Green innovation, resource price and carbon emissions during the COVID-19 times: New findings from wavelet local multiple correlation analysis

Shah, Muhammad Ibrahim; Foglia, Matteo; Shahzad, Umer; Fareed, Zeeshan

doi:10.1016/j.techfore.2022.121957

Cited by 41 publications

(15 citation statements)

References 57 publications

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“…In this paper, we use a more effective and innovative framework compared to those utilized in prior studies. While the investigations of (Wu et al, 2022), (Adebayo, 2022) and (Shah et al, 2022) the time-frequency nexus between CO 2 emissions, coal consumption, natural resource use, and economic expansion "dynamically" (i.e., over time) across various time periods. This approach enhances our capacity to comprehend the fundamental relationships between these indicators.…”

Section: Industrialization Brought On By Economic Expansion Acceleratesmentioning

confidence: 99%

“…In this paper, we use a more effective and innovative framework compared to those utilized in prior studies. While the investigations of (Wu et al, 2022), (Adebayo, 2022) and (Shah et al, 2022) implemented traditional wavelet tools, such as Multiple wavelet coherence (MWT), Wavelet coherence (WTC), Cross wavelet coherence (CWT), and Partial wavelet coherence (PWT), this paper employs an innovative technique known as WLMC. The WLMC is a potent method developed by (Polanco‐Martínez et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

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Trade‐off between environmental sustainability and economic growth through coal consumption and natural resources exploitation in China: New policy insights from wavelet local multiple correlation

Adebayo

2022

Geological Journal

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Challenges brought on by the rapid rate of economic growth include the depletion of natural resources (NAR) and environmental deterioration. Due to its abundant mineral resources and rapid economic growth, China has gained attention from both the developing and developed worlds. Using data from 1970/Q1 to 2020/Q4, this paper evaluates the time‐frequency nexus between CO2 emissions and natural resources, coal consumption, and economic growth. The study employs the Wavelet Local Multiple Correlation (WLMC) to explore this nexus. This approach enhances the capacity to comprehend the fundamental relationships between these indicators at different frequencies. To the best of the investigator' knowledge, this is the first empirical investigation to explore the time‐frequency nexus between natural resource, economic growth, coal use, and CO2 emissions in China, thus filling a gap in the literature. Furthermore, wavelet coherence is employed as a robustness check. The WLMC bivariate cases revealed that economic growth, coal consumption, and natural resources drive CO2 emissions positively at all frequencies, that is, in the short and long‐term, thus leading to environmental degradation. Furthermore, the wavelet coherence results support the outcomes of the WLMC bivariate cases. This study offers significant implications for policy and insights that are supported by the findings.

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Section: Industrialization Brought On By Economic Expansion Acceleratesmentioning

confidence: 99%

“…In this paper, we use a more effective and innovative framework compared to those utilized in prior studies. While the investigations of (Wu et al, 2022), (Adebayo, 2022) and (Shah et al, 2022) implemented traditional wavelet tools, such as Multiple wavelet coherence (MWT), Wavelet coherence (WTC), Cross wavelet coherence (CWT), and Partial wavelet coherence (PWT), this paper employs an innovative technique known as WLMC. The WLMC is a potent method developed by (Polanco‐Martínez et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Trade‐off between environmental sustainability and economic growth through coal consumption and natural resources exploitation in China: New policy insights from wavelet local multiple correlation

Adebayo

2022

Geological Journal

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“…As the world economy recovers from COVID-19, carbon emissions linked to energy are rebounding rapidly (Shah et al 2022 ; Ray et al 2022 ; Razzaq et al 2020 ). It is estimated that China will contribute over 11.9 billion tons of carbon emissions in 2021, which is 33% of the global total, according to the latest analysis by the International Energy Agency (IEA).…”

Section: Introductionmentioning

confidence: 99%

The impact of local government competition and green technology innovation on economic low-carbon transition: new insights from China

