SES Areas: Selecting appropriate
scenarios in the CHMA tool
Oxford Economics were commissioned to
evaluate the range of available housing
scenarios in the CHAM HoNDA toolkit and
recommend the range of scenarios selected
for each of the 6 SES areas.
This short report seeks to outline our
selection and justify each, based on the
evidence.
Prepared for Edinburgh City Council
Overview
Executive summary
Introduction and approach
Evidence and rationale
2
Executive summary
Executive summary – approach
 Oxford Economics were asked to examine the range of alternative scenarios available in the Centre
for Housing Market Assessment’s (CHMA) HNDA model for the 6 South Eastern Scotland areas.
 The research undertaken and recommendations made consider the above factors in relative
independence. Thus, we did not consider what impact the factors or scenarios chosen would have
on housing market demand. Instead, we focussed solely on our expectations of which scenarios
best reflected the future outlook for the area.
 Oxford Economics’ Local Model of Administrative Districts (LOMAD) produces economic forecasts
for income, house prices and affordability. These were utilised in the comparison of HNDA
scenarios, with our methodology to recommend the scenario that best represented our baseline
expectations. We applied bespoke methods to inform our thinking regarding income distribution and
intermediate (rental market) demand. An overview of our baseline modelling methodology is
included within the report, and a brief overview of our approach to income distribution and
intermediate demand is below:
 Income distribution: Firstly (and primarily), we focussed on historical trends within the ASHE data.
This was augmented by a review of research we previously undertook in the US and finally checked
against baseline sectoral employment forecasts.
 Intermediate (rental market) demand: we developed a bespoke model based on the average
house price*Bank of England base rate and expected income levels (drawn from our earlier
forecasts). From this, we forecast private rent values across the SES area. Guidance within the
HNDA model suggests that this element of the tool should only be used when the user has a strong
inclination that rental values will move considerably different from house prices
4
Executive summary – scenario recommendations
Area / Input
3a) Income
growth
3b) Income
distribution
4) Prices &
affordability
5) Intermediate
demand
East Lothian
Modest
Increase
Creeping
Inequality
No Real
Growth
No Real
Growth
Edinburgh
Modest
Increase
Creeping
Equality
OBR
Estimates
Modest
Increase
Fife
Modest
Increase
Creeping
Inequality
No Real
Growth
No Real
Growth
Midlothian
Modest
Increase
Creeping
Inequality
No Real
Growth
No Real
Growth
Scottish Borders
Modest
Increase
Creeping
Equality
No Real
Growth
No Real
Growth
West Lothian
Modest
Increase
Flat
Strong
Recovery
Modest
Increase
5
Executive summary – rationale
 The table above outlines the scenarios we would recommend from the HNDA. Our rationale was to
prioritise the longer term trends over those in the short / medium term.
 There is a suitable degree of similarity across the SES areas; indeed, only Edinburgh and West
Lothian show significant variation. The rationale for this is below:
 Edinburgh: Oxford Economics expect the economic recovery to be focussed around professional
(‘tradable’) services, most concentrated in urban areas. As a result, our forecast for the City of
Edinburgh suggests 36,100 additional jobs and 71,100 additional people by 2030. Therefore, it is
not unexpected that the scenario recommendations for the city would vary on the upside from those
in the surrounding areas.
 West Lothian: Development around Edinburgh Airport, in conjunction with the on-going tram line
development in Western Edinburgh has led to an increase in economic activity in the west of the
City which creeps out into the surrounding city region areas. As a result, population in West Lothian
has expanded by over 12% since 2000, and is forecast to grow by a further 12% by 2030 (22,000
additional people). Similarly, employment is expected to grow by 14%. The increased economic
prosperity results in increased demand for housing, thus increasing house prices. The historical
data for income distribution is considerably volatile, hence resulting in ‘flat’ being chosen as the
most appropriate outcome.
 A comprehensive evidence base underpinning our rationale is provided in the main body of the
report. We believe the primary recommendations are the most likely outcomes, but in certain cases,
have suggested an alternative, secondary recommendation.
