Browsing by Author "Tiwari, Aviral Kumar"

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A cross-quantile correlation and causality-in-quantile analysis on the relationship between green investments and energy commodities during the COVID-19 pandemic period
(Studies in Economics and Finance, 2024) Sharma, Aarzoo; Tiwari, Aviral Kumar; Abakah, Emmanuel Joel Aikins; Owusu, Freeman Brobbey
Purpose This paper aims to examine the cross-quantile correlation and causality-in-quantiles between green investments and energy commodities during the outbreak of COVID-19. To be specific, the authors aim to address the following questions: Is there any distributional predictability among green bonds and energy commodities during COVID-19? Is there exist any directional predictability between green investments and energy commodities during the global pandemic? Can green bonds hedge the risk of energy commodities during a period of the financial crisis. Design/methodology/approach The authors use the nonparametric causality in quantile and cross-quantilogram (CQ) correlation approaches as the estimation techniques to investigate the distributional and directional predictability between green investments and energy commodities respectively using daily spot prices from January 1, 2020, to March 26, 2021. The study uses daily closing price indices S&P Green Bond Index as a representative of the green bond market. In the case of energy commodities, the authors use S&P GSCI Natural Gas Spot, S&P GSCI Biofuel Spot, S&P GSCI Unleaded Gasoline Spot, S&P GSCI Gas Oil Spot, S&P GSCI Brent Crude Spot, S&P GSCI WTI, OPEC Oil Basket Price, Crude Oil Oman, Crude Oil Dubai Cash, S&P GSCI Heating Oil Spot, S&P Global Clean Energy, US Gulf Coast Kerosene and Los Angeles Low Sulfur CARB Diesel Spot. Findings From the CQ correlation results, there exists an overall negative directional predictability between green bonds and natural gas. The authors find that the directional predictability between green bonds and S&P GSCI Biofuel Spot, S&P GSCI Gas Oil Spot, S&P GSCI Brent Crude Spot, S&P GSCI WTI Spot, OPEC Oil Basket Spot, Crude Oil Oman Spot, Crude Oil Dubai Cash Spot, S&P GSCI Heating Oil Spot, US Gulf Coast Kerosene-Type Jet Fuel Spot Price and Los Angeles Low Sulfur CARB Diesel Spot Price is negative during normal market conditions and positive during extreme market conditions. Results from the non-parametric causality in the quantile approach show strong evidence of asymmetry in causality across quantiles and strong variations across markets. Practical implications The quantile time-varying dependence and predictability results documented in this paper can help market participants with different investment targets and horizons adopt better hedging strategies and portfolio diversification to aid optimal policy measures during volatile market conditions. Social implications The outcome of this study will promote awareness regarding the environment and also increase investor’s participation in the green bond market. Further, it allows corporate institutions to fulfill their social commitment through the issuance of green bonds. Originality/value This paper differs from these previous studies in several aspects. First, the authors have included a wide range of energy commodities, comprising three green bond indices and 14 energy commodity indices. Second, the authors have explored the dependency between the two markets, particularly during COVID-19 pandemic. Third, the authors have applied CQ and causality-in-quantile methods on the given data set. Since the market of green and sustainable finance is growing drastically and the world is transmitting toward environment-friendly practices, it is essential and vital to understand the impact of green bonds on other financial markets. In this regard, the study contributes to the literature by documenting an in-depth connectedness between green bonds and crude oil, natural gas, petrol, kerosene, diesel, crude, heating oil, biofuels and other energy commodities.
Analyzing the static and dynamic dependence among green investments, carbon markets, financial markets and commodity markets
(International Journal of Managerial Finance, 2025-01-17) Abakah, Emmanuel Joel Aikins; Tiwari, Aviral Kumar; Oliyide, Johnson Ayobami; Appiah, Kingsley Opoku
Purpose This paper investigates the static and dynamic directional return spillovers and dependence among green investments, carbon markets, financial markets and commodity markets from January 2013 to September 2020. Design/methodology/approach This study employed both the quantile vector autoregression (QVAR) and time-varying parameter VAR (TVP-VAR) technique to examine the magnitude of static and dynamic directional spillovers and dependence of markets. Findings Results show that the magnitude of connectedness is extremely higher at quantile levels (q = 0.05 and q = 0.95) compared to those in the mean of the conditional distribution. This connotes that connectedness between green bonds and other assets increases with shock size for both negative and positive shocks. This further indicates that return shocks spread at a higher magnitude during extreme market conditions relative to normal periods. Additional analyses show the behavior of return transmission between green bond and other assets is asymmetric. Practical implications The findings of this study offer significant implications for portfolio investors, policymakers, regulatory authorities and investment community in terms of carefully assessing the unique characteristics offered by each markets in terms of return spillovers and dependence and diversifying the portfolios. Originality/value The study, first, uses a relatively new statistical technique, the QVAR advanced by Ando et al. (2018), to capture upper and lower tails’ quantile price connectedness and directional spillover. Therefore, the results possess adequate power against departure from mean-based conditional connectedness. Second, using a portfolio of green investments, carbon markets, financial markets and commodity markets, the uniqueness of this study lies in the examination of the static and dynamic dependence of the markets examined.
