Advancing environmental sustainability in the G-7: The impact of the digital economy, technological innovation, and financial accessibility using panel ARDL approach

Journal of Economy and Technology, Год журнала: 2024, Номер unknown

Опубликована: Июнь 1, 2024

This study examines the impact of digital economy, technological innovation, financial accessibility, and urbanization on CO2 emissions in G-7 region from 1990 to 2019. The analysis employed Cross-Sectional Dependence (CSD) Slope Homogeneity tests, revealing presence CSD issues heterogeneous slope coefficients. First- second-generation panel unit root tests indicated no problem within dataset, with variables showing mixed integration orders. Panel cointegration confirmed that are cointegrated over long run. To assess short-run long-run impacts explanatory emissions, utilized Autoregressive Distributed Lag (ARDL) model. findings indicate economy significantly reduces while economic growth, increase region. robustness ARDL results was validated using Driscoll-Kraay standard errors, Augmented Mean Group (AMG), Common Correlated Effects (CCEMG) estimations. Additionally, Dumitrescu-Hurlin causality test revealed a unidirectional causal relationship between GDP innovation. Furthermore, bidirectional found accessibility as well emissions. These provide comprehensive insights into dynamic interactions economic, technological, environmental region, highlighting complexity achieving sustainable development.

Язык: Английский

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Digital technology innovation and corporate resilience

Global Finance Journal, Год журнала: 2024, Номер unknown, С. 101042 - 101042

Опубликована: Сен. 1, 2024

Язык: Английский

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Analyzing How AI impact Environmental Sustainability: Case Study for USA

Research Square (Research Square), Год журнала: 2025, Номер unknown

Опубликована: Фев. 5, 2025

This study investigates the role of private investment in Artificial Intelligence (AI) promoting environmental sustainability United States from 1990 to 2019. It also analyzes impact financial globalization, technological innovation, and urbanization by testing Load Capacity Curve (LCC) hypothesis. The employs stationarity tests, which indicate that variables are free unit root problems exhibit mixed orders integration. Using Autoregressive Distributive Lag (ARDL) Model bound test, finds cointegrated long run. short-run long-run estimations ARDL model confirm existence LCC hypothesis States, revealing a U-shaped relationship between income load capacity factor. results show AI has significant positive correlation with factor, thus sustainability. Conversely, innovation globalization negative factor both short To validate estimation approach, Fully Modified OLS, Dynamic Canonical Correlation Regression methods, all support results. Additionally, Granger Causality test reveals unidirectional causal AI, economic growth,

Язык: Английский

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Bringing Climate Action Into Perspective: Do the Engagements of Green Energy, Technological Innovation, and Tourism Matter in the Post‐COP27 Era?

Natural Resources Forum, Год журнала: 2025, Номер unknown

Опубликована: Фев. 27, 2025

ABSTRACT This study examines how green energy, technological innovation, and tourism affect the volatility of carbon dioxide emissions in global economy, considering role globalization, economic growth, population. uses STIRPAT framework based on 1995–2019 dataset. In addition, augmented mean group estimator, fully modified ordinary least squares, dynamic method moments quantile regression are employed to analyze stated model. The results reveal that variables interrelate long run. Moreover, positively drives surge greenhouse gas across quantiles, robustly long‐run estimates obtained from other estimators. Green energy significantly mitigates upper quantiles Other covariates meet expected signs. this context, heterogeneity conditional distribution CO 2 is unveiled throughout examined. Likewise, analysis makes it possible verify functional roles current future environmental degradation. From results, some policy implications derived so respective governments can consider them. These measures focus boosting renewable resources attain sustainability.

Язык: Английский

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Role of mineral resource rents, renewable energy, and energy efficiency toward carbon neutrality in China

Energy Nexus, Год журнала: 2025, Номер unknown, С. 100394 - 100394

Опубликована: Фев. 1, 2025

Язык: Английский

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Analyzing the Impact of Economic Growth, FDI and Energy Use on CO2 Emission in Kenya: An ARDL Approach

Research Square (Research Square), Год журнала: 2025, Номер unknown

Опубликована: Фев. 20, 2025

This study estimates the effects of Gross Domestic Product (GDP), population, renewable energy consumption, fossil fuels, and foreign direct investment (FDI) on Kenya's carbon emissions between 1972 2021. investigation makes use “Autoregressive Distributed Lag (ARDL)” method, which is grounded in theoretical framework as “Stochastic Impacts by Regression Population, Affluence, Technology” model known (STIRPAT) model. The ARDL bound test structural break were also used study. According to our preliminary results, data exhibits long-run cointegration; a result, uses ARDL, adept at handling both short- long-term effects, essential. lends credence earlier research demonstrating that rise GDP population can result an increase country's CO₂ emissions. Kenya may reduce its damaging dioxide transitioning sources. All place impacts growth parity. Achieving sustainable development goals will require substantial infrastructure, making this analysis potentially useful planning establishing strategies for future financial funding sector. For fuels are negative but insignificant. FDI has insignificant positive effect environment. Based these findings, policymakers make informed decisions energy.

