Amar Rao

57344924300

Publications - 21

Climate resilience through finance: The divergent roles of institutions and markets

Publication Name: Finance Research Letters

Publication Date: 2025-11-01

Volume: 85

Issue: Unknown

Page Range: Unknown

Description:

This study investigates the divergent roles of financial institutions and financial markets in shaping climate resilience, with a focus on lower- and middle-income countries. Using a panel dataset spanning 1996–2021, we employ fixed effects models with Driscoll–Kraay standard errors and instrumental variable (IV-2SLS) techniques to address cross-sectional dependence, heteroskedasticity, and endogeneity. Our findings reveal that well-developed financial institutions, such as commercial and development banks, have a consistently positive and significant impact on climate resilience, especially when supported by strong governance frameworks. Interaction effects show that governance quality, particularly regulatory quality and control of corruption, significantly amplifies the effectiveness of financial institutions. Conversely, the role of financial markets appears more complex and context-dependent: in the absence of robust governance, financial markets can exhibit negative or neutral effects on resilience outcomes. These results underscore the importance of institutional quality in determining whether financial development supports or hinders climate adaptation. The study offers actionable insights for policymakers seeking to leverage finance for climate-resilient development in emerging economies.

Open Access: Yes

DOI: 10.1016/j.frl.2025.108008

SDG adoption and firm risk: The impact of ESG performance, investor confidence, and agency cost

Publication Name: International Review of Economics and Finance

Publication Date: 2025-07-01

Volume: 101

Issue: Unknown

Page Range: Unknown

Description:

This study investigates the nexus between firm-level Sustainable Development Goals (SDG) adoption and firm risk using a unique dataset of National Stock Exchange (NSE) 500 companies from 2019 to 2024. It constructs a novel SDG adoption index to assess this relationship and reveals a noteworthy reduction in firm risk associated with SDG adoption. The results remain robust after a battery of robustness checks, including endogeneity concerns using 2SLS IV and system GMM and sample selection bias through Heckman's two-stage methods. Furthermore, the mechanism test indicates that SDG adoption reduces firm risk by enhancing investor confidence, improving ESG performance, and reducing agency costs. In addition, heterogeneity analyses demonstrate that the impact is more accentuated for enterprises with higher information asymmetry, higher board gender diversity, and non-state ownership. The results carry significant implications for investors, corporations, and policymakers seeking to mitigate risk and foster sustainable practices, particularly within the context of the COVID-19 pandemic and emerging markets.

Open Access: Yes

DOI: 10.1016/j.iref.2025.104205

Crude oil Price forecasting: Leveraging machine learning for global economic stability

Publication Name: Technological Forecasting and Social Change

Publication Date: 2025-07-01

Volume: 216

Issue: Unknown

Page Range: Unknown

Description:

The volatility of the energy market, particularly crude oil, significantly impacts macroeconomic indices, such as inflation, economic growth, currency exchange rates, and trade balances. Accurate crude oil price forecasting is crucial to risk management and global economic stability. This study examines various models, including GARCH (1,1), Vanilla LSTM, GARCH (1,1) LSTM, and GARCH (1,1) GRU, to predict Brent crude oil prices using different time frequencies and sample periods. The LSTM and GARCH (1,1)-GRU hybrid models showed superior performance, with LSTM slightly better in predictive accuracy and GARCH (1,1)-GRU in minimizing squared errors. These findings emphasize the importance of precise crude oil price forecasting for the global energy market and manufacturing sectors that rely on crude oil prices. Accurate forecasting helps ensure economic sustainability and stability and prevents disruptions to production and distribution chains in both developed and emerging economies. Policymakers may choose to implement energy security measures in response to the significant impact of crude oil price volatility on the macroeconomic indicators. These measures could include maintaining strategic reserves, diversifying energy sources, and decreasing the dependence on volatile oil markets. By doing so, a country's ability to handle oil price fluctuations and ensure a stable energy supply can be enhanced.

