Yaru Huang, Yaojun Ye and Mengling Zhou
This paper aims to build an improved grey panel clustering evaluation model and evaluate the comprehensive development potential of industrial economy, society and ecological…
Abstract
Purpose
This paper aims to build an improved grey panel clustering evaluation model and evaluate the comprehensive development potential of industrial economy, society and ecological environment in the Yangtze River Economic Belt of China. The purpose of this study is to provide some theoretical basis and tool support for management departments and relevant researchers engaged in industrial sustainable development.
Design/methodology/approach
This study uses the driving force pressure state impact response analysis framework to build a comprehensive evaluation index system. Based on the center point triangle whitening weight function, it classifies the panel grey clustering of improvement time and index weight.
Findings
The results show that there are great differences in the level of industrial ecological development in different regions of the Yangtze River Economic Belt, which further illustrates the scientificity and rationality of the evaluation method proposed in this paper.
Practical implications
Due to the industrial ecological development is in a constantly changing state, and the information is uncertain. Whitening weight function is introduced to represent the complete information of relevant data. The industrial ecological evaluation involves a comprehensive complex system, which belongs to the panel data analysis problem. The improved grey panel clustering evaluation model is applied to grade the industrial ecological development level of the Yangtze River Economic Belt. The results have important guiding significance for the balanced development of industrial ecology in the region.
Social implications
Due to the industrial ecological development is in a constantly changing state, and the information is uncertain. Whitening weight function is introduced to represent the complete information of relevant data. The industrial ecological evaluation involves a comprehensive complex system, which belongs to the panel data analysis problem. In order to improve the effectiveness of industrial ecological evaluation, the improved grey panel clustering evaluation model is applied to grade the industrial ecological development level of the Yangtze River Economic Belt. The results have important guiding significance for the balanced development of industrial ecology in the region.
Originality/value
the new model proposed in this paper complements and improves the grey clustering analysis theory of panel data, that is, aiming at the subjective limitation of using time degree to determine time weight in panel grey clustering, a comprehensive theoretical method for determining time weight is creatively proposed. Combining the DPSIR (Driving force-Pressure-State-Influence-Response) model model with ecological development, a comprehensive evaluation model is constructed to make the evaluation results more authentic and comprehensive.
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Yang Gao, Yangyang Li and Yaojun Wang
This paper aims to explore the interaction between investor attention and green security markets, including green bonds and stocks.
Abstract
Purpose
This paper aims to explore the interaction between investor attention and green security markets, including green bonds and stocks.
Design/methodology/approach
This study takes the Baidu index of “green finance” as the proxy for investor attention and constructs several generalized prediction error variance decomposition models to investigate the interdependence. It further analyzes the dynamic interaction between investor attention and the return and volatility of green security markets using the rolling time window.
Findings
The empirical analysis and robustness test results reveal that the spillovers between investor attention and the return and volatility of the green bond market are relatively stable. In contrast, the spillover level between investor attention and the green stock market displays significant time-varying and asymmetric effects. Moreover, the volatility spillover between investor attention and green securities is vulnerable to major financial events, while the return spillover is extremely sensitive to market performance.
Originality/value
The conclusion further expands the practical application and theoretical framework of behavioral finance in green finance and provides a new reference for investors and regulators. Besides, this study also lays a theoretical basis for investors to focus on the practical application of volatility prediction and risk management in green securities.