RESUMEN
Certain nations have opted for stimulus-based regulations to curtail emissions, build a liveable, environmentally friendly setting, and work towards aspirational mitigation targets. New Zealand (NZ) prefers an Emission Trading Scheme (ETS) to taxation, mitigating emissions on one hand while retaining incentives for economic growth on the other. As a result, NZ has initiated a legal framework since 2008 to allow its economic sectors to engage in ETS and minimize emissions. Yet, selecting the appropriate sectors and effectively adjusting sector-specific regulations remain critical and complex challenges in the global design of ETS since both excessive and insufficient intervention can lead to inefficiencies in the system's functioning. Therefore, this study begins validating the NZ ETS's abatement potential regarding sectoral carbon intensity by executing the double machine learning techniques, consolidating the ETS efficacy that has robustly mitigated sectoral carbon intensity in NZ during 2006-2020. However, this conclusion seems invalid at the disaggregated level when focusing on forward-backward linkages, where NZ's input-output tables furnish a compelling scenario of sectoral dependencies and the products (residuals) they provide. Altogether, the regulatory requirements are either too strict or too lax, leaving out five of the 24 (as a whole) key sectors. Rather, the ETS could be powerful, providing these five key sectors are well tackled, necessitating a reformulation of the ongoing ETS regulatory regime.
Asunto(s)
Gases de Efecto Invernadero , Nueva Zelanda , Desarrollo Económico , Carbono/análisis , Dióxido de Carbono/análisis , ChinaRESUMEN
In the context of globalization, the role of the digital economy in carbon emissions may generate spatial spill over effects. This study comprehensively applies a spatial model to understand the nexus between the digital economy and carbon emissions in 67 economies from 2010 to 2019. Specifically, this study contributes by introducing a spatial panel threshold model, which helps to present the new evidence regarding decarbonization process. Empirical findings exemplify that the digital economy remarkably reduces local carbon emissions, with the positive spatial spill over effects being salient. The spatial moderating effect model uncover that globalization positively affects the nexus between the digital economy and carbon emissions. Interestingly, the spatial panel threshold model designates that the digital economy's reduction effect on local carbon emissions will be tightened, whereas the positive spatial spill over effects turn negative only when globalization surpasses a threshold. Our model has the potential to explain some results that traditional models cannot reach.