Analyzing time-varying tail dependence between leveraged loan and debt markets in the U.S. economy
(International Review of Finance, 2024-06) Tiwari, Aviral Kumar; Trabelsi, Nader; Abakah, Emmanuel Joel Aikins; Lee, Chi-Chuan
This study analyzes the time-varying dependence between U.S. leveraged loan and debt markets within a highly linked financial system using a quantile-based time-varying connectedness framework to determine the hedging benefits of leveraged loans for financial investors at various quantiles. Based on daily closing price data from November 28, 2008 to October 3, 2023, the evidence demonstrates considerable (moderate) spillovers across the leveraged loan and debt markets for severe (normal) occurrences, with additional results indicating symmetric interaction. In terms of risk spillover, we also affirm the dominance of short-term fixed-income instruments over leveraged loans and long-term bonds. These findings indicate that no hedging or diversification occurred among the investigated markets.
Assessing the impact of renewable energy and non-renewable energy use on carbon emissions: evidence from select developing and developed countries
(Environment, Development and Sustainability, 2025-02) Rai, Pratibha; Gupta, Priya; Saini, Neha; Tiwari, Aviral Kumar
Renewable Energy (RE) is essential for balancing economic and environmental conditions to attain Sustainable Development Goals (SDGs). This paper investigates the relationship between carbon emissions (CO2) and RE use, considering Non-renewable Energy (NRE) and macroeconomic variables such as Foreign Direct Investment, Gross Domestic Product, and Trade in eight major polluting nations from 1990 to 2019, constrained by data idiosyncratic features. The Error Correction Model using Autoregressive Distributed Lag methodology reveals that RE effectively lowers carbon emissions on average, but high economic growth and NRE use significantly contribute to environmental degradation. Additionally, while a reduction in CO2 emissions with RE use is evident through panel data analysis using the random-effect model. However, country-wise and panel data analyses do not substantiate the Environmental Kuznets Curve (EKC) hypothesis. The study confirms a long-run cointegrated relationship among the variables. It highlights the necessity for tailored energy innovations, as the weak validation of the overemphasized EKC hypothesis indicates that a generic solution is only sometimes applicable for mitigating emissions that facilitate the achievement of SDGs. This inquiry contributes to the extant literature by providing a nuanced understanding of the associations amongst macroeconomic variables, renewable and non-renewable energy consumption, and carbon emissions and offers critical insights for policy formulation. The requirement of indispensable energy innovations to achieve SDGs is emphasized. It is necessary to decrease the share of NRE use in total energy consumption and to increase the percentage share of RE use.
Asymmetric spillover effects in energy markets
(International Review of Economics & Finance, 2024-04) Tiwari, Aviral Kumar; Abakah, Emmanuel Joel Aikins; Doğan, Buhari; Adekoya, Oluwasegun B.; Wohar, Mark
This paper explores the asymmetric relationship between clean and dirty energy markets. The study uses the time-varying and frequency-domain spillover approaches, while accounting for asymmetries. We use natural gas, gasoline, gas oil, heating oil, crude oil, coal, petroleum, kerosene, propane, and diesel to denote dirty energy markets and wind, solar and clean energy markets to denote clean energy markets. We use daily data running from May 18, 2011, to August 12, 2020. According to the results obtained, good news in fluctuations in global energy market indices increases the integration of international energy markets in the long run compared to bad news. Our result show that transmission of good and bad volatilities in global energy market indices are dispersed with different time-varying intensities. Empirical evidence further reveals that good news increases integration of international energy markets in the long run compared to bad news. Additionally, markets transmit more bad volatility on average than good volatility during global events. According to the results of the research, we foresee that portfolio managers and investors may experience difficulties in diversifying opportunities in financial volatility periods in the short term. Overall, our findings reveal asymmetric risk effects in investment opportunities between clean and dirty energy. As a result of this information, investors can diversify their investments in the clean energy sector in the long term by using the asymmetry in good and bad fluctuations.
