数字乡村建设对农村居民收入增长的影响——来自国家数字乡村试点的证据
基于国家试点政策与县域面板数据的实证研究，结论可靠，对数字乡村政策评估有重要参考价值，但发表时间较早，时效性不足。
余泽田、张世博、吴俣、彭华、董晓霞在《智慧农业(中英文)》2026年第8卷第3期发表文章,基于2014—2023年全国727个县域面板数据,将2020年国家数字乡村试点政策视为准自然实验,构建双重差分模型识别数字乡村建设对农村居民收入增长的影响。研究发现:国家数字乡村试点政策显著促进农村居民收入增长,但未对城乡收入差距产生显著影响;机制分析表明政策主要通过促进劳动力配置调整和提高创业活跃度推动增收,且经济基础、数字金融普惠水平和工业化程度会正向调节增收效应。后续应继续推进数字乡村建设,围绕优化劳动力配置、提升创业活跃度增强政策传导能力,统筹配套条件,强化数字红利普惠共享。DOI: 10.12133/j.smartag.SA202602009。
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Smart Agriculture ›› 2026, Vol. 8 ›› Issue (3): 147-158.doi: 10.12133/j.smartag.SA202602009
数字乡村建设对农村居民收入增长的影响——来自国家数字乡村试点的证据
余泽田, 张世博, 吴俣, 彭华, 董晓霞(
)
- 中国农业科学院农业信息研究所，北京 100081，中国
收稿日期:2026-02-03出版日期:2026-05-30基金项目:国家重点研发计划项目(2024YFD1700505); 农业农村部政府购买服务项目(08250132)作者简介:. 余泽田，博士研究生，研究方向为农业经济。E-mail：[email protected]； 张世博，硕士研究生，研究方向为农业经济。E-mail：[email protected] 余泽田、张世博为并列第一作者通信作者:董晓霞，博士，研究员，研究方向为农业经济。E-mail：[email protected]
The Impact of Digital Rural Development on Rural Residents' Income Growth: Evidence from the National Digital Rural Pilot Program
YU Zetian, ZHANG Shibo, WU Yu, PENG Hua, DONG Xiaoxia()
- Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Received:2026-02-03Online:2026-05-30Foundation items:National Key Research and Development Program of China(2024YFD1700505); Government Procurement Service Project of the Ministry of Agriculture and Rural Affairs(08250132)About author:YU Zetian, E-mail: [email protected]; ZHANG Shibo, E-mail:[email protected]Corresponding author:DONG Xiaoxia, E-mail: [email protected]
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## 可视化 0摘要/Abstract
摘要：
【目的/意义】 为识别数字乡村建设是否能够促进农村居民增收，并厘清其作用机制，以国家数字乡村试点政策为准自然实验，系统考察数字乡村建设对农村居民收入增长的影响。研究有助于为科学评估数字乡村政策成效、优化农民增收路径提供经验证据。 【方法】 基于2014—2023年全国727个县域面板数据，将2020年国家数字乡村试点政策视为准自然实验，构建双重差分模型识别数字乡村建设对农村居民收入增长的影响，并通过平行趋势检验、安慰剂检验、PSM-DID等方法进行稳健性检验，进一步结合机制检验和调节效应模型分析其作用路径。 【结果和讨论】 国家数字乡村试点政策显著促进了农村居民收入增长，但未对城乡收入差距产生显著影响。机制分析表明，政策主要通过促进劳动力配置调整和提高创业活跃度推动农村居民增收，且经济基础、数字金融普惠水平和工业化程度会正向调节增收效应。 【结论】 数字乡村建设是提升农村居民收入的有效路径，后续应持续推进，并围绕优化劳动力配置、提升创业活跃度增强政策传导能力，统筹配套条件，强化数字红利普惠共享。
关键词:数字乡村,农村居民增收,城乡包容性增长,双重差分模型,调节效应模型,数字技术
Abstract:
[Objective] Digital rural construction has become an important strategy for promoting rural revitalization and breaking the long-standing urban-rural dual structure in China. Under the goals of common prosperity and agricultural modernization, sustained income growth for rural residents is a key policy concern. Existing studies have explored the economic effects of digital rural development, but several gaps remain. Most research focuses on a single outcome rather than jointly considering income growth and broader inclusive development. Many studies also rely on composite indices that may be endogenous to local conditions. In addition, the channels through which digital rural policies affect rural income have not been fully clarified. To address these issues, the National Digital Rural Pilot Policy was used as a quasi-natural experiment in this research to examine whether digital rural construction raises rural residents' income, the transmission mechanisms of this effect and its effect on the urban-rural income gap. [Methods] Using the county-level panel data for 727 counties in China from 2014 to 2023, the 2020 launch of the National Digital Rural Pilot Policy was treated as a quasi-natural experiment, and a difference-in-differences model was applied to identify the policy's effect on rural residents' per capita