Abstract: Statisticians use data from different data sources for building statistical models, computing analyses and constructing forecasts. Based on their results, economic subjects (companies, government and households) make decisions. Better models lead to better decisions. One of the critical assumptions of excellent and valuable statistical models is the high quality of inputs – statistical data. Regardless of the data source type, the requirements for the quality of statistical data are the same.

The first part of the presentation introduces data quality requirements. It discusses the level of fulfilment of these requirements at several examples from different social and economic statistics (labour statistics, SILC, household budget survey, national accounts). The second part focuses on demographic issues with a particular accent on covid-19 statistics. How does the pressure on data timeliness influence other aspects of covid-19 data quality? The final part uses the Bayesian approach for the assessment of the covid-19 data relevance. Join presentation with Jakub Fischer and Tomáš Karel.