- ASA 2021 Statistics and Information Systems for Policy Evaluation
- A cura di Bruno Bertaccini, Luigi Fabbris, Alessandra Petrucci
Total Process Error framework: an application to economic statistical registers
- Roberta Varriale
- Fabiana Rocci
- Orietta Luzi
- © 2021 Author(s) |
- CC BY 4.0
- DOI: 10.36253/978-88-5518-461-8.28
In recent years, the Italian national institute of statistics (Istat), together with most National Statistical Institutes, is progressively moving from traditional production models based on the use of primary source of information - represented by direct surveys - to new production strategies based on the combined use of different primary and secondary sources of information. As result, new multisource statistical processes have been built, that guarantee a major improvement of both amount and quality of information about several phenomena of public interest. In this context, the Total Process Error (TPE) framework has been recently proposed in literature for assessing the quality of multisource processes. The TPE framework represents an evolution of the Zhang’s two-phase life-cycle approach and it additionally includes an operational tool to connect the steps of the multisource production process to the phases of the quality evaluation framework. TPE framework can be used both to support a multisource process design and to monitor an entire production process, in order to provide key elements to assess the quality of both the processes and their statistical outputs. In the present work, we describe as a case study in the new context of Istat production of official statistics the use of the TPE framework to support the process design of the Register for Public Administrations.
- Keywords:
- quality assessment,
- total error,
- multisource processes,
- statistical registers,
ISTAT, Italian National Institute of Statistics, Italy
ISTAT, Italian National Institute of Statistics, Italy
ISTAT, Italian National Institute of Statistics, Italy
- AA.VV. (2014). Memobust Handbook on Methodology of Modern Business Statistics. Available at: https://ec.europa.eu/eurostat/cros/system/files/Memobust%20glossary%20def.pdf.
- Rocci F., Varriale R., Luzi O. (2022). Total process error: An approach for assessing and monitoring the quality of multisource processes. Forthcoming in Journal of Official Statistics, June 2022.
- Wallgren, A. and B. Wallgren. (2014). Register based statistics: Administrative data for statistical purposes. John Wiley & Sons, Ltd.
- Zhang, L.C. 2012. Topics of statistical theory for register-based statistics and data integration. Statistica Neerlandica, 66 (1), pp. 41-63.
Informazioni sul capitolo
Titolo del capitolo
Total Process Error framework: an application to economic statistical registers
Autori
Roberta Varriale, Fabiana Rocci, Orietta Luzi
Lingua
English
DOI
10.36253/978-88-5518-461-8.28
Opera sottoposta a peer review
Anno di pubblicazione
2021
Copyright
© 2021 Author(s)
Licenza d'uso
Licenza dei metadati
Informazioni bibliografiche
Titolo del libro
ASA 2021 Statistics and Information Systems for Policy Evaluation
Sottotitolo del libro
BOOK OF SHORT PAPERS of the on-site conference
Curatori
Bruno Bertaccini, Luigi Fabbris, Alessandra Petrucci
Opera sottoposta a peer review
Anno di pubblicazione
2021
Copyright
© 2021 Author(s)
Licenza d'uso
Licenza dei metadati
Editore
Firenze University Press
DOI
10.36253/978-88-5518-461-8
eISBN (pdf)
978-88-5518-461-8
eISBN (xml)
978-88-5518-462-5
Collana
Proceedings e report
ISSN della collana
2704-601X
e-ISSN della collana
2704-5846