Measuring the Accuracy of Aggregates Computed from a Statistical Register

Alleva, Giorgio; Falorsi, Piero Demetrio; Petrarca, Francesca; Righi, Paolo

doi:10.2478/jos-2021-0021

Cited by 3 publications

(1 citation statement)

References 22 publications

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“…In general, imputation has been performed by using a combination of different methods, which have been applied to distinct groups of related variables, taking into account their distributional characteristics, their relationships with other variables, and exploiting all the available administrative information (Di Zio et al 2016). It is worthwhile to note that measuring the additional uncertainty on register outputs due to imputation is still an issue under study at Istat (Di Zio et al 2017;Alleva et al 2021).…”

Section: The Statistical Register For Structural Business Statistics ...mentioning

confidence: 99%

Total Process Error: An Approach for Assessing and Monitoring the Quality of Multisource Processes

Rocci

Varriale

Luzi

2022

Journal of Official Statistics

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Most National Statistical Institutes are progressively moving from traditional production models to new strategies based on the combined use of different sources of information, which can be both primary and secondary. In this article, we propose a framework for assessing the quality of multisource processes, such as statistical registers. The final aim is to develop a tool supporting decisions about the process design and its monitoring, and to provide quality measures of the whole production. The starting point is the adaptation of the life-cycle paradigm, that results in a three-phases framework described in recent literature. An evolution of this model is proposed, focusing on the first two phases of the life-cycle, to better represent the source integration/combination phase, that can vary accordingly to the features of different types of processes. The proposed enhancement would improve the existing quality framework to support the evaluation of different multisource processes. An application of the proposed framework to two Istat (Italian national statistical institute) registers in the economic area taken as case studies is presented. These experiences show the potentials of such tool in supporting National Statistical Institutes in assessing multisource statistical production processes.

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Section: The Statistical Register For Structural Business Statistics ...mentioning

confidence: 99%

Total Process Error: An Approach for Assessing and Monitoring the Quality of Multisource Processes

Rocci

Varriale

Luzi

2022

Journal of Official Statistics

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Methodological, technological and design challenges in the new multisource statistics ecosystem

Alleva¹,

Baldacci²,

Falorsi³

2021

SJI

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We are experiencing noteworthy changes in our societies, related to the impact of health and safety in the post-COVID19 pandemic; globalization; digital technologies; on the perimeter, organization and performances of companies; and climate change, including on ecosystems and biodiversity. In this paper, we present future challenges and developments of statistics and official statistics along four main axes: data, capabilities to manage data, methods, and data governance. Nobody can address alone the new challenges of the information society. Partnerships among official statistics, academia, public and private researches, and users, are fundamental. It is necessary to adopt a strategy and a coherent plan of action at the global level to support the modernization of official statistics to answer societal challenges.

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Estimation models used in 2021 Permanent Population Census: Current activity status, Occupation, Industry and Status in employment.

CHIANELLA,

CICCAGLIONI,

ERCOLANI

2024

SIEDS

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Every year, Istat is involved in Census estimates production, which is obtained by integrating sample data with information from administrative sources. As regards the production of labour estimates, Istat produces Current activity status estimates for Italian dissemination. In 2023, in addition to these estimates, to comply with EU regulations, referred to the year 2021, estimates for Occupation, Industry and Status in employment were also produced. The estimation process for Employed/Not Employed is already well documented. For this reason, the procedure for estimating the Unemployed and Outside the labour force (students, retired people, housewives, other) and the variables related to Occupation, Industry and Status in employment will be here described. The estimates of these variables were produced at municipal level. The estimation models were implemented in R software through the ‘multinom’ function included in the ‘nnet’ package which allows to fit multinomial log-linear models using neural networks. The article aims to describe the different estimation models and the procedures used for choosing and defining the auxiliary variables included in the models. The administrative sources used were mainly social welfare and income sources and they allowed to identify ‘work signs’ of each individual.

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Measuring the Accuracy of Aggregates Computed from a Statistical Register

Cited by 3 publications

References 22 publications

Total Process Error: An Approach for Assessing and Monitoring the Quality of Multisource Processes

Total Process Error: An Approach for Assessing and Monitoring the Quality of Multisource Processes

Methodological, technological and design challenges in the new multisource statistics ecosystem

Estimation models used in 2021 Permanent Population Census: Current activity status, Occupation, Industry and Status in employment.

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