[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-3365":3,"related-3365":54},{"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":24,"tags":26,"search_phrases":32,"slug":35,"view_count":36,"doi":37,"paper":38,"created_at":53},3365,"The Impact of Agricultural Digitization on Green Total Factor Productivity in Agriculture: Evidence from 30 Provinces in China","https:\u002F\u002Fdoi.org\u002F10.3390\u002Fsu18199758","Amid tighter resource and environmental limits in China, the integration of digitization and greening gives new momentum to sustainable agriculture; however, its methods and structural conditions remain unclear. This study utilizes provincial panel data from 2011–2023 and the super-efficiency SBM-GML model to estimate agricultural green total factor productivity (AGTFP). It empirically examines the green empowerment effect of agricultural digitization, its transmission pathways, and structural boundaries. Unlike existing studies that rely on input-oriented or rural-level digitalization measures and qualitative regional groupings, this study constructs an agriculture-specific index, identifies agricultural socialized services (ASS) as an organizational channel, examines the moderating role of environmental regulation, and uses a continuous threshold variable to identify the structural breakpoint at which digitization’s green effect changes. The findings indicate that digitization considerably enhances AGTFP, and this association remains stable across a range of robustness checks. Mechanism analysis indicates that ASS partially mediates this effect, while environmental regulation intensity positively moderates the relationship. Heterogeneity and threshold analyses show that the empowering effect is only significant in the eastern region, but not in the central and western regions; it is significant in the main grain-producing areas. Moreover, a tentative structural breakpoint is identified when the grain-sown area proportion reaches 0.486. Since this threshold is statistically significant only at the 10% level, it should be regarded as preliminary evidence. Accordingly, we recommend regionally differentiated digital agriculture strategies, strengthening the socialized agricultural service system, and enhancing synergy between environmental regulation and digital empowerment to effectively advance the green transformation of China’s agriculture.","在中国资源与环境约束趋紧的背景下，数字化与绿色化的融合为可持续农业注入了新动力；然而，其实现路径与结构性条件仍不明确。本研究利用2011—2023年省级面板数据和超效率SBM-GML模型测算农业绿色全要素生产率（AGTFP），实证检验了农业数字化的绿色赋能效应、传导路径及结构边界。与现有研究依赖投入导向或农村层面数字化指标以及定性区域分组不同，本研究构建了农业专属指数，识别出农业社会化服务（ASS）作为组织化渠道，考察了环境规制的调节作用，并使用连续门槛变量识别数字化绿色效应发生变化的结构性断点。研究发现，数字化显著提升了AGTFP，且该关联在一系列稳健性检验中保持稳定。机制分析表明，ASS在其中发挥部分中介作用，而环境规制强度正向调节该关系。异质性与门槛分析显示，赋能效应仅在东部地区显著，在中西部地区不显著；在粮食主产区显著。此外，当粮食播种面积占比达到0.486时，识别出一个初步的结构性断点。由于该门槛仅在10%水平上统计显著，应将其视为初步证据。