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基于农户视角农业绿色全要素生产率的测度与分析

程永生 张德元 汪侠

程永生, 张德元, 汪侠. 基于农户视角农业绿色全要素生产率的测度与分析[J]. 中国生态农业学报 (中英文), 2023, 31(5): 820−834 doi: 10.12357/cjea.20220562
引用本文: 程永生, 张德元, 汪侠. 基于农户视角农业绿色全要素生产率的测度与分析[J]. 中国生态农业学报 (中英文), 2023, 31(5): 820−834 doi: 10.12357/cjea.20220562
CHENG Y S, ZHANG D Y, WANG X. Measurement and analysis of agricultural green total factor productivity based on farmers’ perspectives[J]. Chinese Journal of Eco-Agriculture, 2023, 31(5): 820−834 doi: 10.12357/cjea.20220562
Citation: CHENG Y S, ZHANG D Y, WANG X. Measurement and analysis of agricultural green total factor productivity based on farmers’ perspectives[J]. Chinese Journal of Eco-Agriculture, 2023, 31(5): 820−834 doi: 10.12357/cjea.20220562

基于农户视角农业绿色全要素生产率的测度与分析

doi: 10.12357/cjea.20220562
基金项目: 安徽省2022年度哲学社会科学规划项目(AHSKQ2022D039)资助
详细信息
    通讯作者:

    程永生, 主要研究方向为绿色高质量发展与产业经济。E-mail: chengyongsheng@aliyun.com

  • 中图分类号: F32

Measurement and analysis of agricultural green total factor productivity based on farmers’ perspectives

Funds: The study was supported by the Philosophy and Social Science Foundation of Anhui Province (AHSKQ2022D039).
More Information
  • 摘要: 提升农业绿色全要素生产率, 加快农业绿色转型是全面建成社会主义现代化强国的必然选择。研究以中国家庭追踪调查(China Family Panel Studies, CFPS)的全国性大容量样本农户数据为蓝本, 在微观测度方法比较分析的基础上, 基于技术优化的Malmquist-Luenberger指数为基准, 测度分析了农户层农业绿色全要素生产率的状况, 并进一步选用核密度估计法和Dagum基尼系数法, 揭示了微观样本农业绿色全要素生产率的动态演变规律及其区域差异特征。主要研究发现如下: 1)技术优化的Malmquist-Luenberger指数测度显示, 2014年、2016年和2018年3期样本农户的农业绿色全要素生产率均值为1.0030, 总体发展态势良好; 农业绿色技术变化、绿色技术效率变化的共同作用是驱动农户层面农业绿色发展变化的主要引致因素, 且后者的影响程度远大于前者; 农户资源配置、管理模式及组织方式的改善优化, 在现阶段是农户发展绿色农业的提升关键, 其影响相对高于农户农业生产技术的革新。2)通过核密度估算发现, 2016年和2018年样本农户的绿色全要素生产率集中度较高, 农业绿色技术效率并未出现两级分化, 但农业绿色技术进步呈现上升趋势。3) Dagum基尼系数法结果表明, 农户层面农业绿色全要素生产率的区域差距不断缩小, 区域差距的降幅达22.32%, 超变密度是引致主因; 在区域内差距上, 东、西、中部地区内部, 农户的绿色农业差距依次递减; 在区域间差距上, 东西、东中、中西部间差距不断缩小、协同性不断增强, 但差距易受到环境因素影响。
  • 图  1  农业绿色全要素生产率(a, b)、农业绿色技术效率变化(c, d)和农业绿色技术变化(e, f)的核密度分布

    左图为使用虚拟户主的主观污染感知度作为非期望产出; 右图为使用农业化学需氧量、总氮、总磷等标排放量等客观农业面源污染作为非期望产出。The left panel uses the subjective pollution perception of the virtual household head as the non-desired output; the right panel uses objective agricultural non-point source pollution such as agricultural chemical oxygen demand, total nitrogen, total phosphorus equivalents emissions as the non-desired output.

