Natural resource extraction - Sustainable development relationship and energy productivity moderation in resource-rich countries: A panel Bayesian regression analysis

被引:1
|
作者
De Sisto, Marco [1 ]
Ul-Durar, Shajara [2 ,3 ]
Arshed, Noman [4 ]
Iqbal, Mubasher [5 ]
Nazarian, Alireza [6 ]
机构
[1] RMIT Univ, Grad Sch Business & Law, 445 Swanston St, Melbourne, Vic 3000, Australia
[2] Univ Sunderland, Sch Business Management, Edinburgh Bldg,Chester Rd, Sunderland SR1 3SD, England
[3] Univ Durham, Business Sch, Mill Hill Lane, Durham DH1 3LB, England
[4] Sunway Univ, Kuala Lumpur, Malaysia
[5] Univ Lahore, Dept Econ, Lahore, Pakistan
[6] Univ Westminster, Sch Business Management, 35 Marylebone Rd, London NW1 5LS, England
关键词
Bayesian regression; Energy productive capacity; Natural resource extraction; Social development; Sustainability; ENVIRONMENT;
D O I
10.1016/j.jclepro.2024.143775
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Social development is essential for improving quality of life, fostering stability, driving economic growth, achieving sustainable goals, enhancing human capital, encouraging civic engagement, building resilience, and fostering innovation, thereby ensuring inclusive, equitable, and sustainable progress. The Social Progress Index (SPI), also known as social development, contains all these features. This study aims to examine the impact of natural resource extraction on social development quadratically using data from 2011 to 2022. The focus of the study is on resource-rich countries. In this study, productive capacity in the energy sector is used as a social development determinant and a natural resource consumption moderator, ensuring sustainability in social development. Analyzing the quadratic relationship allows us to model and understand nonlinear relationships between the predictor and the outcome variable, capturing the effects that change direction or strength at different levels of the predictor. In this study, Bayesian regression is incorporated as an econometric approach. It provides more flexible modelling, incorporates prior knowledge, and offers a full distribution of parameter estimates, leading to better uncertainty quantification and more robust predictions. These estimates confirms a Ushaped natural resource extraction and social development relationship. Energy productive capacities in resource-rich countries not only enhance social development but also ensure the sustainable extraction of natural resources leading to sustainable social development. Population density and biodiversity are incorporated as control variables of the model. The impact of both is positive on social development.
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页数:12
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