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DOMICILE 1.0: An Agent-Based Simulation Model for Population Estimates at the Domicile Level

  • Cameron S. Griffith
  • David A. Swanson
  • Michael Knight
Chapter
Part of the Applied Demography Series book series (ADS, volume 2)

Abstract

Agent-Based Models (ABMs) collectively represent an individual modeling method that, along with two related approaches, Microsimulation (MSM) and Cellular Automata (CA, also known as Artificial Neural Networks or ANN), has received attention as a demographic forecasting tool in the past 20 or so years (see, e.g., Andreassen 1993; Bandyopadhyay and Chattopadhyay 2006; Billari and Prskawetz 2003; Booth 2006; Charette 2010; Clarke and Holm 1987; Harding and Gupta 2007; Martel 2010; Sokolova et al. 2006; Van der Gaag et al. 2005; Zinn et al. 2010). This development corresponds to observations made by Smith et al. (2001: 367) that while population projections were primarily made at the national and state levels until the 1970s, they started being routinely made for lower levels of geography such as census tracts and block groups, which, in turn, generated demand for even lower levels of geography such as tax assessor files, block faces, and street segments. They observed that this trend implied that projections would eventually be made for individual addresses, households, and people. Indeed, this observation has been borne out and the reason is largely due to the development of individual ­modeling methods, including ABM.

Keywords

Infant Mortality Person Agent Street Segment Block Group Population Projection 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  • Cameron S. Griffith
    • 1
  • David A. Swanson
    • 2
  • Michael Knight
    • 3
  1. 1.Department of Sociology, Anthropology, and Social WorkCentral Michigan UniversityMt. PleasantUSA
  2. 2.Blakely Center for Sustainable Suburban Development and Department of SociologyUniversity of CaliforniaRiversideUSA
  3. 3.3rdWave ResearchVeronaUSA

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