College of Transport & Communications, Shanghai Maritime University, Shanghai, China.
College of Transport & Communications, Shanghai Maritime University, Shanghai, China.
Mar Pollut Bull. 2023 Apr;189:114730. doi: 10.1016/j.marpolbul.2023.114730. Epub 2023 Feb 15.
The COVID-19 epidemic made the most countries to take strict lockdown measures, what has seriously caused an unprecedented impact in the shipping industries, whereas these measures have also played a significant impact to control carbon emissions from international shipping. Here, we try to use the threshold generalized autoregressive conditional heteroscedasticity and the exponential generalized autoregressive heteroscedasticity to investigate whether the fluctuations of the control variable on carbon emissions from international shipping are asymmetric or not. On this basis, the GARCH-MIDAS model is introduced to discuss whether the newly confirmed cases are independent of control variables and have an impact on the fluctuation of carbon emissions. From the results, we find that the information contained in the newly confirmed cases cannot be covered when adding the other control variables. In addition, the newly confirmed cases have a negative impact on the volatility of carbon emissions, while the other control variables significantly increase carbon emissions. This study provides a quantitative research method for the analysis of the volatility and impact factors on international shipping carbon emissions, which helps to formulate more reasonable emission reduction measures and promote the low-carbon transformations of the global shipping industry.
新冠疫情大流行使大多数国家采取了严格的封锁措施，这对航运业造成了前所未有的影响，而这些措施也对控制国际航运的碳排放产生了重大影响。在这里，我们尝试使用门限广义自回归条件异方差和指数广义自回归异方差来研究国际航运碳排放的控制变量波动是否具有非对称性。在此基础上，引入 GARCH-MIDAS 模型来讨论新确诊病例是否独立于控制变量，以及对碳排放波动是否有影响。结果表明，在添加其他控制变量时，无法涵盖新确诊病例中包含的信息。此外，新确诊病例对碳排放波动有负面影响，而其他控制变量则显著增加了碳排放。本研究为分析国际航运碳排放的波动性和影响因素提供了定量研究方法，有助于制定更合理的减排措施，推动全球航运业的低碳转型。
