NTEM Planning Data Version 6.2 

## Guidance Note Department For Transport

May 2011 

| Issue/revision    | Issue 1          | Revision 1       | Revision 2       | Revision 3    |
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| Final             |                  |                  |                  |               |
| Remarks           | Final Draft for  | Issue            |                  |               |
| Client review     |                  |                  |                  |               |
| Maps updated to   |                  |                  |                  |               |
| 2011/2031         |                  |                  |                  |               |
| Date              | 09 May 2011      | 2 June 2011      | 8 June 2011      |               |
| Clare Lindsay     |                  |                  |                  |               |
| Prepared by       | Duncan Forbes    | Andrew Young     |                  |               |
| Clare Lindsay     |                  |                  |                  |               |
| Clare Lindsay     |                  |                  |                  |               |
| (+DfT Appendix F) |                  |                  |                  |               |
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| Checked by        | Kaveh Jahanshahi | Kaveh Jahanshahi | Kaveh Jahanshahi |               |
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| Authorised by     | Clare Lindsay    | Clare Lindsay    | Clare Lindsay    |               |
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| Project number    | 11642097         | 11642097         | 11642097         |               |
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| Guidance          |                  |                  |                  |               |
| Guidance 2.2      |                  |                  |                  |               |
| Guidance _ draft  |                  |                  |                  |               |

WSP Development and Transportation 66-68 Hills Road Cambridge CB2 1LA Tel: +44 (0)1223 558050 Fax: +44 (0)1223 558051 http://www.wspgroup.com WSP UK Limited | Registered Address WSP House, 70 Chancery Lane, London, WC2A 1AF, UK | Reg No. 01383511 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 
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 

## 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       |     |
|                                                                                             |     |
| 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                                             |     |
|                                                                                             |     |
| 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                     |     |
|                                                                                             |     |
| Figure 2.8  Allocating workers from balancing areas to zones                                |     |
|                                                                                             |     |
| 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)                                       |     |
|                                                                                             |     |
| Figure 4.7  Forecast of total employment (jobs) by region, 2006-2041 (thousands)            |     |
|                                                                                             |     |
| Figure 5.1  Expected growth factors applied as weights and trends                           | 40  |
|                                                                                             |     |
| Figure 5.2  2001 Planning area types used in household EGF calculation                      |     |
|                                                                                             |     |
| Figure 5.3  Expected Growth Factors for households (district control areas)                 |     |
|                                                                                             |     |
|                                                                                             |     |
| Figure 6.1  Average household sizes in each study area                                      |     |
|                                                                                             |     |
| Figure 6.2  Average household size by district in 2021                                      |     |
|                                                                                             |     |
| 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                                                           |     |
|                                                                                             |     |
|                                                                                             |     |
| Figure 6.6  Remaining Vacant Dwellings after reallocation process                           | 50  |
|                                                                                             |     |
| Figure 6.7  Ratio of workers to jobs by Region over time                                    |     |
|                                                                                             |     |
| 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)                                    |     |
|                                                                                             |     |
| 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)                                                                            |     |
|                                                                                             |     |
| Figure 6.13  Relative difference in total employment (jobs) by zone, 2011 - 2031; NTEM      |     |
| 6.2 (left) and NTEM 5.4 (right)                                                             |     |
|                                                                                             |     |
| 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            |     |
|                                                                                             |     |
| 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)                   |     |
|                                                                                             |     |
| 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           |     |
|                                                                                             |     |
| 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                   |     |
|                                                                                             |     |
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 

## 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. 
" 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. 

## 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. 

## 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. 

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 
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. 

## 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 
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. 

## 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 
" 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. 

## 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. 

| 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. 

## 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 dwellingsled 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. 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. 

## 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. 

## 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. 

 
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. 

## 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. 
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.   

## 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. 

## 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. 

 

## 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; 
" 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.   

## 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. 

## 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. 

## 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. 

 

## 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 midyear 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. 

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 
Ward 
Mid-year estimate of people in households by age and gender (district level in Scotland) 
2001 Mid Year Population Estimates 
Region 
Used to derive population control totals 
2001 Sample of Anonymised Records (SAR) 

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. 

