In the literature, the distribution of city size is a controversial issue with two common contenders: the Pareto and the log-normal. While the first is most accredited when the distribution is truncated above a certain threshold, the latter is usually considered a better representation for the untruncated distribution of all cities. In this paper, we reassess the empirical evidence on the best-fitting distribution in relation to the truncation point issue. Specifically, we provide a comparison among four recently proposed approaches and alternative definitions of U.S. cities. Our results highlight the importance to look at issue of the best-fitting distribution together with the truncation issue and provide guidance with respect to the existing tests of the truncation point.

Pareto or lognormal? Best fit and truncation in the distribution of all cities

Modica M
2015

Abstract

In the literature, the distribution of city size is a controversial issue with two common contenders: the Pareto and the log-normal. While the first is most accredited when the distribution is truncated above a certain threshold, the latter is usually considered a better representation for the untruncated distribution of all cities. In this paper, we reassess the empirical evidence on the best-fitting distribution in relation to the truncation point issue. Specifically, we provide a comparison among four recently proposed approaches and alternative definitions of U.S. cities. Our results highlight the importance to look at issue of the best-fitting distribution together with the truncation issue and provide guidance with respect to the existing tests of the truncation point.
Zipf's Law, City Size Distribution, random growth process
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12571/7300
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