数字经济发展对农业气候韧性的影响机制研究 基于调节效应和空间溢出效应分析

陈卫洪; 于晴

doi:10.12357/cjea.20240145

数字经济发展对农业气候韧性的影响机制研究基于调节效应和空间溢出效应分析

陈卫洪^{1, 2,},
于晴^1, ,

1.
贵州大学经济学院　贵阳　550000
2.
贵州省丹穴山朴门永续发展有限公司　长顺　550700

基金项目: 国家社会科学基金项目(BGX230346)、教育部新农科研究与改革实践项目(2020347)、贵州省科技平台及人才团队计划项目(黔科合平台人才[2017]5647)和贵州省教育厅人文社会科学研究项目(2024RW321)资助

详细信息

作者简介:
陈卫洪, 研究方向为农林经济理论与政策、气候变化与低碳经济和资源环境与区域发展、数字经济、农业大数据。E-mail: 15136482431@163.com

通讯作者:
于晴, 研究方向为农村与区域发展、气候变化与低碳经济。E-mail: 1220638927@qq.com

中图分类号: F323; X43
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出版历程
- 收稿日期: 2024-03-21
- 录用日期: 2024-05-07
- 网络出版日期: 2024-05-29
- 刊出日期: 2024-06-09

Study on the influence mechanism of digital economy development on agricultural climate resilienceBased on the analysis of regulatory effects and spatial spillover effects

CHEN Weihong^{1, 2,},
YU Qing^1, ,

1.
School of Economics, Guizhou University, Guiyang 550000, China
2.
Guizhou Danxueshan Permaculture Development Co., Ltd., Changshun 550700, China

Funds: This study was supported by the National Social Science Foundation of China (BGX230346), the New Agricultural Research and Reform Practice Project of Ministry of Education of China (2020347), Guizhou Science and Technology Platform and Talent Team Project (Guizhou Science Platform Talents [2017] 5647), and the Humanities and Social Science Project of Department of Education of Guizhou Province (2024RW321).

More Information

Corresponding author:
YU Qing: E-mail: 1220638927@qq.com

摘要

摘要:
数字经济已成为重塑经济结构、重组生产资源、协调人与自然关系的核心要素。数字经济具有创新性强、覆盖面广、复制容易等优势, 能够迅速渗透到农业生产、经营、产业发展等各个领域。数字经济的快速发展为农业部门应对气候冲击提供了新的思路。本文基于2011—2020年我国30个省(自治区、直辖市, 不包括香港、澳门、台湾和西藏)的面板数据, 使用熵值法对数字经济发展水平和农业气候韧性进行测算, 分析了数字经济对农业气候韧性的影响, 并考察了财政支农和农业保险对该作用机制的调节效应。此外, 还通过构建空间计量模型探析了数字经济发展对农业气候韧性的空间溢出效应。结果表明: 我国农业气候韧性总体呈上升趋势, 但数值偏低, 仍存在较大的上升空间; 东部地区的农业气候韧性指数高于中部、西部以及东北部地区; 数字经济对农业气候韧性具有显著的促进作用, 且存在区域差异, 其中数字经济对东部地区农业气候韧性的促进作用最佳, 对中西部地区影响不显著, 对东北地区农业气候韧性具有抑制作用; 财政支农和农业保险强化了数字经济对农业气候韧性的影响; 数字经济对农业气候韧性的影响具有显著正向的空间溢出效应, 通过对动态空间杜宾模型进行分解发现短期效应要优于长期效应。本文为减缓和适应气候变化, 提升农业气候韧性提供了理论基础与政策依据。
- 数字经济 /
- 农业气候韧性 /
- 调节效应 /
- 空间溢出效应
Abstract:
The digital economy is a fundamental element in reshaping economic structures, optimizing resource allocation, and harmonizing the relationship between humans and nature. The digital economy has advantages such as strong innovation, wide coverage, and easy replication, and can quickly penetrate into various fields such as agricultural production, management, and industrial development. The rapid advancement of the digital economy has introduced new strategies for the agricultural sector to cope with climate shocks. This study utilized panel data from 30 provinces (autonomous regions and municipalities, not including Hong Kong, Macao, Taiwan and Xizang of China) in China from 2011 to 2020. Employing the entropy method, we measured the development levels of the digital economy and agricultural climate resilience. We then analyzed the impact of the digital economy on agricultural climate resilience and examine the regulatory effects of financial support for agriculture and agricultural insurance. Additionally, a spatial econometric model was constructed to explore the spatial spillover effects of digital economic development on agricultural climate resilience. The findings revealed that the overall agricultural climate resilience in China was increasing, albeit from a relatively low base, indicating significant room for improvement. The agricultural climate resilience index was highest in the eastern region, followed by the central, western, and northeastern regions. The digital economy significantly enhanced agricultural climate resilience, with notable regional differences. Specifically, the digital economy showed significant positive impact in the eastern region, no significant effect in the central and western regions, and significant negative impact in the northeastern region. Furthermore, financial support for agriculture and agricultural insurance amplified the positive effects of the digital economy on agricultural climate resilience. The influence of the digital economy on agricultural climate resilience exhibited a significant positive spatial spillover effect. We found that short-term effects surpass long-term effects via decomposing the dynamic spatial Durbin model. This study provides a theoretical and policy foundation for mitigating and adapting to climate change and enhancing agricultural climate resilience.
- Digital economy /
- Agricultural climate resilience /
- Regulation effect /
- Space spillover effect

