西南喀斯特石漠化深度贫困县的贫困影响因素分析  

Analysis on poverty influencing factors in deep poverty county of Karst Rocky-desertified Area in Southwest China

作　　者：杨人懿 钟昌标 杨子生[2] 刘凤莲 彭海英 YANG Renyi;ZHONG Changbiao;YANG Zisheng;LIU fenglian;PENG Haiying(School of Economics,Yunnan University of Finance and Economics,Kunming 650221,China;Institute of Targeted Poverty Alleviation and Development,Yunnan University of Finance and Economics,Kunming 650221,China)

机构地区：[1]云南财经大学经济学院,昆明650221 [2]云南财经大学精准扶贫与发展研究院,昆明650221

出　　处：《世界地理研究》2022年第6期1298-1309,共12页World Regional Studies

基　　金：国家自然科学基金项目(41261018,71673182);国家社会科学基金重大项目(18VSJ023)。

摘　　要：中国西南喀斯特石漠化地区人口-资源-环境-经济矛盾十分突出,严重制约了地区的可持续发展。基于该地区的深度贫困县——广西德保县的2014—2019年各乡镇社会、经济、人口等维度的面板数据,以空间贫困为理论导向,运用空间动态面板模型和GWR模型探索了石漠化地区县域贫困影响因素及溢出效应。空间动态自回归模型结果表明,各乡镇当年的贫困发生率表现出较大的惯性;农村居民恩格尔系数的下降、农村医疗卫生水平的提高、就业水平的提升、少数民族占比的下降、人口密度的降低均可明显地促进地区减贫。空间动态杜宾模型估计结果不仅支持了空间动态自回归模型结果,而且表明农村居民恩格尔系数、农村医疗卫生水平、人口密度分别表现出显著的有益、不利和有益的外溢效应,长期影响更深远。GWR模型结果表明其影响效果具有明显的空间差异性。The contradiction of population, resources, environment and economy is very prominent in karst rocky-desertified areas of Southwest China, which are the bottlenecks restricting the sustainable development of society and economy. Based on the theoretical guide of spatial poverty and the panel data of social, economic, population and other dimensions of Debao County in Guangxi Zhuang Autonomous Region from 2014 to 2019, this paper explored the influencing factors and spillover effects of county poverty in karst rocky-desertified area by using spatial dynamic panel model and GWR Model. The results of Spatial Dynamic Auto-regression Model show that the incidence of poverty in each town shows great inertia. The decline of Engel’s coefficient of rural residents, the improvement of rural health care, the improvement of employment level, the decrease of the proportion of ethnic minorities, and the decrease of population density can significantly contribute to the reduction of regional poverty. The estimation results of the Spatial Dynamic Durbin Model not only support the results of the Spatial Dynamic Auto-regression Model, it also shows that rural residents, Engel’s coefficient, and population density have significant beneficial, adverse and beneficial spillover effects, respectively. And the long-term impact are more profound. The results of GWR model show that the effects of these factors are different in space.

关 键 词：喀斯特石漠化地区 贫困影响因素 空间动态面板模型 空间溢出效应 GWR模型 德保县 

分 类 号：F323.8[经济管理—产业经济]