Econometric analysis of the effects of globalization, technology innovation and renewable energy consumption on CO2 emissions: Evidence from top five CO2-emitting countries

China is one of the largest emitters of carbon dioxide (CO2) emissions in the world. Therefore, it is essential to explore the determinants of CO2 emissions in China. But previous studies so far have not examined how the political risk of this country can affect its CO2 emissions due to the lack of a long-term dataset. Hence, this study aims to capture the effect of political risk on China's CO2 emissions while controlling renewable energy consumption, technological innovation, and the economy's economic growth. We employ Bayer and Hanck cointegration, FMOLS, DOLS, CCR, and frequency domain causality tests to establish the relationship among the variables mentioned above. The outcome of the study reveals that political stability is an important predictor of environmental degradation in China. Moreover, political stability is helpful to lower CO2 emissions, while technological innovation and renewable energy consumption can reduce CO2 emissions, economic growth further deteriorates environmental quality by increasing its carbon emissions. Therefore, the present study recommends that policymakers in China should control political tension in the country to control CO2 emissions and, at the same time, promote technological innovation and renewable energy consumption.

Environmental sustainability is an important issue for current scholars and policymakers in the East Asian and Pacific region. The causal and long-run effects of technological innovation, public–private partnership investment in energy, and renewable energy consumption on environmental sustainability in the East Asian and Pacific regions have not been comprehensively explored while taking into account the role of economic growth using quarterly data for the period 1992–2015. Therefore, the present study aims to close this literature gap using econometric approaches, namely Bayer–Hanck cointegration, autoregressive distributed lag (ARDL), dynamic ordinary least square (DOLS), and fully modified ordinary least square (FMOLS) tests. Furthermore, the study utilizes the frequency domain causality test to capture the causal impact of public–private partnership investment in energy, renewable energy consumption, technological innovation, and economic growth on CO2 emissions. The advantage of the frequency domain causality test is that it can capture the causality between short-term, medium-term, and long-term variables. The outcomes of the ARDL, FMOLS and DOLS show that renewable energy consumption and technological innovation mitigate CO2 emissions, while public–private partnership investment in energy and economic growth increase CO2 emissions. Moreover, the frequency causality test outcomes reveal that technological innovation, public–private partnership investment in energy, and renewable energy consumption cause CO2 emissions, particularly in the long-term. Thus, as a policy recommendation, the present study recommends promoting renewable energy consumption by focusing more on technological innovation in the East Asia and Pacific regions.

Carbon dioxide (CO2), whose atmospheric volume has been increasing, is the principal greenhouse gas (GHG) that causes global warming and climate change. Climate change from increasing greenhouse gases (GHGs) has broad health and environmental influences. Human-emitted GHGs constitute a significant cause of global warming. The main objective of this article is to assess the influence of technological innovation, economic growth, fossil energy use, renewable energy consumption, and globalisation on CO2 emissions (CO2Es) in South Africa over the observation period 1990–2020. The Dynamic Ordinary Least Squares (DOLS) estimator was implemented to examine the relationship between the constituents. The study results indicate that economic growth, fossil energy use, technological innovation, and globalisation boost CO2Es, whereas renewable energy consumption reduces CO2Es. The output of the canonical cointegrating regression and fully modified least squares estimators also supports the output of the DOLS estimator. We concluded that, in South Africa, a rise in economic growth, fossil energy use, technological innovation, and globalisation results in an upsurge in CO2Es. In contrast, an increase in renewable energy consumption leads to a reduction in CO2Es. This research work contributes to the discourse on CO2Es in the South African context. The study recommends that policymakers in South Africa should design policies that foster the formation of a low-carbon country, the consumption of renewable energy, and the implementation of environment-friendly technological innovations that reduce the use of fossil energy.Graphical

This study investigates whether technological innovation and the consumption of renewable energy tend to reduce the emissions of CO2 in the USA by analyzing datasets from January 2010 to May 2022. The main contribution to this study is that we applied a cross-quantile approach, which possesses several strengths compared to other methods used for directional predictability. The empirical results of this research can be concluded as three points: (1) both the consumption of renewable energy and technological innovation significantly and negatively impacted the emissions of CO2 in the short run (i.e., 1month) across high quantiles, which gradually diminished over time (i.e., 3months, 12months, and 24months), implying that technological innovation and the consumption of renewable energy possess a short-lived effect on CO2 emissions, respectively; (2) this relationship remains significant for causal links spanning 1 and 3months and 1 and 2years when the consumption of renewable energy and technological innovation are treated as control variables respectively; (3) a recursive cross-quantilogram was constructed to support further our findings, which showed that the consumption of renewable energy and technological innovation tend to negatively impact the emissions of CO2 across all quantiles. These results imply that an increase in the consumption of renewable energy and technological innovation can curb CO2 emissions in the USA; these effects tend to be more lasting when technological innovation and the consumption of renewable energy are combined. Therefore, future policies focused on curbing the emissions of CO2 should pay attention to the combined effect, which is the promotion of technological innovation and the exploitation of renewable energy sources in the USA.

