[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-421":3,"related-421":64},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":8,"published_at":11,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":24,"tags":26,"primary_topic":32,"secondary_topics":38,"classification":39,"search_phrases":58,"slug":61,"view_count":62,"doi":8,"paper":8,"created_at":63},421,"Debt financing and agricultural income among large-scale grain producers: evidence from Jiangsu Province, China","https:\u002F\u002Fwww.ebiotrade.com\u002Fnewsf\u002F2026-8\u002F20260806165737778.htm","发表于《Frontiers in Sustainable Food Systems》。基于江苏省LSGPs(大规模粮食生产者)调查数据,构建债务融资—要素投入—农业收入理论框架,从融资规模与融资结构双视角展开实证。研究核心问题:大规模粮食生产者仍面临组织能力弱、生产成本上升与经营效率低等约束,其根源在于自有资本有限与规模经营资本需求之间的错配严重制约农业收入持续增长。高效农村金融市场通过改善投资能力、促进农业现代化与增强风险韧性缓解资本约束,但中国农村金融市场仍存在发展不均与服务供给不足。论文发表于Frontiers in Sustainable Food Systems。",null,"《Frontiers in Sustainable Food Systems》：Debt financing and agricultural income among large-scale grain producers: evidence from Jiangsu Province, China\n\n**编辑推荐：**\n\n实现大规模粮食生产者（large-scale grain producers, LSGPs）农业收入增长对保障粮食安全与促进农业可持续发展至关重要。基于2022年江苏省645户LSGPs调查数据，研究人员采用普通最小二乘法（ordinary least squ\n\n实现大规模粮食生产者（large-scale grain producers, LSGPs）农业收入增长对保障粮食安全与促进农业可持续发展至关重要。基于2022年江苏省645户LSGPs调查数据，研究人员采用普通最小二乘法（ordinary least squares, OLS）、两阶段最小二乘法（two-stage least squares, 2SLS）与中介效应模型，考察债务融资对农业收入的影响、机制及规模边界。结果显示，总信贷、传统信贷、民间信贷与贸易信贷对农业收入呈倒U形影响，而数字信贷（digital credit）具有显著正向影响。机制分析表明，债务融资主要通过转入耕地规模、机械投资与基础设施投资提升农业收入；传统信贷与数字信贷经全部三条渠道起效，贸易信贷经转入耕地规模与机械投资起效，民间信贷主要经转入耕地规模起效。债务融资对农业收入的影响亦存在教育异质性：相较初中及以下学历农户，高中及以上学历农户的总信贷与贸易信贷拐点更高，且数字信贷的正向收入效应更显著。研究发现，金融政策应有序推进数字信贷发展、将债务融资控制在适度区间、强化对生产性投资的支持，并按农户受教育程度提供差异化金融服务。\n\n研究背景方面，增加农业收入是现代农业发展核心目标，对保障粮食安全与推进乡村振兴具有根本意义。规模化经营成为农业现代化关键路径，但大规模粮食生产者（LSGPs）仍面临组织能力弱、生产成本上升与经营效率低等约束，其根源在于自有资本有限与规模经营资本需求之间的错配严重制约农业收入持续增长。高效农村金融市场通过改善投资能力、促进农业现代化与增强风险韧性缓解资本约束，但中国农村金融市场仍存在发展不均与服务供给不足，LSGPs融资需求未根本解决。既有文献沿农户债务融资行为、债务融资对要素投入决策影响、债务融资对农业收入影响三条线索展开，但对规模经营下债务融资是否存在适度边界、不同渠道异质效应及作用机制缺乏系统检验。为此，研究人员利用江苏省LSGPs调查数据构建债务融资—要素投入—农业收入理论框架，从融资规模与融资结构双视角展开实证，论文发表于《Frontiers in Sustainable Food Systems》。\n\n关键技术方法上，研究人员基于2022年江苏省常州、无锡、南通、泰州、淮安、徐州、宿迁七市分层随机抽取645户有效LSGPs样本（以50亩为大规模经营阈值），以农业净收入对数为主被解释变量，以总信贷及传统信贷、数字信贷、民间信贷、贸易信贷四类渠道为解释变量，以转入耕地规模、机械投资、基础设施投资为中介变量，控制户主年龄、教育年限、健康、家庭人口、非农收入、技术示范户、自有耕地、地权稳定性等变量并加入城市固定效应。估计策略依次采用OLS基准回归（含融资一次项与平方项捕捉倒U形）、以前期信贷及其平方项为工具变量的2SLS处理双向因果与遗漏变量偏误、utest与边际效应分析严格检验倒U形、逐步回归结合bootstrap（500次）的中介效应模型，以及按户主受教育年限以9年为切分的异质性分组回归。\n\n研究结果部分，第4.1节基准回归表明，总信贷对农业收入呈倒U形，拐点约121万元，94.88%样本低于拐点；传统信贷、民间信贷、贸易信贷同样倒U形，拐点分别约65万、52万、53万元；数字信贷线性显著为正。第4.2节内生性与稳健性检验中，2SLS以去年信贷及其平方项为工具变量，Hausman与DWH检验确认内生性，一阶段F均超10，结论与OLS一致；utest显示区间内斜率由正转负且极值落Fieller置信区间；边际效应在P25—P90为正、样本最大值转负；对农业收入1%缩尾及控制其他信贷渠道后结果稳健。