据此，我们建议采取区域差异化的数字农业策略，强化农业社会化服务体系，并增强环境规制与数字赋能之间的协同效应，以有效推进中国农业绿色转型。",null,"Sustainability","2026-09-23T00:00:00Z","论文",10,false,85,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},22,23,18,14,8,1,"基于30省面板数据的实证研究，方法规范、结论有政策参考价值，但属学术论文且时效性一般，适合主题聚合而非每日精选头条。",[25],{"name":10,"url":6},[27,28,29,30,31],"农业绿色发展","农业数字化","粮食主产区","农业社会化服务","环境规制",[33,34],"农业数字化 绿色全要素生产率","农业社会化服务 环境规制","农业数字化绿色全要素生产率-3365",0,"10.3390\u002Fsu18199758",{"doi":37,"openalex_id":39,"authors":40,"venue":10,"cited_by_count":36,"oa_url":6,"card":45,"direction":51,"ingested_from":52},"W7214071788",[41,43],{"name":42,"orcid":9},"Zhaojuan Meng",{"name":44,"orcid":9},"Guixiang Lin",{"tldr":46,"method":47,"finding":48,"direction":49,"opportunity":50},"基于2011–2023年省级面板数据，检验农业数字化对农业绿色全要素生产率的赋能效应、机制与结构边界","超效率SBM-GML测算AGTFP，构建农业专属数字化指数，中介、调节与连续门槛","数字化显著提升AGTFP，农业社会化服务部分中介，环境规制正向调节，效应仅东部和主产区显著。","农业绿色发展与碳","可深入探究中西部数字化绿色效应缺失的组织与市场条件，并验证粮食播种面积占比0.486的结构断点。","数字乡村与农业信息化","openalex","2026-09-24T23:30:25.917176Z",{"total":55,"page":22,"page_size":55,"items":56},6,[57,103,133,162,210,246],{"id":58,"title":59,"url":60,"summary":61,"summary_zh":62,"content":9,"source_name":63,"source_url":60,"published_at":64,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":65,"score_detail":66,"sources":69,"tags":71,"search_phrases":75,"slug":78,"view_count":36,"doi":79,"paper":80,"created_at":102},3193,"Does Agricultural Unmanned Aerial Vehicle Use Improve Grain Production Efficiency? Evidence from Rural China","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.foodpol.2026.103196","Enhancing grain production efficiency (GPE) is critical for ensuring food security and promoting a more resource-efficient agricultural transformation, particularly in smallholder systems where conventional machinery faces scale and terrain constraints. China’s rapid adoption of agricultural Unmanned Aerial Vehicles (UAVs) offers an opportunity to assess whether digital machinery can improve efficiency without relying on farm expansion. Yet evidence on how UAV use intensity affects GPE, and on the conditions under which gains emerge, remains limited. Using data from 2,030 grain-producing households across nine provinces in the 2022 China Rural Revitalisation Survey, we measure GPE using a super-efficiency slacks-based measure model and estimate the effects of UAV use intensity. The results show a significant U-shaped relationship between UAV use intensity and GPE, with efficiency gains emerging only after UAV use intensity exceeds a certain threshold. UAV use affects GPE primarily through labour substitution and is nonlinearly associated with pesticide inputs. Besides, village-level agricultural service organisations strengthen the positive effects of UAV use, indicating that service provision complements the use of technology. The efficiency effects are stronger in western China and rice production systems, where conventional machinery is relatively constrained. These findings suggest that the benefits of agricultural UAVs depend not simply on adoption, but on sufficiently intensive use and supportive service institutions. Policies that expand access to UAV services and promote their effective integration into farm operations can improve factor allocation and grain production efficiency, especially in areas where conventional mechanisation is less adaptable. More broadly, these efforts can support agricultural digitalisation and sustainable agricultural modernisation.","提升粮食生产效率（GPE）对于保障粮食安全和推动资源节约型农业转型至关重要，尤其是在常规机械面临规模和地形约束的小农户体系中。中国农业无人机（UAV）的快速普及，为评估数字机械能否在不依赖农场规模扩大的情况下提升效率提供了契机。然而，关于无人机使用强度如何影响粮食生产效率以及增益在何种条件下显现的证据仍然有限。基于2022年中国乡村振兴调查中九个省份2030个粮食种植户的数据，我们采用超效率松弛测度模型测算粮食生产效率，并估计无人机使用强度的影响。