基于Logistic回归模型的生计资本与生计策略研究——以云南新平县干热河谷傣族地区为例

doi:10.18402/resci.2016.01.15

摘要/Abstract

摘要：

生计资本是农户生计策略选择的基础,探讨农户生计资本对生计策略选择的影响对于提高农户生计水平具有重要意义。本文以云南新平县干热河谷傣族地区为例,在依据问卷调查数据评估当地农户生计资本现状的基础上,采用Logistic回归模型剖析生计资本与生计策略之间的关系。研究结果表明：①农户的金融资本指数最高,自然资本、人力资本和社会资本居中,物质资本最低。当前研究区农户主要采取纯农型、农兼型和兼农型生计策略;②自然资本和物质资本对纯农型农户生计策略选择的影响最为显著,社会资本和物质资本对农兼型的影响最为显著,而金融资本对兼农型的影响最为显著;③金融资本和社会资本是影响纯农型向农兼型转化的关键因子。就具体生计资本指标而言,家庭收入、领导能力、家庭整体劳动力、人均机械数量和人均水田面积等对由纯农型向农兼型生计策略转化起到促进作用;④金融资本和人力资本是影响纯农型向兼农型转化的关键因子。就具体生计资本指标而言,人均纯收入、彩礼支出、成年劳动力受教育程度、参与社区公共祭祀活动和人均旱地种植面积等对由纯农型向兼农型生计策略转化起到促进作用。

关键词: 农户, 生计资本, 生计策略, Logistic回归模型, 新平县干热河谷

Abstract:

Livelihood capital is the basis for farmers’ livelihood strategy. Probing into the impact of farmers’ livelihood capitals on livelihood strategies is of great significance for improving local farmers’ livelihood. Based on sustainable livelihood approach framework,status quo of livelihood capital for farmers of Xinping dry-hot valley was assessed with field survey data. Logistic regression model was adopted to explore the relationship between livelihood capitals and livelihood strategies. The results showed as follows：firstly,for the five types of livelihood capital,financial capital exhibited the highest index of 0.994,physical capital exhibited the lowest of 0.313,while natural capital,human capital and social capital ranked in between with respective indexes of 0.662,0.569 and 0.479. In the meantime,pure agricultural strategies,agricultural dominant strategies and non-agricultural dominant strategies were the popular ones adopted in the study area. Secondly,natural and physical capitals exerted the most significant impact on farmers’ choice of pure agricultural livelihood strategies,social and physical capitals exerted the most significant impact on farmers’ choice of agricultural dominant ones,while financial capital exerted the most significant impact on farmers’ choice of non-agricultural dominant ones. Thirdly,financial and social capitals were the key factors affecting farmers’ conversion from pure agricultural to agricultural dominant strategies. In particular,total family income,leadership,household labor capacity,per capita number of machines and per capita area of paddy field as well exhibited positive impacts. With increase of proportion of the above-mentioned indexes,odds ratio from pure agricultural strategies to agricultural dominant ones would increase as other conditions remain unchanged. Fourthly,financial and human capitals were the key factors affecting farmers’ conversion from pure agricultural to non-agricultural dominant strategies. In particular,per capita net income,bride expenditure,adult labor education level,participation in community rites and per capita acreage of dry land as well exhibited positive impacts. With increase of proportion of the above-mentioned indexes,odds ratio from pure agricultural strategies to non-agricultural dominant ones would increase as other conditions remain unchanged.

Key words: farmer, livelihood capital, livelihood strategy, logistic regression model, Xinping dry-hot valley

赵文娟, 杨世龙, 王潇. 基于Logistic回归模型的生计资本与生计策略研究——以云南新平县干热河谷傣族地区为例[J]. 资源科学, 2016, 38(1): 136-143.

ZHAO Wenjuan,YANG Shilong,WANG Xiao. The relationship between livelihood capital and livelihood strategy based on logistic regression model in Xinping County of Yuanjiang dry-hot valley[J]. Resources Science, 2016, 38(1): 136-143.

