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土地整治对农业碳排放的影响研究

熊飞雪 赵星磊 郭子毅 朱述斌

熊飞雪, 赵星磊, 郭子毅, 朱述斌. 土地整治对农业碳排放的影响研究−基于高标准农田建设政策的准自然实验[J]. 中国生态农业学报 (中英文), 2023, 31(12): 1−11 doi: 10.12357/cjea.20230353
引用本文: 熊飞雪, 赵星磊, 郭子毅, 朱述斌. 土地整治对农业碳排放的影响研究−基于高标准农田建设政策的准自然实验[J]. 中国生态农业学报 (中英文), 2023, 31(12): 1−11 doi: 10.12357/cjea.20230353
XIONG F X, ZHAO X L, GUO Z Y, ZHU S B. Research on the effects of rural land consolidation on agricultural carbon emissions: a quasi-natural experiment based on the high-standard farmland construction policy[J]. Chinese Journal of Eco-Agriculture, 2023, 31(12): 1−11 doi: 10.12357/cjea.20230353
Citation: XIONG F X, ZHAO X L, GUO Z Y, ZHU S B. Research on the effects of rural land consolidation on agricultural carbon emissions: a quasi-natural experiment based on the high-standard farmland construction policy[J]. Chinese Journal of Eco-Agriculture, 2023, 31(12): 1−11 doi: 10.12357/cjea.20230353

土地整治对农业碳排放的影响研究基于高标准农田建设政策的准自然实验

doi: 10.12357/cjea.20230353
基金项目: 国家自然科学基金项目(71840013)、2021年江西省富硒农业专项(JXFXZD-2021-02)和江西农业大学经济管理学院2023年研究生创新专项资助项目(JG2023013)资助
详细信息
    作者简介:

    熊飞雪, 主要研究方向为农业资源与环境管理。E-mail: feixuexiong@163.com

    通讯作者:

    朱述斌, 主要研究方向为农林经济理论与政策、休闲农业与农村区域发展。E-mail: shubinzhu@163.com

  • 中图分类号: F323

Research on the effects of rural land consolidation on agricultural carbon emissions: a quasi-natural experiment based on the high-standard farmland construction policy

Funds: This study was supported by the National Natural Science Foundation of China (71840013), Jiangxi Province Selenium-Rich Agriculture Special Project 2021 (JXFXZD-2021-02) and 2023 Graduate Student Innovation Special Fund Project, School of Economics and Management, Jiangxi Agricultural University (JG2023013).
More Information
  • 摘要: 在“碳达峰、碳中和”目标下, 高标准农田建设被视为推动农业绿色低碳高质量发展的重要举措。本研究旨在深入探究高标准农田建设政策对农业碳排放的影响效应与作用机制, 为优化政策制定和农业碳减排提供经验依据, 促进低碳农业发展。本文基于2007—2017年中国30个省份的面板数据, 借助高标准农田建设政策和连续DID (Differences-in-differences)模型, 评估高标准农田建设政策对农业碳排放的影响。结果表明: 研究期间, 全国农业碳排放量呈先升后降的倒U型变化趋势, 2015年达到峰值。基准回归结果发现, 高标准农田建设政策显著抑制了农业碳排放。平均来看, 当其他条件不变时, 实施高标准农田建设政策可以显著减少10.1%的农业碳排放量。在替换解释变量和被解释变量以及剔除其他政策影响后, 高标准农田建设政策对农业碳排放的抑制作用依旧显著。动态估计结果显示, 高标准农田建设政策的减碳效应具有滞后性, 减碳效应于2013年显现出来并逐渐增强。机制分析发现, 高标准农田建设政策主要通过降低农业化学品投入强度和提高社会化服务来抑制农业碳排放。异质性分析发现, 高标准农田建设政策的减碳效应主要发生在土地流转程度高的省份和非粮食主产区, 而在土地流转程度低的省份和粮食主产区并未发挥相应的减碳效应。因此, 各级政府应差异化、精准化实施高标准农田建设政策, 关注农业化学化和社会化服务在减碳效应中的作用。
  • 图  1  2007—2017年全国农业碳排放量

    Figure  1.  National agricultural carbon emissions from 2007 to 2017 in China

    图  2  高标准农田建设政策对农业碳排放的动态影响

    Figure  2.  Dynamic impact of high-standard farmland construction policy on agricultural carbon emissions

