Energy Market Dynamics Research Articles

Research on the Correlation Between Carbon Emission Rights and Energy Market: A Case Study of EUA and Oil Market

This study focuses on the importance of the relationship between carbon and oil in the context of global climate change and energy transition. In particular, this paper explores the link between fluctuations in the price of Brent crude oil in the United Kingdom and changes in the European Union Emission Allowances (EUA), which has significant implications for insight into energy market dynamics and policy making. This study uses an autoregressive (VAR) model to analyze the dynamic relationship between the European Union Emission allowances (EUA) market and the oil market from 2018 to 2024. Through Augmented Dickey-Fuller (ADF) stability test, the VAR model is established, the optimal lag order is determined, and the impulse response and Variance decomposition are analyzed. The results show that the EUA market has a short-term positive impact on the response of the oil market. But this effect has diminished over time, indicating the market's ability to self-regulate and stabilize. These findings provide new perspectives for understanding the interaction between global energy markets and environmental policy tools. The findings highlight the importance of considering these market dynamics when developing market strategies and environmental policies.

Hydrogen underground storage for grid electricity storage: An optimization study on techno-economic analysis

This study performs a techno-economic analysis of hydrogen underground storage systems for grid electricity storage, evaluating their economic viability at the plant scale using dynamic optimization. It explores the feasibility of various system configurations and revenue models in the context of volatile electricity prices and the necessity for multiple revenue streams. The hypothesis tested is that large-scale hydrogen storage, despite its low round-trip efficiency, can be economically viable with the right mix of revenue streams. This study uses scenario-based analysis to assess the impacts of different system configurations, including engaging in time-shifting arbitrage, ancillary service markets and blending hydrogen with natural gas. Results indicate potential annual net cash flows of up to $1.5 million from ancillary services integration and $5.2 million from natural gas blending, contingent on specific system sizes. The study concludes that hydrogen underground storage for grid electricity storage can be profitable, and emphasizes that proper system design and precise electricity price forecasting are crucial for optimizing system performance and economic returns. This research sets the stage for further investigations into the scalability of hydrogen storage systems and their broader implications for grid electricity storage and energy market dynamics.

Asymmetric dynamic linkage between consumer sentiment, inflation expectations, and international energy prices: Evidence from time-frequency wavelet and nonlinear analysis.

This study investigates the relationship between consumer sentiment (CONS), inflation expectations (INEX) and international energy prices, drawing on principles from behavioral. We focus on Brent crude oil price and Henry Hub natural gas prices as key indicators of energy market dynamics. Based on the monthly data from January 2003 to March 2023, three wavelet methods are applied to examine the time-frequency linkage, while the nonlinear distributed lag model (NARDL) is used to verify the asymmetric impact of two factors on energy prices. The results highlight a substantial connection between consumer sentiment, inflation expectations and international energy prices, with the former in the short term and the latter in the medium to long term. Especially, these correlations are particularly pronounced during the financial crisis and global health emergencies, such as the COVID-19 epidemic. Furthermore, we detect short-term asymmetric effects of consumer sentiment and inflation expectations on Brent crude oil price, with the negative shocks dominating. The positive effects of these factors on oil prices contribute to observed long-term asymmetry. In contrast, inflation expectations have short-term and long-run asymmetric effects on natural gas price, and both are dominated by reverse shocks, while the impact of consumer sentiment on natural gas prices appears to be less asymmetric. This study could enrich current theories on the interaction between the international energy market and serve as a supplement to current literature.

Advancing Fast Frequency Response Ancillary Services in Renewable-Heavy Grids: A Global Review of Energy Storage-Based Solutions and Market Dynamics

Advancing Fast Frequency Response Ancillary Services in Renewable-Heavy Grids: A Global Review of Energy Storage-Based Solutions and Market Dynamics

Decoding the Developmental Trajectory of Energy Trading in Power Markets through Bibliometric and Visual Analytics

This research leverages bibliometric methodologies, enhanced by the visual analytics capabilities of CiteSpace, to meticulously examine the evolution and current trends in energy trading within power markets, analyzing 642 scholarly articles from the Web of Science Core Collection spanning from 1996 to 2023. The study aims to illuminate the prevailing research landscape, growth patterns, and future directions in energy trading dynamics. Key findings include: (1) A noticeable escalation in the volume of publications, especially from 2021 to 2023, indicating a burgeoning interest and rapid evolution in this research area; (2) The author and institutional collaboration networks are in a nascent stage, with a predominantly China-centric international collaboration pattern, including significant partnerships with the United States, Australia, and the United Kingdom; (3) The focal points of research are centered around themes such as “energy management”, “demand-side innovation”, “decentralized energy trading”, and “strategic optimization”, covering areas such as intelligent grid technologies, energy market dynamics, and sustainable energy solutions. The study recommends enhancing collaborative networks, fusing technological and strategic dimensions in research, increasing focus and funding for emerging technologies, and promoting wider international and cross-disciplinary collaborations to enrich the understanding of energy trading dynamics in the context of electricity markets.