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图 1 2011—2020年中国及各地区农业气候韧性均值变化趋势

Figure 1. Change trend of agricultural climate resilience of China and different regions from 2011 to 2020

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图 2 我国30个省份(自治区、直辖市, 不包括香港、澳门、台湾和西藏)农业气候韧性重心迁移轨迹

Figure 2. Migration track of agricultural climate resilience center of gravity in 30 provinces (autonomous regions and municipalities, not including Hong Kong, Macao, Taiwan and Xizang of China) of China

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表 1 农业气候韧性评价指标体系

Table 1 Evaluation index system of agricultural climate resilience

一级指标 First-level index	二级指标 Second-level index	三级指标 Third-level index	指标说明 Index interpretation	指标属性 Index attribute
抵抗力 Resistance	内在稳定性 Intrinsic stability	农村人均可支配收入 Per capita disposable income in rural area	各省农村人均可支配收入 Rural per capita disposable income in each province	正向 Positive
		农村信息化水平 Rural informatization level	行政村宽带网络覆盖率 Broadband network coverage rate in administrative villages	正向 Positive
		森林覆盖率 Forest coverage rate	各省森林覆盖率 Forest coverage rate in each province	正向 Positive
		农业气象观测站点个数 Number of agrometeorological observation stations	各省农业气象观测业务站点个数 Number of agrometeorological observation stations in each province	正向 Positive
		有效灌溉率 Effective irrigation rate	有效灌溉面积/耕地面积 Effective irrigated area / cultivated land area	正向 Positive
		农业成灾率 Agricultural disaster rate	成灾面积/受灾面积 Disaster-affected area / affected area	负向 Negative
	产供鲁棒性 Robustness of production and supply	第一产业占比 Proportion of primary industry	第一产业增加值占地区生产总值比重 Contribution of added value of the primary industry accounts to the regional GDP	正向 Positive
		人均农林牧渔业增加值 Per capita added value of agriculture, forestry, animal husbandry and fishery	农林牧渔业增加值/农林牧渔业从业人员数 Added value of agriculture, forestry, animal husbandry and fishery / number of employees of agriculture, forestry, animal husbandry and fishery	正向 Positive
		农产品加工比值 Agricultural product processing ratio	农产品加工营业收入/农林牧渔业总产值 Processing and business income of agricultural products / total output value of agriculture, forestry, animal husbandry and fishery	正向 Positive
适应力 Adaptability	可持续性 Sustainability	农业人力资本存量 Agricultural human capital stock	各省人力资本存量 Provincial human capital stock	正向 Positive
		农药使用强度 Pesticide intensity	农药使用量/耕地面积 Pesticide usage / cultivated land area	负向 Negative
		化肥使用强度 Strength of fertilizer use	化肥施用量/耕地面积 Fertilizer application amount / cultivated land area	负向 Negative
		农村人均用电量 Per capita electricity consumption in rural area	农村居民用电量/农村人口 Electricity consumption of rural residents / rural population	正向 Positive
	可恢复性 Restorability	复种指数 Multiple-crop index	农作物播种面积/耕地面积 Crop sown area / cultivated land area	正向 Positive
	可恢复性 Restorability	水土协调度 Soil and water coordination	水土流失治理面积/辖区面积 Soil erosion control area / jurisdiction area	正向 Positive
重构力 Reconstructive power	多样协作性 Diversified collaboration	农业生产合作化程度 Degree of cooperation in agricultural production	农村每万人拥有农民专业合作社数量 Number of specialized farmer cooperatives for every 10 000 rural people	正向 Positive
		单位播种面积农林牧渔服务业产值 Output value of agriculture, forestry, animal husbandry and fishery service industry per unit sown area	农林牧渔服务业产值/农作物播种面积 Output value of agriculture, forestry, animal husbandry and fishery service industry / sown area of crops	正向 Positive
		单位面积农机总动力 Agricultural machinery total power per unit area	农业机械总动力/耕地面积 Total power of agricultural machinery / cultivated land area	正向 Positive
	科技进步性 Technological progress	农业固定资产投资 Investment in agricultural fixed assets	农村住户固定资产投向农业 Fixed assets of rural households invested in agriculture	正向 Positive
	科技进步性 Technological progress	人均农业科研支出 Per capita expenditure on agricultural scientific research	农业科研支出/农村人口数 Agricultural scientific research expenditure / rural population number	正向 Positive