6
Introduction
Introduction
 Oxford Economics were asked to examine the range of alternative scenarios available in the Centre
for Housing Market Assessment’s (CHMA) HNDA model for the 6 South Eastern Scotland areas. In
particular, we were asked to make recommendations regarding: Income growth, Income
distribution, house prices / affordability and Intermediate (rental market) demand.
 The research undertaken and recommendations made consider the above factors in relative
independence. Thus, we did not consider what impact the factors or scenarios chosen would have
on housing market demand. We focussed solely on our expectations of which scenarios best
reflected the future outlook for the area. We feel this is the most appropriate approach to achieve
genuine independence, as the factors above are likely to move with independence against the
housing market.
 Oxford Economics’ Local Model of Administrative Districts (LOMAD) produces economic forecasts
for income, house prices and affordability. These were utilised in the comparison of HNDA
scenarios, with our methodology to recommend the scenario that best represented our baseline
expectations (Within reason – there were no instances where the difference between our
expectations and HNDA’s options were sufficiently different to require a user-defined input). . We
applied bespoke methods to inform our thinking regarding income distribution and intermediate
(rental market) demand. These are discussed on the next slide.
 It should be noted that the scenario growth rates for income, house prices and rental market
demand within the HNDA do not vary by area. In the interest of transparency, we have provided a
table outlining the growth rate for each immediately following our approach
8
Approach – Income forecasting
Relative workplace based
wages
Historical
Imposed forecast
Aim: Manually checked forecast
Scotland weekly
wage
Scaled to
Scotland forecasts
Final LGD workplace based
weekly wages
9
 Oxford Economics’s LOMAD model uses
the Annual Survey of Hours and Earnings
(ASHE) data and forecasts the average
weekly wage on both a resident and
workplace basis. Our approach to
forecasting wages considers the local
authority's
■ Relative wage in comparison to the Scottish
average;
■ Actual wage / expected wage (ensuring the
sectoral composition of the local economy
has an impact)
Scotland annual  The income data are forecast in nominal
earnings from
terms and are aggregated to ‘average
MRM
annual income’ by multiplying by 52.
 Resident based income was used as a
comparator to the HNDA, in line with the
CACI data used within.
HNDA growth rates – income
CHMA Growth rate, forecast, Income, All
areas, selected years
Source: CHMA
10
Approach – income distribution
 Primarily, we focussed on historical statistical trends, using the Annual Survey of Hours and
Earnings (ASHE). We examined the interquartile range (25th / 75th decile) from 2002-2012; we then
forecast this based on either: a) a trend formula, b) compound annual growth rate formula or c) set
it flat (largely due to volatility in the data). We then considered which outcome was most feasible.
 The vast majority of projected income distribution were set on trend; only West Lothian was set as a
‘flat’ forecast, due to considerable annual volatility in the data.
 This approach was augmented by considering previous research undertaken on income distribution
(Household income distribution in the US, 2011), which suggested a greater creeping equality of
incomes across the US, with more people moving into the higher income brackets. However, where
this viewpoint varied from the empirical evidence, we opted for the latter.
 Finally, we compared the forecast interquartile range trends against sectoral employment forecasts
as a final check. The sectors were broadly classed as ‘high income’ and ‘low income. The aim of
this element of the approach was to ensure that the local economic structure did not vary
sufficiently to suggest the presence of more higher income sectors / lower income sectors over the
forecast period. Whilst there are expected changes in sectoral composition, none were deemed
sufficiently prominent to warrant a change in our initial recommendation. (We wanted to ensure that,
for example, a high income sector such as financial services did not move from employing 10% of
the local workforce to employing 20%; such a move could have led to increasing income inequality).
11
HNDA growth rates – income distribution
CHMA Growth rate, forecast, Income distribution, All
areas, Selected years
Source: CHMA
12
Approach – house prices / affordability
Scotland new
 House price data at a local authority level is notably LGD new house
prices
house prices
volatile. (This is a UK-wide problem and is not unique
Historical
Historical
to Scotland). Oxford Economics source our house
Relative new
price data from the Registers of Scotland. Our
house prices
approach to forecasting local authority house prices
Historical
utilised the behavioural effects within the Scottish
forecasts (derived from our regional model). The
local dimension is driven by:
Imposed forecast
■ Relative wage levels between the local authority and
Scotland;
■ Relative labour market performance (measured through
unemployment levels)
 Our expectations are largely that house prices will
grow in line with inflation – outside Edinburgh and
West Lothian (discussed later), and hence the ‘no
real growth’ option was common. In reality, there is
likely to be a greater upside risk, thus suggesting
house price growth could be stronger than forecast
here.
