Analysis of Green Total Factor Productivity of Main Crops in China

doi:10.13304/j.nykjdb.2020.0963

Abstract

Abstract:

More attention should be paid to the green development of agriculture under the constraints of agricultural environmental resource endowments. Assuming the agricultural pollution emission coefficient was a dynamically changing parameter， based on the dynamic measurement of the unexpected output of agricultural non-point source pollution， the SBM super-efficiency model and DEA-Malmquist productivity index were employed to measure the green total factor productivity （GTFP） of major agricultural crops. The results showed as follows：①the environmental technical efficiency of Japonica rice and soybean was greater than 1， while the environmental technical efficiencies of corn， wheat and cotton were less than 1； ② the green total factor productivities of cotton， Japonica rice and corn annual increased by 0.7%， 0.4%， and 0.3%， respectively， while the green total factor productivities of wheat and soybean annual decreased by 1.6% and 1.2%， respectively； ③ green total factor productivity was significantly different from traditional total factor productivity， and its green technology progress was even more significant； ④ improving the educational level of agricultural employees， increasing investment in agricultural science and technology， and strengthening environmental pollution control were endogenously driven to promote green total factor productivity growth. Calculating and analyzing green productivity of crop could reflect the comprehensive production capacity of each crops and the actual productivity status of the main crops.

Key words: environmental technology efficiency, GTFP, theory of dynamic optimal, dynamic measurement

摘要：

在农业环境资源禀赋刚性约束下应更注重农业的绿色发展。假设农业污染排放系数是一个动态变化的参数，基于动态测算农业面源污染非期望产出，运用SBM超效率模型和DEA-Malmquist生产率指数测算主要农作物的绿色全要素生产率。研究发现：①粳稻和大豆的环境技术效率大于1，而玉米、小麦和棉花的环境技术效率小于1；②棉花、粳稻和玉米的绿色全要素生产率年均增长0.7%、0.4%和0.3%，而小麦和大豆的绿色全要素生产率年均降低1.6%和1.2%，主要农作物主产区间的绿色全要素生产率存在差异；③绿色全要素生产率与传统全要素生产率具有明显差异，其绿色技术进步更显著；④提高农业从业人员受教育水平，加大农业科技投资和加强环境污染治理等内生驱动促进绿色全要素生产率增长。分作物测算并分析其绿色全要素生产率，能更好地反映各作物的综合生产能力，体现主要作物的实际生产率状况。

关键词: 环境技术效率, 绿色全要素生产率, 动态优化理论, 动态测算

CLC Number:

F328

Huiquan LI, Shiping MAO. Analysis of Green Total Factor Productivity of Main Crops in China[J]. Journal of Agricultural Science and Technology, 2022, 24(2): 58-67.

李慧泉, 毛世平. 我国主要农作物绿色全要素生产率分析[J]. 中国农业科技导报, 2022, 24(2): 58-67.

Figures/Tables 6

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指标 Indicator	要素 Element	界定 Definition	单位 Unit
投入指标 Input indicator	劳动力Labor factor	劳动力投入量Labor input	人·hm^-2 People·hm^-2
	化肥用量Fertilizer	化肥折纯用量Fertilizer consumption	kg·hm^-2
	机械成本Mechanical cost	机械成本Machinery cost	元·hm^-2 yuan·hm^-2
	其他要素Other elements	其他费用之和Sum of other costs	元·hm^-2 yuan·hm^-2
产出指标 Output indicator	期望产出Expected output	主产品产量Main product yield	kg·hm^-2
产出指标 Output indicator	非期望产出 Undesired output	生产过程中总氮、总磷的排放量之和 Sum of total nitrogen and total phosphorus emissions	kg·hm^-2

指标 Indicator	要素 Element	界定 Definition	单位 Unit
投入指标 Input indicator	劳动力Labor factor	劳动力投入量Labor input	人·hm^-2 People·hm^-2
	化肥用量Fertilizer	化肥折纯用量Fertilizer consumption	kg·hm^-2
	机械成本Mechanical cost	机械成本Machinery cost	元·hm^-2 yuan·hm^-2
	其他要素Other elements	其他费用之和Sum of other costs	元·hm^-2 yuan·hm^-2
产出指标 Output indicator	期望产出Expected output	主产品产量Main product yield	kg·hm^-2
产出指标 Output indicator	非期望产出 Undesired output	生产过程中总氮、总磷的排放量之和 Sum of total nitrogen and total phosphorus emissions	kg·hm^-2

年份 Year	玉米Corn	小麦Wheat	粳稻Rice	棉花Cotton	大豆Soybean
1998—1999	0.876	0.824	0.978	0.897	1.008
2016—2017	1.012	0.947	1.211	1.107	1.284
1998—2017	0.978	0.962	1.078	0.982	1.012

年份 Year	玉米Corn	小麦Wheat	粳稻Rice	棉花Cotton	大豆Soybean
1998—1999	0.876	0.824	0.978	0.897	1.008
2016—2017	1.012	0.947	1.211	1.107	1.284
1998—2017	0.978	0.962	1.078	0.982	1.012

作物 Crop	GTFP	GEC	GTC	TFP	EC	TC
粳稻Rice	1.004	1.000	1.004	1.012	1.000	1.012
玉米Corn	1.003	0.997	1.006	1.006	1.001	1.005
小麦Wheat	0.984	0.980	1.004	0.992	0.999	0.993
棉花Cotton	1.007	0.997	1.010	1.015	1.003	1.012
大豆Soybean	0.988	1.000	0.988	1.003	1.001	1.002