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How moving costs Impact in Schelling’s Segregation Model : An extension to the original model

Author

Listed:
  • Carrasco, Hugo
  • Abreo, Cindy
  • Álvarez-Vaz, Ramón Dr.

    (Universidad de la República)

Abstract

In Schelling’s classical model [1], when an individual feels dissatisfied with the number of unwanted "neighbors," they simply move to another free location, but this is restricted by the city’s density. Furthermore, it is assumed that in real life, moving has many associated costs. For this reason, it is proposed to modify the model and extend it by considering that each agent starts with a certain amount of monetary units (capital C), and that with each unit of time, each agent manages to save a certain amount of monetary units (savings A). If at any given time they feel dissatisfied and have capital greater than or equal to the cost of moving Cm (moving), then they can move to one of the free locations. Otherwise, they cannot, which means that in the next step they may or may not be dissatisfied, depending on what happened to their neighbors. Using models that consider differential costs by group, different initial capitals, and different savings capacities, the impact of these initial conditions on segregation is studied for certain levels of happiness or satisfaction and intolerance. To carry out the simulation, a graphical interface is programmed in a Shiny application implemented in the statistical language R, making it reproducible and available on an OSF platform server at the following link: https://osf.io/ngm9h/.

Suggested Citation

  • Carrasco, Hugo & Abreo, Cindy & Álvarez-Vaz, Ramón Dr., 2025. "How moving costs Impact in Schelling’s Segregation Model : An extension to the original model," SocArXiv 2mkra_v1, Center for Open Science.
    • Handle: RePEc:osf:socarx:2mkra_v1
    DOI: 10.31219/osf.io/2mkra_v1
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    1. Richard Glennie, 2021. "Reproducible Research with R and RStudio (3rd Edition) by Christopher Gandrud," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 26(1), pages 128-129, March.
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