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解释变量		测量指标	权重	指标说明
N	N₁	人均水田面积	0.066	人均水田承包面积/hm²
	N₂	人均旱地面积	0.058	人均旱地承包面积/hm²
	N₃	人均水田种植面积	0.065	人均水田实际种植面积/hm²
	N₄	人均旱地种植面积	0.047	人均旱地实际种植面积/hm²
H	H₁	家庭整体劳动力	0.045	非劳动力为0;半劳动力为0.5;全劳动力为1
	H₂	成年劳动力受教育程度	0.054	文盲为0;小学为0.25;初中为0.5;高中为0.75;专科及以上为1
	H₃	人均教育投入	0.060	家庭人均教育投入/元
P	P₁	畜禽数量	0.036	鸡鸭等为0.25;猪为0.5;牛为1
	P₂	人均机械数量	0.034	人均机械数量/台
	P₃	住房类型	0.037	土掌房为0.5;平顶房为1
F	F₁	家庭收入	0.148	家庭收入/元
F	F₂	人均纯收入	0.164	人均纯收入/元
S	S₁	领导能力	0.072	家里有在镇上、村委会的为1;没有的为0
	S₂	彩礼支出	0.065	家庭彩礼支出/元
	S₃	参与社区公共祭祀活动	0.049	家里有人参加为1,没有为0

农户类型解释变量	纯农型			农兼型			兼农型
农户类型解释变量	（B）	Wald	Exp（B）	（B）	Wald	Exp（B）	（B）	Wald	Exp（B）
N	0.189	4.305**	1.208	0.052	0.473*	1.054	-0.462	11.143***	0.630
H	-0.251	4.019**	0.778	0.091	0.676*	1.095	0.174	1.293*	1.190
P	0.131	0.711*	1.139	0.099	0.506*	1.104	-0.289	3.012**	0.749
F	-0.606	7.342***	0.546	-0.055	0.162*	0.947	0.566	10.117***	1.761
S	-0.283	4.868**	0.753	0.241	4.247**	1.273	0.106	0.450*	1.112
样本数（287）	H-L Chi-square=14.029 （df=8,Sig=0.081）			H-L Chi-square=5.116 （df=7,Sig=0.646）			H-L Chi-square=9.311 （df=8,Sig=0.331）

类型		B	Std. Error	Wald	Sig	Exp （B）
农兼型	截距	0.438	0.218	4.041	0.044	-
	N	-0.108	0.094	1.315	0.251	0.897
	H	0.228	0.131	3.045	0.081	1.256
	P	-0.033	0.170	0.038	0.845	0.967
	F	0.495	0.232	4.550	0.033	1.641
	S	0.303	0.135	5.077	0.024	1.355
兼农型	截距	-0.978	0.338	8.369	0.004	-
	N	-0.525	0.154	11.659	0.001	0.592
	H	0.355	0.178	3.994	0.046	1.426
	P	-0.329	0.199	2.741	0.098	0.720
	F	0.953	0.269	12.561	0.000	2.594
	S	0.262	0.183	2.043	0.153	1.300
参考类型：纯农型

农户类型	解释变量	B	Std.Error	Wald	Sig	Exp（B）
农兼型	截距	0.418	0.249	2.829	0.093	-
	N₁	0.144	0.315	0.208	0.648	1.155
	N₂	-0.633	0.369	2.950	0.086	0.531
	N₃	-0.244	0.347	0.494	0.482	0.784
	N₄	0.000	0.317	0.000	0.999	1.000
	H₁	0.329	0.282	1.366	0.242	1.390
	H₂	0.045	0.284	0.025	0.874	1.046
	H₃	0.188	0.268	0.495	0.482	1.207
	P₁	-0.906	0.728	1.549	0.213	0.404
	P₂	0.162	0.247	0.431	0.512	1.176
	P₃	-0.391	0.286	1.876	0.171	0.676
	F₁	1.448	0.822	3.106	0.078	4.256
	F₂	0.103	0.527	0.038	0.845	1.108
	S₁	0.634	0.248	6.523	0.011	1.885
	S₂	0.155	0.309	0.252	0.615	1.168
	S₃	0.077	0.261	0.086	0.770	1.080
兼农型	截距	-3.251	0.997	10.633	0.001	-
	N₁	-0.781	0.626	1.555	0.212	0.458
	N₂	-0.536	0.620	0.745	0.388	0.585
	N₃	-1.062	0.738	2.068	0.150	0.346
	N₄	0.184	0.501	0.135	0.714	1.202
	H₁	0.027	0.440	0.004	0.952	1.027
	H₂	0.688	0.442	2.430	0.119	1.990
	H₃	0.175	0.439	0.158	0.691	1.191
	P₁	-11.102	4.165	7.103	0.008	0.000
	P₂	0.011	0.407	0.001	0.978	1.011
	P₃	-0.592	0.432	1.876	0.171	0.553
	F₁	-3.309	1.839	3.238	0.072	0.037
	F₂	3.348	1.132	8.747	0.003	28.457
	S₁	0.591	0.428	1.906	0.167	1.805
	S₂	1.599	0.591	7.323	0.007	4.946
	S₃	0.338	0.535	0.400	0.527	1.403
参考类型：纯农型