Open Access: Yes

DOI: 10.1016/j.techfore.2025.124133

Hybrid ML models for volatility prediction in financial risk management

Publication Name: International Review of Economics and Finance

Publication Date: 2025-03-01

Volume: 98

Issue: Unknown

Page Range: Unknown

Description:

Predicting volatility in financial markets is an important task with practical uses in decision-making, regulation, and academic research. This study focuses on forecasting realized volatility in stock indices using advanced machine learning techniques. We examine three key indices: the Shanghai Stock Exchange Composite (SSE), Infosys (INFY), and the National Stock Exchange Index (NIFTY). To achieve this, we propose a hybrid model that combines optimized Variational Mode Decomposition (VMD) with deep learning methods like Artificial Neural Networks (ANN), Long Short-Term Memory (LSTM), and Gated Recurrent Units (GRU). Using data from 2015 to 2022, we analyse how well these models predict volatility. Our findings reveal distinct patterns: the SSE shows high unpredictability, INFY is prone to extreme positive volatility, and NIFTY is relatively moderate. Among the models tested, the Q-VMD-ANN-LSTM-GRU hybrid model consistently performs best, providing highly accurate predictions for all three indices. This model has practical benefits for financial institutions. It improves risk management, supports investment decisions, and provides real-time insights for traders and risk managers. Additionally, it can enhance stress testing and inspire innovative trading strategies. Overall, our study highlights the potential of advanced machine learning, especially hybrid models, to address financial market complexities and improve risk management practices.

Open Access: Yes

DOI: 10.1016/j.iref.2025.103915

Impact of technological advancement and greener energy on sustainable agriculture in Asia: Evidence from selected Asian countries

Publication Name: Sustainable Development

Publication Date: 2025-02-01

Volume: 33

Issue: 1

Page Range: 221-237

Description:

Regardless of major advancements in food production, Asia continues to confront severe food security challenges. Sustainable agriculture presents entirely new prospects by prioritizing the productive worth of human, social, and natural capital—all of which are abundant in Asian nations or can be replenished at a relatively low financial expense. This paper sets out to explore the role of technological innovation, renewable energy use, financial development, globalization, and institutional quality on the environmental sustainability of agriculture, measured by the greenhouse gas emissions from the agricultural sector for top 10 agricultural economies of Asia from 1990 to 2019. To attain the above objective, we employ a variety of econometric models capable of accounting for cross-sectional dependence, including the CS-ARDL model and the Dumitrescu-Hurlin Panel Granger Causality tests. The result indicates that technological innovation as well as the use of renewable energy can reduce the greenhouse gas emissions from the agricultural sector and thus contribute towards enhancing environmental performance of this sector in short and long run. Although globalization result is revealed to be positive, it turns out to be insignificant in both short and long run. Financial development exerts positive and significant effects on agricultural emissions while the institutional quality is found to be increasing the agricultural environmental performance. Finally, we provide policy recommendations based on the results of the study.

Open Access: Yes

DOI: 10.1002/sd.3106

Geopolitical instability and environmental sustainability

Publication Name: Environmental Economics and Policy Studies

Publication Date: 2026-01-01

Volume: 28

Issue: 1

Page Range: 445-471

Description:

Geopolitical instability significantly impacts environmental sustainability, yet its role remains underexplored. This study investigates how geopolitical risk affects ecological footprints and carbon emissions, key proxies for environmental sustainability, using panel data from 27 countries (1990–2020). Panel quantile regression results show a significant relationship between increased geopolitical risk, ecological footprints, and carbon emissions, with coefficients ranging from 0.357 to 0.785 across quantiles in the case of ecological footprints and 0.939–1.961 for carbon emissions. We control the estimation for inflows of foreign direct investment, economic growth, environmental patents, stringency, trade, and population. Economic growth correlates with a decrease in environmental sustainability, while environmental sustainability demonstrates an inverse relationship with ecological footprint and carbon emissions. The findings have policy implications because they can guide policymakers to take risks emanating from geopolitical uncertainty, while formulating environmental policies. Moreover, addressing increased environmental innovation and enhancing coverage of carbon taxes can help maintain environmental sustainability.