PurposeThe purpose of this study is to investigate the nonlinear effects of renewable energy (RE) consumption and economic growth on per capita CO2 emissions during the time span from 1980 to 2020.Design/methodology/approachThe study uses the logistic smooth transition autoregression (STAR) model to decipher the nonlinear relationship between RE consumption, economic growth and CO2 emissions in the Indian economy.FindingsThe estimated results confirm a nonlinear relationship between India’s economic growth, RE consumption and CO2 emissions. The authors found that economic growth positively impacts CO2 emissions until it reaches a specific threshold of 1.81 (per capita growth). Beyond this point, further economic growth leads to a reduction in CO2 emissions. Similarly, RE consumption positively affects CO2 emissions until economic growth reaches the same threshold level, after which an increase in RE consumption negatively impacts CO2 emissions.Research limitations/implicationsThe study suggests that India should optimize the balance between economic growth and RE consumption to mitigate CO2 emissions. Policymakers should prioritize the adoption of RE during the early stages of economic growth. As economic growth reaches the specific threshold of 1.81 per capita, the economy should shift to more sustainable and energy-efficient practices to limit the effect of further CO2 emissions on further economic growth.Originality/valueTo the best of the authors’ knowledge, this study represents the first-ever endeavor to reexamine the nonlinear relationship between RE consumption, economic growth and CO2 emissions in India, using the STAR model.

In the past few decades, the tourism and hospitality sector has not only witnessed significant growth but also contributed tremendously to economic progress with lease inputs. This fastest-growing sector creates a number of environmental challenges, especially in emerging markets where the carbon footprint of tourism constitutes a large share of CO2 emissions. This study explores the effect of international tourism, renewable energy consumption (REN), and eco-friendly technology on CO2 emissions in emerging markets. The AMG, Driscoll-Kraay and Prais-Winsten regression confirm the adverse effects of international tourism on the environment, whereas technological innovation and REN mitigate CO2 emissions. Furthermore, economic growth and population increase CO2 emissions, while foreign direct investment (FDI) reduces CO2 emissions. Although the direct effect of technological innovation is insignificant, the indirect impact is negative and statistically significant; confirming the moderating effect of eco-friendly technology on the relationship between international tourism and CO2 emissions. The MMQR results suggest that REN reduces CO2 emissions across all quantiles. On the other hand, technological innovation significantly reduces CO2 emissions in lower and median quantiles, whereas international tourism and economic growth reduce CO2 emissions across all quantiles. Various directions of causality were reported alongside relevant policy directions.

PurposeThis study is intended to analyze the impact of information and communication technology (ICT) infrastructure, technological innovation, renewable energy consumption and financial development on carbon dioxide emissions in emerging economies.Design/methodology/approachThe present study adopts the autoregressive distributed lag (ARDL) cointegration technique for the annual data collection of Vietnam from 1990 to 2020.FindingsThe results of the study unveil that renewable energy consumption, the interaction between renewable energy consumption and ICT infrastructure and financial development have significant predictive power for carbon dioxide emissions. In the long term, renewable energy consumption, export and population growth reduce CO2 emissions, whereas the interaction between renewable energy consumption and ICT infrastructure and financial development increases CO2 emissions, while ICT infrastructure does not affect emissions. In the short run, changes in ICT infrastructure contribute to carbon dioxide emissions in Vietnam. In addition, changes in renewable energy consumption, financial development, the interaction between ICT infrastructure and renewable energy consumption and population growth have a significant effect on CO2 emissions. Notably, technological innovation has no impact on CO2 emissions in both the short and long run.Originality/valueThe current study provides new insights into the environmental effects of ICT infrastructure, technological innovation, renewable energy consumption and financial development. The interaction between renewable energy consumption and ICT infrastructure has a significant effect on carbon dioxide emissions. The paper suggests important implications for setting long-run policies to boost the effects of financial development, renewable energy consumption and ICT infrastructure on environmental quality in emerging countries like Vietnam in the coming time.

