[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-5469":3,"related-5469":100},{"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,"primary_topic":32,"secondary_topics":38,"classification":39,"search_phrases":78,"slug":81,"view_count":82,"doi":83,"paper":84,"created_at":99},5469,"How institutional digitalization reshapes entrepreneurial activity in new agricultural business forms: quasi-natural experimental evidence from China's Digital Village Pilot Policy","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1946061","New agricultural business forms are a key driving force for developing countries to overcome the constraints of traditional agriculture and achieve sustainability in food systems. However, it remains unclear whether institutional digitalization can effectively stimulate entrepreneurial vitality in new agricultural business forms. This study develops a theoretical framework of “opportunity creation–opportunity identification–opportunity transformation” and treats China's Digital Village Pilot Policy (DVPP), implemented in 2020, as a quasi-natural experiment. Based on panel data from 1,743 counties in China from 2014 to 2023, this study employs Double Machine Learning (DML) and Spatial Durbin Difference-in-Differences (SDM-DID) models, among other methods, to systematically identify the impact, transmission mechanisms, heterogeneous effects, and spatial spillover effects of institutional digitalization on Entrepreneurial Activity in New Agricultural Business Forms (EANA). The results reveal that: (1) DVPP significantly enhances EANA, and this finding remains robust after a series of tests, including placebo tests, Propensity Score Matching–Difference-in-Differences (PSM-DID), Synthetic Control Method–Difference-in-Differences (SCM-DID), and instrumental variable (IV) estimation; (2) agricultural technological innovation, digital infrastructure development, and digital financial development serve as mediating mechanisms; (3) the policy effects are more pronounced in counties with higher levels of digital access, better-developed transportation infrastructure, and higher levels of digital financial development, exhibiting a pattern of Central > Western > Eastern regions, and are significantly stronger in areas with advantages in characteristic agricultural products; (4) DVPP generates a significant negative spatial spillover effect on EANA in neighboring counties. This study expands theoretical understanding of the relationship between institutional digitalization and entrepreneurship in new agricultural business forms and provides empirical evidence for China and other developing countries to optimize digital rural development and foster new agricultural business forms.","农业新业态是发展中国家突破传统农业约束、实现食物系统可持续发展的关键驱动力。然而，制度数字化能否有效激发农业新业态的创业活力仍不明确。本研究构建了“机会创造—机会识别—机会转化”的理论框架，并将中国2020年实施的数字乡村试点政策（Digital Village Pilot Policy，DVPP）视为准自然实验。基于中国1743个县2014—2023年的面板数据，本研究采用双重机器学习（Double Machine Learning，DML）和空间杜宾双重差分（Spatial Durbin Difference-in-Differences，SDM-DID）等模型，系统识别制度数字化对农业新业态创业活动（Entrepreneurial Activity in New Agricultural Business Forms，EANA）的影响、传导机制、异质性效应和空间溢出效应。结果表明：（1）DVPP显著提升了EANA，且该结论在经过安慰剂检验、倾向得分匹配—双重差分（PSM-DID）、合成控制法—双重差分（SCM-DID）和工具变量（IV）估计等一系列检验后依然稳健；（2）农业技术创新、数字基础设施建设和数字金融发展发挥中介机制作用；（3）政策效应在数字接入水平较高、交通基础设施较完善和数字金融发展水平较高的县更为显著，呈现出中部>西部>东部的格局，且在特色农产品优势区显著更强；（4）DVPP对邻近县的EANA产生显著的负向空间溢出效应。