结果表明，无人机使用强度与粮食生产效率之间呈显著的U型关系，效率增益仅在无人机使用强度超过一定阈值后才会显现。无人机使用主要通过劳动替代影响粮食生产效率，并与农药投入呈非线性关联。此外，村级农业服务组织强化了无人机使用的正向效应，表明服务供给与技术使用具有互补性。效率效应在中国西部和水稻生产体系中更强，这些地区常规机械受约束相对较大。这些发现表明，农业无人机的效益不仅取决于是否采用，还取决于足够密集的使用和支持性服务制度。扩大无人机服务可及性并促进其有效融入农场经营的政策，可以改善要素配置和粮食生产效率，尤其是在常规机械化适应性较差的地区。更广泛而言，这些努力能够支持农业数字化和可持续农业现代化。","Food Policy","2026-09-21T00:00:00Z",86,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":67,"relevant":22,"comment":68},9,"基于2030户九省调查的实证研究，揭示无人机使用强度与粮食生产效率的U型关系及服务组织互补作用，方法规范、结论有政策价值，值得进入每日精选。",[70],{"name":63,"url":60},[72,73,28,30,74],"智慧农业","农业无人机","粮食生产效率",[76,77],"农业无人机 粮食生产效率","中国农村振兴调查 无人机","农业无人机粮食生产效率-3193","10.1016\u002Fj.foodpol.2026.103196",{"doi":79,"openalex_id":81,"authors":82,"venue":63,"cited_by_count":36,"oa_url":60,"card":96,"direction":51,"ingested_from":52},"W7213921092",[83,85,88,90,93],{"name":84,"orcid":9},"Xia Xu",{"name":86,"orcid":87},"Xianhui Geng","https:\u002F\u002Forcid.org\u002F0000-0003-3998-7589",{"name":89,"orcid":9},"Zhenzhen Liu",{"name":91,"orcid":92},"Guangqiao Cao","https:\u002F\u002Forcid.org\u002F0000-0002-9364-3376",{"name":94,"orcid":95},"Peng Yuan","https:\u002F\u002Forcid.org\u002F0000-0003-3019-0688",{"tldr":97,"method":98,"finding":99,"direction":100,"opportunity":101},"基于中国农村调查数据，研究无人机使用强度对粮食生产效率的影响及条件。","2022年中国乡村振兴调查2030户数据，超效率SBM模型测效率。","无人机使用强度与粮食生产效率呈U型关系，需超过阈值才增效，主要通过劳动替代。","智慧农业 \u002F 农业物联网","可探究无人机服务组织与农户技术采纳的协同机制，及不同作物和区域的最优使用强度阈值。","2026-09-22T23:30:32.180844Z",{"id":104,"title":105,"url":106,"summary":107,"summary_zh":9,"content":9,"source_name":108,"source_url":9,"published_at":109,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":110,"score_detail":111,"sources":114,"tags":116,"search_phrases":120,"slug":123,"view_count":36,"doi":9,"paper":124,"created_at":132},2110,"《绿色算力建设驱动农业数字化绿色化协同发展的机制研究》 249地级市3 237观测值渐进DID","https:\u002F\u002Fnyxdhyj.isa.ac.cn\u002F","在\"双碳\"目标与数字中国战略双重驱动下,以国家绿色数据中心试点为准自然实验,基于2011—2023年全国249个地级市3237个城市-年份观测值,采用渐进双重差分模型考察绿色算力建设对农业数字化绿色化协同发展的影响及机制。研究发现绿色算力建设显著提升农业数字化绿色化耦合协调度(系数0.076,1%显著水平),主要通过促进数据要素流通、扩大清洁能源应用、推动绿色算力与农业技术融合。西部地区政策效应显著强于东北地区。","农业现代化研究","2026-09-07T00:00:00Z",84,{"impact":17,"substance":18,"depth":112,"authority":20,"freshness":55,"relevant":22,"comment":113},19,"基于249个地级市3237个观测值的渐进DID实证，量化绿色算力对农业数字化绿色化协同的促进效应，方法规范、数据规模大，对数字乡村与农业绿色发展政策有参考价值。",[115],{"name":108,"url":106},[117,118,27,28,119],"数字乡村","数据要素","绿色算力",[121,122],"农业绿色发展 农业数字化 数字乡村 数据要素","农业绿色发展 农业数字化","农业绿色发展农业数字化数字乡村数据要素-2110",{"doi":9,"openalex_id":9,"authors":125,"venue":9,"cited_by_count":36,"oa_url":9,"card":126,"direction":49,"ingested_from":131},[],{"tldr":127,"method":128,"finding":129,"direction":49,"opportunity":130},"以国家绿色数据中心试点为准自然实验，检验绿色算力建设对农业数字化绿色化协同发展的影响。","2011—2023年249个地级市3237个观测值，渐进双重差分模型。","绿色算力建设显著提升农业数字化绿色化耦合协调度，西部效应强于东北。","可探究绿色算力对不同农业细分行业与经营主体的异质性影响，及数据要素流通的微观路径。","agent","2026-09-11T00:04:22.926298Z",{"id":134,"title":135,"url":136,"summary":137,"summary_zh":9,"content":9,"source_name":138,"source_url":9,"published_at":139,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":140,"score_detail":141,"sources":145,"tags":147,"search_phrases":150,"slug":153,"view_count":36,"doi":9,"paper":154,"created_at":161},1962,"Digital Technology Empowering Agricultural Green Transformation and Low-Carbon Development in China","https:\u002F\u002Fem.swfu.edu.cn\u002Finfo\u002F1791\u002F20211.htm","宋闻问、唐勇辉、李宇硕、潘立（西南林业大学）基于中国31个省（自治区、直辖市）2010—2023年面板数据，运用固定效应模型、中介效应模型与门槛效应模型系统探究数字技术对农业碳排放强度的影响。