Asymmetry in returns and volatility between green financial assets, sustainable investments, clean energy, and international stock markets
(Research in International Business and Finance, 2025-01) Doğan, Buhari; Jabeur, Sami Ben; Tiwari, Aviral Kumar; Abakah, Emmanuel Joel Aikins
This paper presents empirical evidence on the asymmetric relationship between green investments and international stock markets. We employ the asymmetric versions of Diebold and Yilmaz (2012) and Barunik and Krehlik (2018) for time-frequency connectedness, analyzing daily returns and volatilities from June 23, 2009, to June 23, 2022. Our study reveals significant time-frequency asymmetries in returns and volatility spillovers between green investments and developed equity markets in the short and long term. Regarding net directional spillovers, the equity markets in the United States, the United Kingdom, Italy, Germany, and France emerge as net transmitters of shocks. In contrast, green investments, notably those in sustainability and the environment, act primarily as net emitters of shocks. China and Japan are the primary recipients of these shocks. Meanwhile, green bonds generally function as net receivers of shocks, with occasional exceptions.
Carbon neutrality: Synergy for energy transition, circular economy and inclusive green growth
(Journal of Environmental Management, 2025-02) Shobande, Olatunji A.; Ogbeifun, Lawrence; Tiwari, Aviral Kumar
The relentless surge in carbon emissions is exacting a devastating toll on human wellbeing, critical infrastructure, and natural ecosystems, leaving a stark and distressing legacy of destruction. Communities worldwide are reeling from the impacts of pervasive smog, record-breaking wildfires, and deadly heatwaves—manifestations of a climate crisis that grows more severe by the day. Once a vanguard of environmental policy, the Organisation for Economic Co-operation and Development (OECD) now struggles with exceeding emissions targets, eroding its credibility and influence. Fragmented implementation of key frameworks—such as Inclusive Green Growth, the Circular Economy, and Energy Transition—has undermined their impact. The urgency of the moment was underscored by the report of COP29, which issued an unequivocal call to action for OECD nations to step up and lead with ambitious, unified strategies. Embracing inclusive green growth (IGG)—a paradigm that harmonizes economic development with environmental sustainability and social equity—offers a clear path forward. By integrating these elements into a cohesive response, the OECD can reignite its leadership role and drive meaningful progress toward a sustainable future. This paper advocates for a unified strategy integrating IGG, CE, and ET to achieve carbon neutrality. It introduces a streamlined environmental model designed to assess the effectiveness of this integrated approach rigorously. Drawing on data from 24 countries between 2000 and 2020, and employing advanced time series and dynamic analysis, this study offers theoretical and empirical insights into the interactions among the key variables. The results show that integrated policies significantly enhance the effectiveness of green growth and energy transitions, ensuring equitable benefits across all societal segments, including marginalized communities. By addressing the complex, interrelated nature of sustainability challenges, these policies offer a robust framework consolidating diverse perspectives and expertise, driving transformative and profound change.
Corporate sustainability practices: An interplay of uncertainty, geopolitical risk and competition
(Journal of Environmental Management, 2025-03) Bhue, Rajesh; Gartia, Umakanta; Panda, Ajaya Kumar; Tiwari, Aviral Kumar
The present study analyses the interplay between uncertainty and sustainability investment in the line of PMC (product market competition), and its impact on the firms' sustainable practices. Based on a sample of 2533 listed companies from 2011 to 2023, it was observed that uncertainty positively influences sustainable investment, and the PMC plays a moderating role in the case of G-20 countries. Furthermore, the research indicates that sustainable investment promotes long-term investment in G-20 countries during the study period and lessens the unfavorable outcome of uncertainty on a firm's value. We employed SGMM (System-generalized method of moments) to concern about the endogeneity issues and for robustness, which was consistent with the empirical results. The study's implications help investors, managers, and policymakers integrate sustainable investment practices with uncertainty alongside pushing sustainable development goals.
Crude oil Price forecasting: Leveraging machine learning for global economic stability, Technological Forecasting and Social Change,
(Technological Forecasting and Social Change, 2025-07) Rao, Amar; Sharma, Gagan Deep; Tiwari, Aviral Kumar; Hossain, Mohammad Razib; Dev, Dhairya
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.