本研究拓展了关于制度数字化与农业新业态创业之间关系的理论认识，为中国及其他发展中国家优化数字乡村发展、培育农业新业态提供了经验证据。",null,"Frontiers in Sustainable Food Systems","2026-10-20T00:00:00Z","论文",10,false,85,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},22,23,18,13,9,1,"基于1743个县面板数据的准自然实验，方法扎实、结论有政策参考价值，值得进入每日精选。",[25],{"name":10,"url":6},[27,28,29,30,31],"数字农业","数字乡村","县域经济","农业政策","农村创业",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},"I6","digital-village","数字乡村与数据要素","\u002Ftopic\u002Fdigital-agriculture\u002Fdigital-village","I",[],{"status":40,"locked":14,"version":41,"method":42,"evidence":43},"classified","2026-10-22.2","rules",{"candidates":44,"agricultural_evidence":47},[45,52,60,67,73],{"code":33,"score":46,"supported":47,"title":48,"abstract":50,"tags":51},15,true,[49],"digital village",[28,49],[28],{"code":53,"score":54,"supported":47,"title":55,"abstract":56,"tags":59},"I2",6,[],[57,58],"机器学习","machine learning",[],{"code":61,"score":62,"supported":47,"title":63,"abstract":64,"tags":66},"G",3,[],[65],"rural development",[],{"code":68,"score":69,"supported":14,"title":70,"abstract":71,"tags":72},"G4",2,[],[],[31,29],{"code":74,"score":22,"supported":14,"title":75,"abstract":76,"tags":77},"I1",[],[],[27],[79,80],"数字乡村试点 新农业业态","DVPP 农村创业","数字乡村试点新农业业态-5469",0,"10.3389\u002Ffsufs.2026.1946061",{"doi":83,"openalex_id":85,"authors":86,"venue":10,"cited_by_count":82,"oa_url":6,"card":92,"direction":96,"ingested_from":98},"W7223041086",[87,89],{"name":88,"orcid":9},"Su Li",{"name":90,"orcid":91},"Changjun Yang","https:\u002F\u002Forcid.org\u002F0009-0000-6236-3489",{"tldr":93,"method":94,"finding":95,"direction":96,"opportunity":97},"用双重机器学习与空间DID评估数字乡村试点政策对新农业业态创业活力的影响。","基于1743县2014-2023面板数据，用DML与SDM-DID做准自然实验。","试点政策显著提升新农业业态创业，经技术创新、数字基建与数字金融中介，并对邻县有负向溢出。","数字乡村与农业信息化","可探究政策负向空间溢出的形成机制及跨县协同激励设计，避免创业资源虹吸。","openalex","2026-10-21T23:30:07.205317Z",{"total":54,"page":22,"page_size":54,"items":101},[102,150,212,287,368,431],{"id":103,"title":104,"url":105,"summary":106,"summary_zh":9,"content":9,"source_name":107,"source_url":9,"published_at":108,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":109,"score_detail":110,"sources":112,"tags":114,"primary_topic":118,"secondary_topics":119,"classification":120,"search_phrases":137,"slug":140,"view_count":82,"doi":9,"paper":141,"created_at":149},4781,"中国数字乡村建设与县域老年照护产业的耦合协调关系及区域差异研究","https:\u002F\u002Fwww.ebiotrade.com\u002Fnewsf\u002F2026-10\u002F20261009225937972.htm","本研究利用中国县域数字乡村指数2018年和2020年及匹配的老年照护产业统计数据,采用综合耦合协调度评价模型考察两大系统之间的耦合协调度及其区域差异。研究发现,全国整体耦合协调水平仍偏低,农村经济、日常生活和治理的数字化与老年照护产业耦合度呈中度失衡。结论建议政府应优先关注数字乡村建设的社会效益,加强农村老年照护的技术和服务支持。","生物通 报道 BMC Geriatrics 2026-10-10","2026-10-10T00:00:00Z",77,{"impact":19,"substance":17,"depth":19,"authority":20,"freshness":54,"relevant":22,"comment":111},"基于县域面板数据的实证研究，揭示数字乡村与老年照护产业耦合失衡，对农村数字化社会效益有政策参考价值。",[113],{"name":107,"url":105},[28,29,115,116,117],"耦合协调","区域差异","老年照护",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":121},{"candidates":122,"agricultural_evidence":47},[123,128,132],{"code":33,"score":124,"supported":47,"title":125,"abstract":126,"tags":127},12,[28],[28],[28],{"code":68,"score":22,"supported":14,"title":129,"abstract":130,"tags":131},[],[],[29],{"code":133,"score":22,"supported":14,"title":134,"abstract":135,"tags":136},"I4",[],[],[115],[138,139],"中国县域数字乡村指数 老年照护产业","区域差异 县域经济 数字乡村 