结果显示：(1)数字技术对农业碳排放强度具有显著且稳健的抑制作用。(2)数字技术通过强化环境规制水平和提升农业社会化服务水平两条核心路径实现碳减排。(3)减排效应存在农业产业集聚门槛特征，集聚水平提升时边际效应递增。(4)在粮食主产区与产销平衡区抑制效应显著，粮食主销区不显著。(5)在低地形起伏地区抑制效应显著，高地形起伏地区则不显著。","Sustainability 2026(4) 西南林业大学经济管理学院","2026-04-01T00:00:00Z",73,{"impact":142,"substance":17,"depth":19,"authority":143,"freshness":22,"relevant":22,"comment":144},20,12,"基于省级面板数据的实证研究，揭示数字技术抑制农业碳排放的机制与异质性，对农业绿色转型有参考价值。",[146],{"name":138,"url":136},[148,30,149,31],"数字农业","碳减排",[151,152],"农业社会化服务 数字农业 环境规制 碳减排","农业社会化服务 数字农业","农业社会化服务数字农业环境规制碳减排-1962",{"doi":9,"openalex_id":9,"authors":155,"venue":9,"cited_by_count":36,"oa_url":9,"card":156,"direction":49,"ingested_from":131},[],{"tldr":157,"method":158,"finding":159,"direction":49,"opportunity":160},"研究数字技术对中国农业碳排放强度的影响及机制。","基于2010-2023年省级面板数据，运用固定效应、中介效应和门槛效应模型。","数字技术显著抑制农业碳排放，通过强化环境规制和提升农业社会化服务实现，且存在产业集聚门槛和区域异质性","可探究数字技术在不同农业产业集聚阶段和地形条件下的差异化减排机制，以及如何优化政策以促进粮食主销区和高地形起伏地区的减排","2026-09-09T00:03:57.053476Z",{"id":163,"title":164,"url":165,"summary":166,"summary_zh":167,"content":9,"source_name":168,"source_url":165,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":169,"score_detail":170,"sources":173,"tags":175,"search_phrases":180,"slug":183,"view_count":36,"doi":184,"paper":185,"created_at":209},3342,"Impact of agricultural greening on food production resilience-empirical evidence from China","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1938875","The Food Production System is generally confronted with external uncertain shocks and rigid constraints from ecological factors. How to strengthen the system’s adaptability and resilience through green transition pathways is a crucial research topic in the field of modern agricultural governance. With the provincial panel data from China, the entropy method is adopted in this paper to measure agricultural greening and food production resilience, and then the two-way fixed-effect model, the moderating-effect model, the threshold-effect model and spatial econometric models are applied for empirical testing. According to the results, the degree of agricultural greening has promoted food production resilience; at the same time, regions show heterogeneity across geographical regions and grain functional zones. Green finance and rural scientific and technological input will also be effective driving forces. There is a single threshold for economic development level; after exceeding it, the marginal promoting effect on resilience weakens, but remains significantly positive. Food production resilience also exhibits significant spatial dependence, and agricultural greening generates positive spillover effects on neighboring provinces under the adjacency-based spatial specification. This paper will provide new ideas for the theory of resilience enhancement and offer some references to help optimize the distribution of agricultural green factors and foster long-term stable grain production.","粮食生产系统普遍面临外部不确定冲击与生态因素的刚性约束。如何通过绿色转型路径增强系统的适应性与韧性，是现代农业农村治理领域的重要研究课题。本文基于中国省级面板数据，采用熵值法测度农业绿色化与粮食生产韧性，进而运用双向固定效应模型、调节效应模型、门槛效应模型及空间计量模型进行实证检验。