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Small-area population forecasting in a segregated city using density-functional fluctuation theory

Author

Listed:
  • Yuchao Chen

    (Cornell University)

  • Yunus A. Kinkhabwala

    (Cornell University)

  • Boris Barron

    (Cornell University
    Cornell University)

  • Matthew Hall

    (Cornell University
    Cornell University)

  • Tomás A. Arias

    (Cornell University)

  • Itai Cohen

    (Cornell University)

Abstract

Policy decisions concerning housing, transportation, and resource allocation would all benefit from accurate small-area population forecasts. However, despite the success of regional-scale migration models, developing neighborhood-scale forecasts remains a challenge due to the complex nature of residential choice. Here, we introduce an innovative approach to this challenge by extending density-functional fluctuation theory (DFFT), a proven approach for modeling group spatial behavior in biological systems, to predict small-area population shifts over time. The DFFT method uses observed fluctuations in small-area populations to disentangle and extract effective social and spatial drivers of segregation, and then uses this information to forecast intra-regional migration. To demonstrate the efficacy of our approach in a controlled setting, we consider a simulated city constructed from a Schelling-type model. Our findings indicate that even without direct access to the underlying agent preferences, DFFT accurately predicts how broader demographic changes at the city scale percolate to small-area populations. In particular, our results demonstrate the ability of DFFT to incorporate the impacts of segregation into small-area population forecasting using interactions inferred solely from steady-state population count data.

Suggested Citation

  • Yuchao Chen & Yunus A. Kinkhabwala & Boris Barron & Matthew Hall & Tomás A. Arias & Itai Cohen, 2024. "Small-area population forecasting in a segregated city using density-functional fluctuation theory," Journal of Computational Social Science, Springer, vol. 7(3), pages 2255-2275, December.
  • Handle: RePEc:spr:jcsosc:v:7:y:2024:i:3:d:10.1007_s42001-024-00305-3
    DOI: 10.1007/s42001-024-00305-3
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    References listed on IDEAS

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