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表 2 数字经济发展水平评价指标体系

Table 2 Evaluation index system of the developmental level of digital economy

一级指标 First-level index	二级指标 Second-level index	指标含义 Index interpretation	指标属性 Index attribute
数字经济发展水平 Developmental level of digital economy	互联网普及率 Internet penetration rate	每百人互联网用户数 Number of internet users per 100 people	正向 Positive
	互联网相关从业人数 Number of internet-related employees	每万人计算机服务和软件从业人员数 Number of computer services and software employees per 10 000 people	正向 Positive
	互联网相关产出 Internet-related output	人均电信业务总量 Total telecom business per capita	正向 Positive
	移动互联网用户数 Number of mobile internet users	每百人移动电话用户数 Number of mobile phones users per 100 people	正向 Positive
	数字金融普惠发展 Inclusive development of digital finance	中国数字普惠金融指数 The China Digital Financial Inclusion Index	正向 Positive

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表 3 数字经济发展对农业气候韧性影响的相关变量描述性统计结果(n=300)

Table 3 Descriptive statistical results of variables related to the impact of digital economy development on agricultural climate resilience (n=300)

变量类型 Variable type	变量名称 Variable name	平均值 Average value	标准差 Standard deviation	最小值 Minimum value	最大值 Maximum value
被解释变量 Explained variable	农业气候韧性 Agricultural climate resilience (ACR)	0.177	0.079	0.111	0.575
核心解释变量 Core explanatory variable	数字经济发展水平 Development level of digital economy (Dig)	0.373	0.174	0.077	0.982
调节变量 Regulated variable	财政支农 Financial support for agriculture (AF)	0.547	0.270	0.092	1.339
调节变量 Regulated variable	农业保险密度 Agricultural insurance density (AID)	0.011	0.012	0.0003	0.092
控制变量 Controlled variable	城镇化率 Urbanization rate (UR)	0.590	0.122	0.35	0.896
	土地流转率 Land transfer rate (TF)	0.318	0.164	0.034	0.911
	农业劳动生产率 Agricultural labor productivity (ALP)	5.116	2.521	1.015	16.812
	公路通达度 Road accessibility (Road)	0.945	0.505	0.089	2.205

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表 4 2011—2020年我国30个省(自治区、直辖市, 不包括香港、澳门、台湾和西藏)农业气候韧性分布格局中心及标准差椭圆参数

Table 4 Center and standard deviation elliptical parameters of the distribution pattern of agricultural climate resilience in 30 provinces (autonomous regions and municipalities, not including Hong Kong, Macao, Taiwan and Xizang of China) of China from 2011 to 2020

