Multi-source data for labour statistics |
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| Coordinator 1 | Professor Roberta Varriale (Sapienza University of Rome) |
In recent years, labour market researchers and National Statistical Institutes involved in producing labour market statistics have increasingly adopted the use of multiple data sources. In addition to survey data, representing a traditional and primary source of information, register data from various sources has become extensively utilized in labour market research and, to some extent, in the production of official statistics.
A novel and promising development in this field is the production of multi-source statistics, achieved by linking information from various independent data sources. This approach offers numerous opportunities, as it combines the strengths of different frameworks: the extensive and detailed objective information provided by register data and the substantively valuable subjective insights obtained through surveys.
From a methodological perspective, linking multiple data sources presents the opportunity to address several aspects of data quality. By drawing on multiple sources of information, it is possible to enhance final estimates both in terms of content and accuracy. Nevertheless, this approach also introduces new methodological challenges.
In this session, we aim to present a range of statistical methods for handling multi-source data, accompanied by examples of results obtained using these methods to demonstrate the advantages of multi-source statistics. In particular, we will highlight the use of latent variable models, which leverage the simultaneous availability of information from multiple sources. This approach offers the benefit of accounting for potential measurement errors in each individual source. The application context for these methods is labour statistics.