Web data affords desirable view of local rents

Nigel Henretty reveals how ONS is experimenting by tapping into linked and open data to establish average monthly rent prices for small areas. 

How much does it cost to rent a property in any given local area?

I’d really like to be able to answer that question, and so would housing policy makers in local authorities across the UK. Given that the size of the private rented sector has near enough doubled over the past decade, it might come as a surprise that we can’t actually measure average rent prices for small areas (smaller than local authorities) using official data. At the risk of embarking on months of migraine-inducing data wrangling, I asked myself a dangerous question. How hard can it be? Long story short, it’s quite hard.

There are already some official statistics that can help to point us in the right direction. First, there’s the snappily titled Index of Private Housing Rental Prices, which tells us about inflation of rent prices at the national and regional level. Then there’s the Valuation Office Agency’s private rental market statistics, which provides us with an indication of average rent prices at the local authority level based on a sample of rental data. Trouble is, neither of these data sets were originally produced to provide small area statistics (because of the model-based method and the sampling respectively) and that’s what policy makers are now really after in a bid to understand the make-up of their local areas.

It’s the housing policy makers that are really at the heart of why a greater understanding of the private rented sector is needed.

At every stage, housing is a very local issue. From the planning process, right through to the building, buying and renting of homes, the situation varies a great deal not just across the country, but even within individual local authorities. In particular, the affordability of housing, the type of homes being built and the tenure in which people live in their accommodation are localised issues. Policy makers trying to react to and plan for these issues need a geographically granular view of housing in their areas. At the moment, that view of the cost of private renting just isn’t available.

Small area statistics

There is some hope though. A few years ago we started using administrative data on property transactions from the Land Registry to produce House Price Statistics for Small Areas (the first rule of housing statistics is that they must take longer to pronounce than produce). The address-level data we use for this allows us to produce small area statistics (down to the middle layer super output area level if you like a bit of geography), which show the price paid for residential properties. Since then, a whole range of address-level administrative data has become available, including some property website data which might just help us crack the small area rent price problem.


Zoopla is a giant amongst websites of the UK property market these days, and as such holds data which offers a rich source of information about properties for sale and for rent. We have used the data to work out the average advertised monthly rent price at the small area level for the whole of Great Britain between 2010 and 2016. Let’s call this ‘Advertised Private Rent Price Statistics for Small Areas’ and maintain the theme of long titles shall we? We’ve also looked at the number of rental property listings over this period to get a clear indicator of rental market activity for each middle layer super output area.

Our initial analysis of the first outputs suggests that the data provides us with a reasonably comparable set of rent prices to the current official statistics for the larger geographies. The fact that we have some first outputs to analyse also suggests that we’ve found a broadly sensible way to handle and geo-reference the rather large amount of administrative data.

Like all good statistics though there are of course many, many caveats and limitations which we need to understand and hopefully overcome. Here are just a few of those, starting with the most challenging:

  • The data relates to properties advertised for rent and so this doesn’t currently cover all rented properties. The difficulty is in describing the extent to which advertised rent prices are representative of all rent prices.
  • Not all properties advertised for rent are included in the data. Some letting agents only use their own website, or other property websites, to advertise properties for rent.
  • Not all rented properties are advertised at all, anywhere. A substantial part of the private rented sector is casual, and these properties therefore may never appear in property website data or any administrative data.
  • Some areas appear to have no properties advertised for rent in the entire time-series of data and we don’t really know why yet.

Looking ahead, we’ll work with the users of rent price statistics to discover if this potential new output would meet their requirements, and whether we can tap into other data sources to overcome some of the limitations. We’d also like to produce information about the rent prices of different property types and sizes. Ultimately, we’re aiming to have a suite of rent price statistics that are comparable across geographies, which will help policy makers genuinely meet the demand for housing in their local areas.

In the statistical utopia of the future, I suspect all this will be possible automatically and programmatically from a constant stream of linked and open big data. Until that happens, I still have a job.

Nigel Henretty is a Statistician for ONS’s Public Policy Division