年份 Year	X轴标准差 Standard deviation of X axis (km)	Y轴标准差 Standard deviation of Y axis (km)	方向角 Direction angle (°)	重心移动距离 Center moving distance (km)
2011	1008.452	1129.774	39.886	—
2014	986.031	1129.845	33.359	25.148
2017	973.294	1121.383	28.576	17.888
2020	956.261	1123.759	24.650	20.616

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表 5 数字经济对农业气候韧性的基准回归结果

Table 5 Benchmark regression results of digital economy on agricultural climate resilience

变量 Variable	ACR
变量 Variable	模型1 Model 1	模型2 Model 2	模型3 Model 3	模型4 Model 4	模型5 Model 5
Dig	0.224^*** (0.023)	0.047^** (0.024)	0.137^*** (0.019)	0.625^*** (0.0616)	0.351^*** (0.066)
UR		0.421^*** (0.036)	−0.345^*** (0.067)	0.162^*** (0.041)	−0.387^*** (0.087)
TF		0.087^*** (0.026)	0.003 (0.021)	0.096^*** (0.024)	−0.026 (0.028)
ALP		−0.004^*** (0.002)	0.004^*** (0.001)	−0.003^** (0.002)	0.005^*** (0.001)
Road		0.010 (0.007)	0.024 (0.018)	0.007 (0.006)	0.024 (0.017)
Constant	0.094^*** (0.010)	−0.103^*** (0.015)	0.544^*** (0.047)	−0.024 (0.016)	0.505^*** (0.085)
Year FE	No	No	No	Yes	Yes
Province FE	No	No	Yes	No	Yes
N	300	300	300	300	300
R²	0.241	0.637	0.952	0.737	0.957
*: P<0.01; : P<0.05; *: P<0.1; 括号内为稳健的标准误。ACR和Dig分别代表农业气候韧性和数字经济发展水平; UR、TF、ALP和Road分别代表城镇化率、土地流转率、农业劳动生产率和公路通达度; Constant、Year FE、Province FE、N和R²分别代表常量、时间固定效应、省份固定效应、样本数和拟合优度。Data in parentheses is the robust standard error. ACR and Dig represent resilience of agricultural climate and level of digital economy development, respectively; UR, TF, ALP, and Road represent urbanization rate, land transfer rate, agricultural labor productivity, and road accessibility, respectively; Constant, Year FE, Province FE, N, and R² represent constant, time fixed effect, province fixed effect, sample size, and goodness of fit, respectively.

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表 6 数字经济发展对农业气候韧性影响的稳健性检验结果

Table 6 Robustness test results of the impact of digital economy development on agricultural climate resilience

项目 Project	ACR
项目 Project	模型1 Model 1	模型2 Model 2
Dig		0.348^*** (−0.083)
LEDE	0.142^*** (−0.022)
UR	−0.336^*** (−0.086)	−0.489^** (−0.194)
TF	−0.057^** (−0.026)	−0.074^* (−0.042)
ALP	0.004^*** (−0.001)	0.002 (−0.002)
Road	0.025 (−0.017)	0.037 (−0.028)
Constant	0.569^*** (−0.074)	0.596^*** (−0.181)
Year FE	Yes	Yes
Province FE	Yes	Yes
R²	0.959	0.963
*: P<0.01; : P<0.05; *: P<0.1。括号内为稳健的标准误。ACR、Dig和LEDE分别表示农业气候韧性、数字经济发展水平和替换衡量指标重新测算的数字经济发展水平; UR、TF、ALP和Road分别表示城镇化率、土地流转率、农业劳动生产率和公路通达度; Constant、Year FE、Province FE和R²分别代表常量、时间固定效应、省份固定效应和拟合优度。模型1指替换解释变量, 模型2指缩短时间跨度。Data in parentheses is the robust standard error. ACR, Dig, and LEDE represent resilience of agricultural climate, level of digital economy development, and level of digital economy development recalculated by replacing measurement indicators, respectively. UR, TF, ALP, and Road represent urbanization rate, land transfer rate, agricultural labor productivity, and road accessibility, respectively. Constant, Year FE, Province FE, and R² represent constant, time fixed effect, province fixed effect, and goodness of fit, respectively. Model 1 refers to replace explanatory variables, and Model 2 refers to shorten the time span.