结果表明，农业绿色化程度提升了粮食生产韧性；同时，不同地理区域与粮食功能区呈现出异质性。绿色金融与农村科技投入也是有效的驱动力量。经济发展水平存在单一门槛，跨越门槛后对韧性的边际促进效应减弱，但仍显著为正。粮食生产韧性还表现出显著的空间依赖性，在邻接空间设定下，农业绿色化对邻近省份产生正向溢出效应。本文将为韧性提升理论提供新思路，并为优化农业绿色要素配置、促进粮食长期稳定生产提供一定参考。","Frontiers in Sustainable Food Systems",79,{"impact":19,"substance":17,"depth":19,"authority":171,"freshness":21,"relevant":22,"comment":172},13,"基于中国省级面板数据的实证研究，方法扎实、结论有政策参考价值，但属学术论文而非产业级事件，适合进入主题聚合而非头条精选。",[174],{"name":168,"url":165},[27,176,177,178,179],"粮食生产韧性","农业科技投入","绿色金融","空间溢出效应",[181,182],"农业绿色化 粮食生产韧性","绿色金融 农村科技投入","农业绿色化粮食生产韧性-3342","10.3389\u002Ffsufs.2026.1938875",{"doi":184,"openalex_id":186,"authors":187,"venue":168,"cited_by_count":36,"oa_url":165,"card":204,"direction":49,"ingested_from":52},"W7214113879",[188,190,193,195,197,199,202],{"name":189,"orcid":9},"Huimin Shao",{"name":191,"orcid":192},"Wenjuan Zhang","https:\u002F\u002Forcid.org\u002F0000-0001-5062-1292",{"name":194,"orcid":9},"Qiong Peng",{"name":196,"orcid":9},"Haichuan Liu",{"name":198,"orcid":9},"Liangyan Lu",{"name":200,"orcid":201},"Mcxin Tee","https:\u002F\u002Forcid.org\u002F0000-0001-7990-8377",{"name":203,"orcid":9},"Qing Jin",{"tldr":205,"method":206,"finding":207,"direction":49,"opportunity":208},"基于中国省级面板数据，实证检验农业绿色化对粮食生产韧性的提升作用。","熵值法测度指标，双向固定效应、调节效应、门槛效应与空间计量模型。","农业绿色化显著提升粮食生产韧性，存在区域异质性、经济门槛及正向空间溢出。","可探究绿色金融与科技投入的协同机制，及跨区域溢出路径的微观落地。","2026-09-24T23:30:07.857044Z",{"id":211,"title":212,"url":213,"summary":214,"summary_zh":215,"content":9,"source_name":168,"source_url":213,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":216,"score_detail":217,"sources":220,"tags":222,"search_phrases":227,"slug":230,"view_count":36,"doi":231,"paper":232,"created_at":245},3338,"Public education investment and agricultural structural transformation: evidence from prefecture-level cities in China's grain-producing provinces","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1942783","The decline of agriculture's relative output weight as non-farm sectors expand is a defining regularity of development, yet its local public-investment correlates within a single economy remain unclear. This study relates local public education-investment intensity—annual education expenditure over city gross domestic product (GDP), a spending flow rather than a human-capital stock—to agricultural structural transformation in 172 prefecture-level cities across China's 13 major grain-producing provinces, using two-way fixed-effects models that compare each city with itself over time. The primary-sector output share is the direct measure of intersectoral composition (3,249 city-year observations, 2005–2023); primary value added per registered resident is a complementary scale outcome that avoids the shared GDP denominator (3,080 observations, 2005–2022). On the share margin the association is negative in the reference specification but not robust, changing sign when city-specific trends and lagged controls are imposed jointly. On the scale margin it is negative in every control set examined, including lagged controls and city trends, and placebo fiscal ratios do not reproduce it; it is nevertheless indistinguishable from zero under province-by-year fixed effects and 13-province few-cluster inference. The three sector-share estimates form an accounting decomposition whose receiving-sector sign reverses across specifications, so no services-led claim is made. All estimates are conditional within-city associations, not causal effects. For grain-producing regions, they motivate coordinating education budgets with agricultural productivity and capacity safeguards rather than reading a falling primary-sector share as modernization.","农业相对产出比重的下降是非农部门扩张过程中的一个典型发展规律，但其在单一经济体内部与地方公共投资的关联仍不明确。