    表  1  高标准农田建设政策对农业碳排放影响的相关变量说明与描述性统计

    Table  1.   Definition and statistical description of relevant variables of high-standard farmland construction policy that have impacts on agricultural carbon emissions

    类型
    Type
    名称
    Name
    符号
    Symbol
    测量方法
    Measurement method
    均值
    Mean
    标准差
    Standard
    deviation
    最小值
    Minimum
    value
    最大值
    Maximum
    value
    被解释变量
    Explained variable
    农业碳排放量
    Agricultural carbon emission (×104 t)
    ACE农业活动碳排放
    Carbon emissions from agricultural activities
    286.463200.17712.159874.300
    核心解释变量
    Core explaining variable
    土地整治面积占比
    Percentage of rural land consolidation area to total area (%)
    HFC中低产田改造与高标准农田面积/耕地
    总面积
    Ratio of area of improved land with low and medium yield and high-standard farmland to total arable land area
    39.23922.7118.012130.039
    控制变量
    Control variable
    受灾程度
    Degree of disaster (%)
    Dis受灾面积/农作物播种面积
    Ratio of disaster area to crop sown area
    20.79014.5670.94569.545
    环境污染治理投资Environmental pollution control investment (%)Env环境污染治理投资/国内总产值
    Ratio of environmental pollution control investment to Gross Domestic Product
    1.3960.6970.3004.240
    农业产业结构
    Agricultural industry structure (%)
    Ind农业总产值/农林牧渔业总产值
    Ratio of total agricultural output value to total output value of agriculture, forestry, animal husbandry and fishery
    52.4598.55033.77578.330
    经济发展水平
    Level of economic development (¥·cap.−1)
    Eco人均国内总产值
    Gross Domestic Product per capita
    42 556.38023 928.0406915.00012 8994.100
    财政支农力度
    Financial support for agriculture (%)
    Fin财政支农支出/总财政支出
    Ratio of financial support for agriculture expenditure to total financial expenditure
    10.8463.0492.86918.966
    种植结构
    Planting structure (%)
    Pla粮食播种面积/农作物播种面积
    Ratio of grain sown area to crop sown area
    65.41712.96532.81595.847
    城镇化率
    Urbanization rate (%)
    Urb城镇人口所占比例
    Percentage of urban population
    54.43713.56828.24089.600
    土地经营规模
    Land operation scale
    (hm2∙cap.−1)
    Sca农作物播种面积/农业劳动力
    Ratio of crop sown area to agricultural labor
    1.2660.5450.5883.761
    中介变量
    Intermediate variable
    农业化学品投入强度 Agricultural chemical products input intensity
    (t∙hm−2)
    ACII化肥、农药、农膜使用总量/
    农作物播种面积
    Ratio of total use amount of fertilizer, pesticide and agricultural film to crop sown area
    0.3970.1330.1530.875
    农业社会化服务
    Agricultural socialization services (×107 ¥∙hm−2)
    ASS农林牧渔服务业产值/
    农作物播种面积
    Raito of output value of agriculture, forestry, animal husbandry and fishery services to crop sown area
    0.2240.1460.0300.903
    下载: 导出CSV

    表  2  2007—2017年各地区农业碳排放情况

    Table  2.   Agricultural carbon emissions in each region from 2007 to 2017 ×104 t 

    地区 Region200720152017地区 Region200720152017
    北京 Beijing25.08618.41515.310河南 Henan707.960874.300856.261
    天津 Tianjin41.08436.83632.160湖北 Hubei401.744444.147422.021
    河北 Hebei682.234600.696539.937湖南 Hunan314.679360.992357.680
    山西 Shanxi141.124168.726162.226广东 Guangdong305.186362.672362.644
    内蒙古 Inner Mongolia195.216328.671331.298广西 Guangxi279.245338.073336.485
    辽宁 Liaoning239.287287.380269.705海南 Hainan71.69695.98987.329
    吉林 Jilin216.945314.227312.849重庆 Chongqing112.751135.393133.294
    黑龙江 Heilongjiang303.266416.230414.070四川 Sichuan327.277358.917349.920
    上海 Shanghai36.86528.90326.977贵州 Guizhou102.826136.151130.082
    江苏 Jiangsu455.379460.457445.116云南 Yunnan228.728353.006356.067
    浙江 Zhejiang259.705265.898255.737陕西 Shaanxi197.149295.596297.065
    安徽 Anhui410.426467.532443.776甘肃 Gansu150.295251.655222.010
    福建 Fujian216.671225.017214.949青海 Qinghai12.15918.35217.539
    江西 Jiangxi201.855226.769216.292宁夏 Ningxia46.83860.11560.293
    山东 Shandong836.884759.961722.101新疆 Xinjiang239.069439.550435.613
    下载: 导出CSV

