Improvements in the UK EU-SILC Matthew Minifie Research Officer, Household Income and Expenditure Analysis E-mail: HIE@ons.gov.uk

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

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) https://www.gov.uk/government/statistics/households-below-average-income-199495-to-201516 LCF Household Disposable Income and Inequality (HDII) https://www.ons.gov.uk/peoplepopulationandcommunity/personalandhouseholdfinances/incomeandwealth/bull etins/householddisposableincomeandinequality/financialyearending2016 Effects of Taxes and Benefits (ETB) https://www.ons.gov.uk/peoplepopulationandcommunity/personalandhouseholdfinances/incomeandwealth/bull etins/theeffectsoftaxesandbenefitsonhouseholdincome/financialyearending2016 Nowcasting household income https://www.ons.gov.uk/peoplepopulationandcommunity/personalandhouseholdfinances/incomeandwealth/bulletins/nowcastinghouseholdincomeintheuk/financialyearending2017 WAS Estimates of wealth and wealth inequality; Exposure to debt; attitudes to saving / debt; monitoring pensions up-take

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)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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