绿色防控技术采纳影响因素及收入效应研究

田路; 郑少锋; 陈如静

doi:10.12357/cjea.20220038

绿色防控技术采纳影响因素及收入效应研究基于792户菜农调查数据的实证分析

doi: 10.12357/cjea.20220038

西北农林科技大学经济管理学院　杨凌　712100

基金项目: 国家自然科学基金项目(7177031481)资助

详细信息

作者简介:
田路, 主要研究方向为农业经济管理。E-mail: tianlu216@163.com

通讯作者:
郑少锋, 主要研究方向为农业经济管理。E-mail: zsf831@163.com

中图分类号: F323.3
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- 被引次数: 0
出版历程
- 收稿日期: 2022-01-16
- 录用日期: 2022-03-11
- 网络出版日期: 2022-05-17
- 刊出日期: 2022-10-10

The influencing factors and income effects of green prevention-control technology adoption — An empirical analysis based on the survey data of 792 vegetable growers

School of Economics and Management, Northwest A&F University, Yangling 712100, China

Funds: This study was supported by the National Natural Science Foundation of China (7177031481).

More Information

Corresponding author: E-mail: zsf831@163.com

摘要

摘要: 本文以山东省寿光市蔬菜种植户为例, 对菜农采纳绿色防控技术的影响因素和收入效应进行定量分析, 以便为绿色防控技术在蔬菜种植行业的有效推广、促进菜农绿色生产和提质增收提供政策参考。基于山东寿光792户菜农的微观数据, 采用赫克曼矫正法模型从“采纳决策”和“采纳程度”两个方面探究了影响菜农绿色防控技术采纳的影响因素, 运用内生转换回归模型分析菜农绿色防控技术采纳对其收入的平均处理效应。研究发现: 1)菜农对绿色防控技术的采纳程度不足, 样本农户中只采纳1项和2项绿色防控技术的数量最多, 占总样本比重分别为36.87%和27.27%; 2)菜农绿色防控技术认知水平、接受质检和培训经历、会主动利用互联网搜集信息对菜农的绿色防控技术采纳行为显著正相关, 地块数量、信息设备数量对菜农的绿色防控技术采纳行为显著负相关; 3)人均收入超过样本平均水平的菜农更乐于接受绿色防控技术, 且该技术的采用可增加菜农年均收入的比重为7.2%。据此, 应发挥绿色防控技术的增收效应, 激发菜农采纳新技术的内生动力, 提出政府应加快健全绿色防控技术推广机制, 完善风险补偿机制、给予菜农技术政策补贴, 增强菜农的科学技术意识、积极推动农户适度规模经营等政策建议。
- 绿色防控技术 /
- 采纳强度 /
- 收入效应 /
- 赫克曼矫正法 /
- 内生转换模型
Abstract: To comply with the agricultural production trend of protecting the ecological environment, reducing the application of chemical pesticides, comprehensively developing green agriculture, and helping the rural areas to achieve long-term development, the Chinese government made efforts to promote the application of green prevention-control technology; however, the application level of this technology in China is not high and existing research on the adoption of green prevention-control technology as a method selection by farmers is insufficient. To promote the adoption of green prevention-control technologies by vegetable farmers, achieve green production and quality improvement and income increase, provide policy reference for the effective promotion of green prevention-control technologies in the vegetable planting industry, and enrich the promotion theory of green prevention-control technologies, this study used vegetable growers in Shouguang City, Shandong Province as an example to quantitatively analyze the influencing factors and income effects of vegetable farmers’ adoption of green prevention-control technologies. Based on the micro-data of 792 vegetable farmers, this study characterized the behavior of vegetable farmers in adopting green prevention-control technology according to two aspects, adoption decision and adoption degree, explored the influencing factors affecting the adoption of green prevention-control technology of vegetable farmers using the Heckman correction method model. And the average treatment effect of the adoption of green prevention-control technology of vegetable farmers on their income was analyzed by using an endogenous conversion regression model. The study found that the degree of adoption of green prevention-control technologies by vegetable farmers was insufficient. The numbers of vegetable farmers adopting one and two green prevention-control technologies were the largest, which were 292 households and 216 households, respectively, accounting for 36.87% and 27.27% of the total sample, respectively. The level of awareness of green prevention-control technology of vegetable farmers, the experience of getting quality testing and training, and the active use of the internet in collection of information were significantly positively correlated with the adoption of green prevention-control technologies by vegetable farmers. Factors such as the number of plots owned, the number of information devices significantly negatively correlated with the adoption of green prevention and control technologies among vegetable farmers. Vegetable farmers whose per capita income exceeded the average sample level were more willing to accept green prevention-control technology, and the use of this technology could increase the proportion of the average annual income of vegetable farmers by 7.2%. Therefore, a variety of factors, such as family, information, and government policies, affect the decision-making and adoption degree of green prevention-control technologies by vegetable farmers; moreover, the adoption of green prevention-control technologies has a positive impact on the income of vegetable farmers. Based on this, we should give full play to the increase in the income effect of green prevention-control technology, stimulate the endogenous motivation of vegetable farmers to adopt new technologies, and propose that the government should accelerate the improvement of the promotion mechanism of green prevention-control technology, improve the risk compensation mechanism, give vegetable farmers science and technology policy subsidies, enhance the scientific and technological awareness of vegetable farmers, and actively promote the moderate-scale operation of farmers.
- Green prevention-control technology /
- Adoption intensity /
- Income effects /
- Heckman correction method /
- Endogenous transformation model

