1. Improvements in the UK EU-SILC
Matthew Minifie
Research Officer, Household Income and Expenditure Analysis

2. Presentation overview
Background to the status quo of UK household finance statistics (micro-level datasets)
Common sampling approach
Harmonisation of income questions on surveys
Editing and imputation processes
New derivation system
Lengthening of longitudinal panel
Future plans – administrative data, online data collection, additional sample

3. Household finance statistics in the UK (1/3)
Current uses:
SLC
Until 2016, follow-up survey to the Family Resources Survey (FRS) and used exclusively for producing longitudinal EU-SILC
From 2017, used to provide both cross-sectional and longitudinal EU-SILC
FRS
Until 2016, used to produce cross-sectional EU-SILC
Households Below Average Income (HBAI)
LCF
Household Disposable Income and Inequality (HDII) etins/householddisposableincomeandinequality/financialyearending2016
Effects of Taxes and Benefits (ETB) etins/theeffectsoftaxesandbenefitsonhouseholdincome/financialyearending2016
Nowcasting household income
WAS
Estimates of wealth and wealth inequality; Exposure to debt; attitudes to saving / debt; monitoring pensions up-take

4. Household finance statistics in the UK (2/3)
Living Costs & Food Survey (LCF)
Survey on Living Conditions (SLC)
Wealth and Assets Survey (WAS)
Unit: Survey sample of private households – representative of UK (WAS GB)
Mode: Face-to-face Computer Assisted Personal Interviewing
Sample: Stratified 2 stage sampling off PAF:
postcode sectors selected as primary sampling unit (PSU) - clusters
Addresses within sectors/clusters selected as secondary unit
Content: Income / tax (employment, property, investments, benefits, pensions)
Housing (accommodation, tenure, mortgages, costs (except WAS))
Economic status, occupation, industry, hours worked
Basic demographics, education, health
Pension contributions
Exclusive:
Detailed expenditure
Rotating module;
Longitudinal 6 waves (annual)
Detailed wealth & debt, financial planning;
Longitudinal (biennial)

5. Household finance statistics in the UK (3/3)
HBAI
Surveys
Outputs
LCF
SLC
FRS
Nowcasting, HDII, ETB
Longitudinal EU-SILC
X-SEC EU-SILC
Wealth in GB
WAS
Summary:
Lack of coherence: large number of sources and outputs so confusing for users
Lack of granularity: multiple surveys with varying sample sizes so currently unable to produce reliable estimates at lower levels of geography
Inefficient:
duplication of effort in data processing due to multiple sources and systems
reliance on expensive face-to-face surveys with falling response rates

6. The future – a new Household Finance Statistics (HFS) datatset
Surveys
Outputs
Benefits
Admin data Co r e
Expenditure
Income distribution / inequalities
Fully coherent income statistics
Increased quality income statistics at lower levels of geography (through larger sample/admin data)
Small core – options for electronic data collection
More efficient collection of data enabling improved timeliness
Capable of meeting wide range of user requirements
Wealth
Low income / poverty (inc. EU-SILC)
Material deprivation & EU SILC modules
Income, consumption & wealth
Micro-simulation models
Other policy needs

7. UK EU-SILC from 2017 (1/3)
2017 EU-SILC will be produced from the ‘combination’ of the Living Costs and Food Survey (LCF) and the Survey on Living Conditions (SLC) known as the Household Financial Statistics (HFS) dataset
In addition to producing EU-SILC, the HFS dataset will be used to create other income statistical outputs using common conceptions, definitions and derivation of household income

8. UK EU-SILC from 2017 (2/3)
Production of 2017 EU-SILC and UK Household Disposable Income and Inequality (HDII)
LCF
SLC W1
SLC W2
SLC W3
SLC W4
SLC W5
SLC W6 W6
Longitudinal EU-SILC W5 W5 W4 W4 W4
HDII and
cross-sectional
EU-SILC W3 W3 W3 W3 W2 W2 W2 W2 W2 W1 W1 W1 W1 W1 W1
Year
Y-5
Year
Y-4
Year
Y-3
Year
Y-2
Year
Y-1
Year Y
Year Y

9. UK EU-SILC from 2017 (3/3)
Production of 2017 EU-SILC and UK Household Disposable Income and Inequality (HDII)
Achieved sample size ~16,600 households
Can meet new NUTS2 precision requirements
Integrated cross-sectional and longitudinal EU-SILC
12 months collection to reduce seasonal effects
Increased alignment and coherence of national and EU- SILC household income statistics

10. Common sampling
Postcode sectors are the PSUs and sorted by various Census factors
PSUs selected jointly within each major stratum
Representative sample by region and month for combined sample as well as each component survey
Sample balanced monthly so can produce consistent rolling annual statistics
Transition to a common NUTS2 (and implicit Census) stratification for LCF and SLC
Joint selection of PSUs / clusters by region
Random allocation of PSUs to survey component (SLC or LCF)
Random selection of addresses

