外来职业农民和本地农户种植多样性差异及影响因素研究

doi:10.18402/resci.2018.09.06

Abstract

Abstract:

Crop diversity is an effective strategy for traditional small-peasant to cope with the impact of agricultural risks. The transition of agriculture driven by migrant professional farmers may be different from local peasant households’crop diversity. The purpose of this study aims to investigate the difference of crop diversity between migrant professional farmers and local peasant households and its influencing factors at farm household level. Based on survey data from 393 farmers’crop diversity in Nanjing City, Jiangsu Province in 2015, we established a Poisson regression model. Different from the previous studies, the current investigation was carried out at farmer level, the farmer is not only the household head but also the family member in charge of agricultural production. Furthermore, the crop diversity was valued more directly by crop kinds instead of diversity index. The result shows that several factors affected farm households’ crop diversity. First of all, compared with the local peasant households, the crop diversity of migrant professional farmers is 17% less than that of local peasant households. Moreover, crop acreage has a significant effect on crop diversity, crop diversity decreases approximately 2.7% with an increase of 1 hm² of crop acreage. Besides, the age of farmers who are in charge of agricultural production, the agriculture land plot quantities of farmers who own, and the distance from peasants residence to the main city zone also have significant effects on crop diversity. Holding all other variables constant, the expected number of crop diversity increases by about 0.9% with an increase of the age of farmers, the expected number of crop diversity increases approximately 4.6% with an increase of 1 plot of agriculture land; the expected number of crop diversity increases approximately 0.8% with an increase of 1 km from peasants residence to the main city zone.

Key words: land economics, migrant professional farmers, Poisson regression model, crop diversity

Menglu YAN, Taiyang ZHONG. The difference of crop diversity between migrant professional farmers and local peasant households and its influencing factors[J].Resources Science, 2018, 40(9): 1752-1761.

Figures/Tables 5

Table 1

Table 2

Variable definitions、selected basis and expected signs for explanatory variables used in the models"

变量	表征指标	变量描述	变量选取依据参考	预期
因变量	y	农户种植种类数/种
解释变量	migrant	农户类型,外来职业农民=1,本地农户=0	邹大燕等^[28],顾霖霞^[29]和谢蓉等^[30]在研究中表明外来农户和本地农户不同的生产经营目的和方式导致其种植类型和种植结构存在差异。因此,本文选取农户类型这一变量	–
	age	农业生产决策者的年龄/岁	Benin等^[16]和Barbara等^[17]研究表明农户年龄、性别、文化程度对种植多样性存在不同程度的影响,一般年长和文化程度较低的女性农户由于劳动能力和农业技术能力的限制,其种植多样性会较低,但不尽然。考虑到农业生产决策者在作物选择上的重要决策作用,因此,本文选取农户农业决策者的年龄、性别和受教育程度这三种变量	+/–
	gender	农业生产决策者的性别,男=1,女=0		+
	edu	农业生产决策者的受教育程度,1=小学以下,2=小学,3=初中,4=高中		+/–
	number	负责农业生产活动的家庭成员的数量/个	钟太洋等^[11]研究表明负责农业生产活动的家庭成员是否参与非农就业以及参与数量是影响农户种植多样性的重要因素之一,因此,本文选取负责农业生产活动的家庭成员的数量这一变量	+
	acreage	种植面积/hm²	钟太洋等^[11]采用种植面积表征经营规模,研究表明,农户种植多样性随着种植面积的增加而增加;而李更生^[14]研究认为经营规模越大,农户种植决策行为越趋于市场化。因此,本文选取种植面积这一变量	+/–
	distance	农户住地到主城区距离/km	金兰等^[15]研究发现距离市场越近,商业化发展程度越高,庭院种植多样性越低;因此,本文选取农户住地到主城区的距离这一变量	+
	piece	农户地块总数/块	王兴稳等^[39]在土地市场的研究中分别选取农户地块总数,平均每户块数和出租块数表征土地细碎化程度,但较少有文献考虑该变量对农户种植多样性的影响。结合本研究问卷数据的实际情况,本文选取农户地块总数这一变量来表征土地细碎化程度	+

Table 2

Table 3

Table 4

Table 5

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调查日期 /月-日	城区	街道	居委会	本地农户样本 /份	外来职业农民样本 /份
11-28	建邺区	江心洲街道	白鹭村委会	33	7
11-29	江宁区	秣陵街道	西旺社区居委会	40	24
12-05	秦淮区	红花街道	广洋村村委会	18	5
	江宁区	淳化街道	田园社区居委会	16	2
12-06	六合区	竹镇镇	大泉村委会	28	1
12-12	高淳区	淳溪镇	双进村委会	19	0
	高淳区	东坝镇	东坝村委会	32	0
	雨花台区	板桥街道	孙家村村委会	29	9
12-13	栖霞区	八卦洲街道	新闸村村委会	30	14
	六合区	龙池街道	路呙村委会	25	9
	江宁区	横溪街道	新杨社区居委会	24	2
12-19	浦口区	星甸镇	龙山社区居委会	38	0
12-19	浦口区	桥林街道	福音社区居委会	30	0
12-26	溧水区	东屏镇	金湖村委会	31	1
	溧水区	晶桥镇	新桥村委会	29	0
总计				422	74

变量名/单位	样本数	最小值	最大值	平均值	标准差
y/种	393	1.00	8.00	1.27	1.24
migrant/（外来职业农民=1,本地农户=0）	375	0	1.00	0.20	0.40
age/岁	240	30.00	84.00	57.77	10.90
gender/（男=1,女=0）	240	0	1.00	0.65	0.48
edu/（1=小学以下,2=小学,3=初中,4=高中）	240	1.00	4.00	1.99	0.84
number/个	339	1.00	5.00	1.78	0.72
acreage/hm²	326	0.01	133.33	1.43	9.28
piece/块	289	1.00	80.00	5.15	6.27
distance/km	361	8.52	79.62	31.37	19.64

变量名	模型1	模型2	模型3
migrant	-0.426***	-0.195*	-0.186*
age		0.008*	0.009**
gender		0.050
edu2		-0.044
edu3		0.027
edu4		-0.079
number	0.481***	0.023	0.027
acreage	-0.028**	-0.027***	-0.028***
piece	0.050***	0.044***	0.045***
distance	0.006**	0.008***	0.008***
常数项	-0.912	-0.448	-0.480
检验统计量
N	330	175	175
Wald chi2（）	93.510	133.240	110.080
Prob > chi2	0.000	0.000	0.000
Log pseudo likelihood	-412.335	-246.240	-246.479
Pseudo R²	0.169	0.084	0.083
AIC	836.669	514.480	506.959
BIC	859.464	549.293	529.112

变量	模型1	模型3
migrant	0.653***	0.830*
age		1.009**
number	1.618***	1.027
acreage	0.973**	0.972***
piece	1.051***	1.046***
distance	1.006***	1.008***
常数项	0.402	0.619

The difference of crop diversity between migrant professional farmers and local peasant households and its influencing factors

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