共 4 条
Modeling green energy and innovation for ecological risk management using second generation dynamic quantile panel data model
被引:2
|作者:
Ul-Durar, Shajara
[1
,2
]
Arshed, Noman
[3
]
De Sisto, Marco
[4
]
Nazarian, Alireza
[5
]
Sadaf, Ashina
[6
]
机构:
[1] Univ Sunderland, Sch Business Management, Edinburgh Bldg,Chester Rd, Sunderland SR1 3SD, England
[2] Univ Durham, Business Sch, Mill Hill Lane, Durham DH1 3LB, England
[3] Univ Educ Lahore, Dept Econ, Div Management & Adm Sci, Lahore, Pakistan
[4] RMIT Univ, Grad Sch Business & Law, 445 Swanston St, Melbourne, Vic 3000, Australia
[5] Univ Westminster, Sch Business Management, 35 Marylebone Rd, London NW1 5LS, England
[6] Univ Durham, Van Mildert Coll, Ogden Ctr Fundamental Phys, Dept Phys, Durham, England
关键词:
Green technology;
Economic activity;
Environmental performance index;
Biodiversity loss;
Habitat destruction;
CROSS-SECTIONAL DEPENDENCE;
CLIMATE-CHANGE;
GLOBAL BIODIVERSITY;
ECONOMIC-GROWTH;
SUSTAINABILITY;
PERFORMANCE;
TECHNOLOGY;
POLLUTION;
TESTS;
GLOBALIZATION;
D O I:
10.1016/j.jenvman.2024.121741
中图分类号:
X [环境科学、安全科学];
学科分类号:
08 ;
0830 ;
摘要:
Ecological risk management has emerged as a critical research and policy development area in energy and environmental economics. Sustained ecology is crucial for the standard of living and food security. As the adverse impacts of environmental degradation and climate change become increasingly apparent it is imperative to understand ecological risk and its interconnectedness with environmental pressure, clean energy, economic activity, globalization, and green technology. Ecological risk is assessed using the environmental performance index which is a holistic indicator of climate change, environmental pressures and human actions in which most of these indicators have spatial effects. This paper explores the multifaceted relationship between identified anthropogenic critical factors and their role in effectively managing ecological risk globally. This study has developed the second-generation dynamic panel quantile regression considering spatial effects of economic activities on ecology across borders of 55 countries between 1995 and 2022. This innovative hybrid estimation scheme that integrated theoretical and econometric aspects makes the model robust to major regression issues. Several implications ranked in decreasing order of its effectiveness are reducing environmental pressure, expediting energy transition, and embracing economic integration while there is a need to work on rejuvenating green technology and green growth.
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