1. Fast-track data project Current status |Future steps | Lessons learned Wenke Apt

2. 31 May 2013 Deadline for reports to the Coordinating Team 3 June 2013 Meeting in Berlin 15 July 2013 Draft from the Coordinating Team to the Partners 9 August 2013 Deadline for comments 30 August 2013 Submission Timeline

3. Participation  11 of the total 14 JPI member states: o Austria, Belgium, Denmark, Finland, France, Germany, Italy, the Netherlands, Spain, Sweden, and the United Kingdom o Plus Croatia with a JPI observer status.  The Scientific Working Group is led by James W. Vaupel, Director of the Max Planck Institute for Demographic Research and member of the JPI Scientific Advisory Board.  Professor McNair advises the group and represents the liaison to the main JPI MYBL governing bodies.

4. Link of data project to JPI’s Strategic Research Agenda  The fast-track data project operates within the broad scope of the Strategic Research Agenda (SRA)  It informs the drafting of the SRA, and help clarify whether there are major data issues which need inclusion in the SRA itself.  The main focus is on data relevant to people over 50.  In this, it takes into account the fact that the life chances of people after 50 are often determined by factors much earlier in the life course, and that such data is of critical importance.

5. Rationale of having a fast-track activity now  Primary purpose is to help improve the quality and relevance of data, and knowledge about data sources among scientists and policymakers.  The reason for prioritising the data issue is that it can improve the relevance and effectiveness of both the SRA itself, and of research proposals which may be made in the light of the SRA.  This issue was identified as a priority by the FUTURAGE project:  “Policy must be based on the best scientific evidence derived from sound data and information, and relevant research.” (p. 11)

6. Purpose of the fast-track data project  The purpose of the project is not about creating new databases.  Rather it seeks to “map” the range of data sources available on ageing, at European, national and more local level: o Describe what data is available at local, national and European level to address the broad policy questions outlined above; o Examine whether there are major gaps in the data available; o Influence those collecting data (i.e. national statistical agencies, NGOs and academia) to use more appropriate models; o Inform researchers and policymakers about the full range of potential data sources, as well as their strengths, limitations, and comparability.

7. Guiding research question the fast-track data project The central issue is:  How can we understand, and improve, the quality of life, and the social and economic contribution of people over the age of 50? There are two, related problems:  Data is often collected in different forms, with inconsistent sampling  Policymakers and scientists often unaware of possible data sources

8. Aspired output of the fast-track activity A "map" of data sources relevant to the study of demographic change as it affects people over the age of 50, bearing in mind a life course perspective. This will be a document in three parts:  An overview and critical analysis of the data available  A detailed list of sources, at national and European levels, describing their key features, strengths and limitation  Recommendations to government, scientific and data agencies on how to improve the quality, comparability, relevance and accessibility  This “map” would provide policymakers and scientists with a comprehensive overview of where to find appropriate data for interdisciplinary and cross-policy research.

9. Audience of the output The audience for the project output will be:  JPI Scientific Advisory Board  JPI General Assembly  Participating national bodies  National and European data agencies  National and European governments and policy agencies  Researchers interested in demographic change and its policy implications

10. 1.Health and performance 2.Social systems and welfare 3.Work and productivity 4.Education and learning 5.Housing, urban development and mobility 6.Public attitudes towards old age 7.Social, civic and cultural engagement 8.Uses of technology 9.Wellbeing 10.Intergenerational relationships Thematic areas of data

11.  Covered data sources should be of high quality, quantitative (only qualitative data if important and nothing else is available), be derived from big data sets, recent, and if possible longitudinal, and policy-relevant.  Where no data was available, or where data was limited of doubtful quality, this should be noted. It may indicate the need for further research, or to changes in routine data collection.  Data sources include registry data, regular surveys, occasional surveys, longitudinal surveys, and qualitative evidence.  The main section of reports deals with statistical data relevant to policymakers. Another smaller section addresses evidence on policies and provide issue-specific information about where to find information about national policies. Data selection

13.  On average five data sources on main topics  On average three data sources on cross-cutting topics Coverage  Underrepresented (or missing) groups: o Population with disabilities o Population with immigrant background o Institutionalised population  Limited geographical scope Temporary framework  Microdata not yet published  Outdated Linkage and data quality  Lost information due to anonymisation Status and challenges of data evaluation

14. Wellbeing – Necessary to establish agreement about the definition and measurement. Relevant data is scattered over a range of sources Education and learning – The most underdeveloped area. In most countries the only available data concerns formal courses in educational institutions, which is a tiny proportion of relevant activity. Attitudes to age – Policymakers need to understand how age is viewed by the general population, and how older people view themselves and the world. There are no consistent measures and data of age discrimination, or of how open older people are to the kinds of policy change, which are likely to happen (pensions, retirement ages etc..). Input for the SRA New and underdeveloped fields

15. Current data misses key groups, including:  The very old – living conditions, preferences, wellbeing and quality of life.  Those living in residential institutions – A high proportion of older people, missed by many surveys.  Migrants – Different migrant groups may have very different characteristics and circumstances, which means very small sample sizes. Also important to understand internal migration within the EU (e.g. movement of people from North to South on retirement, recruitment of care workforce for the West from Eastern Europe)  Highest and lowest socio-economic status groups – To be addressed by weighting data? Input for the SRA Missing data

16. Multiple levels of data collection and policy accountability. National, regional and local data often not joined up Frequency of data collection. In a rapidly changing world published data is often out of date, and data collection systems can be slow to pick up new issues like information technology or social media. Population sizes for surveys. Small countries have difficulty generating appropriate sample sizes Relative importance of self-reporting vs. objective reporting. Subjective indicators (e.g. on health or wellbeing) may not correlate with the objective factors we expect. Objective factors may be inadequate proxies for wellbeing. Input for the SRA Other problems

17.  Development of an online upload tool o Upload o Editing o First step for a repository o Exchange www.demogr.mpg.de/go/jpi Data Map Interface: Current status

23. 31 May 2013 Deadline for reports to the Coordinating Team 3 June 2013 Meeting in Berlin 15 July 2013 Draft from the Coordinating Team to the Partners 9 August 2013 Deadline for comments 30 August 2013 Submission Timeline

24. Thank you.