Purpose Climate change, driven by global warming, poses a significant threat to humanity and disrupts the ecological balance. In Europe, concentrations of air pollutants remain very high, and problems related to air quality and the acceleration of the phenomenon of global warming persist. As a result, carbon taxation has emerged as a key strategy to mitigate climate change. In Romania, environmental taxes are an important instrument of environmental policy as an economic instrument for environmental protection and natural resource management. Using 1990–2021 time series data and an Autoregressive Distributed Lag (ARDL) Bounds cointegration for long-run analysis and the Toda–Yamamoto test for causality analysis, we investigated whether environmental taxes, renewable energy consumption, urbanization and economic growth significantly impact CO2 emissions in Romania.Design/methodology/approachThis paper differs from the assessment of the Environmental Kuznets Curve (EKC) hypothesis (Grossman and Krueger 1991) and instead aims to determine the impact of environmental taxes, renewable energy consumption, per capita GDP and urbanization on CO2 emissions in Romania. The study investigates both short- and long-term effects, as well as Toda–Yamamoto causality linkages (Toda and Yamamoto 1995) between these variables. We adopt an ARDL estimation technique with Bound cointegration test and error correction models (Pesaran et al., 2001) to examine the short- and long-term effects.Findings The findings revealed that environmental taxes positively and significantly reduce CO2 emissions, while urbanization induces CO2 emissions, in the long run. Moreover, in the short run, environmental taxes and renewable energy consumption significantly reduce CO2 emissions while per capita GDP and urbanization significantly increase CO2 emissions. A unidirectional causality exists between renewable energy consumption and CO2 emissions. Thus, to realize its 34% target of renewable energy consumption in 2030, Romania should prioritize the implementation of the Casa Verde Plus program and enforce sustainable urban planning to meet near-zero energy standards. Consequently, the government should continue to enforce carbon taxes to promote environmental sustainability.Originality/value Empirical evidence supports the cointegration relationship between environmental taxes and CO2 emissions, with carbon taxes effectively reducing CO2 emissions and improving environmental quality (Allan et al., 2014; Polat and Polat, 2018; Kiuila et al., 2019, etc.). While existing research (Floros and Vlachou, 2005; Wissema and Dellink, 2007; Aydin and Esen, 2018; Lin and Li, 2011) primarily focuses on country-specific or regional analyses, limited research has been conducted on the impact of carbon taxation on CO2 emissions in Romania. However, to the best of our knowledge, limited research on this phenomenon in Romania exists in response to recommendations for climate change mitigation. Furthermore, urbanization has significantly contributed to rising atmospheric carbon levels and subsequent global warming and climate change (Woldu, 2021). As economic growth, particularly in countries like Romania, drives urbanization, it leads to increased energy demand, expanding urban areas and mounting environmental concerns. This process involves industrial restructuring, and the development of new infrastructure, all of which exert pressure on energy consumption and CO2 emissions (Niu and Lekse, 2018). While economic growth is a primary objective, industrialization and urbanization inevitably generate unintended consequences, including CO2 emissions. However, limited research exists on the impact of urbanization patterns on CO2 emissions in Romania. This study investigates the dynamic causal relationships among urbanization, per capita GDP, carbon taxes, renewable energy consumption and CO2 emissions, considering both short-run and long-run effects in Romania.

Symmetric and asymmetric impact of economic growth, capital formation, renewable and non-renewable energy consumption on environment in OECD countries

This study uses a comparative approach for comparing the nexus of economic growth, renewable and nonrenewable energy consumption, urbanization, trade, and CO2 emissions for South and East Asian countries from 2000 to 2018. The short- and long-run connections between the variables are explored using the dynamic common correlated effects (DCCE) CS-ARDL approach, and the causal linkages are assessed using the Dumitrescu-Hurlin (DH) panel causality test. The data show that the factors have long-term relationships. The findings show that nonrenewable energy consumption and economic growth increase long-term CO2 emissions in South Asia, but trade and use of renewable energy consumption reduce CO2 emissions in the short term. Long-term causal relationships between CO2 emissions, renewable energy use, economic growth, and trade are also revealed by the South Asian causality test. In East Asia, economic growth, NREC, trade, and urbanization increased CO2 emissions in the short and long run, while REC appears to reduce CO2 emissions. According to the causality analysis, long-run bidirectional causation exists between CO2 emissions, renewable energy use, economic growth, and trade. Furthermore, policy suggestions may be made, such as using renewable energy sources to lessen CO2 emissions and improving education and corruption to forecast economic growth in the examined areas.