Open Access: Yes

DOI: 10.1007/s10018-025-00451-6

Temporal dynamics of geopolitical risk: An empirical study on energy commodity interest-adjusted spreads

Publication Name: Energy Economics

Publication Date: 2025-01-01

Volume: 141

Issue: Unknown

Page Range: Unknown

Description:

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 impulse response function methods. The analysis is based on a dataset comprising daily prices of spot and futures contracts (across various maturities) as well as treasury yields. Our findings reveal that geopolitical risks have a significant, negative impact on the interest-adjusted spread of WTI crude oil. In contrast, the interest-adjusted spread of natural gas futures (NGF) displays a more complex pattern: while short-term maturities show an insignificant response, long-term maturities exhibit a significant reaction. Spillover effects are more pronounced in the short term but tend to weaken over longer horizons. This study underscores the dynamic influence of geopolitical risks on both key energy markets. Its findings offer a practical framework for risk management, equipping market participants and policymakers with valuable insights to better understand and respond to geopolitical risks in the energy sector.

Open Access: Yes

DOI: 10.1016/j.eneco.2024.108066

Climate change dynamics for global energy security and equity: Evidence from policy stringency drivers

Publication Name: Journal of Environmental Management

Publication Date: 2024-11-01

Volume: 370

Issue: Unknown

Page Range: Unknown

Description:

This study investigates the dynamic interplay between financial integration, political stability, infrastructure, and global integration in enhancing Energy Security (ES) and Energy Equity (EE) across 50 economies from 2006 to 2018. It addresses gaps in understanding how socio-economic, political, and technological factors collectively influence ES and EE during the global transition from fossil fuels to renewable energy sources. The research aims to reveal the complex relationships and potential trade-offs between energy sustainability, economic growth, and equitable energy distribution. Utilizing robust panel data methods including System GMM, Fixed Effects, and Random Effects, the study examines the impacts of various determinants on ES and EE. The dataset includes annual observations on global integration, financial integration, infrastructure quality, political stability, and other relevant metrics from diverse global sources. The findings reveal that increased financial integration significantly enhances ES by easing capital flow into energy infrastructure, which is crucial for stable energy supply chains. Political stability also positively affects ES, underscoring the importance of stable governance in sustaining energy policies. Conversely, rapid urban growth and inadequate social integration pose challenges to achieving EE, highlighting disparities in energy access worsened by urbanization. Technological advancements and digital connectivity appear as positive drivers for EE, enhancing the efficiency and distribution of energy resources. This study contributes to the literature by providing a detailed examination of how integration into global financial and political systems affects energy strategies at a national level. It offers valuable insights for policymakers on fostering environments conducive to sustainable energy development and fair energy access. The research underscores the importance of incorporating socio-economic and technological advancements in energy policy frameworks to achieve balanced growth and sustainability. Future research directions include exploring the causal relationships and long-term impacts of these factors on ES and EE, particularly in the context of evolving global energy policies and technological advancements.

Open Access: Yes

DOI: 10.1016/j.jenvman.2024.122484

Minerals at the crossroads: Economic policies, global trade, and renewable energy in the global South

Publication Name: Resources Policy

Publication Date: 2024-10-01

Volume: 97

Issue: Unknown

Page Range: Unknown

Description:

No description provided

Open Access: Yes

DOI: 10.1016/j.resourpol.2024.105257

Environmental apprehension under COP26 agreement: Examining the influence of environmental-related technologies and energy consumption on ecological footprint