Digitalization Processes in Distribution Grids: A Comprehensive Review of Strategies and Challenges

This systematic review meticulously explores the transformative impact of digital technologies on the grid planning, grid operations, and energy market dynamics of power distribution grids. Utilizing a robust methodological framework, over 54,000 scholarly articles were analyzed to investigate the integration and effects of artificial intelligence, machine learning, optimization, the Internet of Things, and advanced metering infrastructure within these key subsections. The literature was categorized to show how these technologies contribute specifically to grid planning, operation, and market mechanisms. It was found that digitalization significantly enhances grid planning through improved forecasting accuracy and robust infrastructure design. In operations, these technologies enable real-time management and advanced fault detection, thereby enhancing reliability and operational efficiency. Moreover, in the market domain, they support more efficient energy trading and help in achieving regulatory compliance, thus fostering transparent and competitive markets. However, challenges such as data complexity and system integration are identified as critical hurdles that must be overcome to fully harness the potential of smart grid technologies. This review not only highlights the comprehensive benefits but also maps out the interdependencies among the planning, operation, and market strategies, underlining the critical role of digital technologies in advancing sustainable and resilient energy systems.

The Risk-Return Trade-Off of US Renewable Energy Sector

This study applies the Fama-French three-factor model to analyze the impact of market risk premium, size, and value factors on the stock returns of eight major renewable energy companies listed on the U.S. stock market. Employing linear regression analysis. The analysis indicates that while market trends heavily influence stock returns, the size and value factors' effects vary across different companies. This study contributes to understanding the financial performance of renewable energy firms and underscores the need for industry-specific risk management approaches to bolster investor confidence and facilitate sector growth. The results serve as a foundational reference for investors and policymakers interested in the renewable energy market's dynamics and its future development trajectory.

Time-frequency connectedness between electricity prices in Romania and its determinants in the competitive markets

PurposeIn this paper, we aim to provide an extensive analysis to understand how various factors influence electricity prices in competitive markets, focusing on the day-ahead electricity market in Romania.Design/methodology/approachOur study period began in January 2019, before the COVID-19 pandemic, and continued for several months after the onset of the war in Ukraine. During this time, we also consider other challenges like reduced market competitiveness, droughts and water scarcity. Our initial dataset comprises diverse variables: prices of essential energy sources (like gas and oil), Danube River water levels (indicating hydrological conditions), economic indicators (such as inflation and interest rates), total energy consumption and production in Romania and a breakdown of energy generation by source (coal, gas, hydro, oil, nuclear and renewable energy sources) from various data sources. Additionally, we included carbon certificate prices and data on electricity import, export and other related variables. This dataset was collected via application programming interface (API) and web scraping, and then synchronized by date and hour.FindingsWe discover that the competitiveness significantly affected electricity prices in Romania. Furthermore, our study of electricity price trends and their determinants revealed indicators of economic health in 2019 and 2020. However, from 2021 onwards, signs of a potential economic crisis began to emerge, characterized by changes in the normal relationships between prices and quantities, among other factors. Thus, our analysis suggests that electricity prices could serve as a predictive index for economic crises. Overall, the Granger causality findings from 2019 to 2022 offer valuable insights into the factors driving energy market dynamics in Romania, highlighting the importance of economic policies, fuel costs and environmental regulations in shaping these dynamics.Originality/valueWe combine principal component analysis (PCA) to reduce the dataset’s dimensionality. Following this, we use continuous wavelet transform (CWT) to explore frequency-domain relationships between electricity price and quantity in the day-ahead market (DAM) and the components derived from PCA. Our research also delves into the competitiveness level in the DAM from January 2019 to August 2022, analyzing the Herfindahl-Hirschman index (HHI).