2001 
Percentage 
Age group Working status 
Female 
Male 
Total 
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. 

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. 

| `                                   | SIC(92) code                       |
|-------------------------------------|------------------------------------|
| 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                    |                                    |
| Services (business and other) &     |                                    |
| equipment rental & repair household |                                    |
| goods & postal / courier services   |                                    |
| 502, 504, 527, 641,                 |                                    |
| 6512, 703, 711, 714,                |                                    |
| 852, 853, 93                        |                                    |
| E09                                 |                                    |
| 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 establishments and a possible double counting of workers who work for an agency but also report themselves as self-employed). 

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 
1991 County 
Used to split total employment down into employment sector profiles 
2001 Experian Business Solutions (EBS) employment data 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 
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. 

Britain, 2001 (thousands) 
| Male                                | Male    | Female     | Female     |
|-------------------------------------|---------|------------|------------|
| Employment Type                     |         |            |            |
| NTEM                                |         |            |            |
| Type                                |         |            |            |
| Full                                |         |            |            |
| Time                                |         |            |            |
| Part                                |         |            |            |
| Time                                |         |            |            |
| Full                                |         |            |            |
| Time                                |         |            |            |
| Part                                |         |            |            |
| Time                                | Total   |            |            |
| E03 Education (school)              | E03     |            |            |
| 258                                 | 104     | 391        | 501        |
| E04 Education (higher)              | E04     |            |            |
| 133                                 | 51      | 187        | 220        |
| E05 Education (adult/other)         | E05     |            |            |
| 49                                  | 19      | 74         | 90         |
| E06 Accommodation                   | E06     |            |            |
| 107                                 | 57      | 90         | 121        |
| E07 Retail trade                    | E07     |            |            |
| 1,026                               | 403     | 689        | 1,299      |
| E08 Health/Medical                  | E08     |            |            |
| 295                                 | 100     | 742        | 776        |
| E09 Services                        | E09     |            |            |
| 949                                 | 211     | 844        | 832        |
| E10 Industry/Construction/transport | E10     |            |            |
| 6,048                               | 325     | 1,438      | 518        |
| E11 Restaurants & bars              | E11     |            |            |
| 236                                 | 194     | 180        | 380        |
| E12 Recreation & sport              | E12     |            |            |
| 352                                 | 154     | 274        | 307        |
| E13 Agriculture & fishing           | E13     |            |            |
| 270                                 | 44      | 62         | 53         |
| E14 Business                        | E14     |            |            |
| 3,294                               | 486     | 2,025      | 1,250      |
| Grand Total                         | Total   |            |            |
| 13,016                              | 2,148   | 6,994      | 6,347      |

## 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.  

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 

 
 
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. 

## 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. 

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. 

## 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 

Welsh Unitary 
Authority 
Planning 
document 
used 
Date 
Comment 
Planned 
growth 
Dwellings per 
Annum 
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.  

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; 
 

" 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. 

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. 

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

 

## 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. 

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. 

Yorkshire and The Humber 
Area Type 
East Midlands 
East of England 
London 
North East 
North West 
Scotland 
South East 
South West 
Wales 
West Midlands 
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.   

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 

 
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. 

## 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 

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. 

## 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. 

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. 

6.2.3 
Figure 6.3 shows the vacancy rate 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. 

## 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. 

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. 

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 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. 

## 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). 

| 1 Person                          | 2+ Person    | Total      |
|-----------------------------------|--------------|------------|
| Year                              |              |            |
| Household                         |              |            |
| Population                        | Jobs         | households |
| NTEM 6.2                          |              |            |
| 2001                              |              |            |
|                                   |              |            |
| 56,405,000                        |              | 28,505,000 |
| 2011                              |              |            |
|                                   |              |            |
| 59,679,000                        |              | 29,831,000 |
| 2021                              |              |            |
|                                   |              |            |
| 63,746,000                        |              | 31,576,000 |
| 2031                              |              |            |
|                                   |              |            |
| 67,392,000                        |              | 32,591,000 |
| 2041                              |              |            |
|                                   |              |            |
| 70,337,000                        |              | 33,911,000 |
| NTEM 5.4                          |              |            |
| 2001                              |              |            |
|                                   |              |            |
| 56,405,000                        |              | 28,859,000 |
| 2011                              |              |            |
|                                   |              |            |
| 59,892,000                        |              | 31,710,000 |
| 2021                              |              |            |
|                                   |              |            |
| 64,123,000                        |              | 33,403,000 |
| 2031                              |              |            |
|                                   |              |            |
| 67,679,000                        |              | 35,967,000 |
| 2041                              |              |            |
|                                   |              |            |
| 71,167,000                        |              | 38,684,000 |
| Absolute difference (v6.2 - v5.4) |              |            |
| 2001                              |              | 0          |
| 2011                              |              | -213,000   |
| 2021                              |              | -377,000   |
| 2031                              |              | -287,000   |
| 2041                              |              | -830,000   |
| Relative difference (%)           |              |            |
| 2001                              |              | 0.00%      |
| 2011                              |              | -0.36%     |
| 2021                              |              | -0.59%     |
| 2031                              |              | -0.42%     |
| 2041                              |              | -1.17%     |
|                                   |              |            |

