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

The relationship between livelihood capital and livelihood strategy based on logistic regression model in Xinping County of Yuanjiang dry-hot valley

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。

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.