerability of energy markets from market risk perspective—using a quantile connectedness approach for the first time. Then, by introducing a generalized autoregressive conditional

The prior literature has argued that inter-sectoral supply chain links provide an important channel for technology diffusion and productivity spillovers across industries, but whether such vertical spillovers influence industrial energy use has remained unexplored thus far. This study analyzes how the energy intensity of European industries is affected by vertical technology and energy productivity

Revenue cap regulation (RCR) is increasingly common in the energy sector because it purportedly reduces the regulated firm's disincentive to promote conservation. In comparison with price-cap regulation, RCR can yield higher prices, greater energy conservation, lower service quality and decreased cost-reducing innovation. The distortionary effects of earnings sharing on investment in cost-reducing

The functioning of energy markets is essential for global stability and is heavily influenced by geopolitical risks. Understanding these risks is critical for policymakers, market analysts, and nations. This study investigates the impact of geopolitical risks and their components on the futures markets of WTI crude oil and natural gas, utilizing time and frequency connectedness analysis along with

This paper explores various policies to support climate-neutral hydrogen production, focusing on their interaction with energy markets and cap-and-trade systems such as the EU emission trading scheme. We develop and deploy a state-of-the-art equilibrium model to examine the effect of hydrogen support policies on the interactions between hydrogen, electricity and emission markets. Our analysis shows

This study initially develops a risk spillover network within the energy futures market, subsequently analyzing the impacts of climate attention on the risk spillovers associated with individual contracts in this network. We construct a high-dimensional network of 19 futures contracts CoVaR based on the LASSO-VAR method. Furthermore, we construct a climate attention index using the search volume of

In light of the Conference of Parties 26, carbon information reporting has become ever-increasingly important. Prior studies presented much evidence on whether environmental disclosure could reliably reflect environmental performance. However, very limited evidence has been provided on if environmental disclosure could drive firms to improve future environmental performance. Based on the competing

In order to establish sustainable energy systems and lessen environmental effects via resource efficiency and technological innovations, green supply chain management and renewable energy innovations are crucial. Thus, in this study, for the first time, we investigate how digitization and green supply chains impact renewable energy innovations. The study also examined how inflation and energy prices

Due to rising concerns about climate change and anticipated energy demand increase the Norwegian government advocates for floating offshore wind to decarbonize its oil and gas industry on the Norwegian continental shelf (NCS). To realize this endeavor, small-scale projects are vital for driving technological innovation and cost reduction without incurring the risk of extensive losses. As floating wind

This work investigates the technical and financial performance of deeply decarbonised wholesale electricity markets with uncertain variable renewable generation (VRG), uncertain demand and different types of flexibility. It first finds that different combinations of power reserves (i.e. power generation capacity) and energy reserves (i.e. energy storage capacity), can achieve adequate system reliability

In this paper, we analyze the economic impacts of the West-East Electricity Transmission Project (WEETP) project using the multi-period difference-in-difference (DID) method based on county-level data from 2000 to 2020. Our findings indicate that the WEETP project inhibits firm entry in electricity-exporting regions while encouraging firm entry in electricity-importing regions, thus hindering regional

Previous empirical evidence indicates that the carbon market exerts a positive influence on the performance of corporate green innovation. In light of the proposition that there are differences in the green innovation capabilities of firms, we propose a masking effect hypothesis which suggests that the carbon market does, in fact, improve firms' green innovation performance at the overall level. However

We investigate whether green (brown) portfolios constructed from clean energy ETFs (fossil fuel ETFs) yield positive (negative) returns conditional on climate-related risks. While the green portfolios do not unconditionally outperform the brown ones, the outperformance of green portfolios is statistically significant under the conditional setting using non-parametric estimates with imposing inequality

This paper examines the suspension of the Australian National Electricity Market (NEM) that occurred in June 2022. Our study aims to (i) identify the key factors leading to the market suspension, (ii) investigate the behaviour of market participants and price outcomes during this period, and (iii) provide important recommendations for policy and decision-makers related to avoiding or managing crises

Distributive justice is an important but often overlooked factor in policy evaluation. We thus examine how people's attitudes towards distributive justice affect their preferences for programmes aimed at reducing ambient air pollution resulting from the combustion of fossil fuels for residential heating. To do so, we carried out two multifactorial survey experiments that allowed us to incorporate justice

Income inequality and energy poverty are critical obstacles to the worldwide low-carbon transformation and deeply affect human behavior. Applying a dynamic panel data model, this study investigates the effect of income inequality and energy poverty on global carbon emissions. We determine the effect of the interaction between income inequality and energy poverty on the global low-carbon transformation

This study investigates the relationship between novel and old news sentiment and commodity futures returns. Using TRNA data from Thomson Reuters, we measure daily sentiment of both novel and old news to estimate their impact on commodity futures returns. Our findings reveal that both novel and old news sentiment significantly correlate with returns, with old sentiment having a stronger effect. Notably

