Investigating the asymmetric linkages between infrastructure development, green innovation, and consumption-based material footprint: Novel empirical estimations from highly resource-consuming economies

被引:188
|
作者
Razzaq, Asif [1 ,6 ]
Ajaz, Tahseen [2 ]
Li, Jing Claire [3 ]
Irfan, Muhammad [4 ,5 ]
Suksatan, Wanich [7 ]
机构
[1] Dalian Univ Technol, Sch Management & Econ, Dalian, Peoples R China
[2] Quaid I Azam Univ, Sch Econ, Islamabad, Pakistan
[3] Univ Westminster, Sch Finance & Accounting, London NW1 5LS, England
[4] Beijing Inst Technol, Sch Management & Econ, Beijing 100081, Peoples R China
[5] Beijing Inst Technol, Ctr Energy & Environm Policy Res, Beijing 100081, Peoples R China
[6] ILMA Univ, Dept Business Adm, Karachi, Pakistan
[7] Chulabhorn Royal Acad, HRH Princess Chulabhorn Coll Med Sci, Bangkok, Thailand
关键词
Resources consumption; Consumption-based material footprints; Green innovation; Infrastructure development; STRIPAT; Methods of moment quantiles; ENVIRONMENTAL KUZNETS CURVE; RENEWABLE ENERGY-CONSUMPTION; CO2; EMISSIONS; MATERIAL FLOWS; CARBON EMISSION; TECHNOLOGICAL-INNOVATION; QUANTILE REGRESSION; SUPPLY CHAINS; GAS EMISSIONS; GROWTH;
D O I
10.1016/j.resourpol.2021.102302
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The role of a reliable resource consumption measurement is essential for devising a relevant climate policy. The consumption-based material footprint is trade-adjusted domestic resource consumption that presents an accurate picture of the domestic material footprint. Pursuing the same, this study draws asymmetric linkages between infrastructure development, green innovation, and consumption-based material footprint (MF) in the top 11 highly material-consuming countries. Our preliminary findings strictly reject the preposition of data normality and highlight that the observed relationship is quantile-dependent, which may disclose misleading results in previous studies using linear methodologies. In compliance, a novel empirical estimation technique popularized as Method of Moments Quantile Regression is employed that simultaneously deal with non-normality and structural changes in data. The results exhibit that infrastructure development (green innovation) significantly increases (decreases) MF mainly across medium to higher quantiles (medium-higher level of MF). Interestingly, the resource-depleting effect of infrastructure is highest for higher quantiles and lowest for lower quantiles of MF. Economic growth (globalization) increase MF, and their resource-depleting effect is higher (lowest) for lower quantiles and lowest (highest) for higher quantiles. Lastly, population exhibits an inverted-U shape relationship with MF across lower to higher quantiles. These results suggest pertinent policy recommendations.
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页数:18
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