NTEM: Planning Data Version 6
Source: data.gov.uk (2024-07-04)

National Trip End Model (NTEM). The [freely available TEMPro software is required to view these datasets](https://www.gov.uk/government/publications/tempro-downloads).

The National Trip End Model (NTEM) model forecasts the growth in trip origin-destinations (or productions-attractions) up to 2051 for use in transport modelling. The forecasts take into account national projections of:

- population
- employment
- housing
- car ownership
- trip rates

NTEM forecasts are subject to uncertainty, especially when disaggregated to local zones or travel modes. Before using the NTEM forecasts, the following DfT guidance should be reviewed: 

- [TAG Unit M-4 Forecasting and Uncertainty](https://www.gov.uk/government/publications/webtag-tag-unit-m4-forecasting-and-uncertainty-november-2014) 
- [NTEM Planning Guidance](https://assets.dft.gov.uk/tempro/version7.2/NTEM72-documentation.zip) that provides an overview of the forecasts and the input data used (available in the NTEM Documentation Download below). 

Further technical details are available in the [NTEM specification](https://www.gov.uk/government/publications/webtag-si-ntem-sub-models-july-2016).

Queries regarding the NTEM forecasts should be sent to [Department for Transport](mailto:tempro@dft.gov.uk). To register to receive updates, email [TEMProMailingList@atkinsglobal.com](TEMProMailingList@atkinsglobal.com) to be added to the TEMPro distribution list. 

[GIS boundary files for the NTEM zone system are available](https://data.gov.uk/dataset/visual-boundaries-for-the-national-trip-end-model-ntem).

NTEM Planning Data Version 6.2
Guidance Note

Department for Transport
May 2011

QM

Issue/revision
Issue 1
Revision 1
Revision 2
Revision 3
Remarks
Final Draft for
Client review
Issue
Maps updated to
2011/2031
Final

Date
09 May 2011
2 June 2011
8 June 2011

Prepared by
Duncan Forbes
Clare Lindsay
Andrew Young
Clare Lindsay
(+DfT Appendix F)
Clare Lindsay

Signature
C L F Lindsay
C L F Lindsay
C L F Lindsay

Checked by
Kaveh Jahanshahi
Kaveh Jahanshahi
Kaveh Jahanshahi
Signature
K Jahanshahi
K Jahanshahi
K Jahanshahi

Authorised by
Clare Lindsay
Clare Lindsay
Clare Lindsay

Signature
C L F Lindsay
C L F Lindsay
C L F Lindsay

Project number
11642097
11642097
11642097

File reference
Reports\
Guidance\
NTEM62
Guidance _ draft
Reports\
Guidance\
NTEM62
Guidance 2.2
Reports\
Guidance\
NTEM62_
Guidance

WSP Development and Transportation
66-68 Hills Road
Cambridge
CB2 1LA

Tel: xx-xxxx-xxxx
Fax: xx-xxxx-xxxx
http://www.wspgroup.com

WSP UK Limited | Registered Address WSP House, 70 Chancery Lane, London, WC2A 1AF, UK | Reg No. xx-xxxx-xxxx England | WSP Group plc | Offices worldwide

Contents

1
Introduction
1
1.1
Overview
1
1.2
Summary of changes for NTEM 6.2
1
1.3
Outline of NTEM Forecasting process
4
2
Planning Data Methodology
6
2.1
Summary
6
2.2
Objective
6
2.3
Basic inputs and spatial definitions
8
2.4
Households by control area
10
2.5
Population by control area
13
2.6
Population and households by zone
14
2.7
Employment and workers by zone
15
2.8
Balance workforce and workers
15
2.9
Update Employment forecasts for change in worker profile
21
2.10
Summary of outputs from the Scenario Generator
22
3
Data for 2001 Base Year
23
3.1
Summary
23
3.2
Base year population
23
3.3
Households
25
3.4
Dwellings
26
3.5
Base year employment (jobs)
26
4
Forecast Data and Projections
30
4.1
Summary
30
4.2
Forecast population data
30
4.3
Forecast households data
32
4.4
Policy-based dwellings data
34
4.5
Forecast employment data
37
5
Expected Growth Factors
40
5.1
Summary
40
5.2
Household EGFs
41
5.3
Employment EGFs
45
6
Planning Data Results
47
6.1
Introduction
47

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6.2
Planning data (Scenario Generator)
47
6.3
National Car Ownership Model
57
6.4
National Trip End Model
61

Appendix A
Geography
Appendix B
Segmentation - Definitions
Appendix C
Source of Dwellings Input Assumptions (AMRs)
Appendix D
Demographic Parameters
Appendix E
Mathematical Specification of Methodology
Appendix F
Employment Forecasting Methodology

LIST OF TABLES
Table 2.1 Control total checks before Scenario Generator data processing .................. 10
Table 3.1 Data sources used in deriving base population by NTEM zone ..................... 24
Table 3.2 Population by gender, age group and working status in Great Britain, 2001 . 25
Table 3.3 Regional household control totals by size for the 2001 base year (thousands)
........................................................................................................................................ 26
Table 3.4 Regional dwelling control totals for 2001 base year (thousands) ................... 26
Table 3.5 NTEM employment types ............................................................................... 27
Table 3.6 Data sources used to derive base year employment by NTEM zone ............. 28
Table 3.7 Correspondence between EBS and NTEM employment types ...................... 28
Table 3.8 Jobs in each NTEM category by gender and working status in Great Britain,
2001 (thousands) ............................................................................................................ 29
Table 4.1 Total population projections by region, 2006-2041 (thousands)..................... 31
Table 4.2 Household projections by Region for single person households, 2006-2041
(thousands) ..................................................................................................................... 34
Table 4.3 Household projections by Region for 2+ person households, 2006-2041 ...... 34
Table 4.4: Source of dwelling trajectories for the Welsh Local Authorities ...................... 36
Table 4.5 Dwellings by region, 2006-2041 (thousands) ................................................. 37
Table 4.6 Total employment (jobs) by NTEM sector, 2001 – 2041 (thousands) ............. 39
Table 5.1 Household growth by region and area type .................................................... 43
Table 5.2 Potential source of EGFs for each NTEM employment type a ....................... 46
Table 6.1 Comparison of planning data for Great Britain, v6.2 and v5.4 ........................ 52
Table 6.2 Household car ownership in Great Britain, v6.2 versus v5.4 .......................... 57
Table 6.3 Comparison of total trip productions for Great Britain between v6.2 and v5.4
(millions per average day) ............................................................................................... 61

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LIST OF FIGURES
Figure 1.1 Basic steps in generating the NTEM 6.2 dataset ............................................ 4
Figure 1.2 Structure of a possible series of scenario tests using Scenario Generator ..... 5
Figure 2.1 Summary of planning data forecasting process .............................................. 7
Figure 2.2 First estimate of households by type in each control area based on the
change in population ....................................................................................................... 11
Figure 2.3 Allocation of households to control areas...................................................... 13
Figure 2.4 Derivation of households and population by zone......................................... 14
Figure 2.5 Estimation of population based on potential decrease in zonal populations or
decreasing worker types within a balancing area ............................................................ 17
Figure 2.6 Derivation of maximum number of workers in each zone by age, gender and
employment type ............................................................................................................. 18
Figure 2.7 Allocation of workers by age and gender in a balancing area ....................... 19
Figure 2.8 Allocating workers from balancing areas to zones ........................................ 21
Figure 4.1 Population projections, females (thousands), 2006-2041 ............................. 31
Figure 4.2 Population projections, males (thousands), 2006-2041 ................................ 31
Figure 4.3 Average household size by region based on input data, 2006-2041 ............ 33
Figure 4.4 Household projections by Region for single person households, 2006-2041
(thousands) ..................................................................................................................... 33
Figure 4.5 Household projections by Region for 2+ person households, 2006-2041
(thousands) ..................................................................................................................... 33
Figure 4.6 Dwelling forecasts, 2006-2041 (thousands) .................................................. 37
Figure 4.7 Forecast of total employment (jobs) by region, 2006-2041 (thousands) ....... 38
Figure 5.1 Expected growth factors applied as weights and trends ............................... 40
Figure 5.2 2001 Planning area types used in household EGF calculation ..................... 42
Figure 5.3 Expected Growth Factors for households (district control areas) ........ 45
Figure 6.1 Average household sizes in each study area ................................................ 47
Figure 6.2 Average household size by district in 2021 ................................................... 48
Figure 6.3 Vacancy rates by district in 2021................................................................... 48
Figure 6.4 Household capacity before reallocating or suppressing excess households 49
Figure 6.5 Households suppressed ............................................................................ 49
Figure 6.6 Remaining Vacant Dwellings after reallocation process ............................... 50
Figure 6.7 Ratio of workers to jobs by Region over time ................................................ 51
Figure 6.8 Comparison of planning data output totals, v6.2 versus v5.4........................ 52
Figure 6.9 Relative difference in population, households and employed persons in 2021
(NTEM 6.2 planning data versus NTEM 5.4)................................................................... 53
Figure 6.10 Absolute difference in population, households and employed persons in
2021 (NTEM 6.2 planning data versus NTEM 5.4, thousands) ....................................... 54
Figure 6.11 Growth in total population 2011-2031 by zone in NTEM 6.2 (left) and NTEM
5.4 (right) ......................................................................................................................... 55
Figure 6.12 Growth in total households 2011-2031 by zone in NTEM 6.2 (left) and
NTEM 5.4 (right) .............................................................................................................. 55
Figure 6.13 Relative difference in total employment (jobs) by zone, 2011 – 2031; NTEM
6.2 (left) and NTEM 5.4 (right) ......................................................................................... 56
Figure 6.14 Car ownership through time (v6.2 versus v5.4)........................................... 58
Figure 6.15 Cars per household 2031 by zone, NTEM 6.2 (left) and NTEM 5.4 (right) . 58
Figure 6.16 District growth in households by car ownership, 2011-2031, NTEM 6.2 ..... 59
Figure 6.17 Difference in proportion of household car ownership 2031 by zone between
NTEM versions (v6.2 proportion minus v5.4 proportion of total households) .................. 60
Figure 6.18 Change in Trip Productions over time: NTEM 6.2 v NTEM 5.4 (millions) ... 61
Figure 6.19 Total trips in the average day by purpose in Great Britain, NTEM 6.2 ........ 62
Figure 6.20 Relative difference in total trips by purpose over time in Great Britain; NTEM
6.2 v NTEM 5.4 ............................................................................................................... 63
Figure 6.21 Trips per households by study area in the average day, NTEM 6.2 ........... 63
Figure 6.22 Trips per households by study area in the average day, NTEM 5.4 ........... 64
Figure 6.23 Trips per person by study area in the average day, NTEM v6.2 ................. 64

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Figure 6.24 Growth in trip productions and attractions by district, 2011-2031,
comparison between versions ......................................................................................... 65
Figure 6.25 Rate of growth of modal trip ends (NTEM 6.2 v NTEM 5.4) ....................... 66

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1
Introduction
1.1
OVERVIEW
1.1.1
This introduction provides an overview of the processes, methodology and data
sources used to produce the NTEM 6.2 planning data set.
1.1.2
Section 2 describes the methodology used to convert the input assumptions
into coherent planning data forecasts. This methodology is implemented in a bespoke
software tool, the Scenario Generator, which was redesigned for version 5 and remains
virtually unchanged for version 6.2. This section traces logically through the forecasting
process, attempting to explain the more complex issues diagrammatically. The
mathematical specification of this process is provided in Appendix E.
1.1.3
Section 3 describes the data sources used in the derivation of 2001 base year
inputs. These include population, households, dwellings and employment, segmented
into the required dimensions.
1.1.4
Section 4 describes the forecast data requirements needed by the Scenario
Generator. This covers use of trend-based population, household and employment
figures. The production of a policy-based data set for dwellings and the consultation
process is also described in this section.
1.1.5
Section 5 describes the derivation of Expected Growth Factors used within the
forecasting process. This includes a brief methodological overview and worked
examples.
1.1.6
Section 6 summarises some of the initial results output from the forecasting
process that represent the initial set of forecast planning data, to be subjected to further
consultation with the Regional Planning Bodies.

1.2
SUMMARY OF CHANGES FOR NTEM 6.2
1.2.1
The following elements have been enhanced for NTEM 6.2 (compared with the
earlier NTEM 5.4 dataset):
 Policy-based input dwelling assumptions through time for all Great Britain based
initially on consultation with Regional Planning Bodies, and more recently based on
Local Authorities published housing trajectories.
 The data sources have been updated. NTEM 6.2 uses 2008 based population
projections and the 2008 based household projections; dwellings data for England,
Wales and Scotland reflect the latest Local Authority plans; and the employment
forecast data reflects the effect of the recent recession, using the latest employment
forecasts available from the Office for Budget Responsibility and HM Treasury. The
car ownership forecasts have also been updated with the most recent GDP
forecasts, and also to take into account the decline in car purchasing costs in real
terms between 2001 and 2009.
 The employment forecasting method has been updated.
1.2.2
The following elements have been retained for NTEM 6.2 (compared with the
earlier NTEM 5.4 dataset):
 2001 Census Output Area based NTEM zone geography, with 2,496 zones nested
within local authority districts.

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 Input planning data set to a 2001 base, primarily making use of the 2001 Census of
Population
 Revised approach for the allocation of population and households to zones
 Choice of using weight or trend based growth factoring method in the Scenario
Generator to produce zonal estimates of population and employment.
 Greater segmentation of population data (eg two working age groups, greater
segmentation of elderly age group)
 Flexibility to allow changing definitions of Control Areas and Study Areas in the
Scenario Generator
 Internal adjustment of workforce demand based on supply of available population
1.2.3
The employment data forecasts for NTEM V6.2 are slightly lower than those
adopted for the V5.4 dataset. This results in fewer commuting and business trips in v6.2
compared with v5.4, though the impact on overall travel demand is small.
1.2.4
A number of features of NTEM 6.2 are now discussed in more detail.
GEOGRAPHY
1.2.5
The main spatial unit in NTEM, the NTEM zone, was completely revised for
version 5 of its release. These are now based on 2001 Census Output Areas (2003
based geography) to give a good representation of urbanicity and rurality at a refined
level of geographical detail. There are 2,496 NTEM zones in Great Britain.
1.2.6
The country has been divided into nine “study areas” to represent each Region
of the country. London, the South East and East of England Regions are combined into
a single study area. Intermediate between the zones and the study areas are a set of
control areas to which forecasts are constrained based on administrative boundaries.
The concept of a “balancing area” is retained within which workers at the residence and
workplace end are balanced. The definitions are updated to be compatible with the
revised NTEM zones.
1.2.7
See Appendix A for a map of the new NTEM zones overlaid on defined study
areas and the set of balancing areas used.
UPDATE TO 2001 BASE YEAR
1.2.8
A major pre-processing step in the production of the NTEM planning data for
version 5 was the update to the 2001 base year. This involved extensive use of the
2001 Census of Population. This allowed a considerable level of detail where data may
be obtained at the Output Area level. Indeed, the new NTEM zoning system was
designed to allow for this capability.
1.2.9
Since the construction of NTEM 5.4, new data sources have come to light
which suggest that the distribution of jobs by Region, and the total workers, in 2001 may
have been slightly different to that used in NTEM 5.4. The 2001 planning data has been
updated accordingly.
1.2.10
Generation of the 2001 base data is described in detail in Section 3 of this
guidance note.

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POLICY-BASED DWELLING INPUTS
1.2.11
NTEM 6.2 is based on policy-based forecasts of dwellings in future years. For
NTEM 5.4 the policy-based approach originally involved consultation with each of the
eleven Regional Planning Bodies in Great Britain, which cover Wales, Scotland and the
Government Office Regions in England. More recently this approach has been revised
to use the local authorities’ latest projections, taken from their Annual Monitoring
Reports. It is intended that this will produce future year planning forecast based on
expected realistic development plans. These will hence be of more value when
analysing future patterns of land use and transport.
1.2.12
The primary policy-based element of the data is in the dwelling forecasts. Input
household and population data remains primarily trend-based, although the forecasts
are adjusted by the Scenario Generator for consistency with the policy based dwellings
forecasts. This approach may potentially be adjusted where further consultation or
guidance provides a more realistic insight.
ALLOCATION OF POPULATION AND HOUSEHOLDS
1.2.13
A revised approach is implemented for the allocation of population and
household projections to take account of the availability of dwelling space. Where
household capacity does not meet demand in a specific control area (district),
households will attempt to move to other control areas within the study area (ie Region).
Where spare capacity is not available in the study area overall, household formation
rates are reduced with an implied increase in household size. The level of household
formation may be specified. This affects the propensity for households to relocate to
different areas or for input projections to be reduced.
DIFFERENTIAL GROWTH RATES
1.2.14
Differential growth or decline in employment by sector alters employment rates
for population groups. If the maximum employment rate is reached for any population
group, the gender and then the working status profile of the workforce demanded (ie full
time or part time) is adjusted. For example, if the supply of male full time workers is
exceeded by the demand in a specific area, female full time workers may take their
place as long as the growth in female full time workers allows. This is part of the
balancing of workforce and workers process, where everything is controlled to balancing
area totals.
1.2.15
When applying growth factors to derive households or employment by zone in
the forecasting process, the enhanced Scenario Generator allows the use of growth
factors based on “weights” or “trends”. In both cases the growth factors are used to
scale the previous amount of activity in a zone. This process will over or underestimate
the required change in activity for the study area (Region) as a whole. The subsequent
adjustment made to the growth factors to get the required total in the two approaches
differs. When using weights the growth factors are adjusted proportionally, while trends
based growth factors are adjusted additively. This allows a greater degree of
sophistication in applying growth and caters for situations where a mixture of growth and
decline is forecast within the same control area. This is covered in more detail in
Section 5.

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1.3
OUTLINE OF NTEM FORECASTING PROCESS
1.3.1
The complete process involved in the production of NTEM forecasts can be
seen in Figure 1.1. The process of creating forecast year planning data that concerns
the core of this note involves running through the Scenario Generator that creates
planning data forecasts for input into the National Car Ownership and National Trip End
Models.

Figure 1.1 Basic steps in generating the NTEM 6.2 dataset

1.3.2
The Scenario Generator software reads in projections for population,
households, dwellings and employment at a relatively coarse level. In the case of policy
based dwelling inputs these are extracted from published local authority trajectories.
The software also reads in a set of Expected Growth Factors (EGFs), representing the
levels of growth that would be expected in each zone, as a function of the area type of
that zone, or the observed changes in employment premises.
1.3.3
The software uses the base year demographic characteristics of each zone
from the 2001 Census of Population. From this, the county/district level projections and
the growth factors are used to generate consistent future year planning data at the zonal
level. The process runs incrementally through time, with coarse-level changes over the
next period being applied to the detailed zone-level results of the previous scenario.
This process has been implemented in five year steps for each study area (roughly
equivalent to the Government Office Regions, Scotland and Wales), to a forecast year of
2041. Intermediate years released in the NTEM dataset are generated through linear
interpolation between the five year Scenario Generator forecasts

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1.3.4
Figure 1.2 shows the general structure of a series of forecast runs for a
particular study area. Each subsequent scenario builds on the last and at each point
results may be exported to the National Trip End Model and the National Car Ownership
Model. It is also possible to branch at a certain point and test different planning data
inputs beginning from the results of a forecast scenario.

Figure 1.2 Structure of a possible series of scenario tests using Scenario
Generator

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2
Planning Data Methodology
2.1
SUMMARY
2.1.1
The Scenario Generator is a software tool that produces planning data sets by
using base and forecast data supplied by the user at various levels of geographical and
other detail. These forecasts are designed to be produced for five year intervals from
2001 to 2041. The software is flexible enough to allow forecasting for any required
period at any spatial level given the availability of adequate data input.
2.1.2
For the version 5 (and subsequent) NTEM datasets, this tool has been
redesigned in order to run with a new system of NTEM zones based on 2001 Census
Output Area geography. Several methodological components have also been included
in the enhanced software.
2.1.3
This section outlines the steps that the Scenario Generator performs to
produce a consistent set of planning data forecasts. For specific information on the use
of the software itself, refer to the Scenario Generator User Guide, delivered as part of
the TEMPRO version 5 update.
2.2
OBJECTIVE
2.2.1
The objective of the Scenario Generator is to produce a set of consistent
forecasts of population, households and employment for a set of NTEM zones. The
planning data forecasts are obtained by scaling up or down a set of “previous” zone
specific forecasts to match a new set of control totals for more aggregate areas (districts
/ counties etc) that are input by the user. Pre-processing of forecast data is required to
obtain the initial input control totals.
2.2.2
For each of the main variables there are a set of type categories as follows:

Employment by sector, gender and hours (full / part time)

Population by gender, age and working status

Households by size
2.2.3
Figure 2.1 shows a basic summary of the steps in producing forecast planning
data at the NTEM zone level. The fundamental steps are as follows:
 Derive detailed demographic data for the starting year (ie base data or use a
previously generated scenario)
 Derive future year data from planning projections or policy-based data sets
 Use expected growth factors to assign change in control area totals to the NTEM
zone level
 Balance workforce and workers within a balancing area
 Update worker profile for changes in employment forecasts
 Output planning data for input into the National Car Ownership and Trip End models

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Figure 2.1 Summary of planning data forecasting process

2.2.4
The resulting planning data forecasts are aggregated into fewer categories for
use within the national car ownership and trip end models. These may be exported from
the Scenario Generator in the precise form required by these models.

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2.3
BASIC INPUTS AND SPATIAL DEFINITIONS
STUDY AREA
2.3.1
The methodology assumes that planning data forecasts for each Study Area
will be wholly independent of those for other Study Areas in Great Britain. The Study
Areas have been defined as the Government Office Regions in England, plus Scotland
and Wales. One exception is for the South East, East of England and London Regions.
These three are considered as one Study Area- the Wider South East- since London has
a large impact on working and commuting patterns on its surrounding Regions. The
user may generate forecasts for any one of the Study Areas specified. Multiple Study
Areas may be run in batch. This allows separate updates to be made for each Region
where specific forecast planning data may be obtained in the future.
CONTROL AREAS
2.3.2
Within each study area, forecast data from various projections or policy-based
sources are likely to be provided at a spatial level between NTEM zone and the Region
as a whole. These are defined prior to using the Scenario Generator and are referred to
as Control Areas. This allows the software to bridge the gap between NTEM zones and
the Study Area as a whole. In principle Control Areas could be any level of spatial
aggregation that sits between the NTEM zone definitions and the study area definition,
ie:
NTEM zones  control areas  study area
2.3.3
Two Control Area schemes exist for the main data types:
 Population-based (population, households and dwellings)
 Employment-based (workers and jobs)
2.3.4
For version 6.x of the NTEM datasets, the population-based and the
employment-based Control Areas are both at the local authority district level. This fits in
with the main sources of forecast projections, ie ONS/DCLG population and household
projections and the employment projections.
BASIC INPUT DATA
2.3.5
There are three main planning data inputs to the forecasting process:
households, population and employment (jobs). These input data are typically
government provided trend based projections which may be modified during the process
of developing a coherent set of planning led forecasts. The input variables are:
 Households by size in the study area (Region) for each forecast year
 Population by gender and age for each control area in each forecast year
 Employment (=jobs) by sector, gender and working status in the control area for each
forecast year
2.3.6
The policy based inputs which influence the allocation of population and
workers in the forecasting process are determined from projections of dwellings and
growth factors that represent expected / likely patterns of development.
 Dwellings in each control area in forecast year
 Expected growth factors in each zone for employment type for the time period

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 Expected growth factors in each zone for households (all types) for the time period
2.3.7
As outlined Sections 3 and 4, all working data is adjusted to mid-year estimates
to avoid issues of under-enumeration that may be evident from basic 2001 Census data.
The method of adjusting the data is covered in these sections.
2.3.8
In addition to the basic input, several control parameters are required in each
forecast run. These are base and forecast parameters that are generally global in
nature, controlling the performance of the model. These parameters are described in
more detail in Appendix D.

POPULATION AND HOUSEHOLDS TOTALS
2.3.9
The input population projections require adjustment to account for those
persons not living in households who are excluded from this forecasting process. These
are people who live / work in communal establishments which include residential care
homes, student halls of residence, military barracks and prisons.
2.3.10
According to the 2001 Census 1.8% of the population of England is not
resident in households. Further analysis of the data demonstrates that the proportion of
the population in communal establishments varies dramatically by age and to some
extent by gender. The largest groups of the population not resident in households are
students, mainly between 16-29 and elderly persons aged 65 and over.
2.3.11
There are also marked variations by gender which are most noticeable for the
bulk of the adult population (eg 30-65) where a higher proportion of males are resident in
communal establishments and the elderly where the proportions are greater for females.
2.3.12
There appears to be only a limited variation in the proportions of institutional
variation in the different Regions of the country with the South West having the greatest
proportion of elderly in institutions and the South East having more of the younger
people (students) residing in institutions.
2.3.13
A set of factors is applied at a fairly detailed breakdown of age, greater than the
four main life-stage segments in the model. These are described in Appendix D and
presented later in Table D.3 and Table D.4.
2.3.14
The household totals input are taken directly from government projections as
the totals for the Study Area / Region and summed over household types. This initial
estimate is checked against input dwellings figures and may be subsequently adjusted.
JOBS AND WORKERS TOTALS
2.3.15
A total number of jobs (employment) at the Local Authority (control area) level
in each forecast year are provided as an input. This information is used to scale the jobs
from the previous scenario which are then aggregated to give the study area totals.
2.3.16
To relate the employment measured in units of jobs to the population measured
in units of persons in employment, the numbers of workers are required. A set of factors
is derived to relate the numbers of workers to the numbers of jobs. These are described
in Appendix D.

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CONTROL TOTAL CHECKS
2.3.17
Having established the total numbers of households, people, workers and jobs
some checks are made by the Scenario Generator on the totals to ensure that they are
logically coherent before they are disaggregated both spatially and into the categories
required for the car ownership and trip end models. The user imposes the acceptable
boundary that each variable should fall within.
2.3.18
The ratios of interest are as follows, including the default limits set up in the
system. These are all checked for consistency at the Study Area level.
Table 2.1 Control total checks before Scenario Generator data processing
Ratio
Lower limit
Upper limit
Average adults per household
1
3
Workers to population (employment rate) by
gender and age group
50% in general
90% in general
Households to dwellings / household spaces
(occupancy and vacancy rates)
-10%
10%
Workers to jobs
No limit, but output to log

2.3.19
The results of these checks are written to the log file generated for each run. In
the case that a certain limit is infringed, the tool will report this and in most
circumstances the run will cease. This ensures that the basic input data is robust
enough to produce realistic forecasts.
2.4
HOUSEHOLDS BY CONTROL AREA
2.4.1
The allocation of population and households to control areas (districts by
default) starts with trend based forecasts and then adjusts these to reflect the dwelling
allocations provided by the regional planning bodies. The methodology here is similar to
that outlined in the TEMPROv4.2 policy led planning forecasts for London, the South
East and East of England Regions.
POPULATION – TREND BASED ESTIMATION
2.4.2
The first step is to disaggregate the study area household projections using
input population projections for the control areas. This trend based process assumes
the change in household size is uniform for all control areas within the study area, but
that the starting pattern of household sizes is retained. The result is the first estimate of
household demand for the control area.
2.4.3
The number of households in the control area is then split into 1 person and
multi-person households. Due to the changing household sizes through time it is not
possible to just take the “previous” split between 1 and 2+ person households in each
control area. The overall change for the Region in household size is known from the
input data. Using this information the average size of the 2+ person households in each
control area can be scaled back. Since some control areas have relatively low
household sizes to start with, it is important to check that the resulting number of people
per 2+ person household remains above a specified lower limit (ie 2.1).
2.4.4
If any one control area reaches the lower bound, the household sizes in other
areas will need to be readjusted to retain the Regional control total. This process
iterates until stable, providing the trend-based estimate of households by type.

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Figure 2.2 First estimate of households by type in each control area based on the
change in population

DWELLING SUPPLY – POLICY BASED ESTIMATION
2.4.5
The forecast year households by type for each control area based on the
change in dwellings are also estimated. This is because in reality the choice of
household location in the future is often affected by the amount of dwelling supply. It is
assumed that households and dwelling growth are moving in the same direction, ie both
are growing or both are declining. If this is not the case, the household estimates are
based purely on population trends as calculated in the previous step for that control
area.
2.4.6
To implement this step, the change in households specified by the user at the
regional level for the forecast year is broken down to each control area. This is done by
using the proportion of dwelling growth a control area is forecast to receive relative to the
regional total.
COMBINING TREND AND POLICY BASED ESTIMATES
2.4.7
In practice the pattern of households is likely to be influenced by a mixture of
trends and new developments. Thus, a combination of the population-led and dwellings-
led approaches are taken. The extent to which household forecasts are policy led is
defined by a user specified parameter. To produce the NTEM versions 5 and 6 forecast
planning data set a value of 0.75 was adopted, erring more towards policy based
forecasts than past trends. If this parameter were set to zero the forecasts would be
wholly dependent on population trends, and a value of one indicates that only the
dwelling supply contributes to the estimate of households.

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2.4.8
It will often be the case that the demand for housing in an area cannot be
accommodated by the supply of dwellings. In this case, the Scenario Generator
identifies the excess households in each area. The excess may be suppressed or, if
capacity exists elsewhere in the study area, a proportion of them may be redistributed to
other control areas in the study area.
2.4.9
The potential supply of housing within a control area is based on the number of
available household spaces. This is derived mainly from the number of dwellings
allocated to each control area. Other factors that are considered in each control area
are:
 Occupancy rate (number of households per occupied dwelling)
 Vacancy rate (number of presently uninhabited dwellings)
 Otherwise unoccupied dwellings (second or holiday homes that will not be allocated
new households in the distribution process)
2.4.10
Controls are placed on vacancy and occupancy rates so that these do not
change radically over a forecast period. These may also be controlled by the user.
Occupancy rates may not change by more than 0.5% in a forecast period. Vacancy
rates may not reduce by more than 25% of their previous value. Constraints are also
placed on these variables to maintain a realistic housing profile.
2.4.11
Once calculated, the estimated number of households required in each control
area is compared to the available household spaces. Where this proportion is less than
one, households have enough capacity to locate in that control area. Where the
proportion is greater than one, excess households occur and are relocated or
suppressed or a combination of both.
2.4.12
The suppression of households is expected to alter the mix of household types
in the study area due to the different reaction that different households types will have to
limited housing capacity. The household type profile of those households being
reallocated is assumed to be in line with the control area profile from which the
households are moving. The required suppression is a representation of households
coalescing or a reduction in household formation. This is more likely to impact on one
person households than multi-person households – eg young people staying at home
longer or grouping together to form multi-person households since they are unable to
afford their own place of residence.
2.4.13
Two key user defined parameters are required here:
 The proportion of excess households that are willing to relocate to other control areas
in the Region (default=0.5 for each time period)
 The number of one-person households suppressed per 2+ person households
formed (default=3)
2.4.14
Where households wish to relocate, they are redistributed among the
remaining control areas within the study area that have capacity. In the rare case that
the total capacity in the study area is exceeded, the remainder are suppressed. The
total households that were unable to initially be allocated are distributed among the other
control areas on a pro-rata basis relative to the proportion of capacity out of the study
area total.

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Figure 2.3 Allocation of households to control areas

2.5
POPULATION BY CONTROL AREA
2.5.1
The trend based forecast population is an input for each control area defined.
The household forecasts are adjusted to take account of these population trends, the
expected change in dwellings and to alleviate housing pressure. Since there is some
reallocation of households amongst the control areas within the study area to take
account of planning policy, then there should be an associated reallocation of
population.
2.5.2
The input population projections are adjusted to reflect the policy based
household adjustment. An estimate of the number of people by type in each control
area to be reallocated is calculated from the initial household estimate and the final
household figures by type, taking into account the population profile (persons per
household) in each household type.
2.5.3
Where there is a reduction in the number of households between the trend and
policy based forecasts, the population is reduced based on the persons per household in
that control area. For areas gaining households, the associated population is
determined from the average population profile of all the households relocating.

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2.6
POPULATION AND HOUSEHOLDS BY ZONE
2.6.1
The households remain the main allocation variable based on expected
patterns of development / trends in development. The households in each control area
are thus distributed to the zones within the control areas based on Expected Growth
Factors (EGFs) as specified in Section 5. From the zonal household totals, population
totals by zone may be derived using the numbers of people expected in each household
type. Figure 2.4 shows a diagrammatic view of this process.

Figure 2.4 Derivation of households and population by zone

2.6.2
EGFs for households are applied to households by zone from the previous
scenario to form a profile of household growth for each control area. Where growth
factors are applied it is possible that in certain areas households by type become
negative where areas are in decline. Where this occurs adjustment is required to cap
each case so that they cannot fall below zero. Where this does occur, the total that is
adjusted back must be applied to all other zones pro-rata based on their relative EGF.
This is an iterative process. Once stable, it is applied to ensure that the resulting
number of households in each zone matches the number of households that would be
obtained by applying the adjusted growth factors to the previous household total.
2.6.3
Population estimates by zone may be derived from households by application
of the expected number of people in household type (using those adjusted for the new
population profile after the reallocation of households). Added to disaggregated zonal
population totals from the previous scenario, this produces initial estimates of zonal
population by gender and age. These are then controlled to the user input population
totals for control areas on a pro-rata basis.

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2.7
EMPLOYMENT AND WORKERS BY ZONE
2.7.1
The allocation of the employment from the control areas to the zones is carried
out using one of three approaches:
 An endogenous approach based on household forecasts (eg schools)
 Employment is assumed to follow trends in exogenous industrial sectors
 Insufficient data exists and growth is assumed to be based on previous totals
2.7.2
The approach adopted for each employment type is shown with the description
of the growth factors (EGFs) in Table 5.2.
2.7.3
The allocation of the population led employment is carried out using the
projected change in households by zone. This is then adjusted to match the control
totals for the employment sector within the control area.
2.7.4
The allocation of the remaining employment sectors (non-population led) is
based on a set of growth factors which are exogenously defined. These are calculated
by applying growth factors for each employment sector and then controlling to expected
change in employment for each control area. The expected change in employment is
the previous year’s employment factored up by the input EBS / DfT data at the Local
Authority level.

2.8
BALANCE WORKFORCE AND WORKERS
2.8.1
This process ensures that workers at the residence and workplace ends within
the same area are in balance. This makes use of the balancing area geography that
may be seen in Appendix A. The balancing process is concerned primarily with the
“working age” population (ie 16-29 and 30-64 age groups). The balancing process
ensures that:

there are the correct number of workers of different types living in the balancing
area for the jobs available; and

the number of workers in each zone does not exceed a specified maximum
proportion of the resident population.
2.8.2
These two steps are addressed in turn – first by checking and if necessary
adjusting the gender / working status profile for the required workers in the balancing
area and secondly reallocating the workers amongst the zones within the balancing area
to ensure no zone breaches the ceiling employment rate.
2.8.3
The implied numbers of workers required in balancing area in each age group
for the scenario are obtained by converting the employment forecasts (jobs) in to the
number of workers and then splitting the workers into the working young (16-29) or
working old (30-64) age groups. This makes use of two important sets of user-defined
parameters that:
 convert jobs to workers by gender, work type (full time/ part time) and employment
sector using the Regional profile; and
 divide workers into young or old, based on their gender and work type using the
Regional profile provided by the 2001 SAR.

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2.8.4
The changing employment profile through time should lead to a change in the
gender profile of the workforce in each employment sector. When this change is not
taken into account, the growth in retail and services and the decline in more traditional
industries gradually leads to unbelievably high employment rates for females with
compensating low level rates of male employment. Similarly the changes might be
expected to impact gradually on the split of part time and full-time workers. It is
envisaged that the profiles for the employment sectors will change gradually over time.
Analysis of the input employment data shows a reasonably constant gender split in each
employment sector from 2001 to 2041, indicating this potential problem will occur with
the basic data inputs. As a result the Scenario Generator includes an internal
adjustment of the assumed gender and working status split by employment sector.
2.8.5
This internal adjustment process uses the following key concepts:

Treating the previous population and the new (migrating) population as two
separate groups

Treating declines before and completely independently to growth – logically
they can only be applied to the “previous” population groups.

Using “existing” profiles / employment rates from the previous scenario as an
initial estimate of workers

Calculating maximum possible numbers of workers by type

Adjusting profile of workers demanded so no maxima are breached

Determining how far it is necessary to move from the initial values towards the
maximum values in order to satisfy the demand.
DECREASES IN POPULATION AND / OR WORKERS
2.8.6
If the population in any of the zones within the balancing area is forecast to
decline then this would naturally lead to a decrease in the number of workers in the
zone(s) irrespective of whether the required workforce in the balancing area is forecast
to decline or grow. In addition the workforce required in the balancing area might be
forecast to fall more or less than the reduction caused by the population change, or
alternatively to increase from the previous scenario. This gives two cases which must
be considered initially.
2.8.7
The first stage is to account for any decreases in workers due to decreases in
the population. Where this occurs, the population in full time and part time work is
reduced according to the current proportions of each.
2.8.8
The second stage is required only if the workforce in the balancing area is
forecast to decrease in any work type, gender or age category. In this case the number
of workers is reduced while retaining the total forecast population numbers by zone.
This is achieved by simply scaling back the number of workers (by status) in each zone
to match the control area total. The non workers are then increased proportionally by
the same volume to retain the zonal population totals.

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Figure 2.5 Estimation of population based on potential decrease in zonal
populations or decreasing worker types within a balancing area

INITIAL ESTIMATES OF WORKING STATUS PROFILE OF ZONAL
POPULATION
2.8.9
It is considered that working status profile of large parts of the resident
population will not alter significantly through time, while new developments that lead to
significant growth in an area might have very different profiles to the existing population.
The population is therefore separated into two groups:

The existing residents – from the previous year / scenario with any declines
already subtracted – a group for which the working status is known

Any increase in population in the forecast year for which the working status has
yet to be forecast.
2.8.10
An initial estimate of the population profile can be obtained by assuming the
“new” population takes on the same profile as the existing population.

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MAXIMUM SUPPLY OF WORKERS BY GENDER
2.8.11
The maximum supply of workers by gender in a forecast year is calculated. It
is derived by applying the maximum acceptable change over the forecast period to the
previous scenario. This rate is user defined and defaults to +5% (ie employment rate
could increase from 65% to 70%). A ceiling is also set for this proportion and when
exceeded will cap the maximum worker supply at this level. Maximum employment rate
is set for each gender and life stage combination. A ceiling rate is applied to both full
time and part time worker types, as well as a maximum for both combined. The
Scenario Generator ensures that neither limit is breached.
2.8.12
Since the maximum employment rate has been ascertained, the maximum
supply of workers per zone may be calculated. Working age population in the previous
year may in the forecast year be capable of working to the higher employment rate. In
addition, new working age population introduced through demographic change in the
forecast year may introduce new workers, with the maximum capped to the same
employment rate. This provides the upper bounds for the number of workers by age and
gender.

Figure 2.6 Derivation of maximum number of workers in each zone by age, gender
and employment type

CHECKING / ADJUSTING THE GENDER PROFILE OF THE WORKERS
DEMANDED
2.8.13
On comparing the initial estimates of workers demanded within a balancing
area to the maximum available working population, it is possible that in some cases this
will be exceeded for at least one combination of gender and age. If for example the
demand for male workers cannot be met by the maximum available male workers in the
population in the balancing area, these posts are transferred to female workers if any are
available in the population.
2.8.14
There are three cases consider for each life stage (working young and working
old) in the balancing area:
 There is no excess in demand for workers of either gender;
 There is excess demand for workers of both genders;

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 There is excess demand for workers of one gender but not the other.
2.8.15
Where there is no excess in the demand for workers in a balancing area, this
indicates that the maximum available workers in the population may accommodate the
demand for labour. Therefore no adjustment is necessary between genders.
2.8.16
In the case that there is excess demand for labour for both male and female
workers, there is no capacity to reallocate these workers across genders. Therefore this
excess is simply cut off so that the maximum number of workers does not exceed the
maximum possible working population. This cut off effectively assumes that the posts
will be filled by increases in double jobbing and the numbers of workers aged over 64.
2.8.17
In the case that demand for workers in one gender exceeds supply but not the
other, there is scope for the demand to be met by workers of the other gender. This of
course changes the gender profile of the working population within the balancing area.
This is achieved by allocating workers from one gender type to the other. In the event
that there is insufficient capacity in the other gender to meet the whole demand, this
residual excess is cut off.
2.8.18
Figure 2.7 below shows this allocation process in a simple flow chart up to
providing workers in each balancing area by age and gender. It may help understanding
by assuming that in this stage, workers by age (working young and working old) are
effectively handled separately.

Figure 2.7 Allocation of workers by age and gender in a balancing area

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CHECKING / ADJUSTING THE FULL-TIME / PART-TIME SPLIT OF
WORKERS
2.8.19
At this stage, workers by age and gender have been resolved, removing any
excess workers that cannot be allocated without exceeding the maximum imposed limits.
To give a final forecast of the number of workers in each balancing area, the split
between full time and part time workers needs to be resolved.
2.8.20
For each age and gender combination, the maximum number of workers
available from the population by full time and part time is fixed by the user specified
maximum change in employment rate from the previous scenario (5% by default). The
Scenario Generator checks whether the number of estimated workers falls within these
acceptable limits for each balancing area within the study area.
2.8.21
If full time and part time workers may be accommodated for each case, no
adjustment is required. It is not possible for both rates to be exceeded since all potential
excess has been removed from the previous step.
2.8.22
Where one worker type is in excess, those extra workers are switched to the
other type of work, eg where no more full time workers are permitted, the excess will be
accounted for by increasing the number of part time workers.
2.8.23
This gives a final forecast of workers in each balancing area by age, gender
and work type. From these, new employment rates may be derived and are output from
the Scenario Generator in the log file. The last step is to allocate workers to zones.
ALLOCATIONS OF WORKERS TO ZONES
2.8.24
The allocation of the adjusted and balanced workers to the individual zones is
carried out by looking at the difference between the maximum and initial zonal estimates
for the numbers of workers and determining what proportion of this difference is needed
to achieve the required demand figures.
2.8.25
There are two possible cases:

the workforce demanded is a greater proportion of the population than in the
previous scenario (expected to be the norm),

the workforce demanded is a smaller proportion of the population than in the
previous scenario
2.8.26
If the proportion of the population required to work is less than in the previous
population, the initial estimates by zone are simply scaled back based on the difference
at the balancing area level.
2.8.27
If the proportion of population working has increased then the employment rate
lies somewhere between the initial and the maximum employment rate. Where this is
the case, each zone requires the working population to be scaled up accordingly. An
adjustment factor is derived for the balancing area according to the relative demand for
workers between the initial working population estimate and the maximum number of
workers possible in the balancing area. This factor is used to scale each zone and
controls the total workers across all zones to the balancing area total.