Accelerating renewables: Unveiling the role of green energy markets

The innovative local grey forecasting model for energy production prediction emerges as a pivotal tool in the shift towards renewable energy, embodying the essence of adaptability and precision for the urgent need for sustainable solutions. The integration of such forecasting models is imperative for comprehending the complexities of energy production and market dynamics, ultimately facilitating a seamless transition to a sustainable energy future. Given this, the current study investigates the connections between renewable energy consumption and its determinants, focusing on the role of green energy markets across 12 countries from 2003 to 2021. Employing a novel quantile regression approach, this study analyzes the impact of green energy markets, GDP per capita, urban population, and environmental policies on renewable energy consumption, introducing a renewable energy consumption index for novel insights. Rooted in grey system theory, this study offers a unique approach to predicting energy outputs, crucial for guiding the strategic decisions in green energy markets. The quantile regression analysis reveals that green energy markets have a differential impact on renewable energy consumption whereas Renewable Energy Installed Capacity positively affects renewable energy consumption across all quantiles. Environmental Stringency Policies consistently show a negative impact across all quantiles. By providing reliable predictions of energy production, these findings empower policymakers, investors, and operators to make strategic, data-driven decisions that align with the fluctuating demands of the market and the overarching goals of sustainability and environmental stewardship.

Navigating global energy markets: A review of economic and policy impacts

The global energy landscape is undergoing a profound transformation, marked by shifts in supply and demand dynamics, technological advancements, and evolving policy frameworks. This paper provides a comprehensive review of the economic and policy impacts shaping contemporary global energy markets. Economic forces play a pivotal role in shaping the trajectory of global energy markets. The exploration of unconventional energy sources, such as shale gas and renewable technologies, has disrupted traditional supply chains, influencing market prices and altering the geopolitical dynamics of energy-producing nations. The rise of energy-efficient technologies and the growing demand for cleaner energy sources are redefining the investment landscape, creating new opportunities and challenges for businesses, governments, and consumers alike. Policy decisions at national and international levels exert a profound influence on energy markets. The transition towards a low-carbon economy is a central theme, with governments worldwide implementing a variety of regulatory frameworks, incentives, and penalties to encourage sustainable energy practices. This paper explores the effectiveness and implications of these policies, examining their impact on market competitiveness, innovation, and global cooperation in addressing climate change. The interplay between economic and policy factors is evident in the ongoing energy transition. As countries strive to meet their climate goals, the paper delves into the intricacies of energy market dynamics, analyzing the role of government interventions in fostering innovation, promoting energy security, and addressing socio-economic disparities. Furthermore, the paper highlights the interconnectedness of global energy markets, emphasizing the importance of international collaboration in achieving a sustainable and resilient energy future. By providing a nuanced understanding of the economic and policy influences on global energy markets, this review aims to guide stakeholders in navigating the complexities of an evolving energy landscape.

Power purchase agreements for plus energy neighbourhoods: Financial risk mitigation through predictive modelling and bargaining theory

This paper introduces a continuous 24/7 power purchase agreement (PPA) designed for contracting photovoltaic (PV) generation within sustainable plus energy neighbourhoods (SPENs) or local energy communities, aiming to ensure a stable economic revenue stream for community stakeholders. The PPA involves the sale of solar PV generation, auctioned at a fixed strike price, to an external off-taker. Employing statistical prediction tools such as long short-term memory and auto-regressive modelling, the proposed framework allows hour-to-hour power delivery commitments between seller and buyer, accurately estimating the agreed-upon volume of renewable energy to be exchanged. A fixed PPA price is negotiated utilizing Nash Bargaining Theory, aiming to optimize revenue for the SPEN while minimizing procurement costs for the buyer, thus achieving an economic equilibrium that mitigates the long-term price risk prevalent in wholesale energy markets. Additionally, the proposed methodology includes utilization of a battery energy storage system (BESS) to store excess power or address supply–demand contractual disparities during periods of low PV generation. Simulation results obtained under varying climatic conditions and energy market dynamics across different countries, demonstrate that the proposed PPA framework, by combining risk assessment strategies and statistical learning methods, can effectively reduce associated financial risks while maximizing payoff for the community.