第4.3节机制分析显示，转入耕地规模对全部四类渠道均具中介效应；机械投资中介传统、贸易、数字信贷，不中介民间信贷；基础设施投资仅中介传统与数字信贷。第4.4节教育异质性表明，总信贷倒U形在两组的拐点分别为117.57万与122.44万元；贸易信贷拐点由49.54万升至60.34万；数字信贷在初中及以下组不显著，在高中及以上组线性显著为正。\n\n讨论与结论翻译部分，研究人员基于江苏省645户LSGPs田野调查数据，使用OLS、2SLS与中介效应模型考察债务融资对农业收入的影响，发现总信贷呈倒U形，数字信贷正向，传统、民间、贸易信贷倒U形，超90%样本低于拐点。机制上转入耕地规模中介全部渠道，机械投资中介传统、贸易、数字信贷，基础设施投资仅中介传统与数字信贷。教育异质性显示高中及以上组总信贷与贸易信贷拐点更高，数字信贷正效应集中于该组。政策含义包括：信贷供给应控于适度区间；有序推进数字信贷并提升LSGPs使用能力；规范民间与贸易信贷互补作用；优化对转入耕地、机械与基础设施的生产性信贷支持；按教育程度提供差异化金融服务。研究局限为截面数据难以捕捉动态长期效应、工具变量排除限制未完全验证、样本仅限江苏需谨慎外推。","Frontiers in Sustainable Food Systems 2026-08-06","2026-08-06T00:00:00Z","论文",10,false,78,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},18,24,20,14,2,1,"基于江苏645户数据，系统考察债务融资对农业收入的影响，方法严谨，结论具有政策参考价值，但时效性稍差。",[25],{"name":10,"url":6},[27,28,29,30,31],"江苏","债务融资","大规模粮食生产者","农业收入","农村金融",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},"G3","rural-finance","农村金融与保险","\u002Ftopic\u002Frural-services\u002Frural-finance","G",[],{"status":40,"locked":14,"version":41,"method":42,"evidence":43},"classified","2026-10-22.2","rules",{"candidates":44,"agricultural_evidence":47},[45,51],{"code":33,"score":46,"supported":47,"title":48,"abstract":49,"tags":50},4,true,[],[31],[31],{"code":52,"score":53,"supported":47,"title":54,"abstract":55,"tags":57},"J2",3,[],[56],"农业现代化",[],[59,60],"大规模粮食生产者 债务融资 农业收入 农村金融","大规模粮食生产者 债务融资","大规模粮食生产者债务融资农业收入农村金融-421",6,"2026-08-11T23:57:03.342056Z",{"total":62,"page":22,"page_size":62,"items":65},[66,147,206,252,307,378],{"id":67,"title":68,"url":69,"summary":70,"summary_zh":71,"content":8,"source_name":72,"source_url":69,"published_at":73,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":74,"score_detail":75,"sources":79,"tags":81,"primary_topic":86,"secondary_topics":87,"classification":88,"search_phrases":120,"slug":123,"view_count":21,"doi":124,"paper":125,"created_at":146},4481,"Climate policy uncertainty and agricultural digital-intelligent transformation in China: evidence from provincial panel data","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1909691","Introduction Climate policy uncertainty can affect long-term investment decisions in agriculture, yet its influence on agricultural digital-intelligent transformation remains insufficiently understood. This study examines how lagged climate policy uncertainty affects agricultural digital-intelligent transformation and whether rural finance and agricultural service policies can moderate this relationship. Methods Using panel data from 31 Chinese provinces from 2013 to 2022, we construct an agricultural digital-intelligent transformation index. A two-way fixed effects model, instrumental variable estimation, heterogeneity analysis, and moderation tests are adopted