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Figure 2.8 Allocating workers from balancing areas to zones

NON WORKERS BY ZONE
2.8.28
What remains is the allocation of non-workers to zones. This places the
remaining working age population into the student or other categories. These are
derived from the zonal population and workers and the proportion of non-worker types in
the previous scenario. This means that the number of students will vary by scenario
which is a different assumption to the current version of the Scenario Generator.
2.8.29
In rare cases where no non-workers exist in the previous scenario, yet
allocation of non-workers is required, the assumption is made that all will be allocated to
the other category. The assumption is that the other category is more ubiquitous than
the student category and avoids assigning students in areas potentially a long distance
from, for example, higher education. In practise these values will be very small.

2.9
UPDATE EMPLOYMENT FORECASTS FOR CHANGE IN WORKER
PROFILE
2.9.1
The number of jobs is taken as an input and from this the required number of
workers by gender, age group and working status is determined. This demand for
workers may not be achievable for the given population forecasts. In order to balance
the demand and supply of workers the Scenario Generator internally adjusts the gender,
working status and age profile of the required workforce.
2.9.2
Since the employment forecasts are an input to future scenarios, any
adjustments made to the profile of the working population is carried through to adjust the
profile of the jobs. This update can be carried out as a final step in the estimation
process, solely to provide an improved base from which future scenarios are forecast.

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2.10
SUMMARY OF OUTPUTS FROM THE SCENARIO GENERATOR
2.10.1
The Scenario Generator produces three main output files:
 A log file for the scenario/ set of scenarios generated
 Population and household forecasts for the car ownership model
 Population, household and employment forecasts for the trip end model
2.10.2
The log file summarises the performance and key variables associated with
each scenario run. The log informs the user of the successfulness of the run and any
errors that may have occurred, including warnings where data consistency issues may
need to be resolved. For information purposes, the log file also summarises the key
elements of a scenario run:
 Input parameter settings
 Checks on control totals
 Allocation and suppression of households
 Allocation of population
 Derived control area vacancy rates
2.10.3
The planning data forecasts for the National Car Ownership Model are output
in the appropriate text file format. These are:
 Total population in NTEM zones
 Persons by gender, age and working status
2.10.4
Planning forecasts for the National Trip End Model are output in the expected
database format. These are:
Employment forecasts by zone
 Number of jobs
 Number of households
 Number of jobs by sector
Population forecasts by zone
 Population in NTEM zones by gender, age and working status
2.10.5
In addition to the outputs, the results from the forecasting process are stored in
data tables within the Scenario Generator database.

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3
Data for 2001 Base Year
3.1
SUMMARY
3.1.1
For NTEM 6.2, the base year for the planning data is 2001. This data is
primarily obtained from the 2001 Census of Population and then adjusted to 2001 mid-
year population data to counter the effects of potential under-enumeration from the
Census and for consistency with mid year based projections used for forecasting.
3.1.2
The following data comprise the base year inputs:
 Population living in households (by gender, age and working status in each zone)
 Households (by size in each zone)
 Dwellings (by local authority district control area)
 Employment (jobs, by sector, gender and working status in each zone)
 Mid-year employment estimates for 2001 from projection data (by local authority
district control area)
3.1.3
Several additional parameters are required as part of the base data input:
 Occupancy rate by district
 Vacancy rate by district
 Second homes and holiday homes (by zone)
 Persons per household
3.1.4
Base year data is required at the NTEM zone level. NTEM zones are
aggregations of Census Output Areas (OAs) to represent different area types in each
district.
3.1.5
This section describes the basic data required in the base year- mostly from
using 2001 Census tables at the OA level. Where Census tables are not available at
this level, data at a more coarse spatial level were used and sound methods were
adopted to convert this data to NTEM zones. Those assumptions are outlined here.

3.2
BASE YEAR POPULATION
3.2.1
Base year population is required by gender, age and working status for each
NTEM zone. These are broken down into the following categories:

Gender: male, female

Age: children (0-15), working age: younger (16-29), working age: older (30-64),
pensionable age (65+)

Working status: full time employed, part time employed, full time students, other
3.2.2
Children and those over the age of 64 are not differentiated by working status.
This effectively gives twenty categories of population for each zone.
3.2.3
Table 3.1 shows the data sources used in the derivation of base population
data. These were largely taken from a combination of 2001 Census tables. In order to
achieve the level of segmentation required, these sources were enough when combined,
although categories and definitions between them do vary. Therefore careful matching
was required between these sources.

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Table 3.1 Data sources used in deriving base population by NTEM zone
Data Source
Geography
Description/ Use
Table CAS001
OA
Elderly people (65+) in communal establishments by
gender
Table CAS004
OA
Children (0-15) in households, elderly people (65+) in
households by gender
Table CAS030
OA
People of working age (16-74) in households by
gender and economic activity
Table CAS028
OA
People in households and communal establishments
combined, by age, gender and economic activity
Table UV29
OA
Economically active full time students (aged 16-74) by
employment status
Table ST001
Ward
People in households by age and gender
Table ST028
Ward
People in households and communal establishments
combined, by age, gender and economic activity
Table T02
Ward
Economically active full-time students by life stage
(working young or working old), by working status
2001 Mid Year
Population
Estimates
Ward
Mid-year estimate of people in households by age and
gender (district level in Scotland)
2001 Sample
of Anonymised
Records (SAR)
Region
Used to derive population control totals

3.2.4
In NTEM 6.2, the 2001 Census data has been adjusted to mid-year estimates
of the base year, to overcome potential under-enumeration of data collected from the
2001 Census and for consistency with the mid year based population and household
projections. This adjustment is relevant for all of the main base year variables.
3.2.5
2001 mid-year population estimates were obtained from ONS. Mid-year
population is compared to basic population figures taken from Census table ST01. This
provides a set of scaling factors for gender and age group at ward level for England and
Wales. Mid-year population for Scotland is obtained for districts and hence the scaling
factors are at this level. These scaling factors are used to adjust the multi-dimensional
base population data to mid-year levels. There is a slight difference between age
definitions between the two sources (ie mid year estimates have a 0-14 age category
rather than 0-15). The scaling method takes account of this.
3.2.6
For NTEM 6.2 a further adjustment has been made to the Census based
population data to bring the number of workers (people in employment) in 2001 in line
with the figures available from the Labour Force Survey (in 2001). This was achieved
using a single scaling factor for each Region in England, Scotland and Wales to adjust
the base year working age population derived from the Census (by gender, for the
working age young and old age groups) to match the LFS totals. The non working
population categories (students and others, by gender and age group) were then scaled
back to ensure the total population by age and gender remains consistent with the mid
year estimates.
3.2.7
Table 3.2 shows the total population of Great Britain in the base year, divided
into the dimensions required in the Scenario Generator.

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Table 3.2 Population by gender, age group and working status in Great Britain,
2001
Age group Working status
Female
Male
Total
Percentage
of population
0 - 15
All
11,438,000
20.3%
16 - 29
Full time
2,208,000
3,040,000
5,248,000
9.3%
16 - 29
Part time
983,000
495,000
1,478,000
2.6%
16 - 29
Student
725,000
765,000
1,490,000
2.6%
16 - 29
Other
887,000
533,000
1,420,000
2.5%
30 - 64
Full time
4,895,000
10,063,000
14,957,000
26.5%
30 - 64
Part time
4,109,000
750,000
4,858,000
8.6%
30 - 64
Student
116,000
84,000
200,000
0.4%
30 - 64
Other
4,203,000
2,375,000
6,578,000
11.7%
65+
All
5,002,000
3,735,000
8,736,000
15.5%
All
All
23,128,000
21,840,000
56,405,000
100.0%

3.3
HOUSEHOLDS
3.3.1
Total households by zone are separated into those households with one
person and households with two or more people. This data is adjusted to mid-year
estimates also to be comparable with the rest of the planning data.
3.3.2
The following data sources were used to derive the base year household data:
 Census Table UV51: Households by number of resident people by Output Area
 2001 mid-year household estimates, separated into single person or two or more
person households:
–
for England from the Office of the Deputy Prime Minister (ODPM, February
2005)
–
for Wales from the National Assembly for Wales (NAW, 2003)
–
for Scotland from the General Register Office for Scotland (GROS, 2004)
3.3.3
For each English Government Office Region, Scotland and Wales, UV51 was
used to give the number of households at Output Area level and aggregated to NTEM
zones. These were then summed over Government Office Regions and the totals
compared to the mid-year estimates. A scale factor was derived for each combination of
region and household size and applied to all NTEM zones.

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Table 3.3 Regional household control totals by size for the 2001 base year
(thousands)
Region
1 person
2+ people
Total
East Midlands
489
1,248
1,737
North East
329
746
1,075
North West
871
1,956
2,827
Scotland
722
1473
2,195
South West
620
1,473
2,093
Wales
337
853
1,190
West Midlands
620
1,534
2,154
Wider South East
2,624
5,942
8,566
Yorkshire and the Humber
609
1,460
2,069
Grand Total
7,221
16,685
23,906

3.4
DWELLINGS
3.4.1
Base year dwellings data are taken from Census table UV55 for England and
Wales and the equivalent UV55 table for Scotland. Dwellings are required by population
control area, ie district.
3.4.2
The basic dwellings figures are taken from the Census data and brought into
line with mid-year estimates. This is achieved by making use of development figures
where available or continuing recent trends to move April dwelling totals to June.
Table 3.4 Regional dwelling control totals for 2001 base year (thousands)
Region
Dwellings
East Midlands
1,801
North East
1,124
North West
2,960
Scotland
2,307
South West
2,188
Wales
1,255
West Midlands
2,225
Wider South East
8,821
Yorkshire and the Humber
2,159
Total
24,841

3.5
BASE YEAR EMPLOYMENT (JOBS)
3.5.1
The data required for the 2001 base year is the number of jobs (both employees
and the self employed) in each NTEM zone divided into forty-eight categories by:

Employment sector (12 NTEM categories E03 to E14)

Gender (males and females)

Working status (full time / part time workers)
3.5.2
The definition of NTEM employment types are as shown in Table 3.5.

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Table 3.5 NTEM employment types
`
SIC(92) code
Description
E03
801
Primary and Secondary Education
E04
802
Higher Education
E05
803, 804
Adult/ Other Education
E06
551, 552
Hotels, campsites etc
E07
501, 503, 505, 521-525,
5262, 5263, 55303
Retail trade
E08
851
Health / Medical
E09
502, 504, 527, 641,
6512, 703, 711, 714,
852, 853, 93
Services (business and other) &
equipment rental & repair household
goods & postal / courier services
E10
10-45, 51, 60-62, 631,
632, 634, 90
Industry, Construction & transport
E11
55301, 55302, 554
Restaurants & bars
E12
63303, 91, 9213, 923,
925-927
Recreation & sport
E13
01, 02, 05
Agriculture & fishing
E14
Other
Business

3.5.3
The process is made more complex by the definition of employment.
Household based surveys typically measure the number of workers while employer
surveys provide information on the numbers of jobs. The two data sets differ in some
cases quite markedly due to double jobbing and job sharing in addition to differences
caused by the survey design and samples surveyed (age groups included etc).
3.5.4
The basic data used are shown in Table 3.6 below.
3.5.5
The Census is the most comprehensive data set of workers and forms the basis
of the employment estimates to be input to the NTEM planning data forecasting process.
As with deriving population input data, various different data sources are required to
achieve the dimensions required. These vary in terms of segmentation, spatial detail
and coverage and hence care is needed to combine the sources into a coherent data
set.
3.5.6
Table T10 and W201 for each region in England and Table TV201 for Scotland
is used to provide the proportion of the employed population in each of the 4 categories
of work status and gender in each Region. The IDBR was then used to give the
classification in 12 industrial categories. However, the SIC classification in the Census
does not compare well with the data set being used for forecasting (based on Experian
(EBS) definitions). A separate processing step splits the education category to school,
further and adult education using the IDBR data.
3.5.7
Jobs by employment sector from the EBS data are therefore assigned
equivalent NTEM employment types (see Table 3.7). A breakdown of industrial class for
each of the four categories (by gender and work type) for each local authority district
was derived to apportion workers in each zone into an industry type, by male and female
full time and part time.
3.5.8
Jobs are controlled to the regional 2001 totals from Workforce jobs, scaled
down from the Workforce Jobs total for Great Britain (29.1m) to the previous NTEM total
(28.5m), as the definition of Workforce Jobs is believed to include approximately 0.6m
jobs that are not included in the NTEM definition (including workers living in communal

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establishments and a possible double counting of workers who work for an agency but
also report themselves as self-employed).
Table 3.6 Data sources used to derive base year employment by NTEM zone
Data Source
Geography
Description/ Use in NTEM
Table UV75
OA
Workers by life stage, from ONS for England and
Wales and GROS for Scotland
Table T10
Ward
Workplace population by gender and work type,
from ONS for England and Wales
Table W201
Ward
Origin-destination of workers by gender, full time,
part time or full time student, from ONS
2001 SAR
Region
Cross-tabulation of split of life stage, gender and
working status within the Region
2001 Experian Business
Solutions (EBS)
employment data
1991
County
Used to split total employment down into
employment sector profiles
1998 Inter-Departmental
Business Register (IDBR)
1998 Ward
Allows splitting of education employment into the
three types required in NTEM based on
proportions as at April 1998
2001 Labour Force
Survey (LFS)
Region
Details of rates of second-jobbing by Region,
ONS
Workforce Jobs
Region
Split of jobs by region

Table 3.7 Correspondence between EBS and NTEM employment types
EBS Type
NTEM Type
Education
E03 to E05
Accommodation
E06 & E11
Retail
E07
Health & Medical
E08
Services
E09
Industry, Construction & Transport
E10
Restaurants & Bars
E06 & E11
Recreation & Sport
E12
Agriculture, etc
E13
Business
E14

3.5.9
Data from the 2003 Labour Force Survey (LFS) was originally used to convert
the number of workers to jobs. However for the NTEM 6.2 dataset, the LFS data was
used to adjust the numbers of workers in the Base year population data and does not
affect the employment (jobs) numbers.

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Table 3.8 Jobs in each NTEM category by gender and working status in Great
Britain, 2001 (thousands)
Employment Type
NTEM
Type
Male
Full
Time
Male
Part
Time
Female
Full
Time
Female
Part
Time
Total
E03 Education (school)
E03
258
104
391
501
1,254
E04 Education (higher)
E04
133
51
187
220
590
E05 Education (adult/other)
E05
49
19
74
90
232
E06 Accommodation
E06
107
57
90
121
375
E07 Retail trade
E07
1,026
403
689
1,299
3,417
E08 Health/Medical
E08
295
100
742
776
1,913
E09 Services
E09
949
211
844
832
2,835
E10 Industry/Construction/transport
E10
6,048
325
1,438
518
8,329
E11 Restaurants & bars
E11
236
194
180
380
990
E12 Recreation & sport
E12
352
154
274
307
1,086
E13 Agriculture & fishing
E13
270
44
62
53
429
E14 Business
E14
3,294
486
2,025
1,250
7,054
Grand Total
Total
13,016
2,148
6,994
6,347
28,505

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4
Forecast Data and Projections
4.1
SUMMARY
4.1.1
For each study area and forecast year, the following data are required for any
forecast year / scenario combination:
 Population projections (by age and gender) in each district control area
 Household projections (by size) for the study area (Region)
 Forecast dwellings (in each district control area)
 Employment projections (by sector, gender and working status in each district control
area)
 Zonal growth factors for employment in the period modelled (by sector)
 Zonal growth factors for the period for households

4.2
FORECAST POPULATION DATA
DATA REQUIRED
4.2.1
For future years, the population is required for each control area (district)
subdivided by gender and age group. Ultimately, the groups required are:

Children under 16;

Males/ females aged 16-29;

Males/ females aged 30-64;

Males/ females for each subsequent five-year age band from 65 up to 84;

Males/ females ages 85 and over.
POPULATION PROJECTIONS
4.2.2
Population projections exist in two formats national projections and sub
national projections. Since 2006, the Office for National Statistics has been responsible
for producing both datasets. The most recent national data is 2008 based mid year
estimates, containing projections for England, Wales and Scotland at the national level
for each year up to 2033 then for selected years up to 2083 (including the five year steps
required to 2041). ONS provides a breakdown of these figures to the district level but
only up to 2033, and these sub national projections have also been used for NTEM 6.2.
4.2.3
The forecast extrapolations from 2033 to 2041 for the sub national data use
national data as control totals for England, Wales and Scotland and estimation is made
at the district level. Table 4.1 shows a summary of the total population projections by
year and region input to the NTEM forecasting process. Figure 4.1 and Figure 4.2 show
this trend graphically, separated by gender. The regional population projections act as
control totals for the district level projections.

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Table 4.1 Total population projections by region, 2006-2041 (thousands)
Region
2006
2011
2016
2021
2026
2031
2036
2041
East Midlands
4,364
4,538
4,719
4,912
5,101
5,275
5,431
5,580
East of England
5,607
5,883
6,174
6,471
6,757
7,016
7,268
7,492
London
7,512
7,868
8,206
8,526
8,813
9,083
9,338
9,577
North East
2,555
2,602
2,655
2,709
2,766
2,813
2,852
2,897
North West
6,855
6,943
7,064
7,199
7,326
7,431
7,515
7,619
Scotland
5,117
5,233
5,324
5,411
5,483
5,532
5,558
5,571
South East
8,237
8,565
8,895
9,248
9,600
9,925
10,219
10,485
South West
5,125
5,341
5,556
5,787
6,022
6,240
6,436
6,611
Wales
2,966
3,024
3,104
3,187
3,263
3,326
3,376
3,418
West Midlands
5,368
5,487
5,629
5,782
5,931
6,066
6,178
6,297
Yorkshire and
The Humber
5,141
5,350
5,572
5,797
6,017
6,221
6,404
6,567
Grand Total
58,846
60,834
62,900
65,030
67,080
68,928
70,575
72,114

1,000
1,500
2,000
2,500
3,000
3,500
4,000
4,500
5,000
5,500
2006
2011
2016
2021
2026
2031
2036
2041
East Midlands
East of England
London
North East
North West
Scotland
South East
South West
Wales
West Midlands
Yorkshire and The Humber

Figure 4.1 Population projections, females (thousands), 2006-2041

1,000
1,500
2,000
2,500
3,000
3,500
4,000
4,500
5,000
5,500
2006
2011
2016
2021
2026
2031
2036
2041
East Midlands
East of England
London
North East
North West
Scotland
South East
South West
Wales
West Midlands
Yorkshire and The Humber

Figure 4.2 Population projections, males (thousands), 2006-2041

4.2.4
Data for England, Wales and Scotland at the district level is currently available
from 2008 up to 2033. The long-term trend (2008-2033 for England, 2011 to 2033 for
Wales and Scotland) for each population segment was used to extrapolate district trends
onwards up to 2035, then half this trend to 2041. The results were then controlled to the
national projections for 2036 and 2041.

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4.3
FORECAST HOUSEHOLDS DATA
4.3.1
The household projections input to the NTEM 6.2 forecasts were 2008 based
projections for each country downloaded from the internet. These were from DCLG for
England, the GROS for Scotland and from the Welsh Assembly government websites.
In each case the projections ran from 2008 to 2033 with varying intermediate years
provided. Projections from earlier years (2001 and 2006 – now historic data) were taken
from previously released datasets as used in the earlier versions of NTEM.
4.3.2
All household projection data sets are mid-year based, hence no adjustment is
required to bring them in line with other data.
4.3.3
Household projections are required for five-year intervals from 2001 to 2041 by
region, subdivided into 1 person and 2+ person households. Where household
projections existed, they were taken as given. Forecast extrapolations are carried out
using a simple methodology, separated into two stages:
 Follow trends in household size by region to convert population forecasts into
household forecasts by Region;
 Derive split of 1 person / 2+ persons households by following the trend in the
proportion of 2+ person households for each Region, then applying this to projected
total households
4.3.4
The 2008 household projections are based on the 2008 based population
projections also being used for the NTEM forecasts. In this case it is therefore
unnecessary to scale the household projections to match the population projections.
Previously, in NTEM 5.4, the 2006 household projections required scaling to match with
the 2008 based population projections.
4.3.5
Figure 4.3 shows the derived household sizes for each Region. These are the
based on the input household projection data and may be adjusted by the Scenario
Generator for the later, years if households are suppressed due to insufficient dwellings
being available. The effects of household suppression on the output household sizes are
explained in Section 6.2.
1.90
2.00
2.10
2.20
2.30
2.40
2.50
2006
2011
2016
2021
2026
2031
2036
2041
East Midlands
East
London
North East
North West
Scotland
South East
South West
Wales
West Midlands
Yorkshire and the Humber

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Figure 4.3 Average household size by region based on input data, 2006-2041
4.3.6
The following charts and tables show the final input household projections by
Region between 2001 and 2041, divided into single person and two or more person
households.
0
500
1,000
1,500
2,000
2,500
3,000
2006
2011
2016
2021
2026
2031
2036
2041
Year
East Midlands
East of England
London
North East
North West
Scotland
South East
South West
Wales
West Midlands
Yorkshire and The Humber

Figure 4.4 Household projections by Region for single person households, 2006-
2041 (thousands)

0
500
1,000
1,500
2,000
2,500
3,000
2006
2011
2016
2021
2026
2031
2036
2041
Year
East Midlands
East of England
London
North East
North West
Scotland
South East
South West
Wales
West Midlands
Yorkshire and The Humber

Figure 4.5 Household projections by Region for 2+ person households, 2006-2041
(thousands)

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Table 4.2 Household projections by Region for single person households, 2006-
2041 (thousands)
Region
2006
2011
2016
2021
2026
2031
2036
2041
East Midlands
569
636
703
773
844
910
977
1,039
East of England
728
822
918
1,021
1,124
1,223
1,326
1,419
London
1,204
1,332
1,462
1,598
1,742
1,880
2,016
2,144
North East
367
400
432
464
498
531
564
594
North West
987
1,077
1,168
1,260
1,350
1,434
1,515
1,591
Scotland
809
894
983
1,069
1,155
1,224
1,288
1,336
South East
1,059
1,178
1,302
1,435
1,569
1,697
1,828
1,946
South West
710
791
875
965
1,055
1,140
1,223
1,299
Wales
390
430
477
523
570
611
649
683
West Midlands
704
772
840
911
984
1,054
1,124
1,190
Yorkshire and The Humber
696
774
855
939
1,024
1,106
1,186
1,259
All GB
10,228
11,116
12,031
12,980
13,941
14,840
15,732
16,540

Table 4.3 Household projections by Region for 2+ person households, 2006-2041
Region
2006
2011
2016
2021
2026
2031
2036
2041
East Midlands
1,263
1,298
1,344
1,388
1,427
1,462
1,491
1,507
East of England
1,618
1,679
1,749
1,816
1,875
1,930
1,979
2,005
London
1,976
2,015
2,068
2,123
2,164
2,199
2,222
2,226
North East
731
738
752
764
773
778
781
779
North West
1,921
1,924
1,949
1,974
1,991
2,002
2,002
1,993
Scotland
1,482
1,503
1,521
1,536
1,542
1,556
1,559
1,541
South East
2,349
2,415
2,491
2,564
2,631
2,695
2,752
2,778
South West
1,483
1,531
1,586
1,638
1,687
1,732
1,768
1,786
Wales
882
906
934
959
976
989
995
991
West Midlands
1,510
1,522
1,548
1,574
1,596
1,614
1,626
1,627
Yorkshire and The Humber
1,468
1,511
1,572
1,629
1,678
1,724
1,760
1,778
All GB
18,690
19,053
19,529
19,985
20,367
20,713
20,972
21,052

4.4
POLICY-BASED DWELLINGS DATA
4.4.1
For England and Wales the dwelling stock in 2006 is extracted from “Data on
Dwelling Stock by Local Authority” published by the Office for National Statistics (ONS).
In Scotland, 2006 dwelling stock is obtained from Estimates of Households and
Dwellings in Scotland 2007 (Table 2) published by the General Register Office for
Scotland (GROS) in May 2008.
4.4.2
This is then combined with the projected annual averages of housing
completion from 2006 onwards to calculate the cumulative dwelling stock at Local
Authority level at 5 year intervals from 2006 to 2041.
4.4.3
In NTEM 5.4 the spatial pattern of residential development was based upon
the Regional Spatial Strategies (RSS) for each Region, or the nearest equivalent
documents. For the NTEM6.2 dataset the dwelling trajectories for England, Wales and
Scotland were updated to reflect the latest available published information. Due to the
different planning systems and monitoring requirements in England, Wales and
Scotland), a different methodology was required for each country.

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England
4.4.4
Dwelling growth was obtained from the housing trajectory contained within the
latest Annual Monitoring Report (AMR) published by each local authority. Where the
December 2010 report, covering the financial year 2009/2010 was not available, the
December 2009 report was used.
4.4.5
The creation of 8 new unitary councils in 2009 meant that 36 of the 2001
districts no longer exist. The trajectories for these former authorities have been obtained
from the most recent AMR where available, or from the December 2009 AMR of the
district prior to its abolition.
4.4.6
National Parks also have a statutory duty to provide an AMR containing
dwelling trajectories. These trajectories provide dwellings in addition to those of the
local authorities in which the National Parks reside. Although small, this growth has
been accounted for by uniformly distributing the growth to the local authorities containing
the National Parks.
4.4.7
The AMR was used to determine a trajectory to at least 2021. To extend this to
2041, a trend-based approach was adopted assuming that growth rates continued at the
average rate of the latest 10 years of available projections from the AMRs. Details of the
AMRs providing dwellings inputs can be found in Appendix C.
Wales
4.4.8
Until 2004, Welsh authorities were in the process of developing a Unitary
Development Plan (UDP). However since 2004 changes to the planning system mean
that they moved to develop a Local Development Plan (LDP).
4.4.9
The local authorities are in various stages of the planning process and so:
 Where an adopted LDP is in place, the proposed housing trajectory is used
 Where an un-adopted LDP contains only a single housing trajectory then that is used
 In other cases the trajectory from the UDP was used.
4.4.10
The documents do not set out detailed trajectories, but estimate the level of
growth required over a period of years. The average yearly dwelling growth is then
estimated. Table 4.4 summarises the source of the Welsh dwelling trajectories together
with the planned annual growth rate. In the absence of future year data, a trend-based
approach was adopted based on these dwelling figures in order to derive a complete set
of dwelling assumptions to 2041. The trajectory was extended to 2041 assuming a
yearly growth rate equivalent to that of the yearly average of the latest 10 years
projections

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Table 4.4: Source of dwelling trajectories for the Welsh Local Authorities
Welsh Unitary
Authority
Planned
growth
Dwellings per
Annum
Planning
document
used
Date
Comment
Anglesey
120dpa
UDP
2006

Blaenau Gwent
200dpa
LDP
2008

Bridgend
497dpa
UDP
2005

Caerphilly
685dpa
LDP
2010
Latest update is based upon 10,269 dwellings 2006 to 2026
Cardiff
1120dpa
UDP
2003
The LDP has been stopped by the council due to inspectors
report. This included concerns about housing. UDP plan not
adopted but contains lower growth than LDP
Carmarthenshire
753dpa
UDP
2006

Ceredigion
448dpa after
2011
LDP
2010
LDP suggests 6,000 dwellings 2007-2022
Conwy
420dpa
LDP
2009
LDP suggests 6,300 dwellings 2007-2022
Denbighshire
500dpa
LDP
2009
LDP suggest 7,500 dwellings 2006 to 2022
Flintshire
438dpa
UDP
2006
No LDP. Used 2006 update to UDP (which is not adopted)
Gwynedd SP
335dpa
UDP
2009

Merthyr
253dpa
LDP
2008

Monmouthshire
400dpa after
2011
LDP
2009
LDP has options, but sets out a preferred strategy following
consultation
Neath Port
Talbot
437dpa
UDP
2008
Adopted UDP used
Newport
740dpa
UDP
2006
Adopted UDP used
Pembrokeshire
735dpa after
2011
UDP &
LDP
2006
LDP only provides a trajectory after 2011. UDP used prior to
2011
Powys
409dpa
UDP
2010
Adopted UDP used
Rhondda
465dpa
LDP
2009

Swansea
978dpa
UDP
2008

Torfaen
420dpa
LDP
2008

Glamorgan
500dpa after
2011
UDP &
LDP
2007
LDP only provides a trajectory after 2011. UDP used prior to
2011
Wrexham
501dpa
LDP
2005
LDP. 8065 between 2006 and 2021 (501dpa after 2008)
ScotlandThe LATIS (Land use and Transport in Scotland) framework provides a land
use and transport modelling service in Scotland. In order to ensure the model is kept up
to date Transport Scotland periodically undertake a survey of Local Authorities to
determine their planned dwelling growth. The latest survey was undertaken in 2010, and
the responses have been provided by Transport Scotland and used for the NTEM6.2
dataset. To extend the dataset to 2041, a trend-based approach was adopted assuming
a yearly growth rate equivalent to that of the yearly average of the latest 10 years
projections.
4.4.12 Figure 4.6 and Table 4.5 summarise the dwelling assumptions for each Region
for each five year period from 2006 to 2041.

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0
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
4,500
5,000
2006
2011
2016
2021
2026
2031
2036
2041
Dwellings (000's)
Year
East Midlands
East of England
London
North East
North West
Scotland
South East
South West
Wales
West Midlands
Yorkshire and the Humber

Figure 4.6 Dwelling forecasts, 2006-2041 (thousands)
Table 4.5 Dwellings by region, 2006-2041 (thousands)
Region
2006
2011
2016
2021
2026
2031
2036
2041
East Midlands
1,889
1,972
2,083
2,176
2,261
2,353
2,445
2,537
East of England
2,424
2,532
2,675
2,803
2,921
3,046
3,172
3,298
London
3,229
3,372
3,550
3,711
3,855
4,014
4,173
4,332
North East
1,154
1,203
1,249
1,285
1,317
1,353
1,389
1,425
North West
3,069
3,168
3,322
3,478
3,617
3,762
3,908
4,055
Scotland
2,413
2,558
2,734
2,872
2,981
3,079
3,187
3,295
South East
3,539
3,691
3,858
4,000
4,120
4,255
4,390
4,526
South West
2,282
2,395
2,526
2,660
2,770
2,895
3,019
3,143
Wales
1,329
1,386
1,445
1,505
1,564
1,624
1,683
1,743
West Midlands
2,304
2,373
2,464
2,550
2,645
2,736
2,828
2,920
Yorkshire and the Humber
2,245
2,330
2,444
2,588
2,738
2,886
3,034
3,182
Total GB Dwellings
25,876
26,981
28,350
29,627
30,792
32,003
33,228
34,453

4.5
FORECAST EMPLOYMENT DATA
4.5.1
The employment data input data provides the number of jobs segmented by:
 Gender
 Employment status (full time or part time)
 Employment sector (for the twelve NTEM categories)
4.5.2
Those in full time employment are defined as those that work 30 hours or more
per week. Part time employment is anything less than this.
4.5.3
Employment forecasts are produced by the DfT, using:
 Office for Budget Responsibility employment growth (for 2009-2015, March 2011
budget) and Treasury employment forecasts (2016-2041), as a national level
constraint;
 Experian Business Studies (EBS) forecasts at Local Authority/District level;

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 historic data (1982-2006) by employment sector, at national level (provided by EBS)
 the DfT employment forecasting model, which calculates employment by sector at
Local Authority level.
4.5.4
The EBS historic data, on which the employment sector growth is based, is
divided into relevant categories described above. A correspondence may be derived
between the EBS employment categories and the equivalent NTEM categories as done
for the base year data. The conversion may be seen in Table 3.7 of Section 3.
4.5.5
The EBS data has a self-employed category in addition to full time and part
time employees. These are allocated into full time or part time based on the proportions
given in Census Table ST038 (Sex and industry by employment status by hours
worked). Again, the conversion from SIC92 code to NTEM employment types is
required.
4.5.6
The control total for education employment across the three categories is
derived for each forecast year using the same method. The split between them is
derived by following the trend in population by age group. The trend in population ages
0-15 is applied to primary and secondary education (E03). Higher education (E04)
follows the trend in 16-29 year olds. Adult and other education (E05) follows the 30-64
trend.
4.5.7
Figure 4.7 below shows total employment by Region for each forecast year.
Table 4.6 shows the same input employment forecasts for Great Britain segmented into
each NTEM employment sector.

Figure 4.7 Forecast of total employment (jobs) by region, 2006-2041 (thousands)

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Table 4.6 Total employment (jobs) by NTEM sector, 2001 – 2041 (thousands)
Employment
2001
2006
2011
2016
2021
2026
2031
2036
2041
E03 Primary & Secondary
Schools
1,254
1,437
1,665
1,761
1,853
1,906
1,940
1,979
2,028
E04 Higher Education
590
567
612
615
594
589
587
590
588
E05 Adult Education
232
255
272
282
290
298
301
307
315
E06 Hotels, Campsites etc.
375
380
377
386
390
393
393
394
395
E07 Retail Trade
3,417
3,387
3,033
3,124
3,103
3,066
2,992
2,935
2,874
E08 Health, Medical
1,913
2,172
2,463
2,787
3,032
3,325
3,629
3,932
4,189
E09 Services & Eqpt Rental
2,835
3,066
3,246
3,405
3,521
3,641
3,725
3,826
3,935
E10 Industry, Construct,
Transport
8,329
8,130
7,767
7,186
6,554
5,978
5,394
4,886
4,432
E11 Restaurants & Bars
990
1,051
1,007
1,098
1,154
1,206
1,244
1,291
1,337
E12 Recreation & Sport
1,086
1,166
1,131
1,267
1,370
1,472
1,563
1,668
1,777
E13 Agriculture & Fishing
429
392
353
320
287
256
225
199
177
E14 Business
7,054
7,856
7,904
8,791
9,430
10,060
10,597
11,225
11,864
Grand Total
28,505
29,859
29,831
31,021
31,576
32,191
32,591
33,232
33,912

4.5.8
As part of the forecasting process, the employment totals (jobs) are converted
to numbers of workers within the Scenario Generator using a parameter that defines the
ratio of workers within each employment sector by gender and working status to jobs for
each Region. This is described in more detail in Appendix D.

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5
Expected Growth Factors
5.1
SUMMARY
5.1.1
Expected Growth Factors (EGFs) influence how much employment and
household development from the control area total is distributed to its constituent NTEM
zones. In practice this will be governed by a large array of influences, such as pulls of
demand and constraints of supply. The EGF methodology is necessary in the absence
of a complete set of specific data of individual housing and employment sites over time
below the district or county levels.
5.1.2
The outline is presented here of the generation of EGF assumptions for the
initial set of NTEM forecasts. Where more specific information may be obtained in the
future, the Scenario Generator allows the user flexibility in determining EGFs for every
zone for any forecast period.
5.1.3
There are two sets of EGFs required:
 Household growth for zones within a control area (in this case, districts)
 Employment growth for zones within a control area (in this case, districts), which
requires growth rates for each employment sector by zone (for a certain period).
5.1.4
There are two different schemes for applying the EGFs, depending on which
method the user wishes to implement: growth weights and growth trends. The Scenario
Generator tool is capable of using either one of these methods as determined by the
user.
 Weights: EGFs are used as a basis of proportional change expected in each zone for
the variable in question.
 Trends: EGFs are used as relative linear factors that will distribute to each zone
within a control area based on their relative sizes. This is practically the same as
providing absolute expected growth (or decline) over time.
5.1.5
Figure 5.1 shows the impact of the two approaches graphically. The input
EGFs are applied to the previous scenario data to give an initial estimate of the new
zonal values. These are the points on the left in the charts. The EGFs are then
adjusted so that the required control totals are obtained. In the weights based approach
the adjustment is multiplicative, while in the trends based approach it is additive. This
gives the final set of zonal values shown to the right on the two charts.
EGFs as Weights
-0.1
-0.05
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
Initial
Final
Zone 1
Zone 2
Zone 3
Zone 4
Zone 5
Zone 6
EGFs as Trends
-0.05
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
Initial
Final

Figure 5.1 Expected growth factors applied as weights and trends

5.1.6
The forecasts delivered for NTEM versions 5 and 6 are generated using the
weights-based methodology.

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5.2
HOUSEHOLD EGFS
5.2.1
Household growth factors are required for each NTEM zone, representing the
change in total households. These growth factors are derived by assessing the historic
growth between 1991 and 2001 for each 2001-based Planning Area Type (taken from
the DfT study in “Impacts of land use planning policy on transport demand and
congestion”, 2004). This area typology is based on clustering together areas that
possess similar demographic and morphological characteristics. This resulted in the
identification of seven area types that should share similar patterns of housing
development over time. Figure 5.2 shows the planning area types derived for each
administrative ward in 2001.

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Figure 5.2 2001 Planning area types used in household EGF calculation

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5.2.2
The trend in household change from 1991 to 2001 was taken from the Census
of Population household data. Due to large differences in the geography of the two
sources, a method was used to allow a comparison between them. This involves
breaking down 1991 ward to nearest equivalent OAs and then aggregating to
approximations of 2001 wards.
5.2.3
To increase the accuracy of the area type methodology, growth for different
planning areas were separated into regions. This will contribute towards accounting for
any regional variation in planning policy that may exist. Table 5.1 shows the assumed
growth rates for the planning area types in each region. Note that these are rounded to
the nearest whole percentage.
Table 5.1 Household growth by region and area type
Area Type
East
Midlands
East of
England
London
North
East
North
West
Scotland
South
East
South
West
Wales
West
Midlands
Yorkshire
and The
Humber
Urban Affluent
18%
14%
11%
6%
13%
12%
17%
16%
10%
10%
16%
Urban Other
6%
8%
10%
0%
2%
5%
9%
7%
5%
4%
2%
Suburban Affluent
11%
11%
6%
3%
8%
9%
10%
10%
11%
9%
9%
Suburban Other
11%
12%
0%
7%
7%
9%
9%
12%
10%
8%
8%
Fringe Affluent
14%
10%
4%
14%
11%
11%
9%
13%
15%
11%
16%
Fringe Other
14%
16%
8%
6%
9%
12%
14%
15%
7%
10%
11%
Rural Other
12%
10%
0%
30%
11%
13%
7%
13%
12%
17%
11%

5.2.4
Wards of the same planning area type in a region are assumed to have the
same level of growth (as indicated in Table 5.1). The final household growth factors for
each NTEM zone are therefore a weighted average of growth according to the
constituent OAs that nest within them and their residence within different planning area
types.
5.2.5
On allocating households at the zone level, these growth factors are used to
growth up the households that already exist in those zones. The total growth is
controlled to the total number of households expected in the control area. Therefore
growth factors are adjusted either proportionally (weights-based approach) or linearly
(trend-based approach) in order to obtain the required district household total.

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5.2.6
Figure 5.3 shows the input household EGFs within each control area district.
To aid analysis and understanding, the main detail to note is the relative difference in the
colours within each control area. This indicates the relative growth of each zone within
that control area, between which the total household growth is to be apportioned. The
actual colour presented is of little relevance when comparing different districts.

EXAMPLE

Selby zone in Yorks & Humber (zone code 36UH1) has 63 Output Areas of the
following types:

Urban Other

33 zones
2% expected growth rate
Fringe Other
14 zones
11% expected growth rate
Suburban Other
12 zones
8% expected growth rate
Suburban Affluent
4 zones
9% expected growth rate

Taking a weighted average of the expected rates of household growth within this
zone, Selby has an average expected growth factor of 5.6%

Barlby is a neighbouring zone within the same control area (zone code 36UH5). This
has 11 Output Areas of the following types:

Suburban Affluent
9 zones
9% expected growth rate
Fringe Other
2 zones
11% expected growth rate

Barlby has a weighted average growth factor of 9.4%.

In this example above, Barlby would be expected to receive more household growth
than Selby relative to its initial stock. This of course is not necessarily a greater total
number of households as this will depend on relative initial size and the total internal
adjustment required to the growth factors.

In 2001 Selby has 7,814 households and Barlby has 1,379. Using the growth
factors, the initial estimate of households is thus:

Selby
7,814 * 0.056 = + 438 households
Barlby 1,379 * 0.094 = + 130 households

As an example, if only these two zones were in the control area and our control total
of household growth is 700, we need to factor up the growth rates in order to
achieve this growth.

Using a weight-based approach, this is proportionately (maintaining the same ratio
between growth rates by multiplying through to get the correct growth required):

Selby
7,814 * (0.056 * 700/568) = 7,814 * 0.069 = 540 households
Barlby 1,379 * (0.094 * 700/568) = 1,379 * 0.116 = 160 households

Using a trend-based approach this is linearly (maintaining the same absolute
difference between growth rates):

Selby
7,814 * (0.056 + 0.0144) = 7,814 * 0.0705 = 550 households
Barlby 1,379 * (0.094 + 0.0144) = 1,379 * 0.1085 = 150 households

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Figure 5.3 Expected Growth Factors for households (district control areas)

5.3
EMPLOYMENT EGFS
5.3.1
Table 5.2 shows the proposed source of EGFs for each NTEM employment
type. These are derived by one of two approaches:

Dwellings-led (ie schools and leisure activities)

Constant, all assumed to grow relative to their existing size

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Table 5.2 Potential source of EGFs for each NTEM employment type a
Code
NTEM employment type
Potential EGF source
E03
Primary and secondary school employment
Dwellings-led
E04
Higher education employment
Constant, relative to size
E05
Adult education employment
Constant, relative to size
E06
Hotels, campsites, etc
Constant, relative to size
E07
Retail trade
Constant, relative to size
E08
Health/ medical employment
Constant, relative to size
E09
Services (business & other, eqpt rental, repairs)
Constant, relative to size
E10
Industry, construction and transport
Constant, relative to size
E11
Restaurants and bars
Constant, relative to size
E12
Recreation and sport
Dwellings-led
E13
Agriculture and fishing
Constant, relative to size
E14
Business
Constant, relative to size
E15
Holiday accommodation and second residences
Constant, relative to size

5.3.2
For dwelling-led growth, these types do not require input growth factors, since
they will be allocated using generated household results in the Scenario Generator tool.
5.3.3
The growth factors produced for the NTEM data sets versions 5 and 6 use a
weights-based approach. These factors are set as constant, therefore causing growth to
be distributed pro rata according to existing stock.
5.3.4
The Scenario Generator includes the capability to set the EGFs for each
forecast year. This allows the addition of more specific information where it may be
obtained, for example from approved employment developments and future Local Plans.