Unraveling Turkish agricultural market challenges: Consequences of COVID‐19, Russia–Ukraine conflict, and energy market dynamics

AbstractFor a significant global segment, the volatility in grain prices presents a substantial menace to food accessibility and security. In the global pandemic and the Russia–Ukraine conflict (RUW), numerous nations were caught off guard, exacerbating this predicament and leading to instances where citizens faced purchasing restrictions on sunflower oil. This study employs the VAR (1)‐Asymmetric BEKK‐Generalized Autoregressive Conditional Heteroscedasticity (GARCH) (1,1) model to assess the extent of risks stemming from the pandemic and RUW in critical Turkish agricultural commodity markets: namely, wheat, barley, corn, and sunflower oil. The analysis reveals that the conditional variances of their return series are positively influenced by short‐ and long‐term uncertainties. With the escalations in the global oil market, the enduring hazards within these selected markets in Türkiye have intensified concurrently. The COVID‐19 pandemic has induced a decrease in long‐term uncertainty within wheat and barley markets, wherein noteworthy spillover risks in the barley, corn, and sunflower oil markets have exacerbated risks in the corn market. Empirical findings imply that COVID‐19 and RUW disrupt the agricultural supply chain, leading to impediments in food provisioning and security. The outcomes provide valuable insights to fortify policies, guarantee consistent access to plant‐based protein, and address nutritional insecurity within the nation. These policy measures align with the initiatives undertaken by the United Nations and Türkiye, which actively engage in establishing a grain corridor to facilitate Ukraine's grain exports, thereby ensuring food security and safeguarding agricultural lands. [EconLit Citations: A1, E3, G1, Q0, Q1, Q2, Q4].

Network interlinkages between artificial intelligence and green energy dynamics during the War in a Pandemic: An application of Bayesian vector heterogeneous autoregressions

We investigate time-varying network interlinkages between artificial intelligence development and green energy market dynamics during the War in a Pandemic. While regarding AI development, we use First Trust NASDAQ Artificial Intelligence and Robotics ETF, Global X Robotics and Artificial Intelligence and ishares Robotics and Artificial Intelligence, and the green energy market, including green bonds, clean energy, wind energy, solar energy, natural gas, and crude oil using seven Bayesian vector heterogeneous autoregression fashions. During the short, medium, and long run, this paper differentiates dynamically between network interlinkages between these markets. We found some noteworthy results in our study. We show that network interlinkages exhibit remarkable differences over time. Interlinkages between networks are increased in the short, medium, and long term due to transient events occurring in markets during the studied period. As a result of the ongoing COVID-19 epidemic and the Russia-Ukraine conflict, the long-term ties within the system are significantly impacted. Additionally, based on net directional linkages, market directional links indicate a shift in roles (from shock receiver to shock transmitter) during the epidemic and at the beginning of the Russia-Ukraine conflict. Observations of short- and medium-term trends reveal that all three indexes for artificial intelligence development are shock receivers from outside, which is transmitted to the green energy sector. The results indicate that artificial intelligence development persists as shock receivers in terms of long-horizon measures but become shocking transmitters during the illness crisis of COVID-19 (from January 2019 to January 2020) and the Russia-Ukraine conflict (from early 2022).

The War in Ukraine and Arab Gulf States’ Foreign Policy Shifts

Abstract This paper discusses geopolitical shifts in the international order with regard to divergent perceptions and interests on the war in Ukraine between western states and the Gulf Cooperation Council states (gcc), specifically the Kingdom of Saudi Arabia (KSA) and the United Arab Emirates (UAE). These two leading gcc states now prioritise their own national interests by valuing multipolar partnerships, rather than solely relying on strong strategic ties with the West and US. The article aims to explore to what extent the war in Ukraine reveals a new phase in the power balance between the west and the Arab Gulf states. The initial outcomes of the war have already weakened Russia’s global status and forced Moscow to redirect its strategy towards the east, particularly China. This has also led to increased military cooperation between Russian and Iranian, as well as a rapprochement due to the weight of western economic sanctions imposed on both states. Concurrently, China’s significant role in world policy has become more evident through its direct political involvement in the restoration of Saudi-Iranian diplomatic relations, as seen in the agreement signed in Beijing on 10 March 2023. With the war in Ukraine significantly impacting the global energy market and regional power dynamics, the multipolar momentum gives the advantage to Gulf states that realise that this is an opportune time to capitalise on taking autonomous regional initiatives and fostering diversified partnerships from the west to the east.

