县域生计效率空间分异及其影响因素

Spatial differentiation and influencing factors of livelihood efficiency in county areas

关键词:  生计效率  空间分异  县域尺度  陕南秦巴山区  产业结构

Key words:  livelihood efficiency  spatial differentiation  county scale  Qinba mountain area in Southern Shaanxi  the industrial structure

摘要:

县域作为区域经济的重要组织单元，其生计效率的评估是衡量县域资源整合和利用程度的重要方式。揭示县域生计效率的空间分布特征，对于推动区域协调发展、促进乡村振兴战略具有重要意义。通过构建县域尺度生计效率评估指标体系，以2015—2019年陕南秦巴山区28个县域为研究对象，运用数据包络分析法、空间自相关分析法、Tobit模型等研究方法，探究县域生计效率的空间分布特征及其影响因素。结果表明：（1）2015—2019年陕南秦巴山区县域生计效率呈现上升趋势，但三市生计效率的制约因素有所不同；（2）各区县生计效率总体上呈现“东北高—西南低”的空间分布格局且表现出显著的空间正相关性，与2015年空间分布特征相比，2019年低—低集聚区仍主要分布于汉中市，但高 — 高集聚区有所不同；（3）多种因素共同影响县域生计效率，其中，产业结构、区域条件是影响该地区县域生计效率的关键因素。除此之外，生计投入要素中水资源、人口密度、受教育程度、粮食产量、地方财政、机构贷款均对县域生计效率具有重要影响。未来应充分挖掘县域发展潜力、优化产业结构、加大财政支持与金融补贴力度，打破资源流动壁垒以提高各县域生计效率。

Abstract:

Background, aim, and scope The assessment of livelihood efficiency in the county as an important organizational unit of the regional economy is an important way to measure the extent to which the county’s resources are integrated and utilized. The mountainous areas out of poverty, represented by the Qinba mountain area in Southern Shaanxi, have insufficient endogenous development power and prominent problems of returning to poverty. However, past studies have mostly focused on static livelihood efficiency issues at the farmer scale, neglecting the efficiency assessment of the whole livelihood process, making it difficult to reveal the dynamic trends of livelihoods and the bottlenecks that constrain their development. Exploring the characteristics of the spatial distribution of livelihood efficiency and its influencing factors on a county scale can provide theoretical support for the grass-roots government to rationally integrate resources in the future, and promote the coordinated development of the county economy in the region. Materials and methods By constructing a county-scale livelihood efficiency evaluation index system, this study evaluated 28 districts and counties in the Qinba mountain area of Southern Shaanxi from 2015 to 2019. Data envelopment analysis, spatial autocorrelation analysis, and the Tobit model were used to explore the spatial distribution characteristics and influencing factors of county livelihood efficiency. Results (1) From 2015 to 2019, county livelihood efficiency in the Qinba mountain area of Southern Shaanxi showed an upward trend, but factors restricting livelihood efficiency varied across three cities. (2) Livelihood efficiency in all districts and counties was high in the northeast and low in the southwest, with a significant positive spatial correlation. Compared with the spatial distribution characteristics in 2015, the low—low agglomeration area continued to be mainly distributed in Hanzhong City in 2019, but the high—high agglomeration area had changed. (3) Various factors collectively affect county livelihood efficiency, with industrial structure and regional conditions emerging as the key factors. Discussion This study examined the extent of resource integration and utilization in 28 districts and counties in the Qinba mountain area in Southern Shaanxi, based on sustainable livelihood theory. The number of efficient districts and counties remained small and largely unchanged during the study period, and the main constraints on livelihood efficiency in different districts and counties varied, with technical efficiency being the main constraint in the low and medium efficiency districts and counties, and scale efficiency being the bottleneck for further development in the relatively efficient districts and counties. In addition, districts and counties livelihood efficiency in the study area is dynamically changing and has a certain spatial correlation, showing a spatial distribution pattern of “high in the northeast—low in the southwest”, and there is a Matthew effect, which requires special attention to Xixiang and Zhenba counties, so as to gradually narrow the development gap through a full understanding of the obstacles to the livelihood efficiency of districts and counties. Conclusions In addition to industrial structure and regional conditions, livelihood input factors such as water resources, population density, education level, grain output, local finance, and institutional loans significantly impact county livelihood efficiency, although with varied effects. Continuous adjustment of the input structure of resource factors based on to the actual needs of counties in poverty-stricken mountainous areas is crucial for their high-quality development. Recommendations and perspectives In the future, it is important to leverage each county’s development potential, optimize its industrial structure, boost financial support and subsidies, and break the barriers of resource flow to improve livelihood efficiency.