for empirical analysis. Results The results show that climate policy uncertainty significantly inhibits agricultural digital-intelligent transformation, and this negative effect remains evident after addressing potential endogeneity. Heterogeneity analysis indicates that the inhibitory effect is significant only in regions with moderately developed digital finance and in major grain-consuming areas. Further analysis shows that loans to agriculture, forestry, animal husbandry and fishery industries and the pilot policy for full-process socialized agricultural services positively moderate this relationship and weaken the adverse effect of climate policy uncertainty. Discussion These findings contribute to the literature on climate policy uncertainty and sustainable agricultural transformation by linking policy expectations, agriculture-related loans, and digital-smart agriculture development. The results suggest that stabilizing climate policy expectations, improving rural credit support, and strengthening agricultural service systems are important for promoting climate-resilient and regionally differentiated digital transformation in agriculture.","引言 气候政策不确定性会影响农业的长期投资决策，但其对农业数字化智能化转型的影响尚缺乏充分认识。本研究考察滞后气候政策不确定性如何影响农业数字化智能化转型，以及农村金融和农业服务政策能否调节这一关系。方法 基于2013—2022年中国31个省份的面板数据，构建农业数字化智能化转型指数，采用双向固定效应模型、工具变量估计、异质性分析和调节效应检验进行实证分析。结果 结果表明，气候政策不确定性显著抑制农业数字化智能化转型，且在处理潜在内生性后这一负向效应依然明显。异质性分析表明，该抑制效应仅在数字金融中等发达地区及粮食主销区显著。进一步分析显示，农、林、牧、渔业贷款和农业生产全程社会化服务试点政策对这一关系具有正向调节作用，削弱了气候政策不确定性的不利影响。讨论 这些发现通过将政策预期、涉农贷款与数字智慧农业发展联系起来，为气候政策不确定性与农业可持续转型的文献作出了贡献。结果表明，稳定气候政策预期、完善农村信贷支持、健全农业服务体系，对于促进农业气候韧性型和区域差异化的数字化转型具有重要意义。","Frontiers in Sustainable Food Systems","2026-10-08T00:00:00Z",81,{"impact":17,"substance":76,"depth":17,"authority":20,"freshness":77,"relevant":22,"comment":78},22,9,"基于31省十年面板数据的实证研究，揭示气候政策不确定性对农业数字化智能化转型的抑制效应及农村金融、农业社会化服务的调节作用，方法规范、结论有政策参考价值，值得进入每日精选。",[80],{"name":72,"url":69},[82,83,31,84,85],"数字乡村","智慧农业","农业社会化服务","气候政策",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":89},{"candidates":90,"agricultural_evidence":47},[91,97,103,109,115],{"code":33,"score":92,"supported":47,"title":93,"abstract":94,"tags":96},7,[],[31,95],"rural finance",[31],{"code":98,"score":92,"supported":47,"title":99,"abstract":100,"tags":102},"I1",[],[83,101],"smart agriculture",[83],{"code":104,"score":46,"supported":47,"title":105,"abstract":106,"tags":108},"G2",[],[107],"社会化服务",[84],{"code":110,"score":53,"supported":47,"title":111,"abstract":112,"tags":114},"D",[],[113],"渔业",[],{"code":116,"score":22,"supported":14,"title":117,"abstract":118,"tags":119},"I6",[],[],[82],[121,122],"气候政策不确定性 农业数字化 省级面板","农业数字化智能化转型 