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6
Planning Data Results
6.1
INTRODUCTION
6.1.1
This section outlines the results from NTEM 6.2 and compares them with NTEM
5.4. This will help to explain:

The main trends in the NTEM 6.2 dataset as output from the Scenario
Generator, National Car Ownership Model and National Trip End Model;

The similarities and differences between the NTEM 5.4 and 6.2 datasets to
show how the planning data and ultimately the trip ends may differ from before.
6.1.2
Where data are analysed at a spatially detailed level, the forecast year of 2021
has been used to review the results midway through the forecast process.

6.2
PLANNING DATA (SCENARIO GENERATOR)
PLANNING DATA INTERPRETATION
AVERAGE HOUSEHOLD SIZE
6.2.1
Average household sizes decrease over time as shown in Figure 6.1. These
differ from the implied household sizes from the input projection data due to the impacts
of housing pressure as explained below. The Wider South East has the highest average
household size by 2026 as insufficient dwellings allocations prevent household formation
and more people living together in 2+ person households.
1.75
2.00
2.25
2.50
2001
2006
2011
2016
2021
2026
2031
2036
2041
Average household size
Year
East Midlands
North East
North West
Scotland
South West
Wales
West Midlands
Wider South East
Yorks & Humber

Figure 6.1 Average household sizes in each study area

6.2.2
Figure 6.2 shows the average household sizes at the district level in the 2021
forecast year. The separate chart colours represent the nine study areas. Most districts
fall into a range of around 2 to 2.3 persons per household (72%). Wider South East
shows the largest spread of household sizes by 2021- the highest in Slough at 2.56
persons per household and the lowest in City of London at 1.77.

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Figure 6.2 Average household size by district in 2021
VACANCY RATES
6.2.3
Figure 6.3 shows the vacancy rate by district in 2021.

Figure 6.3 Vacancy rates by district in 2021

6.2.4
Observations concerning vacancy rates over time are as follows:

Generally high in Scotland, the North East, the North West and the West
Midlands.

Bournemouth in the South West and Eilean Siar in Scotland are relatively very
high compared to other districts in these two Regions.

In most Regions with relatively low vacancy rates by 2021, all constituent
districts converge to the base rate of 1% towards 2041. This is due to
household inputs being relatively higher than dwelling inputs at the Regional
level.

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HOUSING PRESSURE
6.2.5
Where household capacity is insufficient within one control area (district) 50% of
the excess households are reallocated evenly to the other control areas (districts) in the
Region with vacant dwellings available and the other half of the excess are suppressed.

6.2.6
Figure 6.4 and
6.2.7
Figure 6.5 below show information from the household allocation process in the
Scenario Generator for forecast runs of each year and study area, showing first the
capacity after the initial allocation and secondly the households suppressed during the
allocation process based on space available.

Figure 6.4 Household capacity before reallocating or suppressing excess
households

Figure 6.5 Households suppressed

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6.2.8
Figure 6.6 shows the number of remaining vacant dwellings after reallocating
the initial excess households in each NTEM zone. It can be seen that some areas with
relatively high household capacity such as Wider South East has no vacant dwellings left
in the later years. This is due to large amount of suppression and reallocation within
those regions. On the other hand, Scotland and the North West are among the areas
which still have some vacant dwellings left after reallocating of the excess households.

Figure 6.6 Remaining Vacant Dwellings after reallocation process

6.2.9
In general, compared to NTEM 5.4, the housing pressure and so the number of
suppressed households is increased substantially, in some locations by around 100%.
Overall household and dwellings inputs to the NTEM forecasts for 2041 are both lower in
NTEM 6.2 than in NTEM 5.4. In key areas the reduction in dwellings provision is greater
than the change in household projections. In the Wider South East for instance, the
spare capacity declines to 0 after 2021 resulting in suppressing around 400,000
households in 2041.
6.2.10 It can be seen in the Wider South East and East Midlands in particular that the
number of households input for the Region and hence attempted to be allocated is
greater than the planned number of household spaces (effectively dwellings) This is
indicative of the extrapolated DCLG household projections being greater than the
extrapolated policy-based dwellings data. Spare capacity is consumed in the earlier
forecast years, resultantly limiting capacity in future years.
6.2.11 In the example of Scotland and the North West, housing pressure is much less
than in the South East due to a smoother increasing trend in population and a more than
sufficient planned supply of dwellings that meet the projected household input.
Therefore there is always spare capacity in this study area and hence minimal
household suppression.

RATIO OF WORKERS TO JOBS
6.2.12 The mild declining trend of changes in the ratio of workers to jobs is similar to
the one observed in NTEM 5.4. This is because employment forecasts are fairly in line
with population forecasts and hence there are sufficient people under pensionable age

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to fill the jobs. The profile changes slightly as the employment sectors with different
levels of job sharing grow at different rates through time.
6.2.13 As shown in Figure 6.7, the Regions with the lowest ratios of workers to jobs are
the Wider South East and, Scotland.

Figure 6.7 Ratio of workers to jobs by Region over time

COMPARISON OF PLANNING DATA OUTPUTS
6.2.14 A comparison has been made between old and new planning data results by
comparing the car ownership model target files produced from the Scenario Generator
runs. The analyses are shown at the Region and district levels.
6.2.15 At the Great Britain level, there is little change in population and household
totals between NTEM 5.4 and 6.2. However, the difference in jobs is more significant.
Table 6.1 and Figure 6.8 show this for ten year steps from 2001 to 2041.
6.2.16 The small differences in jobs in 2001 reflect the effect of changes in
methodology of estimating the number of base year jobs in NTEM 6.2 (see section 3.5).

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Table 6.1 Comparison of planning data for Great Britain, v6.2 and v5.4
Year
Household
Population
Jobs
1 Person
households
2+ Person
households
Total
households
NTEM 6.2

2001
56,405,000
28,505,000
7,222,000
16,685,000
23,907,000
2011
59,679,000
29,831,000
9,083,000
17,024,000
26,107,000
2021
63,746,000
31,576,000
10,868,000
17,876,000
28,744,000
2031
67,392,000
32,591,000
12,567,000
18,448,000
31,015,000
2041
70,337,000
33,911,000
14,245,000
18,763,000
33,008,000
NTEM 5.4

2001
56,405,000
28,859,000
7,222,000
16,685,000
23,906,000
2011
59,892,000
31,710,000
8,847,000
17,449,000
26,296,000
2021
64,123,000
33,403,000
10,737,000
18,245,000
28,982,000
2031
67,679,000
35,967,000
12,776,000
19,184,000
31,960,000
2041
71,167,000
38,684,000
15,207,000
20,224,000
35,431,000
Absolute difference (v6.2 – v5.4)
2001
0
-354,000
0
0
1,000
2011
-213,000
-1,879,000
236,000
-425,000
-189,000
2021
-377,000
-1,827,000
131,000
-369,000
-238,000
2031
-287,000
-3,376,000
-209,000
-736,000
-945,000
2041
-830,000
-4,773,000
-962,000
-1,461,000
-2,423,000
Relative difference (%)
2001
0.00%
-1.23%
0.00%
0.00%
0.00%
2011
-0.36%
-5.93%
2.67%
-2.44%
-0.72%
2021
-0.59%
-5.47%
1.22%
-2.02%
-0.82%
2031
-0.42%
-9.39%
-1.64%
-3.84%
-2.96%
2041
-1.17%
-12.34%
-6.33%
-7.22%
-6.84%

Figure 6.8 Comparison of planning data output totals, v6.2 versus v5.4

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6.2.17 The following observations can be made:

Total population was slightly higher in v5.4 than v6.2 in the later forecast years,
while it is the same in the base year in both versions. This is also the case for
the number of one person and 2+ person households.

Total employment is lower in v6.2 compared to v5.4 in both base and future
years specifically in the later forecast years.
6.2.18 Figure 6.9 shows differences between versions at the Regional level for 2021.
This is a comparison between the National Car Ownership Model target file as output by
the Scenario Generator. Employment in the chart is defined as people of working age in
employment.

Figure 6.9 Relative difference in population, households and employed persons in
2021 (NTEM 6.2 planning data versus NTEM 5.4)

6.2.19 Most Regions on the whole show some discrepancies between the two planning
data versions specifically for employment. Figure 6.10 below shows absolute
differences in key demographic variables by Region. An observation of note is that the
male FT and PT and female FT employment is lower across the board than in the
previous planning data. In Wider South East, this reduction is more significant. Overall
total population in 2021 in Great Britain is lower by only 377,000 while the number in
employment is lower by 573,000. The absolute difference is 238,000 for total number of
households.

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Figure 6.10 Absolute difference in population, households and employed persons
in 2021 (NTEM 6.2 planning data versus NTEM 5.4, thousands)

6.2.20 Growth in NTEM zone level demographic variables show some differences, as
shown in the Figures below for population, households and employment growth. As a
result, users of the planning data – and ultimately the trip end data – may find some
differences between NTEM 6.2 and NTEM 5.4. This is especially the case where zone
level data is used.
6.2.21 The population growth presented in Figure 6.11 should be largely in line with the
ONS population projections at the control area level. This will vary, however, where
population is moved across each Region through the household allocation process. The
spatial variability is similar between the two versions. The growth rate from 2011 to
2031 in general is lower on the north coast of Cornwall and the North West, particularly
the lake district, and slightly higher in the south west of Wales and the highlands of
Scotland in NTEM V6.2 compared to that in NTEM V5.4.
Household growth shown in Figure 6.12 displays more differences between the two
versions compared to growth in population. The growth rate is higher in Scotland and
parts of the South West, where household capacity was more and household
suspension was lower (refer to
6.2.22
Figure 6.4 and Figure 6.5) and lower in the North West due to the lower
population, and in the South East due to limited dwelling provision.

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Figure 6.11 Growth in total population 2011-2031 by zone in NTEM 6.2 (left) and
NTEM 5.4 (right)

Figure 6.12 Growth in total households 2011-2031 by zone in NTEM 6.2 (left) and
NTEM 5.4 (right)

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6.2.23 Employment levels demonstrate significant differences between the two
versions. Figure 6.13 shows the difference in the growth rate between 2011 and 2031.
NTEM 6.2 shows the general trend of much lower growth in employment in the whole
GB, particularly the in the south of England compared to NTEM 5.4. A few areas are still
forecast to grow quite strongly including parts of Wales and South Cambridgeshire.
6.2.24 The main cause of this lower level of growth in NTEM 6.2 is that the national
employment growth forecast has been altered in line with the economic downturn.

Figure 6.13 Relative difference in total employment (jobs) by zone, 2011 – 2031;
NTEM 6.2 (left) and NTEM 5.4 (right)

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6.3
NATIONAL CAR OWNERSHIP MODEL
GREAT BRITAIN COMPARISONS
6.3.1
The table and chart below show the comparison between old and new car
ownership forecasts for Great Britain. These show that the different versions of car
ownership data compare relatively well: there have been no significant changes to the
car ownership model other than revised purchase costs and GDP. Version 6.2 has a
slightly lower proportion of households without a car and a greater proportion of one-car
households.
6.3.2
Regional level car ownership profiles reflect a very similar trend to the Great
Britain profile.
Table 6.2 Household car ownership in Great Britain, v6.2 versus v5.4

Household owning x cars

Absolute Values (thousands)
Proportions (%)
Year
0 cars
1 car
2 cars
3+
cars
P0
P1
P2
P3P
Version 5.4

2001
6,578
10,464
5,508
1,357
28%
44%
23%
6%
2006
6,497
11,138
5,898
1,512
26%
44%
24%
6%
2011
6,332
11,875
6,410
1,679
24%
45%
24%
6%
2016
6,335
12,566
6,847
1,811
23%
46%
25%
7%
2021
6,433
13,343
7,282
1,924
22%
46%
25%
7%
2026
6,541
14,019
7,653
2,049
22%
46%
25%
7%
2031
6,737
14,993
8,085
2,145
21%
47%
25%
7%
2036
6,830
15,947
8,555
2,275
20%
47%
25%
7%
2041
7,022
17,033
9,013
2,363
20%
48%
25%
7%
Version 6.2

2001
6,474
10,466
5,586
1,381
27%
44%
23%
6%
2006
5,838
11,366
6,120
1,579
23%
46%
25%
6%
2011
5,908
12,319
6,298
1,582
23%
47%
24%
6%
2016
5,713
13,207
6,806
1,727
21%
48%
25%
6%
2021
5,860
13,917
7,149
1,817
20%
48%
25%
6%
2026
5,940
14,512
7,486
1,950
20%
49%
25%
7%
2031
6,016
15,133
7,802
2,064
19%
49%
25%
7%
2036
6,036
15,705
8,129
2,209
19%
49%
25%
7%
2041
6,010
16,157
8,453
2,388
18%
49%
26%
7%
Comparison: v6.2-5.4

2001
-104
2
78
24
-0.4%
0.0%
0.3%
0.1%
2006
-660
227
222
67
-2.5%
1.2%
1.0%
0.3%
2011
-424
444
-111
-97
-1.5%
2.0%
-0.3%
-0.3%
2016
-622
641
-41
-84
-2.2%
2.5%
-0.1%
-0.3%
2021
-573
574
-133
-106
-1.8%
2.4%
-0.3%
-0.3%
2026
-601
493
-167
-99
-1.7%
2.2%
-0.2%
-0.2%
2031
-721
140
-283
-81
-1.7%
1.9%
-0.1%
-0.1%
2036
-793
-242
-427
-66
-1.5%
1.5%
-0.1%
0.1%
2041
-1,012
-876
-560
25
-1.6%
0.9%
0.2%
0.6%

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0%
10%
20%
30%
40%
50%
60%
2001
2006
2011
2016
2021
2026
2031
2036
2041
Proportion of total households
Year
0 car HH v5.4
1 car HH v5.4
2 car HH v5.4
3+ car HH v5.4
0 car HH v6.2
1 car HH v6.2
2 car HH v6.2
3+ car HH v6.2

Figure 6.14 Car ownership through time (v6.2 versus v5.4)

6.3.3
Figure 6.15 shows the average number of cars per household in each district in
2031. More dense urban areas tend to have fewer cars per household than districts
outside of metropolitan areas. The Wider South East outside of Greater London has the
highest level of car ownership. The pattern between the two versions is broadly similar.

Figure 6.15 Cars per household 2031 by zone, NTEM 6.2 (left) and NTEM 5.4 (right)

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DISTRICT LEVEL COMPARISONS
6.3.4
District level maps of the change in households by cars owned can be seen in
Figure 6.16. This demonstrates the general trend of increased car ownership through
time across Great Britain, with greater levels of growth in higher car owning households.

Figure 6.16 District growth in households by car ownership, 2011-2031, NTEM 6.2

6.3.5
NTEM 6.2 does show some differences in household car ownership proportions
when compared to v5.4. This comparison is shown in the maps in Figure 6.17. As

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demonstrated at a global level, most areas experience a decline in the proportion of
households without a car and an increase in the proportion with 1 car. The spatial
pattern of changes for the households with two and three or more cars is more mixed
though the changes are relatively small.

Figure 6.17 Difference in proportion of household car ownership 2031 by zone
between NTEM versions (v6.2 proportion minus v5.4 proportion of total
households)

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6.4
NATIONAL TRIP END MODEL
COMPARISON OF TOTAL TRIPS
6.4.1
The National Trip End Model gives details of trip productions and attractions
that are ultimately made available through the TEMPRO system. Several differences
exist between the previous and latest versions of the data. In summary, the volume of
trips made in NTEM 6.2 is slightly less in the later forecast years than in the previous
version. This is due to lower population and the overall decrease in employment in
NTEM 6.2.
6.4.2
District and zone level trip patterns may also differ to a large extent due to
variations in dwellings and household allocation and employment locations from the
previous version.
Table 6.3 Comparison of total trip productions for Great Britain between v6.2 and
v5.4 (millions per average day)
Version
2001
2006
2011
2016
2021
2026
2031
2036
2041
NTEM 6.2
93.9
97.5
100.5
104.2
107.5
110.7
113.4
115.9
118.7
NTEM 5.4
93.6
96.5
100.7
104.4
107.9
111.0
113.9
117.0
120.4
Difference
0.4
0.9
-0.1
-0.2
-0.3
-0.3
-0.6
-1.1
-1.7
% Difference
0.4%
1.0%
-0.1%
-0.2%
-0.3%
-0.2%
-0.5%
-0.9%
-1.4%

80
85
90
95
100
105
110
115
120
125
2001
2006
2011
2016
2021
2026
2031
2036
2041
Trip productions
Millions
Year
NTEM 6.2
NTEM 5.4

Figure 6.18 Change in Trip Productions over time: NTEM 6.2 v NTEM 5.4 (millions)

6.4.3
Comparing total trips from the National Trip End Model between the two
versions, it is evident that version 6.2 has only slightly less.

The main reason for less number of trips in the latest version of NTEM could be
mainly related to lower population and to using revised version of employment
projection data which predict considerably less number of jobs compared to that
provided in the employment projection data used for NTEM V5.4. Trip rates
vary by working status hence the trip end forecasts adjust in line with
employment changes.

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TRIPS BY PURPOSE
6.4.4
Figure 6.19 shows the trend in trips made by purpose through time for an
average day.
0
5
10
15
20
25
2001
2006
2011
2016
2021
2026
2031
2036
2041
Total trips
Millions
Year
HBW
HBEB
HBEd
HBShop
HBPB
HBRec
HBVF
HBHols
NHBW
NHBEB
NHBEd
NHBShop
NHBPB
NHBRecVF
NHBHols

Figure 6.19 Total trips in the average day by purpose in Great Britain, NTEM 6.2

6.4.5
In NTEM 6.2, as with NTEM 5.4, most trip purposes show an increase in the
number of trips through time, due to the population increases. Some purposes such as
HBW and HBEB show a dip in total number of trips between 2006 and 2011, a result of
the economic downturn.
6.4.6
Figure 6.20 shows the proportional change in trips made in an average day by
purpose over time between NTEM 5.4 and NTEM 6.2. This clearly shows that unlike the
small difference in number of trips over all purposes, the purpose by purpose difference
is quite significant specifically for home based and non home based work and business
and education purposes.
6.4.7
As expected the difference is biggest in 2011 as the number of trips is estimated
to be less for work and business trips and more for education trips. This difference has
then become smaller for the later forecast years.

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-10.0%
-8.0%
-6.0%
-4.0%
-2.0%
0.0%
2.0%
4.0%
6.0%
8.0%
2001
2006
2011
2016
2021
2026
2031
2036
2041
% Difference in total trips
Year
HBW
HBEB
HBEd
HBShop
HBPB
HBRec
HBHols
HBVF
NHBW
NHBEB
NHBEd
NHBShop
NHBPB
NHBRecVF
NHBHols
Total

Figure 6.20 Relative difference in total trips by purpose over time in Great Britain;
NTEM 6.2 v NTEM 5.4

AVERAGE TRIPS PER HOUSEHOLD
6.4.8
The trends in the average number of trips per household in the two versions are
shown in Figure 6.21 and Figure 6.22 below. Both data sets show a similar decrease in
the number of trips.
NTEM 6.2
3.00
3.25
3.50
3.75
4.00
4.25
4.50
2001
2006
2011
2016
2021
2026
2031
2036
2041
Year
Trips per household
East Midlands
North East
North West
Scotland
South West
Wales
West Midlands
Wider South East
Yorks & Humber
GB

Figure 6.21 Trips per households by study area in the average day, NTEM 6.2

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NTEM 5.4
3.00
3.25
3.50
3.75
4.00
4.25
4.50
2001
2006
2011
2016
2021
2026
2031
2036
2041
Year
Trips per household
East Midlands
North East
North West
Scotland
South West
Wales
West Midlands
Wider South East
Yorks & Humber
GB

Figure 6.22 Trips per households by study area in the average day, NTEM 5.4

AVERAGE TRIPS PER PERSON
6.4.9
Trips per person in each study area have a slight upward trend over time after
the dip in 2011. Overall change however is minimal since trip rates have not been
modified through time.
NTEM 6.2
1.50
1.55
1.60
1.65
1.70
1.75
2001
2006
2011
2016
2021
2026
2031
2036
2041
Year
Average daily trips per person
East Midlands
North East
North West
Scotland
South West
Wales
West Midlands
Wider South East
Yorks & Humber
GB

Figure 6.23 Trips per person by study area in the average day, NTEM v6.2

COMPARISON OF TRIP PRODUCTIONS AND ATTRACTIONS
6.4.10 Figure 6.24 below shows a comparison of the total trip productions and
attractions (summed over all modes) at the district level from the trip end model results
between NTEM 5.4 and NTEM 6.2.

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Figure 6.24 Growth in trip productions and attractions by district, 2011-2031,
comparison between versions

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6.4.11
Figure 6.25 below compares the rate of growth through time in trip ends by
mode in NTEM 6.2 compared with NTEM 5.4. It should be remembered that the mode
split in NTEM is a constant cost mode split which ignores any changes in the costs of
motoring (fuel and taxation) and public transport fares. These need to be taken into
account separately when using modal NTEM forecasts. This shows that the car trips
continue to have the highest rate of growth through time, though the rate of growth in
NTEM 6.2 is lower than seen previously in NTEM 5.4. Bus travel continues to have the
lower rate of growth through time, though increased on the previous version. These
changes will be driven primarily by the forecast changes in car ownership.
Growth in trips by mode from 2001
0.90
1.00
1.10
1.20
1.30
1.40
1.50
2001
2006
2011
2016
2021
2026
2031
2036
2041
Walk v6.2
Walk v5.4
Cycle v6.2
Cycle v5.4
Car Driver v6.2
Car Driver v5.4
Car Pax v6.2
Car Pax v5.4
Bus v6.2
Bus v5.4
Rail v6.2
Rail v5.4

Figure 6.25 Rate of growth of modal trip ends (NTEM 6.2 v NTEM 5.4)

Appendices, Figures & Tables

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Appendix A
Geography

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BALANCING AREAS

Figure A.1 Balancing areas in Great Britain

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STUDY AREAS AND NTEM ZONES

Figure A.2 Study areas used in the Scenario Generator and overlaid NTEM zones.
NB All Scottish islands are also included but may appear off the map

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Table A.1 NTEM zones within each study area
Zone
Code
ZoneName
Zone
Code
ZoneName
Zone
Code
ZoneName
East Midlands
1590
31UB4
Whetstone
1669
32UF4
Long Sutton
454
00FK0
rural
1591
31UB5
Cosby
1670
32UF5
Crowland
455
00FK1
Derby(main)
1592
31UB6
Earl Shilton(part of)
1671
32UF6
Sutton Bridge
456
00FN0
rural
1593
31UB7
Enderby
1672
32UG0
rural
457
00FN1
Leicester(main)
1594
31UB8
Narborough
1673
32UG1
Grantham
458
00FN2
Beaumont Leys
1595
31UB9
Countesthorpe
1674
32UG2
Great Gonerby
459
00FP0
rural
1596
31UC0
rural
1675
32UG3
Stamford
460
00FP1
Oakham
1597
31UC1
Leicester(part of)
1676
32UG4
Market Deeping(main)
461
00FP2
Uppingham
1598
31UC10
Markfield(part of)
1677
32UG5
Bourne
462
00FY1
Nottingham(main)
1599
31UC11
Quorndon
1678
32UH0
rural
463
00FY2
Clifton
1600
31UC2
Birstall
1679
32UH1
Lincoln(part of)
464
00FY3
West Bridgford(part of)
1601
31UC4
Loughborough
xx-xxxx-xxxx
32UH2
Gainsborough
465
00FY4
Carlton(part of)
1602
31UC5
Shepshed
xx-xxxx-xxxx
32UH3
Welton/Dunholme
987
17UB0
rural
1603
31UC6
Mountsorrel
xx-xxxx-xxxx
32UH4
Saxilby
988
17UB00
rural
1604
31UC7
Sileby
xx-xxxx-xxxx
32UH5
Cherry Willingham/Reepham
989
17UB1
Heanor
1605
31UC8
Anstey
xx-xxxx-xxxx
32UH6
Nettleham
990
17UB2
Ripley
1606
31UC9
Barrow upon Soar
xx-xxxx-xxxx
32UH7
Market Rasen
991
17UB3
Derby(part of)
1607
31UD0
rural
1734
34UB0
rural
992
17UB4
Alfreton
1608
31UD1
Leicester(part of)
1735
34UB1
Corby
993
17UB5
Jacksdale(part of)
1609
31UD2
Market Harborough
1736
34UC0
rural
994
17UB6
Belper
1610
31UD3
Lutterworth
1737
34UC1
Northampton(part of)
995
17UB7
Duffield
1611
31UD4
Broughton Astley
1738
34UC2
Daventry
996
17UB8
Kiburn
1612
31UD5
Kibworth Harcourt
1739
34UC3
Brixworth
997
17UC0
rural
1613
31UD6
Fleckney
1740
34UC4
Long Buckby
998
17UC2
Mansfield(part of)
1614
31UE0
rural
1741
34UC5
Hinton
999
17UC3
South
Normanton/Pinxton(main)
1615
31UE1
Groby
1742
34UD0
rural
1000
17UC4
Bolsover
1616
31UE2
Ratby
1743
34UD00
rural
1001
17UC5
Shirebrook
1617
31UE3
Hinckley
1744
34UD1
Rushden(main)
1002
17UC6
Clowne
1618
31UE4
Earl Shilton(main)
1745
34UD2
Higham Ferrers
1003
17UC7
Creswell
1619
31UE5
Atherstone(part of)
1746
34UD3
Raunds
1004
17UC8
Whitwell nr Worksop
1620
31UE6
Markfield(main)
1747
34UD4
Irthlingborough
1005
17UC9
Tibshelf
1621
31UE7
Desford
1748
34UD5
Oundle
1006
17UD0
rural
1622
31UE8
Newbold Verdon
1749
34UD6
Thrapston
1007
17UD1
Chesterfield(main)
1623
31UG0
rural
1750
34UE0
rural
1008
17UD2
Staveley(main)
1624
31UG1
Melton Mowbray
1751
34UE1
Kettering
1009
17UD3
New Whittington
1625
31UG2
Bottesford
1752
34UE2
Burton Latimer
1010
17UF0
rural
1626
31UH0
rural
1753
34UE3
Desborough
1011
17UF1
Matlock
1627
31UH1
Donisthorpe
1754
34UE4
Rothwell
1012
17UF2
Ashbourne
1628
31UH2
Swadlincote(part of)
1755
34UF0
rural
1013
17UF3
Wirksworth
1629
31UH3
Coalville
1756
34UF1
Northampton(main)
1014
17UF5
Bakewell
1630
31UH4
Ashby-de-la-Zouch
1757
34UF2
Wootton/Hardingstone(main)
1015
17UF6
Darley Dales
1631
31UH5
Castle Donington
1758
34UG0
rural
1016
17UG0
rural
1632
31UH6
Ibstock
1759
34UG1
Wootton/Hardingstone(part of)
1017
17UG1
Long Eaton
1633
31UH7
Measham
1760
34UG2
Brackley
1018
17UG2
IIkeston
1634
31UH8
Kegworth
1761
34UG3
Towcester
1019
17UG3
Breaston
1635
31UJ1
Wigston
1762
34UG4
Middleton Cheney
1020
17UG4
Borrowash
1636
31UJ2
Oadby
1763
34UH0
rural
1021
17UG6
Derby(part of)
1637
32UB0
rural
1764
34UH1
Wellingborough
1022
17UG7
West Hallam
1638
32UB1
Boston
1765
34UH3
Earls Barton
1023
17UH0
rural
1639
32UB2
Kirton (Boston)
1766
34UH4
Irchester
1024
17UH1
Glossop/Hollingworth(main)
xx-xxxx-xxxx
32UC0
rural
1767
34UH5
Finedon
1025
17UH2
Buxton
xx-xxxx-xxxx
32UC1
Skegness
1768
34UH6
Wollaston
1026
17UH3
New Mills(main)
xx-xxxx-xxxx
32UC10
Alford
1826
37UB0
rural
1027
17UH4
Chapel-en-Le-Frith
xx-xxxx-xxxx
32UC2
Ingoldmells
1827
37UB1
Hucknall
1028
17UH5
Whaley Bridge
xx-xxxx-xxxx
32UC3
Louth
1828
37UB2
Sutton in Ashfield
1029
17UJ0
rural
xx-xxxx-xxxx
32UC4
Mablethorpe/Sutton on Sea
1829
37UB3
Kirkby in Ashfield(main)
1030
17UJ1
Mosborough/Highlane(part of)
xx-xxxx-xxxx
32UC5
Horncastle
1830
37UB4
Jacksdale(main)
1031
17UJ10
Wingerworth
xx-xxxx-xxxx
32UC6
Coningsby
1831
37UB5
South Normanton/Pinxton(part of)
1032
17UJ11
Shirland
xx-xxxx-xxxx
32UC7
Woodhall Spa(main)
1832
37UB6
Selston/Underwood/Brimsley(main)
1033
17UJ13
Grassmoor
xx-xxxx-xxxx
32UC8
Holton le Clay
1833
37UC0
rural
1034
17UJ14
Pilsley/Lower Pilsley
1650
32UC9
Chapel St Leonards
1834
37UC1
Worksop
1035
17UJ2
Staveley(part of)
1651
32UD1
Lincoln(main)
1835
37UC2
East Retford
1036
17UJ4
Chesterfield(part of)
1652
32UD2
Birchwood
1836
37UC3
Carlton-in-Lindrick
1037
17UJ5
Dronfield
1653
32UE0
rural
1837
37UC5
Harworth/Bircotes
1038
17UJ6
Clay Cross/North Wingfield
1654
32UE1
Lincoln(part of)
1838
37UD0
rural
1039
17UJ7
Killamarsh
1655
32UE10
Metheringham
1839
37UD1
Beeston and Stapleford
1040
17UJ8
Eckington
1656
32UE11
Skellingthorpe
1840
37UD2
Eastwood
1041
17UK0
rural
1657
32UE2
Waddington
1841
37UD3
Kimberley
1042
17UK1
Derby(part of)
1658
32UE3
Sleaford
1842
37UD4
Nottingham(part of)
1043
17UK2
Swadlincote(main)
1659
32UE4
Heighington/Washingborough
1843
37UD6
Selston/Underwood/Brimsley(part
of)
1044
17UK3
Stapenhill/Winshill(part of)
1660
32UE5
Ruskington
1844
37UE0
rural
1045
17UK4
Tutbury/Hatton(part of)
1661
32UE6
Bracebridge Heath
1845
37UE1
Carlton(main)
1046
17UK5
Melbourne
1662
32UE7
Woodhall Spa(part of)
1846
37UE2
Arnold
1047
17UK6
Hilton
1663
32UE8
Branston
1847
37UE3
Nottingham(part of)
1585
31UB0
rural
1664
32UE9
Heckington
1848
37UE4
Kirkby in Ashfield(part of)
1586
31UB1
Leicester(part of)
1665
32UF0
rural
1849
37UE5
Calverton
1587
31UB10
Stoney Stanton
1666
32UF1
Spalding
1850
37UE6
Ravenshead
1588
31UB2
Kirby Muxloe
1667
32UF2
Pinchbeck
1851
37UE7
Burton Joyce(main)
1589
31UB3
Blaby
1668
32UF3
Holbeach
1852
37UF0
rural

11642097
NTEM 62 Guidance

ZoneID
Zonecode
ZoneName
ZoneID
Zonecode
ZoneName
ZoneID
Zonecode
ZoneName
1853
37UF1
Mansfield(main)
392
00EF3
Thornaby
North West
1854
37UF2
Mansfield Woodhouse
393
00EF4
Ingleby
58
00BL0
rural
1855
37UF3
Warsop
394
00EF6
Eaglescliffe
59
00BL1
Bolton(main)
1856
37UF4
Rainworth(part of)
395
00EH0
rural
60
00BL10
Blackrod
1857
37UG0
rural
396
00EH1
Darlington
61
00BL2
Farnworth
1858
37UG00
rural
1128
20UB0
rural
62
00BL3
Bromley Cross/Bradshaw
1859
37UG1
Mansfield(part of)
1129
20UB1
Chester-le-Street(main)
63
00BL4
Horwich
1860
37UG2
Newark-on-Trent
1130
20UB2
Houghton-Le-Spring(part of)
64
00BL5
Little Lever(main)
1861
37UG3
Boughton/Ollerton
1131
20UB3
Ouston
65
00BL6
Kearsley
1862
37UG4
Rainworth(main)
1132
20UB4
Pelton
66
00BL7
Atherton(part of)
1863
37UG5
Southwell
1133
20UB5
Sacriston
67
00BL8
Swinton and Pendlebury(part of)
1864
37UG6
Edwinstowe
1134
20UB6
Great Lumley
68
00BL9
Westhoughton
1865
37UG7
Blidworth
1135
20UD0
rural
69
00BM0
rural
1866
37UG8
Burton Joyce(part of)
1136
20UD1
Stanley
70
00BM1
Bury(main)
1867
37UG9
Bilsthorpe
1137
20UD10
Lanchester
71
00BM2
Radcliffe
1868
37UJ0
rural
1138
20UD2
Annfield Plain
72
00BM3
Prestwich
1869
37UJ00
rural
1139
20UD3
Consett
73
00BM4
Whitefield
1870
37UJ1
West Bridgford(main)
1140
20UD4
Leadgate
74
00BM5
Ramsbottom
1871
37UJ2
Ruddington
1141
20UD5
Castleside
75
00BM6
Tottington
1872
37UJ4
Bingham
1142
20UD6
Chopwell(part of)
76
00BM7
Middleton(part of)
1873
37UJ5
Cotgrave
1143
20UD7
Langley Park
77
00BM8
Little Lever(part of)
1874
37UJ6
Radcliffe on Trent
1144
20UD8
Esh Winning(part of)
78
00BM9
Manchester(part of)
1875
37UJ7
Keyworth
1145
20UD9
Burnopfield
79
00BN1
Manchester(main)
1876
37UJ8
East Leake
1146
20UE0
rural
80
00BN2
Stockport(part of)
North East
1147
20UE1
Durham
81
00BN3
Salford(part of)
233
00CH0
rural
1148
20UE2
Brandon nr Durham
82
00BN4
South Manchester
234
00CH1
Gateshead
1149
20UE3
Ushaw Moor
83
00BP0
rural
235
00CH2
Felling
1150
20UE4
Esh Winning(main)
84
00BP1
Oldham
236
00CH3
Whickham
1151
20UE5
Bowburn
85
00BP2
Chadderton
237
00CH4
Ryton
1152
20UE6
Coxhoe
86
00BP3
Royton
238
00CH5
Blaydon
1153
20UE7
Sherburn nr Durham
87
00BP4
Failsworth
239
00CH6
Chester-le-Street(part of)
1154
20UF0
rural
88
00BP5
Shaw
240
00CH7
Rowlands Gill
1155
20UF2
Peterlee
89
00BP6
Rochdale(part of)
241
00CH8
Chopwell(main)
1156
20UF3
Seaham
90
00BP7
Dobcross/Uppermill
242
00CH9
Sunniside
1157
20UF4
Easington
91
00BQ0
rural
243
00CJ0
rural
1158
20UF5
Murton
92
00BQ1
Rochdale(main)
244
00CJ1
Newcastle upon Tyne
1159
20UF6
Blackhall Colliery
93
00BQ2
Middleton(main)
245
00CJ2
Newburn
1160
20UF7
Wingate
94
00BQ3
Heywood
246
00CJ3
Gosforth
1161
20UF8
Shotton Colliery
95
00BQ4
Littleborough
247
00CJ4
Wide Open(part of)
1162
20UF9
Wheatley Hill
96
00BQ5
Milnrow
248
00CK0
rural
1163
20UG0
rural
97
00BQ6
Wardle
249
00CK1
Wallsend
1164
20UG00
rural
98
00BQ7
Bury(part of)
250
00CK2
North Shields
1165
20UG1
Newton Aycliffe
99
00BR0
rural
251
00CK3
Whitley Bay
1166
20UG2
Spennymoor
100
00BR1
Salford(main)
252
00CK4
Long Benton/Killingworth
1167
20UG3
Ferryhill
101
00BR2
Swinton and Pendlebury(main)
253
00CK5
Tynemouth
1168
20UG4
Shildon
102
00BR3
Eccles
254
00CK6
Shiremoor
1169
20UG5
Sedgefield
103
00BR4
Walkden
255
00CK7
Wide Open(main)
1170
20UG6
Chilton
104
00BR5
Irlam
256
00CK8
Dudley (Tyne & Wear)
1171
20UH0
rural
105
00BR6
Tyldesley(part of)
257
00CL0
rural
1172
20UH1
Barnard Castle
106
00BS0
rural
258
00CL1
South Shields
1173
20UJ0
rural
107
00BS1
Stockport(main)
259
00CL2
Jarrow
1174
20UJ1
Bishop Auckland
108
00BS2
Cheadle and Gatley
260
00CL3
Hebburn
1175
20UJ2
Crook
109
00BS3
Hazel Grove and Bramhall
261
00CL4
Boldon
1176
20UJ3
Willington nr Crook
110
00BS4
Bredbury and Romiley
262
00CL5
Cleadon
1177
20UJ4
Coundon
111
00BS5
Brinnington
263
00CL6
Whitburn
1769
35UB0
rural
112
00BS6
SouthManchester(part of)
264
00CM0
rural
1770
35UB1
Alnwick
113
00BS7
Marple
265
00CM1
Washington
1771
35UB2
Amble
114
00BS8
High Lane(main)
266
00CM2
Houghton-Le-Spring(main)
1772
35UC0
rural
115
00BT0
rural
267
00CM3
Hetton-le-Hole
1773
35UC1
Berwick-upon-Tweed
116
00BT1
Ashton-under-Lyne
268
00CM5
Sunderland
1774
35UD0
rural
117
00BT10
Glossop/Hollingworth(part of)
374
00EB0
rural
1775
35UD1
Blyth
118
00BT11
Mossley
375
00EB1
Hartlepool
1776
35UD2
Cramlington
119
00BT12
Buckton Vale
376
00EC0
rural
1777
35UD3
Seaton Delaval
120
00BT2
Hyde
377
00EC1
Middlesbrough(main)
1778
35UD4
Seaton Sluice
121
00BT3
Denton
378
00EE0
rural
1779
35UE0
rural
122
00BT4
Droylsden
379
00EE1
Redcar
1780
35UE1
Morpeth
123
00BT5
Stalybridge
380
00EE10
New Marske
1781
35UE2
Ponteland
124
00BT6
Dukinfield
381
00EE2
Eston and South Bank
1782
35UE3
Pegswood
125
00BT7
Audenshaw
382
00EE3
Middlesbrough(part of)
1783
35UF0
rural
126
00BT8
Longdendale
383
00EE4
Guisborough
1784
35UF1
Hexham
127
00BT9
Stockport(part of)
384
00EE5
Marske-by-the-Sea
1785
35UF2
Prudhoe
128
00BU0
rural
385
00EE6
Skelton
1786
35UF3
Haltwhistle
129
00BU1
Sale
386
00EE7
Saltburn-by-the-Sea
1787
35UG0
rural
130
00BU2
Stretford
387
00EE8
Brotton
1788
35UG1
Ashington (Wansbeck)
131
00BU3
Urmston
388
00EE9
Loftus
1789
35UG2
Bedlington
132
00BU4
Altrincham
389
00EF0
rural
1790
35UG3
Guide Post
133
00BU5
Hale
390
00EF1
Stockton-on-Tees
1791
35UG4
Newbiggin-by-the-Sea
134
00BU6
Partington
391
00EF2
Billingham

