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DC Field | Value | Language |
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dc.contributor.author | Asif Razzaq | en_US |
dc.contributor.author | Yufeng Wang | en_US |
dc.contributor.author | Supat Chupradit | en_US |
dc.contributor.author | Wanich Suksatan | en_US |
dc.contributor.author | Farrukh Shahzad | en_US |
dc.date.accessioned | 2022-10-16T07:03:22Z | - |
dc.date.available | 2022-10-16T07:03:22Z | - |
dc.date.issued | 2021-08-01 | en_US |
dc.identifier.issn | 0160791X | en_US |
dc.identifier.other | 2-s2.0-85109434734 | en_US |
dc.identifier.other | 10.1016/j.techsoc.2021.101656 | en_US |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85109434734&origin=inward | en_US |
dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/75877 | - |
dc.description.abstract | 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. | en_US |
dc.subject | Business, Management and Accounting | en_US |
dc.subject | Social Sciences | en_US |
dc.title | Asymmetric inter-linkages between green technology innovation and consumption-based carbon emissions in BRICS countries using quantile-on-quantile framework | en_US |
dc.type | Journal | en_US |
article.title.sourcetitle | Technology in Society | en_US |
article.volume | 66 | en_US |
article.stream.affiliations | The Chinese University of Hong Kong, Shenzhen | en_US |
article.stream.affiliations | Guangdong University of Petrochemical Technology | en_US |
article.stream.affiliations | Ilma University | en_US |
article.stream.affiliations | Chulabhorn Royal Academy | en_US |
article.stream.affiliations | Dalian University of Technology | en_US |
article.stream.affiliations | Chiang Mai University | en_US |
Appears in Collections: | CMUL: Journal Articles |
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