    Figure  1.  Kernel density distribution of agricultural green total factor productivity (a, b), agricultural green technical efficiency change (c, d) and agricultural green technological change (e, f)

    表  1  改进后的农业绿色全要素生产率测算体系

    Table  1.   An improved system for measuring agricultural green total factor productivity

    目标层
    Target layer
    一级指标
    Primary indicator
    二级指标
    Secondary indicator
    变量定义
    Specific variable
    and description
    指标单位
    Indicator unit
    符号
    Symbol
    农业绿色全要素生产率 Agricultural green total factor productivity 投入指标
    Input
    indicators
    资本 Capital 农业生产的流动性资本投入与固定性资本投入之和
    Sum of liquid capital inputs and fixed capital inputs in agricultural production
    ¥ x1
    劳动力 Labor 过去12个月参与的自家农业生产活动的家庭成员数 Number of household members involved in home-based agricultural production activities in the past 12 months Persons x2
    土地 Land 承包地面积与租用地面积之和
    Sum of contracted land area and leased land area
    hm² x3
    期望产出
    指标
    Desired output indicators
    农产品总产出
    Total agricultural output
    过去12个月, 家庭所生产的农产品、养殖物及副产品销售收入以及自家消费总值之和
    Sum of income from the sale of agricultural products, farm products and by-products produced by the household and the total value of own consumption in the past 12 months
    ¥ y1
    非期望产出指标
    Non-desired output indicators
    农业面源污染
    Agricultural non-point source pollution
    农业化学需氧量(COD)等标排放量
    Agricultural chemical oxygen demand (COD) equivalent emissions
    t yu2
    农业总氮(TN)等标排放量
    Agricultural total nitrogen (TN) equivalent emissions
    yu3
    农业总磷(TP)等标排放量
    Agricultural total phosphorus (TP) equivalent emissions
    yu4
    主观污染感知度
    Subjective pollution perception degree
    采用农业活动管账人对环境污染问题严重度的感知, 0代表不严重, 10代表非常严重
    Perception of the severity of environmental pollution problems by the custodians of agricultural activities: 0 = not serious, 10 = very serious.
    yu1
    下载: 导出CSV

    表  2  农业绿色全要素生产率测算的投入和产出指标的描述性统计结果

    Table  2.   Results of descriptive statistics for input and output indicators for measuring agricultural green total factor productivity

    指标
    Index
    样本量
    Sample size
    均值
    Mean value
    标准差
    Standard deviation
    最大值
    Maximum value
    最小值
    Minimum value
    资本 Capital973511.071529.62840.00601000.0000
    劳动力 Labor97353.86801.82981.000021.0000
    土地 Land97350.82352.31920.006773.3333
    农产品总产出 Total agricultural output973516.496835.83450.0010900.0000
    主观污染感知度 Subjective pollution perception degree97356.53002.50241.000010.0000
    化学需氧量等标排放量 Chemical oxygen demand equivalent emissions97352.03742.17630.00879.4930
    总氮等标排放量 Total nitrogen equivalent emissions973538.544027.13811.4973131.6150
    总磷等标排放量 Total phosphorus equivalent emissions973513.553410.07840.976058.9300
    下载: 导出CSV

    表  3  农业绿色全要素生产率测算的投入和产出指标的相关性检验

    Table  3.   Correlation test of input and output indicators for measuring agricultural green total factor productivity

    指标
    Index
    资本
    Capital
    劳动力
    Labor
    土地
    Land
    农产品
    总产出
    Total agricultural
    output
    主观污染
    感知度
    Subjective pollution
    perception degree
    化学需氧量
    等标排放量
    Chemical oxygen demand equivalent emissions equivalent
    emissions
    总氮等标
    排放量
    Total nitrogen equivalent
    emissions
    TP等标
    排放量
    Total phosphorus equivalent
    emissions
    资本 Capital 1.0000
    劳动力 Labor 0.0453*** 1.0000
    土地 Land 0.0512*** 0.0191* 1.0000
    农产品总产出
    Total agricultural output
    0.7714*** 0.0507*** 0.0324*** 1.0000
    主观污染感知度
    Subjective pollution perception degree
    0.0421*** 0.0400*** 0.0378*** 0.0233** 1.0000
    化学需氧量等标排放量
    Chemical oxygen demand equivalent emissions
    0.0473*** 0.0939*** 0.0568*** 0.0285*** 0.0435*** 1.0000
    总氮等标排放量
    Total nitrogen equivalent emissions
    0.0377*** 0.0875*** 0.0703*** 0.0193* 0.0161*** 0.3675*** 1.0000
    总磷等标排放量
    Total phosphorus equivalent emissions
    0.0352*** 0.1113*** 0.0595*** 0.0415*** 0.0212*** 0.4296*** 0.8178*** 1.0000
      ***、**、*分别表示在1%、5%、10%水平显著。***, ** and * denote significance at the 1%, 5%, and 10% levels.
    下载: 导出CSV