135
00BU7
Bowdon

NTEM 62 Guidance
11642097

ZoneID
Zonecode
ZoneName
ZoneID
Zonecode
ZoneName
ZoneID
Zonecode
ZoneName
136
00BU8
SouthManchester(part of)
902
13UE1
Ellesmere Port(main)
1539
30UH1
Morecambe
137
00BW0
rural
903
13UE2
Neston
1540
30UH2
Lancaster
138
00BW1
Leigh
904
13UG0
rural
1541
30UH3
Bolton-le-Sands
139
00BW10
Abram
905
13UG00
rural
1542
30UH4
Carnforth
140
00BW11
Ashton-in-Makerfield(main)
906
13UG1
Wilmslow
1543
30UH5
Lancaster University
141
00BW12
Golborne
907
13UG10
Wilmslow
1544
30UJ0
rural
142
00BW13
Appley Bridge(main)
908
13UG2
Poynton
1545
30UJ1
Nelson
143
00BW14
Shevington
909
13UG3
Macclesfield
1546
30UJ2
Colne
144
00BW15
Aspull
910
13UG4
Prestbury
1547
30UJ3
Brierfield
145
00BW2
Tyldesley(main)
911
13UG5
Knutsford
1548
30UJ4
Barrowford & Carr Hall
146
00BW3
Hindley
912
13UG6
New Mills(part of)
1549
30UJ6
Barnoldswick
147
00BW4
Atherton(main)
913
13UG7
Bollington
1550
30UJ7
Earby
148
00BW6
Wigan
914
13UG8
High Lane(part of)
1551
30UK0
rural
149
00BW7
Standish
915
13UG9
Disley
1552
30UK1
Preston(main)
150
00BW8
Ince-in-Makerfield
916
13UH0
rural
1553
30UK2
Longridge(part of)
151
00BW9
Orrell(main)
917
13UH00
rural
1554
30UL0
rural
152
00BX0
rural
918
13UH1
Helsby
1555
30UL1
Blackburn(part of)
153
00BX1
Huyton-with-Roby
919
13UH2
Runcorn(part of)
1556
30UL2
Clitheroe
154
00BX2
Liverpool(part of)
920
13UH3
Northwich
1557
30UL3
Longridge(main)
155
00BX3
Prescot(main)
921
13UH4
Winsford
1558
30UL4
Whalley
156
00BX4
Widnes(part of)
922
13UH5
Frodsham
1559
30UM0
rural
157
00BX5
Kirkby(main)
923
13UH6
Weaverham
1560
30UM1
Whitworth
158
00BY1
Liverpool(main)
924
13UH7
Moulton (Vale royal)
1561
30UM2
Accrington(part of)
159
00BZ0
rural
925
13UH8
Sandiway
1562
30UM3
Rawtenstall
160
00BZ1
St Helens
958
16UB0
rural
1563
30UM4
Haslingden
161
00BZ2
Haydock
959
16UB1
Workington
1564
30UM5
Bacup
162
00BZ3
Prescot(part of)
960
16UB2
Seaton nr Workington
1565
30UN0
rural
163
00BZ4
Ashton-in-Makerfield(part of)
961
16UB4
Maryport
1566
30UN1
Preston(part of)
164
00BZ5
Newton-le-Willows
962
16UB5
Cockermouth
1567
30UN2
Leyland(main)
165
00BZ6
Billinge
963
16UB6
Wigton
1568
30UN3
Longton
166
00BZ7
Rainford
964
16UB7
Keswick
1569
30UN4
Higher Walton(main)
167
00CA0
rural
965
16UC0
rural
1570
30UP0
rural
168
00CA1
Bootle
966
16UC1
Barrow-in-Furness
1571
30UP1
Skelmersdale
169
00CA2
Crosby
967
16UC2
Isle of Walney
1572
30UP2
Orrell(part of)
170
00CA3
Litherland
968
16UC3
Dalton-in-Furness
1573
30UP3
Southport(part of)
171
00CA4
Southport(main)
969
16UC4
Askam in Furness
1574
30UP4
Ormskirk
172
00CA5
Formby
970
16UD0
rural
1575
30UP5
Burscough Bridge
173
00CA6
Kirkby(part of)
971
16UD1
Carlisle
1576
30UP6
Tarleton
174
00CA7
Maghull/Lydiate
972
16UD2
Brampton nr Carlisle
1577
30UP7
Appley Bridge(part of)
175
00CB0
rural
973
16UE0
rural
1578
30UP8
Banks
176
00CB1
Birkenhead
974
16UE00
rural
1579
30UQ0
rural
177
00CB2
Wallasey
975
16UE1
Whitehaven
1580
30UQ1
Thornton/Cleveleys
178
00CB3
Bebington
976
16UE2
Cleator Moor
1581
30UQ2
Fleetwood
179
00CB4
Greasby/Moreton
977
16UE3
Millom
1582
30UQ3
Poulton-le-Fylde(main)
180
00CB5
Heswall
978
16UE4
Egremont
1583
30UQ4
Garstang
181
00CB6
Hoylake/West Kirby
979
16UF0
rural
1584
30UQ5
Preesall
397
00ET0
rural
980
16UF1
Penrith
Scotland
398
00ET1
Runcorn(main)
981
16UG0
rural
2233
QA0
rural
399
00ET2
Widnes(main)
982
16UG1
Kendal
2234
QA1
Aberdeen
400
00EU0
rural
983
16UG2
Ulverston
2235
QA2
Cove Bay
401
00EU1
Warrington
984
16UG3
Windermere
2236
QA3
Dyce
402
00EU2
Great Sankey
985
16UG4
Grange-over-Sands
2237
QA4
Kingswells
403
00EU3
Stockton Heath/Thelwall
986
16UG5
Ambleside
2238
QA5
Peterculter & Milltimber
404
00EU4
Risley
1513
30UD0
rural
2239
QB0
rural
405
00EU5
Lymm
1514
30UD1
Burnley
2240
QB15
Ellon
406
00EU6
Culcheth
1515
30UD2
Padiham
2241
QB16
Fraserburgh
407
00EU7
Burtonwood
1516
30UE0
rural
2242
QB21
Huntly
408
00EX0
rural
1517
30UE1
Chorley
2243
QB24
Inverurie
409
00EX1
Blackburn(main)
1518
30UE2
Clayton & Whittle-le-Woods
2244
QB26
Kemnay
410
00EX2
Darwen
1519
30UE3
Euxton
2245
QB30
Macduff
411
00EY1
Blackpool
1520
30UE4
Leyland(part of)
2246
QB39
Peterhead
884
13UB0
rural
1521
30UE6
Adlington
2247
QB41
Portlethen
885
13UB1
Ellesmere Port(part of)
1522
30UE7
Coppull
2248
QB49
Stonehaven
886
13UB2
Chester
1523
30UE8
Higher Walton(part of)
2249
QB55
Turriff
887
13UC0
rural
1524
30UE9
Eccleston
2250
QB56
Westhill (Aberdeensh
888
13UC1
Kidsgrove(part of)
1525
30UF0
rural
2251
QB6
Banchory
889
13UC2
Congleton
1526
30UF1
Lytham St. Anne's
2252
QB7
Banff
890
13UC3
Sandbach
1527
30UF2
Poulton-le-Fylde (part of)
2253
QC0
rural
891
13UC4
Alsager(main)
1528
30UF3
Kirkham
2254
QC1
Arbroath
892
13UC5
Middlewich
1529
30UF5
Freckleton/Warton
2255
QC11
Kirriemuir
893
13UC6
Holmes Chapel
1530
30UG0
rural
2256
QC13
Montrose
894
13UD0
rural
1531
30UG1
Blackburn(part of)
2257
QC3
Brechin
895
13UD00
rural
1532
30UG2
Accrington(main)
2258
QC4
Carnoustie
896
13UD1
Crewe
1533
30UG3
Oswaldwistle
2259
QC5
Dundee(part of)
897
13UD2
Alsager(part of)
1534
30UG4
Great Harwood (Hyndburn)
2260
QC8
Forfar
898
13UD3
Nantwich
1535
30UG5
Clayton-le-moors
2261
QD0
rural
899
13UD4
Haslington
1536
30UG6
Church
2262
QD00
rural
900
13UD5
Shavington
1537
30UG7
Rishton
2263
QD12
Oban
901
13UE0
rural
1538
30UH0
rural
2264
QD17
Rothesay

11642097
NTEM 62 Guidance

ZoneID
Zonecode
ZoneName
ZoneID
Zonecode
ZoneName
ZoneID
Zonecode
ZoneName
2265
QD3
Campbeltown
2344
QQ11
Grangemouth
2423
QZ13
Coatbridge
2266
QD6
Dunoon
2345
QQ13
Hallglen (Falkirk)
2424
QZ15
Cumbernauld
2267
QD8
Helensburgh
2346
QQ14
Polmont
2425
QZ22
Holytown
2268
QE0
rural
2347
QQ17
Stenhousemuir
2426
QZ23
Kilsyth
2269
QE11
Hawick
2348
QQ4
Bo'ness
2427
QZ24
Moodiesburn
2270
QE13
Jedburgh
2349
QQ5
Bonnybridge
2428
QZ25
Motherwell
2271
QE14
Kelso
2350
QQ7
Carron
2429
QZ27
New Stevenston
2272
QE20
Peebles
2351
QQ8
Denny
2430
QZ28
Newarthill
2273
QE21
Selkirk
2352
QR0
rural
2431
QZ29
Newmains
2274
QE8
Eyemouth
2353
QR10
Cardenden
2432
QZ33
Shotts
2275
QE9
Galashiels
2354
QR14
Cowdenbeath
2433
QZ34
Stepps
2276
QF0
rural
2355
QR18
Cupar
2434
QZ35
Viewpark
2277
QF1
Alloa
2356
QR19
Dalgety Bay
2435
QZ36
Wishaw
2278
QF2
Alva
2357
QR2
Anstruther
2436
QZ5
Bellshill
2279
QF3
Clackmannan
2358
QR20
Dunfermline
2437
RA0
rural
2280
QF7
Tillicoultry
2359
QR26
Glenrothes
2438
RA1
Kirkwall
2281
QF8
Tullibody
2360
QR30
Inverkeithing
2439
RB0
rural
2282
QG0
rural
2361
QR31
Kelty
2440
RB14
Crieff
2283
QG1
Alexandria
2362
QR32
Kennoway
2441
RB21
Kinross
2284
QG2
Bonhill
2363
QR33
Kincardine
2442
RB27
New Scone
2285
QG3
Clydebank
2364
QR37
Kirkcaldy
2443
RB28
Perth
2286
QG4
Dumbarton
2365
QR4
Ballingry
2444
RB5
Auchterarder
2287
QG5
Duntocher and Hardga
2366
QR41
Leven
2445
RB8
Blairgowrie
2288
QG6
Faifley
2367
QR43
Lochgelly
2446
RC0
rural
2289
QG8
Old Kilpatrick
2368
QR47
Newport-on-Tay
2447
RC1
Bishopton
2290
QH0
rural
2369
QR49
Oakley
2448
RC10
Kilbarchan
2291
QH1
Annan
2370
QR51
Rosyth
2449
RC12
Linwood
2292
QH14
Kirkcudbright
2371
QR54
St Andrews
2450
RC14
Paisley
2293
QH16
Locharbriggs
2372
QR58
Tayport
2451
RC15
Renfrew
2294
QH18
Lockerbie
2373
QR7
Buckhaven
2452
RC2
Bridge of Weir
2295
QH20
Newton Stewart
2374
QR8
Burntisland
2453
RC3
Elderslie
2296
QH24
Stranraer
2375
QS0
rural
2454
RC4
Erskine
2297
QH3
Castle Douglas
2376
QS2
Glasgow
2455
RC6
Houston
2298
QH5
Dalbeattie
2377
QT0
rural
2456
RC9
Johnstone
2299
QH6
Dumfries
2378
QT1
Alness
2457
RD0
rural
2300
QJ0
rural
2379
QT14
Culloden
2458
RD2
Lerwick
2301
QJ1
Dundee(main)
2380
QT15
Dingwall
2459
RE0
rural
2302
QK0
rural
2381
QT20
Fort William
2460
RE11
Prestwick
2303
QK1
Auchinleck
2382
QT25
Invergordon
2461
RE14
Troon
2304
QK12
Galston
2383
QT26
Inverness
2462
RE2
Ayr
2305
QK13
Hurlford and Crooked
2384
QT33
Nairn
2463
RE6
Girvan
2306
QK14
Kilmarnock
2385
QT41
Tain
2464
RE8
Maybole
2307
QK17
Mauchline
2386
QT42
Thurso
2465
RF0
rural
2308
QK19
New Cumnock
2387
QT44
Westhill (Highland)
2466
RF00
rural
2309
QK20
Newmilns
2388
QT45
Wick
2467
RF13
East Kilbride
2310
QK23
Stewarton
2389
QU0
rural
2468
RF15
Glasgow
2311
QK5
Cumnock
2390
QU1
Gourock
2469
RF17
Hamilton
2312
QK8
Darvel
2391
QU2
Greenock
2470
RF19
Kirkmuirhill and Bla
2313
QK9
Drongan
2392
QU4
Kilmacolm
2471
RF20
Lanark
2314
QL0
rural
2393
QU5
Port Glasgow
2472
RF21
Larkhall
2315
QL1
Bearsden
2394
QW0
rural
2473
RF23
Lesmahagow
2316
QL2
Bishopbriggs
2395
QW2
Bonnyrigg
2474
RF27
Stonehouse
2317
QL4
Kirkintilloch
2396
QW3
Dalkeith
2475
RF28
Strathaven
2318
QL5
Lennoxtown
2397
QW5
Gorebridge
2476
RF29
Uddingston
2319
QL6
Lenzie
2398
QW6
Loanhead
2477
RF3
Blantyre
2320
QL7
Milngavie
2399
QW7
Mayfield
2478
RF4
Bothwell
2321
QL8
Milton of Campsie
2400
QW9
Penicuik
2479
RF5
Carluke
2322
QM0
rural
2401
QX0
rural
2480
RG0
rural
2323
QM11
Musselburgh
2402
QX10
Forres
2481
RG10
Dunblane
2324
QM12
North Berwick
2403
QX12
Keith
2482
RG17
Stirling
2325
QM15
Prestonpans
2404
QX15
Lossiemouth
2483
RG3
Bannockburn
2326
QM16
Tranent
2405
QX2
Buckie
2484
RG4
Bridge of Allan
2327
QM2
Cockenzie
2406
QX6
Elgin
2485
RH0
rural
2328
QM3
Dunbar
2407
QY0
rural
2486
RH11
Fauldhouse
2329
QM8
Haddington
2408
QY00
rural
2487
RH14
Linlithgow
2330
QN0
rural
2409
QY1
Ardrossan
2488
RH15
Livingston
2331
QN1
Barrhead
2410
QY10
Kilwinning
2489
RH2
Armadale
2332
QN3
Clarkston
2411
QY12
Largs
2490
RH23
Whitburn
2333
QN4
Eaglesham
2412
QY14
Saltcoats
2491
RH3
Bathgate
2334
QN5
Giffnock
2413
QY17
Stevenston
2492
RH4
Blackburn (West Lothian)
2335
QN6
Neilston
2414
QY18
West Kilbride
2493
RH7
Broxburn
2336
QN7
Newton Mearns
2415
QY2
Beith
2494
RH9
East Calder
2337
QP0
rural
2416
QY4
Dalry
2495
RJ0
rural
2338
QP1
Edinburgh
2417
QY5
Dreghorn
2496
RJ7
Stornoway
2339
QP2
Kirkliston
2418
QY8
Irvine
South West
2340
QP3
Queensferry
2419
QY9
Kilbirnie
483
00HA0
rural
2341
QP4
Currie
2420
QZ0
rural
484
00HA1
Bristol(part of)
2342
QQ0
rural
2421
QZ1
Airdrie
485
00HA2
Bath
2343
QQ10
Falkirk
2422
QZ10
Chapelhall
486
00HA3
Norton-Radstock

NTEM 62 Guidance
11642097

ZoneID
Zonecode
ZoneName
ZoneID
Zonecode
ZoneName
ZoneID
Zonecode
ZoneName
487
00HA4
Keynsham
1054
18UB6
Budleigh Salterton
1277
23UC3
Moreton-in-Marsh
488
00HA5
Peasedown St John
1055
18UB7
Lyme Regis(part of)
1278
23UC4
Bourton-on-the-Water
489
00HA6
Paulton
1056
18UB8
Ottery St.Mary
1279
23UD0
rural
490
00HA7
Saltford
1057
18UC0
rural
1280
23UD1
Tutshill/Sedbury
491
00HB1
Bristol(main)
1058
18UC1
Exeter
1281
23UD2
Coleford
492
00HB2
Avonmouth
1059
18UC2
Topsham
1282
23UD3
Cinderford
493
00HC0
rural
1060
18UD0
rural
1283
23UD4
Lydney
494
00HC1
Easton-in-Gordano
1061
18UD1
Tiverton
1284
23UD5
Newent
495
00HC10
Winscombe
1062
18UD2
Crediton
1285
23UE0
rural
496
00HC11
Long Ashton
1063
18UD3
Cullompton
1286
23UE1
Gloucester(main)
497
00HC12
Congresbury
1064
18UE0
rural
1287
23UF0
rural
498
00HC2
Weston-super-Mare
1065
18UE1
Barnstaple
1288
23UF1
Gloucester(part of)
499
00HC5
Clevedon
1066
18UE2
Ilfracombe
1289
23UF2
Stroud
500
00HC6
Nailsea
1067
18UE3
Braunton
1290
23UF3
Stonehouse
501
00HC7
Backwell
1068
18UE4
South Molton
1291
23UF6
Nailsworth
502
00HC8
Portishead
1069
18UE5
Fremington
1292
23UF7
Dursley
503
00HC9
Yatton
1070
18UG0
rural
1293
23UF8
Chalford
504
00HD0
rural
1071
18UG00
rural
1294
23UF9
Wotton-under-Edge
505
00HD00
rural
1072
18UG1
Plymouth(part of)
1295
23UG0
rural
506
00HD1
Kingswood
1073
18UG2
Ivybridge
1296
23UG1
Innsworth/Churchdown
507
00HD2
Bristol(part of)
1074
18UG3
Totnes
1297
23UG2
Gloucester(part of)
508
00HD3
Mangotsfield
1075
18UG4
Kingsbridge
1298
23UG3
Cheltenham(part of)
509
00HD4
Frampton
Cotterell/Winterbourne
1076
18UG5
Dartmouth
1299
23UG4
Tewkesbury
510
00HD5
Stoke Gifford
1077
18UH0
rural
1300
23UG5
Ashchurch
511
00HD7
Chipping Sodbury
1078
18UH1
Newton Abbot
1301
23UG6
Bishop's Cleeve
512
00HD9
Thornbury
1079
18UH10
Ashburton
1302
23UG7
Winchcombe
513
00HG1
Plymouth(main)
1080
18UH11
Exminster
1931
40UB0
rural
514
00HH0
rural
1081
18UH2
Teignmouth
1932
40UB00
rural
515
00HH1
Torquay
1082
18UH3
Dawlish
1933
40UB1
Frome
516
00HH2
Paignton
1083
18UH5
Kingsteignton
1934
40UB2
Street
517
00HH3
Brixham
1084
18UH6
Kingskerswell
1935
40UB3
Wells
518
00HN0
rural
1085
18UH7
Bovey Tracey
1936
40UB4
Shepton Mallet
519
00HN1
Bournemouth(main)
1086
18UH8
Buckfastleigh
1937
40UB5
Glastonbury
520
00HP0
rural
1087
18UH9
Chudleigh
1938
40UC0
rural
521
00HP1
Poole(main)
1088
18UK0
rural
1939
40UC00
rural
522
00HP2
Bournemouth(part of)
1089
18UK00
rural
1940
40UC1
Bridgwater
523
00HP3
Oakley
1090
18UK1
Bideford
1941
40UC2
Burnham-on-Sea/Highbridge
524
00HX0
rural
1091
18UK2
Northam
1942
40UC3
Cheddar
525
00HX1
Swindon(main)
1092
18UK3
Great Torrington
1943
40UC4
North Petherton
526
00HX2
Highworth
1093
18UL0
rural
1944
40UD0
rural
527
00HX3
Wroughton
1094
18UL00
rural
1945
40UD1
Yeovil
926
15UB0
rural
1095
18UL1
Tavistock
1946
40UD2
Chard
927
15UB1
Saltash
1096
18UL2
Okehampton
1947
40UD3
Crewkerne
928
15UB2
Torpoint
1097
18UL3
Horrabridge/Yelverton
1948
40UD4
Wincanton
929
15UB3
Liskeard
1098
19UC0
rural
1949
40UD5
Ilminster
930
15UB4
Looe
1099
19UC1
Christchurch
1950
40UD6
Martock
931
15UB5
Callington
1100
19UC2
Burton
1951
40UD7
Somerton
932
15UC0
rural
1101
19UD0
rural
1952
40UD8
Castle Cary
933
15UC1
Falmouth(main)
1102
19UD1
Poole(part of)
1953
40UE0
rural
934
15UC2
Penryn(main)
1103
19UD2
Ferndown
1954
40UE1
Taunton
935
15UC3
Truro
1104
19UD4
Wimborne Minster
1955
40UE2
Wellington nr Taunton
936
15UC4
Perranporth
1105
19UD5
Verwood
1956
40UF0
rural
937
15UD0
rural
1106
19UD6
St Leonards
1957
40UF1
Minehead
938
15UD1
Camborne/Redruth
1107
19UE0
rural
1958
40UF2
Watchet
939
15UD2
Penryn(part of)
1108
19UE1
Blandford Forum
2182
46UB0
rural
940
15UD3
Falmouth(part of)
1109
19UE2
Gillingham nr Shaftsbury
2183
46UB1
Devizes
941
15UD4
Helston
1110
19UE3
Shaftesbury
2184
46UB2
Marlborough
942
15UD5
Porthleven
1111
19UG0
rural
2185
46UB3
Tidworth
943
15UE0
rural
1112
19UG1
Poole(part of)
2186
46UB4
Ludgershall
944
15UE1
Bodmin
1113
19UG2
Swanage
2187
46UB5
Pewsey
945
15UE2
Launceston
1114
19UG4
Wareham
2188
46UC0
rural
946
15UE3
Wadebridge
1115
19UG6
Lytchett Matravers
2189
46UC1
Swindon(part of)
947
15UE4
Bude/Stratton
1116
19UH0
rural
2190
46UC2
Chippenham
948
15UF0
rural
1117
19UH00
rural
2191
46UC3
Calne
949
15UF1
Penzance
1118
19UH2
Weymouth(part of)
2192
46UC4
Corsham
950
15UF2
St Ives (Cornwall)
1119
19UH3
Dorchester
2193
46UC5
Wootton Bassett
951
15UF3
Hayle
1120
19UH4
Bridport
2194
46UC6
Lyneham
952
15UG0
rural
1121
19UH5
Sherborne
2195
46UC7
Malmesbury
953
15UG1
St Austell
1122
19UH6
Lyme Regis(main)
2196
46UC8
Cricklade
954
15UG2
Newquay
1123
19UJ0
rural
2197
46UC9
Purton
955
15UG3
St Blazey/Par
1124
19UJ1
Weymouth(main)
2198
46UD0
rural
956
15UG4
St Columb Major
1125
19UJ2
Overcombe/Preston
2199
46UD1
Salisbury
957
15UH0
rural
1126
19UJ3
Easton/Weston
2200
46UD2
Durrington/Bulford
1048
18UB0
rural
1127
19UJ4
Fortuneswell
2201
46UD3
Amesbury
1049
18UB1
Exmouth
1272
23UB1
Cheltenham(main)
2202
46UD4
Wilton
1050
18UB2
Sidmouth
1273
23UB2
Charlton Kings
2203
46UF0
rural
1051
18UB3
Honiton
1274
23UC0
rural
2204
46UF1
Trowbridge
1052
18UB4
Seaton (Devon)
1275
23UC1
Cirencester
2205
46UF2
Melksham
1053
18UB5
Axminster
1276
23UC2
Tetbury
2206
46UF3
Bower Hill

11642097
NTEM 62 Guidance

ZoneID
Zonecode
ZoneName
ZoneID
Zonecode
ZoneName
ZoneID
Zonecode
ZoneName
2207
46UF5
Warminster
678
00NU1
Llanelli
757
00PL0
rural
2208
46UF6
Westbury
679
00NU2
Carmarthen
758
00PL1
Abercarn/Newbridge(part of)
2209
46UF7
Bradford-on-Avon
680
00NU3
Ammanford
759
00PL2
Ebbw Vale
Wales

681
00NU4
Pontardulais(part of)
760
00PL3
Brynmawr
603
00NA0
rural
682
00NU5
Burry Port
761
00PL4
Tredegar
604
00NA1
Holyhead
683
00NU6
Brynamman/Gwaun-Cae-
Gurwen(part of)
762
00PL5
Abertillery
605
00NA2
Menai Bridge/Llandegfan
684
00NU7
Cross Hands
763
00PL6
Llanhilleth
606
00NA3
Llangefni
685
00NU8
Glanaman
764
00PM0
rural
607
00NA4
Llanfairpwllgwyngyll
686
00NU9
Tumble
765
00PM1
Cwmbran
608
00NC0
rural
687
00NX0
rural
766
00PM2
Pontypool
609
00NC00
rural
688
00NX1
Swansea(main)
767
00PM3
Caerleon(part of)
610
00NC1
Bangor
689
00NX2
Pontardawe/Clydach(part of)
768
00PM4
Blaenavon
611
00NC2
Caernarfon/Caeathro
690
00NX3
Gorseinon
769
00PP0
rural
612
00NC3
Bethesda/Rachub
691
00NX4
Pontardulais(main)
770
00PP1
Chepstow
613
00NC4
Blaenau Ffestiniog
692
00NX5
Bishopston
771
00PP2
Abergavenny
614
00NC5
Pwllheli
693
00NZ0
rural
772
00PP3
Caldicot
615
00NC6
Tywyn
694
00NZ00
rural
773
00PP4
Monmouth
616
00NC7
Porthmadog
695
00NZ1
Neath
774
00PP5
Magor
617
00NE0
rural
696
00NZ2
Port Talbot
775
00PR0
rural
618
00NE00
rural
697
00NZ3
Pontardawe/Clydach(main)
776
00PR1
Newport (Gwent)
619
00NE1
Abergele
698
00NZ4
Swansea(part of)
777
00PR4
Caerleon(main)
620
00NE2
Colwyn Bay
699
00NZ5
Ystradgynlais/Ystalyfera(part
of)
778
00PT0
rural
621
00NE3
Llandudno
700
00NZ6
Brynamman/Gwaun-Cae-
Gurwen(main)
779
00PT1
Cardiff(main)
622
00NE4
Deganwy/Llandudno Junction
701
00NZ7
Cwmavon/Pontrhydyfen
780
00PT2
Radyr
623
00NE5
Penrhyn Bay
702
00NZ8
Glyn-Neath
781
00PT3
Taff's Well(part of)
624
00NE6
Conwy
703
00PB0
rural
West Midlands

625
00NE7
Llanfairfechan
704
00PB1
Bridgend
269
00CN0
rural
626
00NE8
Llanrwst
705
00PB2
Maesteg
270
00CN1
Birmingham(main)
627
00NG0
rural
706
00PB3
Porthcawl
271
00CN2
Sutton Coldfield(main)
628
00NG1
Rhyl
707
00PB4
Pyle
272
00CQ0
rural
629
00NG3
Prestatyn
708
00PB5
Aberkenfig/Bryncoch
273
00CQ1
Coventry(main)
630
00NG4
Denbigh
709
00PB6
Pencoed
274
00CR1
Dudley (West Midlands)
631
00NG5
Ruthin
710
00PB7
Pontycymer
275
00CR2
Halesowen
632
00NG6
Rhuddlan
711
00PD0
rural
276
00CR3
Stourbridge(main)
633
00NG7
Saint Asaph
712
00PD1
Penarth
277
00CS1
Oldbury/Smethwick
634
00NJ0
rural
713
00PD2
Dinas Powys
278
00CS2
West Bromwich
635
00NJ1
Broughton
714
00PD3
Cardiff(part of)
279
00CS3
Yew Tree
636
00NJ12
Mold
715
00PD4
Barry
280
00CT0
rural
637
00NJ13
Hope/Caergwrie(main)
716
00PD5
Llantwit Major
281
00CT1
Solihull
638
00NJ14
Penyffordd
717
00PD6
Rhoose
282
00CT2
Birmingham(part of)
639
00NJ2
Saltney(main)
718
00PD7
Cowbridge
283
00CT3
Knowle
640
00NJ3
Shotton/Hawarden
719
00PF0
rural
284
00CT4
Shelly Green
641
00NJ4
Connah's Quay
720
00PF1
Rhondda
285
00CT6
Balsall
642
00NJ5
Buckley
721
00PF10
Tonyrefail
286
00CU0
rural
643
00NJ6
Flint
722
00PF11
Beddau
287
00CU1
Walsall(main)
644
00NJ8
Holywell
723
00PF12
Ferndale
288
00CU2
Brownhills
645
00NL0
rural
724
00PF13
Llanharan
289
00CU3
Aldridge
646
00NL1
Wrexham
725
00PF14
Penrhys
290
00CU4
Sutton Coldfield(part of)
647
00NL10
Hope/Caergwrie(part of)
726
00PF15
Glyncoch
291
00CU5
Pelsall
648
00NL11
Chirk
727
00PF16
Ynysybwl
292
00CU6
Birmingham(part of)
649
00NL3
Wrexham(part of)
728
00PF17
Taff's Well(main)
293
00CU7
Shelfield
650
00NL4
Rhosllanerchrugog
729
00PF2
Pontypridd
294
00CU8
Rushall
651
00NL5
Cefn-mawr
730
00PF3
Church Village
295
00CW1
Wolverhampton(main)
652
00NL6
Ruabon
731
00PF4
Llantwit Ferdre
466
00GA0
rural
653
00NL7
Coedpoeth
732
00PF6
Aberdare
467
00GA1
Hereford
654
00NL8
Gresford
733
00PF7
Cwmbach
468
00GA2
Great Malvern(part of)
655
00NL9
Llay
734
00PF8
Mountain Ash/Abercynon
469
00GA3
Leominster
656
00NN0
rural
735
00PF9
Llantrisant/Pontyclun
470
00GA4
Ross-on-Wye
657
00NN0a
rural
736
00PH0
rural
471
00GA5
Ledbury
658
00NN0b
rural
737
00PH1
Merthyr Tydfil
472
00GA6
Bromyard
659
00NN0c
rural
738
00PH2
Abercanaid/Troedyrhiw
473
00GF0
rural
660
00NN1
Newtown
739
00PH3
Treharris/Nelson(main)
474
00GF1
Telford
661
00NN2
Ystradgynlais/Ystalyfera(main)
740
00PH4
Merthyr Vale
475
00GF10
Newport nr Telford
662
00NN3
Brecon
741
00PH5
Cyfarthfac
476
00GF2
Oakengates/Donnington
663
00NN4
Welshpool
742
00PK0
rural
477
00GF4
Ironbridge & Madeley
664
00NN5
Llandrindod Wells
743
00PK00
rural
478
00GF5
Hadley
665
00NQ0
rural
744
00PK1
Risca
479
00GF8
Wellington (Telford)
666
00NQ1
Aberystwyth
745
00PK10
Rhymney
480
00GL0
rural
667
00NQ2
Cardigan
746
00PK11
Abertridwr/Senghenydd
481
00GL1
Stoke-on-Trent(main)
668
00NS0
rural
747
00PK12
New Tredegar
482
00GL2
Kidsgrove(part of)
669
00NS1
Haverfordwest
748
00PK13
Llanbradach
1910
39UB0
rural
670
00NS2
Milford Haven
749
00PK2
Gelligaer
1911
39UB1
Broseley
671
00NS3
Pembroke Dock
750
00PK3
Blackwood
1912
39UB2
Bridgnorth
672
00NS4
Pembroke
751
00PK4
Bargoed
1913
39UB3
Albrighton
673
00NS5
Tenby
752
00PK5
Oakdale/Pontllanfraith
1914
39UB4
Shifnal
674
00NS6
Neyland
753
00PK6
Abercarn/Newbridge(main)
1915
39UB5
Highley
675
00NS7
Fishguard
754
00PK7
Caerphilly
1916
39UC0
rural
676
00NU0
rural
755
00PK8
Bedwas
1917
39UC1
Market Drayton
677
00NU00
rural
756
00PK9
Treharris/Nelson(part of)
1918
39UC2
Whitchurch

NTEM 62 Guidance
11642097

ZoneID
Zonecode
ZoneName
ZoneID
Zonecode
ZoneName
ZoneID
Zonecode
ZoneName
1919
39UC3
Wem
2128
44UE1
Redditch(part of)
43
00BA1
Merton
1920
39UC4
Ellesmere
2129
44UE2
Stratford-upon-Avon
44
00BB1
Newham
1921
39UD0
rural
2130
44UE3
Alcester
45
00BC1
Redbridge(main)
1922
39UD1
Oswestry
2131
44UE4
Southam
46
00BD1
Richmond upon Thames
1923
39UD2
Gobowen
2132
44UE5
Studley
47
00BE1
Southwark(main)
1924
39UE0
rural
2133
44UE6
Wellesbourne
48
00BE2
Southwark(part of)
1925
39UE1
Shrewsbury
2134
44UE7
Shipston on Stour
49
00BF0
rural
1926
39UE2
Bayston Hill
2135
44UE8
Bidford-on-Avon
50
00BF1
Sutton(main)
1927
39UF0
rural
2136
44UF0
rural
51
00BF2
Croydon(part of)
1928
39UF1
Ludlow
2137
44UF1
Coventry(part of)
52
00BF3
Banstead/Tadworth(part of)
1929
39UF2
Church Stretton
2138
44UF2
Leamington Spa
53
00BG1
Tower Hamlets
1930
39UF3
Tenbury Wells(part of)
2139
44UF3
Warwick
54
00BH1
Waltham Forest
1959
41UB0
rural
2140
44UF4
Kenilworth
55
00BJ1
Wandsworth
1960
41UB1
Cannock(main)
2210
47UB0
rural
56
00BK1
Westminster(part of)
1961
41UB2
Rugeley
2211
47UB1
Birmingham(part of)
57
00BK2
Westminster(main)
1962
41UB3
Norton Canes
2212
47UB2
Hagley
528
00JA0
rural
1963
41UC0
rural
2213
47UB3
Bromsgrove
529
00JA1
Peterborough(main)
1964
41UC00
rural
2214
47UB4
Catshill
530
00JA2
Market Deeping(part of)
1965
41UC1
Burton Upon Trent
2215
47UB5
Barnt Green
531
00KA1
Luton(main)
1966
41UC2
Stapenhill/Winshill(main)
2216
47UB6
Alvechurch
532
00KF1
Southend-on-Sea
1967
41UC3
Uttoxeter
2217
47UC0
rural
533
00KG0
rural
1968
41UC4
Tutbury/Hatton(main)
2218
47UC1
Worcester(part of)
534
00KG1
Grays
1969
41UC5
Barton-under-Needwood
2219
47UC2
Great Malvern(main)
535
00KG2
Tilbury
1970
41UD0
rural
2220
47UC3
Tenbury Wells(main)
536
00KG3
Stanford Le Hope/ Corringham
1971
41UD1
Sutton Coldfield(part of)
2221
47UD0
rural
537
00KG4
South Ockendon
1972
41UD3
Fazeley(main)
2222
47UD1
Redditch(main)
538
00KG5
Aveley
1973
41UD4
Burntwood
2223
47UE1
Worcester(main)
539
00KG6
Linford
1974
41UD5
Lichfield
2224
47UF0
rural
540
00LC0
rural
1975
41UD6
Armitage
2225
47UF3
Summerfield nr Kidderminster
541
00LC1
Gillingham(main)
1976
41UE0
rural
2226
47UF4
Droitwich
542
00LC2
Chatham(main)
1977
41UE1
Newcastle-under-Lyme(main)
2227
47UF6
Evesham
543
00LC3
Strood(main)
1978
41UE2
Kidsgrove(main)
2228
47UF7
Pershore
544
00LC4
Rochester
1979
41UE3
Stoke-on-Trent(part of)
2229
47UG0
rural
545
00LC5
Hoo
1980
41UE4
Audley
2230
47UG1
Kidderminster
546
00MA0
rural
1981
41UE5
Madeley/Middle Madeley
2231
47UG2
Stourport-on-Severn
547
00MA1
Sunningdale/Ascot(part of)
1982
41UF0
rural
2232
47UG3
Bewdley
548
00MA2
Bracknell
1983
41UF00
rural
Wider South East
549
00MA3
Crowthorne(part of)
1984
41UF1
Wolverhampton(part of)
1
00AA1
City of London
550
00MA4
Sandhurst
1985
41UF10
Kinver
2
00AB1
Barking and Dagenham
551
00MB0
rural
1986
41UF11
Featherstone nr
Wolverhampton
3
00AC0
rural
552
00MB1
Reading(part of)
1987
41UF2
Walsall(part of)
4
00AC1
Barnet
553
00MB2
Newbury
1988
41UF3
Stourbridge(part of)
5
00AC2
Borehamwood(part of)
554
00MB3
Thatcham
1989
41UF4
Great Wyrley
6
00AD0
rural
555
00MB5
Burghfield Common
1990
41UF5
Cannock(part of)
7
00AD1
Bexley
556
00MB6
Hungerford
1991
41UF6
Stafford(part of)
8
00AD3
Dartford(part of)
557
00MB7
Goring/Streatley(part of)
1992
41UF7
Wombourne
9
00AE1
Brent
558
00MB8
Pangbourne/Whitchurch(main)
1993
41UF8
Codsall
10
00AF0
rural
559
00MB9
Mortimer
1994
41UF9
Penkridge
11
00AF1
Bromley
560
00MC0
rural
1995
41UG0
rural
12
00AF3
Biggin Hill(main)
561
00MC1
Reading(main)
1996
41UG1
Stoke-on-Trent(part of)
13
00AG1
Camden(main)
562
00MD0
rural
1997
41UG2
Newcastle-under-Lyme(part
of)
14
00AG2
Camden(part of)
563
00MD1
Slough(main)
1998
41UG3
Stafford(main)
15
00AH1
Croydon(main)
564
00MD2
Colnbrook
1999
41UG4
Stone (Staffordshire)
16
00AH2
New Addington
565
00ME0
rural
2000
41UG5
Gnosall
17
00AJ1
Ealing
566
00ME1
Sunningdale/Ascot(main)
2001
41UH0
rural
18
00AK0
rural
567
00ME2
Virginia Water(part of)
2002
41UH1
Stoke-on-Trent(part of)
19
00AK1
Enfield
568
00ME3
Cookham
2003
41UH2
Leek
20
00AL1
Greenwich
569
00ME4
Maidenhead(main)
2004
41UH3
Biddulph
21
00AM1
Hackney
570
00ME5
Windsor/Eton
2005
41UH4
Cheadle
22
00AN1
Hammersmith and Fulham
571
00ME6
Old Windsor
2006
41UK1
Tamworth
23
00AP1
Haringey
572
00ME8
Datchet
2007
41UK2
Fazeley(part of)
24
00AQ0
rural
573
00MF0
rural
2110
44UB0
rural
25
00AQ1
Harrow
574
00MF1
Reading(part of)
2111
44UB1
Coleshill
26
00AR0
rural
575
00MF2
Wokingham
2112
44UB2
Water Orton
27
00AR1
Havering(main)
576
00MF3
Crowthorne(main)
2113
44UB3
Hartshill(part of)
28
00AS0
rural
577
00MF5
Twyford
2114
44UB4
Atherstone(main)
29
00AS1
Hillingdon(main)
578
00MF6
Spencers Wood
2115
44UB5
Dordon/Polesworth
30
00AS2
Harefield
579
00MG0
rural
2116
44UB6
Kingsbury
31
00AS3
Hillingdon(main)
580
00MG1
Milton Keynes
2117
44UB7
Baddesley Ensor
32
00AT1
Hounslow
581
00MG10
Woburn Sands(main)
2118
44UC0
rural
33
00AT2
Hounslow
582
00MG2
Bletchley
2119
44UC1
Bedworth
34
00AU1
Islington(main)
583
00MG3
Wolverton/Stony Stratford
2120
44UC2
Exhall
35
00AU2
Islington(part of)
584
00MG4
Newport Pagnell
2121
44UC3
Nuneaton
36
00AW1
Kensington and
Chelsea(main)
585
00MG9
Olney
2122
44UC4
Hartshill(main)
37
00AW2
Kensington and Chelsea(part
of)
586
00ML0
rural
2123
44UC5
Bulkington
38
00AX0
rural
587
00ML1
Brighton
2124
44UD0
rural
39
00AX1
Kingston upon Thames
588
00ML2
Hove
2125
44UD1
Coventry(part of)
40
00AY1
Lambeth(main)
589
00ML3
Portslade
2126
44UD2
Rugby
41
00AY2
Lambeth(part of)
590
00ML4
Rottingdean/Saltdean(main)
2127
44UE0
rural
42
00AZ1
Lewisham
591
00MR1
Portsmouth(main)

11642097
NTEM 62 Guidance

ZoneID
Zonecode
ZoneName
ZoneID
Zonecode
ZoneName
ZoneID
Zonecode
ZoneName
592
00MR2
Waterlooville(part of)
850
12UC6
Sutton (East Cambridge)
1223
22UF1
Chelmsford
593
00MS1
Southampton(main)
851
12UD0
rural
1224
22UF2
Wickford(part of)
594
00MW0
rural
852
12UD1
Wisbech(main)
1225
22UF3
South Woodham Ferrers
595
00MW1
Newport (Isle of Wight)
853
12UD2
March
1226
22UF4
Danbury/Little Baddow
596
00MW2
Ryde
854
12UD3
Whittlesey
1227
22UF5
Writtle
597
00MW3
Sandown/Shanklin
855
12UD4
Chatteris
1228
22UF6
Boreham
598
00MW4
Cowes/Northwood
856
12UD5
Doddington/Wimblington
1229
22UG0
rural
599
00MW5
Freshwater/Totland
857
12UE0
rural
1230
22UG1
Colchester
600
00MW6
Ventnor
858
12UE1
Peterborough(part of)
1231
22UG2
Wivenhoe
601
00MW7
Wootton (IOW)
859
12UE10
Sawtry
1232
22UG4
Tiptree
602
00MW8
Bembridge
860
12UE11
Brampton (Huntingdon)
1233
22UG5
West Mersea
782
09UC0
rural
861
12UE12
Warboys
1234
22UG6
Marks Tey
783
09UC1
Flitwick
862
12UE13
Somersham
1235
22UG7
West Bergholt
784
09UC10
Potton
863
12UE14
Little Paxton
1236
22UH0
rural
785
09UC11
Marston Moretaine
864
12UE3
St Neots
1237
22UH1
Loughton
786
09UC2
Ampthill
865
12UE4
Huntingdon
1238
22UH10
North Weald Bassett
787
09UC3
Biggleswade
866
12UE5
St Ives (Huntingdon)
1239
22UH11
Theydon Bois
788
09UC4
Henlow/Shefford
867
12UE6
Hemingford Grey
1240
22UH2
Waltham Abbey
789
09UC5
Sandy
868
12UE7
Ramsey
1241
22UH3
Chigwell
790
09UC6
Stotfold
869
12UE8
Yaxley
1242
22UH4
Hoddesdon(part of)
791
09UC7
Woburn Sands(part of)
870
12UE9
Godmanchester
1243
22UH5
Redbridge(part of)
792
09UC8
Cranfield
871
12UG0
rural
1244
22UH7
Sawbridgeworth(part of)
793
09UC9
Arlesey
872
12UG1
Cambridge(part of)
1245
22UH8
Epping
794
09UD0
rural
873
12UG10
Bar Hill
1246
22UH9
Chipping Ongar
795
09UD1
Bedford
874
12UG11
Waterbeach
1247
22UJ1
Harlow
796
09UD2
Kempston
875
12UG12
Willingham
1248
22UK0
rural
797
09UD3
Rushden(part of)
876
12UG2
Great Shelford
1249
22UK1
Maldon
798
09UD4
Bromham/Bridge End
877
12UG3
Girton
1250
22UK2
Burnham-on-Crouch
799
09UD5
Wootton nr Bedford
878
12UG4
Fulbourn
1251
22UK3
Southminster
800
09UD6
Clapham (Bedford)
879
12UG5
Histon
1252
22UK4
Maylandsea
801
09UE0
rural
880
12UG6
Sawston
1253
22UK5
Wickham Bishops/Great Totham
802
09UE1
Dunstable
881
12UG7
Cottenham
1254
22UL0
rural
803
09UE2
Luton(part of)
882
12UG8
Melbourn
1255
22UL1
Rayleigh
804
09UE3
Leighton Buzzard
883
12UG9
Linton
1256
22UL2
Rochford
805
09UE4
Barton in the Clay
1178
21UC1
Eastbourne(main)
1257
22UL3
Hockley
806
09UE5
Toddington
1179
21UD1
Hastings(main)
1258
22UL4
Hullbridge
807
09UE6
Eaton Bray(main)
1180
21UF0
rural
1259
22UL5
Great and Little Wakering
808
09UE7
Caddington
1181
21UF1
Rottingdean/Saltdean(part of)
1260
22UN1
Clacton-on-Sea
809
11UB0
rural
1182
21UF2
Burgess Hill(part of)
1261
22UN2
rural
810
11UB00
rural
1183
21UF3
Seaford
1262
22UN3
Harwich
811
11UB1
Aylesbury
1184
21UF4
Peacehaven
1263
22UN4
Frinton and Walton
812
11UB2
Buckingham
1185
21UF5
Lewes
1264
22UN5
Brightlingsea
813
11UB3
Wendover
1186
21UF6
Newhaven
1265
22UN6
Manningtree
814
11UB4
Haddenham nr Thame
1187
21UG0
rural
1266
22UN7
Jaywick
815
11UB5
Winslow
1188
21UG1
Bexhill
1267
22UQ0
rural
816
11UB6
Eaton Bray(part of)
1189
21UG3
Hastings(part of)
1268
22UQ00
rural
817
11UB7
Aston Clinton
1190
21UG4
Battle
1269
22UQ1
Saffron Walden
818
11UC0
rural
1191
21UG5
Rye
1270
22UQ2
Great Dunmow
819
11UC1
Hazlemere/Tylers Green(part
of)
1192
21UH0
rural
1271
22UQ3
Stansted Mountfitchet
820
11UC3
Amersham
1193
21UH1
Eastbourne(part of)
1303
24UB0
rural
821
11UC4
Chesham
1194
21UH2
Crowborough
1304
24UB1
Basingstoke
822
11UC5
Chalfont
St.Peter/Gerrards(main)
1195
21UH3
Hailsham
1305
24UB2
Basing
823
11UC6
Beaconsfield(part of)
1196
21UH4
Uckfield
1306
24UB3
Tadley
824
11UC7
Great Missenden/Prestwood
1197
21UH5
Heathfield
1307
24UB4
Hook (Hampshire)(part of)
825
11UC8
Chalfont St.Giles
1198
21UH6
Wadhurst
1308
24UB5
Oakley nr Basingstoke
826
11UE0
rural
1199
21UH7
Forest Row
1309
24UB6
Whitchurch (Hampshire)
827
11UE1
Hillingdon(part of)
1200
22UB1
Basildon
1310
24UB7
Bramley
828
11UE2
Slough(part of)
1201
22UB2
rural
1311
24UB8
Overton nr Basingstoke
829
11UE3
Farnham Royal
1202
22UB3
Billericay(main)
1312
24UB9
Kingsclere
830
11UE4
Stoke Poges
1203
22UB5
Wickford(main)
1313
24UC0
rural
831
11UE5
Maidenhead(part of)
1204
22UC0
rural
1314
24UC00
rural
832
11UE6
Chalfont
St.Peter/Gerrards(part of)
1205
22UC1
Braintree
1315
24UC1
Waterlooville(part of)
833
11UE7
Beaconsfield(main)
1206
22UC2
Witham
1316
24UC10
Headley
834
11UE8
Iver/Iver Heath
1207
22UC3
Halstead nr Colne
1317
24UC11
Four Marks/Medstead
835
11UF0
rural
1208
22UC4
Kelvedon
1318
24UC2
Havant(part of)
836
11UF1
High Wycombe
1209
22UC5
Coggeshall
1319
24UC3
Farnham(part of)
837
11UF2
Hazlemere/Tylers
Green(main)
1210
22UC6
Silver End
1320
24UC4
Bordon
838
11UF3
Bourne End/Flackwell Heath
1211
22UC7
Earls Colne
1321
24UC5
Alton
839
11UF5
Marlow
1212
22UC8
Hatfield Peverel
1322
24UC6
Petersfield
840
11UF6
Princes Risborough
1213
22UC9
Sible Hedingham
1323
24UC7
Liss(main)
841
11UF7
Stokenchurch
1214
22UD0
rural
1324
24UC8
Hindhead(part of)
842
11UF8
Walter's Ash/Naphill
1215
22UD1
Brentwood
1325
24UC9
Liphook
843
12UB1
Cambridge(main)
1216
22UD2
Billericay(part of)
1326
24UD0
rural
844
12UC0
rural
1217
22UD3
Doddinghurst/Wyatts Green
1327
24UD1
Eastleigh(main)
845
12UC1
Newmarket(part of)
1218
22UD4
Ingatestone
1328
24UD2
Bishopstoke
846
12UC2
Ely
1219
22UE0
rural
1329
24UD3
Southampton(part of)
847
12UC3
Soham
1220
22UE1
Benfleet
1330
24UD4
Bursledon
848
12UC4
Littleport
1221
22UE2
Canvey Island
1331
24UD5
Hedge End
849
12UC5
Burwell
1222
22UF0
rural
1332
24UD7
Netley