Decoding mood of the Twitterverse on ESG investing: opinion mining and key themes using machine learning
(Management Research Review, 2024-07) Jaiswal, Rachana; Gupta, Shashank; Tiwari, Aviral Kumar
Purpose Grounded in the stakeholder theory and signaling theory, this study aims to broaden the research agenda on environmental, social and governance (ESG) investing by uncovering public sentiments and key themes using Twitter data spanning from 2009 to 2022. Design/methodology/approach Using various machine learning models for text tonality analysis and topic modeling, this research scrutinizes 1,842,985 Twitter texts to extract prevalent ESG investing trends and gauge their sentiment. Findings Gibbs Sampling Dirichlet Multinomial Mixture emerges as the optimal topic modeling method, unveiling significant topics such as “Physical risk of climate change,” “Employee Health, Safety and well-being” and “Water management and Scarcity.” RoBERTa, an attention-based model, outperforms other machine learning models in sentiment analysis, revealing a predominantly positive shift in public sentiment toward ESG investing over the past five years. Research limitations/implications This study establishes a framework for sentiment analysis and topic modeling on alternative data, offering a foundation for future research. Prospective studies can enhance insights by incorporating data from additional social media platforms like LinkedIn and Facebook. Practical implications Leveraging unstructured data on ESG from platforms like Twitter provides a novel avenue to capture company-related information, supplementing traditional self-reported sustainability disclosures. This approach opens new possibilities for understanding a company’s ESG standing. Social implications By shedding light on public perceptions of ESG investing, this research uncovers influential factors that often elude traditional corporate reporting. The findings empower both investors and the general public, aiding managers in refining ESG and management strategies. Originality/value This study marks a groundbreaking contribution to scholarly exploration, to the best of the authors’ knowledge, by being the first to analyze unstructured Twitter data in the context of ESG investing, offering unique insights and advancing the understanding of this emerging field.
Do Environmental, Social, and Governance (ESG) practices help mitigate bank default risk?
(Journal of Environmental Management, 2025-04) Biswas, Abhijit; Das, Arindam; Tiwari, Aviral Kumar; Patro, Archana
The study aims to investigate the ESG practices and bank default risk nexus in India, considering both short-term and long-term perspectives. Employing panel data covering 27 Indian banks spanning from 2012–13 to 2021–2022, the research utilizes the two-step ‘system GMM’ approach to examine the nexus above. A bank's ESG practices are found to be associated negatively with its default risk. This association holds for individual pillars of ESG, except for the environmental pillar. Notably, no evidence supports reverse causality, indicating that a bank's default risk does not appear to impact its ESG practices. The findings align with the hypothesis that ESG practices help mitigate default risk in banks. Embracing this hypothesis could provide policymakers and regulators with a foundation for influencing banks to integrate ESG practices into their operational frameworks more extensively. The consistent sign of coefficients for the ESG variables across short-run and long-run periods suggests stability in the relationship between ESG variables and bank default risk. However, the long-run coefficients exert a more substantial impact than their short-run counterparts. Therefore, strategically adopting ESG practices can fetch a competitive advantage by reducing default risk for banks, especially over the long term. Given the time required for ESG initiatives to yield results, evaluating their impact on bank default risk is most effectively accomplished with a focus on the long term. Among the ESG pillars, the Governance (G) pillar exhibits the most potent negative impact. In contrast, the Environment (E) pillar demonstrates the mildest negative effect on bank default risk in both short-run and long-run contexts. These outcomes are expected as governance significantly influences a bank's risk-taking behaviour, while the direct environmental impacts of banking activities tend to be relatively limited.
Does financial development support renewable energy consumption: Evidence from the UK
(Renewable Energy, 2025-04-15) Demirtas, Cuma; Tiwari, Aviral Kumar; Soyu Yıldırım, Esra
This study explores the effects of financial development on the use of renewable energy (RE) in the United Kingdom (UK) between 1980 and 2020, by taking control variables such as urbanization and economic growth into account. For this purpose, wavelet transforms and the fresh Fourier quantile causality test are employed. Our empirical findings demonstrate that both immediately and over time, the use of renewable energy (REC) is stimulated by financial development. Additionally, financial institutions' efficiency and market depth play a significant role in encouraging the REC. In line with the study's general conclusions, it is suggested that the UK should implement policies that increase the spread and effectiveness of financial institutions and financial markets in order to support environmental quality. By using novel approaches, the study investigates the effects of six sub-indicators, namely the effectiveness, depth, and accessibility of financial markets and institutions on the REC.