老年照护","中国县域数字乡村指数老年照护产业-4781",{"doi":9,"openalex_id":9,"authors":142,"venue":9,"cited_by_count":82,"oa_url":9,"card":143,"direction":96,"ingested_from":148},[],{"tldr":144,"method":145,"finding":146,"direction":96,"opportunity":147},"研究中国县域数字乡村建设与老年照护产业的耦合协调关系及区域差异。","基于2018和2020年县域数字乡村指数与老年照护产业数据，构建耦合协调度模型。","全国整体耦合协调水平偏低，数字化与老年照护产业呈中度失衡，区域差异明显。","可深入探究数字乡村建设对农村老年照护服务可及性的因果影响及技术赋能路径。","agent","2026-10-13T00:08:38.106787Z",{"id":151,"title":152,"url":153,"summary":154,"summary_zh":9,"content":9,"source_name":155,"source_url":9,"published_at":9,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":156,"score_detail":157,"sources":161,"tags":163,"primary_topic":167,"secondary_topics":172,"classification":174,"search_phrases":200,"slug":203,"view_count":22,"doi":9,"paper":204,"created_at":211},4402,"数字乡村建设：通往城乡融合的路径检验 — 来自长三角电子商务进农村综合示范县的证据","http:\u002F\u002Fwww.qikanzj.com\u002Fhek\u002Fzrzyxb\u002Fmulu\u002F456395.html","基于长三角 151 个县域城乡数据,通过耦合协调度模型、Dagum 基尼系数法以及多期 DID 等方法探究,电子商务进农村综合示范县政策显著提高县域城乡融合发展水平;未列入淘宝村建设的地区尤其是偏远欠发达地区居民更能从电子商务建设中获利;机制上更依赖信息壁垒破除和创业活力提升路径,在滞后数字生活环境下推进示范县政策更有利于促进城乡融合发展。","无锡学院数字经济与管理学院 浙江工业大学经济学院《自然资源学报》",80,{"impact":17,"substance":18,"depth":158,"authority":159,"freshness":69,"relevant":22,"comment":160},19,14,"基于长三角151个县域的多期DID实证研究，方法规范、结论可靠，对数字乡村与城乡融合政策有较强参考价值，但发布日期不明、时效性偏弱。",[162],{"name":155,"url":153},[28,164,29,165,166],"长三角","城乡融合","电子商务进农村",{"code":168,"slug":169,"name":170,"path":171,"parent_code":61},"G6","rural-integration","帮扶与城乡融合","\u002Ftopic\u002Frural-services\u002Frural-integration",[173],{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},{"status":40,"locked":14,"version":41,"method":42,"evidence":175},{"candidates":176,"agricultural_evidence":47},[177,182,186,191,195],{"code":168,"score":178,"supported":47,"title":179,"abstract":180,"tags":181},11,[165],[165],[],{"code":33,"score":21,"supported":47,"title":183,"abstract":184,"tags":185},[28],[],[28],{"code":187,"score":22,"supported":14,"title":188,"abstract":189,"tags":190},"E5",[],[],[166],{"code":68,"score":22,"supported":14,"title":192,"abstract":193,"tags":194},[],[],[29],{"code":196,"score":22,"supported":14,"title":197,"abstract":198,"tags":199},"G5",[],[],[165],[201,202],"长三角 电子商务进农村 综合示范县","数字乡村 城乡融合 县域","长三角电子商务进农村综合示范县-4402",{"doi":9,"openalex_id":9,"authors":205,"venue":9,"cited_by_count":82,"oa_url":9,"card":206,"direction":96,"ingested_from":148},[],{"tldr":207,"method":208,"finding":209,"direction":96,"opportunity":210},"基于长三角151县数据，检验电商进农村示范县政策对城乡融合的促进作用。","耦合协调度模型、Dagum基尼系数与多期DID，使用长三角县域面板数据。","示范县政策显著提升城乡融合，偏远欠发达地区获益更多，机制为破除信息壁垒与提升创业活力。","可探究数字生活滞后地区政策效果的长期持续性及信息壁垒破除的微观农户机制。","2026-10-08T00:07:46.709393Z",{"id":213,"title":214,"url":215,"summary":216,"summary_zh":217,"content":9,"source_name":218,"source_url":215,"published_at":219,"category":12,"cover_url":9,"hotness":220,"is_selected":14,"score":156,"score_detail":221,"sources":223,"tags":228,"primary_topic":232,"secondary_topics":233,"classification":235,"search_phrases":259,"slug":262,"view_count":54,"doi":263,"paper":264,"created_at":286},3562,"Toward Common Prosperity: Spatially Heterogeneous Effects and Mechanisms of Digital Village Construction on the Urban–Rural Income Gap in Mountainous China","https:\u002F\u002Fdoi.org\u002F10.3390\u002Fland15101801","Mountainous regions are critical to promoting inclusive growth and reducing spatial inequality