Asymmetric inter-linkages between green technology innovation and consumption-based carbon emissions in BRICS countries using quantile-on-quantile framework

被引:268
作者
Razzaq, Asif [1 ,2 ]
Wang, Yufeng [3 ]
Chupradit, Supat [4 ]
Suksatan, Wanich [5 ]
Shahzad, Farrukh [6 ]
机构
[1] Dalian Univ Technol, Sch Management & Econ, Dalian, Peoples R China
[2] ILMA Univ, Dept Business Adm, Karachi, Pakistan
[3] Chinese Univ Hongkong, Shenzhen Finance Inst, Shenzhen 518000, Guangdong, Peoples R China
[4] Chiang Mai Univ, Fac Associated Med Sci, Dept Occupat Therapy, Chiang Mai 50200, Thailand
[5] Chulabhorn Royal Acad, HRH Princess Chulabhorn Coll Med Sci, Fac Nursing, Bangkok, Thailand
[6] Guangdong Univ Petrochem Technol, Sch Econ & Management, Maoming, Guangdong, Peoples R China
关键词
Green innovation; Consumption-based carbon emissions; Terrestrial-based carbon emissions; BRICS; Quantile on quantile; RENEWABLE ENERGY-CONSUMPTION; CO2; EMISSIONS; INTERNATIONAL-TRADE; IMPACT; GROWTH;
D O I
10.1016/j.techsoc.2021.101656
中图分类号
D58 [社会生活与社会问题]; C913 [社会生活与社会问题];
学科分类号
摘要
The role of reliable Carbon emission measures and relevant climate policy is imperative in realizing Sustainable Development Goals. A large extent of the literature concludes the emissions-mitigating effect of green innovations in a linear framework and ignored structural changes, technological revolutions, and socio-economic reforms that create non-linearity. Apart from that, there is a murky relationship between emissions and green innovation, where two-way links exist between both variables. Therefore, this study draws the inter-linkages between green technology innovation (GI) and carbon emissions (consumption-based and terrestrial emissions) in BRICS countries using monthly data from 1990 to 2017. Our preliminary findings strictly reject the preposition of data normality and highlight that the observed relationship is quantile-dependent. Therefore, a complete set of non-linear modeling is employed that included; Quantile unit root, Quantile cointegration, Quantile causality, and Quantile on Quantile regression to unveil hidden unit root, cointegration, causality, and association between variables. The results exhibit that the emissions-mitigating effect of GI is only pronounced at higher emissions quantiles in Brazil, China, India, and Russia, whereas at lower emissions quantile, GI is weekly or positively linked with carbon emissions. On the flipside, higher carbon emissions instigate GI across medium to higher emissions quantiles in Brazil, China, and India. Unlike them, Russia produces different outcomes, where higher emissions are associated with lower GI across all quantiles. The overall results suggest that GI (carbon emissions) mitigate (instigate) carbon emissions (GI) when a country is embodied with higher level of emissions.
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页数:21
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