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

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

熊飞雪^1,,
赵星磊¹,
郭子毅¹,
朱述斌^{1, 2, ,}

1.
江西农业大学经济管理学院　南昌　330045
2.
江西农业大学江西省农村发展研究中心　南昌　330045

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
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出版历程
- 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

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

XIONG Feixue^1
,,
ZHAO Xinglei¹,
GUO Ziyi¹,
ZHU Shubin^{1, 2
, ,}

1.
School of Economics and Management, Jiangxi Agricultural University, Nanchang 330045, China
2.
Rural Development Research Center of Jiangxi Province, Jiangxi Agricultural University, Nanchang 330045, China

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

Corresponding author: E-mail: shubinzhu@163.com

摘要

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。
- 土地整治 /
- 农业碳排放 /
- 高标准农田建设政策 /
- 双重差分法
Abstract: Under the carbon emission pattern of “carbon peak and carbon neutral”, agricultural carbon emissions, as one of the main sources of greenhouse gases, have become a key area for emission reduction. High-standard farmland construction is an important measure for promoting green, low-carbon, and high-quality agricultural development. An in-depth investigation of the effects and mechanisms of high-standard farmland construction policies on agricultural carbon emissions can provide an empirical basis for optimizing policy formulation and reducing agricultural carbon emissions. This is of great significance in promoting the development of low-carbon agriculture. Based on the theories of scale economy and division of labor, this study constructed a theoretical model of “high-standard farmland construction-agrochemical input intensity/socialized service-agricultural carbon emission”. Based on panel data from 30 provinces in China from 2007 to 2017, this study analyzed the effect and mechanism of the high-standard farmland construction policy on agricultural carbon emissions using a continuous differences-in-differences approach (DID) and mediation effect model. By measuring the agricultural carbon emissions of each province, this study found that national agricultural carbon emissions showed an inverted U-shaped trend, rising at the beginning, then declining, and peaking in 2015. Regions such as Henan, Shandong, Hebei, Jiangsu, and Anhui are at the forefront of agricultural carbon emissions nationwide, whereas regions such as Beijing, Shanghai, Tianjin, Hebei, and Shandong have higher rates of agricultural carbon emission reduction. The dynamic estimation results showed that the carbon reduction of the high-standard farmland construction policy had a lag effect, and the carbon reduction effect appeared in 2013 and continued to increase gradually. The results of the benchmark regression showed that a high-standard farmland construction policy significantly suppressed agricultural carbon emissions. On average, when all other conditions remained unchanged, implementing a high-standard farmland construction policy reduced agricultural carbon emissions significantly, i.e., by 10.1%. Robustness tests were conducted using the approach of substituting variables and considering the interference of other relevant policies. The results confirmed the positive effect of the high-standard farmland construction policy on reducing agricultural carbon emissions. The results of the mechanism analysis showed that agricultural chemical input intensity and agricultural socialized services played mediating roles in reducing agricultural carbon emissions through the construction of high-standard farmland. The construction of high-standard farmlands suppressed agricultural carbon emissions, mainly by reducing agricultural chemical input intensity and improving agricultural socialized services. Heterogeneity analysis revealed that the carbon reduction effect of the high-standard farmland construction policy mainly occured in provinces with a high degree of land transfer and in non-food-producing areas. In contrast, it did not have a corresponding carbon reduction effect in provinces with a low degree of land transfer and in food-producing areas. Therefore, the government should strengthen the construction of high-standard farmlands and differentiate the implementation of high-standard farmland construction policies according to local conditions and classifications to give full play to the emission reduction effect. In addition, the government should pay great attention to the role of agricultural chemicalization and socialized agricultural services in carbon reduction effects.
- Land consolidation /
- Agricultural carbon emissions /
- High-standard farmland construction policy /
- Differences-in-differences approach

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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

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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

