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Maximising Registration and IER Charlotte Snelling Social Researcher, Customer Registration Team, Constitution Group, Cabinet Office.

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Presentation on theme: "Maximising Registration and IER Charlotte Snelling Social Researcher, Customer Registration Team, Constitution Group, Cabinet Office."— Presentation transcript:

1 Maximising Registration and IER Charlotte Snelling Social Researcher, Customer Registration Team, Constitution Group, Cabinet Office

2 Individual Electoral Registration 2Maximising Registration and IER A change from the current system of ‘household registration’ to one where everyone registers individually. IER will include a modern electoral registration system with personal responsibility. Applicants will have their identity confirmed or verified before being added to the electoral register. For the first time, citizens will be able to register to vote online.

3 How does IER work? 3 All electors must register to vote individually and have their application verified before being added to the register. Each must provide:  Name  National Insurance Number and  Date of birth These are cross checked with DWP before names are added to the register, or appropriate proof of identity can be provided to an Electoral Registration Officer (ERO). There are alternative ways to verify for those unable to find their National Insurance Number. Requirement for signature dropped –allowing online registration. Maximising Registration and IER

4 The IER Digital Service 4 Data Checked Online Application IER Digital Service Local Authority Citizen Local Authority ……………………… Maximising Registration and IER

5 Maximising registration fund 2013/14 5Maximising Registration and IER DateFunding July 2013 £4.2 million maximising registration funding announced October 2013 £385,848 to Local Authorities/Valuation Joint Boards in 2013 (Activity Oct 2013 – Feb/Mar 2014) February 2014 £3.6 million distributed equitably to every ERO to help them with the costs of local activities for maximising registration. Funds distributed equitably to EROs according to levels of under- registration. Five national organisations awarded funding from the Democratic Engagement Innovation Fund (£215,932). Rock Enrol! learning resource available to all EROs.

6 Why ‘maximising registration’? EROs have a duty to maintain an accurate and complete electoral register. The Government is determined to support EROs in ensuring as complete and accurate a register as possible, as part of the transition to IER. This includes funding and promoting work at a national and local level to maximise registration levels. 6Maximising Registration and IER

7 Analysis of under-registration To inform maximising registration activity, we sought to understand the following: 7Maximising Registration and IER Issue Question ScaleWhat is the number of people ‘missing’ from the electoral register in the UK? PatternsAre there any patterns (regional, demographic) in under-registration? DriversWhat are the demographic drivers behind these patterns?

8 Decline in registration Registration rates have been in steady decline for decades Electoral register 85% to 87% complete in 2011 Approx 6m people ‘missing’ from register Members of certain groups are statistically less likely to be on the register 8Maximising Registration and IER Source: The Electoral Office for Northern Ireland, 2009 Sources: Electoral Commission: Great Britain’s Electoral Registers, 2011 and the Wilks-Heeg Literature Review: Electoral Registration in the UK

9 Completeness levels 9Maximising Registration and IER Completeness rate by age range Completeness rate by ethnicity Source: Electoral Commission: Great Britain’s Electoral Registers, 2011

10 Under-registered groups (URGs) The UK Electoral Commission research on patterns of under-registration: 10Maximising Registration and IER GroupRegister completeness Private renters56% Social renters78% BME groups77% Young people (17-18)55% Young people (19-24)56% EU nationals56% Irish and Commonwealth nationals68% Source: Great Britain’s Electoral Registers, 2011: register completeness in under-registered groups (Electoral Commission, 2011)

11 Regression analysis aimed to find out whether these factors (tenure, ethnicity, age etc.) drive under-registration. Data used: 2011 Census Mid-year population estimates UK Electoral Registration Statistics 11Maximising Registration and IER LA’s registration rate Private renters Social renters Deprivation Young people /students BME residents Foreign- born residents Education LA size Religion Socio- economic group Unemploy ment

12 Highlighted in blue are demographic characteristics with a statistically significant relationship to under- registration. Source: Electoral Registration Analysis (Cabinet Office, 2013) 12Maximising Registration and IER LA’s registration rate Private renters Social renters Deprivation Young people /students BME residents Foreign- born residents Education LA size Religion Socio- economic group Unemploy ment