Does Water Stress Impact GDP Per Capita Growth in the Long Run: A Study of Highly Water-Stressed Nations Over the Period
(Springer Proceedings in Business and Economics, Financial Markets, Climate Risk and Renewables, 2024-12-15) Sharma,Jyoti; Tiwari, Aviral Kumar
Water scarcity is becoming a bigger issue worldwide, and how we manage water has become a major concern for governments in many countries because it is important for economic growth and societal stability. The purpose of this study is to analyse the effects of water stress on the gross domestic product per capita growth (GDPpcg) of the 16 highly water-stressed countries belonging to the Middle East and Africa over the period of 2001–2020. The study utilizes panel data approaches/methods such as pooled, fixed effect (FE), and random effect (RE). The overall empirical findings indicate that water stress and population growth are negatively associated with GDPpcg in these highly water-stressed nations. The total water productivity and annual freshwater withdrawals (billion cubic meters) are positively associated with the GDPpcg in these highly water-stressed nations. Results support the impact of demographic profiles, such as age distribution having a positive effect on GDPpcg, whereas, in FE estimation, population density has a negative impact on GDPpcg. This study comprehensively analyses the multifaceted relationship between water stress and GDP per capita growth. Policymakers may consider prioritizing investments in water-efficient technologies, infrastructure development, and agricultural practices to mitigate the adverse effects of water stress on economic growth.
Dynamics of the relationship between stock markets and exchange rates during quantitative easing and tightening
(Financial Innovation, 2025-01-06) Ahmadian-Yazdi, Farzaneh; Sokhanvar, Amin; Roudari, Soheil; Tiwari, Aviral Kumar
This study utilizes two complementary models, the Time-Varying Parameter Vector Autoregressive Diebold–Yilmaz (TVP-VAR-DY) and the Time-Varying Parameter Vector Autoregressive Baruník–Křehlík (TVP-VAR-BK), to investigate the dynamic volatility transmission between exchange rates and stock returns in major commodity-exporting and -importing countries. The analysis focuses on periods of quantitative easing (QE) and quantitative tightening (QT) from March 15, 2020 to December 30, 2022. The countries examined are Canada and Australia (major commodity exporters) and the UK and Germany (major commodity importers). An essential contribution of this paper is new empirical insights into the dynamics of stock market returns and the transmission of volatility between these markets and exchange rates during the QE and QT periods. The results reveal that causality primarily flows from stock markets to exchange rates, especially during the QT period across all investment horizons. The Toronto Stock Exchange (TSX) emerges as the principal net driver among the markets under study. Furthermore, the Canadian exchange rate (USDCAD) and the Australian Stock Exchange (ASX) are the most significantly affected indices within the network across various investment horizons (excluding the long-term). These findings underscore the importance for investors and policymakers to consider the interplay between exchange rates and stock market returns, particularly in the context of the QE and QT periods, as well as other economic, political, and health-related events. Our findings are relevant to various stakeholders, including governments, traders, portfolio managers, and multinationals.
Environmental, social and governance-type investing: a multi-stakeholder machine learning analysis
(Management Decision, 2025-03-26) Jaiswal, Rachana; Gupta, Shashank; Tiwari, Aviral Kumar
Purpose This research delves into the determinants influencing the adoption of environmental, social and governance (ESG) investing through an analysis of social media dialogs using the uses and gratification theory. Design/methodology/approach This study employs a mixed-methods approach, integrating sentiment analysis, topic modeling, clustering, causal loop analysis and ethnography to examine ESG-related content on social media. Analyzing social media data, study identified key themes and derived ten propositions about ESG investing. Industry professionals, financial advisors and investors further validated these findings through expert interviews. Combining data-driven analysis and qualitative insights provides a comprehensive understanding of how social media shapes investor preferences and decision-making in the ESG domain. Findings Environmental aspects, such as conservation, preservation of natural resources, renewable and clean energy, biodiversity, restoration and eco-friendly products and technologies, shape attitudes toward ESG investing. Social considerations, including inclusivity, diversity, social justice, human rights, stakeholder engagement, transparency, community development and philanthropy, significantly influence ESG investing sentiments. Governance elements such as transparency, accountability, ethical governance, compliance, risk management, regulatory compliance and responsible leadership also play a pivotal role in shaping ESG investing opinions. Practical implications This study presents actionable insights for policymakers and organizations by identifying key constructs in ESG investing and proposing an integrated framework that includes mediating factors like resource efficiency and stakeholder engagement alongside moderating elements such as regulatory environment and investor preferences. Policymakers should establish standardized ESG reporting frameworks, incentivize sustainable practices and use social media data for regulatory purposes. For businesses, integrating social media insights into decision-making can enhance ESG communication strategies and accountability. These measures will foster greater transparency, strengthen investor relations and contribute to a more sustainable and inclusive global economy. Originality/value To the authors' best knowledge, this is the first study to investigate improving ESG investing preferences based on big data mined from social media platforms.