农村金融","气候政策不确定性农业数字化省级面板-4481","10.3389\u002Ffsufs.2026.1909691",{"doi":124,"openalex_id":126,"authors":127,"venue":72,"cited_by_count":137,"oa_url":69,"card":138,"direction":144,"ingested_from":145},"W7221013071",[128,131,133,135],{"name":129,"orcid":130},"Wenwen Wang","https:\u002F\u002Forcid.org\u002F0000-0003-1547-5714",{"name":132,"orcid":8},"Yuanyi Yang",{"name":134,"orcid":8},"Yanru Yu",{"name":136,"orcid":8},"Yanwei Zhang",0,{"tldr":139,"method":140,"finding":141,"direction":142,"opportunity":143},"研究气候政策不确定性如何抑制中国农业数字化智能化转型，并检验农村金融与服务政策的调节作用。","2013-2022年31省面板数据，构建农业数字化智能化转型指数，用双向固定效应","气候政策不确定性显著抑制农业数字化智能化转型，该效应仅在数字金融中等发达地区和粮食主销区显著。","数字乡村与农业信息化","可深入探究气候政策预期稳定机制与数字金融、农业社会化服务的协同路径，及区域差异化转型策略。","智慧农业 \u002F 农业物联网","openalex","2026-10-09T23:30:06.185798Z",{"id":148,"title":149,"url":150,"summary":151,"summary_zh":8,"content":8,"source_name":152,"source_url":8,"published_at":153,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":154,"score_detail":155,"sources":158,"tags":160,"primary_topic":164,"secondary_topics":165,"classification":166,"search_phrases":193,"slug":196,"view_count":46,"doi":8,"paper":197,"created_at":205},1508,"金融支持推进乡村全面振兴助力加快农业强国建设——第十九届中国农村金融发展论坛会议综述","https:\u002F\u002Fh.mffb.com.cn\u002Fa\u002F475184.html","综述显示第十九届中国农村金融发展论坛围绕数字金融与共同富裕主题形成以下发现：银行机构数字普惠金融水平对共同富裕具有显著促进作用、金融监管在其中发挥了正向调节效应；契约链主要通过促进社会化服务与缓解信贷约束增收、数字链则通过提升数字素养与扩大金融参与增收；农户参与数字经济通过生产智能化、供销平台化、金融普惠化三维协同机制显著促进财富积累。数字普惠金融通过促进非农就业与提升金融可得性不仅增加了农民收入，还推动了低收入群体收入阶层跃迁。","农业信息网","2026-09-01T00:00:00Z",77,{"impact":19,"substance":19,"depth":17,"authority":156,"freshness":92,"relevant":22,"comment":157},12,"论坛综述提炼了数字普惠金融促进共同富裕的实证结论，对农村金融研究有参考价值。",[159],{"name":152,"url":150},[161,162,163,31],"乡村振兴","共同富裕","数字普惠金融",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":167},{"candidates":168,"agricultural_evidence":47},[169,174,180,184,188],{"code":33,"score":170,"supported":47,"title":171,"abstract":172,"tags":173},13,[31],[31],[31,163],{"code":52,"score":175,"supported":47,"title":176,"abstract":178,"tags":179},8,[177],"农业强国",[],[],{"code":104,"score":53,"supported":47,"title":181,"abstract":182,"tags":183},[],[107],[],{"code":37,"score":22,"supported":14,"title":185,"abstract":186,"tags":187},[],[],[161],{"code":189,"score":22,"supported":14,"title":190,"abstract":191,"tags":192},"G4",[],[],[162],[194,195],"数字普惠金融 乡村振兴 共同富裕 农村金融","数字普惠金融 乡村振兴","数字普惠金融乡村振兴共同富裕农村金融-1508",{"doi":8,"openalex_id":8,"authors":198,"venue":8,"cited_by_count":137,"oa_url":8,"card":199,"direction":142,"ingested_from":204},[],{"tldr":200,"method":201,"finding":202,"direction":142,"opportunity":203},"综述农村金融论坛，探讨数字金融促进共同富裕的机制与效应。","论坛综述，归纳实证研究结论。","数字普惠金融促进共同富裕，金融监管正向调节，多维机制增收。","可深入研究数字普惠金融在农业细分领域的差异化效应及监管适配机制。","agent","2026-09-03T00:06:44.980923Z",{"id":207,"title":208,"url":209,"summary":210,"summary_zh":8,"content":8,"source_name":211,"source_url":8,"published_at":212,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":213,"score_detail":214,"sources":217,"tags":219,"primary_topic":224,"secondary_topics":225,"classification":226,"search_phrases":239,"slug":242,"view_count":137,"doi":243,"paper":244,"created_at":251},5463,"中国粮食生产现代化时空演变特征及影响因素分析 (Spatiotemporal Evolution and Influencing Factors of Grain Production Modernization in China)","http:\u002F\u002Fzgnjhxb.niam.com.cn\u002FCN\u002F10.13733\u002Fj.jcam.issn.2095-5553.2026.10.042","基于2011—2023年省级面板数据，六维构建粮食生产现代化指标，用核密度、空间自相关与GTWR分析。水平稳步提升，呈主产区＞主销区＞产销平衡区梯度；山东、江苏、安徽形成稳定高—高集聚区。数字普惠金融与财政支农正向。","中国农机化学报 2026-10-20","2026-10-20T00:00:00Z",79,{"impact":17,"substance":215,"depth":17,"authority":170,"freshness":77,"relevant":22,"comment":216},21,"基于省级面板数据构建六维指标并采用GTWR方法，结论对粮食生产现代化区域差异与数字普惠金融作用有参考价值，但属学术论文，公共影响有限。",[218],{"name":211,"url":209},[220,221,163,222,223],"粮食安全","财政支农","粮食生产现代化","空间集聚",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":227},{"candidates":228,"agricultural_evidence":47},[229,234],{"code":33,"score":230,"supported":47,"title":231,"abstract":232,"tags":233},5,[],[221],[163,221],{"code":235,"score":22,"supported":14,"title":236,"abstract":237,"tags":238},"A8",[],[],[220],[240,241],"粮食生产现代化 时空演变","数字普惠金融 粮食生产","粮食生产现代化时空演变-5463","10.13733\u002Fj.jcam.issn.2095-5553.2026.10.042",{"doi":243,"openalex_id":8,"authors":245,"venue":8,"cited_by_count":137,"oa_url":8,"card":246,"direction":142,"ingested_from":204},[],{"tldr":247,"method":248,"finding":249,"direction":142,"opportunity":250},"构建六维指标测度2011—2023年中国粮食生产现代化水平并分析其时空演变与影响因素。","省级面板数据，六维指标体系，核密度、空间自相关与GTWR模型。","现代化水平稳步提升，呈主产区>主销区>产销平衡区梯度，山东、江苏、安徽为稳定高—高集聚区。","可探究数字普惠金融与财政支农的协同机制，并细化到县域尺度检验空间溢出效应。","2026-10-21T00:10:08.522187Z",{"id":253,"title":254,"url":255,"summary":256,"summary_zh":8,"content":8,"source_name":257,"source_url":8,"published_at":258,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":259,"score_detail":260,"sources":262,"tags":264,"primary_topic":269,"secondary_topics":270,"classification":277,"search_phrases":293,"slug":296,"view_count":21,"doi":297,"paper":298,"created_at":306},4730,"政策型农业信贷担保能否激励农户采纳秸秆还田技术","https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1948304\u002Ffull","基于微观数据与变量法,实证评估政策型农业信贷担保对农户采纳秸秆还田技术的影响。