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. 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.  
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. 

 
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. 

 

## 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. 

|                             | Household owning x cars    |        |
|-----------------------------|----------------------------|--------|
|                             |                            |        |
| Absolute Values (thousands) | Proportions (%)            |        |
| Year                        | 0 cars                     | 1 car  |
| cars                        |                            |        |
| Version 5.4                 |                            |        |
|                             |                            |        |
| 2001                        | 6,578                      | 10,464 |
| 2006                        | 6,497                      | 11,138 |
| 2011                        | 6,332                      | 11,875 |
| 2016                        | 6,335                      | 12,566 |
| 2021                        | 6,433                      | 13,343 |
| 2026                        | 6,541                      | 14,019 |
| 2031                        | 6,737                      | 14,993 |
| 2036                        | 6,830                      | 15,947 |
| 2041                        | 7,022                      | 17,033 |
| Version 6.2                 |                            |        |
|                             |                            |        |
| 2001                        | 6,474                      | 10,466 |
| 2006                        | 5,838                      | 11,366 |
| 2011                        | 5,908                      | 12,319 |
| 2016                        | 5,713                      | 13,207 |
| 2021                        | 5,860                      | 13,917 |
| 2026                        | 5,940                      | 14,512 |
| 2031                        | 6,016                      | 15,133 |
| 2036                        | 6,036                      | 15,705 |
| 2041                        | 6,010                      | 16,157 |
| Comparison: v6.2-5.4        |                            |        |
|                             |                            |        |
| 2001                        | -104                       | 2      |
| 2006                        | -660                       | 227    |
| 2011                        | -424                       | 444    |
| 2016                        | -622                       | 641    |
| 2021                        | -573                       | 574    |
| 2026                        | -601                       | 493    |
| 2031                        | -721                       | 140    |
| 2036                        | -793                       | -242   |
| 2041                        | -1,012                     | -876   |
|                             |                            |        |

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.   

## 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. 

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 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. 

## 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. 

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% 

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. 

## Trips By Purpose

6.4.4 
Figure 6.19 shows the trend in trips made by purpose through time for an average day. 

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.  
 

## 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.   

## 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. 

 

