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Population Size Estimation and Linkage Errors: the Multiple Lists Case

Author

Listed:
  • Di Consiglio Loredana

    (Italian National Institute of Statistics (Istat), via Balbo 16, 00184Roma, Italy.)

  • Tuoto Tiziana

    (Italian National Institute of Statistics (Istat), via Balbo 16, 00184Roma, Italy.)

Abstract

Data integration is now common practice in official statistics and involves an increasing number of sources. When using multiple sources, an objective is to assess the unknown size of the population. To this aim, capture-recapture methods are applied. Standard capture-recapture methods are based on a number of strong assumptions, including the absence of errors in the integration procedures. However, in particular when the integrated sources were not originally collected for statistical purposes, this assumption is unlikely and linkage errors (false links and missing links) may occur. In this article, the problem of adjusting population estimates in the presence of linkage errors in multiple lists is tackled; under homogeneous linkage error probabilities assumption, a solution is proposed in a realistic and practical scenario of multiple lists linkage procedure.

Suggested Citation

  • Di Consiglio Loredana & Tuoto Tiziana, 2018. "Population Size Estimation and Linkage Errors: the Multiple Lists Case," Journal of Official Statistics, Sciendo, vol. 34(4), pages 889-908, December.
    • Handle: RePEc:vrs:offsta:v:34:y:2018:i:4:p:889-908:n:5
    DOI: 10.2478/jos-2018-0044
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    References listed on IDEAS

    as
    1. Alessio Farcomeni & Luca Tardella, 2010. "Reference Bayesian methods for recapture models with heterogeneity," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 19(1), pages 187-208, May.
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