Family Resources Survey

1. Family Resources Survey Data Linking Jo Cockerham

2. Overview • Background • Uses of linked data • Development of consent question • Methodology • Match rates • Results from linked 2006/07 data • Future projects • Questions?

3. The Family Resources Survey • Launched in 1992 by DWP • 26,000 private households in UK (about 24,000 in GB) • Detailed information on incomes and benefit receipt, tenure and housing costs, savings • Fieldwork carried out by ONS and NatCen

4. Background to data linking work • 2004 Strategic Review of FRS • Problems with take-up statistics • Improvements to administrative data • New FRS contract from April 2006

5. Intended uses of linked data • Statistical and research purposes only • Improve the quality of FRS data • Longitudinal analyses – tracking how different groups move in and out of work and how their situation changes over time • Initially to only be made available internally at DWP and to selected HMRC analysts • Will not be used for operational purposes, such as fraud detection

6. Informed consent • Requires informed consent of respondent (Data Protection Act 1998) • Personal details need to be passed to DWP for linking (name, address, sex, date of birth – and NINO pre 2008) • Pilot study took place in 2006 • Developed consent question which was introduced in November 2006

7. Features of 2006 consent question • Asked at end of questionnaire • Separate block to collect full name, address, NINO, date of birth • Written consent forms • Detailed wording • Proxy consent packs

8. Consent in 2006/07 FRS • Consent lower than anticipated • 40 - 45 per cent for personal interviews • Approx 35 per cent including proxies • Known biases: • Consent rate lower among ethnic minorities • Consent falls slightly as age increases • Employees have higher consent than self-employed

9. Development of new consent question • Question suspended from August 2007 • Resources diverted to development of improved question • Qualitative pilot October 2007 • Quantitative pilot in January 2008

10. Qualitative pilot • 30 in-depth interviews with respondents: split into 3 samples • Concluded that question needed to be simplified, more informal and required further clarification in the wording • Interviewer focus groups • Findings consistent with respondent interviews

11. Quantitative pilot Conducted in January 2008 main stage sample (1900 individuals) To test: • Achieved consent rate • Simplified version of the question • Removal of paper consent forms • Improved survey materials • Removal of NINO/collection of personal details as part of main questionnaire

12. 2008 pilot results • Consent rate rose to 62% • No bias between sub-groups • Leaflet received positive response • No difference between DWP and ONS consent • New question introduced from April 2008

13. Administrative data held by DWP • Despite low consent rate, useful analyses can be carried out. • The FRS has been linked to the Work and Pensions Longitudinal Study (WPLS). • 500 million lines of data covering: • benefit claims • employment spells • annual earnings • savings • tax credits • pensions • operational data on customers activities (e.g. participation in back to work programmes).

14. FRS DATA F R S I D Personal Details FRS DATA – Dataset 1 F R S I D F R S I D Personal Details – Dataset 2 Imputation, editing and DV creation on full FRS. F R S I D Personal Details O R C I D FRS DATA - full release to users as in previous years Forward consenting cases to Data Matching team in DWP F R S I D O R C I D FRS DATA – for those giving consent to link F R S I D O R C I D FRS DATA O R C I D FRS DATA O R C I D WPLS

15. Matching methodology • “Traffic lights” system • Staged approach by NINO, then surname (soundex), initial of forename, DoB, gender and postcode sector

16. Matching methodology • Where match for NINO is not available, fuzzy matching by surname (soundex), initial of forename, DoB, gender and postcode sector

17. Matching Rates 2006/07 data

18. Results from Linked Data: Savings • Savings/assets data on FRS criticised as unreliable i.e. underestimates people’s savings. • This can impact on high profile National Statistics. For example, figures on Pension Credit Take-Up. • Work carried out to assess the level of any under-reporting, compared the FRS to the HMRC data. • Several caveats: • sample size small • HMRC data covers fewer savings products than the FRS • HMRC data only available to 2004/5.

19. Savings Data • Table below shows the comparison of the FRS measure with the FRS/HMRC measure of total capital • HMRC figure is calculated using combination of FRS assets plus HMRC assets • Where an HMRC account exists, they have higher/larger amounts in them Note: These figures are unpublished and should not be reproduced or quoted

20. Comparison of benefits • Only compared benefit spells which were live at the time of interview. • 10 key benefits were examined.

21. Numbersclaiming benefits

22. Comparison of WPLS with FRS

23. Comparison of Benefit Amounts Note: These figures are unpublished and should not be reproduced or quoted

24. Future Project Proposals • Investigating how benefits analysis may improve FRS validation • Rematch the data without using NINO to compare the quality of the match with/without NINO • Investigating how benefit mis-reporting affects total household income • Linking FRS earnings data to investigate how people are living on reported zero or low incomes • Comparison of FRS employment outcomes to data derived from P45 information

25. Questions ????