Land demand is high in cities.
Cities have access to good jobs, people and specialized consumption services. High
demand and the limited supply of urban land translate into high land prices. In
turn, high prices promote high density land uses. If a parcel in the square
mile costs hundreds of millions, expect to find a tall office building there
rather than a bucolic bungalow. Despite all this, it is common to find vacant or severely underused land in cities. Old
factories, derelict dwellings, abandoned car parks; all are common images from
urban life. But, for an economist, this is quite surprising. Is it that some
land is simply unresponsive to demand conditions?
Having a good answer to this
question is important. Unused land makes our cities larger and our commutes
longer. In stark distinction with parks, or undeveloped green-field land, abandoned
previously-developed parcels are usually quite unpleasant (in econ-talk, they
generate strong negative externalities). Planning authorities and local
governments often have specific policies to promote land re-development, by
offering tax breaks, grants or financing options to developers of infill land.
Understanding how demand affects re-development helps us to anticipate whether
these policies will be successful. Moreover, it also gives us a hint on whether
or not market forces can themselves achieve the goal of re-developing these
sites.
In a recent Centre for Economic
Performance, Urban and Spatial Programme discussion paper, I
address this question by using data on brownfields across England. As you may
know, in the UK brownfield is the
name usually given to land which was previously developed but is currently
underused or vacant. Policies fostering redevelopment of brownfield land in
priority over green-field (“brownfield-first”) have been a feature of the
planning system at least since the 1990s and have seen some resurgence of
interest in recent
years. Whether these policies are actually effective in encouraging
brownfield re-development in response to housing demand remains unclear. In this paper, I use data on brownfield sites
to test whether the prevalence of empty land in cities is indeed sensitive to
demand conditions. In essence, I want to test whether high demand (or high
price) areas are more likely to be re-developed than otherwise identical areas
where demand is lower. The resulting estimate measures the price sensitiveness
of brownfield re-development. If you are versed in economics, this is like
estimating a price elasticity of land supply. There are several challenges when
trying to estimate these parameters properly. I briefly discuss them below in
case you are interested.
My findings indicate that
brownfield re-development is indeed affected by local demand conditions. In the
long run, re-development follows demand. Quantitatively, a 1% increase in
prices leads to a 0.07% decrease in the probability of having brownfield land
in a given hectare. This number looks very small but the baseline probability
of finding brownfield land in my sample is also low, standing at roughly 1.5%.
Hence, I conclude that price differences can induce substantial variation in
the presence of empty land in our cities. Importantly, this is the case despite
the tight planning restrictions that characterize the UK. This is not to say
that planning restrictions cannot influence re-development. In my paper, I show
that re-development of parcels in areas with tougher planning (such as the
South East) is less sensitive to demand conditions.
To sum up, my results show that
market forces do affect brownfield development in the long run.[1]
According to my estimates, a large but plausible increase of prices of roughly
20% would lead to re-development of a large fraction of brownfields in English
cities. It also suggests incentive based policies such as grants or tax breaks
could, at least in principle, achieve substantial long-run re-development. Finally,
the paper shows that equilibrium land supply is neither fixed nor determined
exclusively by sprawl; it can also be shaped by development within the cities’
footprint.
Technical Details
My analysis is based on data for previously-developed
land sites in England, as recorded in the National Land Use Database of
Previously Developed Land (NLUD-PDL). I use the 2007 version of this dataset,
but newer versions can be found online.
Data on prices are obtained from the land registry and data for land use
changes are obtained from the Land Use Change Survey.
There are a few technical hurdles we have to
overcome before we can obtain credible estimates of the price sensitivity of
re-development. On the first place, because brownfield sites tend to generate
negative externalities on nearby residents, they themselves affect prices. A
growing literature has made this case over the last decade.[2]
As a result, there is substantial scope for reverse causality, from vacant
sites to prices. In addition, re-development costs may be correlated with
amenities that affect land prices directly. For example, in a monocentric city,
low amenity areas away from the city centre may be harder to re-develop because
of reduced accessibility. Other confounders, such as differences in the type of
sites (e.g. residential vs. industrial) in different areas could also bias
naïve estimates.
In order to overcome this problem
I need a demand shifter, a variable that affects demand without affecting
supply conditions. In this study, I use school quality as my demand shifter. A
long literature has documented price effects of school quality in residential
markets and the UK is not an exception (see for example Gibbons, Machin and
Silva, 2013). Combining data from school quality with detailed maps, I
implement a two-stage boundary discontinuity design which uses school quality
as an instrument in a regression of brownfield location variables on prices.
The boundary discontinuity design uses school admission boundaries to ensure I
am comparing locations which are very close to one another but have access to
primary education of different quality. This method is what allows me to obtain
credible estimates of the price sensitivity of re-development.
Note: See Figure
description in the text.
An illustration of the result is
provided in the figure above. The horizontal axis represents distance to a
school-admission (county) boundary, with negative distances corresponding to
the side with low
average school quality and positive distances corresponding to the side with
high average school quality. The vertical axis measures the probability that a
given hectare contains brownfield land. Fourth degree polynomials fitted on the
raw data represented in solid lines. The discontinuity observed in the middle
of the figure shows that brownfield land is less common in high demand
locations. More details can be found in the paper.
References
Gamper-Rabindran, S., &
Timmins, C. (2013). Does cleanup of hazardous waste sites raise housing values?
Evidence of spatially localized benefits. Journal of Environmental Economics
and Management, 65(3), 345-360.
Gibbons, S., Machin, S., &
Silva, O. (2013). Valuing school quality using boundary discontinuities. Journal
of Urban Economics, 75, 15-28.
Greenstone, M., & Gallagher,
J. (2008). Does hazardous waste matter? Evidence from the housing market and
the superfund program. The Quarterly Journal of Economics, 123(3),
951-1003.
[1] My
estimates however, are based on very long run changes. Anecdotal evidence shows
that re-development can take a long time. It took 50 years to re-develop the
areas around the London Royal Docks or Battersea Power station.
[2]
See for example the contributions in Greenstone and Gallagher (2008) and
Gamper-Rabindran and Timmins (2013).