    表  4  2016年和2018年基于技术优化Malmquist-Luenberger指数的农业绿色全要素生产率及其分解项

    Table  4.   Agricultural green total factor productivity and its decomposition terms based on technology-optimized Malmquist-Luenberger index for 2016 and 2018

    年份
    Year
    排名
    Rank
    农户代码
    Farmer
    code
    绿色全要素
    生产率
    ML(1)
    绿色技术
    效率变化
    MLTEC(1)
    绿色技术
    进步变化
    MLTC(1)
    农户代码
    Farmer
    code
    绿色全要素
    生产率
    ML(2)
    绿色技术
    效率变化
    MLTEC(2)
    绿色技术
    进步变化
    MLTC(2)
    2016前15名
    Top 15
    4405603.75121.96301.91095002333.76201.98891.8915
    3501083.56321.99941.78215108763.70291.96871.8809
    4417163.42321.98101.72814405603.62101.98621.8231
    5107952.55101.59051.60394417163.55141.97361.7994
    3301772.41941.98371.21975002363.29821.99261.6552
    3601722.30631.78471.29235106673.04361.98901.5302
    4419412.06321.50011.37545002382.77421.61721.7154
    5106672.05281.98751.03295107952.76591.57081.7608
    3201341.89471.71661.10375107902.63061.73991.5120
    1304311.88981.52521.23905002412.56851.67951.5294
    6208471.86801.61401.15736208472.55001.96761.2960
    1407291.86701.58781.17584419412.54741.69751.5007
    4417381.85661.25921.47446210772.48911.96721.2653
    3301751.85611.60691.15515002852.41361.75991.3714
    4410731.84241.45931.26252202122.20191.88261.1696
    后15名
    Last 15
    4502090.61300.55391.10675001490.50280.50550.9947
    5104010.60720.51121.18776213220.50080.63900.7837
    6211260.60490.59471.01726209700.49940.50650.9861
    5001490.59680.50021.19312109370.48680.51100.9527
    4401560.58930.63360.93012118000.48430.54140.8946
    4405080.58230.64760.89921200930.47480.68710.6910
    6200110.55260.54561.01286211970.47330.63330.7474
    6103280.54580.50961.07096214800.44850.57120.7853
    2109370.54190.52161.03886103280.44140.52240.8451
    6831260.53780.54940.97886211260.43850.55670.7876
    2118000.51970.52300.99376212890.41970.56630.7412
    6212890.51970.57680.90101403440.40810.57820.7058
    5304230.48930.60080.81446200110.40530.50630.8007
    1403440.45510.53450.85143501000.40250.77120.5219
    1406470.43460.51210.84866214760.37750.50940.7410
    平均 Average1.00991.01650.99281.01751.02940.9828
    2018前15名
    Top 15
    4416523.59801.99861.80025106505.47011.99342.7441
    5106503.58061.99721.79284416523.59611.99811.7998
    1401522.80381.95111.43704403413.24321.88151.7237
    3704482.40481.95511.23001401522.71561.81851.4933
    5301362.39891.98871.20625301362.47141.98741.2435
    4403412.15831.75521.22976212362.44921.96631.2456
    2109402.14671.72031.24793704482.40751.95841.2293
    1403611.85431.63591.13356202232.40381.93291.2436
    5505661.60991.56061.03166212852.07411.72261.2041
    6211771.60861.29171.24546211771.96211.49071.3162
    4415621.59321.30101.22462109401.94011.39901.3868
    4108581.59041.37461.15706214761.88891.66381.1353
    1309281.53411.37091.11916212751.77291.56161.1353
    3703261.52371.28621.18465505661.75261.61101.0879
    6202231.48961.51130.98566205491.74391.44781.2046
    后15名
    Last 15
    5303350.64270.54461.18011407290.57810.57900.9984
    5302520.63120.55721.13285203420.57670.65850.8758
    6208470.63120.62051.01722108220.57300.50981.1240
    3201340.62390.58941.05865002380.57220.66140.8651
    4502400.62210.53701.15845002850.56250.56580.9942
    4501990.61980.60531.02403601720.53110.52451.0126
    6208780.61430.60851.00976210770.52050.53940.9650
    4419410.60260.59201.01795002330.45260.58970.7676
    6208270.60160.52111.15445002360.44470.50300.8841
    3601720.52690.52800.99786208470.42430.50950.8329
    5106670.52070.50001.04125106670.41930.50000.8386
    4417160.48730.50640.96224405600.31030.50190.6183
    3301770.47640.50490.94364419410.30210.53990.5596
    5107950.34450.52710.65355107950.29930.53270.5617
    4405600.23930.50610.47284417160.26630.50430.5281
    平均 Average0.99600.97651.02000.99740.97131.0259
      限于篇幅, 仅展示出农业绿色全要素生产率排名前15位、后15位农户和样本农户年度均值的结果。其中, ML(1)、MLTEC(1)、MLTC(1)分别表示使用虚拟户主主观污染感知度作为非期望产出的农业绿色全要素生产率、绿色技术效率变化、绿色技术进步变化; ML(2)、MLTEC(2)、MLTC(2)分别表示使用农业化学需氧量、总氮和总磷等标排放量等农业面源污染作为非期望产出的农业绿色全要素生产率、绿色技术效率变化、绿色技术进步变化。Due to the limitation of space, only the results of the top 15 farmers, the bottom 15 farmers and the annual average value of the sample farmers are shown. Among them, ML(1), MLTEC(1), and MLTC(1) denote agricultural green total factor productivity, green technical efficiency change, and green technological progress change using virtual household head subjective pollution perception as non-desired outputs; ML(2), MLTEC(2), and MLTC(2) denote agricultural green total factor productivity, green technical efficiency change, and green technical progress change in agriculture using agricultural non-point source pollution such as agricultural chemical oxygen demand, total nitrogen, and total phosphorus equivalents emissions as non-desired output.
    下载: 导出CSV

