贵州省乡村贫困空间格局与形成机制分析

以贫困态势严峻、区域内部贫困差异大的贵州省为研究区,分析了贵州省区县层面乡村贫困的空间异质性和空间依赖性格局,定量测度了乡村贫困空间差异的影响因素和因素效应的空间差异性,进而归纳了贵州省乡村贫困的形成机制。结果发现,贵州省区县乡村贫困具有时空稳定性,呈现出东、南、西部高而中、北部低的“马蹄”形空间异质性格局。区县贫困存在较强的空间依赖性,“高-高”型贫困地域即空间贫困陷阱区域,集聚分布在贵州省的东南部、南部。定量模型发现,坡度、到所在市中心的距离、青少年人口占比、少数民族人口占比是导致贵州区县层面乡村贫困空间差异的显著因素,且这些因素的效应水平呈现出不同的空间模式。产业发展受限、劳动力流动性差、金融和人力资本积累不足是贵州贫困空间形成的主导机制。最后建议扶贫政策层面应将基于地方和基于人的政策相结合。

Spatial Patterns and Determinants of Rural Poverty: A Case of Guizhou Province,China

China has been a long-period fast economic growth after its opening policy. The whole degree of poverty in China has decreased sharply, which plays an important role in fulfilling Millennium Development Goals (MDG) made by the United Nations. As a developing country, however, China still has a challenge of reducing poverty and promoting regional development. Rural poverty is still a serious problem in rural China, especially in mountainous or ethnic areas. Different scales of governments in China develop much poverty-alleviation policy, but the efficacy of these policy are sometimes low because “one size fits all” policy always neglect regional difference in poverty resulting from different contexts of different places. Spatial patterns and determinants of regional poverty is a key theme for scholars from many disciplines. Giving that determinants of rural poverty in different places are different and the effects of significant factor are dependent on spatial scales, there is a need for more empirical evidences at different scales or in different regions. Furthermore there is little study to explore the spatial variations of effects of determinants. The present article can fill these gap to some extent through analyzing the determinants of county-level poverty and its spatial variation of their effects within Guizhou Province in the southwestern China. The rate of county-level poverty is largely different within this province. Based on methods of OLS regression, spatial econometric and geographic weighted regression (GWR), this article studies spatial variations and determinants of rural poverty at the county level. The results show that rate of rural poverty is higher in the eastern, southern, western counties than middle and northern counterparts. There is a significant spatial autocorrelation of rural poverty, for index of Moran’s I is between 0.45 and 0.55, which indicates that poverty of neighboring counties have a positive effect on the poverty of a specific county. Some counties with a high-high poor pattern fall into spatial trap of poverty based on results of index of Local Moran’s I. These counties are located at southeast and southern parts of Guizhou and have a high proportion of ethnic minorities’ population. For the determinants, the OLS estimation results show that topographic slope, distance to a local urban center, the percentage of teenagers, the percentage of ethnic minorities are key determinants of spatial variations in rural poverty at the county level. The effects of these four factors are found to have different spatial patterns based on GWR analysis. There is no significant effect for distance to the provincial capital on the rural poverty. The above results have important policy implication. The core implication is to combine place-based and people-based policy, which surpass the current Poverty-Targeting-Alleviation (jing zhun fu pin) initiatives dominating poverty-reduction policy of China’s governments.