    表  3  高标准农田建设政策对农业碳排放的基准回归结果

    Table  3.   Baseline regression results of high-standard farmland construction policy on agricultural carbon emissions

    变量
    Variable
    模型1
    Model 1
    模型2
    Model 2
    HFC×T2011−0.154*** (0.055)−0.101** (0.038)
    Dis0.000 (0.000)
    Env0.026 (0.027)
    Ind0.003 (0.003)
    Eco0.169 (0.116)
    Fin0.019*** (0.006)
    Pla−0.003 (0.004)
    Urb0.011 (0.009)
    Sca0.069 (0.054)
    常数项
    Constant term
    5.187*** (0.024)2.752** (1.205)
    年份固定效应
    Year fixed effect
    已控制 Control

    已控制 Control
    已控制 Control

    已控制 Control
    省份固定效应
    Provincial fixed effect
    观测值数
    Number of observations
    330330
    R20.43750.5664
      HFC和T2011分别表示土地整治面积占比和高标准农田建设政策实施时点虚拟变量。其他变量解释说明见表1。*、**和***分别表示在10%、5%和1%的统计水平显著相关; 括号内为稳健标准误。HFC and T2011 are percentage of area of land consolidation to total arable land area and dummy variable of time related to policy implementation, respectively. The explanations of the other variables are shown in Table 1. *, ** and *** indicate significant correlations at 10%, 5%, and 1% levels, respectively. The robust standard errors are in parentheses.
    下载: 导出CSV

    表  4  高标准农田建设政策对农业碳排放影响的稳健性检验结果

    Table  4.   Robustness test results of the impact of high-standard farmland construction policy on agricultural carbon emissions

    变量
    Variable
    模型3 (替换核心解释变量)
    Model 3 (substitution of core explaining variable)
    模型4 (替换被解释变量)
    Model 4 (substitution of explained variable)
    剔除其他政策干扰
    Remove other policy distractions
    模型5 (化肥农药零增长政策)
    Model 5 (fertilizer and pesticide zero growth policy)
    模型6 (土地流转政策)
    Model 6 (land transfer policy)
    HFC×T2011−0.086** (0.035)−0.061* (0.031)−0.096*** (0.035)
    CADI×T2011−0.053** (0.023)
    Tra−0.004** (0.002)
    常数项 Constant term2.894** (1.275)9.425*** (1.430)0.265 (1.330)2.802** (1.072)
    控制变量 Control variable

    已控制 Control

    已控制 Control


    已控制 Control

    已控制 Control


    已控制 Control

    已控制 Control


    已控制 Control

    已控制 Control
    年份固定效应
    Year fixed effects
    省份固定效应
    Provincial fixed effects
    观测值数
    Number of observations
    330330240330
    R20.55240.91810.66980.5967
      HFC、T2011、 CADI和Tra分别表示土地整治面积占比、高标准农田建设政策实施时点虚拟变量、单位农作物播种面积农业综合开发投入和土地流转水平。*、**和***分别表示在10%、5%和1%的统计水平上显著相关; 括号内为稳健标准误。HFC, T2011, CADI and Tra are percentage of area of land consolidation to total arable land area, dummy variable of time related to policy implementation, comprehensive investment for agriculture per unit crop sown area, and land transfer level, respectively. *, ** and *** indicate significant correlations at 10%, 5%, and 1% levels, respectively. The robust standard errors are in parentheses.
    下载: 导出CSV

    表  5  高标准农田建设政策对农业碳排放的动态影响估计结果

    Table  5.   Dynamic estimation results of the impact of high-standard farmland construction policy on agricultural carbon emissions