Publication Name: International Journal of Environmental Science and Technology

Publication Date: 2024-08-01

Volume: 21

Issue: 12

Page Range: 7999-8012

Description:

Governments internationally strive to balance environmental health and economic development. Modern economies, specifically emerging ones, emphasize the importance of eco-friendly progress, where the pace of economic growth limits the ecological footprint. The ecological footprint denotes both the trajectory of natural resource extraction in the economic process and how quickly these resources can be replenished, as well as the capacity of the ecological sector to absorb waste from this process. This study examines 38 countries from 1994 to 2020 to investigate the drivers of the ecological footprint and found that environmentally related technologies harmfully influence ecological deprivation but are positively affected by gross domestic product growth. Renewable energy diminishes pollution levels, while urbanization has an insignificant effect. Imports were only found to be significant with one econometric technique, and their impact on the ecological footprint was positive. Income level affects the influence of gross domestic product on the ecological footprint. Lower-income quantiles have a more significant impact than higher quantiles. The Granger causality test shows bidirectional causality between the ecological footprint and exogenous factors: eco-technologies, gross domestic product/capita, renewable energy, urbanization, and imports.

Open Access: Yes

DOI: 10.1007/s13762-024-05526-7

Empowering energy transition: Green innovation, digital finance, and the path to sustainable prosperity through green finance initiatives

Publication Name: Energy Economics

Publication Date: 2024-08-01

Volume: 136

Issue: Unknown

Page Range: Unknown

Description:

This study delves into the intricate relationship between financial digitization and green innovation, aiming to shed light on their dynamic interplay within a global context. Spanning from 2003 to 2020, the study encompasses 15 diverse countries, encompassing both developed and emerging economies, including Australia, Brazil, Canada, China, France, Germany, India, Italy, Japan, Mexico, Russian Federation, South Africa, Turkey, the United Kingdom, and the USA. It not only explores the direct connection between financial digitization and green innovation but also takes into account various controlling factors such as economic growth, industrial value addition, research and development expenditure, and gross national expenditure. The key findings from quantile regression reveal financial digitization have a significant positive effect, indicating that in countries with lower green innovation levels, an increase in digital financial services significantly boosts green innovation. This positive impact persists across quantiles, even in countries with higher green innovation levels, albeit to a lesser degree. Economic growth consistently shows a negative association with green innovation across all quantiles. Research and development expenditure consistently demonstrate a positive relationship with green innovation across all quantiles, emphasizing that countries allocating a higher percentage of their economic growth to research and development expenditure activities experience substantial increases in green innovation. This underscores that countries allocating a higher percentage of their economic growth to research and development expenditure activities experience substantial increases not only in green innovation but also in the facilitation of green finance initiatives.

Open Access: Yes

DOI: 10.1016/j.eneco.2024.107736

Carbon conundrums: Geopolitical clashes and market mayhem in the race for sustainability

Publication Name: Journal of Environmental Management

Publication Date: 2024-01-15

Volume: 350

Issue: Unknown

Page Range: Unknown

Description:

This research presents an in-depth investigation into the dynamic correlation between geopolitical conflicts and carbon markets utilizing the Time-Varying Parameter Vector Autoregression (TVP-VAR) technique. The analysis focuses on the interconnectedness between the Geopolitical Risk Index Daily (GPRD) and vital carbon pricing instruments, specifically the Intercontinental Exchange Endex European Union Allowance (ECEFDC), KraneShares California Carbon Allowance Strat ETF (KCCAK), Shanghai Environment and Energy Exchange China Emission Allowances Online Transactions (SAXCEA), and S&P Global Ex-Japan LargeMidCap Carbon Efficient Index (SPGJ). The daily fluctuations were traced from May 2021 to July 2023. The analysis is divided into short- and long-term connectedness, with particular emphasis on the impact of the Russia-Ukraine conflict on the GPRD's spillover on carbon markets. The short-term connectedness (1–5 days) between GPRD and ECEFDC shows variability, fluctuating between 10% and 40%. Conversely, long-term connectedness exhibited a significant increase during the conflict, peaking at approximately 34% by mid-2022. The analysis of the Total Dynamic Connectedness (TCI) between the GPRD and the KCCAK indicates comparable magnitudes, although with minor initial discrepancies. The short-term connectedness of GPRD and KCCAK decreases from its peak of approximately 10% to approximately 1%. Conversely, long-term connectedness varies between approximately 32% and 2% from May 2022 onwards. The long-term connectedness between GPRD and SAXCEA revealed variable patterns, peaking at around 18% at the beginning of the sample period and rapidly reducing to around 1% within two months. The analysis of the connectedness between GPRD and the SPG) identifies intense fluctuations in both TCI and long-term connectedness. After an initial increase and decrease, these patterns rebound and experience another increase. This research provides significant insights into the complex dynamics of geopolitical conflicts and carbon markets, particularly the impact of the Russia-Ukraine conflict on carbon market behavior.

Open Access: Yes

DOI: 10.1016/j.jenvman.2023.119631

Energy in the backseat? Investigating decarbonization dialogue in supply chain tweets during and after COVID-19

Publication Name: Annals of Operations Research

Publication Date: 2026-04-01

Volume: 359

Issue: 1

Page Range: 581-613

Description:

While we move into the seventh year of the signing of Paris agreement, research scholars and supply chain firms have paid a lot of emphasis on environmental sustainability with the aim of achieving net zero targets by 2050. However, the global pandemic has somewhat disturbed the focus from environment to resilience due to severe economic implications of COVID-19. In this paper, we contribute to the very scant discussion on Twitter Analytics by analysing supply chain tweets with COVID-19 at the backdrop. Our approach involves analysing how decarbonization related discussions have evolved by capturing the tweets across three timelines: pre pandemic, pandemic and post pandemic. By integrating descriptive analytics, content analytics and machine learning algorithm in topic modelling, we extract textual intelligence related to emissions and pollution from leading firms involving supply chain management. We find that although decarbonization related discussions are at bare minimum in terms of the proportion of discussions within the supply chain context, the overall emotion of tweets indicate fear across all three timelines. Moreover, it was surprising to note that although pollution levels came down due to low economic activity during pandemic, we found more discussions during COVID in comparison to pre-COVID times. Pollution and waste caused by plastics, fuel consumption, reduction in greenhouse gas emission are some of the key topics that emerged during pandemic times. Our paper makes a modest contribution on the role of social media analytics within supply chain context around COVID-19.

Open Access: Yes

DOI: 10.1007/s10479-023-05806-4

Work from home practices as corporate strategy- an integrative review

Publication Name: Heliyon

Publication Date: 2023-09-01

Volume: 9

Issue: 9

Page Range: Unknown

Description:

The Covid 19 pandemic led to major changes at the individual, organisational and institutional levels of policy, productive functions, and organising. During Covid 19 morbidity, public institutions enforced social isolation, mandatory self-isolation, quarantines, and administrative regulatory lockdowns, which led to a movement away from the physical, material world and into an all-consuming digital universe. With growing interest in work-from-home (WFH) opportunities, this article provides an integrative review of 107 papers. It comprises the bibliometric analysis and manual review of the articles, on the basis of which we present an elaborative discussion and agenda for future research. According to the analysis, WFH looks a tad of a double-edged sword in that it may have major but unintended repercussions for institutions, and organizations as well as hidden, positive as well as negative consequences for individuals/employees. One of the significant insight from our analysis was the absence of HR function's strategic or operational input or oversight during corporate WFH strategies. We suggest several theoretical frameworks for further developing, theorizing, and empirically testing various aspects of WFH. Further, we recognise that WFH is becoming increasingly visible as a result of the pandemic scenario and significant technical advancements, which must be reflected in the research. Finally, because WFH represents a significant disruption in how organizations produce work and manage it, we propose employee and managerial consequences as future research agendas.