Gasoline Prices and Presidential Approval Ratings of the United States
(American Politics Research, 2025-09) Gupta, Rangan; Pierdzioch, Christian; Tiwari, Aviral Kumar
We use random forests, a machine-learning technique, to formally examine the link between real gasoline prices and presidential approval ratings of the United States (US). Random forests make it possible to study this link in a completely data-driven way, such that nonlinearities in the data can easily be detected and a large number of control variables, in line with the extant literature, can be considered. Our empirical findings show that the link between real gasoline prices and the presidential approval ratings is indeed nonlinear, and that the former even has predictive value in an out-of-sample exercise for the latter. We argue that our findings are in line with the so-called pocketbook mechanism, which stipulates that the presidential approval ratings depend on gasoline prices because the latter have sizable impact on personal economic situations of voters
Geopolitical risk and real estate stock crash
(Finance Research Letters, 2025-06) Abakah, Emmanuel Joel Aikins; Abdullah, Mohammad; Akinsomi, Omokolade; Tiwari, Aviral Kumar
We investigate the effect of geopolitical risk (GPR) on real estate stock crashes while accounting for the impact of cash holdings and financial constraints in this relationship. Using a dataset from 28 countries covering the period of 2000 to 2023 from 1805 firms, we document that geopolitical risk increases real estate stock price crash risk. Our result remains consistent using an alternate proxy of geopolitical risk and even after considering endogeneity concerns using 2SLS and Entropy balanced samples. Our result shows the negative impact of GPR is stronger for firms with high cash holdings and high financial constraints.
How do economies decarbonize growth under finance-energy inequality? Global evidence
(Energy Economics, 2025-02) Tiwari, Aviral Kumar; Trinh, Hai Hong; Hong Vo, Diem Thi; Sharma, Gagan Deep
The study investigates the multidecade complexity between economic growth and carbon emissions across income groups and regions for 180 economies over the past decades. We find that the global economy has been decarbonizing its economic growth. The effects of growth on decarbonization are conditional on outcome distributions. The Paris Agreement (COP21) and renewable energy consumption (REC) are robust mechanisms toward green growth. Financial development (FD) presents its moderation to decarbonized growth. The study makes the following novel contributions to prior literature streams. First, complex GDP-CO2 nexuses are conditional on green factors and decarbonization is foremost for our global inclusive growth. Second, the friendliness of FD to the environment relies on green transition. It is worth noting that financial institutions and markets are exposed to climate risk drivers leading to our great challenge to promote green finance. Decarbonization is our global and constant efforts toward inclusive growth. Under finance-energy inequality, renewable energy capacity and finance are critical to decarbonized economic growth.
How do systematic risk spillovers reshape investment outcomes?
(Finance Research Letters, 2025-04) Tao, Miaomiao; Roubaud, David; Tiwari, Aviral Kumar; Silva, Emilson
We investigate the effects of domestic and cross-border systematic risk spillovers on corporate investment metrics, using stock indices comprising 212 energy firms across 36 countries, spanning July 1, 2009, to August 31, 2023, sourced from S&P Global Commodity Insights®. The two-layered network underscores the catastrophic consequences induced by the Russia–Ukraine conflict in Europe. Our regression results designate that systematic risk spillovers composed of domestic and cross-border risks hinder corporate real investments while encouraging new investments and diminishing inefficiencies. Yet geopolitical risk amplifies these risks, leading to broader disruptions in investment behaviors.
How do systematic risk spillovers reshape investment outcomes?
(Finance Research Letters, 2025-04) Tao, Miaomiao; Roubaud, David; Tiwari, Aviral Kumar; Silva, Emilson
We investigate the effects of domestic and cross-border systematic risk spillovers on corporate investment metrics, using stock indices comprising 212 energy firms across 36 countries, spanning July 1, 2009, to August 31, 2023, sourced from S&P Global Commodity Insights®. The two-layered network underscores the catastrophic consequences induced by the Russia–Ukraine conflict in Europe. Our regression results designate that systematic risk spillovers composed of domestic and cross-border risks hinder corporate real investments while encouraging new investments and diminishing inefficiencies. Yet geopolitical risk amplifies these risks, leading to broader disruptions in investment behaviors.