disposable income.The analysis controlled for economic foundation, fiscal expenditure, financial development, population density, savings level, industrialization, service-sector development, and education. To test robustness, parallel trend tests, placebo tests, the exclusion of special samples, controls for other concurrent policies, and propensity score matching combined with DID estimation were conducted. Mechanism tests were used to examine whether the policy works through labor allocation optimization and enhanced entrepreneurial activity, while moderating effect models assessed whether county economic foundation, digital financial inclusion, and industrialization strengthen the income-enhancing effect. [Results and Discussions] The results showed that the National Digital Rural Pilot Policy significantly increased rural residents' income. After county and year fixed effects as well as other relevant factors were controlled for, the policy led to a significant increase in rural per capita disposable income, and this finding remained robust across a series of tests. Dynamic analysis showed no significant difference in pre-policy trends between pilot and non-pilot counties, while the positive effect emerged after policy implementation and strengthened over time, indicating a sustained and cumulative policy impact. Mechanism analysis identified two main channels through which the policy promoted income growth. First, digital rural construction improved labor allocation by fostering new forms of rural economic activity, such as digital agriculture and rural e-commerce, reducing labor market frictions, and improving the matching efficiency between labor and employment opportunities. Second, it enhanced entrepreneurial activity by lowering market entry and operating costs, increasing the vitality of agriculture-related business entities, and creating more opportunities for local business development and income generation. The income-enhancing effect was more pronounced in counties with a stronger economic foundation, higher levels of digital financial inclusion, and greater industrialization. However, although the policy significantly increased rural residents' income, it did not significantly reduce the urban-rural income gap, suggesting that absolute income growth did not necessarily lead to relative distributional convergence. [Conclusions] Digital rural construction is an effective pathway for increasing rural residents' income in China. By exploiting the National Digital Rural Pilot Policy as a quasi-natural experiment, this study provides more credible evidence on the income effects of digital rural development and clarifies its main transmission mechanisms. Future policy efforts should continue to advance digital rural construction while focusing on improving labor allocation, enhancing entrepreneurial activity, and strengthening county-level supporting conditions. Greater attention should also be paid to digitally disadvantaged areas and vulnerable rural groups in order to promote the inclusive sharing of digital dividends and foster more balanced urban-rural development.
Key words:digital rural construction,rural residents' income growth,urban-rural inclusive growth,difference-in-differences model,moderating?effect model,digital technology
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余泽田, 张世博, 吴俣, 彭华, 董晓霞. 数字乡村建设对农村居民收入增长的影响——来自国家数字乡村试点的证据[J]. 智慧农业(中英文), 2026, 8(3): 147-158.