13
Aim: Manually
checked forecast
Scotland new house
price from MRM
Raw LGD new
house price
Scaled to Scotland
new house prices
Final LGD new
house price
Weighted
average of new
house prices
and population
HNDA growth rates – house prices
CHMA Growth rate, forecasts, House Prices, All areas,
Selected Areas
Source: CHMA
14
Approach – intermediate (rental market) demand
 The intermediate rental market demand scenarios were informed by recent research undertaken on
rental prices and rental demand by Oxford Economics for the National Housing Federation across
English regions.
 The literature review undertaken in this research was utilised to inform our thinking about what the
factors that drive rental prices. Fahri and Young (2010, University of Auckland) examined private
residential rents across New Zealand cities and noted that private rents are primarily driven by:
■ Supply side; mortgage interest payments on buy-to-let properties); and
■ Demand side: ability to pay (income).
 Thus we developed a bespoke model based on the average house price*Bank of England base rate
and expected income levels (drawn from our earlier forecasts). From this, we forecast private rent
values across the SES area.
 Guidance within the HNDA model suggests that this element of the tool should only be used when
the user has a strong inclination that rental values will move considerably differently from house
prices. Therefore, in instances where rental growth was suitably similar to house price growth –
East Lothian, Fife, Midlothian, and Borders), we recommend keeping rents in line with house
prices. Only in Edinburgh and West Lothian, where house price growth is expected to be strongest,
do we suggest a different outcome – that intermediate demand be set ‘1 scenario slower’ than
house prices.
15
HNDA growth rates – intermediate demand
CHMA Growth rate, forecasts, Intermediate Demand, All
areas, Selected Years
Source: CHMA
16
Approach – datasets used (1)
Scenario
Dataset
Last year
of data
Notes
Income growth
Annual Survey of Hours
and Earnings (AHSE)
2012
Median, Gross pay, all workers,
residence based
Oxford Economics
LOMAD Model
2012, with
forecasts to
2030
Median, Gross pay, all workers,
residence based
Annual Survey of Hours
and Earnings (AHSE)
2012
Median wage and percentile
data, with distribution measures
as the ratio of the 25/75 deciles
(as it the methodology in CHMA).
All workers, residence based.
Oxford Economics
LOMAD Model
2012, with
forecasts to
2030
Employment by sector forecasts
were utilised to provide an insight
into employment structure and
what the implications of this
might be for income distribution
Register of Scotland:
Local Authority
Residential Property
Data
June 2013
Mean values. The quarterly data
are converted to an annual
series using a weighted average
based on transactions (from the
same report).
Income distribution
House prices
17
Approach – datasets used (2)
Scenario
Dataset
Last year
of data
Notes
House prices
Register of Scotland:
Local Authority
Residential Property
Data
June 2013
Mean values. The quarterly data
are converted to an annual
series using a weighted average
based on transactions (from the
same report).
Oxford Economics
LOMAD Model
2013 (half
year), with
forecast to
2030
The forecasts are driven by
demand for housing (as
measured by population
increases), relative income
increases (using personal
disposable income, which
incorporates interest rate
changes) and changes in
unemployment as a labour
market proxy.
Scottish Government –
Housing Statistics for
Scotland (key
information and
summary tables)
2012
The intermediate demand figures
were estimated using a
regression equation based on
leading academic literature. The
Scottish social rental data by
local authority was used to
‘sense check’ the estimates.
Intermediate demand
18
Rationale and evidence
Rationale – the evidence (overview)
 This section relays the empirical evidence on which the recommendations are based.
Specifically:
■ Income growth: A line chart compares the Oxford Economics baseline (our basis for the
recommendation) against the scenario chosen from HNDA. This will allow the reader to
compare the variation in the two. In no instance did we feel it sufficient to warrant the
development of a new scenario. A table also compares the Oxford baseline growth rate against
the range of scenarios in the HNDA.
