Planning and Fuel Use: a Critical Survey

Alan W. EvansUniversity of Reading

Or – Lies, Damned Lies, and Statistics

• With apologies to Mark Twain and/or Benjamin Disraeli

Introduction

• Land Use Planning, Fuel Use and CO2

Emissions

• Planning Deals with Externalities

• CO2 Emission is an Externality

• Therefore Planning can Deal with it

Dr Pangloss Finds His Profession

• ‘High densities result in reduced car use, therefore we need increased densities.

• But, thankfully, we have green belts and countryside protection so all is for the best in the best of all possible (planning) worlds.

• We just have to ensure that building is at high density on brownfield sites.’

• All the evidence that is needed is contained in a figure in Newman and Kenworthy (1989) showing ‘gasoline use per capita versus urban density’ for cities around the world in 1980.

• Suspicious economists might think that this pattern results from price and income differences rather than differences in density.

• Newman & Kenworthy have an answer – another graph which shows the same relationship ‘adjusted to US income, vehicle efficiencies and gasoline prices’ in 1980.

• In this format the figure was used to justify high densities in England by:

• The Rogers Report, 1999• Planning Policy Guidance, 2000

and, but suspiciously, in The Barker Report, 2006

• But an even more suspicious economist might ask how the adjustment is done.

• So London’s estimated gasoline consumption per capita increases by about 20% with this adjustment.

• From 12,426 MJ to about 15,000 MJ (the exact figure is not given).

• But a Londoner’s average income increases from $4,990 to $8,089 (the average for US cities) i.e. by 60%

• And fuel prices drop from 70 cents per litre to 23.6 cents per litre, i.e. by two thirds.

• Maybe it’s because of a fall in fuel efficiency from 10.7 litres per 100km to the US average of 15.35 litres per 100km, i.e. by 43% .

• But that doesn’t make sense either,

particularly as N&K state that in the long run the question of fuel efficiency would become unimportant.

• Their view seems to be that in the short run the sort vehicles which already exist are important.

• But in the long run people will buy more/less efficient cars as fuel prices rise/fall.

• Generally N & K give only averages for groups of cities – US, Australian, European, and Asian

• They give figures for only one city, the Canadian city of Toronto

Toronto

• The only city for which full data is given.

• There incomes would rise from $7,521 to $8,089, i.e. by 7%

• Fuel prices would change from 23.5c to 23.6c per litre, i.e. by less than ½%

• Fuel efficiency would improve from 16.3 to 15.35 litres per 100km, i.e. by 6%.

• Acording to Newman and Kenworthy these small changes should result in substantial falls in consumption per capita.

• From 34,813MJ in 1980 • To 29,995MJ in the short run

• And to 26,090MJ in the long run• A fall of 14% in the short run and of 25%

the long run!

One Conclusion

• What is shown in the diagram as “adjusted to US incomes and prices” is calculated using the ‘short run elasticities’ not the ‘long run’!

• Misleading? Deliberate or accidental?

A Second Conclusion

• There is no way in which an increase in incomes of 6% can result in a 25% fall in consumption.

• There is something very wrong with their figures.

One Explanation

• A research assistant invented the figures which showed what N&K wanted them to show so no-one checked them.

• The assistant collected the money, N&K got what they wanted –everyone was happy.

• I think this is probably true, but..

A Second Possibility

• N & K give too much detail, emphasise how generous the elasticities used are, etc.

• Sometimes are very accurate, which they emphasise, e.g. incomes in US cities, sometimes very approximate, e.g. incomes in German cities which are all the same, or London which is attributed with the average UK income.

• Maybe all this detail is to persuade the reader accurate calculations are being done, when they aren’t, like the conjurer’s chatter.

Recalculation

• What would their figure look like if it had been calculated the way they said it had?

• This has been done for the Australian and European cities (except Moscow)

• The relationship of fuel use with density is a lot less clear.

Other Urban Problems

• There are reasons for not recalculating:

• Moscow – in 1980 it was communist.