worldwide. Digital village construction offers a new pathway to overcome geographical constraints and reshape urban–rural income distribution in these areas. Using county-level data for 2020 and focusing on mountainous China, this study integrates the Theil index, IV-2SLS, MGWR, and mediation models to characterize the spatial pattern of the urban–rural income gap (URIG) and identify the spatially heterogeneous effects and potential mechanisms of digital village construction across different geomorphological settings. The results indicate that: (1) Large and highly dispersed URIG are concentrated in mountainous regions. On average, the gap is approximately twice as large as that in non-mountainous regions and varies markedly across geomorphological types. URIG is highest in mountain counties, shows the greatest variation in plateau counties, and tends to be lower in hill counties. (2) Digital village construction exerts a significant negative effect on URIG in mountainous China, with the effect being stronger than in non-mountainous regions and generally increasing in magnitude from east to west. (3) The effects of different DVI dimensions on URIG exhibit substantial spatial heterogeneity and vary in their spatial scales of influence. Rural economy digitalization shows widespread and consistently negative effects and emerges as the dominant dimension across most mountainous regions, while the effect of other dimensions is more localized, particularly rural life digitalization, which shows stronger negative effects in mountain counties, plateau counties, and underdeveloped mountainous counties. (4) Agricultural operation modernization and labor allocation optimization constitute potential channels underlying the association between digital village construction and a narrower URIG, with the estimated indirect effect being more pronounced through labor allocation optimization. These findings provide empirical evidence for advancing inclusive development in mountainous regions amid China’s common prosperity agenda, with broader implications for place-based digital village construction.","山区对于促进包容性增长和缩小全球空间不平等至关重要。数字乡村建设为这些地区突破地理约束、重塑城乡收入分配格局提供了新路径。本研究以2020年县级数据为基础，聚焦中国山区，综合运用泰尔指数、IV-2SLS、MGWR和中介模型，刻画城乡收入差距（URIG）的空间格局，并识别数字乡村建设在不同地貌条件下的空间异质性效应及其潜在机制。结果表明：（1）规模较大且高度分散的URIG集中于山区。其平均值约为非山区的两倍，且在不同地貌类型间差异显著。URIG在山区县最高，在高原县变异最大，在丘陵县则趋于较低水平。（2）数字乡村建设对中国山区URIG具有显著负向影响，其效应强于非山区，且总体上呈自东向西递增态势。（3）数字乡村建设不同维度对URIG的影响表现出显著的空间异质性，且其影响的空间尺度各异。农村经济数字化呈现出广泛且稳定的负向效应，并在大多数山区成为主导维度，而其他维度的效应则更具局部性，尤其是农村生活数字化，在山区县、高原县及欠发达山区县表现出更强的负向效应。（4）农业经营现代化和劳动力配置优化构成数字乡村建设与URIG缩小之间关联的潜在渠道，其中通过劳动力配置优化的间接效应更为明显。上述发现为中国共同富裕议程下推进山区包容性发展提供了经验证据，并对因地制宜推进数字乡村建设具有更广泛的启示。","Land","2026-09-25T00:00:00Z",25,{"impact":19,"substance":17,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":222},"基于县域数据的实证研究，方法扎实、结论对山区数字乡村政策有参考价值，但属学术论文，公共传播热度有限。",[224,225],{"name":218,"url":215},{"name":226,"url":227},"MDPI Land 15(10), 1801 2026-09-25","https:\u002F\u002Fwww.mdpi.com\u002F2073-445X\u002F15\u002F10\u002F1801",[28,29,229,230,231],"农业数字化","山区农业","城乡收入差距",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[234],{"code":168,"slug":169,"name":170,"path":171,"parent_code":61},{"status":40,"locked":14,"version":41,"method":42,"evidence":236},{"candidates":237,"agricultural_evidence":47},[238,242,247,251,255],{"code":33,"score":46,"supported":47,"title":239,"abstract":240,"tags":241},[49],[28,49],[28],{"code":168,"score":124,"supported":47,"title":243,"abstract":245,"tags":246},[244],"rural