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Optimal Population Path Fitting for Flawed Vital Statistics and Censuses

Author

Listed:
  • Noël Bonneuil

    (Institut National d’Études Démographiques
    École des Hautes Études en Sciences Sociales)

  • Elena Fursa

    (Federal University of South Russia)

Abstract

A problem, often encountered in the analysis of historical data, is the difficulty in overcoming missing or flawed data. Lotka-McKendrick discrete demographic model, including migration, is combined with stochastic optimization to fit available censuses and vital statistics series to reconstruct missing population data, in the presence of one or two censuses. Simulations help to calibrate the method and determine error weights associated with each data series. An empirical case study is made using data from an administrative subdivision in southern Russia for the period 1863–1916.

Suggested Citation

  • Noël Bonneuil & Elena Fursa, 2011. "Optimal Population Path Fitting for Flawed Vital Statistics and Censuses," Journal of Optimization Theory and Applications, Springer, vol. 148(2), pages 301-317, February.
    • Handle: RePEc:spr:joptap:v:148:y:2011:i:2:d:10.1007_s10957-010-9756-4
    DOI: 10.1007/s10957-010-9756-4
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    References listed on IDEAS

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    1. repec:cai:popine:popu_p1998_53n1-2_0270 is not listed on IDEAS
    2. Salvatore Bertino & Eugenio Sonnino, 2003. "The stochastic inverse projection and the population of Velletri (1590-1870)," Mathematical Population Studies, Taylor & Francis Journals, vol. 10(1), pages 41-73.
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    Cited by:

    1. Noël Bonneuil & Elena Fursa, 2012. "Optimal Marriage Fitting for Imperfect Statistics," Journal of Optimization Theory and Applications, Springer, vol. 153(2), pages 532-545, May.

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