HTML全文

图 1 采用不同数量绿色防控技术的农户占比分布图

Figure 1. Distribution of proportions of sample vegetable farmers adopting different numbers of green prevention-control technologies

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表 1 样本菜农采纳不同绿色防控技术的分布情况

Table 1. Distribution of different green prevention-control technologies adopted by sample vegetable famers

	农药防治 Pesticide control	物理防治 Physical control	生物防治 Biotic-control	生态调控 Ecological regulation
采纳户数 Number of adopted households	567	332	267	136
未采纳户数 Number of not adopted household	224	459	524	655
总户数 Total number of households	792	792	792	792

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表 2 菜农绿色防控技术采纳影响因素模型的变量定义、预期方向及描述性统计

Table 2. Variable definition, expected direction and descriptive statistics of influencing factors model of vegetable farmers’ green prevention-control technology adoption

变量名称 Variable name			变量含义 Variable meaning	预期方向 Expected direction	均值 Mean	标准差 Standard deviation
因变量 Dependent variable	是否使用绿色防控技术 Whether to use green prevention- control technology		1=是, 0=否 1=yes, 0=no		0.88	0.32
因变量 Dependent variable	采纳绿色防控技术个数 Number of green prevention-control technologies adopted		农户采纳该技术的实际个数 Actual number of farmers adopting this technology		1.65	1.01
自变量 Independent variable	个人因素 Personal element	性别 Gender	1=男性, 0=女性 1=male, 0=female	+	0.60	0.49
		年龄 Age	农户的年龄 Farmer’s age	−	51.41	8.83
		年龄平方 Age square	农户年龄的平方 Square of farmer’s age	−	2720.84	914.55
		教育 Education	农户的上学时长(年) Schooling years of farmers	+	7.79	2.96
	家庭因素 Family factors	种植人数 Number of planters	农户家庭主营蔬菜种植的人数 Number of farmers mainly engaged in vegetable cultivation	−	2.06	0.62
		蔬菜面积 Vegetable area	农户目前种植蔬菜的实际面积 Actual area of vegetables at present (hm²)	+	0.27	0.35
		地块数 Number of plots	农户种植的实际地块数 Actual number of plots planted by farmers	−	2.04	1.63
	信息因素 Information factors	互联网 Internet	1=是, 0=否 1=yes, 0=no	+	0.48	0.50
		信息设备 Information devices	电脑、智能手机的数量 Number of computers and smart phones	+	2.31	0.95
		您是否会利用信息设备主动搜集信息 Will you actively collect information by using information equipment?	1=是, 0=否 1=yes, 0=no	+	0.86	0.35
	政府因素 Government factors	种植技术 Planting technique	接受技术培训次数 Number of technical trainings received	+	3.25	1.01
		质量检测 Quality detection	接受质量检测的次数 Number of times of quality inspection	+	0.95	0.22
		安全培训 Safety training	接受安全培训次数 Number of safety trainings	+	0.36	0.48
		指导化肥 Guide fertilizer	接受指导化肥次数 Number of times of receiving fertilizer instruction	+	0.76	0.43
	识别变量 Identification variable	您觉得绿色防控技术有效吗 Do you think that green prevention and control technology is effective?	1=是, 0=否 1=yes, 0=no	+	0.80	0.40

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表 3 绿色防控技术采纳的收入效应模型变量定义、预期方向及描述性统计

Table 3. Variable definition, expected direction and descriptive statistics of revenue effect model of adoptation of green prevention-control technologies

变量名称 Variable name		变量含义 Variable meaning	预期方向 Expected direction	均值 Mean	标准差 Standard deviation
因变量 Dependent variable	农业收入 Farming income	每公顷净收益对数 Logarithm of average net income per hectare (¥)		13.18	0.79
自变量 Independent variable	是否使用绿色防控技术 Whether to use green prevention and control technology	1=是, 0=否 1=yes, 0=no	+	0.88	0.32
自变量 Independent variable	采纳绿色防控技术个数 Number of green prevention and control technologies adopted	农户采纳该技术的实际个数 Actual number of farmers adopting this technology	+	1.65	1.01

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表 4 菜农绿色防控技术采纳决策和采纳程度影响因素的估计结果及OLS回归和Logit回归对比

Table 4. Estimation of factors influencing the adoption decision and adoption degree of green prevention-control technology of vegetable farmers, and the comparison of OLS regression and Logit regression

