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

Author

Listed:
  • Yuan Hsiao

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

  • Lee Fiorio
  • Jonathan Wakefield
  • Emilio Zagheni

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

Abstract

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

    as
    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

    Keywords

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

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