NTEM 62 Guidance
11642097

ZoneID
Zonecode
ZoneName
ZoneID
Zonecode
ZoneName
ZoneID
Zonecode
ZoneName
1333
24UD8
Hamble
1412
26UF4
Baldock
1491
29UM2
Sittingbourne
1334
24UE0
rural
1413
26UF5
Hitchin
1492
29UM4
Minster
1335
24UE1
Fareham/Portchester
1414
26UF6
Royston(Herts)
1493
29UM5
Queenborough
1336
24UE2
Stubbington
1415
26UF7
Knebworth
1494
29UM6
Faversham
1337
24UE3
Locks Heath
1416
26UG0
rural
1495
29UM7
Sheerness
1338
24UF1
Gosport
1417
26UG1
Watford(part of)
1496
29UN0
rural
1339
24UF2
Lee-on-the-Solent
1418
26UG2
St Albans
1497
29UN1
Margate
1340
24UG0
rural
1419
26UG3
Hatfield(part of)
1498
29UN2
Ramsgate
1341
24UG1
Yateley
1420
26UG4
Harpenden
1499
29UN3
Broadstairs
1342
24UG2
Frogmore
1421
26UG5
Redbourn
1500
29UP0
rural
1343
24UG3
Fleet
1422
26UG6
Wheathampstead
1501
29UP1
Chatham(part of)
1344
24UG4
Hook (Hampshire)(main)
1423
26UH0
rural
1502
29UP2
Tonbridge
1345
24UG5
Hartley Wintney
1424
26UH1
Stevenage(main)
1503
29UP3
Aylesford/East Malling
1346
24UH0
rural
1425
26UJ0
rural
1504
29UP4
Snodland
1347
24UH1
Waterlooville(main)
1426
26UJ1
Watford(part of)
1505
29UP5
Borough Green
1348
24UH2
Havant(main)
1427
26UJ2
South Oxhey
1506
29UP6
Kings Hill
1349
24UH3
Portsmouth(part of)
1428
26UJ3
Rickmansworth
1507
29UQ0
rural
1350
24UH4
Emsworth
1429
26UJ4
Chorleywood
1508
29UQ1
Royal Tunbridge Wells
1351
24UH5
Hayling Island
1430
26UJ5
Hillingdon(part of)
1509
29UQ2
Paddock Wood
1352
24UJ0
rural
1431
26UJ6
Kings Langley(part of)
1510
29UQ3
Pembury
1353
24UJ1
New Milton/Barton-on-Sea
1432
26UK1
Watford(main)
1511
29UQ4
Cranbrook
1354
24UJ10
Marchwood
1433
26UL0
rural
1512
29UQ5
Hawkhurst
1355
24UJ11
Milford on Sea
1434
26UL1
Hatfield(main)
xx-xxxx-xxxx
33UB0
rural
1356
24UJ12
Bransgore
1435
26UL2
Welwyn Garden City
xx-xxxx-xxxx
33UB1
Thetford
1357
24UJ3
Totton
1436
26UL3
Welwyn/Codicote(main)
xx-xxxx-xxxx
33UB2
East Dereham
1358
24UJ4
Ashhurst/Netley Marsh
1437
26UL4
Welwyn North
xx-xxxx-xxxx
33UB3
Attleborough
1359
24UJ5
Hythe nr Southampton
1438
26UL5
Potters Bar(part of)
xx-xxxx-xxxx
33UB4
Watton
1360
24UJ6
Lymington
1439
26UL6
Cuffley
xx-xxxx-xxxx
33UB6
Swaffham
1361
24UJ7
Fawley
1440
26UL7
Brookmans Park
xx-xxxx-xxxx
33UC0
rural
1362
24UJ8
Ringwood
1441
29UB0
rural
xx-xxxx-xxxx
33UC1
Norwich(part of)
1363
24UJ9
Fordingbridge/Sandleheath
1442
29UB1
Ashford
xx-xxxx-xxxx
33UC2
Taverham
1364
24UL1
Farnborough
1443
29UB2
Tenterden
xx-xxxx-xxxx
33UC4
Brundall
1365
24UL2
Aldershot(main)
1444
29UC0
rural
xx-xxxx-xxxx
33UC5
Aylsham
1366
24UN0
rural
1445
29UC1
Herne Bay
xx-xxxx-xxxx
33UC6
Spixworth
1367
24UN00
rural
1446
29UC2
Whitstable
xx-xxxx-xxxx
33UC7
Horsford
1368
24UN1
Eastleigh(part of)
1447
29UC3
Canterbury
xx-xxxx-xxxx
33UC8
Wroxham/Hoveton(part of)
1369
24UN2
Southampton(part of)
1448
29UC5
Sturry
1700
33UD0
rural
1370
24UN3
Andover
1449
29UD0
rural
1701
33UD1
Great Yarmouth
1371
24UN4
Romsey
1450
29UD1
Dartford(main)
1702
33UD2
Caister-on-Sea
1372
24UN5
North Baddesley
1451
29UD2
Swanscombe
1703
33UD3
Hemsby
1373
24UP0
rural
1452
29UD3
Longfield/New Ash Green(part
of)
1704
33UD4
Belton nr Yarmouth
1374
24UP1
Eastleigh(part of)
1453
29UD4
Sutton-at-Hone/South
Darenth(main)
1705
33UD5
Martham
1375
24UP2
Whiteley
1454
29UE0
rural
1706
33UE0
rural
1376
24UP3
Winchester
1455
29UE1
Dover
1707
33UE1
King's Lynn/West Lynn
1377
24UP4
Bishops Waltham
1456
29UE2
Whitfield
1708
33UE10
Terrington St. Clement
1378
24UP5
Denmead
1457
29UE3
Deal
1709
33UE3
Wisbech(part of)
1379
24UP6
Alresford
1458
29UE4
Sandwich
1710
33UE4
Heacham
1380
24UP7
Kings Worthy
1459
29UE5
Aylesham
1711
33UE5
Hunstanton
1381
24UP8
Colden Common
1460
29UG0
rural
1712
33UE6
Downham Market
1382
26UB0
rural
1461
29UG1
Gravesend
1713
33UE8
Dersingham
1383
26UB1
Cheshunt
1462
29UG2
Northfleet
1714
33UE9
Outwell
1384
26UB2
Hoddesdon(main)
1463
29UG3
Strood(part of)
1715
33UF0
rural
1385
26UC0
rural
1464
29UG4
Meopham
1716
33UF1
North Walsham
1386
26UC1
Hemel Hempstead
1465
29UG5
Culverstone Green
1717
33UF2
Cromer
1387
26UC2
Kings Langley(main)
1466
29UG6
Higham/Shorne
1718
33UF3
Fakenham
1388
26UC3
Berkhamsted
1467
29UG7
Istead Rise
1719
33UF4
Sheringham
1389
26UC4
Tring
1468
29UH0
rural
1720
33UF5
Stalham
1390
26UC5
Bovingdon
1469
29UH1
Chatham(part of)
1721
33UF6
Holt
1391
26UD0
rural
1470
29UH2
Maidstone
1722
33UF7
Wroxham/Hoveton(main)
1392
26UD1
Hoddesdon(part of)
1471
29UH3
Staplehurst
1723
33UG0
rural
1393
26UD10
Standon
1472
29UH4
Coxheath
1724
33UG1
Norwich(main)
1394
26UD2
Sawbridgeworth(main)
1473
29UK0
rural
1725
33UH0
rural
1395
26UD3
Stevenage(part of)
1474
29UK1
Bromley(part of)
1726
33UH1
Norwich(part of)
1396
26UD5
Hertford
1475
29UK2
Sevenoaks
1727
33UH10
Long Stratton
1397
26UD6
Ware
1476
29UK3
Swanley/Hextable
1728
33UH11
Loddon
1398
26UD7
Bishop's Stortford
1477
29UK4
Longfield/New Ash
Green(main)
1729
33UH4
Wymondham
1399
26UD8
Buntingford
1478
29UK5
Edenbridge
1730
33UH5
Diss
1400
26UD9
St Margarets
1479
29UK6
Otford/Kemsing
1731
33UH7
Poringland
1401
26UE0
rural
1480
29UK7
Sutton-at-Hone/South
Darenth(part of
1732
33UH8
Hethersett
1402
26UE1
Bushey
1481
29UK8
West Kingsdown
1733
33UH9
Harleston
1403
26UE2
Watford(part of)
1482
29UL0
rural
1877
38UB0
rural
1404
26UE3
Borehamwood(main)
1483
29UL1
Folkestone
1878
38UB1
Banbury
1405
26UE4
Potters Bar(main)
1484
29UL2
Hythe
1879
38UB2
Bicester
1406
26UE5
Radlett
1485
29UL3
Romney
1880
38UB3
Kidlington
1407
26UE6
Shenley
1486
29UL4
Dymchurch/St Mary's Bay
1881
38UB4
Bloxham
1408
26UF0
rural
1487
29UL5
Hawkinge
1882
38UC0
rural
1409
26UF1
Stevenage(part of)
1488
29UL6
Lydd
1883
38UC1
Oxford(main)
1410
26UF2
Welwyn/Codicote(part of)
1489
29UM0
rural
1884
38UD0
rural
1411
26UF3
Letchworth
1490
29UM1
Gillingham(part of)
1885
38UD1
Oxford(part of)

11642097
NTEM 62 Guidance

ZoneID
Zonecode
ZoneName
ZoneID
Zonecode
ZoneName
ZoneID
Zonecode
ZoneName
1886
38UD10
Goring/Streatley(main)
2063
43UF00
rural
2173
45UG1
Burgess Hill(main)
1887
38UD11
Pangbourne/Whitchurch(part
of)
2064
43UF1
Banstead/Tadworth(main)
2174
45UG2
Haywards Heath
1888
38UD12
Cholsey
2065
43UF2
Croydon(part of)
2175
45UG3
East Grinstead(main)
1889
38UD2
Didcot(main)
2066
43UF3
Sutton(part of)
2176
45UG4
Hurstpierpoint/Keymer
1890
38UD3
Thame
2067
43UF4
Reigate/Redhill
2177
45UG5
Crawley Down
1891
38UD4
Henley-on-Thames
2068
43UF5
Horley
2178
45UG6
Copthorne
1892
38UD5
Wallingford
2069
43UF6
Salfords
2179
45UG7
Cuckfield
1893
38UD6
Benson
2070
43UG0
rural
2180
45UH1
Worthing
1894
38UD7
Wheatley/Horspath
2071
43UG1
Egham
2181
45UH2
Littlehampton(part of)
1895
38UD8
Chinnor
2072
43UG2
Addlestone
Yorkshire and the Humber
1896
38UD9
Sonning Common
2073
43UG3
Chertsey
182
00CC0
rural
1897
38UE0
rural
2074
43UG4
Woking/Byfleet(part of)
183
00CC1
Barnsley
1898
38UE1
Oxford(part of)
2075
43UG5
Virginia Water(main)
184
00CC10
Dearne
1899
38UE2
Abingdon
2076
43UG6
Ottershaw
185
00CC11
Thurnscoe
1900
38UE3
Didcot(part of)
2077
43UH0
rural
186
00CC12
Penistone
1901
38UE4
Wantage/Grove
2078
43UH1
Staines
187
00CC13
Brierley
1902
38UE5
Faringdon
2079
43UH2
Sunbury
188
00CC2
Hoyland Nether
1903
38UE6
Shrivenham
2080
43UH3
Shepperton
189
00CC3
Wombwell
1904
38UE7
Kennington
2081
43UH4
Feltham
190
00CC4
Darton
1905
38UF0
rural
2082
43UH5
Walton and Weybridge(part of)
191
00CC5
Cudworth
1906
38UF1
Witney
2083
43UJ0
rural
192
00CC6
Worsbrough
1907
38UF3
Carterton
2084
43UJ1
West End
193
00CC7
Royston nr Barnsley
1908
38UF4
Chipping Norton
2085
43UJ2
Windlesham
194
00CC8
Darfield
1909
38UF5
Eynsham
2086
43UJ3
Woking/Byfleet(part of)
195
00CC9
Dodworth
2008
42UB0
rural
2087
43UJ4
Sunningdale/Ascot(part of)
196
00CE0
rural
2009
42UB1
Ipswich(part of)
2088
43UJ5
Camberley/Frimley
197
00CE1
Mexborough
2010
42UB2
Sudbury
2089
43UJ6
Aldershot(part of)
198
00CE10
Conisbrough
2011
42UB3
Hadleigh
2090
43UJ7
Lightwater
199
00CE11
New Rossington
2012
42UB4
Glemsford
2091
43UJ8
Bagshot
200
00CE12
Adwick le Street
2013
42UC0
rural
2092
43UK0
rural
201
00CE13
Carcroft
2014
42UC00
rural
2093
43UK00
rural
202
00CE14
Askern
2015
42UC1
Newmarket(main)
2094
43UK1
Caterham and Warlingham
203
00CE15
Tickhill
2016
42UC3
Mildenhall
2095
43UK3
East Grinstead(part of)
204
00CE16
Finningley
2017
42UC5
Lakenheath
2096
43UK4
Biggin Hill(part of)
205
00CE17
Bawtree/Austerfield
2018
42UC6
Brandon nr Thetford
2097
43UK5
Oxted
206
00CE2
Doncaster
2019
42UD0
rural
2098
43UK6
Smallfield
207
00CE3
Bentley
2020
42UD1
Ipswich(main)
2099
43UK7
Lingfield
208
00CE4
Kirk Sandall
2021
42UE0
rural
2100
43UL0
rural
209
00CE5
Armthorpe
2022
42UE1
Ipswich(part of)
2101
43UL1
Farnham(main)
210
00CE6
Hatfield nr Doncaster
2023
42UE2
Stowmarket
2102
43UL2
Godalming(main)
211
00CE7
Stainforth
2024
42UE3
Needham Market
2103
43UL3
Haslemere(main)
212
00CE8
Bessacarr
2025
42UE4
Claydon
2104
43UL4
Cranleigh
213
00CE9
Thorne/Moorends
2026
42UE5
Elmswell
2105
43UL6
Milford/Witley
214
00CF0
rural
2027
42UF0
rural
2106
43UL7
Hindhead(main)
215
00CF1
Rotherham
2028
42UF00
rural
2107
43UL8
Bramley and Wonersh
216
00CF10
Thurcroft
2029
42UF1
Bury St Edmunds
2108
43UM0
rural
217
00CF11
Thorpe Hesley
2030
42UF3
Haverhill
2109
43UM1
Woking/Byfleet(main)
218
00CF2
Rawmarsh
2031
42UG0
rural
2141
45UB0
rural
219
00CF3
Aughton
2032
42UG1
Ipswich(part of)
2142
45UB1
Sompting/Lancing
220
00CF4
Sheffield(part of)
2033
42UG2
Martlesham Heath
2143
45UB2
Shoreham
221
00CF5
Wath upon Dearne
2034
42UG3
Felixstowe
2144
45UB3
Southwick
222
00CF6
Swinton
2035
42UG4
Woodbridge
2145
45UC0
rural
223
00CF7
Anston/Dinnington/Laughton
Common
2036
42UG5
Leiston
2146
45UC1
Littlehampton(main)
224
00CF8
Maltby
2037
42UH0
rural
2147
45UC3
Bognor Regis
225
00CF9
Wales
2038
42UH1
Lowestoft/Corton
2148
45UC4
Westergate/Barnham/Yapton
226
00CG0
rural
2039
42UH2
Beccles
2149
45UC5
Arundel
227
00CG1
Sheffield(main)
2040
42UH3
Halesworth
2150
45UD0
rural
228
00CG2
Chapeltown
2041
42UH4
Bungay
2151
45UD0a
rural
229
00CG3
Mosborough/Highlane(main)
2042
42UH5
Kessingland
2152
45UD0b
rural
230
00CG4
Beighton
2043
42UH6
Southwold
2153
45UD1
Chichester
231
00CG5
Stocksbridge
2044
43UB0
rural
2154
45UD2
Southbourne
232
00CG6
Oughtibridge & Wharncliffe Side
2045
43UB1
Walton and Weybridge(main)
2155
45UD3
Haslemere(part of)
296
00CX0
rural
2046
43UB2
Esher/Molesey
2156
45UD4
Selsey
297
00CX1
Bradford(main)
2047
43UB3
Cobham/Oxshott
2157
45UD5
Liss(part of)
298
00CX10
Steeton
2048
43UC0
rural
2158
45UD6
Midhurst
299
00CX11
Silsden
2049
43UC1
Epsom and Ewell
2159
45UD7
East Wittering
300
00CX12
Haworth
2050
43UD0
rural
2160
45UD8
Tangmere/Boxgrove
301
00CX13
Burley in Wharfedale
2051
43UD1
Leatherhead(part of)
2161
45UE1
Crawley(main)
302
00CX14
Wilsden
2052
43UD3
Woking/Byfleet(part of)
2162
45UF0
rural
303
00CX15
Addingham
2053
43UD4
Aldershot(part of)
2163
45UF1
Crawley(part of)
304
00CX2
Keighley
2054
43UD5
Guildford
2164
45UF2
Horsham
305
00CX3
Shipley
2055
43UD6
Godalming(part of)
2165
45UF3
Steyning/Upper Beeding
306
00CX4
Bingley
2056
43UD7
Send/West Clandon/Ripley
2166
45UF4
Southwater
307
00CX5
Baildon
2057
43UD8
East Horsley
2167
45UF5
Storrington
308
00CX6
Queensbury
2058
43UE0
rural
2168
45UF6
Billingshurst
309
00CX7
Menston
2059
43UE1
Leatherhead(main)
2169
45UF7
Henfield
310
00CX8
Brighouse(part of)
2060
43UE2
Crawley(part of)
2170
45UF8
Pulborough
311
00CX9
Ilkley
2061
43UE3
Dorking
2171
45UF9
West Chiltington Common
312
00CY0
rural
2062
43UF0
rural
2172
45UG0
rural
313
00CY1
Brighouse(main)

NTEM 62 Guidance
11642097

ZoneID
Zonecode
ZoneName
ZoneID
Zonecode
ZoneName

314
00CY10
Mytholmroyd
431
00FC1
Grimsby

315
00CY2
Shelf
432
00FC2
Cleethorpes

316
00CY3
Huddersfield(part of)
433
00FC3
Humberston

317
00CY4
Halifax
434
00FC4
Waltham

318
00CY5
Elland
435
00FC5
New Waltham

319
00CY6
Todmorden
436
00FC6
Immingham/Killingholme(main)

320
00CY7
Northowram
437
00FD0
rural

321
00CY8
Hebden Bridge
438
00FD1
Scunthorpe

322
00CY9
Ripponden
439
00FD2
Immingham/Killingholme(part
of)

323
00CZ0
rural
440
00FD3
Barton-upon-Humber

324
00CZ1
Huddersfield(main)
441
00FD4
Brigg

325
00CZ10
Meltham
442
00FD5
Winterton

326
00CZ11
Shepley/Shelley
443
00FD6
Broughton nr Scunthorpe

327
00CZ12
Kirkburton
444
00FD7
Epworth

328
00CZ13
Marsden
445
00FD8
Messingham

329
00CZ2
Dewsbury
446
00FD9
Crowle

330
00CZ3
Batley
447
00FF0
rural

331
00CZ4
Cleckheaton and Liversedge
448
00FF1
York

332
00CZ5
Holmfirth/Honley
449
00FF2
Haxby

333
00CZ6
Mirfield
450
00FF3
Strensall

334
00CZ7
Heckmondwike
451
00FF4
Copmanthorpe

335
00CZ8
Bradford(part of)
452
00FF5
Poppleton

336
00CZ9
Skelmanthorpe/Clayton West
453
00FF6
Bishopthorpe

337
00DA0
rural
1792
36UB0
rural

338
00DA00
rural
1793
36UB1
Skipton

339
00DA1
Leeds
1794
36UB2
Glusburn

340
00DA10
Great Preston/Kippax
1795
36UB3
Settle

341
00DA11
Garforth
1796
36UC0
rural

342
00DA12
Otley(main)
1797
36UC1
Northallerton

343
00DA14
Wetherby & Collington
1798
36UC2
Thirsk

344
00DA15
Boston Spa
1799
36UC3
Stokesley

345
00DA16
Bramhope
1800
36UC4
Great Ayton

346
00DA17
Swillington
1801
36UC5
Bedale

347
00DA18
East Keswick/Bardsey
1802
36UC6
Easingwold

348
00DA2
Morley
1803
36UD0
rural

349
00DA3
Pudsey
1804
36UD1
Harrogate/Knaresborough

350
00DA4
Guiseley/Yeadon
1805
36UD2
Ripon/Sharow

351
00DA5
Horsforth
1806
36UD3
Otley(part of)

352
00DA6
Lofthouse/Stanley(part of)
1807
36UD4
Boroughbridge

353
00DA7
Bradford(part of)
1808
36UE0
rural

354
00DA9
Rothwell nr Leeds
1809
36UE1
Catterick Garrison

355
00DB0
rural
1810
36UE2
Richmond

356
00DB1
Wakefield
1811
36UF0
rural

357
00DB10
Featherstone (Yorkshire)
1812
36UF1
Norton & Malton

358
00DB12
Hemsworth
1813
36UF3
Pickering

359
00DB13
Normanton North
1814
36UG0
rural

360
00DB14
Upton
1815
36UG1
Scarborough

361
00DB15
Ackworth Moor Top
1816
36UG2
Eastfield

362
00DB16
Crofton
1817
36UG3
Scalby

363
00DB17
Ryhill
1818
36UG4
Whitby

364
00DB18
Fitzwilliam
1819
36UG5
Filey

365
00DB19
Walton
1820
36UG6
Hunmanby

366
00DB2
Ossett
1821
36UH0
rural

367
00DB3
Lofthouse/Stanley(main)
1822
36UH1
Selby

368
00DB4
Horbury
1823
36UH3
Tadcaster

369
00DB5
Castleford
1824
36UH4
Sherburn in Elmet

370
00DB6
Normanton South
1825
36UH5
Barlby

371
00DB7
Pontefract

372
00DB8
South Kirkby/South Elmsall

373
00DB9
Knottingley

412
00FA1
Kingston upon Hull(main)

413
00FB0
rural

414
00FB00
rural

415
00FB1
Kingston upon Hull(part of)

416
00FB10
Pocklington

417
00FB11
North Ferriby/Swanland

418
00FB12
Withernsea

419
00FB13
Market Weighton

420
00FB14
Howden

421
00FB15
Stamford Bridge

422
00FB16
South Cave

423
00FB2
Bridlington

424
00FB3
Beverley

425
00FB4
Goole

426
00FB5
Great Driffield

427
00FB6
Hedon

428
00FB8
Brough/Elloughton/Welton

429
00FB9
Hornsea

430
00FC0
rural

11642097
NTEM 62 Guidance

11642097
NTEM 62 Guidance

Appendix B
Segmentation - Definitions

NTEM 62 Guidance
11642097

POPULATION SEGMENTS
Population is segmented by:
 Age / life stage (input)
 Age / life stage (forecasting and output)
 Gender
 Working status (for the 16-64 age groups only)
Age / life stage
(input)
Age / life stage
(forecasting / output)
Gender
Working status (for the 16 – 64
age groups only)
0 – 15
16 – 29
30 – 64
65 – 69
70 – 74
75 – 79
80 – 84
85+
0 – 15
16 – 29
30 – 64
65+
Male
Female
Full time ( 30 hours per week)
Part time (< 30 hours per week)
Students (not working)
Other non working

HOUSEHOLD SEGMENTS
Households are segmented by number of persons (not just adults). There are two
segments:
 1 person households
 2+ person households

EMPLOYMENT SEGMENTS
Employment (jobs) are segmented by:
 sector
 gender
 working status / type
There are 12 employment sectors defined in the planning data forecasts. These relate
to the trip attraction variables required by the trip end model. The definitions are as
shown below. The gender and working status segmentation is as defined above for the
population.

11642097
NTEM 62 Guidance

Employment
type
SIC(92) code
Description
E03
801
Primary and Secondary Education
E04
802
Higher Education
E05
803, 804
Adult/ Other Education
E06
551, 552
Hotels, campsites etc
E07
501, 503, 505, 521-525,
5262, 5263, 55303
Retail trade
E08
851
Health / Medical
E09
502, 504, 527, 641,
6512, 703, 711, 714,
852, 853, 93
Services (business and other) &
equipment rental & repair household
goods & postal / courier services
E10
10-45, 51, 60-62, 631,
632, 634, 90
Industry, Construction & transport
E11
55301, 55302, 554
Restaurants & bars
E12
63303, 91, 9213, 923,
925-927
Recreation & sport
E13
01, 02, 05
Agriculture & fishing
E14
Other
Business

11642097
NTEM 62 Guidance

Appendix C Source of Dwellings Input
Assumptions (AMRs)

NTEM 62 Guidance
11642097

Local Planning
Authority
Website
Document
Date
Projection
years
Adur District Council
http://www.adur.gov.uk/docs/planning/adur-development-
plan/annual-monitoring-report-dec-2010.pdf
Dec-10
2026
Arun DC
http://www.arun.gov.uk/assets/Planning/Policy_from_2010/Annual
_Monitoring_Report/Annual_Monitoring_Report_2009-
10_Bookmarked.pdf
Dec-10
2025/6
Ashford DC
http://www.ashford.gov.uk/pdf/Final%20AMR%2009-10.pdf
2010
2021
Aylesbury Vale DC

30/09/2009

Basingstoke and
Deane BC
http://www.basingstoke.gov.uk/NR/rdonlyres/B910F948-C4D1-
418D-B874-8CE036ACAAC3/0/AMR2010FINAL.pdf
AMR 2010,
undated
2020/21
Bracknell Forest BC
http://www.bracknell-forest.gov.uk/bracknell-forest-annual-
monitoring-report-2009-to-2010.pdf
2011
2025/26
Brighton & Hove
Council
http://www.brighton-hove.gov.uk/downloads/bhcc/ldf/AMR_2009-
10.pdf
AMR 2009-
2010
2024/25
Canterbury Council
http://www.canterbury.gov.uk/assets/localplan/AMR-Apr09-
Mar10%20Finalc.pdf
undated
2014/15
Cherwell DC
http://www.cherwell.gov.uk/media/pdf/q/c/AMR_2010.pdf
Nov-10
2025/26
Chichester DC
http://www.chichester.gov.uk/index.cfm?articleid=5102
2009
2014/15
Chiltern DC
http://www.chiltern.gov.uk/downloads/9_Housing_2008-
09_Complete.pdf
Dec-09
2025
Crawley BC
http://www.crawley.gov.uk/stellent/groups/public/documents/report
/int201796.pdf
2010
2025/2026
Dartford BC
http://www.dartford.gov.uk/planningpolicy/documents/AMR2008-
09GOSEversion.pdf
Dec-09
2025/26
Dover DC
http://www.dover.gov.uk/pdf/AMR%202009%20to%202010.pdf
Dec-10
2025/26
East Hampshire DC
http://www.easthants.gov.uk/ehdc/formsfordownload.nsf/0/CB3384
2F5A71FF6B802577F80035A525/$File/AMR+Final+version.pdf;
Dec-10
2027/28
Eastbourne BC
http://www.eastbourne.gov.uk/EasySiteWeb/getresource.axd?Ass
etID=147532&type=full&servicetype=Inline
Dec-10
2026/27
Eastleigh BC
http://www.eastleigh.gov.uk/PDF/2009-
2010AnnualMonitoringReport.pdf
Dec-10
2006-2014
Elmbridge BC
http://www.elmbridge.gov.uk/documents/detail.htm?pk_document=
18977
09/10
2004-2025
Epsom and Ewell
BC
http://www.epsom-ewell.gov.uk/NR/rdonlyres/B092A08A-9D47-
4AC3-8C7D-
B696CC4A628B/0/AnnualMonitoringReport200910.pdf
09/10
2001-2025
Fareham BC
http://www.fareham.gov.uk/pdf/planning/amr2010.pdf
Dec-10
2005-2025
Gosport BC
http://www.gosport.gov.uk/sections/your-council/council-
services/planning-section/annual-monitoring-report/
Nov-10
2005-2025
Gravesham BC
http://www.gravesham.gov.uk/media/pdf/t/c/Gravesham_Annual_
Monitoring_Report_2010_Revised.pdf
Dec-10
2006-2025
Guildford BC
http://www.guildford.gov.uk/CHttpHandler.ashx?id=7559&p=0
09/10
2001-2009
Hart DC
http://www.hart.gov.uk/final_amr_for_hart_dc_december_2010.pdf
Dec-10
2004-2025
Hastings BC
http://www.hastings.gov.uk/ldf/amr2009_2010.pdf
Dec-10
2004-2025
Havant BC
http://www.havant.gov.uk/PDF/AMR%202010%20opt%20for%20w
eb.pdf
Dec-10
2001-2025
Horsham DC
http://www.horshamdistrictldf.info/Files/AMR_0809.pdf
Dec-09
2001-2025
Isle of Wight
http://www.iwight.com/living_here/planning/images/2AMR08_09.p
df
Dec-09
2005-2025
Lewes DC
http://www.lewes.gov.uk/Files/plan_AMR_2010.pdf
09/10
2003-2025

11642097
NTEM 62 Guidance

Local Planning
Authority
Website
Document
Date
Projection
years
Maidstone BC
http://www.maidstone.gov.uk/pdf/101214%20AMR%20final%20wit
h%20cover.pdf
Dec-10
2004-2009
Medway Council
http://www.medway.gov.uk/pdf/AMR%202010%20vol1.pdf
Dec-10
2006-2027
Mid Sussex DC
http://www.midsussex.gov.uk/Nimoi/sites/msdcpublic/resources/A
MR%202008%20-%202009%20Final%20_addendum_1.pdf
08/09
2004-2025
Milton Keynes
Council
http://www.miltonkeynes.gov.uk/planning-
policy/documents/MK_2009-10_AMR_%282%29.pdf
Dec-10
2004-2025
Mole Valley DC
http://www.molevalley.gov.uk/media/pdf/9/8/Merged_AMR.pdf
09/10
2004-2025
New Forest DC
http://www.newforest.gov.uk/index.cfm?articleid=6618&articleactio
n=dispmedia&mediaid=10106
Dec-09
2004-2025
New Forest National
Park Authority
http://www.newforestnpa.gov.uk/final_amr_2010.pdf
Nov-10
2001-2025
Oxford Council
http://www.oxford.gov.uk/Direct/AnnualMonitoringReport200910.p
df
Dec-10
2001-2025
Portsmouth Council
http://www.portsmouth.gov.uk/media/AMR2010.pdf
Dec-10
2004-2026
Reading BC
http://ww2.reading.gov.uk/documents/servingyou/planning/local_d
evelopment_framework/Annual_Monitoring_Report_2010.pdf
Dec-10
2002-2025
Reigate & Banstead
http://www.reigate-banstead.gov.uk/Images/AMR%202009_tcm9-
39500.pdf
2008-2009
2003-2025
Rother DC
http://www.rother.gov.uk/media/pdf/8/4/AMR_FINAL.pdf
Dec-10
2004-2025
Runnymede BC
http://www.runnymede.gov.uk/portal/binary/com.epicentric.content
management.servlet.ContentDeliveryServlet/RBC%2520Portal/LG
CL%2520Categories/Environment/Land%2520%2526%2520premi
ses/Planning/Local%2520Development%2520Framework/AMR_0
809.pdf
AMR
2008/09
2001-2025
Rushmoor BC
http://www.rushmoor.gov.uk/media/adobepdf/i/9/FINAL_AMR_201
0.pdf
Dec-10
2001-2026
Sevenoaks DC
http://www.sevenoaks.gov.uk/documents/amr_2010_.pdf
Dec-10
2006-2025
Shepway DC
http://www.shepway.gov.uk/UserFiles/File/pdf/local-plan/annual-
monitoring-report/Shepway%20AMR%202010.pdf
09/ 10
2005-2015
Slough BC
http://www.slough.gov.uk/documents/AMR_09-10_Web_Vn.pdf
Dec-10
2006-2025
South
Buckinghamshire
DC
http://www.southbucks.gov.uk/includes/documents/cm_docs/2011/
a/annualmonitoringreportcovering200910.pdf
Dec-10
2006-2025
South Oxfordshire
DC
http://www.southoxon.gov.uk/ccm/content/planning/local-
plan/annual-monitoring-report.en
09/10
2006-2025
Southampton
Council
http://www.southampton.gov.uk/Images/Southampton%20CC%20
AMR%202009-10_tcm46-279848.pdf
09/10
2001-2025
Spelthorne BC
http://www.spelthorne.gov.uk/annual_monitoring_report_2010_fina
l.pdf
Nov-10
2004-2025
Surrey Heath BC
http://www.surreyheath.gov.uk/planning/planningpolicyandconserv
ation/AMR.htm?textsize=1
Dec-10
2001-2025
Swale BC
http://www.swale.gov.uk/assets/Planning-General/Planning-
Policy/Annual-Monitoring-Report/Swale-Borough-Council-AMR-09-
10-with-cover.pdf
09/10
2006-2025
Tandridge DC
http://www.tandridge.gov.uk/yourcouncil/documents/document_dis
play.htm?pk_document=2800
Dec-10
2003-2025
Test Valley BC
http://www.testvalley.gov.uk/pdf/Annual%20Monitoring%20Report
%2009-10(1).pdf
Dec-10
2006-2025
Thanet DC
http://www.thanet.gov.uk/environment__planning/planning/ldf_and
_local_plan/local_development_framework-
08/09
2001-2025

NTEM 62 Guidance
11642097

Local Planning
Authority
Website
Document
Date
Projection
years
1/annual_monitoring_report/annex_3_housing_trajectory.aspx
Tonbridge and
Malling BC
http://www.tmbc.gov.uk/assets/planning_policy/LDF/AMR2009_FI
NAL_211209.pdf
08/09
2006-2020
Tunbridge Wells BC
http://www2.tunbridgewells.gov.uk/pdf/PP_AMR_December_2010.
pdf
Dec-10
2006-2025
Vale of White Horse
DC
http://www.whitehorsedc.gov.uk/Images/AMR%202009-
10%20final_tcm4-8200.pdf
Dec-10
2006-2025
Waverley BC
http://www.waverley.gov.uk/downloads/file/1540/annual_monitorin
g_report_amr_2008-09-main_report
08/09
2006-2024
Wealden DC
http://www.wealden.gov.uk/Wealden/Planning_and_Building_Cont
rol/Planning_Policy/Local_Development_Framework
09/10
2004-2015
West Berkshire DC
http://www.westberks.gov.uk/CHttpHandler.ashx?id=21560&p=0
Dec-09
2002-2024
West Oxfordshire
DC
https://www.westoxon.gov.uk/files/download/7935-4212.pdf
Dec-10
2006-2019
Winchester Council
http://www.winchester.gov.uk/Documents/LDF/AMR%202010/Ann
ualMonitoringReport2010.pdf
Dec-10
2004-2025
Windsor &
Maidenhead
http://www.rbwm.gov.uk/public/pp_amr2010_report.pdf
Dec-10
2005-2025
Woking BC
http://www.woking.gov.uk/planning/policy/ldf/amr/amr200910.pdf
Dec-10
2003-2026
Wokingham DC
http://www.wokingham.gov.uk/planningcontrol/planning/planningp
olicies/ldf/amr/?assetdetesctl3161295=182845
Dec-10
2001-2025
Worthing BC
http://www.worthing.gov.uk/worthings-
services/planningandbuildingcontrol/planningpolicy/localdevelopm
entframework/annualmonitoringreport/pdffile,76728,en.pdf
Dec-10
2003-2025
Wycombe DC
http://www.wycombe.gov.uk/council-services/planning-and-
building/planning-policy/wycombe-development-framework.aspx
Dec-10
2001-2025
Babergh DC
http://www.babergh-south-suffolk.gov.uk/NR/rdonlyres/A3F24CF9-
E9B4-4BBF-8F05-E38B986B0CEB/0/AMR20092010.pdf
AMR 2009-
2010
to 20/21
Basildon DC
http://www.basildon.gov.uk/CHttpHandler.ashx?id=2114&p=0
2009
to
2024/2025
Bedford BC
http://www.bedford.gov.uk/environment_and_planning/planning_to
wn_and_country/planning_policy/annual_monitoring_report.aspx
Dec-10
to
2015/2016
Braintree DC
http://www.braintree.gov.uk/NR/rdonlyres/4CE7CBE7-7775-4FC7-
92F0-87085D5F460D/0/finalreport.pdf
1/4/09 -
31/3/10
to
2025/2026
Breckland DC
http://80.82.124.74/sites/default/files/legacy_files/breckland_amr_
2009.pdf
2009
to
2025/2026
Brentwood BC
http://www.brentwood.gov.uk/index.php?cid=880
Dec-10
to
2024/2025
Broadland
http://www.broadland.gov.uk/PDF/AMR_09-10_22.12.10.pdf
09/10
2001-2025
Broads Authority
http://www.broads-authority.gov.uk/broads/live/planning/future-
planning-and-policies/local-development-
framework/Annual_Monitoring_Report__2009-2010.pdf
Autumn
2010
2007-2023
Broxbourne BC
http://www.broxbourne.gov.uk/pdf/AMR%202009-
2010%20(Dec%2010)_Part1.pdf
Dec-10
2001-2025
Cambridge Council
http://www.cambridge.gov.uk/public/docs/Annual-Monitoring-
Report-2010.pdf
Dec-10
to
2020/2021
Castle Point DC
http://www.castlepoint.gov.uk/file/AMR_Final_08_09.pdf
2008/2009
to
2024/2025
Central Bedfordshire
Council
http://www.centralbedfordshire.gov.uk/images/LDF%20AMR%20(
North)%20Dec%202010_tcm5-35791.pdf
Dec-10
2001-2025