income",[244],[231],{"code":68,"score":22,"supported":14,"title":248,"abstract":249,"tags":250},[],[],[29],{"code":37,"score":22,"supported":14,"title":252,"abstract":253,"tags":254},[],[],[229],{"code":74,"score":22,"supported":14,"title":256,"abstract":257,"tags":258},[],[],[229],[260,261],"数字乡村 城乡收入差距 山区","县域 数字乡村 泰尔指数","数字乡村城乡收入差距山区-3562","10.3390\u002Fland15101801",{"doi":263,"openalex_id":265,"authors":266,"venue":218,"cited_by_count":82,"oa_url":215,"card":281,"direction":96,"ingested_from":98},"W7214349448",[267,270,273,276,278],{"name":268,"orcid":269},"Xueting Yang","https:\u002F\u002Forcid.org\u002F0000-0003-4633-2185",{"name":271,"orcid":272},"Xiaoping Qiu","https:\u002F\u002Forcid.org\u002F0000-0001-6310-5959",{"name":274,"orcid":275},"Fubiao Zhu","https:\u002F\u002Forcid.org\u002F0000-0002-4606-3336",{"name":277,"orcid":9},"Mingkai Xu",{"name":279,"orcid":280},"Yun Xu","https:\u002F\u002Forcid.org\u002F0000-0002-2442-7792",{"tldr":282,"method":283,"finding":284,"direction":96,"opportunity":285},"研究数字乡村建设对中国山区城乡收入差距的空间异质性影响及机制。","用2020年县级数据，结合泰尔指数、IV-2SLS、MGWR与中介模型。","数字乡村建设显著缩小山区城乡收入差距，效应自东向西增强，且存在地貌与维度异质性。","可深入探究不同地貌下数字乡村各维度的空间尺度差异及劳动力配置中介的微观路径。","2026-09-26T23:30:38.665617Z",{"id":288,"title":289,"url":290,"summary":291,"summary_zh":292,"content":9,"source_name":10,"source_url":290,"published_at":293,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":294,"score_detail":295,"sources":298,"tags":300,"primary_topic":303,"secondary_topics":304,"classification":305,"search_phrases":348,"slug":351,"view_count":69,"doi":352,"paper":353,"created_at":367},3453,"The impact of digital village construction on rural population migration decisions","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1875724","Introduction With the widespread application of digital technologies such as big data and cloud computing in agriculture and rural areas, digital village construction has become a key initiative for promoting agricultural modernization and rural revitalization. Understanding how this process reshapes rural population mobility is therefore essential. This paper examines the impact of digital rural construction on rural residents’ migration decisions and identifies the underlying mechanisms. Methods We match household-level data from the 2020 China Rural Revitalization Survey (CRRS) with the county-level Digital Rural Index developed by Peking University, and estimate Logit models of the out-migration decision. A comprehensive battery of robustness checks is conducted, including alternative estimation models, sample restriction, exclusion of policy confounding, replacement of the core explanatory and dependent variables, omitted variable tests, and instrumental variable approaches. Mechanism and heterogeneity analyses are then performed. Results Digital rural construction significantly inhibits rural population out-migration, and this finding remains robust across all checks. The inhibitory effect is transmitted primarily through two mechanisms: encouraging non-agricultural business participation and expanding the scale of rural industries. The substitution effect arising from improved land resource allocation efficiency is weaker than the labor release