YU Zetian, ZHANG Shibo, WU Yu, PENG Hua, DONG Xiaoxia. The Impact of Digital Rural Development on Rural Residents' Income Growth: Evidence from the National Digital Rural Pilot Program[J]. Smart Agriculture, 2026, 8(3): 147-158.
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[图/表 12](javascript:;)
表1
数字乡村增收效应研究主要变量的描述性统计结果
| 变量 | 说明 | 样本量 | 均值 | 标准差 | 最小值 | 最大值 |
|---|---|---|---|---|---|---|
| 农村居民收入 | 农村居民人均可支配收入/万元 | 7 270 | 1.288 | 0.515 | 0.510 | 3.562 |
| 数字乡村试点政策 | 见2.2节 | 7 270 | 0.018 | 0.134 | 0.000 | 1.000 |
| 经济基础 | 县区人均GDP/万元 | 7 270 | 3.497 | 2.336 | 0.802 | 17.218 |
| 财政水平 | 人均地方财政一般预算支出/万元 | 7 270 | 0.206 | 0.192 | 0.031 | 1.746 |
| 金融水平 | 人均年末金融机构各项贷款余额/万元 | 7 270 | 2.546 | 1.985 | 0.352 | 21.043 |
| 人口规模 | 年末总人口/行政区域总面积/（万人/km 2） | 7 270 | 0.031 | 0.033 | 0.000 | 0.425 |
| 储蓄水平 | 人均城乡居民储蓄存款余额/万元 | 7 270 | 2.655 | 1.297 | 0.340 | 11.250 |
| 工业化程度 | 第二产业增加值/GDP | 7 270 | 0.387 | 0.153 | 0.058 | 0.772 |
| 服务化程度 | 第三产业增加值/GDP | 7 270 | 0.430 | 0.108 | 0.164 | 0.838 |
| 教育水平 | 普通中学在校学生数/年末总人口 | 7 270 | 0.058 | 0.017 | 0.011 | 0.104 |
表1
表2
数字乡村试点对农村居民收入影响的基准回归结果
| 变量 | 农村居民收入 |
|---|---|
| （1） | （2） |
| 数字乡村试点 | 0.477*** |
| 经济基础 | |
| 财政水平 | |
| 金融水平 | |
| 人口规模 | |
| 储蓄水平 | |
| 工业化程度 | |
| 服务化程度 | |
| 教育水平 | |
| 年份固定效应 | |
| 县区固定效应 | |
| 常数项 | 1.279*** |
| 样本量 | 7 270 |
| R 2 | 0.037 |
表2
图1
农民收入平行趋势检验结果 注：以2019年为基准期，在95%的置信区间下绘制。
图1
图2
效应基准回归的伪政策年份安慰剂检验结果
图2
图3
基准回归的随机置换安慰剂检验结果
图3
表3
基准回归的稳健性检验：剔除特殊样本
| 变量 | 农村居民收入 |
|---|---|
| 数字乡村试点 | 0.471*** |
| （0.026） | |
| 控制变量 | |
| 时间固定效应 | |
| 县区固定效应 | |
| 样本量 | 6 640 |
| R 2 | 0.034 |
表3
表4
基准回归的稳健性检验：排除其他政策干扰
| 变量 | 是否是信息进村入户工程试点 | 是否是革命老区县 | 是否为少数民族自治县 |
|---|---|---|---|
| 数字乡村试点 | 0.048*** | 0.049*** | 0.049*** |
| （0.019） | （0.019） | （0.019） | |
| 控制变量 | 已控制 | 已控制 | 已控制 |
| 时间固定效应 | 已控制 | 已控制 | 已控制 |
| 县区固定效应 | 已控制 | 已控制 | 已控制 |
| 样本量 | 7 270 | 7 270 | 7 270 |
| R 2 | 0.921 | 0.921 | 0.921 |
表4
表5
基准回归的稳健性检验：更换回归模型
| 变量 | 农村居民收入 |
|---|---|
| 数字乡村试点 | 0.049*** |
| （0.019） | |
| 控制变量 | 已控制 |
| 时间固定效应 | 已控制 |
| 县区固定效应 | 已控制 |
表5
表6
数字乡村试点对农村居民收入影响的异质性检验结果
| 变量 | 数字基础 | 经济基础 | 地理区域 | 地形起伏度 |
|---|---|---|---|---|
| 数字乡村试点 | 0.002 | -0.030* | 0.095*** | 0.078** |
| （0.023） | （0.018） | （0.031） | （0.034） | |
| 数字乡村试点*数字基础 | 0.077** | |||
| （0.032） | ||||
| 数字乡村试点*经济基础 | 0.096*** | |||
| （0.026） | ||||
| 数字乡村试点*地理区域（以东部为基准） | ||||
| 中部 | -0.073 | |||
| （0.047） | ||||
| 西部 | -0.049 | |||
| （0.038） | ||||
| 数字乡村试点*地形起伏度 | -0.048 | |||
| （0.039） | ||||
| 控制变量 | 已控制 | 已控制 | 已控制 | 已控制 |
| 时间固定效应 | 已控制 | 已控制 | 已控制 | 已控制 |
| 县区固定效应 | 已控制 | 已控制 | 已控制 | 已控制 |
| 样本量 | 7 270 | 7 270 | 7 270 | 7 270 |
| R 2 | 0.921 | 0.921 | 0.921 | 0.921 |
表6
表7
数字乡村试点影响农村居民收入的中介机制检验结果
| 变量 | 劳动力配置 | 创业活跃度 |
|---|---|---|
| 数字试点政策 | 0.033** | 7.848* |
| （0.014） | （4.664） | |
| 控制变量 | 已控制 | 已控制 |
| 时间固定效应 | 已控制 | 已控制 |
| 县区固定效应 | 已控制 | 已控制 |
| 样本量 | 2 420 | 6 910 |
| R 2 | 0.220 | 0.216 |
表7
表8
数字乡村试点影响农村居民收入的调节效应检验结果
| 变量 | 农村居民收入 |
|---|---|
| 数字乡村试点政策 | -0.275*** |
| GDP | -0.062*** |
| 数字乡村试点政策*GDP | 0.193*** |
| 北大数字金融普惠指数 | |
| 数字乡村试点政策*北大数字金融普惠指数 | |
| 工业化水平 | |
| 数字乡村试点政策*工业化水平 | |
| 控制变量 | 已控制 |
| 时间固定效应 | 已控制 |
| 县区固定效应 | 已控制 |
| 样本量 | 7 270 |
| R 2 | 0.922 |
表8
表9
进一步分析：对城乡包容性增长的影响
| 变量 | 城乡收入差距 |
|---|---|
| 数字试点政策 | 0.041 |
| （0.033） | |
| 控制变量 | 已控制 |
| 时间固定效应 | 已控制 |
| 县区固定效应 | 已控制 |
| 样本量 | 7 270 |
| R 2 | 0.417 |
表9
[参考文献 31](javascript:;)
[1]穆克瑞. 新发展阶段城乡融合发展的主要障碍及突破方向[J]. 行政管理改革, 2021(1): 79-85.
