中国出口贸易隐含碳的趋势预测及结构转移研究OA北大核心CSTPCD
Research on the trend prediction and structure transfer of embodied carbon in China's export trade
基于特征选择的Lasso方法分别确定影响中国出口贸易隐含碳排放(CO2)总量和强度的核心指标,并由此构建BO-BiLSTM模型对总量变动和强度演进的趋势展开预测,同时采用Markov链进一步探讨中国出口贸易隐含碳排放的结构转移现象.结果表明:(1)2021-2035年间中国出口贸易隐含碳排放总量呈现阶梯式减少的趋向,预计2030年达到1.98 Gt,在 2035年降为1.83 Gt,出口贸易规模扩大和国际经贸形势改善是关键影响因素.(2)2021…查看全部>>
Based on the Lasso method of feature selection,the core indicators affecting the total amount and intensity of embodied carbon emissions(CO2)in China's export trade are determined respectively,and the BO-BiLSTM model was constructed to predict the trend of total amount change and intensity evolution.At the same time,the Markov chain was used to further explore the structural transfer phenomenon of embodied carbon emissions in China's export trade.The results…查看全部>>
胡剑波;麦骏南
贵州财经大学经济学院,贵阳 550025贵州财经大学大数据应用与经济学院,贵阳 550025
出口贸易隐含碳投入产出模型机器学习预测
Export trade embodied carbonInput-output modelMachine learning prediction
《气候变化研究进展》 2024 (1)
62-74,13
国家社会科学基金项目"中国隐含碳全要素生产率动态演进与提升策略研究"(23XJY022)
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