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The Scottish Government

The Scottish Government Using Administrative Data in the Housing Supply Indicator Claire Boag, Communities Analytical Services Outline Who we are Pros and cons of administrative data NI 32 – Increase the rate of new house building. What does that actually mean? New build components

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The Scottish Government

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  1. The Scottish Government Using Administrative Data in the Housing Supply Indicator Claire Boag, Communities Analytical Services

  2. Outline • Who we are • Pros and cons of administrative data • NI 32 – Increase the rate of new house building. What does that actually mean? • New build components • Conversions • Refurbishments • Things to consider

  3. Housing Statistics branch • Collect, analyse and disseminate housing data • 20 administrative returns from local authorities: • Local authority housing management • Changes to stock levels • Right to buy sales • New house building • Also have access to administrative data collected by others: • Housing Benefit / Market Evidence • Housing Association new build • Landlord Registration

  4. Advantages of administrative data • Low costs of obtaining data from an existing source. • Faster and more frequent analysis may be possible. • In particular, the time between an event occurring and being recorded • Eg - most housing stats data available immediately (exceptions include private new build) • frequency – eg. quarterly figures for local authorities could be difficult to achieve with a survey without huge expense • Sometimes more detailed figures are available • Eg - for geographical areas where data has geographic referencing • No statistical sampling errors or non-response bias. • Doesn’t rely on memory of respondent.

  5. Disadvantages of administrative data • Effort may be needed to make administrative sources useable for statistical purposes. Eg – estimating missing values, getting rid of redundant data, linking to other data sources • Lack of independence – not controlled by statisticians. • Definitions and classifications may often not be ideal for statistical purposes. Eg - data on housing association starts is actually based on approvals. • Coverage of the data may not be complete and it may be difficult to make comparisons with other statistics. Eg – landlord registration database Eg – HB claimants from RRS v DWP • Changes in provider data systems may cause discontinuities. Eg – housing list cleaning or system improvements • There may be some danger of interruption to the supply of data. Eg - staff turnover in LAs Eg – IT problems • There may be constraints on the use of data Eg – Market Evidence Database

  6. Housing supply indicator • Data on housing supply informs National Indicator 32 (Increase the rate of new house building), and comprises the following elements: • new house building: houses completed by or for housing associations, local authorities or private developers for below market rent or low cost home ownership; houses completed for market sale by private developers. • refurbishment: houses acquired by housing associations and refurbished either for rent or low cost home ownership. Refurbishment of private dwellings funded wholly or partly through the Affordable Housing Investment Programme. • conversion: new dwellings created by conversion from non-housing to housing use.

  7. Housing supply indicator Terminology issues • Increase the rate of new house building • Uses absolute numbers not rates • Includes new housing provided through other means

  8. Private new build data • Data provided on a quarterly basis by local authorities via the NB2 return. • Can be based on different data/methods in each LA though each should be consistent over time. • No marked seasonality but data for individual quarters is volatile therefore quarterly change unreliable

  9. Local authority new build data • Data provided on a quarterly basis by local authorities via the NB1 return. • Council house building limited in recent years, therefore numbers small and data volatile • Errors fairly unlikely since numbers low

  10. Housing association new build data • Data provided on a quarterly basis by HID colleagues from the AHIP database • Data provided by those involved with managing the developments therefore quality higher than private new build. • Very volatile

  11. Annual new build • Annual new build data much less volatile – change more clearly shown • Issues - Need to watch out for duplication across sectors • LA new build with AHIP funding • Purchase of private new build by LA for social rent

  12. Conversions • Collected from local authorities through annual return

  13. Refurbishments • This is proxy data – we only have information on housing association refurbishments and private refurbishments receiving public subsidy. • All other private refurbishments (resulting in addition to housing supply) are excluded

  14. Things to consider (1) How and why was the data collected? • Private and local authority new build • Paper based returns, produced purely for the SG. Data tends not to be heavily used within the councils (with a few exceptions). • Labour intensive, burdensome return • Based on a combination of completion certificates, site visits and council tax assessors data • Smaller, more urban local authorities are more likely to use site visits, large rural authorities need to rely on completion certificates • There is anecdotal evidence that there are issues with completion certificates in some councils, eg: self-builders have no incentive to apply for a certificate. Often long delays between ‘effective’ completion and legal completion.

  15. Things to consider (2) How and why was the data collected? • Housing association new build and refurbishments • Information collected by SG Housing Investment Division to monitor Affordable Housing Investment Programme. • Data extracted from live database, and HID carry out quality assurance checks before passing it on. • Delays in the recording of completions mean that the data is subject to annual revisions each March, therefore quarterly or calendar year monitoring inappropriate. • Conversions • Information on conversions are provided by local authorities on the annual Stock4 return. • Data is provided in summary form, therefore there is little scope for us to check the accuracy, other than to compare with other LAs and over time • Difficulty collecting information from local authorities

  16. Things to consider (3) Is there a consistent time series of estimates? • Private and local authority new build • Information has been collected in its current form since 1986. • Issues with data for Highland – new source used, but revisions made back to 2000 so no issues with consistency in recent years. • If a local authority changes the way it collects or records the information, we will only know if they tell us. • Housing association new build and refurbishments • provided since 1992 • Changes afoot with HA starts – we will need to consider creating consistent back series • Conversions • Consistent at least since 2001. Prior to that was collected as part of new build data. No obvious inconsistencies

  17. Summary • Know how the data is collected • More scope for error with paper based collection • Data that is difficult to collect will be more error prone • Know why the data is collected and how it’s used by the provider • The more it’s used by the data provider, the more accurate it should be • Understand the nature of volatility in the data • Is it a real change or a data artefact? • Investigate unexpected peaks and troughs • Know whether there are definitional or system changes that would cause a discontinuity in a time series

  18. Contacts Email housingstatistics@scotland.gsi.gov.uk, or Telephone: 0131 244 7234 Fax: 0131 244 0446 Post: Communities Analytical Services (Housing Statistics) Area 1-F Dockside Scottish Government Victoria Quay Edinburgh EH6 6QQ

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