In recent years, the worsening global geopolitical conditions have led investors and policy makers to become increasingly concerned about systemic risk in the global energy market. However, the existing literature has little empirical evidence on this problem from a geopolitical perspective. Based on an Elastic-Net-VAR model for depicting high-dimensional left-tail interdependence, this paper measures

This study extends recently introduced neural networks approach, based on a regularized distributional multilayer perceptron (DMLP) technique for a multivariate case electricity price forecasting. The performance of a fully connected architecture and a LSTM architecture of neural networks are tested. Different from previous studies we incorporate dependence between multiple exchanges (EPEX and Nord

This paper develops a capped-call option model to evaluate sustainable insurance for achieving common prosperity. It integrates policyholder protection (Sustainable Development Goal 3 (SDG 3)) and the cap-and-trade mechanism (SDG 7) in modeling the Gini coefficient, thereby connecting SDGs 3 and 7 with common prosperity. The main findings are as follows. Life insurance policies that prioritize saving

The slow adoption of residential energy-efficiency retrofits continues to hamper the energy transition. We study incentives for adoption by proposing a model of optimal investment under uncertainty where the wealth-maximising agent has the option to delay. Stochastic portfolio returns and energy prices are taken into account. An extension of the model where the energy carrier is switched, e.g. from

This study presents the first analysis of the nexus between the Southern Oscillation Index (SOI), a measure of climate risk, and segmented clean energy indices (such as solar, renewable, and bioenergy). Our research findings indicate that (i) the Granger quantile causality significance of SOI on segmented clean energy indices is asymmetric across different conditional quantiles. Significant predictability

The aim of this paper is to analyse the key effects contributing to changes in energy imports in the European Union (EU-27) in the period 2000–2020. Using the Logarithmic Mean Divisia Index (LMDI), the analysis examines the effect of changes in six factors—energy structure, energy dependence, energy transformation efficiency, energy yield after transformation, energy efficiency and activity—on imports

Time variation and persistence are crucial properties of volatility that are often studied separately in energy volatility forecasting models. Here, we propose a novel approach that allows shocks with heterogeneous persistence to vary smoothly over time, and thus model the two together. We argue that this is important because such dynamics arise naturally from the dynamic nature of shocks in energy

This research examines the energy efficiency of city districts through the Malmquist–DEA model and investigates the spatial effects of the service trade and the digital economy on energy efficiency in urban green development. The study also delves into the specific context of the AI service trade to gain insights into and align with the emerging digital intelligence industry. The interplay of the service

The accurate forecasting of carbon returns is paramount for enabling informed investment decisions, promoting emissions reduction, and effectively shaping policies to combat climate change. In this paper, we propose a novel method to improve carbon returns predictability in a data-rich environment. The innovations of the model are manifested in two key dimensions: (i) a feature selection strategy based

Electricity storage and inter-regional transmission are expected to play a greater role in mitigating the power surplus caused by the large-scale introduction of solar power generation. In this study, we evaluate the impacts of these two power arbitrages and provide their welfare implications. We develop a simple analytical framework based on the demand and supply in the power market, and apply the

This study explores the degree to which per capita aggregate renewable energy production is converging across U.S. states. Specifically, we examine both relative (club) convergence and weak σ-convergence. The results reject overall convergence in per capita aggregate renewable energy production for the panel of U.S. states, but identifies two convergence clubs. The results also suggest that there is

This research aims to evaluate the accuracy of the long-term relationship between renewable and sustainable energy sectors and emerging technologies, including quantum computing, artificial intelligence (AI), and big data. Using a novel methodology that integrates the Time-Varying Parameter Vector Autoregressive (TVP-VAR) frequency connectedness approach with Long Short-Term Memory (LSTM) neural networks

Renewable energy innovations are essential for mitigating greenhouse gas emissions and addressing climate change, guaranteeing a more pristine and healthful environment. Moreover, these advancements stimulate economic expansion by establishing novel sectors and employment prospects while improving energy reliability and ecological viability. For the first time, the current study explores how supply

Highlighting the unprecedented rise in CO2 emissions from the global energy sector, the paper discusses the significant shift towards renewable energy, which has reshaped financial markets and investment landscapes. Despite the transition, conventional fossil fuel energy remains pivotal to the global economy, influencing renewable energy markets, especially during financial crises. Using advanced methodologies

This paper investigates the influence of peer financial choices on the capital structure decisions of European and North American listed companies in the oil and gas sector. It also examines how commodity prices, particularly oil and natural gas prices, and their corporate hedging affect capital structure policies. The findings underscore the existence of peer effects in the oil and gas industry, indicating

Carbon allowance price is an important tool to reduce carbon emissions and achieve carbon neutrality. It is necessary to establish a predictive model to provide accurate and reliable information to managers and participants in the carbon trading market. Therefore, a novel probability density prediction model, called TS2Vec-based distribution Transformer (TDT), is proposed. TDT consists of two stages:

The domain of energy poverty is increasingly recognised as a multifaceted global challenge stemming from limited income, high energy costs, and inefficient housing. The issue affects different social groups and regions unevenly, even within Europe. This paper investigates energy poverty across 32 economies, including EU member states and several non-EU European countries, over the period from 2004