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Empirical analysis on the connection between power-law distributions and allometries for urban indicators

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  • Alves, L.G.A.
  • Ribeiro, H.V.
  • Lenzi, E.K.
  • Mendes, R.S.

Abstract

We report on the existing connection between power-law distributions and allometries. As it was first reported in Gomez-Lievano et al. (2012) for the relationship between homicides and population, when these urban indicators present asymptotic power-law distributions, they can also display specific allometries among themselves. Here, we present an extensive characterization of this connection when considering all possible pairs of relationships from twelve urban indicators of Brazilian cities (such as child labor, illiteracy, income, sanitation and unemployment). Our analysis reveals that all our urban indicators are asymptotically distributed as power laws and that the proposed connection also holds for our data when the allometric relationship displays enough correlations. We have also found that not all allometric relationships are independent and that they can be understood as a consequence of the allometric relationship between the urban indicator and the population size. We further show that the residuals fluctuations surrounding the allometries are characterized by an almost constant variance and log-normal distributions.

Suggested Citation

  • Alves, L.G.A. & Ribeiro, H.V. & Lenzi, E.K. & Mendes, R.S., 2014. "Empirical analysis on the connection between power-law distributions and allometries for urban indicators," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 409(C), pages 175-182.
  • Handle: RePEc:eee:phsmap:v:409:y:2014:i:c:p:175-182
    DOI: 10.1016/j.physa.2014.04.046
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    1. Jan Eeckhout, 2004. "Gibrat's Law for (All) Cities," American Economic Review, American Economic Association, vol. 94(5), pages 1429-1451, December.
    2. Mantegna,Rosario N. & Stanley,H. Eugene, 2007. "Introduction to Econophysics," Cambridge Books, Cambridge University Press, number 9780521039871, September.
    3. Luiz G A Alves & Haroldo V Ribeiro & Ervin K Lenzi & Renio S Mendes, 2013. "Distance to the Scaling Law: A Useful Approach for Unveiling Relationships between Crime and Urban Metrics," PLOS ONE, Public Library of Science, vol. 8(8), pages 1-8, August.
    4. Dion R J O’Neale & Shaun C Hendy, 2012. "Power Law Distributions of Patents as Indicators of Innovation," PLOS ONE, Public Library of Science, vol. 7(12), pages 1-9, December.
    5. Luis Bettencourt & Geoffrey West, 2010. "A unified theory of urban living," Nature, Nature, vol. 467(7318), pages 912-913, October.
    6. Luís M A Bettencourt & José Lobo & Deborah Strumsky & Geoffrey B West, 2010. "Urban Scaling and Its Deviations: Revealing the Structure of Wealth, Innovation and Crime across Cities," PLOS ONE, Public Library of Science, vol. 5(11), pages 1-9, November.
    7. Yannick Malevergne & Didier Sornette, 2006. "Extreme Financial Risks : From Dependence to Risk Management," Post-Print hal-02298069, HAL.
    8. Alves, Luiz G.A. & Ribeiro, Haroldo V. & Mendes, Renio S., 2013. "Scaling laws in the dynamics of crime growth rate," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(11), pages 2672-2679.
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    7. Cardoso, M. & Afonso, L.H.D. & Neli, R.R. & Souza, W.E., 2024. "Simplified model relating blank and null votes to voter turnout from Brazilian state elections results," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 645(C).
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