Author
Changhua Shao
Bio: Changhua Shao is an academic researcher from Qingdao University of Science and Technology. The author has contributed to research in topics: Financial market efficiency. The author has an hindex of 1, co-authored 1 publications receiving 12 citations.
Topics: Financial market efficiency
Papers
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TL;DR: In this article, the DEA-SBM (Data Envelopment Analysis-Super Slack Based Measure) model and GML (Global Malmquist-Luenberger) index were combined to measure the efficiency of green technology innovation in 30 provinces of China from 2003 to 2017.
252 citations
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TL;DR: Wang et al. as discussed by the authors analyzed the impact of digital finance on green technology innovation and found that digital finance significantly promotes green technologies and this finding holds even through serial robustness tests, and they attributed the promotion effects to a reduction in corporate financing constraints, industrial structure upgrading and manufacturing development.
156 citations
TL;DR: Wang et al. as mentioned in this paper constructed a policy-and market-oriented green financial development index system with the help of a local green finance development index and assessment report in 2019 and then calculate the green financial index by using time and space ranges via the entry-weight method.
140 citations
TL;DR: In this article, a comprehensive assessment of the interrelationships among environmental regulation, clean energy consumption, and economic growth is presented, where the authors estimate a production function accounting for heterogeneity by using the finite mixture model.
121 citations
TL;DR: In this article, the impact of telecommunications infrastructure on green technology innovation is investigated. But, the authors focus on the effect of the infrastructure on the green technology development process and do not consider the effects of the underlying infrastructure.
120 citations
01 Jan 2022
TL;DR: In this paper , a comprehensive assessment of the interrelationships among environmental regulation, clean energy consumption, and economic growth is presented, where the authors estimate a production function accounting for heterogeneity by using the finite mixture model.
Abstract: Applying balanced panel data comprised of 27 provinces spanning the period from 2000 to 2015, this research estimates a production function accounting for heterogeneity by using the finite mixture model to provide, for the first time, a comprehensive assessment of the interrelationships among environmental regulation, clean energy consumption, and economic growth. It is noteworthy here that we calculate clean energy consumption at the level of China's provinces to avoid measurement error. The main findings can be summarized as follows. First, environmental regulation matters for the nexus between clean energy consumption and economic growth. Specifically, regulation enhances the positive effect of clean energy consumption on economic growth, thus prompting provinces to transform onto a clean growth path. Second, there exists heterogenous nexuses between clean energy consumption and economic growth in different growth paths, as clean energy consumption not only facilitates growth in paths B and C, but also restrains growth in path A. Third, ignoring measurement error of clean energy consumption and adopting a misspecification of the production function will bias estimation results when analyzing the impact of clean energy consumption on economic growth. In comparison to applying clean energy consumption data and the Solow decomposition framework accounting for heterogeneity, employing clean energy production data and using the traditional Solow decomposition framework will both underestimate the significance of clean energy consumption's impact on economic growth.
105 citations