Energy market dynamics and institutional sustainability: How affect the Europe's circular economy

This paper considers socioeconomic, environmental, institutional and demographic issues necessary for the circular economy (CE) transition, employing a sample of 27 European Union (EU) countries and the UK using panel data method. Environmental degradation, asymmetry and inequality in the recovery conditions from the COVID-19 pandemic, which have been particularly aggravated over the last three years (2019–2022), as well as the energy crisis in the Eurozone raise significant challenges for social cohesion and CE policies. This analysis aims to examine whether a change in the structure of the energy markets, densely populated areas, environmental performance, institutional quality, social protection and innovation affect the CE. The results reveal that circular activity is robustly and positively affected by factors such as institutional quality, resource productivity and entrepreneurship. As the level of social protection increases, the percentage of the population willing to adopt the CE principles increases, while EU countries consume more raw materials than they can actually recycle. An increase of 1% in the market share of the largest electricity production companies and the market share of companies supplying the largest volume of natural gas is linked to a reduction of 0.30% and 0.33%, respectively, in the circularity rate. This suggests that under imperfect competition in energy markets, there are signs of undermining the efforts of EU countries to collect waste for recovery.

Modern Trends in Global Energy and Assessment of the Ever-Increasing Role of Digitalization

The global changes which are affecting countries at the moment act as a ‘censor’ of modern energy relations and energy market development strategies in general. The development of the energy market is no longer considered in terms of its efficiency but more in terms of its survivability under the influence of external environmental factors and its ability to maintain an acceptable level of energy safety. In order to fully balance a country’s internal interests and increase its competitiveness in the global energy market, the importance of the problem of choosing a development strategy—following the path of energy independence or cooperative development—is becoming evident. The purpose of this paper is to identify an effective energy strategy for a country under the influence of contemporary challenges. The object of the study is the Russian energy market and the energy companies as its key players. In this context, it examines the situations where Russia and other energy market players are unequally affected by external environmental factors. Particular emphasis is placed on the possibility of overcoming the negative impact of environmental factors during the implementation of measures aimed at ensuring energy safety, achieving a better environmental situation in the country by reducing CO2 emissions, and strengthening the country’s position in the global energy market by changing its own energy development strategy. The dependence of the financial outcome of the energy complex companies of the Russian Federation on the factors of the external and internal environment was determined as the main direction of the study. The financial outcome of the Russian energy complex companies in this article serves as a landmark indicator of energy market development. The working hypothesis of the research is the authors’ claim that it is necessary for modern energy companies in Russia, as important participants in the energy market of the country, to transform their strategy in the direction of deepening cooperation under the influence of external and internal environmental factors. The methodological and theoretical framework of this study consists of classical and modern economic science, covering the analysis of energy market dynamics and structure, as well as the theories aimed at selecting the most effective strategies under the influence of external and internal environmental factors. The study is based on the works of domestic and foreign scientists devoted to the issues of competitiveness, strategic planning, and sustainable development in the context of total digitalization. Within the framework of the conducted research, we used methods of system and factor analysis; statistical research methods, in particular the analysis of dynamic changes, as well as correlation and regression analysis; and methods of comparison, analogy, and generalization. An important source of data on the financial result of companies in the Russian energy sector was the materials of the Federal State Statistics Service of the Russian Federation. As a result of this paper, a notable influence of external and internal environmental factors is determined. Among the most significant factors, digitalization is identified as a development trend. It also represents a driver of improvement in Russia’s energy market, both in terms of improving its competitiveness and environmental safety and in terms of strengthening the country’s leadership position in the global energy market. In addition to the findings, this article provides a theoretical contribution and recommendations for the development of theoretical ideas concerning the choice of an effective strategy for the development of Russia’s energy market. Future research directions are also considered, and the implications of the presented analysis for further research are discussed.

Tackling market opportunities for the biomass production in Romania

Abstract The European Green Deal sets out a detailed vision for Europe to become a climate-neutral continent by 2050 by providing clean, secure, and affordable energy. Thus, with the aim of providing a market-oriented perspective on the economic potential of biomass-related activities, several data were analyzed in this research paper. The positive impact of the green transition is necessary to be studied both at macroeconomic and microeconomic levels. In this context, the research question addressed was: What is the impact of the green transition on farms’ performance and national economy? A descriptive statistical analysis was carried out in order to prove the importance of specific crops, taking into consideration the movements in the energy market and the farmer’s constraints in the era of the European Green Deal. The main objective of this research was to determine if biomass is one of the optimal solutions able to gather all these European desiderates. This conference paper identifies the best scenario for an agricultural farm using diversification activities and the macroeconomic impact of the biomass crops. Currently, the European context is the most favorable for resorting to biomass crops, especially if considering the recent global energy market dynamics. Additionally, there is a need for activities diversification at the farm level in order for them to become greener and to boost their socio-economic and environmental performance. Results confirm that there is considerable economic potential for biomass production in Romania. The added value of the paper is provided by both microeconomic and macroeconomic approaches.