    交互项
    Interaction term
    估计系数
    Estimated coefficient
    标准误
    Standard
    error
    P
    P value
    HFC×2007 0.060 0.043 0.168
    HFC×20080.0400.0400.322
    HFC×20090.0380.0250.145
    HFC×20100.0290.0180.129
    HFC×2012−0.0220.0150.159
    HFC×2013−0.0420.0180.025
    HFC×2014−0.0780.0280.009
    HFC×2015−0.0880.0390.031
    HFC×2016−0.0950.0360.014
    HFC×2017−0.1230.0480.015
      HFC表示土地整治面积占比。2007、2008、2009、2010、2012、2013、2014、2015、2016和2017表示年份虚拟变量。HFC refers to the percentage of land consolidation area to total arable land area. 2007, 2008, 2009, 2010, 2012, 2013, 2014, 2015, 2016 and 2017 refer to the year dummy variables.
    下载: 导出CSV

    表  6  高标准农田建设政策对农业碳排放影响的机制检验结果

    Table  6.   Mechanism test results of the impact of high-standard farmland construction policy on agricultural carbon emissions

    变量
    Variable
    模型7
    Model 7 (ACII)
    模型8
    Model 8 (ASS)
    模型9
    Model 9 (ACE)
    模型10
    Model 10 (ACE)
    HFC×T2011−0.025* (0.013)0.045* (0.025)−0.085** (0.038)−0.086** (0.037)
    ACII0.645** (0.282)
    ASS−0.341* (0.194)
    常数项 Constant term1.054** (0.462)1.144** (0.552)2.071* (1.111)3.142*** (1.122)
    控制变量 Control variable
    已控制 Controlled
    已控制 Control

    已控制 Controlled
    已控制 Control

    已控制 Controlled
    已控制 Control

    已控制 Controlled
    已控制 Control
    年份固定效应 Year fixed effects
    省份固定效应 Provincial fixed effects
    观测值数 Number of observations330330330330
    R20.50310.79430.59790.5851
      HFC和T2011分别表示土地整治面积占比和高标准农田建设政策实施时点虚拟变量。ACII、ASS和ACE解释见表1。*、**和***分别表示在10%、5%和1%的统计水平显著相关; 括号内为稳健标准误。HFC and T2011 are percentage of area of land consolidation to total arable land and dummy variable of time related to policy implementation, respectively. Details of ACII, ASS and ACE can be seen in Table 1. *, ** and *** indicate significant correlation at 10%, 5%, and 1% levels, respectively. Robust standard errors are in parentheses.
    下载: 导出CSV

    表  7  高标准农田建设政策对农业碳排放影响的异质性回归结果

    Table  7.   Heterogeneity regression results of the impact of high-standard farmland construction policy on agricultural carbon emissions

    变量
    Variable
    模型11 (土地流转程度高)
    Model 11 (high level
    of land transfer)
    模型12 (土地流转程度低)
    Model 12 (low level
    of land transfer)
    模型13 (粮食主产区)
    Model 13 (Major grain
    producing areas)
    模型14 (非粮食主产区)
    Model 14 (non-grain
    producing areas)
    HFC×T2011−0.120*** (0.036)−0.062 (0.067)−0.032 (0.023)−0.111* (0.054)
    常数项 Constant term3.085***(1.006)4.167** (1.925)5.630*** (1.246)2.095 (1.585)
    控制变量 Control variable已控制 Controlled已控制 Controlled已控制 Controlled已控制 Controlled
    年份固定效应 Year fixed effects已控制 Controlled已控制 Controlled已控制 Controlled已控制 Controlled
    省份固定效应 Provincial fixed effects
    观测值数 Number of observations143187143187
    R20.72820.66430.64270.7098
      HFC和 T2011分别表示土地整治面积占比和高标准农田建设政策实施时点虚拟变量。*、**和***分别表示在10%、5%和1%的统计水平显著相关; 括号内为稳健标准误。HFC and T2011 are percentage of area of land consolidation to total arable land and dummy variable of time related to policy implementation, respectively. *, ** and *** indicate significant correlation at 10%, 5%, and 1% levels, respectively. Robust standard errors are in parentheses.
    下载: 导出CSV
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  • 附表1 区域土地流转水平和农业功能区分区.docx
    附表2 2007—2017年各地区农业碳排放情况.docx
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  • 收稿日期:  2023-06-27
  • 录用日期:  2023-08-18
  • 修回日期:  2023-08-26
  • 网络出版日期:  2023-09-05

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