Язык: Английский

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Quantile analysis of the role of renewable energy technology on carbon neutrality in organization for economic co-operation and development countries

International Journal of Energy Sector Management, Год журнала: 2025, Номер unknown

Опубликована: Март 25, 2025

Purpose This study aims to investigate the relatedness between renewable energy technology (RET) and carbon intensity among 36 Organization for Economic Co-operation Development (OECD) nations. Design/methodology/approach method allows them examine relationship RET across different quantiles of latter. Findings The findings reveal a negative association emission in OECD countries, indicating that these nations can reduce emissions by harnessing technologies. analysis shows substantial consistent effect on intensity. Furthermore, incorporation additional economic indicators, such as gross domestic product trade openness, enhances results emphasizes their importance modeling research underscores vital role accurately advocates development targeted policies maximize benefits Originality/value Prior studies often use pooled ordinary least squares methodology, which lead skewed due heterogeneous nature panel datasets. To address this issue, they quantile regression model assess impact within countries.

Язык: Английский

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Analyzing the Nexus between AI Innovation and Ecological Footprint in Nordic Region: Impact of Banking Development and Stock Market Capitalization using Panel ARDL method

Journal of Environmental Science and Economics, Год журнала: 2024, Номер 3(3), С. 41 - 68

Опубликована: Сен. 1, 2024

This study investigates the impact of Artificial Intelligence (AI) innovation on ecological footprint in Nordic region from 1990 to 2020, alongside effects banking development, stock market capitalization, economic growth, and urbanization. Utilizing STIRPAT model, incorporates cross-sectional dependence slope homogeneity tests, revealing issues heterogeneity dependence. The analysis employs both first second-generation panel unit root confirming that variables are free problems. Panel cointegration tests demonstrate cointegrated long run. To explore short- long-term relationships, utilizes Autoregressive Distributed Lag (ARDL) model. ARDL results indicate urbanization positively correlate with short Conversely, AI development negatively footprint. validate estimations, robustness checks performed using Fully Modified OLS, Dynamic Fixed Effects all which support initial findings. Furthermore, D-H causality test identify causal relationships. show a unidirectional relationship between innovation, urbanization, In contrast, bidirectional exists growth footprint, as well

Язык: Английский

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Leveraging AI for a Greener Future: Exploring the Economic and Financial Impacts on Sustainable Environment in the United States

Journal of Environmental Science and Economics, Год журнала: 2024, Номер 3(3), С. 1 - 30

Опубликована: Авг. 25, 2024

In response to increasing environmental challenges, the United States has deliberately adopted technical advancements promote sustainable development. This includes efforts decrease pollution, improve energy efficiency, and encourage use of environmentally friendly technology in different industries. study investigates role Artificial Intelligence (AI) promoting sustainability from 1990 2019. It also examines impacts financial development, ICT use, economic growth on Load Capacity Factor (LCF). Various unit root tests revealed no issues mixed integration orders among variables. The Autoregressive Distributive Lag (ARDL) model explored cointegration, indicating long-run relationships ARDL findings confirm Curve hypothesis for States, with AI positively correlating LCF both short long run. Conversely, development population significantly reduce LCF. Robustness checks using FMOLS, DOLS, CCR estimation approaches align results. Granger causality reveal unidirectional growth, AI, bidirectional between Diagnostic results are free heterogeneity, serial correlation, specification errors. underscores importance enhancing while highlighting adverse

Язык: Английский

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Determinants of environmental sustainability in the United States: analyzing the role of financial development and stock market capitalization using LCC framework

Discover Sustainability, Год журнала: 2024, Номер 5(1)

Опубликована: Окт. 10, 2024

This research investigates how the USA's load capacity factor (LCF) has been impacted by trade openness, financial development, stock market capitalization, and industrialization over period 1990–2022. study also tests "Load Capacity Curve (LCC)" hypothesis. Various unit root were conducted to determine stationarity of dataset, revealing that variables are free from problems exhibit mixed orders integration. The "Autoregressive Distributed Lag (ARDL)" bounds test confirmed co-integration among variables. results ARDL model validated existence LCC hypothesis in USA. findings demonstrated is positively correlated with LCF, whereas openness negatively LCF. To ensure robustness estimations, employed several regressions, all which validity results. Additionally, pairwise Granger causality revealed unidirectional causal relationships between GDP capitalization while no found development LCF advocate USA should advance eco-friendly industrial practices environmental sustainability, alongside regulated markets institutions mandate utilization green investments.

Язык: Английский

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