## 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.   
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. 

## Appendices, Figures & Tables Balancing Areas Study Areas And Ntem Zones

| 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                     |         |
| 1680                             | 32UH2   |
| Gainsborough                     |         |
| 465                              | 00FY4   |
| Carlton(part of)                 |         |
| 1602                             | 31UC5   |
| Shepshed                         |         |
| 1681                             | 32UH3   |
| Welton/Dunholme                  |         |
| 987                              | 17UB0   |
| rural                            |         |
| 1603                             | 31UC6   |
| Mountsorrel                      |         |
| 1682                             | 32UH4   |
| Saxilby                          |         |
| 988                              | 17UB00  |
| rural                            |         |
| 1604                             | 31UC7   |
| Sileby                           |         |
| 1683                             | 32UH5   |
| Cherry Willingham/Reepham        |         |
| 989                              | 17UB1   |
| Heanor                           |         |
| 1605                             | 31UC8   |
| Anstey                           |         |
| 1684                             | 32UH6   |
| Nettleham                        |         |
| 990                              | 17UB2   |
| Ripley                           |         |
| 1606                             | 31UC9   |
| Barrow upon Soar                 |         |
| 1685                             | 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)       |         |
| 1640                             | 32UC0   |
| rural                            |         |
| 1767                             | 34UH5   |
| Finedon                          |         |
| 1025                             | 17UH2   |
| Buxton                           |         |
| 1641                             | 32UC1   |
| Skegness                         |         |
| 1768                             | 34UH6   |
| Wollaston                        |         |
| 1026                             | 17UH3   |
| New Mills(main)                  |         |
| 1642                             | 32UC10  |
| Alford                           |         |
| 1826                             | 37UB0   |
| rural                            |         |
| 1027                             | 17UH4   |
| Chapel-en-Le-Frith               |         |
| 1643                             | 32UC2   |
| Ingoldmells                      |         |
| 1827                             | 37UB1   |
| Hucknall                         |         |
| 1028                             | 17UH5   |
| Whaley Bridge                    |         |
| 1644                             | 32UC3   |
| Louth                            |         |
| 1828                             | 37UB2   |
| Sutton in Ashfield               |         |
| 1029                             | 17UJ0   |
| rural                            |         |
| 1645                             | 32UC4   |
| Mablethorpe/Sutton on Sea        |         |
| 1829                             | 37UB3   |
| Kirkby in Ashfield(main)         |         |
| 1030                             | 17UJ1   |
| Mosborough/Highlane(part of)     |         |
| 1646                             | 32UC5   |
| Horncastle                       |         |
| 1830                             | 37UB4   |
| Jacksdale(main)                  |         |
| 1031                             | 17UJ10  |
| Wingerworth                      |         |
| 1647                             | 32UC6   |
| Coningsby                        |         |
| 1831                             | 37UB5   |
| South Normanton/Pinxton(part of) |         |
| 1032                             | 17UJ11  |
| Shirland                         |         |
| 1648                             | 32UC7   |
| Woodhall Spa(main)               |         |
| 1832                             | 37UB6   |
| Selston/Underwood/Brimsley(main) |         |
| 1033                             | 17UJ13  |
| Grassmoor                        |         |
| 1649                             | 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   |
| 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                            |         |
Selston/Underwood/Brimsley(part of) 
 
  
  
  
 
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 
 
  
  
 
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 
 
  
  
  
 
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 
 
  
  
  
 
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 
 
  
  
  
 
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 
 
  
  
  
 
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 
2122 
44UC4 
Hartshill(main) 
37 
00AW2 
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) 
Kensington and Chelsea(main) 
585 
00MG9 
Olney 
Kensington and Chelsea(part of) 
586 
00ML0 
rural 
 
  
  
  
 
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 
 
  
  
  
 
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) 
1686 
33UB0 
rural 
1356 
24UJ12 
Bransgore 
1435 
26UL2 
Welwyn Garden City 
1687 
33UB1 
Thetford 
1357 
24UJ3 
Totton 
1436 
26UL3 
Welwyn/Codicote(main) 
1688 
33UB2 
East Dereham 
1358 
24UJ4 
Ashhurst/Netley Marsh 
1437 
26UL4 
Welwyn North 
1689 
33UB3 
Attleborough 
1359 
24UJ5 
Hythe nr Southampton 
1438 
26UL5 
Potters Bar(part of) 
1690 
33UB4 
Watton 
1360 
24UJ6 
Lymington 
1439 
26UL6 
Cuffley 
1691 
33UB6 
Swaffham 
1361 
24UJ7 
Fawley 
1440 
26UL7 
Brookmans Park 
1692 
33UC0 
rural 
1362 
24UJ8 
Ringwood 
1441 
29UB0 
rural 
1693 
33UC1 
Norwich(part of) 
1363 
24UJ9 
Fordingbridge/Sandleheath 
1442 
29UB1 
Ashford 
1694 
33UC2 
Taverham 
1364 
24UL1 
Farnborough 
1443 
29UB2 
Tenterden 
1695 
33UC4 
Brundall 
1365 
24UL2 
Aldershot(main) 
1444 
29UC0 
rural 
1696 
33UC5 
Aylsham 
1366 
24UN0 
rural 
1445 
29UC1 
Herne Bay 
1697 
33UC6 
Spixworth 
1367 
24UN00 
rural 
1446 
29UC2 
Whitstable 
1698 
33UC7 
Horsford 
1368 
24UN1 
Eastleigh(part of) 
1447 
29UC3 
Canterbury 
1699 
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 
1374 
24UP1 
Eastleigh(part of) 
1453 
29UD4 
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 
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 
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) 
Longfield/New Ash Green(part of) 
1704 
33UD4 
Belton nr Yarmouth 
Sutton-at-Hone/South Darenth(main) 
1705 
33UD5 
Martham 
Longfield/New Ash Green(main) 
1729 
33UH4 
Wymondham 
Sutton-at-Hone/South Darenth(part of 
1732 
33UH8 
Hethersett 
 