■ Income distribution: For each area, a line chart is plotted to show how the income distribution
measure (the interquartile range) is forecast to change. This shows the Oxford expectation, the
scenario we recommend and all other scenarios.
■ House prices / affordability: A line chart highlighting how the Oxford baseline compares
against the scenario chosen is provided, along with a table of annual average growth rates, to
allow the user to compare how the range of scenario options (and OE baseline) compare.
■ Intermediate (rental market demand): A table comparing the annual average growth rate of
our rent prices against the house prices is included to show how they compare. As noted
earlier, the emphasis of this scenario within HNDA is that the core assumption should be the
same as the expectation of house prices, unless there is sufficient reason to believe otherwise.
20
East Lothian – Income growth
East Lothian Income Growth
Index, 2011 - 2032
The ‘modest increase’ scenario
suggests that the average
income will increase to £57,550
in 2030, from £29,700 currently.
Note: Option highlighted in yellow is the
desired scenario
21
East Lothian – income distribution
East Lothian Income
Distribution, 2011 - 2032
Forecast
22
We recommend scenario
creeping inequality, which
forecasts that the average
higher earner will earn 3.8
times the average lower
earner, a change of 1.9
from current levels.
East Lothian – house prices
East Lothian House Price
Index, 2011 - 2030
The ‘no real growth’ scenario
suggests that the average
income will increase to £544,000
in 2030, from £371,800 currently.
Note: Option highlighted in yellow is the
desired scenario
23
East Lothian – intermediate demand
Rental market price Increases, In Comparison with
House Prices, East Lothian, 2013 - 2030
Note: Option highlighted in yellow is the desired
scenario
Additional Note: Rental market – median growth
House Prices – Mean growth
24
Edinburgh – Income growth
Edinburgh Income Growth
Index, 2011 - 2032
The ‘modest increase’ scenario
suggests that the average
income will increase to £57,800
in 2030, from £31,500 currently.
Note: Option highlighted in yellow is the
desired scenario
25
Edinburgh – income distribution
Edinburgh Income
Distribution, 2011 -2032
Forecast
We recommend scenario
creeping equality, which
forecasts that the average
higher earner will earn 2.7
times the average lower
earner, a change of 0.7 from
current levels.
Alternatively, the second
choice – should it be required,
would be a flat income
distribution, as it is likely there
will always be a presence of
high value added jobs in
Edinburgh with high levels of
remuneration.
26
Edinburgh – house prices
Edinburgh House Price Index,
2011 - 2030
The ‘OBR estimate’ scenario
suggests that the average
income will increase to £539,500
in 2030, from £269,000 currently.
A modest recovery would be an
alternative choice; the growth
rate over the period is similar, but
the modest recovery suggests a
higher level of growth in the short
term.
OE Forecast
OBR Estimate
No Real Growth
Flat
Modest Recovery
Strong Recovery
Gradual Decline
27
Average Annual %
growth 2011-2030
3.8
3.8
2.2
1.2
3.5
4.6
0.1
Note: Option highlighted in yellow is the
desired scenario
Edinburgh – intermediate demand
Rental market price Increases, In Comparison with
House Prices, Edinburgh, 2013 - 2030
Based on the
analysis
undertaken, no real
growth is our
recommended
scenario.
However, modest
increase is an
alternative option.
Note: Option highlighted in yellow is the desired
scenario
Additional Note: Rental market – median growth
House Prices – Mean growth
28
Fife – Income growth
Fife Income Growth Index,
2011 - 2032
The ‘modest increase’ scenario
suggests that the average
income will increase to £51,600
in 2030, from £28,050 currently.
Note: Option highlighted in yellow is the
desired scenario
29
Fife – income distribution
Fife Index Distribution,
2011 -2032
Forecast
30
We recommend scenario
creeping inequality, which
forecasts that the average
higher earner will earn 3.9
times the average lower
earner, a change of 1.5
from current levels.