13 Confirmation 1.Matching of existing electoral register against records held by DWP. 2.Electors ‘passported’ to new system without being required to provide personal identifiers. 3.Electoral administrators free to focus limited resources on minority of electors who cannot be confirmed and those currently unregistered. Confirmation Dry Run (CDR), Summer 2013 All LAs in England and Wales, and all VJBs in Scotland; 46 million people’s records checked. 13Maximising Registration and IER

14 CDR results Green flag – positive result, individual confirmed Amber flag – possible match, may be confirmed by local data matching Red flag – no match found Average green match rate of 78%, median of 81% (range 47-86%). Average increases to 85% with local data matching. 15 to 22% of currently registered electors unlikely to confirm. Lower in: urban areas, student towns, predominantly private renter areas... Source: Simplifying the transition to Individual Electoral Registration: An evaluation of the ‘confirmation dry run’ – using data matching to confirm electors on the electoral register (Cabinet Office, 2013) 14Maximising Registration and IER

15 Students HMO residents Private renters Less likely to confirm Young people (18-24) People born outside UK Social housing residents BME individuals More likely to confirm 15Maximising Registration and IER Source: Electoral Registration Analysis (Cabinet Office, 2013)

16 Maximising registration: phase 1 Competitive process with funding awarded to 24 Local Authorities (LAs) and Valuation Joint Boards (VJBs), including some joint cross-LA bids. Case studies of activities undertaken by LAs fall into three broad categories: 1.Partnership working with third parties (i.e. housing associations, universities, schools) to target under registered groups 2.Undertaking intensive canvassing of URGs 3.Publicity and communications activity to target under-registered groups 16Maximising Registration and IER

17 Examples of engagement activities Partnership working with third parties Attending Youth Service meetings Registration sessions in schools Liaising with social housing providers to include registration forms in welcome packs for new tenants Intensive Canvassing Targeted mail-outs to wards with low registration rates Identifying the numbers of specific URGs against Census data of the total number living in the authority. Local data could then establish where wards have a higher proportion of households with URG profiles. Publicity / communications activity Face-to-face promotion at sixth form colleges and universities Announcements on university radio channels Promotional flyers with Council Tax bills and Social Housing tenant newsletters Social media, QR codes and bespoke videos to universities and colleges 17Maximising Registration and IER

18 18Maximising Registration and IER

19 Evaluation To help inform future registration maximising strategies, and develop future funding opportunities for LAs/VJBs. To measure impact and process. - How many new registrations? - How were the registrations achieved? - How cost-effective were the activities? To identify examples of good practice suitable for wider roll-out. - Successful activities - Lessons learnt - Recommendations To make a wider contribution to debates on the efficiency and effectiveness of traditional canvass activity versus more innovative approaches. 19Maximising Registration and IER

20 Local rates of under-registration Local data matching against electoral register Council tax records, housing association records, housing benefits claimants lists, local housing databases Education records and ONS Electoral Statistics Two-tier data sharing Census data, population estimates, Electoral Commission registration rates MOSAIC analysis Utilising local organisations and specialist community groups Records from previous canvasses 20Maximising Registration and IER

21 Impact -Overall impact on registration rate -URG completeness before/after -% increase -% registered of those targeted (success rate) Colour coded/marked forms, website sign up, pre-populated forms Noting duplicate, incomplete, ineligible forms -Cost per elector targeted and cost per elector registered -Estimating registrations from engagement -Tracking registration figures against events -Control areas and social ‘experiments’ 21Maximising Registration and IER

22 Process 1.Objectives –Why targeting chosen URGs? How targeting chosen URGs? 2.Delivery –Any changes? Any obstacles? What was successful? Partnerships? 3.Impact on workflows –Any additional training needs? Extra work? How easily incorporated? 4.Evaluation method –How were registrations captured? Engagement? Feedback? 5.Costs –Additional costs? Efficiency savings? 6.Lessons learnt –Recommendations? Future changes? 22Maximising Registration and IER

23 Preliminary findings... Responses from 20 of 24 LAs/VJBs received Process of analysis ongoing Interviews and case studies planned We have also produced evaluation guidance and forms for LAs/VJBs which received funding following the announcement in Feb Initial assessments are currently coming in outlining plans for activity. Evaluation is being strongly encouraged across LAs and VJBs. 23Maximising Registration and IER

24 Any questions? Charlotte Snelling Social Researcher, Customer Registration, Constitution Group, Cabinet Office 24Maximising Registration and IER


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