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Modeling the bias of digital data: an approach to combining digital and survey data to estimate and predict migration trends


  • Yuan Hsiao

    (Max Planck Institute for Demographic Research, Rostock, Germany)

  • Lee Fiorio
  • Jonathan Wakefield
  • Emilio Zagheni

    (Max Planck Institute for Demographic Research, Rostock, Germany)


No abstract is available for this item.

Suggested Citation

  • Yuan Hsiao & Lee Fiorio & Jonathan Wakefield & Emilio Zagheni, 2020. "Modeling the bias of digital data: an approach to combining digital and survey data to estimate and predict migration trends," MPIDR Working Papers WP-2020-019, Max Planck Institute for Demographic Research, Rostock, Germany.
  • Handle: RePEc:dem:wpaper:wp-2020-019
    DOI: 10.4054/MPIDR-WP-2020-019

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    References listed on IDEAS

    1. Håvard Rue & Sara Martino & Nicolas Chopin, 2009. "Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(2), pages 319-392, April.
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    More about this item


    USA; computational demography; digital demography; migration; migration measurement;
    All these keywords.

    JEL classification:

    • J1 - Labor and Demographic Economics - - Demographic Economics
    • Z0 - Other Special Topics - - General

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