TY - JOUR
T1 - ー种新的绿色激励指标构建方法及其应用
AU - Yifei, Zhang
AU - Wenhao, Chi
AU - Yunjie, Wei
AU - Shaolong, Sun
AU - Jue, Wang
N1 - Publisher Copyright:
© 2022 Science China Press. All rights reserved.
PY - 2022/10
Y1 - 2022/10
N2 - Improving and developing the green financial system is a vital tool to achieve emission peak and carbon neutrality, and the research on green incentive (GI) in Chinese securities market is conducive to further discovering the impacts of policies and green risk compensation on the market. First, based on the classical C A P M and a return, we construct brand-new GI indicators with distinct incentive factors by the index of environmental protection industry. Second, to investigate the characteristics of GI indexes, this work proposes a systematic hybrid analysis method by integrating the causality test, trend analysis and regression significance test, which can also reveal the advantages and merits of our established indicators. Third, the empirical results demonstrate that under different incentive factors, GIs can exhibit obvious leading trend, significant regression coefficient and predictive explanatory power, with regard to the environmental protection industry index. The conclusion points out that the trend of the environmental protection index is affected by the green risk compensation required by the market in a long term, and meanwhile, it also provides a valuable reference for tracking and predicting the index.
AB - Improving and developing the green financial system is a vital tool to achieve emission peak and carbon neutrality, and the research on green incentive (GI) in Chinese securities market is conducive to further discovering the impacts of policies and green risk compensation on the market. First, based on the classical C A P M and a return, we construct brand-new GI indicators with distinct incentive factors by the index of environmental protection industry. Second, to investigate the characteristics of GI indexes, this work proposes a systematic hybrid analysis method by integrating the causality test, trend analysis and regression significance test, which can also reveal the advantages and merits of our established indicators. Third, the empirical results demonstrate that under different incentive factors, GIs can exhibit obvious leading trend, significant regression coefficient and predictive explanatory power, with regard to the environmental protection industry index. The conclusion points out that the trend of the environmental protection index is affected by the green risk compensation required by the market in a long term, and meanwhile, it also provides a valuable reference for tracking and predicting the index.
KW - environmental protection industry
KW - green incentive
KW - incentive factor
KW - index forecasting
KW - trend analysis
UR - https://www.scopus.com/pages/publications/85192220676
U2 - 10.12012/CJoE2022-0044
DO - 10.12012/CJoE2022-0044
M3 - 文章
AN - SCOPUS:85192220676
SN - 2096-9732
VL - 2
SP - 738
EP - 759
JO - China Journal of Econometrics
JF - China Journal of Econometrics
IS - 4
ER -