This percentage has decreased since 2012, when 63.8% of dwellings were owner-occupied. County and UA, NUTS 3 and combined authority data have been constrained to aggregated LA data from MHCLG.Survey data are based on a sample of the population, which is not always representative of the true population. When comparing the rate of owner-occupied dwellings in 2012 and 2017, there was a slightly lower percentage of local authority districts in the higher bands (70 to 79.99% and 80 to 89.99%) in 2017 than in 2012. This Research Output is not an official statistic. There are typically three main tenure categories: owner-occupied, privately rented and social housing.To derive tenure from the APS, the tenure and landlord of accommodation variables are used to categorise households into each of the three categories in line with For the households that have Tenure equals Rented, look at Landlord of accommodation variable.If there is no response to the tenure question from the APS, or no landlord of accommodation response if the household was rented, the household was excluded from our analysis.The APS data used to produce this Research Output are from a household survey and so only cover dwellings that are occupied and do not provide data on any vacant dwellings. We suppressed these larger geographies even when the private sector sample size for that larger area was 50 or more so that the suppressed local authority estimates cannot be derived. This means that we are confident that 19 out of 20 times, changes will be down to real changes in our population, rather than a result of sampling variability or randomness variation.We also produced a coefficient of variation (CV) for each estimate, by considering the proportion of dwellings in the private sector (p), and the sample size from the APS for the number of dwellings in the private sector (n), using the following formula:The lower the CV, the lower amount of uncertainty there is around an estimate.
Research Outputs: Subnational dwelling stock by tenure estimates, England: 2012 to 2015 Investigating the use of data from the Annual Population Survey (APS) and occupancy rates from the English Housing Survey (EHS) to estimate the number of dwellings by tenure … Annual estimates of the tenure of dwellings for subnational geographies will provide evidence to help planning authorities set housing policy, and allows them to monitor the distribution of tenure over time within an area and between areas.This Research Output provides the latest information about research into new methods and data sources used to produce annual subnational estimates of the dwelling stock by tenure in England. GOV.WALES uses cookies which are essential for the site to work. In addition, the dwelling stock figures include vacant dwellings. It is important to make a vacancy rate adjustment that adjusts for tenure because the likelihood of a privately rented dwelling being vacant is usually higher than for owner-occupied dwellings.
This is an update to our There are three main types of tenure for which dwellings can be categorised: owner-occupied, privately rented and socially rented. Figure 4 shows that the five local authorities with the lowest percentage of owner-occupied dwellings in the East of England were significantly lower than the five local authorities with the highest percentages in 2017. Tenure breakdown is estimated from the 2011 Census, the Annual Population Survey, local authority and registered social landlord returns.Dwelling stock estimates: as at 31 March 2013: as at 31 March 2013Dwelling stock estimates: 2011 census count and rolled forward estimates Things you need to know about this release. The figures presented here are based on March 2017 because this is the latest available Scottish Household Survey dataset. These research outputs are not official statistics on dwelling stock by tenure. This shows how these estimates are useful in identifying areas that have significantly different tenure distributions, despite being relatively close geographically.In 2017, the percentage of dwellings that were owner-occupied ranged from 24.5% in Tower Hamlets in London to 84.5% in Ribble Valley in the North West. An exception for this is regions, because the regional APS data are constrained to regional MHCLG data, from which you cannot derive an LA’s stock.
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