Liu

et al. 2022

Environ Sci Pollut Res

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The government-led Chinese economic development system determines that local government competition is a significant factor affecting the economic low-carbon transition. Driving an economic development mode with green technology innovation as the core is the critical path to realizing an economic low-carbon transition. Consequently, it is of significant practical relevance to investigate the impact of local government competition and green technology innovation on the economic low-carbon transition under the government-led Chinese economic development system. This paper systematically explores the nexus between green technology innovation and economic low-carbon transition in terms of local government competition perspective using the system generalized method of moments, panel threshold model, and geographically weighted regression on the basis of a dataset of 30 provincial administrative areas in China from a period of 2006–2019. The results indicate that green technology innovation significantly promotes the economic low-carbon transition. Local government competition not only significantly dampens the economic low-carbon transition but also considerably inhibits the positive effect of green technology innovation on the economic low-carbon transition. A significant N-shaped association is evident between green technology innovation and the economic low-carbon transition when green technology innovation is applied as a threshold, while such association is insignificant when local government competition is used as a threshold. Compared with high-competition intensity areas, green technology innovation promotes economic low-carbon transition weaker in low- competition intensity areas, while local government competition inhibits economic low-carbon transition stronger. However, local government competition significantly inhibits the positive effect of green technology innovation on the economic low-carbon transition in low-competition intensity areas, while insignificant in high-competition intensity areas. The geographically weighted regression technique as a whole also verified the above results. Therefore, policymakers should not only increase research and development investment in green technologies, but also develop a regionally linked low-carbon emission reduction system to avoid ineffective competition among governments to facilitate the earlier fulfillment of the “dual carbon” goal.

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“…used for transport in cars and personnel services, heating, cooling, and lighting of large office buildings), decreasing energy demand depending on the before-mentioned development. 27 , 28 The progress trend of both industrial CO 2 emissions and COVID-19 pandemic cases is presented in Figure 1(a) .…”

Section: Introductionmentioning

confidence: 99%

Effect of green bonds, oil prices, and COVID-19 on industrial CO₂ emissions in the USA: Evidence from novel wavelet local multiple correlation approach

Adebayo

Kartal

2023

Energy & Environment

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This study explores the effect of green bonds, oil prices, and the coronavirus disease 2019 (COVID-19) pandemic on industrial carbon dioxide (CO2) emissions. In this context, this study examines the United States of America (USA), which is the biggest economy in the world, uses weekly data between March 6, 2020 and September 30, 2022, and applies a novel wavelet local multiple correlation (WLMC) approach under time-varying and frequency-varying perspective. The novel empirical findings shows that (i) there is a strong negative (positive) co-movement between industrial CO2 emissions and green bonds in the short-run (long-run); (ii) there is a strong positive (negative) co-movement between industrial CO2 emissions and oil price in the medium-run (long-run); (iii) there is a strong negative (positive) co-movement between industrial CO2 emissions and the COVID-19 pandemic in the medium-run (long-run); (iv) the oil price is the dominant factor, whereas there are changing effect of the variables on each other at different times and frequencies; and (vi) overall, there are long-run asymmetric and dynamic correlations between industrial CO2 emissions and variables. Hence, the empirical results highlight the asymmetric, time-varying, and frequency-varying effects of green bonds, oil prices, and the COVID-19 pandemic on industrial CO2 emissions by presenting fresh and novel evidence. Moreover, the study proposes policy implications for the USA government.

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Green innovation, resource price and carbon emissions during the COVID-19 times: New findings from wavelet local multiple correlation analysis

Cited by 41 publications

References 57 publications

Trade‐off between environmental sustainability and economic growth through coal consumption and natural resources exploitation in China: New policy insights from wavelet local multiple correlation

Trade‐off between environmental sustainability and economic growth through coal consumption and natural resources exploitation in China: New policy insights from wavelet local multiple correlation

The impact of local government competition and green technology innovation on economic low-carbon transition: new insights from China

Effect of green bonds, oil prices, and COVID-19 on industrial CO₂ emissions in the USA: Evidence from novel wavelet local multiple correlation approach

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Green innovation, resource price and carbon emissions during the COVID-19 times: New findings from wavelet local multiple correlation analysis

Cited by 41 publications

References 57 publications

Trade‐off between environmental sustainability and economic growth through coal consumption and natural resources exploitation in China: New policy insights from wavelet local multiple correlation

Trade‐off between environmental sustainability and economic growth through coal consumption and natural resources exploitation in China: New policy insights from wavelet local multiple correlation

The impact of local government competition and green technology innovation on economic low-carbon transition: new insights from China

Effect of green bonds, oil prices, and COVID-19 on industrial CO2 emissions in the USA: Evidence from novel wavelet local multiple correlation approach

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Product

Resources

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Effect of green bonds, oil prices, and COVID-19 on industrial CO₂ emissions in the USA: Evidence from novel wavelet local multiple correlation approach