effect of land transfer. The effect is more pronounced in eastern and western regions, among part-time farming and non-agricultural households, in non-mountainous areas, and among labor force groups aged 40 and above with junior secondary education or below. Digital rural construction also increases both the non-agricultural business income and the wage income of rural households. Discussion By uncovering the specific pathways and group-level heterogeneity through which digital village construction shapes migration decisions at the micro level, this study provides empirical evidence and policy implications for leveraging digitalization to promote local rural employment and advance urban–rural integrated development.","引言 随着大数据、云计算等数字技术在农业农村领域的广泛应用，数字乡村建设已成为推进农业现代化和乡村振兴的重要举措。理解这一过程如何重塑农村人口流动，因而至关重要。本文考察数字乡村建设对农村居民迁移决策的影响，并识别其内在机制。方法 本文将2020年中国乡村振兴调查（CRRS）的农户层面数据与北京大学发布的县域数字乡村指数进行匹配，估计农村人口外流决策的Logit模型。研究进行了一系列全面的稳健性检验，包括替代估计模型、样本限制、排除政策混杂因素、替换核心解释变量和被解释变量、遗漏变量检验以及工具变量方法。随后进行机制分析和异质性分析。结果 数字乡村建设显著抑制了农村人口外流，且这一发现在所有检验中均保持稳健。这种抑制效应主要通过两条机制传导：促进非农创业参与和扩大乡村产业规模。土地资源配置效率提升所带来的替代效应弱于土地流转的劳动力释放效应。该效应在东部和西部地区、兼业农户和非农户、非山区，以及40岁及以上、初中及以下学历的劳动力群体中更为明显。数字乡村建设还提高了农村家庭的非农经营收入和工资性收入。讨论 通过揭示数字乡村建设在微观层面影响迁移决策的具体路径和群体异质性，本研究为利用数字化促进农村本地就业、推进城乡融合发展提供了经验证据和政策启示。","2026-09-24T00:00:00Z",84,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":296,"relevant":22,"comment":297},8,"基于CRRS与北大数字乡村指数的微观实证研究，机制与异质性分析扎实，对数字乡村就业政策有参考价值。",[299],{"name":10,"url":290},[27,28,301,165,302],"乡村振兴","农村人口流动",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":306},{"candidates":307,"agricultural_evidence":47},[308,312,319,326,331,336,340,344],{"code":33,"score":46,"supported":47,"title":309,"abstract":310,"tags":311},[49],[28,49],[28],{"code":313,"score":54,"supported":47,"title":314,"abstract":315,"tags":318},"G2",[],[316,317],"土地流转","land transfer",[],{"code":320,"score":54,"supported":47,"title":321,"abstract":322,"tags":325},"J2",[],[323,324],"农业现代化","agricultural modernization",[],{"code":61,"score":327,"supported":47,"title":328,"abstract":329,"tags":330},4,[],[301],[301],{"code":68,"score":62,"supported":47,"title":332,"abstract":333,"tags":335},[],[334],"乡村产业",[],{"code":168,"score":62,"supported":47,"title":337,"abstract":338,"tags":339},[],[165],[],{"code":196,"score":22,"supported":14,"title":341,"abstract":342,"tags":343},[],[],[165],{"code":74,"score":22,"supported":14,"title":345,"abstract":346,"tags":347},[],[],[27],[349,350],"中国乡村振兴调查 数字乡村指数","数字乡村建设 农村劳动力迁移","中国乡村振兴调查数字乡村指数-3453","10.3389\u002Ffsufs.2026.1875724",{"doi":352,"openalex_id":354,"authors":355,"venue":10,"cited_by_count":82,"oa_url":290,"card":362,"direction":96,"ingested_from":98},"W7214148499",[356,358,360],{"name":357,"orcid":9},"Deshan Li",{"name":359,"orcid":9},"Shuangqiang Li",{"name":361,"orcid":9},"Fengming Li",{"tldr":363,"method":364,"finding":365,"direction":96,"opportunity":366},"数字乡村建设显著抑制农村人口外流，并揭示其作用机制与群体异质性。","匹配2020年CRRS农户数据与北大县域数字乡村指数，构建Logit模型。","数字乡村建设通过促进非农创业和扩大乡村产业规模抑制外迁，且效应存在区域与群体差异。","可探究数字乡村抑制外迁的长期动态效应及对城乡收入差距的反馈机制。","2026-09-25T23:30:06.381563Z",{"id":369,"title":370,"url":371,"summary":372,"summary_zh":373,"content":9,"source_name":10,"source_url":371,"published_at":374,"category":12,"cover_url":9,"hotness":13,"is_selected":47,"score":375,"score_detail":376,"sources":379,"tags":381,"primary_topic":385,"secondary_topics":386,"classification":387,"search_phrases":410,"slug":413,"view_count":62,"doi":414,"paper":415,"created_at":430},3336,"Prosper