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Population Size Estimation Using Multiple Incomplete Lists with Overcoverage

Author

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  • Di Cecco Davide
  • Di Zio Marco
  • Filipponi Danila
  • Rocchetti Irene

    (Italian National Statistical Institute, via Cesare Balbo 16, Rome00184, Italy.)

Abstract

The quantity and quality of administrative information available to National Statistical Institutes have been constantly increasing over the past several years. However, different sources of administrative data are not expected to each have the same population coverage, so that estimating the true population size from the collective set of data poses several methodological challenges that set the problem apart from a classical capture-recapture setting. In this article, we consider two specific aspects of this problem: (1) misclassification of the units, leading to lists with both overcoverage and undercoverage; and (2) lists focusing on a specific subpopulation, leaving a proportion of the population with null probability of being captured. We propose an approach to this problem that employs a class of capturerecapture methods based on Latent Class models. We assess the proposed approach via a simulation study, then apply the method to five sources of empirical data to estimate the number of active local units of Italian enterprises in 2011.

Suggested Citation

  • Di Cecco Davide & Di Zio Marco & Filipponi Danila & Rocchetti Irene, 2018. "Population Size Estimation Using Multiple Incomplete Lists with Overcoverage," Journal of Official Statistics, Sciendo, vol. 34(2), pages 557-572, June.
  • Handle: RePEc:vrs:offsta:v:34:y:2018:i:2:p:557-572:n:14
    DOI: 10.2478/jos-2018-0026
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    References listed on IDEAS

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    1. Elena Stanghellini & Peter G. M. van der Heijden, 2004. "A Multiple-Record Systems Estimation Method that Takes Observed and Unobserved Heterogeneity into Account," Biometrics, The International Biometric Society, vol. 60(2), pages 510-516, June.
    2. Shirley Pledger, 2000. "Unified Maximum Likelihood Estimates for Closed Capture–Recapture Models Using Mixtures," Biometrics, The International Biometric Society, vol. 56(2), pages 434-442, June.
    3. Francesco Bartolucci & Antonio Forcina, 2001. "Analysis of Capture-Recapture Data with a Rasch-Type Model Allowing for Conditional Dependence and Multidimensionality," Biometrics, The International Biometric Society, vol. 57(3), pages 714-719, September.
    4. Li‐Chun Zhang, 2012. "Topics of statistical theory for register‐based statistics and data integration," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 66(1), pages 41-63, February.
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    Cited by:

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    2. Zhang Li-Chun, 2019. "A Note on Dual System Population Size Estimator," Journal of Official Statistics, Sciendo, vol. 35(1), pages 279-283, March.
    3. Ton de Waal & Arnout van Delden & Sander Scholtus, 2020. "Multi‐source Statistics: Basic Situations and Methods," International Statistical Review, International Statistical Institute, vol. 88(1), pages 203-228, April.

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