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表 7 数字经济发展对农业气候韧性影响的区域异质性回归结果

Table 7 Regional heterogeneity regression results of the impact of digital economy development on agricultural climate resilience

变量 Variable	ACR
变量 Variable	东部 East	中部 Middle	西部 West	东北部 Northeast
Dig	0.577^*** (−0.206)	0.072 (−0.097)	−0.015 (−0.078)	−0.641^** (−0.221)
Constant	0.126 (−0.277)	0.214^*** (−0.047)	0.280^*** (−0.060)	−0.253 (−0.381)
Controls	Yes	Yes	Yes	Yes
Year FE	Yes	Yes	Yes	Yes
Province FE	Yes	Yes	Yes	Yes
N	100	60	120	30
R²	0.952	0.987	0.881	0.876
*: P<0.01; : P<0.05。括号内为稳健的标准误。ACR表示农业气候韧性; Dig表示数字经济发展水平; Controls表示上文提到的一系列控制变量; Constant、Year FE、Province FE、N和R²分别表示常量、时间固定效应、省份固定效应、样本数和拟合优度。Data in parentheses is the robust standard error. ACR represents agricultural cliamte resilience. Dig represents digital economy development level. Controls represent a series of control variables mentioned earlier. Constant, Year FE, Province FE, N, and R² represent constant, time fixed effect, province fixed effect, sample size, and goodness of fit, respectively.

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表 8 财政支农和农业保险的调节效应分析结果

Table 8 Analysis results of the regulation effect of financial support for agriculture and agricultural insurance

变量 Variable	ACR
变量 Variable	模型1 Model 1	模型2 Model 2
Dig	0.322^*** (4.72)	0.175^** (2.00)
AF	−0.082^*** (−2.66)
Dig×AF	0.078^** (2.05)
AID		−0.168 (−0.84)
Dig×AID		0.549^** (2.19)
Constant	0.483^*** (0.086)	0.389^*** (−0.090)
Controls	Yes	Yes
Year FE	Yes	Yes
Province FE	Yes	Yes
N	300	300
R²	0.957	0.958
*: P<0.01; : P<0.05。括号内为稳健的标准误。ACR、Dig、AF、AID分别表示农业气候韧性、数字经济发展水平、财政支农和农业保险密度; Controls表示上文提到的一系列控制变量; Constant、Year FE、Province FE、N和R²分别表示常量、时间固定效应、省份固定效应、样本数和拟合优度。Data in parentheses is the robust standard error. ACR, Dig, AF, and AID represent agricultural climate resilience, digital economy development level, financial support for agriculture, and agricultural insurance density, respectively. Controls represent a series of control variables mentioned earlier. Constant, Year FE, Province FE, N, and R² represent constant, time fixed effect, province fixed effect, sample size, and goodness of fit, respectively.

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表 9 农业气候韧性和数字经济的全局空间自相关检验结果

Table 9 Results of the global spatial autocorrelation test of agricultural climate resilience and digital economy development level

年份 Year	农业气候韧性 Agricultural climate resilience			数字经济发展水平 Digital economy development level
年份 Year	Moran’s I	Z值 Z value	P值 P value	Moran’s I	Z值 Z value	P值 P value
2011	0.112	4.492	0.000	0.221	5.439	0.000
2012	0.129	4.693	0.000	0.222	5.500	0.000
2013	0.146	5.009	0.000	0.221	5.455	0.000
2014	0.165	5.102	0.000	0.207	5.279	0.000
2015	0.186	5.372	0.000	0.194	5.015	0.000
2016	0.182	5.362	0.000	0.202	5.249	0.000
2017	0.187	5.330	0.000	0.187	4.876	0.000
2018	0.191	5.316	0.000	0.175	4.534	0.000
2019	0.195	5.114	0.000	0.172	4.475	0.000
2020	0.182	5.076	0.000	0.163	4.314	0.000

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表 10 数字经济发展对农业气候韧性效应的空间计量模型检验结果

Table 10 Spatial econometric model test results of the impact of digital economy development on agricultural climate resilience

