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This meeting was organized as part of the Conference of European Statisticians’ work programme for 2022, within the context of the High-Level Group for the Modernisation of Official Statistics. In particular, the expert meeting explored the following themes:
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| Provisional Programme | ||
| Information Notice 1 | ||
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Opening |
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Presentation on the UNECE High-Level Group for the Modernisation of Official Statistics Taeke Gjaltema |
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Session 1a: Modernisation of data editing and statistical production (Part 1)Session Organizers: Darren Gray (Statistics Canada) and Pedro Revilla (INE, Spain) |
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Multiple software systems for the editing and imputation process of the 7th General Census of Agriculture Simona Rosati |
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Towards a new integrated uniform production system for business statistics at Statistics Netherlands: quality indicators to guide top-down analysis Frank Aelen & Anita Vaasen-Otten |
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The SCIA system implementing Fellegi and Holt methodology compared to the recent R packages Simona Rosati |
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Towards a new integrated uniform production system for business statistics at Statistics Netherlands: automatic data editing with multiple data sources Wilco de Jong & Sander Scholtus |
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Keynote presentation |
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Robust imputation procedures in the presence of influential units in surveys David Haziza |
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Session 2: Lightning talksSession Organizer: Alexander Kowarik (Statistics Austria) |
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A modern statistical production process based on administrative registers Ewelina Wójcik |
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e-invoice time series nowcasting with R Bruno Lima |
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Session 3: New and emerging methodsSession Organizers: Simona Rosati (Istat, Italy) and Sander Scholtus (Statistics Netherlands) |
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Machine learning Imputation for Social Surveys – Random forest imputation of ONS’ Household Financial Survey Mark Edward |
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Application of the “SwissCheese” method for the imputation of partial non-response in the Survey on Income and Living Conditions Michael Leuenberger |
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Stacking machine-learning models for anomaly detection: comparing AnaCredit to other banking datasets Andrea del Monaco |
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Discover the hidden validation rules in your data with ‘validatesuggest’ Olav ten Bosch |
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Session 1b: Modernisation of data editing and statistical production (Part 2)Session Organizers: Simona Rosati (Istat, Italy) and David Salgado (INE, Spain) |
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Validation rule management Mark van der Loo |
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Banff’s next step: an open-source data editing system for advanced tools and collaboration Darren Gray |
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Growing a Modern Edit and Imputation System Darcy Miller & Megan Lipke |
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Automatic Data Editing and Imputation Experience in 2020 Mexican Census Edgar Vielma |
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Session 4: Machine Learning /Artificial Intelligence for editing and imputationSession Organizers: Alexander Kowarik (Statistics Austria) and Daniel Kilchmann (Federal Statistics Office, Switzerland) |
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Improving statistical data editing with Machine Learning: some use cases in Statistics Spain Sandra Barragán |
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Application of the MissForest algorithm for imputation in the Survey on Income and Living Conditions Blandine Bianchi |
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Robust regression, MissForest and calibration combined with non-linear optimization to impute VAT turnover Jacques Saliba |
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Univariate and multivariate goodness (of fit) of imputation Maria Thurow & Florian Dumpert |
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The imputation of the “Attained Level of Education” in the base register of individuals through Neural Networks using sampling weights Fabrizio De Fausti |
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Session 5: Use of administrative data for editing and imputationSession Organizers: Ágnes Andics (Central Statistical Office, Hungary) and Pedro Revilla (INE, Spain) |
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Data imputation for the purposes of statistical research with the use data from administrative registers Paweł Murawski |
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Producing admin-based property floor area statistics for England and Wales: methods, data and quality Stephan Tietz & Emily Mason-Apps |
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The use of administrative records for data imputation in Mexico's Economic Censuses José Luis Mercado Hernández |
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Session 6: QualitySession Organizers: Darren Gray (Statistics Canada) and Sander Scholtus (Statistics Netherlands) |
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Experimental Short-Term Statistics based on Data Imputation Methods Jan Ditscheid |
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Variance estimation for the mass imputation of the “Attained level of education” in the Italian Base Register of individuals: A comparison between analytical and MonteCarlo estimates Romina Filippini |
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Comparison between Clark and Kokic and Bell approaches in winsorization Romain Lesauvage |
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Automatic selective editing approach using machine learning: an application to VAT data Benjamin Vasquez |
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