  
  
  
 
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 
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) 
Anston/Dinnington/Laughton Common 
 
  
  
  
 
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 
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 
    
  
  
  
  
Immingham/Killingholme(part of) 
  
  
  

# Appendix B Segmentation - Definitions

## 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+ 
Male Female 
Full time (• 30 hours per week) 
Part time (< 30 hours per week) Students (not working) Other non working 
0 - 15 16 - 29 30 - 64 65 - 69 70 - 74 75 - 79 80 - 84 85+ 

 

## 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. 

| SIC(92) code                        | Description                        |
|-------------------------------------|------------------------------------|
| type                                |                                    |
| 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                    |                                    |
| Services (business and other) &     |                                    |
| equipment rental & repair household |                                    |
| goods & postal / courier services   |                                    |
| 502, 504, 527, 641,                 |                                    |
| 6512, 703, 711, 714,                |                                    |
| 852, 853, 93                        |                                    |
| E09                                 |                                    |
| 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                            |                                    |
|                                     |                                    |
|                                     |                                    |
|                                     |                                    |
|                                     |                                    |

## Appendix C Source Of Dwellings Input Assumptions (Amrs)

Local Planning 
Authority 
Website 
Document 
Date 
Projection 
years 
Adur District Council 
http://www.adur.gov.uk/docs/planning/adur-developmentplan/annual-monitoring-report-dec-2010.pdf 
Dec-10 
2026 
Dec-10 
2025/6 
Arun DC 
http://www.arun.gov.uk/assets/Planning/Policy_from_2010/Annual _Monitoring_Report/Annual_Monitoring_Report_2009- 10_Bookmarked.pdf 
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-annualmonitoring-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 
Dec-10 
2027/28 
East Hampshire DC 
http://www.easthants.gov.uk/ehdc/formsfordownload.nsf/0/CB3384 2F5A71FF6B802577F80035A525/$File/AMR+Final+version.pdf;  
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 
09/10 
2001-2025 
Epsom and Ewell BC 
http://www.epsom-ewell.gov.uk/NR/rdonlyres/B092A08A-9D47- 4AC3-8C7D- B696CC4A628B/0/AnnualMonitoringReport200910.pdf 
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/councilservices/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 
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/planningpolicy/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 
AMR 
2008/09 
2001-2025 
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 
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/annualmonitoring-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 
http://www.southbucks.gov.uk/includes/documents/cm_docs/2011/ a/annualmonitoringreportcovering200910.pdf 
Dec-10 
2006-2025 
South Buckinghamshire DC South Oxfordshire DC 
http://www.southoxon.gov.uk/ccm/content/planning/localplan/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 
09/10 
2006-2025 
Swale BC 
http://www.swale.gov.uk/assets/Planning-General/Planning- Policy/Annual-Monitoring-Report/Swale-Borough-Council-AMR-09- 10-with-cover.pdf 
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 
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 
Dec-10 
2003-2025 
Worthing BC 
http://www.worthing.gov.uk/worthingsservices/planningandbuildingcontrol/planningpolicy/localdevelopm entframework/annualmonitoringreport/pdffile,76728,en.pdf 
Wycombe DC 
http://www.wycombe.gov.uk/council-services/planning-andbuilding/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 
Autumn 
2010 
2007-2023 
Broads Authority 