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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	286.463	200.177	12.159	874.300
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	39.239	22.711	8.012	130.039
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	20.790	14.567	0.945	69.545
	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	1.396	0.697	0.300	4.240
	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	52.459	8.550	33.775	78.330
	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	42 556.380	23 928.040	6915.000	12 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	10.846	3.049	2.869	18.966
	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	65.417	12.965	32.815	95.847
	城镇化率 Urbanization rate (%)	Urb	城镇人口所占比例 Percentage of urban population	54.437	13.568	28.240	89.600
	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	1.266	0.545	0.588	3.761
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	0.397	0.133	0.153	0.875
中介变量 Intermediate variable	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	0.224	0.146	0.030	0.903

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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 Region	2007	2015	2017	地区 Region	2007	2015	2017
北京 Beijing	25.086	18.415	15.310	河南 Henan	707.960	874.300	856.261
天津 Tianjin	41.084	36.836	32.160	湖北 Hubei	401.744	444.147	422.021
河北 Hebei	682.234	600.696	539.937	湖南 Hunan	314.679	360.992	357.680
山西 Shanxi	141.124	168.726	162.226	广东 Guangdong	305.186	362.672	362.644
内蒙古 Inner Mongolia	195.216	328.671	331.298	广西 Guangxi	279.245	338.073	336.485
辽宁 Liaoning	239.287	287.380	269.705	海南 Hainan	71.696	95.989	87.329
吉林 Jilin	216.945	314.227	312.849	重庆 Chongqing	112.751	135.393	133.294
黑龙江 Heilongjiang	303.266	416.230	414.070	四川 Sichuan	327.277	358.917	349.920
上海 Shanghai	36.865	28.903	26.977	贵州 Guizhou	102.826	136.151	130.082
江苏 Jiangsu	455.379	460.457	445.116	云南 Yunnan	228.728	353.006	356.067
浙江 Zhejiang	259.705	265.898	255.737	陕西 Shaanxi	197.149	295.596	297.065
安徽 Anhui	410.426	467.532	443.776	甘肃 Gansu	150.295	251.655	222.010
福建 Fujian	216.671	225.017	214.949	青海 Qinghai	12.159	18.352	17.539
江西 Jiangxi	201.855	226.769	216.292	宁夏 Ningxia	46.838	60.115	60.293
山东 Shandong	836.884	759.961	722.101	新疆 Xinjiang	239.069	439.550	435.613

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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)
Dis		0.000 (0.000)
Env		0.026 (0.027)
Ind		0.003 (0.003)
Eco		0.169 (0.116)
Fin		0.019^*** (0.006)
Pla		−0.003 (0.004)
Urb		0.011 (0.009)
Sca		0.069 (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	已控制 Control 已控制 Control	已控制 Control 已控制 Control
观测值数 Number of observations	330	330
R²	0.4375	0.5664
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.

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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
变量 Variable		模型4 (替换被解释变量) Model 4 (substitution of explained variable)	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 term	2.894^** (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	330	330	240	330
R²	0.5524	0.9181	0.6698	0.5967
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.

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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值 P value
HFC×2007	0.060	0.043	0.168
HFC×2008	0.040	0.040	0.322
HFC×2009	0.038	0.025	0.145
HFC×2010	0.029	0.018	0.129
HFC×2012	−0.022	0.015	0.159
HFC×2013	−0.042	0.018	0.025
HFC×2014	−0.078	0.028	0.009
HFC×2015	−0.088	0.039	0.031
HFC×2016	−0.095	0.036	0.014
HFC×2017	−0.123	0.048	0.015
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.

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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)
ACII			0.645^** (0.282)
ASS				−0.341^* (0.194)
常数项 Constant term	1.054^** (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 observations	330	330	330	330
R²	0.5031	0.7943	0.5979	0.5851
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.

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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 term	3.085^***(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	已控制 Controlled	已控制 Controlled	已控制 Controlled	已控制 Controlled
观测值数 Number of observations	143	187	143	187
R²	0.7282	0.6643	0.6427	0.7098
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.

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