11642097
NTEM 62 Guidance

Local Planning
Authority
Website
Document
Date
Projection
years
Chelmsford BC
http://www.chelmsford.gov.uk/index.cfm?articleid=11653
Dec-10
to 2021
Colchester BC
http://www.colchester.gov.uk/Info_page_two_pic_2_det.asp?art_id
=2880&sec_id=1286
Dec-10
to
2023/2024
Dacorum BC
http://www.dacorum.gov.uk/pdf/strategicPlanning-10.12.23-AMR-
2010_Final.pdf
Dec-10
to2030/203
1
East
Cambridgeshire DC
http://www.eastcambs.gov.uk/sites/default/files/ldf/annual_monitori
ng_report_2009_30107.pdf
Dec-09
to
2024/2025
East Hertfordshire
DC
http://www.eastherts.gov.uk/index.jsp?articleid=11714
Dec-10
to
2025/2026
Epping Forest DC
http://www.eppingforestdc.gov.uk/Library/files/planning/Local_Dev
elopment_Framework/Evidence_Base/AMRs/EFDC%20AMR%20f
inal%202009.pdf
Dec-09
2001-2020
Fenland DC
http://www.fenland.gov.uk/ccm/content/development-
policy/ldf/amr/amr2008-09.en
Dec-09
2001-2025
Forest Heath DC
http://www.forest-heath.gov.uk/NR/rdonlyres/D8FB4B9C-BB3F-
4998-9866-3EAFC4E41683/0/AMR20092010FINAL.pdf
Dec-10
2001-2030
Great Yarmouth BC
http://www.great-yarmouth.gov.uk/2009-amr-master.pdf
('08/'09
report)
2001-2024
Harlow DC
http://www.harlow.gov.uk/pdf/Annual%20Monitoring%20Report%2
02009%20V3.pdf
09/10
2001-2020
Hertsmere BC
http://www.hertsmere.gov.uk/planning/dnld_200074/FINALAMR20
08_09.pdf?action=open
Dec-09
2001-
Huntingdonshire DC
http://www.huntingdonshire.gov.uk/SiteCollectionDocuments/HDC
CMS/Documents/Planning%20Documents/PDF%20Documents/Lo
cal%20Development%20Framework/AMR%20December%202010
.pdf
Dec-10
2001-2025
Ipswich BC
http://www.ipswich.gov.uk/downloads/Ipswich_AMR_2009-10.pdf
Dec-10
2001-2025
Kings Lynn & West
Norfolk BC
http://www.west-
norfolk.gov.uk/pdf/Kings%20Lynn%20and%20West%20Norfolk%2
0AMR%20dec%202010.pdf
Dec-10
2009-2025
Luton and South
Bedfordshire Joint
Planning Committee
http://www.shapeyourfuture.org.uk/documents/LutonandsouthernCen
tralBedsAMR0910.pdf
09/10
2001-2025
Maldon DC
http://www.maldon.gov.uk/NR/rdonlyres/C55F33E8-9F6E-4486-
A098-07F8A31C2920/13792/AMR2010.pdf
Dec-10
2001-2009
Mid Suffolk DC
http://www.midsuffolk.gov.uk/NR/rdonlyres/074F136F-DBF9-
4FFB-80D7-68024EE577D6/0/AnnualMonitoringReport2009.pdf
Dec-09
2001-2024
North Hertfordshire
DC
http://www.north-herts.gov.uk/annual_monitoring_report_2009-
2010.pdf
Dec-10
2001-2030
North Norfolk DC
http://www.northnorfolk.org/ldf/documents/Annual_Monitoring_Rep
ort_2008-2009.pdf
Dec-09
2001-2023
Norwich Council
http://www.norwich.gov.uk/intranet_docs/A-
Z/Planning%20Policy/AMR_09_10.pdf
Dec-10
2001-2024
Peterborough
Council
http://www.peterborough.gov.uk/PDF/env-plan-research-
Pboro%20LDF%20AMR%202010.pdf
Dec-10
2002-2024
Rochford DC
http://www.rochford.gov.uk/pdf/planning_evibase_annual_monitori
ng_report0910.pdf
Dec-10
2009-2030
South
Cambridgeshire DC
http://www.scambs.gov.uk/documents/retrieve.htm?pk_document=
909653
Dec-10
2001-2024
South Norfolk
http://www.south-
norfolk.gov.uk/planning/media/LDF_Annual__Monitoring_Report_
2009-10.pdf
Dec-10
2001-2024

NTEM 62 Guidance
11642097

Local Planning
Authority
Website
Document
Date
Projection
years
Southend-on-Sea
BC
http://www.southend.gov.uk/downloads/download/232/annual_mo
nitoring_report
Dec-09
2001-2022
St Albans Council
http://www.stalbans.gov.uk/Images/Annual%20Monitoring%20Rep
ort%202010_tcm15-15454.pdf
Dec-10
2001-2027
St Edmundsbury BC
http://www.stedmundsbury.gov.uk/sebc/live/pdf/planning/helpdesk/
FINAL%20AMR%200910%20SMALL%20FILE%2003.12.10.pdf
Dec-10
2001-2030
Stevenage BC
http://www.stevenage.gov.uk/planningandregeneration/planningre
gulationsandpolicy/ldf/dnld_ldf/Annual_Monitoring_Report_2010.p
df
Sep-10
2001-2020
Suffolk Coastal DC
http://www.suffolkcoastal.gov.uk/NR/rdonlyres/1D4F13DE-85F8-
46DB-A5B0-
E11169A191A6/0/SCDCAnnualMonitoringReport2010.pdf
Dec-10
2001-2026
Tendring DC
http://www.tendringdc.gov.uk/NR/rdonlyres/1ED82123-AE46-
4C69-9CEB-
CA1A066959AF/7998/TDC2009AMRFinalVersionwithAppendices
andCover.pdf
Dec-09
2001-2025
Three Rivers DC
http://www.threerivers.gov.uk/GetResource.aspx?file=Annual
Monitoring Report 2008_09.pdf
Dec-09
2001-2025
Thurrock Council
http://www.thurrock.gov.uk/planning/strategic/pdf/monitor_annual_
2010.pdf
Dec-10
2001-2025
Uttlesford DC
http://www.uttlesford.gov.uk/uttlesford/file/Annual%20Monitoring%
20Report%2010.pdf
Dec-10
2001-2025
Watford BC
http://www.watford.gov.uk/ccm/content/planning-and-
development/watford-annual-monitoring-report-2010.en
09/10
2001-2030
Waveney DC
http://www.waveney.gov.uk/NR/rdonlyres/793E5B28-50C5-4A20-
8A70-159FC99DBCCB/0/AMR200910FinalVersion.pdf
Dec-10
2001-2024
Welwyn Hatfield DC
http://www.welhat.gov.uk/CHttpHandler.ashx?id=3515&p=0
Dec-10
2001-2025
Barking &
Dagenham LBC
http://www.barking-dagenham.gov.uk/8-leisure-
envir/planning/local-dev-framework/pdf/monitoring-report-0910-
main.pdf
Dec-10
2001-2024
Barnet LBC
http://www.barnet.gov.uk/annual-monitoring-report-2009-10.pdf
Dec-10
2001-2025
Bexley LBC
http://www.bexley.gov.uk/CHttpHandler.ashx?id=5561&p=0
Dec-09
2003-2024
Brent
http://www.brent.gov.uk/tps.nsf/Files/LBBA-
820/$FILE/AMR%20200809.pdf
08/09
2003-2024
Bromley LBC
http://www.bromley.gov.uk/environment/planning/planningpolicy/ldf
/Bromley+Annual+Monitoring+Report.htm
Dec-09
2004-2015
Camden LBC
http://www.camden.gov.uk/ccm/content/environment/planning-
and-built-environment/development-plans-and-policies/local-
development-framework/evidence-base-and-
monitoring.en;jsessionid=85CCF11CF0ED46B7D519E60E746A4
DFB
09/10
2005-2025
City of London
http://www.cityoflondon.gov.uk/NR/rdonlyres/F0EE446C-D872-
4D5D-9BC5-5F12CB4F2092/0/DP_PL_CityofLondonAMR.pdf
08/09
2001-2015
Croydon LBC
http://www.croydon.gov.uk/contents/departments/planningandrege
neration/pdf/912686/amr0910final
09/10
2001-2020
Ealing LBC
http://www.ealing.gov.uk/ealing3/export/sites/ealingweb/services/e
nvironment/planning/planning_policy/local_development_framewo
rk/amr/_docs/amr_2009-2010.pdf
Dec-10
2003-2030
Enfield LBC
http://www.enfield.gov.uk/downloads/file/1859/annual_monitoring_
report_april_08-march_09
Jan-10
2003-2024
Greenwich LBC
http://www.greenwich.gov.uk/Greenwich/Strategies/LandAndBuildi
ngDevelopmentPlan/AnnualMonitoringReport.htm
09/10
2001-2019

11642097
NTEM 62 Guidance

Local Planning
Authority
Website
Document
Date
Projection
years
Hackney LBC
http://www.hackney.gov.uk/Assets/Documents/Annual-Monitoring-
Report-2009-10.pdf
Oct-10
2006-2025
Hammersmith &
Fulham LBC
http://www.lbhf.gov.uk/Images/AMR%202010%20website_tcm21-
154853.pdf
Dec-10
2002-2024
Haringey LBC
http://www.haringey.gov.uk/annual_monitoring_report_2008-
09.pdf
Dec-09
2001-2025
Harrow LBC
http://www.harrow.gov.uk/downloads/file/8881/annual_monitoring_
report_december_2010
Dec-10
2004-2025
Havering LBC
http://www.havering.gov.uk/CHttpHandler.ashx?id=20335&p=0
Dec-09
2003-2023
Hillingdon LBC
http://www.hillingdon.gov.uk/media/pdf/o/2/LB_Hillingdon_AMR_2
009-2010.pdf
Dec-10
2004-2025
Hounslow LBC
http://www.hounslow.gov.uk/ldf_amr_2010.pdf
Dec-10
2004-2025
Islington LBC
http://www.islington.gov.uk/DownloadableDocuments/Environment
/Pdf/ldf_pack/Annual_Monitoring_Report_2009.pdf
Dec-09
2002-2024
Kensington &
Chelsea LBC
http://www.rbkc.gov.uk/planningandconservation/planningpolicy/an
nualmonitoringreport.aspx
Dec-10
2002-2023
Kingston Upon
Thames LBC
http://www.kingston.gov.uk/rbk_2010_amr__small_web_version_-
2.pdf
Dec-10
2004-2024
Lambeth LBC
http://www.lambeth.gov.uk/NR/rdonlyres/3CDFED5B-A4D3-4C78-
8D03-
6E3683EA784B/0/LambethAnnualMonitoringReport200910.pdf
09/10
2003-2024
Lewisham LBC
http://www.lewisham.gov.uk/NR/rdonlyres/499499AA-6B85-4980-
9112-5F0A9CD04A1D/0/AMR200910.pdf
09/10
2004-2025
Merton LBC
http://www.merton.gov.uk/living/planning/planningpolicy/ldf/merton
_amr_08_09_-_full_version.pdf
08/09
2003-2017
Newham LBC
http://www.newham.gov.uk/NR/rdonlyres/E749857E-5679-44B5-
8674-
7222E3E7D60E/0/LocalDevelopmentFrameworkAnnualMonitoring
Report20092010.pdf
09/10
2002-2026
Redbridge LBC
http://www.redbridge.gov.uk/cms/planning_land_and_buildings/pla
nning_policy__regeneration/local_development_framework/ldf_an
nual_report.aspx
Dec-10
2001-2016
Richmond Upon
Thames LBC
http://www.richmond.gov.uk/richmond_2009-2010_amr.pdf
Dec-10
2001-2025
Southwark LBC
http://www.southwark.gov.uk/downloads/download/1860/annual_
monitoring_report_amr
Dec-10
2001-2025
Sutton LBC
http://www.sutton.gov.uk/index.aspx?articleid=2339
Dec-09
2006-2023
Tower Hamlets LBC
http://www.towerhamlets.gov.uk/lgsl/851-
900/856_local_development_framewor/annual_monitoring_report.
aspx
08/09
2003-2024
Waltham Forest LBC
http://www.walthamforest.gov.uk/final-amr-09-10.pdf
Dec-10
2004-2025
Wandsworth LBC
http://www.wandsworth.gov.uk/downloads/file/3891/annual_monito
ring_report_amr_200910
09/10
2004-2025
Westminster LBC
http://www3.westminster.gov.uk/docstores/publications_store/Cop
y%20of%20AMR%202008-09.pdf
Dec-09
2006-2015
Darlington BC
http://www.darlington.gov.uk/dar_public/documents/Development
%20and%20Environment/Development%20and%20Regeneration/
Planning%20Services/Policy/AMR_200910_FINAL_DOCUMENT_
App_1_separate.pdf
Dec-10
2004-2025
Durham Council
http://content.durham.gov.uk/PDFRepository/AnnualMonitoringRe
portDuhamCountyCouncil200809.pdf
08/09
2004-2023

NTEM 62 Guidance
11642097

Local Planning
Authority
Website
Document
Date
Projection
years
Gateshead
http://www.gateshead.gov.uk/DocumentLibrary/Building/Strategies
/AMR/GatesheadCouncilAnnualMonitoringReport20082009.pdf
Dec-09
2004-2024
Hartlepool BC
http://www.hartlepool.gov.uk/downloads/file/6887/annual_monitori
ng_report_2009-10
Dec-10
2004-2020
Middlesbrough BC
http://www.middlesbrough.gov.uk/public/Planning/LDF%20pdfs/A
MR%202009-10.pdf
Dec-10
2004-2025
Newcastle Upon
Tyne Council
http://www.newcastle.gov.uk/wwwfileroot/regen/ldf/AMR_2008_09.
pdf
08/09
2004-2029
North Tyneside MBC
http://www.northtyneside.gov.uk/pls/portal/NTC_PSCM.PSCM_We
b.download?p_ID=515173
Dec-09
2004-2025
Northumberland
Council
http://www.northumberland.gov.uk/default.aspx?page=3459
Dec-10
2004-2015
Northumberland NP
http://www.northumberlandnationalpark.org.uk/state_of_the_park_
report_2010.pdf
Jun-10

Redcar & Cleveland
BC
http://www.redcar-
cleveland.gov.uk/main.nsf/608BBE195DFBD9ED8025717200386
C67/$FILE/AMR%20Final%20version%2009-10.pdf
Dec-10
2005-2025
South Tyneside
MBC
http://www.southtyneside.info/CHttpHandler.ashx?id=9868&p=0
Dec-10
2004-2020
Stockton-on-Tees
BC
http://www.stockton.gov.uk/resources/planning/amr/AMR2009201
0.pdf
Dec-10
2004-2024
Sunderland Council
http://www.sunderland.gov.uk/CHttpHandler.ashx?id=2039&p=0
Dec-09
2004-2023
Allerdale DC
http://www.allerdale.gov.uk/downloads/page1010/AMR_2009-
2010(Read-Only).pdf
Dec-10
2003-2026
Barrow-in-Furness
BC
http://www.barrowbc.gov.uk/pdf/AMR%202009-10%20Final.pdf
Dec-10
2003-2024
Blackburn with
Darwen BC
http://www.blackburn.gov.uk/upload/pdf/AMR5_final_2010032610
5259.pdf
Dec-09
2003-2020
Blackpool Council
http://www.blackpool.gov.uk/NR/rdonlyres/E666ECE4-C7BF-
458A-9C18-2AB50AC60069/0/FinalAMR10withFrontCover.pdf
Dec-10
2003-2020
Bolton MBC
http://www.bolton.gov.uk/sites/DocumentCentre/Documents/Annu
al%20Monitoring%20Report%202008-2009%20New.pdf
Dec-09
2003-2025
Burnley BC
http://www.burnley.gov.uk/site/scripts/download_info.php?fileID=3
595&PHPSESSID=b09fc7e9ee69ff4f97a83ac847987d6b
Dec-10
2003-2020
Bury MBC
http://www.bury.gov.uk/NR/rdonlyres/F7B49252-F799-4B34-
BD4A-81AF9BF2B641/0/AnnualMonitoringReport2010.pdf
Dec-10
2003-2025
Carlisle
http://www.carlisle.gov.uk/pdf/amr2009.pdf
Dec-09
2001-2023
Cheshire East
http://www.cheshireeast.gov.uk/environment_and_planning/planni
ng/spatial_planning/local_development_framework/annual_monito
ring_report.aspx
Dec-10
2001-2025
Cheshire West and
Chester
http://www.cheshirewestandchester.gov.uk/planning/spatial_planni
ng/ldf/annual_monitoring_report.aspx
08/09
2003-2020
Chorley
http://www.chorley.gov.uk/CHttpHandler.ashx?id=3619&p=0
08/09
2003-2023
Copeland DC
http://www.copelandbc.gov.uk/pdf/AMR%20final%20for%20web1.
pdf
09/10
2003-2020
Eden DC
http://www.eden.gov.uk/planning-and-development/eden-local-
development-framework/annual-monitoring-report/
Dec-09
2005-2024
Fylde BC
http://www.fylde.gov.uk/local-plan/local-development-
framework/annual-monitoring-report/
Dec-10
2003-2020
Halton BC
http://www2.halton.gov.uk/pdfs/environment/planning/annualmonit
oring2009
Dec-09
2003-2020

11642097
NTEM 62 Guidance

Local Planning
Authority
Website
Document
Date
Projection
years
Hyndburn BC
http://www.hyndburnbc.gov.uk/downloads/AMR09-10.pdf
Dec-10
2003-2024
Knowsley MBC
http://www.knowsley.gov.uk/pdf/2010KnowsleyAMRFinal.pdf
Dec-10
2002-2026
Lake District NP
http://www.lakedistrict.gov.uk/lake_district_docs95/amr_0910.pdf
09/10
2003-2020
Lancaster Council
http://www.lancaster.gov.uk/planning-environment/forward-
planning/local-development-framework/annual-monitoring-report/
Dec-10
2003-2024
Liverpool Council
http://www.liverpool.gov.uk/Images/tcm21-169655.pdf
08/09
2003-2023
Manchester Council
http://www.manchester.gov.uk/downloads/download/972/annual_
monitoring_report
08/09
2003-2020
Oldham MBC
http://www.oldham.gov.uk/localdf-annual-monitoring-report-
2010.pdf
Dec-10
2003-2030
Pendle BC
http://www.pendle.gov.uk/downloads/file/5919/annual_monitoring_
report_200910
Dec-10
2003-2020
Preston BC
http://www.preston.gov.uk/environment-and-
planning/planning/planning-policies/local-development-
framework/annual-monitoring-report/
Dec-09
2003-2023
Ribble Valley BC
http://www.ribblevalley.gov.uk/downloads/file/7354/annual_monitor
ing_report_2010
Dec-10

Rochdale MBC
http://www.rochdale.gov.uk/pdf/2010-04-
30_LDF_AMR_December_2009.pdf
Dec-09
2003-2025
Rossendale BC
http://www.rossendale.gov.uk/downloads/AMR_2009-2010.pdf
Dec-10
2003-2025
Salford Council
http://www.salford.gov.uk/planning-annual-monitoring-report.htm
Dec-10
2003-2024
Sefton MBC
http://www.sefton.gov.uk/pdf/PERD_2010_AMR.pdf
Dec-10
2003-2020
South Lakeland DC
http://www.southlakeland.gov.uk/downloads/page2028/AMR_2010
.pdf
Dec-10
2003-2024
South Ribble
http://www.southribble.gov.uk/upload/public/attachments/xx-xxxx-xxxx_
amr_report.pdf
Dec-10
2003-2020
St Helens MBC
http://localdevelopment.sthelens.gov.uk/SITEMAN/publications/31/
AMR_2009_Amended_Feb10.pdf
Dec-09
2003-2024
Stockport MBC
http://stockport-
consult.limehouse.co.uk/portal/pp/zzz_adopteddocuments/aaa_lds
amrsci/amr_1/amr
Dec-10
2005-2024
Tameside MBC
http://www.tameside.gov.uk/planning/ldf/annualmonitoring
Dec-09
2003-2023
Trafford MBC
http://www.trafford.gov.uk/cme/live/dynamic/DocMan2Document.a
sp?document_id=30B134BE-3ED7-4A5A-943A-B6CAF2A1F0B9
Dec-10
2003-2025
Warrington BC
http://www.warrington.gov.uk/content_documents/Documents/Plan
ning/Latest_AMR.pdf
08/09
2003-2020
West Lancashire DC
http://www.westlancsdc.gov.uk/PDF/Final_AMR2010.pdf
Dec-10
2001-2022
Wigan MBC
http://www.wigan.gov.uk/NR/rdonlyres/DF12BDD8-682E-44C0-
B556-31116BA7917F/0/FifthAnnualMonitoringReport1305kb.pdf
Dec-09
2002-2020
Wirral MBC
http://www.wirral.gov.uk/my-services/environment-and-
planning/planning/local-development-framework/annual-
monitoring-reports
09/10
2003-2020
Wyre BC
http://www.wyrebc.gov.uk/Page.aspx?PgeID=73766
Dec-10
2003-2020
Bath & NE Somerset
Council
http://www.bathnes.gov.uk/SiteCollectionDocuments/Environment
%20and%20Planning/Planning/planning%20policy/Annual%20Mo
nitoring%20Report%202009-10.pdf
Dec-10
2003-2025
Bournemouth BC
http://www.bournemouth.gov.uk/Library/PDF/Living/Planning/Plan
ning_Policy/Local/AMR_200910/2009-10_AMR_FINAL_WEB.pdf
Dec-10
2001-2025
Bristol Council
http://www.bristol.gov.uk/ccm/cms-
service/stream/asset/?asset_id=36038163
09/10
2002-2016
Cheltenham
http://www.cheltenham.gov.uk/downloads/FINAL_AMR_2010__23
.12.10.pdf
Dec-10
2003-2025

NTEM 62 Guidance
11642097

Local Planning
Authority
Website
Document
Date
Projection
years
Christchurch BC
http://www.dorsetforyou.com/media.jsp?mediaid=158684&filetype
=pdf
Dec-10
2001-2025
Cornwall Council
http://www.cornwall.gov.uk/default.aspx?page=22474
09/10
2001-2015
Cotswold DC
http://consult.cotswold.gov.uk/portal/fp/amr/annual_monitoring_rep
ort_2008-2009?tab=files
Dec-09
2001-2024
Dartmoor NP
http://www.dartmoor-
npa.gov.uk/__data/assets/pdf_file/0019/63028/AMR-2010.pdf
Dec-10
2004-2024
East Devon DC
http://www.eastdevon.gov.uk/plg_amrreport08-09.pdf
Dec-09
2001-2015
East Dorset
http://www.dorsetforyou.com/media.jsp?mediaid=158749&filetype
=pdf
Dec-10
2003-2025
Exeter Council
http://www.exeter.gov.uk/index.aspx?articleid=4738
Dec-10
2002-2025
Exmoor NP
http://www.exmoor-nationalpark.gov.uk/amr_08-09_final.pdf
08/09
2002-2023
Forest of Dean DC
http://investforestofdean.org.uk/media/Assets/ForwardPlan/docum
ents/Annual%20Monitoring%20Report/AMR_2010.pdf
Dec-10
2004-2019
Gloucester Council
http://www.gloucester.gov.uk/Documents/councilservices/Planning
/localplan/LDF/gnelp1983/GloucesterCityAMR2010.pdf
09/10
2006-2025
Isles of Scilly
Council
http://committees.scilly.gov.uk/mgConvert2PDF.aspx?ID=532
Dec-08
2003-2019
Mendip DC
http://www.mendip.gov.uk/Documents/Organisational%20Develop
ment/2009%20AMR.pdf
Dec-09
2006-2025
Mid Devon DC
http://www.middevon.gov.uk/index.aspx?articleid=4016
09/10
2001-2025
North Devon DC
http://www.northdevon.gov.uk/amr_2009.pdf
Dec-09
2001-2013
North Dorset DC
http://www.dorsetforyou.com/media.jsp?mediaid=158534&filetype
=pdf
Dec-10
2004-2015
North Somerset
Council
http://www.n-somerset.gov.uk/NR/rdonlyres/01545246-53A9-
40AF-A931-12BB6AF77CB9/0/NorthSomersetAMR2009FINAL.pdf
08/09
2006-2025
Plymouth Council
http://www.plymouth.gov.uk/amr2009.pdf
08/09
2002-2025
Poole
http://www.boroughofpoole.com/downloads/assets/Annual_Monito
ring_Report_2010.pdf
Dec-10
2006-2027
Purbeck DC
http://www.dorsetforyou.com/media.jsp?mediaid=148639&filetype
=pdf
Dec-09
2001-2025
Sedgemoor DC
http://www.sedgemoor.gov.uk/CHttpHandler.ashx?id=7580&p=0
Dec-10
2006-2025
South
Gloucestershire
Council
http://www.southglos.gov.uk/NR/rdonlyres/F775B83A-F14A-427D-
A5A5-DE9A1CC4C3A9/0/PTE100296.pdf
Dec-10
2006-2025
South Hams DC
http://www.southhams.gov.uk/amr_2010_final.pdf
Dec-10
2001-2015
South Somerset DC
http://ww2.southsomerset.gov.uk/media/pdf/d/i/AMR_2008-
2009_DX_07.01.10.pdf
Dec-09
2009-2024
Stroud DC
http://www.stroud.gov.uk/info/localplan/annual_monitoring_report0
9.pdf
Dec-09
2003-2025
Swindon BC
http://www.swindon.gov.uk/amr_report-2.pdf
08/09
2003-2025
Taunton Deane BC
http://www.tauntondeane.gov.uk/irj/go/km/docs/CouncilDocuments
/TDBC/Documents/Forward%20Planning/Annual%20Monitoring%
20Report%202010.pdf
09/10
2006-2025
Teignbridge DC
http://www.teignbridge.gov.uk/CHttpHandler.ashx?id=28094&p=0
Dec-10
2001-2015
Tewkesbury
http://www.tewkesbury.gov.uk/media/pdf/j/j/LDF_Annual_Monitorin
g_Report_2008-_20009.pdf
Dec-09
2003-2025
Torbay Council
http://www.torbay.gov.uk/amr2009.pdf
Dec-09
2001-2026
Torridge
http://www.torridge.gov.uk/CHttpHandler.ashx?id=6732&p=0
Dec-10
2001-2014

11642097
NTEM 62 Guidance

Local Planning
Authority
Website
Document
Date
Projection
years
West Devon BC
http://www.westdevon.gov.uk/upload/public/attachments/1088/AM
R%20Final%2008%20Dec.pdf
Dec-10
2001-2025
West Dorset DC
http://www.dorsetforyou.com/media.jsp?mediaid=158272&filetype
=pdf
Dec-10
2001-2009
West Somerset DC
http://www.westsomersetonline.gov.uk/getattachment/Planning---
Building/Planning-Policy/Local-Development-Framework/Annual-
Monitoring-Report/West-Somerset-LDF-Annual-Monitoring-2008-
09.pdf.aspx
Dec-09
2001-2009
Weymouth and
Portland BC
http://media.weymouth.gov.uk/docstore/planning/planningpolicy/A
MR/POL_20100105_AMR.pdf
Dec-09
2002-2013
Wiltshire Council
http://consult.wiltshire.gov.uk/portal/spatial_planning/amr/annual_
monitoring_report?tab=files
09/10
2001-2015
Birmingham Council
http://www.birmingham.gov.uk/cs/Satellite?c=Page&childpagenam
e=Development-
Planning%2FPageLayout&cid=1223092558807&pagename=BCC
%2FCommon%2FWrapper%2FWrapper
08/09
2001-2013
Bromsgrove DC
http://www.bromsgrove.gov.uk/cms/pdf/AMR%202009.pdf,
http://www.bromsgrove.gov.uk/cms/pdf/AMR%202010%20%20low
%20res.pdf
Dec 09,
Dec 10
2001-2025
Cannock Chase DC
http://www.cannockchasedc.gov.uk/downloads/Annual_Monitoring
_Report_2009-2010.pdf
Dec-10
2003-3025
Coventry Council
http://www.coventry.gov.uk/ccm/navigation/environment/planning/l
ocal-development-framework/annual-monitoring-
report/;jsessionid=aQOP63Lqqy79
Oct-09
2001-2025
Dudley
http://www.dudley.gov.uk/environment--
planning/planning/planning-policy/local-development-
framework/annual-monitoring-report
Dec-10
2006-2025
East Staffordshire
BC
http://www.eaststaffsbc.gov.uk/Services/Planning%20Policy%20A
nnual%20Monitoring%20Reports/Annual%20Monitoring%20Repor
t%202009.pdf
08/09
2001-2021
Herefordshire DC
http://www.herefordshire.gov.uk/docs/AMR_Complete(1).pdf
Dec-09
2001-2022
Lichfield DC
http://www.lichfielddc.gov.uk/downloads/AMR_2010_FINAL.pdf
Dec-10
2006-2025
Malvern Hills
http://www.malvernhills.gov.uk/cms/pdf/SWAMR%202010%20(fina
l).pdf
Dec-10
2002-2025
Newcastle under
Lyme
http://www.newcastle-
staffs.gov.uk/Documents/Newcastle%20under%20Lyme%20AMR
%202009_10.pdf
Dec-10
2006-2025
North Warwickshire
BC
http://www.northwarks.gov.uk/site/scripts/documents_info.php?doc
umentID=120&pageNumber=4
Dec-09
2002-2025
Nuneaton and
Bedworth BC
http://www.nuneatonandbedworth.gov.uk/environment-
planning/planning/planning-policy/local-development-
framework/annual-monitoring-report
09/10
2001-2025
Redditch BC
http://redditch.whub.org.uk/cms/PDF/Annual%20Monitoring%20Re
port%2008-09.pdf
Dec-09
2001-2025
Rugby BC
http://www.rugby.gov.uk/downloads/AMR_2008-2009_final_21-1-
2010.pdf
Dec-09
2001-2025
Sandwell MBC
http://www.sandwell.gov.uk/downloads/file/2009/annual_monitorin
g_report_200910
Dec-10
2002-2024
Shropshire Council
http://www.shropshire.gov.uk/planning.nsf/viewAttachments/EWET
-8C4CU5/$file/shropshire-annual-monitoring-report-2009.pdf
08/09
2003-2025
Solihull MBC
http://www.solihull.gov.uk/Attachments/amr_2009.pdf
08/09
2001-2025
South Staffordshire
DC
http://www.sstaffs.gov.uk/Files/SSDC%20AMR%20FINAL%20200
8-2009.pdf
08/09
2006-2025

NTEM 62 Guidance
11642097

Local Planning
Authority
Website
Document
Date
Projection
years
Stafford BC
http://www.staffordbc.gov.uk/live/Documents/Forward%20Planning
/LDF/AMR-2009---10.pdf
09/10
2001-2020
Staffordshire
Moorlands DC
http://www.staffsmoorlands.gov.uk/downloads/Staffordshire_Moorl
ands_Final_AMR_21_12_10.pdf
Nov-10
2001-2025
Stoke on Trent
Council
http://www.stoke.gov.uk/ccm/cms-
service/stream/asset/?asset_id=2296148
09/10
2006-2025
Stratford on Avon
DC
http://www.stratford.gov.uk/files/seealsodocs/10535/Annual%20M
onitoring%20Report%202009.pdf
Dec-09
2001-2025
Tamworth BC
http://www.tamworth.gov.uk/pdf/Annual_Monitoring_Report_2010.
pdf
Dec-10
2006-2025
Telford and Wrekin
Council
http://www.telford.gov.uk/downloads/AMR_2010.pdf
09/10
2006-2025
Walsall
http://www.walsall.gov.uk/annual_monitoring_report_2010.pdf
Dec-10
2004-2025
Warwick DC
http://www.warwickdc.gov.uk/NR/rdonlyres/2D4BCE31-FA3D-
45F4-A0AA-1EBA8A8EF163/0/AMR2010withcovers.pdf
Dec-10
2001-2025
Wolverhampton
http://www.wolverhampton.gov.uk/NR/rdonlyres/F21EABF2-FF7E-
4642-8862-3D40E8A0E167/0/WolverhamptonAMR2010Final.pdf
Dec-10
2001-2025
Worcester Council
http://www.malvernhills.gov.uk/cms/pdf/SWAMR%202010%20(fina
l).pdf
Dec-10
2001-2015
Wychavon
http://www.malvernhills.gov.uk/cms/pdf/SWAMR%202010%20(fina
l).pdf
Dec-10
2002-2025
Wyre Forest DC
http://www.wyreforestdc.gov.uk/cms/non-lgnl-pages/planning-and-
regulatory-servic/planning-policy/monitoring-reports.aspx
Dec-10
2004-2025
Barnsley MBC
http://www.barnsley.gov.uk/amr-2009-1
AMR
2008/2009
to 26/27
Bradford DC
http://www.bradford.gov.uk/NR/rdonlyres/A9068B78-9007-42FE-
8BAB-7F35D9A0276A/0/AMRDOCUMENTDEC2010.pdf
Dec-10
None
provided
Calderdale MBC
http://www.calderdale.gov.uk/environment/planning/development-
framework/monitoring-report09.pdf
AMR
2008/2009
to 25/26
Craven DC
http://www.cravendc.gov.uk/NR/rdonlyres/0B3E7E70-FF78-4AFF-
AD78-638AD0D0E004/4674/FinalAMR0910forwebsite.pdf
Dec-10
to 25/26
Doncaster MBC
http://www.doncaster.gov.uk/Images/Annual%20Monitoring%20Re
port%202010_tcm2-75715.pdf
Dec-10
to 25/26
East Riding of
Yorkshire Council
http://www.eastriding.gov.uk/corp-
docs/forwardplanning/docs/monitoring/amr/AMR2010.pdf
Dec-10
to 25/26
Hambleton DC
http://www.hambleton.gov.uk/Hambleton%20District%20Council/Pl
anning/LDF/AMR2010.pdf
Dec-10
to 25/26
Harrogate BC
http://www.harrogate.gov.uk/pdf/DS-P-
LDF_AnnualMonitoringReport_09_B.pdf
AMR
2008/2009
to 23/24
Kingston upon Hull
http://hullcc-
consult.limehouse.co.uk/portal/planning/amr/annual_monitoring_re
port_2009?pointId=625831
AMR
2008/2009
to 25/26
Kirklees MBC
http://www.kirklees.gov.uk/business/planning/LDF/pdf/AMR2009-
10final.pdf
Dec-10
to 27/28
Leeds Council
http://www.leeds.gov.uk/files/Internet2007/2009/52/leeds%20ldf%
20amr%202009%20updated%20for%20publication.pdf
AMR
2008/2009
to 25/26
North East
Lincolnshire BC
http://www.nelincs.gov.uk/GetAsset.aspx?id=fAA0ADkAMAA0AH
wAfABUAHIAdQBlAHwAfAAwAHwA0
Dec-10
to 26/26
North Lincolnshire
Council
http://www.planning.northlincs.gov.uk/PlanningReports/AMR/AMR
2009.pdf
Dec-09
2025/26

11642097
NTEM 62 Guidance

Local Planning
Authority
Website
Document
Date
Projection
years
North York Moors
NP
http://www.northyorkmoors.org.uk/uploads/publication/10161.pdf
Dec-09
No
projection
Richmondshire DC
http://www.richmondshire.gov.uk/planning/planning-policy/local-
development-framework/annualmonitoringreport.aspx
2009
See note.
Rotherham MBC
http://www.rotherham.gov.uk/downloads/file/4386/annual_monitori
ng_report_2010
Dec-10
2025/26
Ryedale DC
http://extranet.ryedale.gov.uk/PDF/Ryedale%20AMR%202009.pdf
Dec-09
2020/21
Scarborough BC
http://www.scarborough.gov.uk/pdf/AMR%202010%20FINAL_test.
pdf
Dec-10
2003-2023
Selby DC
http://www.selby.gov.uk/upload/FINAL_DRAFT_AMR_2009-10.pdf
09/10
2001-2025
Sheffield Council
http://www.sheffield.gov.uk/planning-and-city-
development/planning-documents/sdf/sdf-annual-monitoring-report
Dec-09
2004-2025
Wakefield MDC
http://www.wakefield.gov.uk/NR/rdonlyres/77726D30-0EB3-4703-
9672-71EFBFFFBF41/0/LDF_AnnualMonitoringReport2010.pdf
Dec-10
2002-2025
York Council
http://www.york.gov.uk/content/45053/xx-xxxx-xxxx/Local_develo
pment_framework/200809AMR
Dec-09
2003-2014
Amber Valley BC
http://www.ambervalley.gov.uk/NR/rdonlyres/CEDA8A07-5FAA-
4577-B846-F658E6754542/0/AMR20092010.pdf
Dec-10
2009/10 -
2025/6
Ashfield DC
http://www.ashfield-dc.gov.uk/ccm/cms-
service/stream/asset/?asset_id=12689038&
Dec-10
2009/10 -
2025/6
Bassetlaw DC
http://www.bassetlaw.gov.uk/pdf/Final%20AMR%202009.pdf
Dec-09
to 2014/15
Blaby DC
http://idocs.blaby.gov.uk/external/planning-
building/planning/annual-monitoring-report-2009.pdf
Dec-09
to 2025/6
Bolsover DC
http://www.bolsover.gov.uk/images/pdfs/Planning_Policy/Annual_
Monitoring_Report/submission_version_5th_%20amr.pdf
Dec-09
to 2025/6
Boston BC
http://www.boston.gov.uk/index2.php?option=com_docman&task=
doc_view&gid=2018&Itemid=3276
09/10
9/10 -
15/16
Broxtowe BC
http://www.broxtowe.gov.uk/CHttpHandler.ashx?id=20468&p=0
Dec-10

Charnwood BC
http://www.charnwood.gov.uk/files/documents/annual_monitoring_
report_2009_2010/ANNUAL%20MONITORING%20REPORT%20
2009-10.pdf
Dec-10

Chesterfield BC
http://www.chesterfield.gov.uk/Site/1/Documents/Environment/Loc
al%20Development%20Framework/Annual%20Monitoring%20Re
port/AMR6%20Submission%20document.pdf
Dec-10

Corby
http://www.nnjpu.org.uk/docs/AMR%202009-10%20-%20Final.pdf
Dec-10
to 20/21
Daventry
http://www.northampton.gov.uk/downloads/AMR2010.pdf
Dec-10
to 25/26
Derby Council
http://www.derby.gov.uk/NR/rdonlyres/61F3B8C0-2A0F-42CD-
9830-5341BF4C34D9/0/AMR_2010.pdf
Dec-10
to 25/26
Derbyshire Dales
DC
http://www.derbyshiredales.gov.uk/Images/Derbyshire%20Dales%
20District%20Counc3_tcm19-155488.pdf
Dec-10
to 25/26
East Lindsey DC
http://www.e-lindsey.gov.uk/NR/rdonlyres/022A9506-D73C-4253-
8836-E79E7E761D9A/0/AnnualMonitoringReport2009.pdf
AMR
2008/2009
to 15/16
East
Northamptonshire
http://www.nnjpu.org.uk/docs/AMR%202009-10%20-%20Final.pdf
Dec-10
to 20/21
Erewash BC
http://www.erewashcouncil.com/ldf/files/EBC%20AMR6%20(2009-
10).pdf
Dec-10
2001-2025
Gedling BC
http://www.gedling.gov.uk/amr_2009-10.pdf
Dec-10

Harborough DC
http://www.harborough.gov.uk/downloads/AMR_2010_LDS_Updat
e_-_electronic_version.pdf
Dec-10
to 25/26

NTEM 62 Guidance
11642097

Local Planning
Authority
Website
Document
Date
Projection
years
High Peak BC
http://www.highpeak.gov.uk/planning/localframework/monitoringre
port_2008-2009.pdf
AMR
2008/2009
to 25/26
Hinckley and
Bosworth BC
http://www.hinckley-
bosworth.gov.uk/downloads/file/1729/annual_monitoring_report_2
009-10
Dec-10
to 25/26
Kettering BC
http://www.nnjpu.org.uk/docs/AMR%202009-10%20-%20Final.pdf
Dec-10
to 20/21
Leicester Council
http://www.leicester.gov.uk/EasySiteWeb/getresource.axd?AssetI
D=72305&type=full&servicetype=Attachment
Dec-10
to 25/26
Lincoln Council
http://www.ourcityourfuture.co.uk/doclib/State_Of_City_Report_Fin
al_2009.pdf
AMR
2008/2009
to 25/26
Mansfield DC
http://www.mansfield.gov.uk/CHttpHandler.ashx?id=2846&p=0
AMR
2008/2009
to 25/26
Melton BC
http://www.melton.gov.uk/pdf/Melton%20AMR%202010%20FINAL
.pdf
Dec-10
to 25/26
Newark and
Sherwood DC
http://www.newark-
sherwooddc.gov.uk/ppimageupload/holding/Image97790.PDF
Dec-10
to 25/26
North East
Derbyshire DC
http://www.ne-
derbyshire.gov.uk/Easysite/admin/AssetManager_ServeAsset.asp
AMR
2008/2009
to 25/26
North Kesteven
http://www.n-
kesteven.gov.uk/upload/public/attachments/1323/Annual_Monitori
ng_Report_2010.pdf
Dec-10
to 25/26
North West
Leicestershire DC
http://www.nwleics.gov.uk/files/documents/annual_monitoring_rep
ort_2010/Annual%20Monitoring%20Report%202010.pdf
Dec-10
to 25/26
Northampton BC
http://www.northampton.gov.uk/downloads/AMR2010.pdf
Dec-10
to 25/26
Nottingham Council
http://www.nottinghamcity.gov.uk/CHttpHandler.ashx?id=23517&p
=0
Dec-10
to 25/26
Oadby and Wigston
BC
http://www.oadby-
wigston.gov.uk/Home/Planning/Forward%20Plans/Local%20Devel
opment/AMR%2008-09%20Full.pdf
AMR
2008/2009
to 25/26
Peak NP
http://old.peakdistrict.gov.uk/ldfamr2008-09.pdf
08/09
2001-2023
Rushcliffe BC
http://www.rushcliffe.gov.uk/upload/public/attachments/287/Appen
dix_4_Trajectory_Figures_AMR_2010.pdf
Dec-10
to 25/26
Rutland UA
http://www.rutland.gov.uk/ppimageupload/Image97402.PDF
Dec-10
to 25/26
South Derbyshire
DC
http://www.south-derbys.gov.uk/Images/2010%20AMR_tcm21-
152905.pdf
Dec-10
to 25/26
South Holland DC
http://www.sholland.gov.uk/NR/rdonlyres/0E757839-3023-4690-
9C33-A2B947ECD268/0/AMR20092010.pdf
Dec-10
to 25/26
South Kesteven DC
http://www.southkesteven.gov.uk/CHttpHandler.ashx?id=4537&p=
0
Dec-10
to 25/26
South
Northamptonshire
http://www.northampton.gov.uk/downloads/AMR2010.pdf
Dec-10
to 25/26
Wellingborough
http://www.nnjpu.org.uk/docs/AMR%202009-10%20-%20Final.pdf
Dec-10
to 20/21
West Lindsey
http://www.west-
lindsey.gov.uk/upload/public/attachments/1170/West_Lindsey_Dis
trict_Council_2009_AMR.pdf
AMR
2008/2009
no
Projection

11642097
NTEM 62 Guidance

Planning documents for Wales
Local Planning
Authority
Website
Document
Date
Projection
years
Isle of Anglesey
http://www.anglesey.gov.uk/upload/public/attachments/50/Vision_
and_Main_Options.pdf
http://www.anglesey.gov.uk/upload/public/attachments/76/Chapter
_16_Housing.pdf
2006
2010-2016
Blaenau Gwent
http://www.blaenau-
gwent.gov.uk/documents/Documents_Environment/LDP_Draft_Pr
eferred_Strategy.pdf
2008
2006-2021
Bridgend
http://www.bridgend.gov.uk/web/groups/public/documents/report/0
57945.pdf
http://www.bridgend.gov.uk/BCBCUDP/english/text/text04.htm
2005
2001-2016
Caerphilly
http://www.caerphilly.gov.uk/pdf/Environment_Planning/LDP/writte
n-statement.pdf
Nov-10
2006-2021
Cardiff
http://www.cardiff.gov.uk/objview.asp?object_id=16560
http://www.cardiff.gov.uk/ObjView.asp?Object_ID=3844
2007
2006-2016
Carmarthenshire
http://www.cartoplus.co.uk/carmarthenshire/english/text/04_h_hou
sing.htm
2006
2001-2016
Ceredigion
http://www.ceredigion.gov.uk/utilities/action/act_download.cfm?me
diaid=23626
Dec-10
2007-2022
Conwy
http://www.conwy.gov.uk/upload/public/attachments/378/Conwy_D
eposit_LDP_ENGLISH.pdf
2009/2010
2007-2022
Denbighshire
http://denbighddms.wisshost.net/webfiles/Deposit/LDP%20final%2
0version%2023%20sep%20English%20low%20res.pdf
2009
2001-2022
Flintshire
http://www.flintshire.gov.uk/wps/wcm/connect/8c493800497bc02b
8068bfbfb73e2b74/UDP_DPPReport_Housing_Requirement.pdf?
MOD=AJPERES
2003
2001-2015
Gwynedd
http://www.cartogold.co.uk/gwynedd/text/english/05_social.html#h
Jul-09
2001-2016
Merthyr Tydfil
http://www.merthyr.gov.uk/NR/rdonlyres/04502615-243F-4432-
BBA5-0B8F4A472DCB/0/WrittenStatement.pdf
2008
2006-2021
Monmouthshire
http://www.monmouthshire.gov.uk/downloads/Preferred_Strategy_
Complete.pdf
http://www.monmouthshire.gov.uk/downloads/Part_II.pdf
2006
2001-2021
Neath Port Talbot
http://www.npt.gov.uk/PDF/udp_adopted_text.pdf
2008
2001-2016
Newport
http://www.newport.gov.uk/stellent/groups/public/documents/plans
_and_strategies/cont063489.pdf
2006
2001-2011
Pembrokeshire
http://www.pembrokeshire.gov.uk/objview.asp?object_id=5577&la
nguage=
http://www.pembrokeshire.gov.uk/content.asp?nav=109%2C141%
2C142&parent_directory_id=646
2006
2001-2021
Powys
http://www.powys.gov.uk/uploads/media/Written_statement_final_
web_en_04.pdf
Mar-10
2001-2016
Rhondda, Cynon,
Taff
http://www.rhondda-cynon-
taf.gov.uk/en/relateddocuments/publications/developmentplanning
/localdevelopmentplan2006-
2021/depositdraftlocaldevelopmentplan.pdf
2009
2006-2021
Swansea
http://www.swansea.gov.uk/media/pdf/8/5/UDP_Written_Statemen
t_Final_Version.pdf
Nov-08
2001-2016
Torfaen
http://test.torfaen.contensis.co.uk/EnvironmentAndPlanning/Planni
ng/ForwardPlanning/Publications/PreferredStrategy.pdf
2008
2006-2021
The Vale of
Glamorgan
http://www.valeofglamorgan.gov.uk/files/Living/Planning/Policy/UD
P/UDP.pdf
2007
2001-2026
Wrexham
http://www.wrexham.gov.uk/assets/pdfs/planning/udp/written_state
ment_e.pdf
http://www.wrexham.gov.uk/assets/pdfs/planning/ldp/deposit_docu
ments/reports/ldp_written_statement_deposit.pdf
2005
2001-2021

11642097
NTEM 62 Guidance

Appendix D Demographic Parameters

NTEM 62 Guidance
11642097

SUMMARY
There are several sets of assumptions that are required in the operation of the Scenario
Generator in addition to the base and forecast year inputs. These affect the way in
which population, households and employment are allocated to zones in forecast years.
The following base year parameters are required by the Scenario Generator:
 Minimum number of average adults per household
 Maximum number of average adults per household
 Weighting of population trends versus dwellings policy in allocation of households
(1=fully dwellings-led, 0=fully population-led, 0.5=evenly weighted)
 Maximum acceptable difference between households and dwellings
 Number of one person households suppressed per 2+ person households created
 Maximum allowable increase in occupancy rate
 Minimum allowable vacancy rate
 Maximum allowable rate of decrease in vacancy rate
 Proportion of population in communal establishments (by age and gender for the
study area)
 Ratio of jobs to workers (by sector, gender and working status for the study area)
 Expected number of people in each household type (by type, gender and life stage in
each district control area)
In addition, the following forecast parameters are required by the Scenario Generator:
 Proportion of workers by gender and working status that are in each life stage
 Proportion of excess households that relocate to other control areas where capacity
is exceeded
 Minimum acceptable employment rate by gender and age group
 Maximum acceptable employment rate by gender and age group
 Maximum acceptable change in employment rate by gender, age and working status

BASE YEAR PARAMETERS

Types of persons in households (S)
This parameter is required for each district control area to split the number of persons by
age and gender into household types (one person or two or more person households).
The data sources for the derivation of these parameters are:

11642097
NTEM 62 Guidance

Table D.1 Data sources for calculating parameter pi
Data source
Spatial scale
Description of use
Census
Table ST004
District, Unitary Authority
Count of people, by gender and age-group
Census
Table UV051
District, Unitary Authority
Count of households, occupied by 1-person
and 2+people
2001 SAR
Region
Proportion of people in each household
type, gender and age group

The Census data gives the total number of people in each type of household for each
control area and a cross-tabulation of gender against age group. This data is factored
up to mid-year level estimates to counter under-enumeration issues. This provides a
consistent control total for At region level, the 2001 SAR gives the number of sampled
individuals in each cross-category of gender/age/household size. The proportions from
the 2001 SAR are applied to the Census data down to the district level. These are
controlled to the Census totals in order to keep a consistent average household size.

