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Synthetic populations: review of the different approaches

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  • BARTHELEMY Johan
  • CORNELIS Eric

Abstract

Microsimulations may involve a large number of agents. It is then practically impossible or too expensive to obtain a fully and complete disaggregated data set about these agents of interest. Moreover, if such a dataset was available, its use would be potentially problematic in view of stringent privacy laws. To address this problem one may build an artificial population starting from known aggregate data. Most of the known generation methods are explained in this paper. Their advantages and limitations are discussed and references are given for further details.

Suggested Citation

  • BARTHELEMY Johan & CORNELIS Eric, 2012. "Synthetic populations: review of the different approaches," LISER Working Paper Series 2012-18, Luxembourg Institute of Socio-Economic Research (LISER).
    • Handle: RePEc:irs:cepswp:2012-18
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    References listed on IDEAS

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    1. Beckman, Richard J. & Baggerly, Keith A. & McKay, Michael D., 1996. "Creating synthetic baseline populations," Transportation Research Part A: Policy and Practice, Elsevier, vol. 30(6), pages 415-429, November.
    2. Ann Harding & Rachel Lloyd & Anthea Bill & Anthony King, 2004. "Assessing Poverty and Inequality at a Detailed Regional Level: New Advances in Spatial Microsimulation," WIDER Working Paper Series RP2004-26, World Institute for Development Economic Research (UNU-WIDER).
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    Keywords

    transport simulation; micro simulation; iterative proportional fitting procedures; optimization;
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