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Zipf law for Brazilian cities

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  • Moura, Newton J.
  • Ribeiro, Marcelo B.

Abstract

This work studies the Zipf law for cities in Brazil. Data from censuses of 1970, 1980, 1991 and 2000 were used to select a sample containing only cities with 30,000 inhabitants or more. The results show that the population distribution in Brazilian cities does follow a power-law similar to the ones found in other countries. Estimates of the power-law exponent were found to be 2.22±0.34 for the 1970 and 1980 censuses, and 2.26±0.11 for censuses of 1991 and 2000. More accurate results were obtained with the maximum likelihood estimator, showing an exponent equal to 2.41 for 1970 and 2.36 for the other 3 years.

Suggested Citation

  • Moura, Newton J. & Ribeiro, Marcelo B., 2006. "Zipf law for Brazilian cities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 367(C), pages 441-448.
  • Handle: RePEc:eee:phsmap:v:367:y:2006:i:c:p:441-448
    DOI: 10.1016/j.physa.2005.11.038
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    Cited by:

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    5. Simos Meintanis, 2009. "A unified approach of testing for discrete and continuous Pareto laws," Statistical Papers, Springer, vol. 50(3), pages 569-580, June.
    6. Chami Figueira, F. & Moura, N.J. & Ribeiro, M.B., 2011. "The Gompertz–Pareto income distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(4), pages 689-698.
    7. Valente J. Matlaba & Mark J. Holmes & Philip McCann & Jacques Poot, 2013. "A Century Of The Evolution Of The Urban System In Brazil," Review of Urban & Regional Development Studies, Wiley Blackwell, vol. 25(3), pages 129-151, November.
    8. Arshad, Sidra & Hu, Shougeng & Ashraf, Badar Nadeem, 2019. "Zipf’s law, the coherence of the urban system and city size distribution: Evidence from Pakistan," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 87-103.
    9. Asif, Muhammad & Hussain, Zawar & Asghar, Zahid & Hussain, Muhammad Irfan & Raftab, Mariya & Shah, Said Farooq & Khan, Akbar Ali, 2021. "A statistical evidence of power law distribution in the upper tail of world billionaires’ data 2010–20," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    10. Lang, Wei & Long, Ying & Chen, Tingting & Li, Xun, 2019. "Reinvestigating China’s urbanization through the lens of allometric scaling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 1429-1439.
    11. Rusanovskiy, Viktor (Русановский, Виктор) & Markov, Vladimir (Марков, Владимир) & Brovkova, Anna (Бровкова, Анна), 2018. "Modeling the Effects of Spatial Localization in Urban Agglomerations of Russia [Моделирование Эффекта Пространственной Локализации В Городских Агломерациях России]," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 6, December.
    12. Kii, Masanobu & Akimoto, Keigo & Doi, Kenji, 2012. "Random-growth urban model with geographical fitness," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(23), pages 5960-5970.
    13. Calderín-Ojeda, Enrique, 2016. "The distribution of all French communes: A composite parametric approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 385-394.
    14. Hasan Engin Duran & Andrzej Cieślik, 2021. "The distribution of city sizes in Turkey: A failure of Zipf’s law due to concavity," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(5), pages 1702-1719, October.
    15. Gómez-Déniz, Emilio & Calderín-Ojeda, Enrique, 2015. "On the use of the Pareto ArcTan distribution for describing city size in Australia and New Zealand," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 821-832.
    16. Kaichun Zhou & Anzhou Fu & Can Xiao & Ping Tang & Junyi Zhang & Binggeng Xie, 2023. "Understanding Idle Land Using Local Environmental Characteristics: A Case Study of Liuyang, China," Sustainability, MDPI, vol. 15(8), pages 1-19, April.
    17. Nikolay K. Vitanov & Marcel Ausloos, 2015. "Test of two hypotheses explaining the size of populations in a system of cities," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(12), pages 2686-2693, December.
    18. Sarabia, José María & Prieto, Faustino, 2009. "The Pareto-positive stable distribution: A new descriptive model for city size data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(19), pages 4179-4191.
    19. Chen, Yanguang & Wang, Jiejing, 2014. "Recursive subdivision of urban space and Zipf’s law," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 392-404.
    20. Fernández-Rosales, Iván Yair & Angulo-Brown, Fernando & Pérez-Campuzano, Enrique & Guzmán-Vargas, Lev, 2020. "Distance distributions of human settlements," Chaos, Solitons & Fractals, Elsevier, vol. 136(C).
    21. Yang Li & Hua Shao & Nan Jiang & Ge Shi & Xin Cheng, 2018. "The Evolution of the Urban Spatial Pattern in the Yangtze River Economic Belt: Based on Multi-Source Remote Sensing Data," Sustainability, MDPI, vol. 10(8), pages 1-21, August.
    22. Huimin Xu & Shougeng Hu & Xi Li, 2023. "Urban Distribution and Evolution of the Yangtze River Economic Belt from the Perspectives of Urban Area and Night-Time Light," Land, MDPI, vol. 12(2), pages 1-21, January.

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