Household/ Dwelling differential (\)
This parameter sets a maximum limit on the difference between the number of
households and the number of dwellings, ie how many more dwellings than households
there may be. This is at the Region level and offers a check that the data is not orders
of magnitude from expected values. Figure D.1 shows the difference in these ratios in
2001 for each region, taken from 2001 Census data. A value of 0.1 was assigned to this
parameter.
1.005
1.01
1.015
1.02
1.025
1.03
1.035
1.04
1.045
1.05
1.055
1.06
East Midlands
East
London
North East
North West
Scotland
South East
South West
Wales
West Midlands
Yorkshire and the
Humber

Figure D.1 Ratio of dwellings to households in each region, Source: 2001 Census

NTEM 62 Guidance
11642097

Minimum number of adults in households (Emin)
Although theoretically there are a very small number of zero-adult households in the
Census, this value can be assumed to be 1.

Maximum number of adults in households (Emax)
Figure D.2 shows that the average number of adults in each region varies between 1.75
and just over 1.9. The Emax variable required is for the regional level. Bearing in mind
the trend towards 1 person households, it is doubtful that this will ever go over an
average of two persons per household in any region. However, to cover the possibility
of this being the case when back-casting, this may exceed 2. For instance, Wales had
approximately 2.03 adults per household in 1991. Therefore Emax should be set to 3 to
catch any serious data problem that may occur when generating a scenario.
1.7
1.75
1.8
1.85
1.9
1.95
East Midlands
Eastern
London
North East
North West
South East
South West
Wales
West Midlands
Yorkshire and the
Humber

Figure D.2 Average number of adults per households, Source: 2001 Census

Occupancy rate (T)
Occupancy rate is the number of households that occupy household spaces (ie
dwellings). There are rare circumstances where more than one household can inhabit a
dwelling. A set of occupancy rates is required for each district control area. This is
derived from households from Census Table UV51 and dwellings from Census Table
UV55.
Communal residents (D)
The proportion of communal residents in the population by gender and age group is
required. The DCLG data set of population projections contains household population
estimates for 1991-2021, whilst the GAD data set contains total population estimates for
2003-2043. By subtracting one from the other for the overlap period of 2003-2021, the
estimated communal populations are derived, as shown in Table D.2. Apart from an
absolute dip from 2003-2006, this shows a solid rise from 1.4% to 4.2% (2006-21).

11642097
NTEM 62 Guidance

Table D.2 Total, household, and inferred communal population of England, 2003-
2021.
Year
Total population
(K)
Household
population (K)
Inferred communal
population (K)
Household population
as % of total
Inferred communal
population as % of total
2003
48,966
49,856
890
98.22%
1.78%
2006
49,783
50,483
700
98.61%
1.39%
2011
50,413
51,595
1,182
97.71%
2.29%
2016
51,076
52,770
1,694
96.79%
3.21%
2021
51,704
53,954
2,250
95.83%
4.17%

The input populations to the forecasts have the communal residents removed during the
Scenario Generator process, as it is the household population that is used.
The proportion of communal residents in each Region, gender and age group are taken
from the 2001 Census. The proportions used for each nominated age group can be
seen in Table D.3 and Table D.4. It is these figures that are input as the communal
residents’ parameters. Older age groups are broken down into more detail since this
group contains the majority of communal residents, as can be seen in Figure D.3. This
chart also shows a major difference between the 1991 and 2001 Census in the
treatment of students living in halls of residence. These are now enumerated in the
2001 Census as communal residents in their area of study whereas in 1991 they were
enumerated at the parental home.
Table D.3 Proportion of male population that is resident in communal
establishments, by region and age group.
Grouped ages
and regions
North
East
North
West
Yorks &
Humber
East
Midlands
West
Midlands
London +
SE + EE
South
West
0 to 14
0%
0%
0%
0%
0%
1%
1%
15 to 29
4%
4%
4%
5%
4%
5%
6%
30 to 64
1%
1%
1%
1%
1%
1%
1%
65 to 69
1%
1%
1%
1%
1%
1%
1%
70 to 74
2%
2%
1%
1%
1%
1%
1%
75 to 79
3%
3%
3%
2%
2%
2%
2%
80 to 84
6%
5%
5%
4%
4%
4%
4%
85 to 89
12%
11%
11%
10%
9%
8%
10%
90 to 94
23%
20%
19%
20%
17%
16%
21%
95 +
27%
27%
28%
28%
23%
24%
34%

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11642097

Table D.4 Proportion of female population that is resident in communal
establishments, by region and age group.
Grouped ages
and regions
North
East
North
West
Yorks &
Humber
East
Midlands
West
Midlands
London +
SE + EE
South
West
0 to 14
0%
0%
0%
0%
0%
0%
1%
15 to 29
3%
3%
3%
3%
3%
3%
4%
30 to 64
0%
0%
0%
0%
0%
0%
1%
65 to 69
1%
1%
1%
1%
1%
1%
1%
70 to 74
2%
2%
1%
1%
1%
1%
1%
75 to 79
4%
4%
4%
4%
3%
3%
3%
80 to 84
9%
9%
8%
8%
7%
7%
8%
85 to 89
19%
18%
18%
18%
16%
15%
18%
90 to 94
34%
34%
33%
34%
29%
28%
34%
95 +
48%
49%
49%
49%
44%
43%
51%

Communal residents in England, as a proportion of all residents
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
35.0%
40.0%
1991
2001

Figure D.3 Comparison of recorded communal residency in 1991 and 2001.

Dwelling vacancy levels (Q)
Census Table CAS048 splits the dwellings into occupied and unoccupied for the 2001
base year, with unoccupied further subdivided into second homes (including holiday
accommodation) and into vacant dwellings.

Dwellings not used as main residence (S)
In the previous version of TEMPRO, the information required for this parameter was the
number / proportion of dwellings that are not used as the main residence, i.e. used as a
holiday home, student accommodation, or second homes. A change will be realised in
TEMPRO v5 due to the different method recording of students between the 1991 and
2001 Censuses. In the 1991 Census, students are treated as being usually resident at
their main residence, ie their parental address. In 2001, students are treated as being
usually resident at their term-time address. This effectively decreases the apparent
amount of student accommodation as second homes and increases the number of
student communal residents where living in halls of residence.

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Census Table CAS048 provides the number of usually unoccupied dwellings, separated
into second and holidays homes or vacant dwellings.

Ratio of workers to jobs (J)
This parameter is responsible for converting jobs to workers. This is primarily due to the
fact that workers are not constrained to having one job and occasionally have second
jobs, intuitively more often in the case of part time workers. This parameter is also used
in the preparation of the base year data where jobs are required as input rather than
workers derived from the Census. A set of these parameters are required by
employment sector, gender and work type (full time/ part time) for each Region.
Jobs to workers are calculated using the 2001 EBS LA level dataset. This is by gender,
work type and EBS employment type and hence requires a match-up with the NTEM
employment types. The parameter required by the Scenario Generator is also required
by work type, ie full time or part time jobs. In the absence of satisfactory data, it was
estimated that 95% of those with second jobs will be part time workers, leaving 5% of full
time workers having second jobs.
FORECAST YEAR PARAMETERS
Minimum and maximum acceptable employment rate and change in employment rate
over time (Vmin, Vmax, Vˆ )
This parameter is used in the Scenario Generator to check that the employment rate lies
within a certain threshold. Where this threshold is breached, the program stops
generating the scenario. This prevents the model from falling outside acceptable levels.
The parameters are set for each gender and working age group.
The ONS definition of employment rate is “…the proportion of the working-age
population who are in employment”. The working age population comprises men aged
16-64 and women aged 16-59. The LFS definition of employment is anyone who does
at least one hour’s paid work in the week prior to their LFS interview, or has a job that
they are temporarily away from. Also included are people who do unpaid work in a
family business and people on Government-supported training schemes.
The previous maximum employment rate in TEMPRO 4.2 was 85%, citing Berkshire as
having the highest rate of around this total, while the national average struggled to
exceed 75%. A rate is required far in excess of the national average for those counties
that have higher than average rates. Clearly in this case differentiation by gender and
life stage is required as well. A similar method is employed to determine the new
parameter values.
Analysis done comparing EBS data with ONS population projections over time suggests
that males on average have higher rates of employment than females. Also, no one
county control area should exceed a 90% employment rate. Table D.5 shows the
parameters suggested for use in the Scenario Generator. It should be noted that these
are input by time period, although these default values should be practical in all cases.

NTEM 62 Guidance
11642097

Table D.5 Suggested minimum and maximum employment rates for all forecast
years
Gender
Age group
Minimum
Maximum
Female
16-29
50%
90%
Male
16-29
55%
90%
Female
30-64
55%
90%
Male
30-64
65%
90%

The maximum change in employment rate over a specified period is also required. A
similar analysis of trends over time in the change in employment rate indicates that for a
five year period, the maximum change in employment rate for any gender/ worker type
category is less than 3% (for female part time workers between 2006 and 2001). For the
Scenario Generator, a maximum change parameter of 5% has been input to cover all
reasonable cases. Where this is breached the generator will stop, indicating unrealistic
data issues.

Maximum allowable change in occupancy rate ('Tmax)
A factor is required to set the maximum rate at which this may change over the forecast
period length. Indications from the 1991 to 2001 inter-Censal trend show that a value of
0.5% more than adequately caters for each case. It is not anticipated that this rate will
differ significantly over time and therefore is fixed at this value.

Proportion of workers in each working age group (U)
This parameter determines the proportion within the working age groups (16-29 and 30-
64) that are of each gender and worker type combination. This is required for each
region. Worker type here is either full time or part time only.
The 2001 SAR allows cross tabulation of all the required fields to construct the
parameter for each region. The 2001 Census only counts those that are employed
below the age of 75 and above the age of 15. For information purposes workers in the
64-74 group have also been extracted from the 2001 SAR.
Table D.6 shows the proportion of workers expected in the working young and working
old groups by gender for each Region. These values include those aged 65 or greater,
entailing that the proportions do not sum to one.

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NTEM 62 Guidance

Table D.6 Proportion of workers within each working age group by gender, work
type and Region, 2001

Full Time
Part Time

Female
Male
Female
Male
Region
16-29
30-64
16-29
30-64
16-29
30-64
16-29
30-64
East Midlands
0.298
0.696
0.218
0.774
0.190
0.792
0.387
0.528
North East
0.294
0.701
0.215
0.778
0.208
0.778
0.417
0.538
North West
0.298
0.696
0.224
0.767
0.206
0.774
0.391
0.537
Scotland
0.290
0.703
0.226
0.765
0.227
0.754
0.450
0.473
South West
0.293
0.697
0.219
0.770
0.182
0.791
0.349
0.543
Wales
0.275
0.716
0.225
0.761
0.208
0.772
0.365
0.564
West Midlands
0.298
0.696
0.222
0.768
0.195
0.782
0.392
0.519
Wider South East
0.325
0.669
0.237
0.753
0.193
0.780
0.364
0.538
Yorkshire and the
Humber
0.301
0.694
0.227
0.764
0.197
0.787
0.384
0.545

Over time the proportion of workers aged 65 or greater is expected to increase. This is
due to an ageing population and the potential increase in retirement age in forecast
years. Therefore the rho parameters are adjusted downwards slightly over time to
reflect a slightly greater proportion of the workforce being outside of the designated
working age of 16-64.
In NTEM 5.4, Rho parameters were revised in 2001 to exclude communal
establishments from the population.

Proportion of excess households that relocate (O)
Where household allocation within a control area exceeds housing supply, a proportion
of those willing to live in that control area will be dispersed to other control areas with
excess dwelling supply within that study area. This proportion is determined by this
parameter and is specific to each forecast year. This value is set to 0.5, causing half of
excess households to relocate to other districts where housing demand is unfulfilled in
the target district. The remainder will be suppressed or in the case of one person
households may coalesce to become multi-person households (see parameter P).

Dwelling/ population policy-led development (])
This parameter determines in forecast years how much the process of the allocation of
households across control areas will follow the number of available dwellings or the
projected trend in population. A global value of 0.75 is fixed presently, erring more
towards policy based forecasts than past trends. This If this value is set to 1, this
indicates total dependency on dwellings in relocating future households and zero
represents a complete following of the population projections.

NTEM 62 Guidance
11642097

Suppressed single person households that convert to multiple person households (P)
This is a global parameter that determines the number of one person suppressed
households that are reformed as multi-person households. This occurs where
households that wish to locate in a control area are not able to due to restricted dwelling
supply. This models the real-world case where people elect to live with others or move
into a parental home, etc, where they cannot find a suitable dwelling on their own.
This parameter is set to 3, indicating that every third single person household will
convert to multi-person households.

11642097
NTEM 62 Guidance

Appendix E
Mathematical Specification of
Methodology

NTEM 62 Guidance
11642097

NOTATION / TERMINOLOGY
The main variables and their definitions are shown in Table E.1 which also identifies
those variables which are new or differ in their definition from the MVA / DCS
specification.
Table E.1 Quantity variables
Variable
Description
E
Employment (= jobs including the self employed)
H
Households
P
Population (people) living in households
(ie excludes those living in communal establishments)
P = W + N
Pˆ
Total population (input) – includes those in communal establishments
W
Workers (working population) - full time/ part time - definition
changed
N
Non workers (ie students and others) – new variable
D
Dwellings - new variable
S
Household spaces - new variable

The subscripts attached to the variables denote the time and space applicable to the
value while the superscripts denote categories / types of the variables. Forecasts will be
for current year and scenario t for the period p starting from a previous year and
scenario t-1.
Table E.2 Subscripts – time and place
Variable
Description
i
NTEM zone
c
Control area for forecasting tools - an aggregation of i for study area R at
which the forecasts are controlled to exogenous projections.
Existing tool
c=county level
Proposed tool
H
c =district level for home / residential variables – all
variables except E
E
c =county level for employment / workplace variables E
B
Balancing Area, i  B (notation changed from MVA version)
R
Study area to be processed = Region in most cases equivalent to the term
“Definition” in the existing tool.
t
Forecast scenario
If forecast scenario is t, previous forecast scenario is (t-1)
p
Forecast period from scenario (t-1) to scenario t

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NTEM 62 Guidance

Table E.3 Superscripts – categories / dimensions
Superscript
On var:
Category / dimension
a
E
Employment sector = trip attractor type as defined in Section
2.7
g
P, W
Gender (Male, Female, Both –children)
h
H
Modelled household types – 1 and 2+ person hholds
l
P, W
Modelled age bands (<16, 16 – 29, 30 – 64, 65+) (l for life
stage)
m
P
Age (input bands / years) of input data (m  l)
w
P, W, E
Working status - only relevant for 16-29 and 30-64 age groups
On P, w = F – full time, P – part time, S – students, O – other
On W and E, w = F – full time or P – part time
On N, w = S – students, O – other

Other notation / assumptions applied are:
n
used to denote iteration n in an iterative procedure
^
used to identify user specified input data / parameters which may be internally
adjusted during the forecasting process
~
used to denote intermediate values for variables / parameters
(1), (2) used in balancing process to denote many intermediate estimates of a variable
Final forecasts / estimates have no hieroglyphics.

For each of the main variables there are a set of type categories as follows:

Employment by sector, gender and hours (full / part time),
agw
ti
E


Population by gender, age and working status,
glw
tiP


Households by size,
h
ti
H

PARAMTER DEFINITIONS

gm
R
D

the proportion of the population within a given gender and age group
residing in communal establishments in study area (Region) R.

max
min,E
E

acceptable range for number of adults per household in study
area

Eˆ
minimum number of persons allowed per 2+ person household

\
acceptable scale of difference in ratio of households to dwellings in
study area (eg 0.25 means within ±25%)

NTEM 62 Guidance
11642097


cT
the occupancy rate (household spaces per dwelling) in control area c in
2001 starting year

max
T
'
the maximum allowable increase in occupancy rate (households per
dwelling) from the base / starting values

c
X
the vacancy rate in control area c in 2001 starting year

min
X

the minimum allowable vacancy rate

F
the proportion of the vacancy rate from the previous scenario that the
vacancy rate in the present scenario may fall to.

Y
c
S
the number of household spaces in the control area c otherwise
occupied (ie not vacant and not occupied by households – eg holiday
homes) in 2001 starting year

]
proportion of household location that is dwelling / policy led rather than
based on population trends

P
determines the number of one person (type 1) suppressed households
that are reformed as multi person households (type 2)

hgl
c
S

is the expected number of persons of type gl in household type h in
control area c, from 2001 Census (SARs plus standard tables).

agw
R
J

ratio within employment sector a of workers of gender g and working
status w = F or P, to jobs (w=S and O irrelevant here as they are non-
workers).

POPULATION AND HOUSEHOLD TOTALS FOR STUDY AREA (REGION)
Initial estimate of total population is taken as:

¦


R
c
gl
tc
gl
tR
P
P
~
~
and

¦



l
m
gm
R
gm
tc
gl
tc
P
P
D
1
ˆ
~
and c  R
(Eq 1)
where
gm
tc
Pˆ

is the input population by gender g and age m for the control area c of
study area R in scenario t

gm
R
D

is the assumed proportion of the population in age group m of gender
g residing in communal establishments in study area R.

Initial estimate of total households is taken as:

¦

h
h
tR
tR
H
H
ˆ
~

(Eq 2)

11642097
NTEM 62 Guidance

JOBS AND WORKERS TOTALS FOR STUDY AREA (REGION)
A total number of jobs (employment) at the County (control area) level in each forecast
year is provided as an input from the EBS data set. This information can be used to
scale the jobs from the previous scenario which are then aggregated to give the study
area totals.

¦
¸
¸
¹
·
¨
¨
©
§
¸
¸
¹
·
¨
¨
©
§
¸
¸
¹
·
¨
¨
©
§







agw
agw
c
t
agw
tc
agw
c
t
agw
c
t
agw
tc
agw
c
t
c
t
tc
c
t
agw
tc
E
E
E
E
E
E
E
E
E
E
)
001
.0,
ˆ
max(
ˆ
)
001
.0,
ˆ
max(
ˆ
ˆ
ˆ
~
1
1
1
1
1
1

where
¦

agw
agw
tc
tc
Eˆ
Eˆ
and
¦


R
c
agw
tc
agw
tR
E
E
~
~

(Eq 3)
A set of factors are derived to relate the employment measured in units of jobs to the
population measured in units of persons in employment. This allows the derivation of
the number of workers as follows:

¦

a
agw
tR
agw
R
glw
tR
glw
tR
E
W
~
J
U

(Eq 4)
where
agw
tR
E~

is the initial estimate of employment by sector a, gender g and
working status w, for the study area R in year t from Eq 3.

agw
R
J

is the assumed ratio of workers of gender g and working status w to
jobs in employment sector a (stored parameter table that could be
modified occasionally).

glw
tR
U

is the proportion of workers by gender and working status who are in
the working age groups

CONTROL TOTAL CHECKS
The relationship between the adult population and households is checked to ensure that
the average number of adults (in this case aged 16+) per household is acceptable.

max
tR
child
l,
g
gl
tR
min
H~
P~
E
E
d
d
¦
z
where
1
t
min
E
and
min
max
E
E
!

(Eq 5a)
With declining household sizes through time, a second check is prudent. This check
calculates the average number of persons per 2+ person household for the study area
as a whole.

Eˆ
Hˆ
Hˆ
P~
h
tR
h
tR
l,
g
gl
tR
d


¦
2
1
where
2
t
Eˆ
(specified by user)
(Eq 5b)

NTEM 62 Guidance
11642097

The workforce required to satisfy the employment forecasts should also be compared
with the potential workers available from the population forecasts.
gl
max
,t
gl
tR
w
glw
tR
gl
min
,t
P~
W
V
V
d
d ¦
where
1
0

gl
t
gl
t
max
,
min
,
V
V

(Eq 6)
Ratio of workers to jobs: ¦
¦
agw
agw
tR
glw
glw
tR
E
W
~

(Eq 7)
The forecast number of households is checked to ensure that it will fit within the forecast
development of dwellings.

>
@ ¦
¦





'


R
c
Y
c
R
c
c
t
c
tc
tR
S
D
S
F
X
X
T
T
1
min
max
max
,
max
1

(Eq 8)

where

c
t 1

X
is the vacancy rate obtained from the previous scenario and

c
c
t
X
X

0

input.
The ratio of household demand to the supply of space is checked against the bounds
specified and the result output to the log file for the user to check.

\
!

max
~
tR
tR
S
H
1

(Eq 9)

HOUSEHOLDS BY CONTROL AREA
The allocation of population and households to the control areas starts with trend based
forecasts and then adjusts these to reflect the dwelling allocations provided by the
regional planning bodies.
The first step is to disaggregate the study area household projections using input
population forecasts for the control areas. This assumes the change in household size
is uniform for all control areas within the study area, but that the starting pattern of
household sizes is retained.
The previous total household estimates are scaled by the input change in population and
controlled to the input Regional total.

¦
¦
¦
¦
¦






R
c
gl
gl
c
t
gl
gl
tc
c
t
gl
gl
c
t
gl
gl
tc
c
t
tR
tc
P
P
H
P
P
H
H
H
1
1
1
1
~
~
~
1

(Eq 10a)

These households must then be split into those with one person (h=1) and those with
two or more persons (h=2).

11642097
NTEM 62 Guidance

The input household size parameters for the 2+ person households (h=2) are first
adjusted in each control area to reflect the input household forecasts by size. Those for
1 person households remain unchanged. Those for 2+ person households are scaled
based on the change in input data. The lower bound of
2
t
Eˆ
is also applied to the 2+
person household size parameters.

gl
h
c
gl
h
tc
1
1

S
S

gl
h
c
tc
gl
h
tc
A
2
2

S
S
and

E
S
ˆ
gl
gl
h
tc
t
¦
2

The value of the adjustment factor
tc
A is calculated iteratively with estimates of the
number of 2+ person households (h=2) as follows:

¸
¸
¸
¹
·
¨
¨
¨
©
§

¦
¦




gl
gl
h
c
h
tR
R
c
n
h
tc
n
tc
n
tc
ˆ
,
Hˆ
H
A
max
A
2
2
2
1
1
S
E
and

¸¸
¹
·
¨¨
©
§



¦
¦

gl
gl
h
c
n
tc
tc
gl
gl
tc
n
h
tc
A
H
P
H
1
1
~
1
2
2
S

(Eq 10b)
The initial value for the scaling factor should be based on the change from the previous
number of persons in an average 2+ person household to the new average number of
persons in a 2+ person household. Again the lower bound should be applied. Thus:
starting with

¸
¸
¸
¸
¸
¸
¸
¹
·
¨
¨
¨
¨
¨
¨
¨
©
§
¸¸
¸
¹
·
¨¨
¨
©
§

¸¸
¸
¹
·
¨¨
¨
©
§


¦
¦
¦
¦
¦
¦










gl
gl
h
c
R
i
h
i)
t(
R
i
R
i
h
i)
t(
glw
glw
i)
t(
h
tR
h
tR
gl
gl
tR
tc
ˆ
,
H
H
P
Hˆ
Hˆ
P~
max
A
2
2
1
1
1
1
2
1
1
S
E

where
hgl
c
S

is the expected number of persons of type gl in household type h in
control area c
and
h
tR
Hˆ

is the number of households by type input by the user.

tc
H 1

is the estimated total number of households in the control area as
calculated by (Eq 10a)
This iterative process continues until
5
10
1
1


u
d

n
i
1
n
i
A
A
.
Once

2
1

h
tc
H
has been obtained from this iterative process, the number of 1 person
households is obtained by subtraction:

2
1
1
1
1



h
tc
tc
h
tc
H
H
H

(Eq 10c)
In reality the change in dwellings supply will affect the distribution of households. An
allocation of households purely based on the change in dwellings would be:

NTEM 62 Guidance
11642097

If

0
1
!
'


pR
h
R
t
h
tR
D
H
Hˆ
(ie dwellings and households are forecast to move in the same
direction) then:

pR
pc
h
R
t
h
tR
h
c
t
h
tc
D
D
H
H
H
H
'
'





1
1
2
ˆ

where

c
t
tc
pc
D
D
D
1



'
and
¦

'

'
R
c
pc
pR
D
D

(Eq 11)
otherwise

h
R
t
h
c
t
h
R
t
h
tR
h
c
t
h
tc
H
H
H
Hˆ
H
H
1
1
1
1
2







In practice the pattern of households is likely to be influenced by a mixture of trends and
new developments so a combination of the above two approaches seems appropriate:

h
tc
h
tc
h
tc
H
H
H
2
1
1
]
]



~

(Eq 12)
In the absence of any data to determine the mix, the starting assumption is that
75
.0

]

Finally it is necessary to evaluate whether there is an implied excess household demand
over the supply of space and then if appropriate to reallocate the household demand
across the control areas within the study area or to suppress excess demand.
The number of household spaces using the initial vacancy rates and occupancy rates is:

Y
c
t
c
c
tc
tc
S
D
S



1
1 X
T

(Eq 13)
The maximum number of household spaces available in each control area can be
calculated (as seen for the study area in eq 8) as:

>
@
Y
c
t
c
c
tc
tc
S
D
S


'


 F
X
X
T
T
1
min
max
max
,
max
1

(Eq 14)
where:
 the base year occupancy rate (=household spaces / dwellings)
c
T in control area c
can change by a maximum amount
max
T
'

 the vacancy rate obtained in the previous scenario

1

t
c
X
in control area c can
decrease by a maximum proportion F down to a lower bound
min
X
(1%) and
c
c
X
X

0


Y
c
S is the number of household spaces otherwise occupied (derived from the Census
and taken as fixed)

11642097
NTEM 62 Guidance

The adjusted vacancy rate for the scenario (required for future dependent scenarios) is
calculated as:

¸¸
¹
·
¨¨
©
§
¸¸
¹
·
¨¨
©
§





c
tc
tc
tc
t
c
t
c
ct
D
S
H
T
X
F
X
X
X
1
1
min
,
,
max

(Eq 15)
where
tc
H is output by Eq 20
The housing pressure is then calculated as:

max
~
tc
tc
tc
S
H

HPressure

(Eq 16)
If any control area in the study area has excess households, ie
1
!
max
~
tc
tc
S
H
for any c, then
identify spare capacity and reallocate a proportion of the excess households between
the control areas within the study area based on the capacity available

Excess households:
>
@
0,
~
max
~
max
tc
tc
tc
S
H 

X
and
¦


R
c
tc
tR
X
X
~
~

(Eq 17)

Capacity available:
>
@
0,
~
max
max
tc
tc
H
S


tc
C
and
¦


R
c
tc
tR
C
C

(Eq 18)
The user may specify whether all excess households are prepared to relocate within the
study area or whether only a proportion of them will move – in which case the remainder
will be suppressed. If there is insufficient capacity even those identified as willing to
relocate will be suppressed. On this basis the revised estimates of households in each
control area would be:
Households by control area:

¸¸
¹
·
¨¨
©
§



tR
tc
tR
tR
t
tc
tc
tc
C
C
X
X
H
H
C
,
~
min
~
~
O

(Eq 19)
Where:
tO is the proportion of households willing to move to other parts of the study
area. When
1

tO
, this will lead to a reduction in the number of households from that in
the input data. Without an empirical basis for this proportion, initially assume that
5
0.

tO
(ie 50%).
In practice we need to obtain revised household totals by type in each control area.
Thus the types of household being suppressed and relocating need to be estimated.
It is likely that the inadequate space will impact differently on the different household
types and as a result the suppression of households might be expected to alter the mix
of household types in the study area. On this basis the updated household forecasts by
household type for each control area are estimated as:
For household type 1:

¸¸
¹
·
¨¨
©
§
¸
¸
¹
·
¨
¨
©
§
¸¸
¹
·
¨¨
©
§
¸¸
¹
·
¨¨
©
§

¸¸
¹
·
¨¨
©
§
¸¸
¹
·
¨¨
©
§





¦

tR
tc
c
tc
h
tc
tc
t
tR
t
tR
t
t
tc
h
tc
tc
h
tc
h
tc
C
C
H~
H~
X~
,
X~
C
min
H~
H~
X~
H~
H
1
1
1
1
1
1
1
O
O
P
P
O
O

NTEM 62 Guidance
11642097

And for household type 2:

¸¸
¹
·
¨¨
©
§
¸¸
¹
·
¨¨
©
§
¸¸
¹
·
¨¨
©
§

¸¸
¹
·
¨¨
©
§





¦

tR
tc
c
tc
h
tc
tc
t
tR
t
tR
tc
h
tc
tc
t
tc
h
tc
tc
h
tc
h
tc
C
C
H
H
X
X
C
H
H
X
H
H
X
H
H
~
~
~
1,
~
min
~
~
1
1
~
1
~
~
~
~
2
1
2
2
2
O
O
P
O

(Eq 20)
where
h
tc
H~ is the number of households from equation 12, and
P determines the number suppressed households that are reformed as
household type 2. If P =4, then for every 4 single person households
suppressed, 1 multi-person household is formed. Assume P =4 initially as this
is consistent with existing policy led forecasts.
This will work so long as
O
P
P


d
1
tc
tc
H~
X~
, otherwise more 1 person households will be
suppressed than exist . In this exceptional case the program will terminate with an error.
The second term in the equations above is the proportion of the excess that is to be
reallocated to other control areas with spare capacity. The third term is the remaining
proportion of the excess that are suppressed by altering the household formation rates.
The fourth term is the additional households being reallocated to the control area.

The following summary of adjustments made is recorded to the log file:

Excess households identified:

¸¸
¹
·
¨¨
©
§
¸¸
¹
·
¨¨
©
§



¸¸
¹
·
¨¨
©
§






¦
¦
¦
tc
h
tc
R
c
tc
t
R
c
tc
h
tc
tc
t
R
c
h
tc
H
H
X
H
H
X
X
~
~
~
1
1
~
~
~
1
1
1
P
P
O
O
and.

¦
¦
¦






¸¸
¹
·
¨¨
©
§
¸¸
¹
·
¨¨
©
§



¸¸
¹
·
¨¨
©
§

R
c
tc
h
tc
tc
t
R
c
tc
h
tc
tc
R
c
h
tc
H
H
X
H
H
X
X
~
~
~
1
1
1
~
~
~
1
2
2
P
O


Of which

¦



R
c
h
tc
h
tc
H
H
1
1
~
and

¦



R
c
h
tc
h
tc
H
H
2
2
~
were suppressed; and


¦
¦






R
c
h
tc
h
tc
R
c
h
tc
H
H
X
1
1
1
~
and

¦
¦






R
c
h
tc
h
tc
R
c
h
tc
H
H
X
2
2
2
~
were
reallocated.

POPULATION BY CONTROL AREA
The trend based forecast population is an input for each control area defined. The
household forecasts are adjusted to take account of these population trends, (optionally)
the expected change in dwellings and to alleviate housing pressure. Since there is
some reallocation of households amongst the control areas within the study area, then
there should be an associated reallocation of population.
The input trend based population control totals are adjusted to reflect the household
adjustment. An estimate of the number of people by type in each control area to be

11642097
NTEM 62 Guidance

reallocated is calculated from the initial trend based household estimate

h
tc
H 1
and the
final household figures
h
tc
H
by type – taking into account how the household
reallocation is converted into persons.
The input household size parameters for the 2+ person households (h=2) were
previously adjusted in each control area to reflect the household forecasts (Eq 10b).
Those for 1 person households remain unchanged.
We know the number of households which are moved when converting from a trend to a
policy based forecast and we know those who move out of crowded control areas. So
by applying the updated persons per household, the population moving out is:

»
»
¼
º
«
«
¬
ª
¸¸
¹
·
¨¨
©
§
¸¸
¹
·
¨¨
©
§




1
0
1
,
X~
C
min
H~
H~
X~
,
H~
H
max
H
tR
t
tR
tc
h
tc
tc
t
h
tc
h
tc
h
tc
O
O
and
¦


c
h
tc
h
tR
H
H




h
tc
hgl
tc
hgl
tc
H
P
S
and
¦


c
hgl
tc
hgl
tR
P
P

The significant variations in persons per household between alternative control areas
within the study area (Region) should be taken into account when revising the population
forecasts. The average household size for those moving within the study area (Region)
is:



3
h
tR
hgl
tR
hgl
tR
H
P

The population moving into control areas is thus:

¸¸
¹
·
¨¨
©
§
¸¸
¹
·
¨¨
©
§
¸¸
¹
·
¨¨
©
§


3

¦

tR
tc
c
tc
h
tc
tc
t
tR
t
tR
h
tc
h
tc
hgl
tR
hgl
tc
C
C
H~
H~
X~
,
X~
C
min
,
H
H~
max
P
O
O
1
0
1

Having accounted for the changing household size to determine the number of people
moving into and out of each control area, the trend based population forecasts can be
adjusted as:
¦
¦

 


h
hgl
tc
h
hgl
tc
gl
tc
gl
tc
P
P
P
P
~

(Eq 21)

PROCESSING GROWTH FACTORS
The revised approach provides the user with two options:

Weights based factoring – where all input EGFs must be of the same sign. The
adjustment is then applied multiplicatively to ensure the control totals are met.
Thus the relative difference between the input EGFs is retained.

Trend based adjustments- where the input EGFs can be of mixed signs to
reflect growth and decline. In this case the absolute difference between the
EGFs is retained.

NTEM 62 Guidance
11642097

Adjustment to input EGFs for Weights based approach
This works in a similar way to previous version of TEMPRO. An initial adjustment is
made to the growth factors to achieve the required control area changes (note that for
employment the totals are for each sector a – summed over gender and working status
groups gw). The adjusted growth factors would be calculated as:

¦


'

c
i
a
i
t
a
pi
a
pc
a
pi
a
E
g
E
g
0
0
1 ,
ˆ
min
,
~
ˆ
max
pi
g
if
0
d
'
a
pc
E~

and

¦


'

c
i
a
i
t
a
pi
a
pc
a
pi
a
E
g
E
g
0
0
1 ,
ˆ
max
,
~
ˆ
max
pi
g
if
0
!
'
a
pc
E~

where

¦
¦




'
gw
c
i
a
i
t
agw
tc
a
pc
E
E
E
1
~
~

(in fact the ~ is redundant since
a
tc
a
tc
E
E
~

as it is only the gw split that is adjusted).
A further adjustment is then required at the time of application if any of the adjusted
growth factors within the control area is less than -1.
For households the equivalent equations are:

¦


'

c
i
i
t
H
pi
pc
H
pi
H
H
g
H
g
0
0
1 ,
ˆ
min
,
ˆ
max
pi
g
if
0
d
'
pc
H

and

¦


'

c
i
i
t
H
pi
pc
H
pi
H
H
g
H
g
0
0
1 ,
ˆ
max
,
ˆ
max
pi
g
if
0
!
'
pc
H

where

¦
¦




'
h
c
i
h
h
i
t
h
tc
pc
H
H
H
,
1
Adjustment to input EGFs for Trend based approach
This approach maintains the absolute difference between the EGFs and adds a constant
to each EGF to ensure the required control area change is required. There is no
differential treatment for mixed sign EGFs or where the sign of the input EGFs is
different to the control area change required. The only adjustment made is to prevent
negative volumes of activity in any zone in scenario t.
In this case the adjusted growth factors are calculated as:

¦
¦





'


c
i
a
i
t
c
i
a
i
t
a
pi
a
pc
a
pi
a
E
E
g
E
g
1
1
ˆ
ˆ
pi
g

For households the equivalent adjustment is:

11642097
NTEM 62 Guidance

¦
¦




'


c
i
i
t
i
t
H
pi
pc
H
pi
H
pi
H
H
g
H
g
g
1
1
ˆ
ˆ

POPULATION AND HOUSEHOLDS BY ZONE
The households in each control area are distributed to the zones within the control areas
based on expected growth factors which are exogenously specified.
So

0
1
1
,
max
H
pi
i
t
ti
g
H
H




However we require households by type in each zone which can be forecast as:

¦






c
i
i
H
pi
i
t
i
H
pi
i
t
tc
A
g
H
A
g
H
H
0
1
0
1
1
1
,
max
,
max
h
h
h
h
ti
H

(Eq 22)
Where the adjustment term
iA is required to ensure that the resulting number of
households in each zone matches the number of households that would be obtained by
applying the adjusted growth factors to the previous household total. This can be
achieved iteratively (maximum of 100 iterations) as:

¦ ¦
¸
¸
¸
¹
·
¨
¨
¨
©
§







h
c
i
n
i
H
pi
h
i
t
h
i
t
tc
i
t
A
g
H
H
H
H
0
1
1
1
1
,
max
h
1
n
iA

until
01
0
1
.
d


n
iA
1
n
iA
and where
1
0
iA

A first zonal estimate of the population by gender and age is obtained by estimating the
change in population by type from the change in households by type and then adding
the expected change to the previous population. Note that the
hgl
tc
S
values used here
are those obtained once the household forecasts have been determined.

