3.4 Modernisation of Social Statistics DSS Meeting 4-5 March 2013

Background Drivers General approach Efficiency gains Increased responsiveness General approach Removal of obstacles Facilitation of common developments

Integrated system of micro-datasets Core activity: high potential for efficiency gains Reduction of demands in terms of data precision, joint distributions and frequencies Preparation for suitability of web-based questionnaires Preparation for substitution of parts of the data collection by administrative data Aim: from a set of separate surveys to a system of interlinked micro-datasets

Integrated system of micro-datasets: key elements Modularity: Subject matter expertise  Involvement of specialised working groups Multi-purpose (core modules, common standardised modules) Issues: Coherence in terms of terminology and granularity Forward looking perspective Modularisation criteria Re-use of data: Combining results of different surveys Boost in accuracy or opportunity to reduce sample size Issue: Methodological challenges Targeted design: Shorter micro-datasets:  higher response rates, suitability for web questionnaires Larger number of micro-datasets: more flexible joint distributions Issue: Critical review of user needs in terms of joint distributions and their associated requirements in terms of frequency and precision

Integrated system of micro-datasets: key elements Multi-source nature Surveys combined with administrative data Common reference implementation: Mandatory data specification Recommended organisation of the system Programming: Common programming  role of DSS In line with EPSS

Integrated system of micro-datasets : next steps For DSS in October 2013: Outcome of the modularisation Developing concrete scenarios for integration (illustrating potential gains) Developing pilots for testing at national level Legislative issues Roadmap for development

Statistical data matching Ex post matching faces several challenges Opportunities arise from statistical matching that is planned ex ante Statistical matching as a complement to a system of interlinked micro-datasets Indicators based on an extensive battery of questions Simplified module with high predictive power and stand-alone capacity Toolbox of methods

Multi-mode data collection /web questionnaires Drivers Reduced cost of data collection Reduced burden on respondents Growing potential in a context in which the web is increasingly used for contracts with authorities, banking, commerce ESSnet DCSS (Data collection for social surveys using multiple modes) Methodological guidance Possibilities of sharing tools / common developments Design of the data collection, sampling and estimation process in a mixed mode environment

Standardisation of variables and modules Efficiency gains Data collection (modularisation of surveys) Data processing and estimation (matching, linking, data imputation) Dissemination Core Social Variables and beyond More variables and modules Deeper standardisation of definitions and breakdowns Not compulsory in all surveys

Multisource statistics / Use of administrative data sources Drivers Reduced cost of data collection Reduced burden on respondents Re-use of information ESS.VIP Admin (Administrative Data Sources) Common approaches to tackle risks Strategic workshop Steering Group to be put in place

ESS.VIP Admin – Strategic Workshop Key topics Development of a quality framework Quality of input and metadata Common concepts Data linkage Imputations and estimation Role of NSIs in administrative data collection process Confidentiality and data protection EU legislation Sharing best practices Financial resources Commercial data