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US city size distribution: Robustly Pareto, but only in the tail
16 references·7 citing·48 second hop
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References

  • 2009Power-Law Distributions in Empirical Data8,008 cited
  • 2018Power-law distributions in empirical data6,499 cited
  • 1999Zipf's Law for Cities: An Explanation2,043 cited
  • 1972The Sizes and Types of Cities954 cited
  • 2012The Productivity Advantages of Large Cities: Distinguishing Agglomeration From Firm Selection886 cited
  • 1995Trade and Circuses: Explaining Urban Giants837 cited
  • 2004Gibrat's Law for (All) Cities787 cited
  • 2005From sectoral to functional urban specialisation617 cited
  • 2011The Area and Population of Cities: New Insights from a Different Perspective on Cities413 cited
  • 2007Urban Evolutions: The Fast, the Slow, and the Still412 cited
  • 2003Urban evolution in the USA388 cited
  • 1996Confronting the Mystery of Urban Hierarchy387 cited
  • 1997Medium size cities210 cited
  • 2010The size distribution across all cities – Double Pareto lognormal strikes194 cited
  • 2011Testing the Pareto against the lognormal distributions with the uniformly most powerful unbiased test applied to the distribution of cities183 cited
  • 2002On the Rank‐Size Distribution for Human Settlements

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168 cited

Cited by

  • 2015The Geography of Development Within Countries100 cited
  • 2013The size distribution of US cities: Not Pareto, even in the tail65 cited
  • 2016Determinants of city growth in Colombia63 cited
  • 2022Exploring Spatial Network Structure of the Metropolitan Circle Based on Multi-Source Big Data: A Case Study of Hangzhou Metropolitan Circle10 cited
  • 2017Earthquakes economic costs through rank-size laws9 cited
  • 2020The size distribution of ‘cities’ delineated with a network theory‐based method and mobile phone GPS data8 cited
  • 2021URBAN MAGNETISM IN THE GLOBAL CITY FRAMEWORK: EXPLORING THE LINK BETWEEN URBAN FUNCTIONS AND POPULATION GROWTH5 cited