The Impact of Monetary Policy on Green Innovation: Global Evidence

Yin, Hua-Tang; Chang, Chun‐Ping; Wang, Haijie

doi:10.3846/tede.2022.17020

Cited by 68 publications

(29 citation statements)

References 58 publications

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“…In financial economics, the panel unit root test is widely used to investigate the stability of a series (Peng et al 2022 ; Yin et al 2022 ; Charfeddine and Khediri 2016 ; Jung and Maderitsch 2014 ). As booms and busts occur in the cryptocurrency market, checking the stability of transaction behaviors and electricity consumption should consider potential structural breaks (Bouri et al 2019 ; Cheah and Fry 2015 ).…”

Section: Methods and Datamentioning

confidence: 99%

The transaction behavior of cryptocurrency and electricity consumption

et al. 2023

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Rapidly increasing cryptocurrency prices have encouraged cryptocurrency miners to participate in cryptocurrency production, increasing network hashrates and electricity consumption. Growth in network hashrates has further crowded out small cryptocurrency investors owing to the heightened costs of mining hardware and electricity. These changes prompt cryptocurrency miners to become new investors, leading to cryptocurrency price increases. The potential bidirectional relationship between cryptocurrency price and electricity consumption remains unidentified. Hence, this research thus utilizes July 31 2015–July 12 2019 data from 13 cryptocurrencies to investigate the short- and long-run causal effects between cryptocurrency transaction and electricity consumption. Particularly, we consider structural breaks induced by external shocks through stationary analysis and comovement relationships. Over the examined time period, we found that the series of cryptocurrency transaction and electricity consumption gradually returns to mean convergence after undergoing daily shocks, with prices trending together with hashrates. Transaction fluctuations exert both a temporary effect and permanent influence on electricity consumption. Therefore, owing to the computational power deployed to wherever high profit is found, transactions are vital determinants of electricity consumption.

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Section: Methods and Datamentioning

confidence: 99%

The transaction behavior of cryptocurrency and electricity consumption

et al. 2023

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“…Concerning enterprise green innovation activities, researchers are no longer satisfied with an individual study of each potential factor (Yin et al, 2022). Researchers have found that ESG performance aggregates various factors in the pursuit of sustainable development (Wen et al, 2023), which can effectively prevent the omission of influencing factors (Chai et al, 2022; Hao et al, 2023).…”

Section: Introductionmentioning

confidence: 99%

ESG performance and green innovation: An investigation based on quantile regression

et al. 2023

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Using panel data from 37 countries from 1990 to 2019 and applying a quantile regression approach with panel fixed effects, we investigate the impact of national Environmental, Social, and Governance (ESG) performance on green innovation and how this impact varies across different green innovation capacity distributions. The research conclusions are as follows. (1) National ESG performance improvement significantly promotes green innovation. (2) The improvement of environmental performance and governance performance significantly promotes green innovation, but in countries with weak green innovation capabilities, the improvement of social performance reduces the output of green innovation. (3) The role of national ESG performance in promoting green innovation is stronger in countries with weak green innovation capabilities. (4) In non‐high‐income countries, the stronger the green innovation capability is, the more obvious is the promotion of ESG performance to green innovation. The findings of this paper provide empirical evidence and a policy basis for governments to focus on improving ESG performance and to commit to promoting green innovation activities more effectively.

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“…In line with the emergence of practical concerns, the academic world has conducted extensive studies on the impacts of green finance and driving factors for IGTFP. Regarding green finance's effects, the literature has mostly examined how it affects economic growth (Levine, 2005; Yang et al, 2021), environmental quality (Abanyie et al, 2023; Hariyani et al, 2023; Hussain et al, 2023; Mgomezulu et al, 2023; Raihan et al, 2023; Sui & Yao, 2023; Tang et al, 2023; Wang et al, 2023; Zhang, Li, et al, 2021; Zhou et al, 2020), green economy (Chin et al, 2022), industrial upgrading (Wang, Cai, & Elahi, 2021; Wang, Cui, & Zhao, 2021), enterprise investment and financing (Gilbert & Zhou, 2017; Yu et al, 2021), enterprise performance (Huang et al, 2021), enterprise green technology innovation (Yin et al, 2022; Zhang et al, 2022), and performance and risk of financial institutions (Cui et al, 2018; Guan et al, 2017; Lian et al, 2022). In parallel, academics have investigated the forces behind the industrial green revolution from the perspective of environmental regulation (ER) (Peng et al, 2021; Tang et al, 2020; Wang & Shen, 2016), technological innovation (Fu et al, 2022; Hao et al, 2023; Luo et al, 2022; Peng et al, 2022; Wang & Tan, 2021; Wen et al, 2023; Xue et al, 2022; Yang et al, 2022; Yin et al, 2022; Zhao et al, 2022; Zhao et al, 2023; Zheng et al, 2022), and trade openness (Xu et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Green finance, environment regulation, and industrial green transformation for corporate social responsibility

Chen

Chang

2023

Corp Soc Responsibility Env

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In order to meet the strategic goals of carbon peak and carbon neutralization on schedule, it is crucial to examine the effects and limitations of green finance on the green transformation of industry. This research utilizes the entropy method, the Global Malmquist–Luenberger technique, and panel data of 30 provinces in China from 2005 to 2018 to estimate the extent of industrial green transformation and green finance development in each province. It builds static and dynamic panel models to experimentally examine the effect of green finance on industrial green transformation. After introducing environmental regulation (ER), this paper presents how ER influences the link between green finance and industrial green transformation. The research finds the following. (1) According to geographical differences in the growth of green finance and industrial green transformation, the economically developed east region is more advanced than the central and west regions, and the central region is more advanced than the west region. (2) Green finance has a significantly positive impact on industrial green transformation, and this positive influence has certain continuity and inertia. (3) Environmental regulation has a favorable impact on the link between green finance and industrial green transformation; specifically, a rise in the level of environmental regulation stimulates the process of green finance that boosts industrial green transformation. The policy recommendations herein offer reference for the construction of China's green financial system and the promotion of industrial green transformation for CSR.

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The Impact of Monetary Policy on Green Innovation: Global Evidence

Cited by 68 publications

References 58 publications

The transaction behavior of cryptocurrency and electricity consumption

The transaction behavior of cryptocurrency and electricity consumption

ESG performance and green innovation: An investigation based on quantile regression

Green finance, environment regulation, and industrial green transformation for corporate social responsibility

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