Open Access: Yes

DOI: 10.1016/j.heliyon.2023.e19894

What do we learn from Nexus between trade diversification and structural change: informing the future about climate action and Sustainability

Publication Name: Environmental Science and Pollution Research

Publication Date: 2023-08-01

Volume: 30

Issue: 40

Page Range: 92162-92181

Description:

Economic complexity is considered key a driver of social change, structural change, and economic development. Economic complexity is mostly used to capture issues apropos product diversification of exports, trade, technological innovation, human knowledge, and skills. The current study has conducted a detailed bibliometric review of economic complexity, export quality, and trade diversification. In doing so, the authors used the literature up to 2021 to unveil economic complexity’s contextual information that witnessed structural change, social change, and trade indicators. The current study is the first integrative review to report the theoretical contribution, future research agendas, and thematic analysis of economic complexity, export quality, and export diversification. Our study, on the subject of economic complexity, export diversification, and import diversification in the period from 1966 to 2021, was carried out by systematically scanning 386 documents, and it is one of the pioneering studies in this field. In addition, economic diversity, development, and economic complexity; export diversification, import diversification, trade openness, and economic growth; energy, environmental Kuznets curve, and economic complexity; and sustainability and economic diversification are the four main research topics of the study. The findings are discussed apropos of economic complexity and exports, methodological aspects of economic complexity, and environmental issues nexus with economic complexity. The current study reports novel findings toward a path for achieving SDG-9 (industry and innovation) and SDG-13 (climate action). The biometric review enables researchers and policymakers to understand export quality, economic complexity, and the trade nexus and report future research directions for achieving sustainable growth in industries and innovation.

Open Access: Yes

DOI: 10.1007/s11356-023-28770-9

Unveiling temporal and frequency spillovers: Climate-risk indices and energy futures markets

Publication Name: Journal of Environmental Management

Publication Date: 2025-12-01

Volume: 395

Issue: Unknown

Page Range: Unknown

Description:

This study investigates the time- and frequency-domain spillover dynamics between climate-risk indices, namely the Transition Risk Index (TRI), Physical Risk Index (PRI), Global Climate Policy Uncertainty (GCPU))and major energy futures markets, including ICE Europe Brent crude oil futures (continuation), the global crude benchmark (Brent), ICE Europe Low Sulphur Gasoil futures, a European middle-distillate benchmark (Gasoil), Intercontinental Exchange (ICE) Abu Dhabi Murban crude oil futures (continuation), a Middle Eastern light-sweet benchmark (Murban), Shanghai Crude, New York Harbor Ultra-Low Sulphur Diesel futures (NYMEX) continuation (ULSD), and West Texas Intermediate crude oil futures (NYMEX Light Sweet Crude Oil futures continuation) (WTI). Employing a flexible econometric framework based on TVP-VAR and quantile connectedness, the analysis uncovers non-linear, asymmetric, and time-varying spillovers, with markedly stronger linkages during extreme market conditions and in the short term. Energy commodities, particularly Gasoil and WTI, emerge as significant net transmitters of transition risks, amplifying volatility during periods of stress, while long-term spillovers remain relatively weak, reflecting gradual decarbonization trends. The unique contribution of this paper lies in extending the Arbitrage Pricing Theory (APT) by integrating climate risks as dynamic, state-dependent, and non-diversifiable factors, thereby demonstrating how energy asset sensitivities fluctuate across regimes and quantiles. This approach advances the asset pricing and climate finance literature beyond static models by embedding dynamic connectedness into risk transmission analysis. The findings highlight the systemic nature of climate risks and underscore the importance of adaptive financial regulation, forward-looking climate policy, and flexible risk management practices to mitigate volatility and support the global energy transition. These insights provide actionable guidance for policymakers, regulators, and investors navigating the evolving interplay between climate risks and energy markets.

