气候智慧型农业项目能否抑制农业碳排放——来自安徽气候智慧型主要粮食作物生产项目的经验证据

doi:10.3969/j.issn.1004-1524.2023.03.21

浙江农业学报 ›› 2023, Vol. 35 ›› Issue (3): 676-687.DOI: 10.3969/j.issn.1004-1524.2023.03.21

气候智慧型农业项目能否抑制农业碳排放——来自安徽气候智慧型主要粮食作物生产项目的经验证据

魏新彦¹^,²(), 刘颖³^,^*(), 张俊飚¹^,²

1.华中农业大学经济管理学院,湖北武汉 430070
2.湖北农村发展研究中心,湖北武汉 430070
3.北方工业大学经济管理学院,北京 100144

收稿日期:2022-02-23 出版日期:2023-03-25 发布日期:2023-04-07
通讯作者: ^*刘颖,E-mail:liuying@mail.hzau.edu.cn
作者简介:魏新彦(1996—),女,湖北襄阳人,博士研究生,主要研究方向为农业资源与环境经济。E-mail:hzauwxy@foxmail.com
基金资助:
国家社会科学基金重大项目(19AZD020)

Can Climate-Smart Agriculture Project reduce agricultural carbon emission: experience evidence from Climate-Smart Staple Crop Production Project in Anhui, China

WEI Xinyan¹^,²(), LIU Ying³^,^*(), ZHANG Junbiao¹^,²

1. College of Economics and Management, Huazhong Agricultural University, Wuhan 430070, China
2. Hubei Rural Development Research Center, Wuhan 430070, China
3. School of Economics and Management, North China University of Technology, Beijing 100144, China

Received:2022-02-23 Online:2023-03-25 Published:2023-04-07

摘要/Abstract

摘要：

基于安徽省2011—2019年23个县的面板数据,在熊彼特创新理论和波特创新驱动理论的指导下,采用合成控制法评估气候智慧型主要粮食作物生产项目对怀远县农业碳排放的影响及其作用机制。研究发现:气候智慧型主要粮食作物生产项目对农业碳排放的影响效应具有一定的时滞性,在实施当年并未对怀远县人均农业碳排放量产生抑制作用,但有效抑制了2016—2019年怀远县的人均农业碳排放量。经统计,2015—2019年,怀远县的人均农业碳排放量年均下降1.977 6 kg,年均降幅为1.43%。中介检验结果表明,项目运用现代技术和理念推动了农业发展模式的创新,通过创新驱动产生结构效应和技术效应,促进怀远县农业结构转型升级和生物化学型技术进步,进而抑制了农业碳排放。

关键词: 农业碳排放, 气候智慧型农业, 合成控制法, 怀远县, 创新理论, 创新驱动理论

Abstract:

Based on the panel data of 23 counties in Anhui, China during 2011-2019, under the guidance of Joseph Schumpeter’s innovation theory and Baud’s innovation-driven theory, the synthetic control method was adopted to evaluate the effects of the Climate-Smart Staple Crop Production Project on agricultural carbon emissions in Huaiyuan County and to explore the corresponding action mechanism. It was shown that the Climate-Smart Staple Crop Production Project had certain time lag effect on agricultural carbon emission, as it did not inhibit the per capita agricultural carbon emissions in Huaiyuan County in the initial stage, but it effectively suppressed per capita agricultural carbon emissions in Huaiyuan County from 2016 to 2019. It was calculated that the average annual decline of per capita agricultural carbon emissions was 1.977 6 kg (or 1.43%) in Huaiyuan County during 2015-2019. The intermediary test results showed that the project had promoted the innovation of agricultural development pattern by using modern technology and ideas, and had produced structural and technological effects through innovation, by promoting the structural transformation and upgrading of agriculture in Huaiyuan County and the development of biochemical technologies. Thus, the agricultural carbon emissions in Huaiyuan County has been curbed.