变量 Variable	赫克曼矫正法 Heckman correction method				Ols回归 Ols regression		Logit回归 Logit regression
	采纳程度 Adoptation degree		采纳决策 Adoptation decision		采纳程度 Adoptation degree		采纳行为 Adoptation behavior
	系数 Coefficient	标准误 Standard error	系数 Coefficient	标准误 Standard error	系数 Coefficient	标准误 Standard error	系数 Coefficient	标准误 Standard error
性别 Gender	0.050	0.070	0.023	0.138	0.068	0.075	0.087	0.255
年龄 Age	0.002^*	0.033	0.071	0.053	0.057^*	0.032	0.122	0.095
年龄平方 Age square	0.000	0.000	−0.001	0.001	−0.001^*	0.000	−0.001	0.001
教育 Education	0.016^*	0.013	0.027	0.024	0.027^**	0.013	0.061	0.044
种植人数 Number of planters	−0.013	0.055	−0.124	0.098	−0.090	0.056	−0.237	0.176
蔬菜面积 Vegetable area	0.008	0.009	−0.022	0.014	−0.009	0.008	−0.039^*	0.024
地块数 Number of plots	−0.058^**	0.030	0.163^**	0.071	0.012	0.027	0.309^**	0.141
网络 Internet	0.125	0.087	0.301^**	0.140	0.314^***	0.075	0.571^**	0.267
信息设备 Information devices	−0.386^***	0.112	0.218	0.186	−0.161	0.112	0.413	0.341
搜集信息 Gather information	0.016	0.046	0.146	0.090	0.098^**	0.045	0.250	0.167
种植技术 Planting technique	−0.041	0.039	−0.111	0.073	−0.109^***	0.038	−0.228^*	0.136
质量检测 Quality detection	0.474^**	0.197	0.523^**	0.233	0.078	0.158	0.866^**	0.412
安全培训 Safety training	0.126	0.131	0.813^***	0.175	0.328^***	0.077	1.591^***	0.375
指导化肥 Guide fertilizer	0.121	0.083	−0.059	0.147	0.074	0.087	−0.119	0.269
有效性认知 Effective cognition			0.262^*	0.152			0.472^*	0.279
常数项 Constant term	3.022^***	1.033	−1.359	1.529	0.487	0.895	−2.096	2.748
逆米尔斯比率 Mills lambda	−1.414^**
*、、* 分别表示变量在P<0.01、P<0.05和P<0.1置信水平显著。*, and * respectively indicate that the variables are significant at P<0.01, P<0.05 and P<0.1 confidence levels.

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表 5 绿色防控技术采纳行为对采纳和未采纳农户农业收入的影响对比

Table 5. Comparison of the impact of green prevention-control technology adoption behvior on the agricultural income of farmers adopting and unaccepting technology

变量 Variable	绿色防控技术采纳模型 Green prevention-control technology adoption model		农业收入 Farming income
			采纳技术 Adopting technology		未采纳技术 Unaccepting technology
	系数 Coefficient	标准差 Standard deviation	系数 Coefficient	标准差 Standard deviation	系数 Coefficient	标准差 Standard deviation
性别 Gender	−0.227	0.167	−0.790	0.318	−0.060	0.825
年龄 Age	0.005	0.009	0.770	0.146	0.300	0.361
年龄平方 Age square	−0.051^**	0.001	2.060^**	0.001	1.830^*	0.004
教育 Education	−0.036	0.027	3.610^***	0.059	8.400^***	0.145
种植人数 Number of planters	0.186	0.099	−1.900^*	0.266	3.320^***	0.622
蔬菜面积 Vegetable area	0.013	0.016	−1.800^*	0.039	2.100^**	0.094
地块数 Number of plots	0.421	0.141	−1.140	0.145	0.04	0.295
网络 Internet	0.034	0.139	0.370^***	0.386	1.670^*	0.822
信息设备 Information devices	−0.317	0.195	−0.516^**	0.481	0.526	1.254
搜集信息 Gather information	0.484^***	0.087	−2.050^**	0.254	−0.250	0.488
种植技术 Planting technique	0.028	0.074	0.080^**	0.213	0.544^***	0.417
质量检测 Quality detection	0.072	0.245	−0.820	0.562	−0.430	1.849
安全培训 Safety training	−0.070	0.154	1.480	0.682	6.040^***	0.828
指导化肥 Guide fertilizer	0.075	0.148	−2.260^**	0.359	0.750	0.977
有效性认知 Effective cognition	0.116	0.149	—	—	—	—
常数项 Constant term	−0.420	1.594	1.294	0.430	2.062	1.934
rho1	—	—	−0.286^**	0.176	—	—
rho2	—	—	—	—	0.787^***	0.435
Log likelihood	−256.583
*、、* 分别表示变量在P<0.01、P<0.05和P<0.1置信水平显著。*, and * respectively indicate that the variables are significant at P<0.01, P<0.05 and P<0.1 confidence levels.

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表 6 菜农采纳绿色防控技术对农业收入影响的平均处理效应

Table 6. Average treatment effect of the adoption of green prevention-control technology on agricultural income of vegetable farmers

	结果均值 Result mean		平均处理效应(ATT) Average treatment effect	t值 t value	变化率 Rate of change
	采纳 Adopting technology	未采纳 Unaccepting technology	平均处理效应(ATT) Average treatment effect	t值 t value	变化率 Rate of change
农业收入 Farming income	13.479	12.515	0.964	54.247^***	0.072

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