检验类型 Inspection type	检验方法 Method of calibration	统计量值 Statistical value	P值 P value
LM检验 LM checkout	LM-error检验 LM-error test	15.565	0.000
	稳健的LM-error检验 Robust LM-error test	54.449	0.000
	LM-lag检验 LM-lag test	0.010	0.918
	稳健的LM-lag检验 Robust LM-lag test	38.894	0.000
Wald检验 Wald checkout	SDM退化为SEM SDM degenerates into SEM	38.060	0.000
Wald检验 Wald checkout	SDM退化为SAR SDM degenerates into SAR	34.290	0.000
Hausman检验 Hausman-Test	固定效应和随机效应检验 Fixed and random effects tests	20.460	0.040
LR检验 LR checkout	SDM模型退化为SEM模型 SDM model degenerates into SEM model	38.160	0.000
LR检验 LR checkout	SDM模型退化为SAR模型 SDM model degenerates into SAR model	30.350	0.000

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表 11 数字经济发展对农业气候韧性效应的动态空间杜宾回归结果

Table 11 Dynamic spatial Durbin regression results of the impact of digital economy development on agricultural climate resilience

变量 Variable	Main	Wx
Dig	0.338^** (2.370)	1.296^*** (2.640)
L.ACR	−3.688^*** (−3.520)
UR	−0.365^* (−1.801)	−0.926 (−0.962)
TF	0.051 (1.393)	0.665^*** (3.542)
ALP	0.005^** (2.131)	−0.012 (1.220)
Road	0.032^* (1.940)	−0.012 (−0.141)
Spatial rho	0.437^** (2.441)
Variance sigma2_e	0.0001^*** (3.851)
N	300
R²	0.458
*: P<0.01; : P<0.05; *: P<0.1。括号内为t值。Dig、L.ACR、UR、TF、ALP、Road分别代表数字经济发展水平、农业气候韧性滞后一期、城镇化率、土地流转率、农业劳动生产率和公路通达度, Main和Wx分别代表变量对本地区的影响系数和变量对其他地区的空间溢出系数, Spatial rho和Variance sigma2_e分别代表空间效应特异误差和个体效应特异误差, N和R²分别代表样本量和拟合优度。Data in parentheses is t value. Dig, L.ACR, UR, TF, ALP, and Road represent digital economic development level, lag of one period in agricultural climate resilience, urbanization rate, land transfer rate, agricultural labor productivity, and road accessibility, respectively. Main and Wx represent coefficient of influence of variables on the local region and the spatial spillover coefficient of variables on other regions, respectively. Spatial rho and Variance sigma2_e represent spatial effect specific error and individual effect specific error, respectively. N and R² represent sample size and goodness of fit, respectively.

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表 12 数字经济对农业气候韧性效应的空间计量结果分解

Table 12 Decomposition of the spatial measurement results of effect of digital economy on agricultural climate resilience

变量 Variable	短期效应 Short-term effect			长期效应 Long-term effect
变量 Variable	直接效应 Direct effect	间接效应 Indirect effect	总效应 Total effect	直接效应 Direct effect	间接效应 Indirect effect	总效应 Total effect
Dig	0.302^** (2.27)	0.860^** (2.20)	1.162^*** (2.89)	0.473 (0.12)	−0.153 (−0.04)	0.319^*** (3.00)
UR	−0.317 (−1.58)	−0.563 (−0.87)	−0.880 (−1.52)	−1.450 (−0.05)	1.198 (0.04)	−0.252 (−1.49)
TF	0.032 (0.90)	0.473^*** (3.41)	0.506^*** (3.83)	−0.113 (−0.02)	0.252 (0.04)	0.139^*** (4.00)
ALP	0.005^** (2.07)	0.008 (1.03)	0.012^* (1.68)	0.013 (0.05)	−0.010 (−0.04)	0.003^* (1.74)
Road	0.033^* (1.92)	−0.022 (−0.36)	0.012 (0.22)	0.092 (0.05)	−0.088 (−0.05)	0.003 (0.24)
*: P<0.01; : P<0.05; *: P<0.1。括号内为t值。Dig、UR、TF、ALP和Road分别代表数字经济发展水平、城镇化率、土地流转率、农业劳动生产率和公路通达度。Data in parentheses is t value. Dig, UR, TF, ALP, and Road represent digital economic development level, urbanization rate, land transfer rate, agricultural labor productivity, and road accessibility, respectively.

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