Learning spatiotemporal dynamics in wholesale energy markets with dynamic mode decomposition

Energy markets balance electricity generation (supply) and demand while ensuring non-discriminatory access. Understanding energy market dynamics is essential to improving grid efficiency and optimizing the development of new energy conversion and storage technologies. Accurate energy price forecasts are important for many energy storage technologies to be profitable from price arbitrage. In this paper, we apply Dynamic Mode Decomposition (DMD), a popular spatial-temporal reduced-form modeling technique, to forecast 6587 locational marginal prices in the California Day-Ahead Market (DAM). DMD is a promising equation-free modeling technique in systems with inherent periodic tendencies in time such as financial markets and fluid dynamics. Yet we show, for the first time, that DMD cannot reliably forecast day-ahead energy prices due to the periodicity of the data. Instead, we show Augmented DMD (ADMD) overcomes these limitations and is a fast and accurate price forecaster. We benchmark DMD, ADMD, and backcasting forecasting methods for optimal price arbitrage with an energy storage system. Using ADMD, a market-connected energy storage system can capture up to 92% of allowable revenues in rolling horizon simulations. Moreover, ADMD is up to 1000-times faster than time-series forecasting methods and requires orders of magnitude less data than deep/machine learning techniques.

Towards a complex investment evaluation framework for renewable energy systems: A 2-level heuristic approach

Renewable energy technologies still endure critical technical and financial challenges. These challenges demand for specially tailored decision support tools for planning the (renewable-based) strategical expansion of power systems. However, existing tools not always adequately integrate the tactical and operational dimensions of power systems into the evaluation process; hence, the designed investment strategies might fail to foresee how new infrastructure integrates with the existing power system and also fail to capture the volatile energy market dynamics. In this paper, this methodological gap is addressed by presenting a decision aid framework, based on mixed integer programming, for supporting long-term decision-making when planning (the expansion of existing) energy systems. The proposed framework relies on heuristically solving an optimization problem coined as the Generation, transmission and storage location and sizing of operation-aware sustainable power system design problem, which encodes two nested problems: a novel strategic renewable power system expansion problem, and a Unit Commitment problem. Using a case study from the Chilean power system, it is shown that the proposed tool ensures a more realistic and accurate economic evaluation, as it takes into account the influence of the evaluated project on the grid where it will be installed. In the considered case study, the devised framework designs a sustainable power system expansion investment strategy ensuring an investment rate of return of at least 7% and an annualized profit of more than 277 MM USD considering a 30 years evaluation horizon; furthermore, this is accomplished along with an equalization of the spot price resulting in a 13% reduction with respect to the current spot price of the system. This shows the impact of renewable sources and energy storage systems on the market operation. Furthermore, the proposed approach is used to investigate how high (public) subsidies on renewable technologies should be in order to increase the penetration of these technologies.

Energy market dynamics and the role of fiscal policy in oil‐exporting countries: a TVAR approach

AbstractWhile realising the macroeconomic significance of oil price fluctuations, this research examines the role of fiscal policy under changing dynamics of energy market for selected oil‐exporting countries. We specify a non‐linear threshold structural vector autoregression model which constitutes policy variables such as general government expenditures and primary fiscal balance and macroeconomic indicators such as real GDP growth and the inflation rate. To capture the energy market dynamics, this research selects Brent crude oil price as threshold variable and segregates the sample period 1991‐2019 as ‘high’ and ‘low’ oil price regimes. While using non‐linear generalised impulse response functions, we find that under higher oil price regime, an increase in government expenditures and reduction in fiscal deficit have larger multiplier effect to enhance output growth in most of the sampled countries. In addition, this research identifies larger inflationary effects of an increase in government expenditures and fiscal deficit under higher oil price regime for all countries except Canada. However, under a higher oil price regime, a fiscal deficit induced output growth, and under a lower oil price regime, a reduction in government expenditure brings inflation in Saudi Arabia. Furthermore, this research provides an alternative measure of threshold crude oil price for the sampled countries to their accounting‐based concept of fiscal break‐even price.