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New perspectives for the quality of sub-municipal data with the Italian permanent population and housing census

  • Giancarlo Carbonetti
  • Stefano Daddi
  • Giampaolo De Matteis
  • Marco Di Zio
  • Davide Fardelli
  • Raffaele Ferrara
  • Fabio Lipizzi
  • Enrico Orsini

Over the years, official statistics have shown increasing attention to the territory in providing detailed and quality information and, in this sense, the Population and Housing Census has always guaranteed the availability of sub-municipal data useful for decision-making processes in the social, economic and environmental fields. The Istat modernization programme introduced the Permanent Census that, differently from the traditional decennial census essentially drew on collecting data from people, is strongly based on the integration of administrative and sample data, and planned for providing yearly statistical figures. This change requires new methodological and IT architectures. It is a revolution that – on the medium term – is expected to provide more stable and coherent figures at various territorial levels.In this framework, sub-municipal data derives from the integration of the Basic Register of Individuals and the Basic Register of Places. The quality of data depends on the quality of the Registers and the procedures adopted to integrate and elaborate input data. In this regard, Istat is working to improve the geocoding information and linkage procedures. One of the problem encountered is that of non-geocoded units. These are units without an allocation into an enumeration area because of problems in administrative data. Istat has studied a procedure integrating deterministic and probabilistic approaches for assigning the enumeration area to those critical units. An experimental study is carried out to evaluate the quality of the imputation procedure. In this paper, we discuss the approach adopted, the evaluation process, the results obtained and the impact on the quality of the data and the spatial analyses that can be carried out.

  • Keywords:
  • population census,
  • administrative data,
  • statistical registers,
  • geo-coding,
  • enumeration area,
  • missing data,
  • data quality,
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Giancarlo Carbonetti

ISTAT, Italian National Institute of Statistics, Italy - ORCID: 0000-0003-1073-9813

Stefano Daddi

ISTAT, Italian National Institute of Statistics, Italy

Giampaolo De Matteis

ISTAT, Italian National Institute of Statistics, Italy

Marco Di Zio

ISTAT, Italian National Institute of Statistics, Italy - ORCID: 0000-0002-6648-6934

Davide Fardelli

ISTAT, Italian National Institute of Statistics, Italy

Raffaele Ferrara

ISTAT, Italian National Institute of Statistics, Italy - ORCID: 0000-0001-7777-3835

Fabio Lipizzi

ISTAT, Italian National Institute of Statistics, Italy

Enrico Orsini

ISTAT, Italian National Institute of Statistics, Italy - ORCID: 0000-0002-3472-4344

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  • Publication Year: 2023
  • Pages: 113-118
  • Content License: CC BY 4.0
  • © 2023 Author(s)

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  • Publication Year: 2023
  • Content License: CC BY 4.0
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Chapter Information

Chapter Title

New perspectives for the quality of sub-municipal data with the Italian permanent population and housing census

Authors

Giancarlo Carbonetti, Stefano Daddi, Giampaolo De Matteis, Marco Di Zio, Davide Fardelli, Raffaele Ferrara, Fabio Lipizzi, Enrico Orsini

Language

English

DOI

10.36253/979-12-215-0106-3.20

Peer Reviewed

Publication Year

2023

Copyright Information

© 2023 Author(s)

Content License

CC BY 4.0

Metadata License

CC0 1.0

Bibliographic Information

Book Title

ASA 2022 Data-Driven Decision Making

Book Subtitle

Book of short papers

Editors

Enrico di Bella, Luigi Fabbris, Corrado Lagazio

Peer Reviewed

Publication Year

2023

Copyright Information

© 2023 Author(s)

Content License

CC BY 4.0

Metadata License

CC0 1.0

Publisher Name

Firenze University Press, Genova University Press

DOI

10.36253/979-12-215-0106-3

eISBN (pdf)

979-12-215-0106-3

eISBN (xml)

979-12-215-0107-0

Series Title

Proceedings e report

Series ISSN

2704-601X

Series E-ISSN

2704-5846

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