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Spatially Balanced Indirect Sampling to Estimate the Coverage of the Agricultural Census

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Studies in Theoretical and Applied Statistics (SIS 2021)

Part of the book series: Springer Proceedings in Mathematics & Statistics ((PROMS,volume 406))

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Abstract

Coverage error in censuses has become an important statistical issue. In this paper we address the design of the coverage survey of the agricultural census through the use of spatially balanced sampling designs and the employment of indirect sampling framework. Spatially balanced sampling exploits the spatial component of the target population, while indirect sampling is taken into account since a frame linked to the target population is assumed to be used. Following the case of the coverage survey of the agricultural census performed by ISTAT in Italy in 2010, some proposals are presented and their efficiency investigated by means of Monte Carlo simulations. Finally, variance estimation is studied.

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Acknowledgements

Federica Piersimoni’s work represents her views and does not necessarily reflect those of ISTAT. This work has been presented at the Advisory Committee on Statistical Methods of ISTAT on 12 January 2021.

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Authors and Affiliations

  1. Directorate for Methodology and Statistical Process Design, Istat, Rome, Italy

    Federica Piersimoni

  2. Department of Social Statistics and Demography, University of Southampton, Southampton, UK

    Francesco Pantalone

  3. Department of Economic Studies, “G. d’Annunzio” University, Pescara, Italy

    Roberto Benedetti

Authors
  1. Federica Piersimoni
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  2. Francesco Pantalone
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  3. Roberto Benedetti
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Corresponding author

Correspondence to Federica Piersimoni .

Editor information

Editors and Affiliations

  1. Department of Economics and Management, University of Pisa, Pisa, Italy

    Nicola Salvati

  2. Department of Economics and Statistics, University of Salerno, Fisciano, Salerno, Italy

    Cira Perna

  3. Department of Economics and Management, University of Pisa, Pisa, Italy

    Stefano Marchetti

  4. School of Mathematics and Applied Statistics, University of Wollongong, Wollongong, NSW, Australia

    Raymond Chambers

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Piersimoni, F., Pantalone, F., Benedetti, R. (2022). Spatially Balanced Indirect Sampling to Estimate the Coverage of the Agricultural Census. In: Salvati, N., Perna, C., Marchetti, S., Chambers, R. (eds) Studies in Theoretical and Applied Statistics . SIS 2021. Springer Proceedings in Mathematics & Statistics, vol 406. Springer, Cham. https://doi.org/10.1007/978-3-031-16609-9_27

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