• Hong Kong – is a very small area and in 1980 one could not travel anywhere far by car.

• Singapore is an island state with one road route out to Johore.

Regression AnalysisFrom the ‘raw’ N&K data Ian Gordon shows:-FU = 5.8 – 0.70d (t= 9.5, Rsq = 0.78)

but with fuel price and incomes:-FU = 6.7 – 0.23d - 0.75p + 0.25y (3.7) (6.0) (0.7)(Rsq =0.95)

The variables are natural logs so the coefficients are elasticities (lower than N&K for p and y)

The Density Variable

• The regression does show density to be important, but there are other problems.

• Firstly, there is N&K’s measurement of density. For the US they use SMSAs which are larger in area than the conurbation.

• For Europe they use political areas which are smaller, e.g. the GLC excludes large areas of outer London

Secondly, N&K disdain economic variables

• Their concern is with ‘parameters …in the direct control of physical and transport planners.’

• So they ignore the cost of public transport, even when most European countries subsidise.

• This means that the coefficient of density in Gordon’s equation is very much an upper estimate, the true figure is about half, i.e. about 0.12.

• This fits with an estimate by Peter Hall in 2001 that doubling density would reduce fuel use by about 15%.

• Which, with Gordon’s estimated price elasticity, would be achieved with a price increase of 20%!

Is higher density always good?

• Evidence from Norway and the Netherlands suggests that high density encourages long distance leisure trips.

• The minimum fuel usage is at 60 dwellings to the hectare ( The English minimum was 30)

• But the evidence shows that the overall savings from increasing density are not great.

• (And it also shows that access to a garden reduces leisure travel.)

British Planning Policy

• Build at high density on brown field sites and contain settlements by the use of Green Belts, etc.

• But this results in dispersion and high fuel use.

O d1 d2

Green Belt

Agricultural Value

Distance

Land Value

C

A

DB

Green Belts

Initial land value gradient AB

Urban expansion would lead to new gradient CD

Green Belt prevents development between BD (d1 to d2)

O d1

H

d2

Green Belt

Agricultural Value

Distance

Land Value

E

C

A

F

G

DB

New higher land value gradient EF, GH

1. Stated aims of green belts in planning terms:

i) To check urban sprawl

ii) To safeguard surrounding countryside

iii) To prevent towns merging

iv) To preserve the character of historic towns

v) To assist in urban regeneration

Originally green belts were intended to be fairly narrow and to provide recreation for the towns they surrounded (e.g. the Greater London Plan of 1944)

There is now nothing about recreation and the belts now cover more land than the towns they surround

2. In economic terms these planning aims should result in:

i) Higher land and property values in the contained urban area

ii) Commuting across the Green Belt

iii) Development on the other side of the Green Belt

iv) Amenity (and certainty) would lead to higher property values in and on the edge of the Green Belt

v) Infill and higher density development within the contained urban area

(1) Brownfield Sites

• Does it make sense to build at high density in the countryside because it is a brownfield site?

• For example an old cottage hospital site five miles west of Reading near Bradfield where a bus stops 800m away about once an hour.

(2) Containment round Oxford

• Oxfordshire planned that new housing would be outside Oxford at smaller towns with good public transport.

• The result, increased use of cars to get to work.

• But new housing adjacent to Oxford did not result in more car use.

New Homes in England

• Between 2000 and 2004 there were 500,000 dwellings added to the housing stock in England

• Of which 300,000 were in urban areas

• And 200,000 in rural areas, a large number being conversions and infill in villages

US Evidence

• Where policies of containment are in force fuel use is greater.

• As people commute from one contained area to another.

Conclusion

• The policies that we have are justified by reference to ‘global sustainability’.

• But the evidence for these policies as reducing fuel use and emissions is non-existent at best.

• And there is evidence that they worsen the situation.

• We know that British policies are there for other reasons – some people think high densities are good per se, some people just want to protect the countryside.

• But can we have a little honesty?