    表  5  农业绿色全要素生产率的区域差距及其来源

    Table  5.   Regional gaps in agricultural green total factor productivity in and their sources

    年份
    Year
    总体差距
    Overall gap
    区域内差距
    Intra-regional gap
    区域间差距
    Inter-regional gap
    超变密度
    Super variable density
    贡献率 Contribution rate (%)
    区域内差距
    Intra-regional gap
    区域间差距
    Inter-regional gap
    超变密度
    Super variable density
    (1)20160.04660.01590.00270.028034.125.7960.09
    20180.03620.01240.00020.023634.250.5565.19
    (2)20160.07800.02740.00410.046535.135.2659.62
    20180.04960.01740.00140.030835.082.8262.10
      (1)、(2)分别表示使用虚拟户主主观污染感知度作为非期望产出、使用农业化学需氧量、总氮、总磷等标排放量等客观农业面源污染作为非期望产出。(1) and (2) denote the use of virtual household subjective pollution perceptions as non-desired output and objective agricultural non-point source pollution such as agricultural chemical oxygen demand, total nitrogen, total phosphorus equivalents emissions as non-desired output.
    下载: 导出CSV

    表  6  东、中、西部农业绿色全要素生产率的区域内差距和区域间差距

    Table  6.   Intra-regional and inter-regional disparities in green total factor productivity in agriculture in East, Central and West

    年份 Year区域内差距 Intra-regional gap区域间差距 Inter-regional gap
    东 East中 Central西 West东—中 East−central东—西 East−west中—西 Central−west
    (1)20160.05510.03570.04770.04570.05150.0419
    20180.03980.02950.03820.03480.03900.0340
    (2)20160.05200.04500.04990.05370.08520.0857
    20180.04030.03480.03580.03770.05440.0515
      (1)、(2)分别表示使用虚拟户主主观污染感知度作为非期望产出、使用农业化学需氧量、总氮、总磷等标排放量等客观农业面源污染作为非期望产出。(1) and (2) denote the use of virtual household subjective pollution perceptions as non-desired output and objective agricultural surface source pollution such as agricultural chemical oxygen demand, total nitrogen, total phosphorus equivalents emissions as non-desired output.
    下载: 导出CSV
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出版历程
  • 收稿日期:  2022-07-21
  • 录用日期:  2022-10-20
  • 网络出版日期:  2022-11-25
  • 刊出日期:  2023-05-10

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