Suchergebnisse

Several developing economies have announced carbon emissions targets for 2020 as part of the negotiating process for a post-Kyoto climate policy regime. China and India's commitments are framed as reductions in the emissions intensity of the economy by 40-45% and 20-25%, respectively, between 2005 and 2020. How feasible are the proposed reductions in emissions intensity for China and India, and how do they compare with the targeted reductions in the US and the EU? In this paper, we use a stochastic frontier model of energy intensity to decompose energy intensity into the effects of input and output mix, climate, and a residual technology variable. We use the model to produce emissions projections for China and India under a number of scenarios regarding the pace of technological change and changes in the share of non-fossil energy. We find that China is likely to need to adopt ambitious carbon mitigation policies in order to achieve its stated target, and that its targeted reductions in emissions intensity are on par with those implicit in the US and EU targets. India's target is less ambitious and might be met with only limited or even no dedicated mitigation policies.

Several developing economies have announced carbon emissions targets for 2020 as part of the negotiating process for a post-Kyoto climate policy regime. China and India's commitments are framed as reductions in the emissions intensity of the economy by 40-45% and 20-25%, respectively, between 2005 and 2020. How feasible are the proposed reductions in emissions intensity for China and India, and how do they compare with the targeted reductions in the US and the EU? In this paper, we use a stochastic frontier model of energy intensity to decompose energy intensity into the effects of input and output mix, climate, and a residual technology variable. We use the model to produce emissions projections for China and India under a number of scenarios regarding the pace of technological change and changes in the share of non-fossil energy. We find that China is likely to need to adopt ambitious carbon mitigation policies in order to achieve its stated target, and that its targeted reductions in emissions intensity are on par with those implicit in the US and EU targets. India's target is less ambitious and might be met with only limited or even no dedicated mitigation policies.

AbstractIn empirical studies, the disparity between financial development and environmental quality has prompted us to examine the impact of credit growth on environmental quality in ASEAN countries. These countries have experienced phenomenal credit growth over the past three decades due to their adoption of financial liberalisation, integration and innovation. In this study, we investigated the role of credit growth on environmental quality while controlling for several macroeconomic variables, including regulatory quality, natural resources, foreign direct investment, globalisation and per capita gross domestic product growth. Using static models (ordinary least square [OLS], random effect model, Panel Corrected Standard Error and partial spatial cross correlation) and dynamic models (dynamic OLS, dynamic random effect and two‐step system generalised methods of moments (GMM) on data spanning from 1984 to 2019, we observed a nonlinear association between credit growth and environmental quality. The findings suggest that credit growth may simultaneously have favourable and detrimental effects on environmental quality. High credit growth can lead to increased emissions and environmental degradation through the promotion of fossil fuel‐driven energy consumption, production and distribution of economic resources. However, if the government promotes regulatory quality and encourages lenders to invest more in green technologies and renewable and sustainable energy sources, credit growth may contribute to improved environmental quality. These results carry important policy implications.

In order to maintain the 2°C climate change target, global carbon intensity of electricity generation needs to achieve a short-term target of 600 g/kWh by 2020. This target is important for China, which has been the largest consumer and producer of electricity since 2011. China has set ambitious targets to reduce its electricity carbon intensity in the 13th five-year plan. For a country as large as China, the outcomes of these policies rely on the implementation strategies and effectiveness of each province. In this study, we estimate the carbon intensities of power generation in China's provinces by 2020. Results show that despite progress in renewable energy growth most provinces are expected to have carbon intensities well above 600 g/kWh by 2020. Renewable energy sources can help reduce carbon intensities in most provinces, but the magnitude of such impacts depends on the coordination among provinces. The over-dependence on coal power generation has made carbon capture and storage a necessity for China's provinces to reduce their carbon intensity for power generation. Therefore, government support should be addressed sooner rather than later.

In order to maintain the 2°C climate change target, global carbon intensity of electricity generation needs to achieve a short-term target of 600 g/kWh by 2020. This target is important for China, which has been the largest consumer and producer of electricity since 2011. China has set ambitious targets to reduce its electricity carbon intensity in the 13th five-year plan. For a country as large as China, the outcomes of these policies rely on the implementation strategies and effectiveness of each province. In this study, we estimate the carbon intensities of power generation in China's provinces by 2020. Results show that despite progress in renewable energy growth most provinces are expected to have carbon intensities well above 600 g/kWh by 2020. Renewable energy sources can help reduce carbon intensities in most provinces, but the magnitude of such impacts depends on the coordination among provinces. The over-dependence on coal power generation has made carbon capture and storage a necessity for China's provinces to reduce their carbon intensity for power generation. Therefore, government support should be addressed sooner rather than later.

AbstractThe study explores the effects of duration of team governance (DTG) on carbon emission intensity of 608 U.S. listed corporations merged three official datasets of Carbon Disclosure Project (CDP), Compuatat and BoardEx over the period 2009–2018, using unbalanced panel data analysis. It bridges three theoretical approaches: group development theory (GDT), social identity theory (SIT) and resource dependence theory (RDT) and applies econometric analysis techniques to investigate corporate carbon emission intensity. The result shows an inverted U‐shaped relationship between DTG and carbon emission intensity. It is interesting that carbon emission intensity increased when the duration is less than 6.52 years, however, the duration exceeds 6.52 years decreases carbon emission intensity. We also find other factors of team size and gender diversity moderate the U‐shaped relationship, further testing the optimal team of 8–11 members and 3–4 women members. Meanwhile, the finding shows that the low‐carbon innovation is an effective mediator for DTG to decrease carbon emission intensity. The paper is important for managerial implication and policy making.