Quantity or quality? The impacts of environmental regulation on firms’ innovation–Quasi-natural experiment based on China's carbon emissions trading pilot

Hu, Jiangfeng; Pan, Xinxin; Huang, Qinghua

doi:10.1016/j.techfore.2020.120122

Cited by 280 publications

(121 citation statements)

References 52 publications

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“…Li et al (2016) used the DEA model to evaluate the sustainable development of resource-based cities. Hu et al (2020a) used the hyperbolic distance function (HDF) model to measure the energy and environment performance of resourcebased cities. Hu et al (2019) used the Super-slack based measure (SBM) function and the Global Malmquist-Luenberger (GML) index to calculate China's manufacturing industrial green total factor productivity.…”

Section: Measurement Of Industrial Green Transformationmentioning

confidence: 99%

Innovation or Introduction? The Impact of Technological Progress Sources on Industrial Green Transformation of Resource-Based Cities in China

et al. 2020

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With the increasingly prominent problems of global resource consumption and environmental pollution, industrial green transformation has become one of the requirements of China’s industrial development in the new era. However, there is a lack of research on the impact of technological innovation and technology introduction on the industrial green transformation of resource-based cities. To bridge this gap, this study uses the panel data of 115 resource-based cities in China from 2003 to 2016, and uses the dynamic panel generalized method of moments (GMM) estimation method to study the impact of technological innovation and technology introduction on industrial green transformation of resource-based cities. The results show that technology introduction has a negative effect on the industrial green transformation of resource-based cities, while technological innovation can have a positive effect. Meanwhile, technology introduction has imparted a greater role to technological innovation in promoting this transformation. In addition, the interactive effects between technological innovation and technology introduction have obvious heterogeneity on the industrial green transformation of different types of resource-based cities. Therefore, resource-based cities should continue to increase investment in scientific research, to constantly improve and consolidate their technological innovation ability, optimize foreign investment strategy in technology introduction, and strengthen the digestion and absorption of imported technology, while increasing technological innovation and personnel training.

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Section: Measurement Of Industrial Green Transformationmentioning

confidence: 99%

Innovation or Introduction? The Impact of Technological Progress Sources on Industrial Green Transformation of Resource-Based Cities in China

et al. 2020

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“…Utility models are new models that make minor improvements on the shape, structure, and utility of existing inventions, which can be quickly produced and applied. Outline designs are rarely employed in the field of energy efficiency [ 9 ]. For patent quality measurement, we differentiated patent types between inventions (high-quality) and utility models (low-quality).…”

Section: Methodsmentioning

confidence: 99%

“…Nesta et al [ 37 ] concluded that environmental regulation plays a crucial role in inducing high-quality green patents. Hu et al [ 9 ] found that the CETS only promoted the innovation quantity and high-quality innovation of state-owned share firms, large-size firms, and eastern-section firms. Guo et al [ 38 ] argued that environmental regulation has a significant effect on both invention and utility models but is a little bit more robust on the impact on green process innovation.…”

Section: Literature Review and Backgroundmentioning

confidence: 99%

“…Aghion et al [ 8 ] discovered the reciprocal causation between environmental regulation and quality of innovation, as measured by types of patents. Hu et al [ 9 ] studied the impact of China’s carbon emissions trading system (CETS) on the quantity and quality of innovation and showed that the CETS has mainly promoted innovation quantity and low-quality innovation. Consequently, we hope to shed light on three questions when evaluating the effectiveness of a particular environmental regulation, with regard to green technology: Does the policy induce green innovation?…”

Section: Introductionmentioning

confidence: 99%

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Induced Effect of Environmental Regulation on Green Innovation: Evidence from the Increasing-Block Pricing Scheme

Liu

Yang

Fan

2021

IJERPH

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With increasing constraints on resources and the environment, it is of great practical importance to discover and utilize the induced effect of green technology through market-based tools, in order to simultaneously realize economic development and ecological sustainability. Based on unique patent data from 1999 to 2013, this paper examines the induced effect of China’s increasing-block electricity pricing scheme (IBP) on energy-efficient patents and checks whether the effect is neutral or biased. Furthermore, the quality of the induced patents is identified. The results reveal that increased green innovation is strongly related to the IBP scheme. In addition, the induced effect is biased towards green technology such that, apart from autonomous technological advances, the biased effect of IBP induced two more energy-efficient patents per hundred technological patents. However, the quality of the induced innovation is relatively low: compared to high-quality inventions, low-quality utility models showed greater and more significant growth due to the IBP. Our paper provides quantitative insight into the impact of the IBP and indicates that a reasonable pricing scheme can benefit both the environment and the economy.

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“…After inspecting the emitting enterprises and setting the baseline, the ETS distributes the CEP to the emitting enterprises through allocation and auctions. The emitting enterprises can trade the CEP with each other to write off the carbon emissions [6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Delegated Proof of Reputation Consensus Mechanism for Blockchain-Enabled Distributed Carbon Emission Trading System

Rao

et al. 2020

IEEE Access

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Most carbon Emission Trading Systems (ETS) rely on a centralized system to manage the transactional tasks, and are vulnerable to security threats. This paper proposes a Blockchain-enabled Distributed ETS (BD-ETS) to improve the security and efficiency of the system. The BD-ETS transforms the centralized Carbon Emissions Permit (CEP) trading mode to a distributed trading system in which the trading mode is based on a smart contract performed in Hyperledger Fabric. In a smart contract, every transaction considers both the offer price and reputation value of the emitting enterprises. The voting power of the emitting enterprise is determined by its reputation value, which stems from their contributions to carbon emission reduction. To achieve consistency of every node in the CEP transactions, we propose a Delegated Proof of Reputation (DPoR) consensus mechanism. Compared to the enhanced Delegated Proof of Stake, the DPoR decreases the attack intention of malicious enterprises and performs better in finding malicious miners faster, thus improving the security of the BD-ETS. A case study and numerical simulations are developed to illustrate how the CEP trading functions, and to validate the DPoR mechanism.

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Quantity or quality? The impacts of environmental regulation on firms’ innovation–Quasi-natural experiment based on China's carbon emissions trading pilot

Cited by 280 publications

References 52 publications

Innovation or Introduction? The Impact of Technological Progress Sources on Industrial Green Transformation of Resource-Based Cities in China

Innovation or Introduction? The Impact of Technological Progress Sources on Industrial Green Transformation of Resource-Based Cities in China

Induced Effect of Environmental Regulation on Green Innovation: Evidence from the Increasing-Block Pricing Scheme

Delegated Proof of Reputation Consensus Mechanism for Blockchain-Enabled Distributed Carbon Emission Trading System

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