[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2028":3},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":6,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":23,"tags":25,"view_count":31,"doi":32,"paper":33,"created_at":51},2028,"Carbon trading and agricultural green total factor productivity: evidence from China’s pilot carbon market and the mediating role of mechanization","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1922103","Agriculture is both a major source of greenhouse gas emissions and highly vulnerable to climate-related risks, yet the implications of carbon pricing for agricultural sustainability remain insufficiently understood. This study examines the effect of China’s carbon trading pilot policy (CTPP) on agricultural green total factor productivity (AGTFP) using a difference-in-differences (DID) model and panel data covering 30 provinces from 2005 to 2022. AGTFP is measured using the SBM–GML index, with agricultural carbon emissions treated as an undesirable output. The baseline results show that the CTPP increases AGTFP by 0.1351 units, equivalent to 18.3% of the sample mean. Given the staggered adoption of the policy, the robustness of this finding is further assessed using the heterogeneity-robust Callaway–Sant’Anna estimator. The resulting estimate remains positive and statistically significant, although cohort-specific pre-treatment variation warrants cautious interpretation. The mediation results suggest that agricultural mechanization, measured by the comprehensive mechanization rate of crop plowing, sowing, and harvesting (AMR), may constitute a potential transmission channel. The Sobel test provides marginal evidence of an indirect effect at the 10% significance level. Regional estimates are positive and statistically significant in eastern and western China but statistically insignificant in central China. These findings provide new evidence that carbon pricing directed at industrial emitters may generate spillovers to agricultural productivity and highlight the importance of coordinating carbon-market development with sustainable agricultural policy.","农业既是温室气体排放的主要来源，又高度易受气候相关风险的影响，然而碳定价对农业可持续性的影响仍缺乏充分认识。本研究利用双重差分（DID）模型和2005—2022年中国30个省份的面板数据，考察中国碳交易试点政策（CTPP）对农业绿色全要素生产率（AGTFP）的影响。AGTFP采用SBM–GML指数测算，并将农业碳排放作为非期望产出处理。基准结果显示，CTPP使AGTFP提高0.1351个单位，相当于样本均值的18.3%。鉴于该政策为交错实施，本文进一步使用对异质性稳健的Callaway–Sant’Anna估计量评估上述发现的稳健性。所得估计值仍为正且具有统计显著性，但各队列处理前差异需谨慎解读。中介结果表明，以农作物耕种收综合机械化率（AMR）衡量的农业机械化可能构成潜在传导渠道。Sobel检验在10%显著性水平上提供了间接效应存在的边际证据。分区域估计显示，东部和西部地区效应为正且具有统计显著性，中部地区则不具统计显著性。上述发现提供了新证据，表明针对工业排放主体的碳定价可能对农业生产率产生溢出效应，并凸显了协调碳市场发展与可持续农业政策的重要性。",null,"Frontiers in Sustainable Food Systems","2026-09-09T00:00:00Z","论文",10,true,82,{"impact":17,"substance":17,"depth":18,"authority":19,"freshness":20,"relevant":21,"comment":22},22,17,13,8,1,"基于中国碳交易试点与30省面板数据的DID研究，证实碳定价对农业绿色全要素生产率存在正向溢出效应，方法规范、结论有新意，对农业绿色低碳政策有参考价值。",[24],{"name":10,"url":6},[26,27,28,29,30],"农业机械化","农业绿色发展","农业碳排放","绿色全要素生产率","碳交易",0,"10.3389\u002Ffsufs.2026.1922103",{"doi":32,"openalex_id":34,"authors":35,"venue":10,"cited_by_count":31,"oa_url":6,"card":44,"direction":48,"ingested_from":50},"W7211993243",[36,38,41],{"name":37,"orcid":9},"Jiayi Hou",{"name":39,"orcid":40},"Alessandra Castellini","https:\u002F\u002Forcid.org\u002F0000-0002-1750-4817",{"name":42,"orcid":43},"Fujiang Huang","https:\u002F\u002Forcid.org\u002F0000-0001-8567-6867",{"tldr":45,"method":46,"finding":47,"direction":48,"opportunity":49},"评估中国碳交易试点政策对农业绿色全要素生产率的影响及其机械化中介机制。","2005-2022年30省面板数据，SBM-GML测度AGTFP，DID与Cal","碳交易试点使AGTFP提高0.1351单位（约18.3%），机械化是潜在中介，东部和西部显著、中部不","农业绿色发展与碳","可深入探究碳市场对农业的溢出机制，并检验机械化之外的其他中介路径及中部失效原因。","openalex","2026-09-10T23:30:07.179345Z"]