研究发现该政策显著促进采纳,主要通过推动社会化服务购买与绿色信贷期限匹配生产周期实现,对数字素养较高、正式社会资本匮乏的农户效应更强","Frontiers in Sustainable Food Systems 2026-10-09","2026-10-09T00:00:00Z",80,{"impact":17,"substance":76,"depth":17,"authority":20,"freshness":175,"relevant":22,"comment":261},"基于微观数据的实证研究，揭示政策型信贷担保通过社会化服务与绿色信贷期限匹配促进秸秆还田，结论具政策参考价值。",[263],{"name":257,"url":255},[107,265,266,267,268],"秸秆还田","农业信贷担保","绿色金融","农户技术采纳",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[271],{"code":272,"slug":273,"name":274,"path":275,"parent_code":276},"H5","waste","面源污染与废弃物利用","\u002Ftopic\u002Fenvironment\u002Fwaste","H",{"status":40,"locked":14,"version":41,"method":42,"evidence":278},{"candidates":279,"agricultural_evidence":47},[280,285,289],{"code":33,"score":170,"supported":47,"title":281,"abstract":283,"tags":284},[282],"农业信贷",[282],[266,267],{"code":272,"score":156,"supported":47,"title":286,"abstract":287,"tags":288},[265],[265],[265],{"code":104,"score":46,"supported":47,"title":290,"abstract":291,"tags":292},[],[107],[107],[294,295],"农业信贷担保 秸秆还田","绿色信贷 农户 技术采纳","农业信贷担保秸秆还田-4730","10.3389\u002Ffsufs.2026.1948304\u002Ffull",{"doi":297,"openalex_id":8,"authors":299,"venue":8,"cited_by_count":137,"oa_url":8,"card":300,"direction":304,"ingested_from":204},[],{"tldr":301,"method":302,"finding":303,"direction":304,"opportunity":305},"实证评估政策型农业信贷担保对农户采纳秸秆还田技术的影响。","基于微观数据与变量法进行实证分析。","政策显著促进采纳，通过社会化服务购买与绿色信贷期限匹配实现。","农业绿色发展与碳","可探究数字素养与信贷担保协同机制，及对异质性农户的精准政策设计。","2026-10-12T00:11:14.617567Z",{"id":308,"title":309,"url":310,"summary":311,"summary_zh":312,"content":8,"source_name":72,"source_url":310,"published_at":313,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":314,"score_detail":315,"sources":319,"tags":321,"primary_topic":326,"secondary_topics":327,"classification":333,"search_phrases":353,"slug":356,"view_count":53,"doi":357,"paper":358,"created_at":377},4289,"When climate risk intensifies, does insurance pay off? A community case study of China's agricultural insurance reform","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1954205","In the context of mounting global climate threats, fostering resilience in food production systems has become a critical imperative for upholding national food security. This paper exploits the staggered implementation, beginning in 2018, of China's agricultural insurance reforms covering full production costs and planting income as a quasi-natural experiment. Drawing on provincial panel data from 2013 to 2024, we first develop a multidimensional composite index to capture food production resilience. A staggered difference-in-differences specification is then adopted to systematically assess the causal effect of these reforms on such resilience and to explore the underlying transmission channels. Moreover, from a novel climate change perspective, the analysis examines the heterogeneous treatment effects across varying degrees of climate risk exposure. The empirical findings reveal that the policy-led agricultural insurance reform significantly and robustly enhances China's food production resilience. Mechanism tests indicate