11. Harmonisation of survey questions (1/2)
Questions on material deprivation, work intensity and a few income components added to LCF
For 2017 income questions on LCF and SLC conceptually the same, but from 2018 income questions are the same
Numerous meetings and discussions between stakeholders
Question wording on other household surveys taken into account
Variables on relevant administrative data sources taken into account

12. Harmonisation of survey questions (2/2)
Approach taken:
Questionnaire comparison review
Identification of missing income concepts
Analysis of variables between surveys
Focus groups
Expert review by researchers
Discussion with users
Programming, testing and debugging
Guidance to interviewers
Interviewer feedback

13. Editing and imputation processes
Previously there were markedly different editing and imputation strategies implemented on data collected from the Living Costs and Food Survey (LCF) and the Survey on Living Conditions (SLC)
Review of editing and imputation procedures
Implementation of a monthly editing process
Improvements to imputation processing code
Early delivery of data to help prepare main imputation processing code
Larger donor pool for imputation

14. Improving the EU-SILC derivation program (1/2)
Numerous issues with pre-existing EU-SILC derivation code (e.g., inefficient, duplicate code for final and non-imputed data)
Aims:
Set up a system capable of deriving EU-SILC from combined LCF and SLC variables
Utilise macros to reduce length of code and increase efficiency
Have one section of code for producing imputation factors and income flags
Harmonise derivation of household income in EU-SILC and HDII and have a system capable of simultaneously producing EU-SILC and HDII

15. Improving the EU-SILC derivation program (2/2)

16. Increasing length of longitudinal panel
In 2017 a 5th wave was added to the SLC
In 2018 a 6th wave was added to the SLC
Adjustments made to sampling and field interviewing systems to accommodate the additional waves
Extensive testing to ensure rotation of information in the field interviewing systems worked
Increase the sample size available for deriving estimates of persistent poverty
Provides a longer time period for which to analyse transitions in household income and living conditions and the causes of these transitions

17. Future plans – incorporation of WAS
Work has commenced looking at including the Wealth and Assets Survey (WAS) into the HFS
WAS has adopted the same sampling strategy as LCF and SLC
WAS has adapted its questionnaire to take on many of the common income questions found in LCF and SLC
Work has started at looking how to incorporate WAS into the common imputation process used for LCF and SLC
WAS achieves ~10,000 household interviews a year and is also a longitudinal survey
WAS provides an insight into the link between household income and wealth

18. Future plans – administrative data (1/3 )
The UK is committed to making use of administrative data in the production of household income statistics
Administrative data could be utilised to improve sampling, monitor quality and shorten questionnaires by replacing questions and providing variables for direct use in the production of statistical outputs
Recent legislation, the Digital Economy Act, should act as an enabler

19. Future plans – administrative data (2/3)
We have visited the statistical agencies of Ireland, Italy and the Netherlands to learn how they utilise administrative data in their statistical outputs
ONS staff have been seconded to other government departments in possession of administrative data to gain knowledge of the data
Numerous data sources identified as being of use for production of income outputs
Negotiations under way with the relevant government departments in order to get data into ONS

20. Future plans – administrative data (3/3 )
Three important administrative data sources:
RTI
Real time information
Owned by Her Majesty’s Revenue and Customs (HMRC)
Contains information on employee pay and pension payments
Timely – uploaded 2 days after submission of information
Big data - ~ 65 million submissions per month SA
Self Assessment
Contains information on self-employed, foreign and investment income including high income earners (£100,000+ pa)
Time lag up to 10 months between income reference period and submission deadline
NBD
Owned by Department for Work and Pensions (DWP)
Contains information on a number of benefits including Job Seekers’ Allowance, Disability Living Allowance, State Pension)
Information at individual benefit claim level (including information on claimant, other household members, component of claim

21. Online data collection
ONS currently testing electronic data collection on a number of its surveys
Planned testing of online data collection for the Survey on Living Conditions (SLC) in 2019 – testing underway as to what information to collect and from which respondents
There is ongoing research into utilising a “digital diary” for the expenditure element of the Living Costs and Food Survey (LCF)
Ongoing engagement with research community on potential and impact of online data collection

22. Summary (1/2)
Cross-sectional sample size of EU-SILC has been increased significantly due to the Household Financial Statistics (HFS) transformation programme
Large sample size of HFS to satisfy national and regional precision requirements
A harmonised core of income questions has been adopted on different household social surveys
A common sampling strategy has been introduced for survey components feeding the HFS

23. Summary (2/2) Increased duration of longitudinal element of HFS
Harmonisation of concepts and derivation of household income in EU-SILC and domestic outputs
HFS to be used for income statistical outputs, including EU-SILC, which will improve coherency
Aim to use administrative data in the near future for improving the sampling design, question replacement and quality assurance purposes
Testing the potential for online data collection for household financial information

24. Any questions?