Using Zoopla adverts to examine the private rented sector

The Urban Big Data Centre has purchased data from property website Zoopla, including historical online adverts back to 2010 for the whole of Britain. These data have the potential to fill gaps in our knowledge about the housing market - not just housing sales but also the private rental market.

There is currently a considerable gap in our knowledge of the nature and scale of the private rented sector in the UK. Much of what we know comes from the census, but these data have serious limitations as they are only available every 10 years. We need data that allow continuous monitoring of the sector over time, providing local authorities, central government and academic researchers with a clear understanding of changes. The Zoopla data have the potential to help fill the gaps in our current understanding of the private rented sector, but only if it provides accurate estimates of the market.

At the UBDC, we are currently examining the quality of the data and its potential for use in making accurate estimates of the private rented sector. As part of this validation work, we are comparing the Zoopla data 2011 census estimates of private renting stock. Although at an early stage, the results are very encouraging and we are sharing some of the results in this blog.

The Zoopla data is available to anyone through the UBDC, although the use of the property-level data is restricted to non-commercial purposes. The results of the validation work will be published on our website and will be available with the data.

Initial comparisons

One simple comparison is to look at how the number of Zoopla adverts in an area compares with the number of rental households in that area in the 2011 Census. Below, we show results for Scottish Datazones (small areas with a population between 500 and 1000 people). The Zoopla data are for years 2013-1016 - so there is a bit of a time difference. Even so, results are promising with a high correlation for the whole sample (R=0.67) (Table 1). If we split the Datazones by levels of deprivation, the correlations are very similar, suggesting consistency in coverage of different segments of the market.

 

Table1: Correlation Private rental household (census 2011) by Zoopla Properties at Scottish Datazones

 

 

Private rental by Zoopla properties

Zoopla Property numbers

2013-2016

R=

0.67*

44195

Dep 1 and 2

R=

0.67*

11147

Dep 3 and 4

R=

0.69*

8811

Dep 5 and 6

R=

0.667*

9615

Dep 7 and 8

R=

0.61*

8199

Dep 9 and 10

R=

0.66*

6423

*P>= 0.001

 

If we split properties by the year of advert, we also see consistency in the correlations (Table 2). We can’t tell from these whether the Zoopla data are tracking the growth of the sector since 2011, but there is at least consistency in the relationship.

 

Table2: Correlation Private rental household (census 2011) by Zoopla Properties over the four years at Datazone

 

 

 

Private rental by Zoopla properties

Zoopla Property numbers

 

2013

R=

0.67

14973

17118

2014

R=

0.68

17294

19713

2015

R=

0.69

12924

14633

2016

R=

0.64

13149

14807

 

We can take the analysis down to a more detailed level by mapping Intermediate Zones in Glasgow (areas with a population of 3-4000). Again, these maps show that areas with high levels of Zoopla properties appear to correspond well to areas where there are high levels of private rental households as recorded by the 2011 Census.  

Figure1: Private rental households for Glasgow (census 2011) (top) Zoopla properties for Glasgow (bottom) at Intermediate zone level.

Private-rental-households-Glasgow-census-2011.jpg    Zoopla-properties-Glasgow-at-Intermediate-zone-level.jpg 

These early results are very promising and suggest it will be possible to get good estimates of the private rental market based on Zoopla data.

There is much to do to produce more detailed analysis and robust estimates in these data. The most exciting and innovative next step is linking the adverts to large household surveys to see what proportion of people living in the private rented sector appear to be in a property captured by our data, and where coverage is better or worse.  That analysis has the potential to really strengthen our confidence in the data. However, even these early efforts suggest that these data will help to fill at least some of the gaps in our knowledge of the private rented sector.

You can find out more about our housing data on this site, or contact us for more information. We have also set up an email discussion list on housing data and related issues that you can join via the JISCMail website.

Author: Mark Livingston

Mark is a social scientist with over 12 years post doctoral experience working both in public health and urban studies. Currently, he is the Programme Manager for the Integrated Multimedia City Data (iMCD) research project.

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