The anatomy of SW10

Analyses of house sales often focus on the wider UK market. In this blog, we’ll take a deep dive into one of London’s more-than 100 postcode districts, drawing on 10,000 property transactions to see how key events have shaped its market in recent years. The object of our focus will be SW10 which forms part of the Royal Borough of Kensington and Chelsea.

Looking at the anatomy of SW10 in the chart below, we find that over 80% of property transactions are for leasehold flats / maisonettes.  In contrast, detached freehold properties are a prized scarcity: Only 40 of the circa 10k transactions, over the past 20 years, were for detached properties.

The rise of house values

The following plot shows the bulk of the transactions from the start of 1995 through to autumn 2017. Each dot is a transaction. I’ve focused here on those up to £2m.  These account for close to 95% of the total. The excluded 5% range from £2m to a staggering £55m.

The most obvious characteristic of the SW10 market is the sustained growth in property value.  But there is a lot more to this picture on closer inspection.

The punch of the Financial Crisis, and a flurry of jabs

By overlaying the key events of the past 20 years, we see that the Financial Crisis in particular has had a dramatic effect on the market. The density of dots to the left is visibly different to that on the right. And the right-side reveals a tale of a market briefly evaporating at the beginning of the “credit crunch”, before tentatively starting to re-emerge.

By colouring the dots red and blue, we also see the tendency for freehold properties to secure higher prices than leasehold. Owning both the building and the land on which it stands, outright and in perpetuity, is clearly a significant benefit for freehold buyers.  There could also be a confounding factor of freehold properties tending to be larger on average, but the square-footage data associated with these transactions is unavailable to test if that is the case.

Another interesting feature of the data is the noticeable horizontal banding of dots at the £250k and £500k price levels. For most of the past 20 years, these have been key stamp duty thresholds.  More recently £250k, £925k and £1.5m have become the key break-points. Stamp duty is now a punishing 10% and 12% for £925k+ and £1.5m+ properties respectively.

The above plot also shows a distinct vertical banding around August / September 2003.  This is more clearly seen in the alternative histogram plot below.  What prompted this spike in sales volume is unclear.

The above chart also clearly shows the fall off in volume to the right of the Financial Crisis.  And it more clearly reveals the impact of the end-of-2014 stamp duty jab which took the wind out of a market that was just starting to recover from the 2007/08 “credit crunch”.

A case for a more gently-graduated stamp duty?

For anyone needing to sell a property valued just a little above the stamp duty thresholds, it may be difficult to avoid a painful compromise on price to entice buyers.

Holding on to such properties, may be the better course where feasible. It’s a shame that the Government cannot employ the “softer gloves” of a more gently-graduated stamp duty. Those caught in the “sour spot” may simply find future budget adjustments shadowing the changing value of their biggest asset.

Adding square-footage, or re-configuring a property into smaller flats, could be options for those with the means and the scope to make changes.  But that’s not easy in this unique densely-populated and tightly-regulated urban environment.

R tools used

	Packages	Functions
	SPARQL	SPARQL
	dplyr	filter; mutate; group_by; summarise; if_else
	stringr	str_replace
	tibble	tibble
	lubridate	as_datetime
	ggplot2	geom_bar; geom_density; geom_histogram; geom_vline; geom_point
	ggthemes	theme_economist

The code may be viewed here.

Citations

R Development Core Team (2008). R: A language and environment for
statistical computing. R Foundation for Statistical Computing,
Vienna, Austria. ISBN 3-900051-07-0, URL http://www.R-project.org.

Contains HM Land Registry data © Crown copyright and database right 2017. This data is licensed under the Open Government Licence v3.0.

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