PurposeThis study aims to examine the impact of logistics performance and technological innovation on environmental quality in Africa, focusing on carbon dioxide (CO2) emissions and renewable energy consumption as indicators of environmental quality.Design/methodology/approachThe study employs a panel data analysis of 43 African countries over the period 1990–2021. Data on logistics performance, technological innovation, CO2 emissions, and renewable energy consumption are sourced from the World Development Indicators database of the World Bank. Grounded in the Triple Bottom Line (TBL) framework, which integrates economic, social and environmental dimensions of sustainability, the analysis utilises the generalised method of moments (GMM) technique to address the issue of endogeneity.FindingsThe regression results reveal significant relationships between logistics performance, technological innovation and environmental quality indicators. Logistics performance demonstrates a negative impact on CO2 emissions, while technological innovation positively influences renewable energy consumption. The interactive effect of logistics performance and technological innovation mitigates CO2 emissions, aligning with the TBL framework’s environmental dimension by promoting sustainability. Furthermore, trade openness exhibits a significant negative effect on both CO2 emissions and renewable energy consumption. The findings highlight the potential synergies between logistics performance and technological innovation in driving environmental sustainability while offering economic benefits and addressing social well-being.Practical implicationsThe findings suggest the importance of prioritising investments in enhancing logistics performance and fostering technological innovation to achieve environmental sustainability goals in Africa.Originality/valueTo the best of the researchers’ knowledge, this study presents an initial attempt to examine the nexus between logistics performance and environmental quality in Africa using the logistics performance index. Furthermore, beyond assessing the individual effects of logistics performance and technological innovation on environmental quality, we delve into their interactive dynamics, adding novelty to the study.

This study aims to reveal the impact of renewable and non-renewable energy consumption on CO2 emissions in Türkiye and the potential to reach the CO2 emission level targeted in the 2030 Paris Agreement. In the first stage, the cointegration relationship was analyzed with the AARDL model approach using annual data for 1965-2022. According to the results of the analysis, in the long run, non-renewable energy consumption increases CO2 emissions, while renewable energy consumption decreases CO2 emissions. In the second phase of the research, three scenarios were prepared for each of renewable and non-renewable energy consumption. For nine scenarios, including combinations of these scenarios, CO2 emissions that may occur until 2030 were estimated using the econometric simulation method. According to the estimation results, the low non-renewable energy consumption and high renewable energy consumption scenario was determined as the scenario that can reduce CO2 emissions the most until 2030. However, even in this case, it is understood that more investment in renewable energy will be required since the 2030 CO2 emission reduction target will not be achieved. Therefore, policymakers need to enact policies to increase incentives for renewable energy generation in both the public and private sectors and take steps to improve the necessary infrastructure.

Environmental degradation poses a severe threat to life on earth. Similarly to other countries, emerging seven (E‐7) countries have been struggling to decrease their dependence on non‐renewable energy sources by adopting environment friendly technologies for reducing environmental deterioration and to achieve sustainable development goals (SDGs) of the United Nations. In present study, we reassessed the technological policies of E‐7 countries, and addressed the issues of affordable and clean energy, institutional quality (IQU), and sustained economic growth (EGR) to address the problem of environmental deterioration. For this purpose, we have investigated the role of renewable energy consumption (REC), technological innovations (TINs), IQU, and EGR on CO2 emissions (CE) by using the panel quantile regression (PQR) for the period from 1996 to 2020. The empirical outcomes of FGLS reveal that a 1% increase in REC, TIN, and IQU reduces the CE by 0.145%, 0.233%, and 0.249%, while a 1% rise in EGR and population (POPU) raises the CE by 0.993% and 1.546% respectively. Similarly, the results of PQR demonstrate that REC, TIN, and IQU reduce CE, whereas EGR and POPU increase environmental degradation. The impact of TIN on CE is high at lower quantiles and low at higher quantiles. The impact of IQU on CE is low at lower quantiles and high at higher quantiles Based on these findings, we have recommended a comprehensive SDG‐oriented policy framework, so that E‐7 countries can make progress towards achieving the objectives of SDG 16, SDG 13, SDG 7, SDG 8, and SDG 9.

This study examines the relationship between renewable and nuclear energy consumption, carbon dioxide emissions and economic growth by using the Granger causality and non-linear impulse response function in a business cycle in Spain. We estimate the threshold vector autoregression (TVAR) model on the basis of annual data from the period 1970–2018, which are disaggregated into quarterly data to obtain robust empirical results through avoiding a sample size problem. Our analysis reveals that economic growth and CO2 emissions are positively correlated during expansions but not during recessions. Moreover, we find that rising nuclear energy consumption leads to decreased CO2 emissions during expansions, while the impact of increasing renewable energy consumption on emissions is negative but insignificant. In addition, there is a positive feedback between nuclear energy consumption and economic growth, but unidirectional positive causality running from renewable energy consumption to economic growth in upturns. Our findings do indicate that both nuclear and renewable energy consumption contribute to a reduction in emissions; however, the rise in economic activity, leading to a greater increase in emissions, offsets this positive impact of green energy. Therefore, a decoupling of economic growth from CO2 emissions is not observed. These results demand some crucial changes in legislation targeted at reducing emissions, as green energy alone is insufficient to reach this goal.

Pathways to carbon neutrality in G7 economies: The role of technology-innovation and R&D in reducing CO2 emissions