Fife – house prices
Fife House Price Index,
2011 - 2030
The ‘no real growth’ scenario
suggests that the average
income will increase to £234,000
in 2030, from £159,900 currently.
Note: Option highlighted in yellow is the
desired scenario
31
Fife – intermediate demand
Rental market price Increases, In Comparison with
House Prices, Fife, 2013 - 2030
Note: Option highlighted in yellow is the desired
scenario
Additional Note: Rental market – median growth
House Prices – Mean growth
32
Midlothian – Income growth
Midlothian Income Growth
Index, 2011 -2032
The ‘modest increase’ scenario
suggests that the average
income will increase to £54,750
in 2030, from £29,250 currently.
Note: Option highlighted in yellow is the
desired scenario
33
Midlothian – income distribution
Midlothian Income
Distribution, 2011 -2032
Forecast
We recommend scenario
creeping inequality, which
forecasts that the average
higher earner will earn 3.8
times the average lower
earner, a change of 1.9 from
current levels.
Alternatively, the second
choice – should it be required,
would be a flat income
distribution,
34
Midlothian – house prices
Midlothian House Price Index,
2011 -2030
The ‘no real growth’ scenario
suggests that the average
income will increase to £265,900
in 2030, from £181,700 currently.
Note: Option highlighted in yellow is the
desired scenario
35
Midlothian – intermediate demand
Rental market price Increases, In Comparison with
House Prices, Midlothian, 2013 - 2030
Note: Option highlighted in yellow is the desired
scenario
Additional Note: Rental market – median growth
House Prices – Mean growth
36
Scottish Borders – Income growth
Scottish Borders Income
Growth Index, 2011 -2032
The ‘modest increase’ scenario
suggests that the average
income will increase to £48,750
in 2030, from £26,500 currently.
Note: Option highlighted in yellow is the
desired scenario
37
Scottish Borders – income distribution
Scottish Borders Income
Distribution, 2011 - 2032
Forecast
We recommend scenario
creeping equality, which
forecasts that the average
higher earner will earn 2.6
times the average lower
earner, a change of 0.4 from
current levels.
Alternatively, the second
choice – should it be
required, would be a flat
income distribution,
38
Scottish Borders – house prices
Scottish Borders House Price
Index, 2011 - 2030
Forecast
The ‘no real growth’ scenario
suggests that the average
income will increase to £307,350
in 2030, from £206,240 currently.
Note: Option highlighted in yellow is the
desired scenario
39
Scottish Borders – intermediate demand
Rental market price Increases, In Comparison with
House Prices, Scottish Borders, 2013 - 2030
Note: Option highlighted in yellow is the desired
scenario
Additional Note: Rental market – median growth
House Prices – Mean growth
40
West Lothian – Income growth
West Lothian Income Growth
Index, 2011 - 2032
The ‘modest increase’ scenario
suggests that the average
income will increase to £55,300
in 2030, from £30,100 currently.
Note: Option highlighted in yellow is the
desired scenario
41
West Lothian – income distribution
West Lothian Income
Distribution, 2011 -2032
Forecast
We recommend scenario
flat, which forecasts that the
average higher earner will
earn 3.4 times the average
lower earner, a change of
1.3 from current levels.
Alternatively, West Lothian
is amongst the fastest
growing areas in Scotland
and as such, creeping
inequality could be
considered as a second
option.
42
West Lothian – house prices
West Lothian House Price
Index, 2011 - 2030
The ‘strong recovery’ scenario
suggests that the average
income will increase to £331,750
in 2030, from £151,800 currently.
Note: Option highlighted in yellow is the
desired scenario
43
West Lothian – intermediate demand
Rental market price Increases, In Comparison with
House Prices, West Lothian, 2013 - 2030
Note: Option highlighted in yellow is the desired
scenario
Additional Note: Rental market – median growth
House Prices – Mean growth
44
Based on the
analysis
undertaken, modest
growth is our
recommended
scenario.
However, the strong
growth in West
Lothian could lead
to it emerging as a
preferred location to
live, and hence
strong recovery
could be considered
as a second option.
Contact Details:
Alan Mitchell
Senior Economist
Oxford Economics
Tel: 028 9263 5412
amitchell@oxfordeconomics.com