Open Access: Yes

DOI: 10.1016/j.jenvman.2025.127847

US financial stress, regional spillovers, and global economic policy uncertainty

Publication Name: Finance Research Letters

Publication Date: 2026-02-01

Volume: 89

Issue: Unknown

Page Range: Unknown

Description:

We study how financial stress originating in the United States (US), Advanced Economies (ADV), and Emerging Markets (EM) relates to movements in Economic Policy Uncertainty (EPU). Using monthly data for 2000-2024, we estimate horizon-specific responses to ΔEPU to one-standard-deviation innovations in ΔFinancial Stress Index (FSI) via Jordà (2005) local projections with four lags and standard controls ΔBloomberg Commodity Index (BCOM), ΔFederal Funds Rate (FEDFUNDS), ΔU.S. Dollar Index (DollarIdx), ΔCBOE Volatility Index (VIX). Across regions, the impact coefficient is negative,indicating that stress shocks are associated with an immediate reduction in the month-over-month change of EPU. Beyond impact, responses are small in magnitude, yielding limited persistence; cumulative effects over six months are modest and typically encompassed by wide confidence bands. Taken together, the evidence suggests that policy-uncertainty index adjusts quickly to stress realizations, with little systematic propagation at monthly horizons. This transience is most consistent with information/communication channels whereby policy guidance and rapid market repricing compress subsequent uncertainty innovations, while allowing for regional heterogeneity.

Open Access: Yes

DOI: 10.1016/j.frl.2025.109168

Economic sustainability and institutional quality in the green energy transition: Evidence from developing economies

Publication Name: International Economics

Publication Date: 2026-03-01

Volume: 185

Issue: Unknown

Page Range: Unknown

Description:

This study examines whether renewable energy adoption unconditionally contributes to economic outcomes in developing countries, or whether it can, under certain institutional conditions, impede economic progress. Analyzing panel data from 45 developing countries (2000–2020) using Driscoll–Kraay standard errors, we find a statistically significant negative association between an increasing renewable energy share and both GDP growth and GDP per capita. Crucially, institutional quality plays a pivotal moderating role. While stronger institutions, such as control of corruption and rule of law, mitigate negative impacts on per capita income and employment, they paradoxically appear to exacerbate the negative effect on overall GDP growth, suggesting a more transparent internalization of transition costs in better-governed environments. Furthermore, our findings demonstrate significant heterogeneity across income levels: low-income countries experience positive economic effects from renewable energy adoption, whereas lower-middle-income countries face more pronounced negative impacts. These results challenge the uniformly positive narrative of green growth, underscoring that the energy transition involves significant economic trade-offs critically dependent on a nation's institutional framework and developmental stage. Policymakers must adopt context-specific strategies to navigate these complexities effectively.

Open Access: Yes

DOI: 10.1016/j.inteco.2025.100669

Climate risk spillovers and financial tail-events: Evidence from quantile analysis

Publication Name: Research in International Business and Finance

Publication Date: 2026-05-01

Volume: 85

Issue: Unknown

Page Range: Unknown

Description:

This study investigates the dynamic and asymmetric connectedness between four crude oil benchmarks (Brent, WTI, INE, Murban) and three climate risk indexes (Physical Risk Index, Transition Risk Index, and U.S. Climate Policy Uncertainty Index). Addressing a critical gap in the literature, which often relies on linear models and average connectedness, we employ the quantile-on-quantile connectedness method to capture non-linear, asymmetric, and state-dependent spillovers, particularly under extreme market conditions. Our analysis reveals that climate risk indexes are predominantly net receivers of shocks from oil markets, with connectedness intensifying sharply during periods of market stress, political conflict, or sudden climate events. The findings highlight that systemic risk is significantly elevated at extreme quantiles, demonstrating that linear models may substantially underestimate true systemic risk during critical junctures. Methodologically, this research demonstrates the efficacy of quantile-on-quantile connectedness in revealing tail-risk effects. Empirically, it provides the most comprehensive comparison to date of connectedness across diverse crude oil benchmarks and climate risk indexes. The results offer crucial insights for investors seeking resilient portfolios, and for policymakers and regulators in designing macro-prudential oversight frameworks that recognize the non-linear and state-dependent nature of climate-financial contagion, emphasizing the need for flexible policies and continuous monitoring.