or beggar thy neighbor? non-farm employment effects and spatial spillovers of China's National Digital Village Pilot Program","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1950504","Introduction Counties are a key spatial unit linking cities and villages in China's rural transformation, yet many still lack the industrial base, market scale, and non-farm job opportunities needed to absorb rural labor. This study examines whether China's National Digital Village Pilot Program expands rural non-farm employment and whether its effects extend beyond pilot counties. Methods Using a panel of 1,450 Chinese counties and 24,111 county-year observations from 2007 to 2024, this study exploits the staggered implementation of the 2020 and 2024 pilot cohorts as a quasi-natural experiment. The policy effect is estimated using a multi-period difference-in-differences model and cross-validated with stacked DID and the Callaway-Sant'Anna estimator. Robustness is further assessed through propensity score matching, inverse probability weighting, entropy balancing, placebo tests, and alternative samples and specifications. Transmission channels, heterogeneity, and spatial effects are also examined. Results The National Digital Village Pilot Program increased rural non-farm employment in pilot counties by approximately 25% relative to non-pilot counties, and the result remains robust across alternative identification and estimation strategies. The two-step transmission-channel analysis provides evidence consistent with two potential channels: enhanced county-level innovation and improved mobile network access capability. The policy effect is significantly stronger in central-region counties than in western counties and stronger in smaller counties than in larger ones, with weaker evidence of a larger effect in counties with lower human capital. Spatial analysis shows a positive direct effect on pilot counties but a negative spillover effect on neighboring counties. Discussion The findings indicate that digital village development can strengthen local non-farm employment absorption, but part of the local gain may reflect a spatial reallocation of economic activity rather than net regional job creation. Effective implementation therefore requires not only county-level digital development but also cross-county resource coordination and regional policy integration.","引言 县域是中国城乡转型中连接城市与乡村的关键空间单元，但许多县域仍缺乏吸纳农村劳动力所需的产业基础、市场规模和非农就业机会。本研究考察中国国家数字乡村试点项目是否扩大了农村非农就业，以及其效应是否超出试点县范围。方法 本研究使用2007年至2024年间1，450个中国县域、24，111个县—年观测值的面板数据，将2020年和2024年试点批次的分批实施作为准自然实验。政策效应采用多期双重差分模型估计，并通过堆叠双重差分和Callaway-Sant'Anna估计量进行交叉验证。稳健性进一步通过倾向得分匹配、逆概率加权、熵平衡、安慰剂检验以及替代样本和设定加以评估。研究还考察了传导渠道、异质性和空间效应。结果 国家数字乡村试点项目使试点县的农村非农就业相对于非试点县增加了约25%，且该结果在替代性识别和估计策略下保持稳健。两步传导渠道分析提供的证据与两个潜在渠道相一致：县域创新能力增强和移动网络接入能力改善。政策效应在中部地区县域显著强于西部地区县域，在较小县域强于较大县域，而在人力资本较低县域效应更大的证据较弱。空间分析显示，政策对试点县具有正向直接效应，但对邻近县域产生负向溢出效应。讨论 研究结果表明，数字乡村发展能够增强本地非农就业吸纳能力，但部分本地收益可能反映的是经济活动的空间再配置，而非区域净就业创造。