US city size distribution: Robustly Pareto, but only in the tail
US city size distribution: Robustly Pareto, but only in the tail
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DOI：
10.1016/j.jue.2012.06.005
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发表时间：
2013-01-01
影响因子：
6.3
通讯作者：
Skouras, Spyros
中科院分区：
文献类型：
--
作者：
Ioannides, Yannis;Skouras, Spyros
我们使用美国城市的三种不同定义凭经验确定上尾服从帕累托定律而不是对数正态分布。我们强调对城市规模分布主体（包括大多数城市）与其上尾部（包括大多数人口）之间的切换点的估计。特别是对于 2000 年人口普查地点数据，我们的首选模型表明，从对数正态分布到帕累托法则的转变发生在人口 60,290 周围的狭窄置信区间内，相应的帕累托指数为 1.25。大多数城市遵循对数正态分布；但上尾部以及大多数人口都遵守帕累托法则。我们使用 Rozenfeld 等人的区域聚类数据获得了上尾部的定性相似结果。 （2011）和美国人口普查结合了大都市和小都市地区的数据，尽管较小规模的分布形状对所使用的定义很敏感。 (C) 2012 Elsevier Inc. 保留所有权利。
We establish empirically using three different definitions of US cities that the upper tail obeys a Pareto law and not a lognormal distribution. We emphasize estimation of a switching point between the body of the city size distribution (which includes most cities) and its upper tail (which includes most of the population). For the 2000 Census Places data, in particular, our preferred model suggests that switching from a lognormal to a Pareto law occurs within a narrow confidence interval around population 60,290, with a corresponding Pareto exponent of 1.25. Most cities obey a lognormal; but the upper tail and therefore most of the population obeys a Pareto law. We obtain qualitatively similar results for the upper tail with the Area Clusters data of Rozenfeld et al. (2011), and the US Census combined Metropolitan and Micropolitan Areas data, though the shape of that distribution at smaller sizes is sensitive to the definition used. (C) 2012 Elsevier Inc. All rights reserved.