Diagnosis of rural poverty pattern and its influencing factors in Yunnan province based on spatial econometric model

Chinese government devoted continuously to the rural poverty reduction program which was a long-term hot shot of government and academia since the Reform and Opening Up policy in 1978. Targeted poverty alleviation stratagem which aimed to fully eliminating regional overall poverty in 2020 was put into practice since 2013 in China. Since then, it achieved huge success and the number of people living in extreme poverty reduced sharply in China. But absolute poverty still existed in rural, for the increasing development disparity on account of regional variation; the urban-rural gap was prominent. According to research on rural poverty influencing factors, we found that it had significant differences at different areas and different scales, and lacked a common understanding. For it rarely thought about spatial effects of regional rural poverty for those current existing research on rural poverty influencing factors, it was necessary to study rural poverty influencing factors further. This paper analyzed spatial pattern of rural poverty and main influencing factors on county scale, by applying spatial econometric model and GIS spatial analysis based on the field trip and statistical data which including 15 factors that might influence rural poverty potentially for all of 129 counties in Yunnan province from 2010 to 2015, which intended to providing the theory basis for the formulation and implementation of scientific and effective regional macroscopic poverty reduction policy, and improving poverty reduction that combining poverty status and regional differences even more. This study carried out poverty alleviation and development zoning in Yunnan province, and proposed discrepant policy of regional rural poverty reduction. Results showed that: 1) The number of rural poverty population decreased year by year in Yunnan province, but which was still a high incidence area for rural poverty in China. Rural poverty demonstrated a "center-periphery-edge" pattern which corresponded to low, medium and high poverty among the 129 counties in Yunnan. High poverty areas were concentrated on the northwest, northeast, southeast and south of Yunnan, which involved Jinsha river reaches, Lancang river valley, Nujiang river valley and Red river basin. 2) Regression results of spatial lag model (SLM) showed that the significant influencing factors which affected county rural poverty included terrain relief, traffic distance to municipal government, illiterate rate of population at 15 years old and above of rural, number of hospital beds per thousand people, rate of elderly population at 65 years old and above of rural in Yunnan for the past few years. The regression coefficients of the five significant influencing factors were 0.005, 0.044, 0.380, -1.257 and -2.132 respectively. It produced positive effects on rural poverty for factors of terrain relief, traffic distance to municipal government, illiteracy rate at 15 years old and above of rural in Yunnan province, and the other two factors produced negative effects. 3) Rural poverty had regional differences in Yunnan. In terms of poverty degree and major factors of poverty influencing, Yunnan province was divided into 6 poverty reduction areas which were high poverty area at northwest of Yunnan, high poverty area at northeast of Yunnan, medium-high poverty area at west frontier of Yunnan, medium poverty area at west of Yunnan, high poverty area at southeast of Yunnan and low poverty area at central area of Yunnan. Poverty reduction should be accurately implemented according to regional poverty and major factors of poverty influencing, and strengthened the join forces between adjacent counties to consolidate results of poverty reduction in Yunnan. The spatial effect is an important part of regional rural poverty research, and can provide references for scientific and rational policy setting of regional poverty reduction. © 2019, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.