that advances in agricultural technology and the expansion of large-scale farming operations serve as important pathways through which the insurance policy takes effect. Further investigation shows that climate change risk positively moderates the policy impact: as climate risk intensifies, the marginal contribution of insurance to resilience becomes stronger. Heterogeneity analysis also demonstrates that the policy effect is more pronounced in western China and in localities with higher rates of disaster-induced losses. Taken together, these results offer solid empirical backing for broadening the pilot programs of full cost and planting income insurance. They also establish a theoretical basis for positioning publicly supported agricultural insurance as an effective instrument for climate change adaptation, providing valuable guidance on strengthening the climate adaptability and resilience of food production to ensure national food security.","在全球气候威胁日益加剧的背景下，增强粮食生产系统的韧性已成为维护国家粮食安全的关键任务。本文以2018年起分阶段实施的中国农业保险覆盖完全生产成本和种植收入的改革为准自然实验，基于2013—2024年省级面板数据，首先构建多维复合指数以刻画粮食生产韧性，继而采用交错双重差分模型系统评估该改革对粮食生产韧性的因果效应并探究其传导机制。此外，本文从气候变化这一新视角出发，考察了不同气候风险暴露程度下的异质性处理效应。实证结果表明，政策主导的农业保险改革显著且稳健地提升了中国粮食生产韧性。机制检验表明，农业技术进步与规模化经营扩张是保险政策发挥作用的重要路径。进一步研究发现，气候变化风险对政策效应具有正向调节作用：随着气候风险加剧，保险对韧性的边际贡献增强。异质性分析还表明，政策效应在中国西部地区以及灾害损失率较高的地区更为显著。综上，上述结果为扩大完全成本保险和种植收入保险试点提供了坚实的经验依据，也为将公共支持的农业保险定位为气候变化适应的有效工具奠定了理论基础，为增强粮食生产的气候适应性与韧性、保障国家粮食安全提供了有价值的政策启示。","2026-10-05T00:00:00Z",88,{"impact":18,"substance":316,"depth":317,"authority":20,"freshness":175,"relevant":22,"comment":318},23,19,"基于2013-2024年省级面板数据的交错DID准自然实验，证实农业保险改革显著提升粮食生产韧性且气候风险具有正向调节作用，方法规范、结论可靠，对完善农业保险试点具有政策参考价值。",[320],{"name":72,"url":310},[220,322,323,324,325],"农业保险","农业政策","气候适应","生产韧性",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[328],{"code":329,"slug":330,"name":331,"path":332,"parent_code":276},"H7","climate","气候适应与防灾减灾","\u002Ftopic\u002Fenvironment\u002Fclimate",{"status":40,"locked":14,"version":41,"method":42,"evidence":334},{"candidates":335,"agricultural_evidence":47},[336,342,348],{"code":33,"score":337,"supported":47,"title":338,"abstract":340,"tags":341},15,[339],"agricultural insurance",[322,339],[322],{"code":329,"score":13,"supported":47,"title":343,"abstract":344,"tags":347},[],[345,324,346],"气候变化","climate change",[324],{"code":235,"score":92,"supported":47,"title":349,"abstract":350,"tags":352},[],[220,351],"food security",[220],[354,355],"农业保险改革 粮食生产韧性","完全成本保险 种植收入保险","农业保险改革粮食生产韧性-4289","10.3389\u002Ffsufs.2026.1954205",{"doi":357,"openalex_id":359,"authors":360,"venue":72,"cited_by_count":137,"oa_url":310,"card":372,"direction":304,"ingested_from":145},"W7220367453",[361,364,366,368,370],{"name":362,"orcid":363},"Changzhe