¸
¹
·
¨
©
§



¦

0,
max
~
1
h
gl
i
1-t
gl
ti
h
h
i
t
ti
hgl
tc
H
H
P
P
S

(Eq 23)
The first estimate must then be adjusted to ensure the input control totals on population
are met. Thus the population by zone is obtained as:

¦


c
i
gl
ti
gl
tc
P
P
P
P
~
~gl
ti
gl
ti
to ensure
gl
tc
c
i
gl
ti
P
P

¦


(Eq 24)
The change in the zonal population from the previous scenario is:

NTEM 62 Guidance
11642097

gl
i
tP
P
P
1



'
gl
ti
gl
pi

(Eq 25)
The working status for the population within the zone is established as part of the
balancing process for the demand for workers.

EMPLOYMENT AND WORKERS BY ZONE
The allocation of the employment from the control areas to the zones is carried out using
two mechanisms:
 Following dwelling-led distribution of population
 Independent of changes in dwellings and population, following exogenous
employment growth by sector
The allocation of the population led employment is carried out using the same zonal
growth factors as the household information and is then adjusted to match the control
totals for the employment sector. Thus zonal employment is initially calculated as:

i
t
ti
agw
i
t
agw
ti
H
H
E
E
1
1
1



(Eq 26)
A single scalar adjustment is then applied to ensure the control totals are met

¦


c
i
agw
ti
agw
ti
agw
tc
agw
ti
E
E
E
E
1
1
~
~
so that ¦


c
i
agw
tc
agw
ti
E
E
~
~

(Eq 27)
where
agw
tc
E~

is the initial employment data for the control area from Eq 3.
The input growth factors are adjusted to estimate the zonal employment as:

¦






c
i
a
pi
agw
i
t
a
pi
agw
i
t
agw
tc
agw
ti
g
E
g
E
E
E
0
1
0
1
1
1
,
max
,
max
~
~

(Eq 28)

BALANCE WORKFORCE AND WORKERS
The balancing process is concerned primarily with the “working age” population (ie l =
16-29 and 30-64 age groups). It is assumed that the proportion of the retired (aged 65+)
population will not be of sufficient significance. The balancing process ensures that:

there are the correct number of workers of different types living the in the
balancing area for the jobs available; and

the number of workers in each zone does not exceed a specified maximum
proportion of the resident population.
The implied numbers of workers required in balancing area in the scenario given the
employment forecast are:

11642097
NTEM 62 Guidance

¦
¦

¸
¹
·
¨
©
§

B
i
a
agw
ti
agw
R
gw
l
tR
glw
tB
E
W
~
~
|
J
U
for w = F ,P
(Eq 29)
The change in the demand for workers from the previous scenario is:

glw
B
t
glw
tB
glw
pB
W
W
W
1



'
~
~
for w = F ,P
(Eq 30)
The changing employment profile through time should lead to a change in the gender
profile of the workforce in each employment sector. The Scenario Generator includes an
internal adjustment of the assumed gender and working status split by employment
sector.
This internal adjustment process uses the following key concepts:

Treating the previous population and the new population as two separate
groups

Treating declines before and completely independently to growth – logically
they can only be applied to the “previous” population groups.

Using “existing” profiles / employment rates from the previous scenario as an
initial estimate of workers

Calculating maximum possible numbers of workers by type

Adjusting profile of workers demanded so no maxima are breached

Determining how far it is necessary to move from the initial values towards the
maximum values in order to satisfy the demand.

DECREASES IN POPULATION AND / OR WORKERS
The first stage is to account for any decreases in workers due to decreases in the
population. This gives an intermediate population estimate:
If
0

'
gl
pi
P
then

¸¸
¹
·
¨¨
©
§
'





gl
i
t
glw
i
t
gl
pi
glw
i
t
glw
ti
P
P
P
P
P
1
1
1
1
otherwise

glw
i
t
glw
ti
P
P
1
1


(Eq 31)
and

¦


B
i
glw
ti
glw
tB
P
P
1
1

(Eq 32)
The second stage is required only if either (FT, PT or both) of the required workforce
categories w for the gender and age group gl in the scenario t is less than in the
previous scenario (t-1). In this case the number of workers of type w must be reduced
while retaining the total forecast population numbers by zone (from Eq 31). This is
achieved by simply scaling back the number of workers (by status) in each zone to
match the control area total. The non workers are then increased by the same volume
to retain the zonal population totals.
Thus if
0

'
w
pB
W
then :

NTEM 62 Guidance
11642097

¦


B
i
P
F
w
gl
ti
P
F
w
gl
tB
P
F
w
gl
ti
P
F
w
gl
ti
P
W
P
P
,
,
,
,
1
1
2
for w = F,P
(Eq 33)
At this stage the total population by gender and age remains as above so that:

¦

w
glw
ti
gl
ti
gl
ti
P
P
P
1
1
2

(Eq 34a)
with the non working population (not required at this stage) being the difference:

¦



P
F
w
P
F
w
gl
ti
gl
ti
O
S
w
gl
ti
P
P
P
,
,
,
2
2
2

(Eq 34b)
This gives an intermediate forecast of population by working status

glw
ti
P 2
accounting
for decreases in population and / or workers.
If
0
t
'
gl
pi
P
and
0
t
'
w
pB
W
then there are no decreases in population or workers. In
this case the starting population data are the previous scenario results. To simplify
notation for remaining balancing process, set

glw
i
t
glw
ti
P
P
1
2


.

INITIAL ESTIMATES OF WORKING STATUS PROFILE OF POPULATION
IN EACH ZONE
For this part it is proposed to treat the population in two groups:

The existing residents – from the previous scenario (year ) with any declines
already subtracted – a group for which the working status w is known:

glw
ti
P 2


The change in population in period p (from (t-1) to t):

gl
i
t
gl
ti
gl
pi
P
P
P
1



'
for
which the working status w has yet to be forecast.
An initial estimate of the population profile can be obtained by assuming the “new”
population takes on the same profile as the existing population:
Thus

¸¸
¹
·
¨¨
©
§
'


gl
ti
glw
ti
gl
pi
glw
ti
glw
ti
P
P
P
P
P
2
2
2
3
~
for w= F, P
(Eq 35)
If there is no existing population, the new population is split equally betwwn FT and PT
workers.
The adjusted initial estimate of workers for zone and the balancing area is then
calculated:

glw
ti
glw
ti
glw
ti
P
P
P
max
,
4
,
3
~
min
3

for w= F, P

¦


B
i
glw
ti
glw
tB
P
P
3
3
for w= F, P
(Eq 36)

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NTEM 62 Guidance

MAXIMUM SUPPLY OF WORKERS BY GENDER
For the new population the maximum rate is the specified ceiling rate. Thus:
Maximum employment rate for existing population in zone :

¸
¹
·
¨
©
§

'

¦

gl
w
glw
i
t
glw
gl
ti
max
1
max
max
,
,
min
V
V
V
V

(Eq 37)
Or

gl
gl
ti
max
max
,
V
V

when there is no existing data
Giving a maximum supply of employees:

gl
ti
gl
ti
gl
ti
P
P
2
2
max
,
max
,
V

(Eq 38)

and a possible maximum for each working status type of:

gl
ti
glw
glw
i
t
glw
ti
P
P
2
2
1
max
,
max
,
~
V
V
'




Although it may not be possible for both maxima by working status to be attained within
the overall ceiling rate.
Ie it is possible that

¦

w
glw
ti
gl
ti
P
P
max
,
max
,
~ 2
2
or

¦
z
w
glw
ti
gl
ti
P
P
max
,
max
,
~ 2
2
.
The two estimates

gl
ti
P
max
,
2
and

glw
ti
P
max
,
~ 2
are used in separate stages of the
remaining forecasting steps.
For the “new” population the maximum number of employees by gender is:
New population:

gl
t
gl
pi
gl
pi
P
P
max
,
max
,
V
'

'
3

(Eq 39)
Thus the maximum workers in zone:

gl
pi
gl
ti
gl
ti
P
P
P
max
,
max
,
max
,
3
2
3
'


(Eq 40)
Aggregating the results for all zones in the balancing area, gives a maximum number of
male and female workers by age group:
Maximum workers by gender in balancing area:

¦


B
i
gl
ti
gl
tB
P
P
max
,
max
,
3
3

(Eq 41)
The working status profile of the change in the demand for workers (ie the new demand)
is used to split the potential workers in the “new population” into the two working status
groups:

¦
'
'
'

'
w
glw
pB
glw
pB
gl
max
,
pi
glw
max
,
pi
,
W
max
,
W
max
P
P
1
1
3
3

(Eq 42)
The maximum number of workers by gender and working status available in the
population is then calculated as:

NTEM 62 Guidance
11642097

glw
pi
glw
ti
glw
ti
P
P
P
max
,
max
,
max
,
~
3
2
4
'


and

¦


B
i
glw
ti
glw
tB
P
P
max
,
max
,
4
4
(Eq 43)
Since the estimates of the maximum full and part time workers may sum to more than
the physical maximum a final adjustment is required.
To make this final adjustment the difference between the initial zonal estimates

glw
ti
P 3

and

glw
max
,
ti
P 4
are considered for the two cases w=F and w=P. For the working status
with the smallest difference between the initial estimate and the initial maximum the
maximum value is taken. For the other working status the maximum value is
recalculated to ensure the overall employment rate is not breached. Thus:
If

gl
max
,
ti
w
glw
max
,
ti
P
P
3
4
d
¦
, then

glw
max
,
ti
glw
max
,
ti
P
P
4
5

Else:

F
w
gl
max
,
ti
F
w
gl
max
,
ti
P
P

4
5
if

P
w
gl
ti
P
w
gl
max
,
ti
F
w
gl
ti
F
w
gl
max
,
ti
P
P
P
P




3
4
3
4

Else

P
w
gl
max
,
ti
gl
max
,
ti
F
w
gl
max
,
ti
P
P
P



4
3
5

and vice versa:

P
w
gl
max
,
ti
P
w
gl
max
,
ti
P
P

4
5
if

F
w
gl
ti
F
w
gl
max
,
ti
P
w
gl
ti
P
w
gl
max
,
ti
P
P
P
P




3
4
3
4

else

F
w
gl
max
,
ti
gl
max
,
ti
P
w
gl
max
,
ti
P
P
P



4
3
5

CHECKING / ADJUSTING THE GENDER PROFILE OF THE WORKERS
DEMANDED
Excess workers are:

0,
3
~
max
,
max
,
P
F
w
gl
tB
gl
tB
gl
tB
P
W
Z



and
¦

g
gl
tB
l
tB
Z
Z

(Eq 44)
Capacity for workers is:

0
3
,
~
max
,
max
,
gl
tB
P
F
w
gl
tB
gl
tB
W
P
Y


(Eq 45)
If
gl
tB
l
tB
Y
Z
!
, then modifying the gender profile will not completely resolve any mismatch
and in this case
gl
tB
l
tB
Y
Z

workers are lost from the working age population – assumed
to be filled by the over 65s and by increased double jobbing.
The final estimates of workforce by gender are:

l
tB
gl
tB
gl
tB
gl
tB
gl
tB
Z
Y
Z
W
W
,
min
~



(Eq 46)

CHECKING / ADJUSTING THE FULL-TIME / PART-TIME SPLIT OF
WORKERS
The next step is to finalise the working status of the population in the balancing area. To
start, it is assumed that the working status profile of the modified demand is the same as
for the initial demand. So the demand for workers by working status is:

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NTEM 62 Guidance

gl
tB
glw
tB
gl
tB
glw
tB
W
W
W
W
~
~

1

(Eq 47)
By this stage it is ensured that the demand for male and female workers can be
accommodated within the population supply. As before there is either an excess or
capacity calculated as:

Excess workers are:

0
5
1
,
P
W
max
Z
glw
max
,
tB
glw
tB
glw
tB


and
¦

w
glw
tB
gl
tB
Z
Z

(Eq 48)
Theoretical capacity for workers is:

0
1
5
,
W
P
max
Y
gl
tB
glw
max
,
tB
glw
tB


(Eq 49)
In practice there may be less capacity than indicated by equation 49 since the sum of
the maxima for the two working status groups could in theory be greater than the
available population. However since adjustments have already been made to the
workforce demanded by gender and age group, balanced estimates of workforce by
gender, age and working status can be calculated as:

gl
tB
glw
tB
glw
tB
glw
tB
glw
tB
Z
Y
Z
W
W
,
min



1

(Eq 50)
And a revised set of employment rates:

gl
tB
glw
tB
glw
tB
P
W

V

(Eq 51)

ALLOCATIONS OF WORKERS TO ZONES
Required data:
Workers to be accommodated in the balancing area are:
glw
tB
W
from equation 50.
Initial estimates of workers in the balancing area are

glw
tB
P 3
- from equation 36
Adjustment required to initial estimates to match demand:

glw
tB
glw
tB
P
W
3


The maximum number of workers in the balancing area is

gl
max
,
tB
P 3
from equation 41,
with separate estimates of the maximum number of workers by status

glw
max
,
tB
P 5
being
available from equation 43.
Maximum adjustment to initial estimates that is possible is then

glw
tB
glw
tB
P
P
3
4

max
,

There are two possible cases:

the workforce demanded is a greater proportion of the population than in the
previous scenario (expected to be the norm), ie

glw
tB
glw
tB
P
W
3
t
; or

NTEM 62 Guidance
11642097


the workforce demanded is a smaller proportion of the population than in the
previous scenario, ie

glw
tB
glw
tB
P
W
3

If the proportion of the population required to work is less than in the previous population
(ie

glw
tB
glw
tB
P
W
3

) the initial estimates can be scaled back and:

glw
ti
glw
tB
glw
tB
glw
ti
P
P
W
W
3
3

If the proportion of population working has increased then the employment rate lies
somewhere between the initial and the maximum employment rate:

glw
max
,
tB
glw
tB
glw
tB
P
W
P
5
3
d
d

and the proportion of the possible adjustment that is required is:

glw
tB
glw
max
,
tB
glw
tB
glw
tB
glw
tB
P
P
P
W
3
5
3



W

the zonal forecasts of workers by zone are calculated as:

glw
ti
glw
max
,
ti
glw
tB
glw
ti
glw
ti
glw
ti
P
P
P
P
W
3
5
3



W

These two cases can be combined into the single equation:

glw
ti
glw
max
,
ti
glw
tB
glw
ti
glw
tB
glw
tb
glw
ti
P
P
,
max
P
P
W
,
min
W
3
5
0
3
3
1


¸¸
¹
·
¨¨
©
§

W

(Eq 52)
with the total number of workers being
¦

w
glw
ti
gl
ti
W
W

NON WORKERS BY ZONE
The non working population is the difference between the workers and total population
and the split between students and others is assumed to remain as in the previous
scenario.

gl
i
t
glw
i
t
gl
ti
gl
ti
glw
ti
N
N
W
P
N
1
1




for w=S,O
(Eq 53)

UPDATE EMPLOYMENT FORECASTS FOR CHANGE IN WORKER
PROFILE
The input employment data by sector is obtained by aggregation across the gender and
working status groups:
¦

gw
agw
ti
a
ti
E
E
~

The revised split is then estimated as:

11642097
NTEM 62 Guidance

¦
¦
¦
¦
¦
¸
¹
·
¨
©
§

gw
l
glw
tB
l
glw
tB
agw
ti
l
glw
tB
l
glw
tB
agw
ti
a
ti
agw
ti
W
W
E
W
W
E
E
E
~
~
~
~

(Eq 54)

11642097
NTEM 62 Guidance

Appendix F
Employment Forecasting
Methodology

NTEM 62 Guidance
11642097

The material in this Appendix has been provided by the Department for Transport.
The NTEM Employment forecasting methodology was developed by the Department for
Transport as part of the development of NTEM 6.1 following a review of the exogenous
employment forecasts in earlier NTEM datasets. It has been modified slightly for
NTEM 6.2. The advantages of the new methodology are:

that it is constrained to employment growth consistent with HM Treasury
projections of Gross Domestic Product (GDP), and can easily be updated in line
with new GDP projections;

that it provides a stable forecast of employment in each employment sector.
Figure F.1 on the next page provides an overview of the steps involved in the process.
Broadly speaking:

steps 0 to 2 forecast total employment across all sectors, first nationally (based
on GDP), then progressively across smaller areas by combining population
projections and exogenous employment forecasts;

steps 3 to 5 forecast employment by sector, using population and GDP data
and growth rates based on historic data for a 24 year period.
The outputs from the methodology were carefully reviewed prior to inclusion in
NTEM 6.2 to ensure that the results were realistic. The methodology may be subject to
further updates in future versions of the NTEM dataset.

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NTEM 62 Guidance

1It should be noted that, strictly speaking, “Regional” means NTEM study area. This is consistent
with the definition of Regions in Great Britain, except for London, South East and East. These last
three regions are combined as a single study area, Wider South East.
Figure F.1 Overview of the NTEM 6.1 Employment Forecasting Method

Step 3:
Employment by sector,
National Level
Step 0:
Total Employment, National
Level
Step 1:
Total Employment, Regional
Level
1
Step 2:
Total Employment, Local
Authority Level
Step 4:
Employment by sector,
Regional Level
1
Step 5:
Employment by sector, Local
Authority Level
Exogenous Employment
forecasts,
Local Authority Level
Historic Employment by
Sector,
National Level
Historic Population by Age
Group,
National Level
GDP Projections,
National Level
Regional growth rates by
sector
Customer-based and
Employee-based growth
rates by sector
KEY to box styles:
Main steps
Data inputs
Subsidiary processes
Population projections,
Local Authority Level
Historic GDP growth,
National Level

NTEM 62 Guidance
11642097

GENERAL NOTATION
The following style of notation is used throughout:
Y
.
EN

is used to denote NTEM National Employment for year Y. This is
calculated in Step 0, using a simple calculation based on GDP forecasts.
Y
.
r
ER

is used to denote NTEM Regional Employment for Region r and Year Y.
This is calculated in Step 1, by combining exogenous employment
forecasts with trends in population growth.
Y
.
a
EA

is used to denote NTEM Employment by Local Authority, for Local
Authority a and Year Y. This is calculated in Step 2, using a trivial
extension of Step 1.
Y
.
s.
EN

is used to denote NTEM National Employment for year Y and sector s.
This is calculated in Step 3, by combining two alternative forecasts based
on different assumptions.
Y
.
s.r
ER

is used to denote NTEM Regional Employment for Region r, Year Y and
employment sector s. This is calculated in Step 4, and uses the iterative
proportional fitting (Furnessing) method, using
Y
.
s.
EN
and
Y
.
r
ER
as
constraints.
Y
.
s.a
EA

is used to denote NTEM Employment by Local Authority, for Local
Authority a, Year Y and employment sector s. This is calculated in Step 5,
and uses the iterative proportional fitting (Furnessing) method, using
Y
.
s.r
ER

and
Y
.
a
EA
as constraints.
The final NTEM employment forecasts are obtained by combining other employment
forecasts, based on different assumptions. These different employment forecasts are
represented as the first part of the superscript. The different forecasts used are as
follows:
E
Exogenous Employment
P
Employment based on working age Population
C
Customer-based forecast
W
Workforce-based forecast
L
Local growth forecast

In the event, the P (employment based on working age population) forecasts were not
used in NTEM 6.2, but the capability to use them has been retained should this be
needed in the future.

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NTEM 62 Guidance

So, for example:
Y
.
E
a
EA

represents Exogenous Employment (total over all sectors), for Local
Authority a and year Y.
1This can be aggregated into Regional level (
Y
.
E
r
ER

for each region r) or national level (
Y
.
E
EN
).
Y
.
P
r
ER

represents Population-based Employment (total over all sectors) for region
r and year Y.
Y
.
C
s.
EN

represents a Customer-based employment forecast for year Y and
employment sector s. This is only used at a national spatial level.
Y
.
W
s.
EN

represents a Workforce-based employment forecast for year Y and
employment sector s. This is only used at a national spatial level.
Y
.
L
s.r
ER

represents a Local-data-based employment forecast, for Region r, year Y
and employment sector s.
Y
.
L
s.a
EA

represents a Local-data-based employment forecast, for Local Authority a,
year Y and employment sector s.
It should be noted that, in fact, this calculation is carried out separately for employment
by gender (male/female) and work status (full time/ part time). However, for simplicity,
we have not included separate superscripts for these categories.
In the base year, 2001, the employment by gender, work status and, where appropriate,
by sector and Local Authority, is consistent with a common set of control totals, ie for
base year B:
B
.
P
B
.
E
B
.
EN
EN
EN

B
.
W
s.
B
.
C
s.
B
.
s.
EN
EN
EN

B
.
L
s.a
B
.
s.a
EA
EA

Each of the six steps (0 to 5) is described in turn. Other parameters required to carry out
the calculation are introduced as required.

1 This uses data supplied by Experian Business Strategies in 2009. In NTEM 6.2 this is
controlled to the 2001 data from TEMPRO 6.0, which was based on the 2001 Census.

NTEM 62 Guidance
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STEP 0: TOTAL EMPLOYMENT, NATIONAL LEVEL
Total employment for year Y, at a National level, is calculated from the previous year Y-1
by:
Y
.1
Y
.
E
N
1
Y
.
Y
.
g
EN
EN

 u

where:
Y
.1
Y
.
E
N
g


is the growth rate in employment from the previous year.
For years up to 2015, this is derived from historic data and Office for Budget
Responsibility forecasts. For years from 2016 onwards, this is calculated from long-term
GDP and productivity forecasts provided by the Treasury, using the following formula:
Y
.1
Y
.
R
N
Y
.1
Y
.
G
N
Y
.1
Y
.
E
N
g
g
g




Where:
Y
.
X
.
G
N
g

is growth in GDP (in real terms) between year X and year Y.
Y
.
X
.
R
N
g

is growth in productivity per worker between year X and year Y.
The standard Treasury assumption is that productivity per worker grows by 2% per year,
ie:
)
B
X
(
Y
.
X
.
R
N
)
02
.1(
g


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NTEM 62 Guidance

STEP 1: TOTAL EMPLOYMENT, REGIONAL (STUDY AREA) LEVEL
In Step 1, the total national employment
Y
.
EN
is disaggregated to produce total
employment by Region,
Y
.
r
ER
for each Region r
2.
The spatial split of employment requires an exogenous employment forecast
Y
.
E
r
ER
which is constructed with due consideration to the economic drivers of
employment.
3 However, in general, the sum of these forecasts across all regions will not
be the same as the total national employment calculated in Step 0, ie:
Y
.
N
r
Y
.
E
r
EN
ER
z
¦


whereas it is necessary that:
Y
.
N
r
Y
.
r
EN
ER

¦


In NTEM 6.2 we used a simple approach to adjust the exogenous forecast by applying a
global scaling factor, ie:
¦

u

N
r
Y
.
E
r
Y
.
Y
.
E
r
Y
.
r
ER
EN
ER
ER
,
However, we are aware that this approach can sometimes cause counterintuitive effects,
with some Regions switching from growth to decline if the global NTEM employment
total is very different to the global total for the exogenous forecast. The example on the
next page illustrates this point.
For NTEM 6.2, it was decided to use this simple approach on the grounds that the
following factor:
¦
N
r
Y
.
E
r
Y
.
ER
EN

remained very close to 1 (within the range 0.98 to 1.02) for all forecast years. However,
had this not been the case, we would have considered combining the exogenous
forecast with a second employment forecast based on growth in population aged 16 to
64, as was previously done in NTEM 6.1. Therefore, the employment forecasting
program retains this flexibility should it be required in the future. This can be specified
mathematically as follows:
)
ER
ER
(
ER
Y
.
P
r
Y
P
Y
.
E
r
Y
E
Y
Y
.
r
D

D
O

2 London, South East and East regions were combined into a single “Region” for the
purpose of this calculation.

3 For NTEM 6.1, these forecasts were supplied by Experian Business Strategies [EBS] in
November 2009. These were retained for NTEM 6.2, but the final NTEM employment
forecast itself is not identical to the NTEM 6.1 forecast as it has been adjusted to take
into account more recent GDP and population projections

NTEM 62 Guidance
11642097

Theoretically, the parameters
Y
O ,
Y
E
D and
Y
P
D can vary by year, although in practice
one of the parameters
Y
O ,
Y
E
D and
Y
P
D
is redundant.
By convention
1
Y
P
Y
E

D

D
. In NTEM 6.2,
1
Y
E
D
and
0
Y
P
D
for all years Y.
The following example illustrates the counterintuitive result that can occur if
Y
O varies
too much :
Example
Consider an example of employment forecasting between 2 years (eg 2001 and 2011)
and three regions with the same level of population growth but differing levels of
employment growth as follows:

Region
number
Population aged 16 to 64
Exogenous Employment
2001
2011
2001
2011
1
100
110
50
60
2
100
110
50
75
3
100
110
50
90
Total
300
330
150
225

Consider what would happen if the “national” employment forecasts (total across all
regions) were much lower, at 180 jobs in 2011. This would require a 20% reduction in
employment overall. If this was applied as a common global reduction for all zones, the
resulting employment would be as follows:

Region
number
Population aged 16 to 64
Employment Forecast
2001
2011
2001
2011
1
100
110
50
48
2
100
110
50
60
3
100
110
50
72
Total
300
330
150
180

This would mean that employment growth in Region 1 would switch sign from positive to
negative, simply because of a reduction in national employment without any
consideration of other characteristics of the Region (including Population growth).
If employment in each Region were to grow in line with working age population, then
each Region would have 55 jobs in 2011 (ie a total of 165 jobs). This is the “population-
based” forecast. By scaling the difference between the exogenous and population-based
forecast, a new forecast is produced as follows:

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NTEM 62 Guidance

Region
number
Population aged 16 to 64
Employment Forecast
2001
2011
2001
2011
1
100
110
50
56
2
100
110
50
60
3
100
110
50
64
Total
300
330
150
180

This means that the employment in Region 1 does not change sign simply because of
the global change in employment, and the rank of growth is preserved (ie Regions with
the greatest growth in the exogenous forecasts still have the greatest growth in this
forecast, although the difference between the Regions is reduced).
It is also instructive to consider an example where the “national” employment growth is
lower than both the population-based and exogenous forecasts. In this instance, the
population-based and exogenous forecasts are combined in proportion with the
“distance” of the total forecast from both the population-based and exogenous forecasts.
For example, if the 2011 “national” employment declined slightly to 145 jobs, the
distance from the population-based forecast would be 20 and the distance from the
exogenous forecast would be 80. The population-based and exogenous forecasts would
be weighted by 80% and 20% respectively, and then a single scaling factor would be
applied to match the total employment.
In this example:

x
80% of the population-based forecast would be 132 jobs
x
20% of the exongenous forecast would be 45 jobs;
x
A scaling factor of 145/177 = 0.8192 would be applied to the weighted
components.
The resulting employment by region would be as follows:

Region
number
Population aged 16 to 64
Employment Forecast
2001
2011
2001
2011
1
100
110
50
46
2
100
110
50
48
3
100
110
50
51
Total
300
330
150
145

Again, this preserves the rank of employment by region, with Regions having the
greatest growth in the exogenous forecast also having greatest growth (or least decline)
in the final forecast.
It should be noted that this is an extreme example – usually, the GDP-based
employment growth calculated in Step 0 would not be 20% lower than the exogenous
forecast at a national level.

NTEM 62 Guidance
11642097

STEP 2: TOTAL EMPLOYMENT, LOCAL AUTHORITY LEVEL
This step calculates
Y
.
a
EA
by combining:

the exogenous forecast at Local Authority level,
Y
.
E
a
EA
;

a population-based forecast at Local Authority level
Y
.P
a
EA
;
using the same parameters O ,
E
D and
P
D generated in Step 1. In NTEM 6.2,
1
E
D

and
0

P
D
.
Thus the formula for calculating
Y
.
a
EA
is:
)
EA
EA
(
EA
Y
.
P
a
P
Y
.
E
a
E
Y
.
a
D

D
O

However, there is a subtlety that should be considered here. At Local Authority level the
spatial distribution of working age population is not a good indicator of the spatial
distribution of employment. Therefore, the population-based employment for each Local
Authority a, in each Region r, was calculated using the Regional population growth, as
follows:
B
r
Y
r
B
.P
a
Y
.
P
a
PR
PR
EA
EA
u

for each
r
a 
This means that:
Y
.P
r
B
r
Y
r
B
.P
r
B
r
Y
r
r
a
B
.
P
a
r
a
Y
.
P
a
ER
PR
PR
ER
PR
PR
EA
EA

u

u
¦
¦



and, given that also:
Y
.
E
r
r
a
Y
.
E
a
ER
EA

¦


then:
Y
.
r
r
a
Y
.
a
ER
EA

¦


STEP 3: EMPLOYMENT BY SECTOR, NATIONAL LEVEL
The split of NTEM employment by employment sector is based on historic growth
relative to underlying population and GDP growth. This is done by constructing and
combining two different forecasting approaches:

customer-based forecasts – based on growth relative to the users of the
services provided by each sector (“customers”);

workforce-based forecasts – based on growth relative to the working age
population.
These are combined in such a way that the total employment across all sectors is
consistent with the national employment total
Y
.
EN
calculated in Step 0.

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NTEM 62 Guidance

Both customer-based and workforce-based forecasts are calculated using a similar
approach. Customer-based forecasts are calculated as follows:
Y
.
B
s.
Y
.
B
s.
B
.
C
s.
Y
.
C
s.
J
U
EN
EN
u
u

where:
B is the base year;
Y
.
B
s.
U
is the growth factor in underlying data between base year B and year Y for
sector s. This can be total population, population within a certain age group or GDP. The
category used varies by employment sector s.
Y
.
B
s.J

is an additional growth factor based on annual growth rates between years B
and Y. These annual growth rates are calibrated from the historic data by employment
sector. This also varies by employment sector s.
Table F., on the next page, shows, for each employment sector:

the data category used to calculate the underlying data growth factor
Y
.
B
s.
U
;

the additional annual growth that was applied on top of the underlying data
Y
.
B
s.J
. The short-term growth rates were applied between 2001 and 2011; the
long term growth rates were applied for years between 2011 and 2041.

Table F.4: Customer categories and underlying growth

Initial examination of the method suggested that in some categories, there had been an
unusually high level of growth in recent years that would not be expected to continue far
into the future. This necessitated the use of short-term growth rates and long-term
growth rates:

short-term growth rates were calibrated from historic employment growth
between 1996 and 2006 and population growth between 1996 and 2006);
Employment Type and
Description
Components of Growth Rates
Underlying Data
Category used
(Age group/GDP)
Additional Growth pa
Short-term
Long-term
E03
Education (School)
0 to 15
3.35%
1.08%
E04
Education (Higher)
16 to 29
1.08%
1.08%
E05
Education (Adult/Other)
16 to 64
1.08%
1.08%
E06
Hotels, campsites etc
16 and over
-0.56%
0.56%
E07
Retail
GDP
-2.58%
-1.93%
E08
Health & Medical
65 and over
1.46%
1.55%
E09
Services
16 and over
0.73%
1.05%
E10
Industry, Construction &
Transport
16 and over
-1.31%
-1.45%
E11
Restaurants & Bars
GDP
-1.24%
-0.82%
E12
Recreation & Sport
GDP
-1.02%
-0.26%
E13
Agriculture, etc
Population
-2.34%
-1.78%
E14
Business
GDP
-0.29%
-0.42%

NTEM 62 Guidance
11642097


long term growth rates were calibrated from historic employment growth
between 1982 and 2006 and population growth between 1981 and 2006.
The three Education categories were an exception to this, as the historic employment
data only gave the total for all three Education categories. The parameters were
developed on the assumption that the 1986-1996 overall additional growth in Education
employment would be applied to:

all three categories in the long term forecasts;

categories E04 and E05 in the short term forecasts.
Overall growth in the short term forecasts was based on 1996-2006 data, with the
remainder of the growth taken by E03. This was compared with a Statistical Release
from the Department for Children, Schools and Families (DCSF), 29 September 2009.
This only reports education employment in state schools and so could not be used to
calibrate a direct growth rate, but the growth rate above in above appeared sensible in
comparison with this Statistical Release.

Workforce-based forecasts are calculated in a similar way:
Y
.
B
s.
B
Y
B
.
W
s.
Y
.
W
s.
K
PN
PN
EN
EN
u
u

where:
B
is the base year;
Y
PN

is national working-age population, hence
B
Y
PN
PN
is growth in working age
population between the base year B and year Y.
The factor
B
Y
PN
PN
is analogous to
Y
.
B
s.
U
in the customer-based forecasts;
Y
.
B
s.
K

is an additional growth factor calibrated from the historic data by employment
sector. This is analogous to
Y
.
B
s.J
in the customer-based forecasts. These
factors vary by employment sector s.
Table F. on the next page shows the additional growth factors
Y
.
B
s.
K
for the workforce-
based forecasts. As with the customer-based forecasts, these are split into short-term
and long-term, with short-term rates being applied between 2001 and 2011, and long-
term rates being applied between 2011 and 2041.
Different growth rates apply to the three education categories as the growth in these
categories is expected to be driven by the students rather than the workforce. The short
term additional growth for category E03 was calculated in the same way as for the
customer-based forecast, by assuming that the short-term additional growth for E04 and
E05 is constrained to be the same as the long-term additional growth.

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NTEM 62 Guidance

Table F.5: Employee categories and underlying growth
Employment Type and Description
Components of Growth Rates
Underlying Data
Category used
(Age group)
Additional Growth pa
Short-term
Long-term
E03
Education (School)
16 to 64
2.52%
1.27%
E04
Education (Higher)
16 to 64
-0.18%
-0.18%
E05
Education (Adult/Other)
16 to 64
1.08%
1.08%
E06
Hotels, campsites etc
16 to 64
-0.59%
0.58%
E07
Retail
16 to 64
-0.44%
0.29%
E08
Health & Medical
16 to 64
1.30%
1.66%
E09
Services
16 to 64
0.70%
1.07%
E10
Industry, Construction &
Transport
16 to 64
-1.34%
-1.43%
E11
Restaurants & Bars
16 to 64
0.93%
1.43%
E12
Recreation & Sport
16 to 64
1.16%
2.00%
E13
Agriculture, etc
16 to 64
-2.56%
-1.91%
E14
Business
16 to 64
1.91%
1.64%

The approach to combining the customer-based and workforce-based forecasts is the
same approach as used for combining the exogenous forecasts and the population-
based forecasts in Step 1. The NTEM employment for employment sector s in year Y,
Y
.
s.
EN
was calculated as a weighted average of
Y
.
C
s.
EN
and
Y
.
W
s.
EN
as follows:
¸
¸
¹
·
¨
¨
©
§


P

Y
.
C
Y
.
W
Y
.
W
s.
Y
.
C
Y
.
C
s.
Y
.
W
Y
Y
.
s.
d
d
EN
d
EN
d
EN

where:
Y
.
C
d

This is the absolute “distance” of the Customer employment forecasts,
aggregated over all sectors, from
Y
.
EN
, ie:
Y
.
s
Y
.
C
s.
Y
.
C
EN
EN
d

¦

This is defined separately for each year Y, but is only ever required at national spatial
area level N.
Y
.
W
d

This is the absolute “distance” of the Workforce-based employment forecast
from
Y
.
EN
, ie:
Y
.
s
Y
.
W
s.
Y
.
W
EN
EN
d

¦

Y
P
is a scaling parameter to ensure that
¦

s
Y
.
s.
Y
.
EN
EN
. It is analogous to
Y
O in
Step 1.

NTEM 62 Guidance
11642097

STEP 4: EMPLOYMENT BY SECTOR, REGIONAL LEVEL
There are two stages to obtaining employment by Region and employment sector:
Stage 1:
update the base year employment to reflect appropriate growth in
customers or working age population (depending on employment sector);
Stage 2:
adjust the matrix to ensure that it is consistent with BOTH:

the forecast employment by Region (from Step 1); AND

the forecast employment by Sector (from Step 3).
Stage 2 is carried out using an iterative proportional fitting (Furnessing) procedure.
In Stage 1, growth is applied to the employment for each Region and Sector in a similar
way to that used for the Customer-based and Employee-based forecasts in Step 3. This
does not form the final forecast - it simply provides a more up-to-date basis for the
Furnessing procedure in Stage 2.
The forecasts for Stage 1 of this process are calculated as follows:
Y
.
B
s.
Y
.
B
s.r
B
.
s.r
Y
.
L
s.r
M
VR
ER
ER
u
u

where:
B
is the base year;
Y
.
B
s.r
VR

is the growth factor in underlying data between base year B and year Y for
Region r and employment sector s. This can be total population, population
within a certain age group or GDP. The underlying data category used
varies by employment sector s. This is analogous to
Y
.
B
s.
U
in the customer-
based forecasts.
Y
.
B
s.
M

is an additional growth factor calibrated from the historic data by
employment sector. This also varies by employment sector s. This is
analogous to
Y
.
B
s.J
and
Y
.
B
s.
K
in the customer-based and workforce-based
forecasts respectively.
Table F.6, on the next page, shows, for each employment sector:

the data category used to calculate the underlying data growth factor
Y
.
B
s.r
VR
.
The data category is either:
–
the customer-based category, where the customers are likely to reside near the
employment;
–
the employee-based category (ie population aged 16 to 64), where the
customers are not likely to reside near the employment;
–
where the customer-based category should be used and the customer-based
category is GDP, a suitable population category is be used as a proxy;

the forecast employment by Sector (from Step 3);

the additional annual growth that was applied on top of the underlying data
Y
.
B
s.
M
. The short-term growth rates were applied between 2001 and 2011; the
long term growth rates were applied for years between 2011 and 2041.

11642097
NTEM 62 Guidance

Table F.6: Regional employment categories and underlying growth
Employment Type and Description
Customer/
Employee
Forecast
used
Components of Growth Rates
Underlying Data
Category used
(Age group/GDP)
Additional Growth pa
Short-
term
Long-
term
E03
Education (School)
Customer
0 to 15
3.35%
1.08%
E04
Education (Higher)
Customer
16 to 29
1.08%
1.08%
E05
Education (Adult/Other)
Customer
16 to 64
1.08%
1.08%
E06
Hotels, campsites etc
Employee
16 to 64
-0.59%
0.58%
E07
Retail
Customer
Population
-0.21%
0.43%
E08
Health & Medical
Customer
65 and over
1.46%
1.55%
E09
Services
Customer
16 and over
0.73%
1.05%
E10
Industry, Construction &
Transport
Customer
16 and over
-1.31%
-1.45%
E11
Restaurants & Bars
Customer
16 and over
0.96%
1.41%
E12
Recreation & Sport
Customer
Population
1.39%
2.14%
E13
Agriculture, etc
Employee
16 to 64
-2.56%
-1.91%
E14
Business
Employee
16 to 64
1.91%
1.84%

Stage 2 is carried out using the biproportioning, or Furnessing, procedure
4. The
following two steps are repeated alternately:

a single factor is applied to all the jobs in the matrix for each employment sector
(each “column”) in order to match the employment sector totals – this is called
the “column balance”;

a single factor is applied to all the jobs in the matrix for each Region (each
“row”), in order to match the regional totals – this is called the “row balance”;
until the results of successive row balances are identical within a defined tolerance level.
Mathematically this can be represented as follows. For each region r:
Y
.
L
s.r
)
2
,0
(
Y
.
s.r
ER
ER

Then for n=1,2,3…, two new employment forecasts are constructed as follows:
¦


u

r
)
2
,1
n
(
Y
.
s.r
Y
.
s
)
2
,1
n
(
Y
.
s.r
)1,n
(
Y
.
s.r
ER
EN
ER
ER

¦
u

s
)1,n
(
Y
.
s.r
Y
.
r
)1,n
(
Y
.
s.r
)
2
,n
(
Y
.
s.r
ER
ER
ER
ER

This Furnessing procedure reaches a tight tolerance level in very few iterations.

4 The Furnessing procedure is frequently used in transport planning to adjust origin-
destination matrices to match vectors of origins and destinations
(Factor to national totals
by sector [column
balance])

NTEM 62 Guidance
11642097

STEP 5: EMPLOYMENT BY SECTOR, LOCAL AUTHORITY LEVEL
Step 5 is carried out in a very similar way to Step 4, but at a greater level of spatial
detail:
Stage 1:
update the base year employment to reflect appropriate growth in
customers or working age population (depending on employment sector);
Stage 2:
adjust the matrix to ensure that it is consistent with BOTH:

the forecast employment by Local Authority (from Step 2);
AND

the forecast employment by Region and Sector (from Step 4).
As with Step 4, Stage 2 is carried out using an iterative proportional fitting (Furnessing)
procedure.
The forecasts for Stage 1 of this process are calculated as follows:
Y
.
B
s.
Y
.
B
s.a
B
.
s.a
Y
.
L
s.a
M
VA
EA
EA
u
u

where:
B
is the base year;
Y
.
B
s.a
VA

is the growth factor in underlying data between base year B and year Y for
Local Authority a and sector s. The underlying data categories used are
exactly the same as for Step 4, except that in Step 5 they are at Local
Authority Level rather than Regional Level.
Y
.
B
s.
M

is defined in the same way as in Step 4.
As with Step 4, Stage 2 is carried out using the biproportioning, or Furnessing,
procedure, but this time at a greater level of spatial detail. The following two steps are
repeated alternately:

a single factor is applied to all the jobs in the matrix for each employment sector
(each “column”) in order to match the employment sector totals – this is called
the “column balance”;

a single factor is applied to all the jobs in the matrix for each Region (each
“row”), in order to match the regional totals – this is called the “row balance”;
until the results of successive row balances are identical within a defined tolerance level.
Mathematically this can be represented as follows. For each Local Authority a in each
Region r:
Y
.
L
s.a
)
2
,0
(
Y
.
s.a
EA
EA

Then for n=1,2,3…, two new employment forecasts are constructed as follows:
¦



u

r
a
)
2
,1
n
(
Y
.
s.a
Y
.
s,r
)
2,1
n
(
Y
.
s.a
)1,n
(
Y
.
s.a
EA
ER
EA
EA

¦
u

s
)
1,
n
(
Y
.
s.a
Y
.
a
)1,n
(
Y
.
s.a
)
2
,
n
(
Y
.
s.a
EA
EA
EA
EA

(Factor to Regional
totals by sector [column
balance])