因此，有效实施不仅需要县域层面的数字发展，还需要跨县域资源协调和区域政策整合。","2026-09-23T00:00:00Z",89,{"impact":377,"substance":18,"depth":158,"authority":159,"freshness":21,"relevant":22,"comment":378},24,"基于1450个县2007-2024年面板数据的准自然实验研究，证实数字乡村试点使县域非农就业提升约25%，但存在对邻县的负向溢出，对政策协调具有实质参考价值。",[380],{"name":10,"url":371},[28,382,29,383,384],"空间溢出","数字乡村试点","非农就业",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":388},{"candidates":389,"agricultural_evidence":47},[390,395,402,406],{"code":33,"score":391,"supported":47,"title":392,"abstract":393,"tags":394},16,[49],[28,49],[28,383],{"code":133,"score":396,"supported":47,"title":397,"abstract":398,"tags":401},7,[],[399,400],"空间分析","spatial analysis",[382],{"code":68,"score":22,"supported":14,"title":403,"abstract":404,"tags":405},[],[],[29],{"code":168,"score":22,"supported":14,"title":407,"abstract":408,"tags":409},[],[],[384],[411,412],"国家数字乡村试点 非农就业","县域 数字乡村 空间溢出","国家数字乡村试点非农就业-3336","10.3389\u002Ffsufs.2026.1950504",{"doi":414,"openalex_id":416,"authors":417,"venue":10,"cited_by_count":82,"oa_url":371,"card":425,"direction":96,"ingested_from":98},"W7214093544",[418,421,423],{"name":419,"orcid":420},"Wei Yang","https:\u002F\u002Forcid.org\u002F0000-0002-0540-5934",{"name":422,"orcid":9},"Lijun Wang",{"name":424,"orcid":9},"Yizhuo Ma",{"tldr":426,"method":427,"finding":428,"direction":96,"opportunity":429},"评估国家数字乡村试点对县域非农就业的影响及空间溢出效应。","2007-2024年1450个县面板数据，多期DID与Callaway-Sant","试点县非农就业增约25%，但邻县出现负向溢出，部分为就业空间再分配。","可探究数字乡村试点的跨县协同机制与负溢出治理，及不同区域差异化政策设计。","2026-09-24T23:30:07.434384Z",{"id":432,"title":433,"url":434,"summary":435,"summary_zh":9,"content":9,"source_name":436,"source_url":9,"published_at":437,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":294,"score_detail":438,"sources":440,"tags":442,"primary_topic":446,"secondary_topics":447,"classification":448,"search_phrases":462,"slug":465,"view_count":54,"doi":9,"paper":466,"created_at":473},3123,"Turning Data into Sustainability: Agricultural Big Data Policy, Capital Composition, and Rural Eco-Environmental Sustainability in China（数据转化为可持续性：中国农业大数据政策、资本构成与农村生态环境可持续性）","https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F18\u002F9478","湖南第一师范学院马克思主义学院 Zhumiao Wang 等联合吉林大学、韩国圆光大学在《Sustainability》18(18): 9478 发表论文（2026-09-16 发表）。农村环境退化是分散的、监测薄弱的、难以治理的，是可持续发展目标（SDGs）最持久的障碍之一。以 2010-2024 年中国 271 个城市面板数据为基础，以 2016 年农业农村大数据政策（ABDP）试点为\"准自然实验\"，采用交错双重差分（DID）设计估计政策对农村生态环境可持续性（RES）的效应。结果显示 ABDP 使 RES 提升 0.0015 个指数点（相当于样本均值 2.91%、分布 6.8 个百分位点）；效应规模取决于政策所面临的资本存量：随农业机械化（AM）上升而下降并在高机械化水平下变得不显著，随数字资本（DC）上升而上升；田间\"做什么\"的资本替代信息，向田间\"传递信息\"的资本补充信息。增益集中在生产—环境维度。","MDPI Sustainability","2026-09-16T00:00:00Z",{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":296,"relevant":22,"comment":439},"基于271城面板数据的交错DID实证，量化农业大数据政策对农村生态可持续性的效应及资本构成的调节作用，方法规范、结论有政策参考价值。",[441],{"name":436,"url":434},[28,443,30,444,445],"农业大数据","双重差分","农村生态环境",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":449},{"candidates":450,"agricultural_evidence":47},[451,455],{"code":33,"score":13,"supported":47,"title":452,"abstract":453,"tags":454},[443],[],[443,28],{"code":456,"score":54,"supported":47,"title":457,"abstract":458,"tags":461},"F5",[],[459,460],"农业机械","机械化",[],[463,464],"农业大数据政策 农村生态环境","Zhumiao Wang 农业大数据","农业大数据政策农村生态环境-3123",{"doi":9,"openalex_id":9,"authors":467,"venue":9,"cited_by_count":82,"oa_url":9,"card":468,"direction":96,"ingested_from":148},[],{"tldr":469,"method":470,"finding":471,"direction":96,"opportunity":472},"以2016年农业大数据政策试点为准自然实验，评估其对中国农村生态环境可持续性的影响。","2010-2024年271个城市面板数据，交错双重差分（DID）设计。","政策使农村生态可持续性提升约2.91%，效应随数字资本上升、随机械化上升而减弱。","可探究数字资本与机械资本的替代\u002F互补机制，及政策效应在非生产维度的异质性。","2026-09-22T00:05:38.376954Z"]