Deng","https:\u002F\u002Forcid.org\u002F0009-0006-0852-5997",{"name":365,"orcid":8},"Maimiao Sun",{"name":367,"orcid":8},"Xueyu Lin",{"name":369,"orcid":8},"Chencan Rao",{"name":371,"orcid":8},"Qiuping Guo",{"tldr":373,"method":374,"finding":375,"direction":304,"opportunity":376},"基于2013-2024省级面板数据，评估中国农业保险改革对粮食生产韧性的因果影响。","多维度韧性指数+交错双重差分，利用2018年起保险改革试点作准自然实验。","保险改革显著提升粮食生产韧性，气候风险越高其边际贡献越强，西部和灾损高地区效果更明显。","可探究保险改革与农业技术、规模化经营的协同机制，及气候风险下保险产品设计与精准赔付的优化路径。","2026-10-06T23:30:05.886883Z",{"id":379,"title":380,"url":381,"summary":382,"summary_zh":8,"content":383,"source_name":384,"source_url":8,"published_at":385,"category":386,"cover_url":8,"hotness":13,"is_selected":47,"score":387,"score_detail":388,"sources":391,"tags":393,"primary_topic":397,"secondary_topics":398,"classification":399,"search_phrases":414,"slug":417,"view_count":22,"doi":8,"paper":8,"created_at":418},4249,"四部门联合印发加快农业保险高质量发展实施方案","https:\u002F\u002Fwww.fengxin.gov.cn\u002Ffxxrmzf\u002Fzfcgxgxx\u002Fpc\u002Fcontent\u002F2104516031187619840\u002Fcontent_2104516031187619840.html","财政部会同农业农村部、金融监管总局、国家林草局联合印发财金〔2026〕88号《关于加快农业保险高质量发展的实施方案》，是我国农业保险近二十年发展经验的提炼。我国农业保险保费规模从2007年52亿元增长到2025年超1550亿元，每年可为上亿户次农户提供风险保障超5万亿元。","为推动农业保险政策更加普惠、区域发展更加均衡、保障质效持续提升，本次《实施方案》明确了下一阶段发展目标：到2030年，基本建成与农户风险保障需求相契合、与现代农业发展相适应、中央与地方分工负责的多层次农业保险体系，总体达到国际先进水平，实现补贴有效率、产业有保障、农民得实惠、机构可持续的多赢格局。\n\n2019年出台的指导性文件提出了到2022年农业保险深度1%、密度500元\u002F人、三大粮食作物保险覆盖率70%以上等阶段性目标。在此基础上，《实施方案》进一步明确如下发展目标：一是“农业保险深度”，即农业保险保费与第一产业增加值的比值，反映农业保险对农村经济发展的贡献，2030年前达到1.9%。二是“农业保险密度”，即农业保险保费与第一产业就业人员数量的比值，反映农业保险人均惠及保障程度，2030年前达到1200元\u002F人。三是“农业保险科技投入强度”，即农业保险机构科技创新投入与农业保险保费的比值，反映农业保险行业科技创新应用水平，2030年前达到1%。其中，农业保险科技创新投入主要包括农业保险科技工作人员支出、科技服务费用、科技类无形资产和固定资产等项目。四是“三大粮食作物保险覆盖率”，对于关系国计民生和粮食安全的三大粮食作物，全国范围内农业保险覆盖率稳定在90%左右，各省份结合实际制定相关目标。同时，提升地方优势特色农业保险对特色农业产业的保障水平，更好发挥富农强农作用。五是“农业保险综合费用率”，强调不得高于20%，引导农业保险承保机构切实降本增效，将更多资源用于风险保障和理赔服务上。","奉新县人民政府 转载财政部金融司 2026-10-01","2026-10-01T01:00:00Z","政策",92,{"impact":389,"substance":18,"depth":317,"authority":337,"freshness":62,"relevant":22,"comment":390},28,"四部门联合印发的全国性农业保险新政，明确2030年保险深度1.9%、密度1200元\u002F人等量化目标，政策条款与数据增量突出，权威性和专业深度俱佳，值得进入每日精选。",[392],{"name":384,"url":381},[220,394,322,395,396],"惠农政策","农业科技投入","风险保障",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":400},{"candidates":401,"agricultural_evidence":47},[402,406,410],{"code":33,"score":156,"supported":47,"title":403,"abstract":404,"tags":405},[322],[322],[322],{"code":235,"score":22,"supported":14,"title":407,"abstract":408,"tags":409},[],[],[220],{"code":52,"score":22,"supported":14,"title":411,"abstract":412,"tags":413},[],[],[395],[415,416],"三大粮食作物保险覆盖率 90%","农业科技投入 农业保险 惠农政策 粮食安全","三大粮食作物保险覆盖率90%-4249","2026-10-06T00:04:59.342384Z"]