多维资本外部性与贫困县经济增长——来自县域贫困区的空间计量分析

Multidimensional Capital Externality and Economic Growth In Poverty Areas A Spatial Econometric Analysis Based on China’s Poverty-stricken Counties

立足于中国505个连片贫困县的县域样本数据,从邻居贫困县外部性和目标贫困县外部性视角考察多维资本对我国连片贫困县经济增长的影响。研究发现:土地资本、物质资本、公共服务资本、政府行为以及技术进步都能通过直接效应显著促进目标贫困县自身经济增长;邻居贫困县中的土地资本、物质资本、公共服务资本以及技术进步都存在正邻居贫困县外部性,而人力资本和地方政府支出则对目标贫困的经济增长具有显著的负邻居贫困县外部性;目标贫困县的耕地资本、物质资本、公共服务资本、技术进步、地方政府支出都能通过正目标贫困县外部性显著促进邻居区域经济增长。同时,在稳健性检验的GNS模型中,土地资本、技术进步以及政府支出的对邻居贫困县的正外部性以及人力资本的负外部性都处于富有弹性区域。

This paper analyzes the impact of multidimensional capital on spatial poverty from the perspective of neighbor externalities(NE)and target area externalities(TAE)by using a variety of econometric regression models to analyze the spatial panel data of 505 poverty regions at the county level in China.It has been found that land capital,physical capital,public service capital,local government behavior and technical progress can all significantly promote the economic growth of poor areas by means of direct effect.Moreover,land capital,physical capital,public service capital and technical progress in neighboring areas have positive NE,while neighboring areas’human capital and local government spending both have significantly negative NE.In addition,land capital,physical capital,public service capital,technical progress and government spending in local areas will all promote neighboring areas’economic growth significantly through positive TAE,and the values of positive TAE from land capital,technical progress and government spending as well as the value of the negative TAE from human capital are all in a flexible interval in the GNS model.