本研究将地方公共教育投资强度——即年度教育支出占城市国内生产总值（GDP）的比重，这是一种支出流量而非人力资本存量——与中国13个粮食主产省172个地级市的农业结构转型相联系，采用双向固定效应模型对每个城市进行自身随时间变化的比较。第一产业产出份额是部门间构成的直接度量（2005—2023年，3,249个城市—年份观测值）；按户籍居民计算的第一产业增加值是一个互补性的规模结果变量，可避免使用共同的GDP分母（2005—2022年，3,080个观测值）。在份额边际上，基准设定中的关联为负但不稳健，当同时加入城市特定趋势和滞后控制变量后符号发生改变。在规模边际上，在所有考察的控制变量组合中——包括滞后控制变量和城市趋势——关联均为负，且安慰剂财政比率无法重现该结果；然而在省份—年份固定效应和13省少数聚类推断下，该关联与零无法区分。三个部门份额估计构成一个核算分解，其接收部门的符号在不同设定间发生反转，因此不提出服务业主导的论断。所有估计均为城市内部的条件关联，而非因果效应。对于粮食主产区而言，这些结果提示应将教育预算与农业生产率和产能保障相协调，而非将第一产业份额下降解读为现代化。",78,{"impact":218,"substance":17,"depth":19,"authority":171,"freshness":67,"relevant":22,"comment":219},16,"基于172个地级市2005—2023年面板数据的实证研究，方法规范、结论审慎，对粮食主产区教育投入与农业结构转型的协调具有参考价值，但属学术论文、影响面偏细分领域。",[221],{"name":168,"url":213},[223,29,224,225,226],"县域经济","农业经济研究","农业结构转型","教育投入",[228,229],"粮食主产区 地级市 教育投入","农业结构转型 主产区 面板数据","粮食主产区地级市教育投入-3338","10.3389\u002Ffsufs.2026.1942783",{"doi":231,"openalex_id":233,"authors":234,"venue":168,"cited_by_count":36,"oa_url":213,"card":240,"direction":51,"ingested_from":52},"W7214101078",[235,237],{"name":236,"orcid":9},"Kewen Hou",{"name":238,"orcid":239},"Xiuzhi Wang","https:\u002F\u002Forcid.org\u002F0000-0002-3770-3231",{"tldr":241,"method":242,"finding":243,"direction":51,"opportunity":244},"研究中国13个粮食主产省172个地级市教育投入强度与农业结构转型的关联。","双向固定效应模型，2005-2023年地级市面板数据，教育支出占GDP比重。","教育投入与农业产出份额关联不稳健，与人均农业增加值负相关但非因果。","可探究教育投入通过人力资本与数字技术采纳影响农业转型的机制，并做因果识别。","2026-09-24T23:30:07.572572Z",{"id":247,"title":248,"url":249,"summary":250,"summary_zh":251,"content":9,"source_name":168,"source_url":249,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":65,"score_detail":252,"sources":254,"tags":256,"search_phrases":260,"slug":263,"view_count":36,"doi":264,"paper":265,"created_at":286},3333,"Beyond administrative boundaries: how agricultural socialized services drive grain-oriented cropping transformation in China","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1920691","China’s grain security rests on a smallholder sector in which the average household cultivates 0.6 hectares, a scale that constrains mechanization and limits gains in production efficiency. Since 2013 the government has responded through agricultural socialized service (ASS) pilots, which deliver mechanized and technical services to fragmented producers without altering land ownership. Causal evidence on how such policies reshape land allocation remains scarce, and their reach beyond implementing jurisdictions has been largely overlooked. Drawing on a panel of 30 Chinese provinces from 2006 to 2022, this study combines a multi-period difference-in-differences design with a spatial Durbin model to estimate the effect of the ASS pilots on grain-oriented cropping structure. The policy raises the grain share of sown area by 2.8 percentage points, an effect concentrated almost entirely in wheat, the most