In the first article in this series I discussed why it is important for us to understand household mobility, outlined the sources currently available to researchers and highlighted the potential of using commercial data as a possible alternative to census or admin data.
Using large scale commercial data sets, such as the Whenfresh/Zoopla Property Transactions and Associated Migration (available via the CDRC), is exciting as it can answer questions and enrich our understanding of mobility patterns and population change in the UK.
The Consumer Data Research Centre has partnered with online property search provider Zoopla and data insight consultancy Whenfresh to obtain data about the characteristics of properties which have been sold in England and Wales. For the 2014 calendar year, visualised here, there were over 900k unique property transactions.
Where do we move?
This image highlights some larger UK cities and the flow of households between them. When a line becomes more opaque on one side it means that the flow of house movers is directed towards the respective city by a majority of people.
1. Over 68% of moves occurred within the same postcode area (e.g. the postcode area starting LS covers Leeds, EX covers Exeter, etc.) and 34% of moves occurred within the same postcode district (e.g. LS1 covers much of Leeds city centre).
2. Largest number of moves within the city:
- London – 6057
- Bristol – 2523
- Nottingham – 1938
- Leeds – 1427
- Sheffield – 1387
- Manchester – 1342
3. London accounts for 7.1% of all moves in England and Wales (either in to, out of or within the city) and is very well connected to the greater South East region, towns on the south coast and other key cities. London and the greater South East has been termed an ‘Escalator Region’, whereby young people move in to gain skills and training before eventually moving on.
How far do we move?
- On the whole, households don’t tend to move very far, the overall median distance of a move in England and Wales is 3.2 miles (we use median distance as opposed to average distances as there are a small number of moves across very large distances which skew the reporting)
- People who move within the East of England move further than anywhere else (2.8 miles) whereas the median distance of moves in London is only 1.6 miles. These values are not surprising, given the settlement patterns in the East of England are very different to those in London: the move from Cambridge to Norwich is 64 miles, compared with just 30 miles between Hayes in the far east of London to Dartford in the far west of London.
- People moving within the regions of the north of England travel shorter distances than those in the south. The median distance of move within the North East is 1.61 miles, within the North West is 1.73 and within Yorkshire and Humber is 2.01 miles. This is compared to 2.42 miles in the South East and 2.3 miles in the South West.
How connected are our cities?
|City||Received households from % of places in England and Wales||Sent households to % of places in England and Wales||More households moving into or out of city?|
Norwich appears to be an attractive destination with 20% connectedness and a net gain of 148 households. Nottingham, York, Leeds, Manchester, Birmingham and Southampton are all well connected cities, appearing in the top ten. One surprisingly well connected city for inflows was Swindon, which received households from 172 other places. The surprising entry in terms of outflow connectivity is Reading, which was connected to 25% of other places.
What data are used in these visualisations?
The Consumer Data Research Centre has partnered with online property search provider Zoopla and data insight consultancy Whenfresh to obtain data about the characteristics of properties which have been sold in England and Wales. For the 2014 calendar year, visualised here, there were over 900k unique property transactions. Attached to these transactions data are the Royal Mail redirection service data which provides details about the forwarding postcode for over 212k households who moved. Those records for which there is a forwarding address (and as such an origin-destination link) represent 19% of the 1.1m residential property sales made in 2014. There are a number of unique advantages to using these data:
- They are timely and easy to update. The data presented are for the calendar year 2014 but other date ranges could be specified.
- They provide good temporal coverage. Instead of a yearly snapshot of transitions they report the exact date that a property was sold. This allows us to start to understand seasonal trends in mobility.
- The geography provided is extremely detailed. Sales (origins) are at address level while destinations are delivered as postcodes. This allows us to start to assess mobility patterns at a very small scale, answering questions about communities rather than the more common administrative units used in previous work.
Consumer data like those used here have a role to play in the future of understanding mobility patterns, and population change more generally.
The visualisations were created by Herwig Scherabon, an expert in data visualization and information design. Interpreting and visualising flow information is particularly difficult because of the dimensions of the data. Having origins and destinations dictates a need for some way of linking the two together, and the volume of data soon becomes unmanageable. This is why design decisions, like being selective in the number of data entries shown or deciding how opaque crossing lines should be, is important when trying to get a message across.
About the author
Dr Nik Lomax is a University Academic Fellow at the University of Leeds, his research focuses on the way in which demographic behaviour changes over time and how people interact with the areas in which they live and work. Much of his work focuses on the dynamic processes involved in migration but he is also interested in the social implications of changing demographic composition: household formation, social exclusion and population ageing for example. Areas are shaped by changing economic conditions, policy interventions and social attitudes, which in turn has an impact on demographic behaviour. Modelling and explaining these complex interaction is key to the work the work which he does.
 Reference to Tony Fielding’s work here
 HMRC data