本文利用卫星监测的数据构造夜间灯光复合指数表征城镇化水平,运用Superefficiency Ray Slacks-Based Measure(Super-RSBM)模型和Global Malmquist-Luenberger(GML)指数测算2000—2021年我国农业低碳全要素生产率(TFP),实证检验城镇化...本文利用卫星监测的数据构造夜间灯光复合指数表征城镇化水平,运用Superefficiency Ray Slacks-Based Measure(Super-RSBM)模型和Global Malmquist-Luenberger(GML)指数测算2000—2021年我国农业低碳全要素生产率(TFP),实证检验城镇化对我国农业低碳TFP的影响及其作用机制,并考察紧凑集约型和规模扩张型两种城镇化推进模式对农业低碳TFP的异质性影响。研究发现,从全国来看,城镇化推进与农业低碳TFP之间具有显著的U型关系,且邻近地区农业低碳TFP的提升对本地区产生示范效应;分区域来看,这种U型关系主要体现在农业适度发展区,而农业优化发展区的城镇化与农业低碳TFP之间呈现显著的正向线性关系,表明农业优化发展区应发挥“领头羊”作用,带动适度发展区早日跨越U型曲线的拐点,实现城镇化带动农业绿色发展;紧凑集约型的城镇化深度推进模式能够显著提升农业低碳TFP,而规模扩张型的城镇化广度推进模式降低了农业低碳TFP;农业低碳技术进步、农村劳动力转移、规模效应、农业产业链延伸和农村居民可支配收入增加是城镇化影响农业低碳TFP的主要途径。展开更多
China has recently implemented a dual-carbon strategy to combat climate change and other environmental issues and is committed to modernizing it sustainably.This paper supports these goals and explores how the digital...China has recently implemented a dual-carbon strategy to combat climate change and other environmental issues and is committed to modernizing it sustainably.This paper supports these goals and explores how the digital economy and green finance intersect and impact carbon emissions.Using panel data from 30 Chinese provinces over the period 2011-2021,this paper finds that the digital economy and green finance can together reduce carbon emissions,and conducts several robustness tests supporting this conclusion.A heterogeneity analysis shows that these synergistic effects are more important in regions with low levels of social consumption Meanwhile,in the spatial dimension,the synergistic effect of the local digital economy and green finance adversely impacts the level of carbon emissions in surrounding areas.The findings of this paper provide insights for policymakers in guiding capital flow and implementing carbon-reduction policies while fostering the growth of China’s digital economy and environmental sustainability.展开更多
文摘本文利用卫星监测的数据构造夜间灯光复合指数表征城镇化水平,运用Superefficiency Ray Slacks-Based Measure(Super-RSBM)模型和Global Malmquist-Luenberger(GML)指数测算2000—2021年我国农业低碳全要素生产率(TFP),实证检验城镇化对我国农业低碳TFP的影响及其作用机制,并考察紧凑集约型和规模扩张型两种城镇化推进模式对农业低碳TFP的异质性影响。研究发现,从全国来看,城镇化推进与农业低碳TFP之间具有显著的U型关系,且邻近地区农业低碳TFP的提升对本地区产生示范效应;分区域来看,这种U型关系主要体现在农业适度发展区,而农业优化发展区的城镇化与农业低碳TFP之间呈现显著的正向线性关系,表明农业优化发展区应发挥“领头羊”作用,带动适度发展区早日跨越U型曲线的拐点,实现城镇化带动农业绿色发展;紧凑集约型的城镇化深度推进模式能够显著提升农业低碳TFP,而规模扩张型的城镇化广度推进模式降低了农业低碳TFP;农业低碳技术进步、农村劳动力转移、规模效应、农业产业链延伸和农村居民可支配收入增加是城镇化影响农业低碳TFP的主要途径。
文摘China has recently implemented a dual-carbon strategy to combat climate change and other environmental issues and is committed to modernizing it sustainably.This paper supports these goals and explores how the digital economy and green finance intersect and impact carbon emissions.Using panel data from 30 Chinese provinces over the period 2011-2021,this paper finds that the digital economy and green finance can together reduce carbon emissions,and conducts several robustness tests supporting this conclusion.A heterogeneity analysis shows that these synergistic effects are more important in regions with low levels of social consumption Meanwhile,in the spatial dimension,the synergistic effect of the local digital economy and green finance adversely impacts the level of carbon emissions in surrounding areas.The findings of this paper provide insights for policymakers in guiding capital flow and implementing carbon-reduction policies while fostering the growth of China’s digital economy and environmental sustainability.