mechanization-compatible of the major grains. Four transmission channels register significant responses: land transfer consolidation, agricultural mechanization, cooperative development, and a widening rather than a narrowing of the grain portfolio. The last of these runs counter to the conventional specialization account and is consistent with service provision relaxing the timing constraint on multiple cropping, so that grain expansion and crop diversity advance together rather than trading off. Heterogeneity tracks physical conditions more closely than administrative geography: the estimated effect in plains provinces is roughly twice that in hilly provinces, whereas differences across the eastern, central and western belts are not statistically distinguishable. Spillovers are substantial. Indirect effects are 1.8 times direct effects and account for close to two thirds of the total, so non-spatial estimation understates the total policy effect by approximately 41% while overstating its purely local component by approximately 40%. Three implications follow: target service expansion by mechanization compatibility rather than by administrative region; sequence implementation outward from high-capacity provinces so that spillovers are harvested deliberately rather than incidentally; and evaluate service-oriented policies at a supra-provincial scale, since province-by-province assessment misstates both their magnitude and their geographic incidence.","中国的粮食安全建立在小农部门之上，户均耕地仅0.6公顷，这一规模制约了机械化并限制了生产效率的提升。自2013年以来，政府通过农业社会化服务（agricultural socialized service，ASS）试点予以应对，在不改变土地所有权的前提下，为细碎化生产者提供机械化与技术服务。关于此类政策如何重塑土地配置的因果证据仍然稀缺，且其超出实施辖区之外的溢出效应在很大程度上被忽视。本研究基于2006年至2022年中国30个省份的面板数据，将多期双重差分设计与空间杜宾模型相结合，估计ASS试点对粮食导向种植结构的影响。该政策使粮食播种面积占比提高2.8个百分点，这一效应几乎完全集中于小麦——主要粮食品种中与机械化兼容性最高者。四条传导渠道呈现显著响应：土地流转整合、农业机械化、合作社发展，以及粮食组合的拓宽而非收窄。最后一条与传统的专业化解释相悖，而与服务供给放松多熟制时间约束相一致，从而使粮食扩张与作物多样性齐头并进而非相互权衡。异质性更多地随自然条件而非行政区划而变化：平原省份的估计效应约为丘陵省份的两倍，而东部、中部和西部地带之间的差异在统计上不可区分。溢出效应十分显著。间接效应为直接效应的1.8倍，占总效应的近三分之二，因此非空间估计将政策总效应低估约41%，同时将其纯本地成分高估约40%。由此得出三点启示：应按机械化兼容性而非行政区划来定位服务扩展；从高能力省份向外依次推进实施，以便有意识地而非偶然地获取溢出效应；并在跨省尺度上评估服务导向型政策，因为逐省评估会误判其效应大小和地理分布。",{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":67,"relevant":22,"comment":253},"基于30省2006—2022年面板数据的准自然实验研究，量化农业社会化服务试点对粮食种植结构的因果效应与跨省溢出，结论对服务政策的空间布局有直接参考价值。",[255],{"name":168,"url":249},[257,258,30,179,259],"粮食安全","农业机械化","农地流转",[261,262],"农业社会化服务 粮食种植结构","农业社会化服务试点 空间杜宾模型","农业社会化服务粮食种植结构-3333","10.3389\u002Ffsufs.2026.1920691",{"doi":264,"openalex_id":266,"authors":267,"venue":168,"cited_by_count":36,"oa_url":249,"card":281,"direction":51,"ingested_from":52},"W7214079035",[268,271,274,276,278],{"name":269,"orcid":270},"Ruofan Liao","https:\u002F\u002Forcid.org\u002F0009-0009-5058-7368",{"name":272,"orcid":273},"Kexin Zhang","https:\u002F\u002Forcid.org\u002F0009-0000-3967-2080",{"name":275,"orcid":9},"Zhengtao Chen",{"name":277,"orcid":9},"Mi Tan",{"name":279,"orcid":280},"Jianxu Liu","https:\u002F\u002Forcid.org\u002F0000-0002-2128-6015",{"tldr":282,"method":283,"finding":284,"direction":51,"opportunity":285},"评估农业社会化服务试点如何跨行政区推动粮食种植结构转型。","2006-2022年30省面板，多期DID与空间杜宾模型。","试点使粮食播种面积占比提高2.8个百分点，以小麦为主，溢出效应约为直接效应的1.8倍。","可研究社会化服务跨区溢出的空间机制，及机械化适配性对作物多样性与粮食安全协同的影响。","2026-09-24T23:30:07.111992Z"]