MU K R. The main barriers and breakthrough direction of urban-rural integration during the new development stage[J]. Administration Reform, 2021(1): 79-85.
[2]陈高威, 温铁军. 破局乡村振兴——中国式农业农村现代化的11个思考[M]. 重庆: 重庆出版社, 2023.
[3]LI F L, HE K. Internet use as a catalyst for high-quality nonfarm employment among rural laborers in China[J]. Review of Development Economics, 2025, 29(4): 2258-2275.
[4]张勋, 万广华, 张佳佳, 等. 数字经济、普惠金融与包容性增长[J]. 经济研究, 2019, 54(8): 71-86.
ZHANG X, WAN G H, ZHANG J J, et al. Digital economy, financial inclusion, and inclusive growth[J]. Economic Research Journal, 2019, 54(8): 71-86.
[5]DEICHMANN U, GOYAL A, MISHRA D. Will digital technologies transform agriculture in developing countries [J]. Agricultural Economics, 2016, 47(S1): 21-33.
[6]SALEMINK K, TOWNSEND L, CHAPMAN P. The remapping of rural digitalisation: A just-rural narrative review[J]. Journal of Rural Studies, 2025, 113: 103499.
[7]崔华滨, 王鹏程. 数字乡村建设推动城乡融合发展的作用机制与实现路径[J]. 南京农业大学学报(社会科学版), 2025, 25(4): 152-163.
CUI H B, WANG P C. The mechanism and path for promoting urban-rural integration through digital villages development[J]. Journal of Nanjing Agricultural University (Social Sciences Edition), 2025, 25(4): 152-163.
[8]平卫英, 王瑶华, 张谊瑞. 数字乡村建设、农村居民增收与城乡收入差距——基于国家数字乡村试点的准自然实验[J]. 农业技术经济, 2025(8): 80-104.
PING W Y, WANG Y H, ZHANG Y R. Digital village construction, rural residents' income increase and rural-urban income gap: Quasi-natural experiment based on the national digital village pilots[J]. Journal of Agrotechnical Economics, 2025(8): 80-104.
[9]HE H Y, LESZCZYNSKI A. Digital rurality: A three-fold model and research agenda[J]. Journal of Rural Studies, 2026, 122: 103958.
[10]霍鹏, 肖荣美, 马九杰. 数字乡村建设的底层逻辑、功能价值与路径选择[J]. 改革, 2022(12): 57-65.
HUO P, XIAO R M, MA J J. The underlying logic, functional value and path choice of digital village construction[J]. Reform, 2022(12): 57-65.
[11]LYTHREATIS S, SINGH S K, EL-KASSAR A N. The digital divide: A review and future research agenda[J]. Technological Forecasting and Social Change, 2022, 175: 121359.
[12]罗廷锦, 茶洪旺. "数字鸿沟"与反贫困研究——基于全国31个省市面板数据的实证分析[J]. 经济问题探索, 2018(2): 11-18, 74.
[13]HJORT J, TIAN L. The economic impact of internet connectivity in developing countries[J]. Annual Review of Economics, 2025, 17(1): 99-124.
[14]QIN Q X, GUO H D, SHI X J, et al. Rural E-commerce and county economic development in China[J]. China & World Economy, 2023, 31(5): 26-60.
[15]高雅, 邬红梅. 数字乡村建设对县域经济发展影响的实证检验[J]. 统计与决策, 2025, 41(10): 102-107.
GAO Y, WU H M. An empirical test on the impact of digital village construction on county-level economic development[J]. Statistics & Decision, 2025, 41(10): 102-107.
[16]SU F, WU B R, ZHANG H M, et al. Examining digital village construction's impact on farmers' common prosperity in China: Dynamic and spatial perspectives[J]. Chinese Geographical Science, 2025, 35(6): 1342-1358.
[17]BERGHOLZ C, FÜNER L, LUBCZYK M, et al. Infrastructure required, skill needed: Digital entrepreneurship in rural and urban areas[J]. Journal of Business Venturing Insights,