The symmetric and asymmetric impacts of green energy, eco-innovation, and urbanization in explaining low-carbon economy for Pakistan

Ullah, Kifayat; Abbas, Shah; Tariq, Muhammad Atiq Ur Rehman; Mahmood, Nasir; Kaechele, Harald

doi:10.1007/s11356-022-24407-5

Cited by 10 publications

(6 citation statements)

References 109 publications

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“…In addition to calculating the CP of each province in China during the period from 2001 to 2020, this study also used the database of the State Intellectual Property Office of China to collect the patent data of RE technology in each province, which was calculated as shown in Equation (7) [37,38].…”

Section: Identification Of Cp-influencing Factorsmentioning

confidence: 99%

“…In Equation (7), REIT it denotes the total patent data. β 1 and β 2 denote the depreciation rate and diffusion rate, respectively, taking the values of 0.36 and 0.30. t is the time, i denotes the province, and j is the patent type.…”

Section: Identification Of Cp-influencing Factorsmentioning

confidence: 99%

“…As an emerging branch within the field of technological innovation research, Renewable Energy Technology Innovation (REIT) has not yet reached a consensus among scholars regarding its categorization. Currently, the terms widely used include green technology (environmental technology and clean technology) and low-carbon technology [6,7]. This paper focuses on technologies that reduce carbon emissions (CEs) within the realm of green technology innovation, primarily referring to technological advancements and innovative activities in the development and utilization of RE, including improvements in existing technologies such as solar, wind, hydropower, geothermal energy, and biomass energy.…”

Section: Introductionmentioning

confidence: 99%

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Impact Mechanism of Renewable Energy Technology Innovation on Carbon Productivity Based on Spatial Durbin Model

Wang,

Chen

2024

Sustainability

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Given the threats to international energy security and the restructuring of energy sources in various countries, China faces the dual challenge of achieving the goals of carbon peaking and carbon neutrality. To promote a reduction in carbon emissions and enhance carbon productivity, it is crucial to innovate renewable energy technology for long-term, low-carbon transformational development. This paper identifies the key factors that affect carbon productivity through pathway analysis and quantitatively examines the direct and spatial spillover impacts of technological advancements in renewable energy using the spatial Durbin model. Finally, this study verifies the pathways through which innovations affect carbon productivity by combining them with the spatial mediation model. The results indicate that innovations in renewable energy technologies significantly enhance carbon productivity. The indirect effects of regional spillover are even more pronounced.

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Section: Identification Of Cp-influencing Factorsmentioning

confidence: 99%

Section: Identification Of Cp-influencing Factorsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Impact Mechanism of Renewable Energy Technology Innovation on Carbon Productivity Based on Spatial Durbin Model

Wang,

Chen

2024

Sustainability

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“…Research related to the impact of international trade on CEs yielded contradictory findings. Some scholars, for example, Rehman et al (2021) and Ullah et al (2022) using ARDL findings in the Pakistan economy context, found positive and fruitful relationships exist between globalization, energy consumption, and international trade, and ecological footprint. Concerning South African economies, Udeagha and Ngepah (2019) explored the link between trade openness and discovered a positive short‐run relationship but a negative correlation in the long run.…”

Section: Literature Reviewmentioning

confidence: 99%

Toward low‐carbon emissions and green growth for sustainable development in emerging economies: Do green trade openness, eco‐innovation, and carbon price matter?

Tariq

Ullah

et al. 2023

Sustainable Development

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Due to substantial development in emerging economies over the last three decades, climate complexities are increasing which have posed serious threats to environmental quality and sustainability. To this end, eco‐innovation, green trade openness (GTO), and carbon price have been recognized as effective tools for environmental mitigation and promotion of green growth (GG) in the core of COP 26, Sustainable Development Goals 2030, and Carbon Neutrality by 2060. Considering this, the aim of this study is to investigate the influence of eco‐innovation, GTO, and carbon price on GG and low‐carbon emissions in emerging economies over the period 1996–2021. The current study provides a standard green Solow growth model by introducing a new GG index using the entropy weight method. This index incorporates 30 indicators across five dimensions which emphasizes the essential roles of the investigated factor. Additionally, the current study provides a new index for GTO utilizing an extensive green trading basket of 255 commodities. Due to the cross‐sectional dependency, and slope heterogeneity in the models, this study used dynamic heterogeneous panel data estimation techniques that is, cross‐sectional based augmented nonlinear autoregressive distributed lag, and nonlinear augmented mean group to probe the asymmetric effects. The outcomes from the empirical analysis reveal that positive shocks in environmental innovation, GTO, carbon price, and green energy mitigate carbon emissions and promote green economic growth while the negative shocks in these variables cause environmental degradation and reduce GG in emerging economies. Finally, from policy insight, this study suggests that policy makers in emerging economies should invigorate GTO, stimulate environmental innovation and green energy, implement carbon price mechanisms, and establish a balance between environmental protection and economic growth.

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“…Scholars have built multidimensional highquality development evaluation systems based on the connotation of high-quality development, and evaluation system is changing dynamically. At present, the issue of carbon emissions cannot be ignored [4,5]. In 2020, China introduced the "dual carbon" goals of "peaking its carbon emissions before 2030 and achieving carbon neutrality by 2060" [6].…”

mentioning

confidence: 99%

Regional Difference and Obstacle Factors of China’s High-Quality Development from the Perspective of Coupling Coordination

Baoling,

Ying

2023

Pol. J. Environ. Stud.

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China's economy has experienced phenomenal growth over the past few decades. However, energy dilemmas, environmental pollution, and the greenhouse effect arise over time [1]. Based on the profound changes in China's economic development environment, the 19th National Congress pointed out that China's economy "has shifted from a stage of high-speed growth to a stage of high-quality development". High-quality development is the fundamental embodiment of the new development concept of innovation, coordination, greenness, openness, and sharing [2,3]. China is a vast country with significant heterogeneity in geographical location, resource endowment, and economic base. Narrowing regional differences and achieving regional balance is a challenge for high-quality development. Therefore, exploring regional differences is a prerequisite for promoting regional collaborative high-quality development.

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The symmetric and asymmetric impacts of green energy, eco-innovation, and urbanization in explaining low-carbon economy for Pakistan

Cited by 10 publications

References 109 publications

Impact Mechanism of Renewable Energy Technology Innovation on Carbon Productivity Based on Spatial Durbin Model

Impact Mechanism of Renewable Energy Technology Innovation on Carbon Productivity Based on Spatial Durbin Model

Toward low‐carbon emissions and green growth for sustainable development in emerging economies: Do green trade openness, eco‐innovation, and carbon price matter?

Regional Difference and Obstacle Factors of China’s High-Quality Development from the Perspective of Coupling Coordination

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