Key words: agricultural carbon emission, climate smart agriculture, synthetic control method, Huaiyuan County, innovation theory, innovation-driven theory

中图分类号:

魏新彦, 刘颖, 张俊飚. 气候智慧型农业项目能否抑制农业碳排放——来自安徽气候智慧型主要粮食作物生产项目的经验证据[J]. 浙江农业学报, 2023, 35(3): 676-687.

WEI Xinyan, LIU Ying, ZHANG Junbiao. Can Climate-Smart Agriculture Project reduce agricultural carbon emission: experience evidence from Climate-Smart Staple Crop Production Project in Anhui, China[J]. Acta Agriculturae Zhejiangensis, 2023, 35(3): 676-687.

图/表 7

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变量 Variable	平均值 Mean	标准差 Standard deviation	最小值 Minimum	最大值 Maximum
C	111.809 1	59.111 7	30.052 5	611.664 5
Z₁	13.275 7	0.888 5	11.164 1	14.851 4
Z₂	0.351 0	0.117 5	0.002 6	0.675 4
Z₃	0.216 0	0.114 2	0.073 1	0.843 6
Z₄	0.485 6	0.093 9	0.050 6	0.686 9
Z₅	6.275 6	0.355 4	5.380 2	7.923 8
Z₆	4.728 9	0.680 8	3.402 9	6.416 2
Z₇	4.561 8	0.410 9	3.530 4	5.236 5

变量 Variable	平均值 Mean	标准差 Standard deviation	最小值 Minimum	最大值 Maximum
C	111.809 1	59.111 7	30.052 5	611.664 5
Z₁	13.275 7	0.888 5	11.164 1	14.851 4
Z₂	0.351 0	0.117 5	0.002 6	0.675 4
Z₃	0.216 0	0.114 2	0.073 1	0.843 6
Z₄	0.485 6	0.093 9	0.050 6	0.686 9
Z₅	6.275 6	0.355 4	5.380 2	7.923 8
Z₆	4.728 9	0.680 8	3.402 9	6.416 2
Z₇	4.561 8	0.410 9	3.530 4	5.236 5

变量符号 Variable symbol	真实值 Real value	拟合值 Synthetic value
Z₁ Z₂	14.787 8 0.391 4	13.876 5 0.413 9
Z₃	0.137 6	0.106 0
Z₄	0.572 0	0.498 1
Z₅	6.177 4	6.193 2
Z₆	4.827 5	4.833 0
Z₇	4.898 6	4.889 8

变量符号 Variable symbol	真实值 Real value	拟合值 Synthetic value
Z₁ Z₂	14.787 8 0.391 4	13.876 5 0.413 9
Z₃	0.137 6	0.106 0
Z₄	0.572 0	0.498 1
Z₅	6.177 4	6.193 2
Z₆	4.827 5	4.833 0
Z₇	4.898 6	4.889 8

年份 Year	影响效应 Effect/kg	变化率 Change rate/%
2015	2.229 9	1.57
2016	-0.408 4	-0.29
2017	-3.479 5	-2.51
2018	-5.6431	-4.10
2019	-2.587 0	-1.84

气候智慧型农业项目能否抑制农业碳排放——来自安徽气候智慧型主要粮食作物生产项目的经验证据

Can Climate-Smart Agriculture Project reduce agricultural carbon emission: experience evidence from Climate-Smart Staple Crop Production Project in Anhui, China

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变量 Variable	lnC	Z₄	lnC	Z₁	lnC	Z₂	lnC
D	-1.650^*** (0.023)	-0.135^*** (0.011)	-0.995^*** (0.340)	-0.024 (0.029)	-1.650^*** (0.024)	-0.263^*** (0.011)	-0.522 (0.617)
Z₄	—	—	4.853^* (2.479)	—	—	—	—
Z₁	—	—	—	—	-0.012 (0.143)	—	—
Z₂	—	—	—	—	—	—	4.283^* (2.293)
常数项 Constant	10.225^*** (0.357)	0.051 (0.175)	9.976^*** (0.661)	12.849^*** (0.346)	10.385^*** (1.874)	0.391^* (0.220)	8.549^*** (0.861)
n	207	207	207	207	207	207	207
R²	0.851	0.719	0.926	0.990	0.851	0.619	0.933

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