The role of green bonds on industrial sustainability for achieving carbon neutrality: Evidence from the artificial neural network method

dc.contributor.authorLau, Chi Keung
dc.contributor.authorPadhan, Hemachandra
dc.contributor.authorKumar Das, Amit
dc.contributor.authorTiwari, Aviral Kumar
dc.contributor.authorGozgor, Giray
dc.contributor.authorJain, Preksha
dc.date.accessioned2025-12-01T07:44:52Z
dc.date.issued2025-01
dc.description.abstractThis paper examines the role of green bonds on industrial sustainability in 15 Organisation for Economic Co-operation and Development (OECD) economies from 2010 to 2020. In this context, we utilise the Augmented Mean Group (AMG), the Artificial Neural Network (ANN), and the Kernel-based Regularised Least Squares (KRLS) methods. It is found that the ANN predicts the influence of green bonds on industrial sustainability more accurately than other methods. It is also observed that green bonds accelerate industrial sustainability in the OECD economies. The upper percentile group is primarily concerned with industrial sustainability rather than the lower- and middle percentile groups. Therefore, the OECD economies should emphasise the green bonds component in the green finance baskets to achieve carbon neutrality.
dc.identifier.issn1878-3384
dc.identifier.urihttps://doi.org/10.1016/j.ribaf.2024.102659
dc.identifier.urihttp://10.0.100.94:4000/handle/123456789/478
dc.language.isoen_US
dc.publisherResearch in International Business and Finance
dc.subjectCarbon neutrality
dc.subjectIndustrial sustainability
dc.subjectGreen bonds
dc.subjectArtificial neural network
dc.subjectOECD economies
dc.titleThe role of green bonds on industrial sustainability for achieving carbon neutrality: Evidence from the artificial neural network method
dc.typeArticle

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