贫穷
星团(航天器)
经济地理学
多元统计
分布(数学)
工作(物理)
经济
贫困率
人口经济学
发展经济学
经济增长
统计
机械工程
工程类
数学分析
计算机科学
数学
程序设计语言
作者
Christopher S. Fowler,Rachel Garshick Kleit
摘要
Abstract Industrial clusters are widely understood as a worthwhile target of local economic development resources. Nevertheless, most of the work on cluster development has asserted benefits that accrue to a regional economy as a whole, with little or no focus on specific links between clusters and poverty alleviation. This article seeks to understand the degree to which economic clusters are associated with lower poverty rates. Specifically, using spatial regression analysis techniques, we examine patterns that link clusters to poverty rates while controlling for the presence of other factors that shape the distribution of poverty in the U nited S tates. When controlling for other economic and demographic factors in a multivariate framework, the presence of industrial clusters is associated with lower poverty rates. Moreover, regions with a higher share of employment in clusters, and with that employment dispersed across many industries within the same cluster, fare even better than those where employment is concentrated in a single industry. Furthermore, while there is evidence that particular clusters are associated with significantly altered poverty rates, not all of these associations are beneficial.
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