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Spatial structure of city population growth

Author

Listed:
  • Sandro M. Reia

    (Purdue University)

  • P. Suresh C. Rao

    (Purdue University
    Purdue University)

  • Marc Barthelemy

    (Université Paris-Saclay, CNRS, CEA, Institut de physique théorique
    Centre d’Analyse et de Mathématique Sociales, CNRS/EHESS)

  • Satish V. Ukkusuri

    (Purdue University)

Abstract

We show here that population growth, resolved at the county level, is spatially heterogeneous both among and within the U.S. metropolitan statistical areas. Our analysis of data for over 3,100 U.S. counties reveals that annual population flows, resulting from domestic migration during the 2015–2019 period, are much larger than natural demographic growth, and are primarily responsible for this heterogeneous growth. More precisely, we show that intra-city flows are generally along a negative population density gradient, while inter-city flows are concentrated in high-density core areas. Intra-city flows are anisotropic and generally directed towards external counties of cities, driving asymmetrical urban sprawl. Such domestic migration dynamics are also responsible for tempering local population shocks by redistributing inflows within a given city. This spill-over effect leads to a smoother population dynamics at the county level, in contrast to that observed at the city level. Understanding the spatial structure of domestic migration flows is a key ingredient for analyzing their drivers and consequences, thus representing a crucial knowledge for urban policy makers and planners.

Suggested Citation

  • Sandro M. Reia & P. Suresh C. Rao & Marc Barthelemy & Satish V. Ukkusuri, 2022. "Spatial structure of city population growth," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
  • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-33527-y
    DOI: 10.1038/s41467-022-33527-y
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    References listed on IDEAS

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    Cited by:

    1. Fei Jin & Lung‐fei Lee & Kai Yang, 2024. "Best linear and quadratic moments for spatial econometric models with an application to spatial interdependence patterns of employment growth in US counties," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(4), pages 640-658, June.

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