农地承包经营权稳定性对农户秸秆还田行为的影响

doi:10.18402/resci.2019.11.02

摘要/Abstract

摘要：

十八届三中全会提出中国农村土地由“二权分离”向“三权分离”转变,以促进土地流转和农业市场化,但也可能导致农户对承包经营权稳定性的整体预期下降,进而影响农民采取如秸秆还田等长期性土地投资的积极性。本文基于2016年河南省农户秸秆处置行为的问卷调研及565个地块样本数据,构建了农户秸秆处置行为三阶段分析框架,并运用二元离散Probit模型分析和识别了农地承包经营权稳定性对农户秸秆还田行为的影响。研究结果表明：由于地权稳定性的差异,农户在拥有承包权的地块上具有更强的秸秆还田意愿。具体来说,样本农户在无承包权的地块上秸秆还田的概率比拥有承包权的地块平均低7.7个百分点。本文根据研究结论提出政策建议：政府应采取额外措施提高耕作者在租赁、托管等无承包权地块上的还田意愿,避免因为土地流转市场规模的扩大和农民采取保护性耕作意愿的降低,导致农村土地和环境问题恶化的潜在风险。

关键词: 承包经营权稳定性, 秸秆还田, 秸秆处置行为, 三权分离, 产权性质, 土地流转, 河南省

Abstract:

The third plenary session of the 18th central committee of the Communist Party of China proposed the transformation of rural land from “separation of two rights” to “separation of three rights” to promote land transfer and agricultural marketization, but it may also lead to the decline of farmers’ overall expectation of the stability of land contract and land-use rights, which may affect the enthusiasm of farmers to take long-term land investment, such as straw retention. Based on a rural household survey of straw treatment in Henan Province in 2016 and a dataset of 565 plot-level observations, we constructed a three-stage framework of households’ straw treatment and examined the effect of stability of land contract and land-use rights on adoption of straw retention using a binary probit model. The empirical results reveal that own-contracted plots are associated with higher willingness of adopting straw retention than those without land contract rights by rural households due to the difference in land tenure stability. Specifically, the surveyed households with land contract rights have on average 7.7 percentage points higher probability of adopting straw retention than those without. According to the conclusions, we put forward the following policy recommendations: the government may take further actions to stimulate farmers’ willingness of straw retention on plots without land contract rights, such as rented and trusteeship plots, in order to reduce the potential risk of deterioration of rural land and environment due to the expansion of land transfer market and the decrease of farmers’ willingness to adopt conservation tillage.

Key words: stability of land contract and land-use rights, straw retention, straw treatment, separation of land rights, nature of property rights, land transfer, Henan Province

高立, 赵丛雨, 宋宇. 农地承包经营权稳定性对农户秸秆还田行为的影响[J]. 资源科学, 2019, 41(11): 1972-1981.

GAO Li, ZHAO Congyu, SONG Yu. Effect of stability of land contract and land-use rights on straw retention of rural households[J]. Resources Science, 2019, 41(11): 1972-1981.

图/表 6

表1

表2

图1

表3

地块产权性质虚拟变量的构建"

变量名称	待估系数	地块类型	地块来源方式
承包权1( $tenur e 1$ )	$δ 1$	Ⅰ	自家分地,未土地调整
承包权2( $tenur e 2$ )	$δ 2$	Ⅱ	自家分地,后经土地调整
承包权3( $tenur e 3$ )	$δ 3$	Ⅳ	通过转让、互换流转入的土地
无承包权( $tenur e 4$ )	$δ 4$	Ⅴ、Ⅶ	通过转包、出租流转入的土地+开荒地

表3

表4

主要变量的解释及描述性统计（N=565）"