Open Access: Yes

DOI: 10.1016/j.ribaf.2026.103337

Energy poverty dynamics and geostrategic shocks: Moderation of financial markets

Publication Name: Energy Policy

Publication Date: 2026-08-01

Volume: 215

Issue: Unknown

Page Range: Unknown

Description:

Universal energy poverty is a key ingredient to social inequality, education barrier and poor health outcome. Therefore, it is crucial for policymakers to identify the factors that mitigates energy poverty. Present study examined the influence of geopolitical risk on energy poverty, focusing on financial market depth, access and efficiency in 42 economies, spanning 2000 to 2022, using instrument variable two stage least square (2SLS), three stage least square (3SLS) approach and double panel threshold regression. The estimation provides following observations. First, geopolitical risk significantly intensify energy poverty over time. Second, natural disasters is a more serious hindrance to energy access. Third, financial markets significantly moderates the favourable spillover effects of geopolitical risk on energy poverty, dampens negative effect of geopolitical risk, improving household energy access, and reducing vulnerability to external shocks. Alongside this, the research provide similar pattern in urban and rural concentration, indicating the severe effect of geopolitical and natural disaster risk in rural areas. Moreover, the research explored several other factors and prioritizes digitalization, economic growth and political liberty as the major attributes for mitigating energy poverty. Hence, this research, provides stronger support for the roles of financial markets and digitalization in mitigating the energy poverty in the long run. This paper further delves into the policy implications arising from the findings.

Open Access: Yes

DOI: 10.1016/j.enpol.2026.115278

Pricing sustainability risk: Climate policy uncertainty and energy market dynamics

Publication Name: Development and Sustainability in Economics and Finance

Publication Date: 2026-06-01

Volume: 10

Issue: Unknown

Page Range: Unknown

Description:

This study investigates the dynamic temporal relationship between climate policy uncertainty (CPU) and international energy prices across nine commodities from January 1992 to June 2024. The research examines whether CPU systematically drives energy price movements and how these relationships evolve over time. We employ dynamic time warping (DTW), a nonparametric pattern recognition technique that accommodates non-linear temporal alignments between time series. Unlike conventional econometric methods that impose fixed lag structures, DTW flexibly maps how CPU influences on energy prices evolve across different periods. We analyse crude oil (WTI and Brent), gasoline, heating oil, coal, liquefied natural gas, natural gas, palm oil, and sunflower oil using multiple DTW step patterns (Rabiner–Juang VI-c, Symmetric1) with Sakoe–Chiba window constraints. Lead–lag analysis quantifies quarterly shifts in temporal precedence between CPU and energy prices. Energy prices demonstrate increasing sensitivity to CPU, particularly after the early 2000s. Traditional fossil fuels show pronounced alignment with CPU during major policy shifts, including the post-2008 financial crisis and 2015 Paris Agreement. CPU often leads energy price movements during regulatory transitions, suggesting markets price anticipated policy risks. Recent years reveal temporal reversals: natural gas and coal prices increasingly lead CPU, indicating market dynamics now drive subsequent policy adjustments as energy transitions accelerate. This research introduces sophisticated temporal analysis using DTW and lead–lag methods to explore evolving CPU-energy price relationships. The study provides fresh insights into how climate-related regulations drive energy market volatility during transitions toward sustainable energy systems, with implications for portfolio management and regulatory design.

Open Access: Yes

DOI: 10.1016/j.dsef.2026.100140