变量类型	变量名称	变量解释	均值	标准差
因变量	秸秆还田	是否采取秸秆还田行为（1=是;0=否）	0.79	0.40
产权性质自变量	承包权1( $tenur e 1$ )	地块是否为1类地块（1=是;0=否）	0.79	0.40
	承包权2( $tenur e 2$ )	地块是否为2类地块（1=是;0=否）	0.10	0.29
	承包权3( $tenur e 3$ )	地块是否为4类地块（1=是;0=否）	0.02	0.14
	无承包权( $tenur e 4$ )	地块是否为5或7类地块（1=是;0=否）	0.08	0.27
户主层面自变量	户主性别( $X 1$ )	户主性别（1=男;0=女）	0.90	0.30
	户主年龄（ $X 2$ ）	户主年龄/周岁	48.46	10.61
	户主风险偏好( $X 3$ )	风险偏好自评分（0~10分,0为不愿冒险）	4.49	1.96
家庭层面自变量	家庭总人口( $X 4$ )	家庭成员总数/人	4.28	1.22
	受教育程度( $X 5$ )	家庭成员最高受教育年限/年	12.54	3.69
	劳动力耕作年限( $X 6$ )	家庭主要务农劳动力平均耕作年限/年	31.55	10.96
	技术培训( $X 7$ )	是否受过农业技术培训（1=是;0=否）	0.06	0.24
	未成年子女( $X 8$ )	是否有未成年子女（1=是;0=否）	0.37	0.48
	家庭年收入( $X 9$ )	农户2016年家庭总收入/万元	4.61	2.99
	农业收入占比( $X 10$ )	农业收入占总收入比重/%	24.26	25.04
地块层面自变量	地块面积( $X 11$ )	地块耕作面积/hm²	0.23	0.49
地块层面自变量	地块离家距离( $X 12$ )	地块离家最短距离/km	0.79	0.62
外部环境自变量	农业机具( $X 13$ )	是否能租到农业耕作机具（1=是;0=否）	0.95	0.21
	政府补贴( $X 14$ )	是否享受农业相关补贴（1=是;0=否）	0.87	0.34
	农业合作组织( $X 15$ )	是否参加农业合作组织（1=是;0=否）	0.09	0.28
	政府贫困扶助( $X 16$ )	是否享受政府贫困扶助（1=是;0=否）	0.28	0.45

表4

表5

Probit模型估计结果（因变量：秸秆还田=1）"

变量	模型（1）	模型（2）	模型（3）	模型（4）
变量	平均边际效应	平均边际效应	平均边际效应	平均边际效应
$tenur e 1$ ：承包权1	0.095***
$tenur e 2$ ：承包权2		-0.112**
$tenur e 3$ ：承包权3			0.135**
$tenur e 4$ ：无承包权				-0.077*
$X 1$ ：户主性别	-0.063	-0.082*	-0.088*	-0.074
$X 2$ ：户主年龄	0.003	0.003	0.003	0.003
$X 3$ ：户主风险偏好	0.020*	0.018*	0.023**	0.024**
$X 4$ ：家庭总人口	0.027**	0.026*	0.024*	0.025*
$X 5$ ：受教育程度	0.004	0.006	0.006	0.005
$X 6$ ：劳动力耕作年限	-0.008***	-0.008***	-0.008***	-0.008***
$X 7$ ：技术培训	0.090	0.071	0.070	0.092
$X 8$ ：未成年子女	-0.111**	-0.114***	-0.109**	-0.109**
$X 9$ ：家庭年收入	-0.026***	-0.026***	-0.025***	-0.025***
$X 10$ ：农业收入占比	-0.002***	-0.002***	-0.002**	-0.002**
$X 11$ ：地块面积	-0.029	-0.046*	-0.049*	-0.034
$X 12$ ：地块离家距离	0.021	0.008	0.010	0.021
$X 13$ ：农业机具	0.133*	0.136*	0.112	0.125*
$X 14$ ：政府补贴	0.148*	0.148*	0.127	0.129
$X 15$ ：农业合作组织	0.271***	0.266***	0.273***	0.276***
$X 16$ ：政府贫困扶助	0.057	0.050	0.031	0.041
地块特征虚拟变量	是	是	是	是
作物虚拟变量	是	是	是	是
Log likelihood	-153.95	-154.56	-157.46	-156.79
Pseudo R²	0.463	0.461	0.451	0.453
预测正确率	89.2%	88.9%	88.9%	88.9%
样本数	565	565	565	565

表5

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