http://www.broads-authority.gov.uk/broads/live/planning/futureplanning-and-policies/local-developmentframework/Annual_Monitoring_Report__2009-2010.pdf 
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 
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 
Dec-09 
2001-2020 
Epping Forest DC 
http://www.eppingforestdc.gov.uk/Library/files/planning/Local_Dev elopment_Framework/Evidence_Base/AMRs/EFDC%20AMR%20f inal%202009.pdf 
Fenland DC 
http://www.fenland.gov.uk/ccm/content/developmentpolicy/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- 
Dec-10 
2001-2025 
Huntingdonshire DC 
http://www.huntingdonshire.gov.uk/SiteCollectionDocuments/HDC
CMS/Documents/Planning%20Documents/PDF%20Documents/Lo cal%20Development%20Framework/AMR%20December%202010 .pdf 
Ipswich BC 
http://www.ipswich.gov.uk/downloads/Ipswich_AMR_2009-10.pdf 
Dec-10 
2001-2025 
Dec-10 
2009-2025 
Kings Lynn & West Norfolk BC 
http://www.westnorfolk.gov.uk/pdf/Kings%20Lynn%20and%20West%20Norfolk%2 0AMR%20dec%202010.pdf 
http://www.shapeyourfuture.org.uk/documents/LutonandsouthernCen tralBedsAMR0910.pdf 
09/10 
2001-2025 
Luton and South Bedfordshire Joint Planning Committee 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 
Dec-10 
2001-2024 
South Norfolk 
http://www.southnorfolk.gov.uk/planning/media/LDF_Annual__Monitoring_Report_ 2009-10.pdf 
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 
Sep-10 
2001-2020 
Stevenage BC 
http://www.stevenage.gov.uk/planningandregeneration/planningre
gulationsandpolicy/ldf/dnld_ldf/Annual_Monitoring_Report_2010.p
df 
Dec-10 
2001-2026 
Suffolk Coastal DC 
http://www.suffolkcoastal.gov.uk/NR/rdonlyres/1D4F13DE-85F8- 46DB-A5B0- E11169A191A6/0/SCDCAnnualMonitoringReport2010.pdf 
Dec-09 
2001-2025 
Tendring DC 
http://www.tendringdc.gov.uk/NR/rdonlyres/1ED82123-AE46- 4C69-9CEB- CA1A066959AF/7998/TDC2009AMRFinalVersionwithAppendices andCover.pdf 
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-anddevelopment/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 
Dec-10 
2001-2024 
Barking & Dagenham LBC 
http://www.barking-dagenham.gov.uk/8-leisureenvir/planning/local-dev-framework/pdf/monitoring-report-0910- main.pdf 
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 
09/10 
2005-2025 
Camden LBC 
http://www.camden.gov.uk/ccm/content/environment/planningand-built-environment/development-plans-and-policies/localdevelopment-framework/evidence-base-andmonitoring.en;jsessionid=85CCF11CF0ED46B7D519E60E746A4 DFB 
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 
Dec-10 
2003-2030 
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 
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 
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 
09/10 
2003-2024 
Lambeth LBC 
http://www.lambeth.gov.uk/NR/rdonlyres/3CDFED5B-A4D3-4C78- 8D03- 6E3683EA784B/0/LambethAnnualMonitoringReport200910.pdf 
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 
09/10 
2002-2026 
Newham LBC 
http://www.newham.gov.uk/NR/rdonlyres/E749857E-5679-44B5- 8674- 7222E3E7D60E/0/LocalDevelopmentFrameworkAnnualMonitoring Report20092010.pdf 
Dec-10 
2001-2016 
Redbridge LBC 
http://www.redbridge.gov.uk/cms/planning_land_and_buildings/pla nning_policy__regeneration/local_development_framework/ldf_an nual_report.aspx 
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 
08/09 
2003-2024 
Tower Hamlets LBC 
http://www.towerhamlets.gov.uk/lgsl/851-
900/856_local_development_framewor/annual_monitoring_report. aspx 
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 
Dec-10 
2004-2025 
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 
Durham Council 
http://content.durham.gov.uk/PDFRepository/AnnualMonitoringRe portDuhamCountyCouncil200809.pdf 
08/09 
2004-2023 
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 
http://www.northumberland.gov.uk/default.aspx?page=3459 
Dec-10 
2004-2015 
Northumberland Council Northumberland NP 
http://www.northumberlandnationalpark.org.uk/state_of_the_park_
report_2010.pdf 
Jun-10 
 
Dec-10 
2005-2025 
Redcar & Cleveland BC 
http://www.redcarcleveland.gov.uk/main.nsf/608BBE195DFBD9ED8025717200386 C67/$FILE/AMR%20Final%20version%2009-10.pdf 
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 
Dec-10 
2001-2025 
Cheshire East 
http://www.cheshireeast.gov.uk/environment_and_planning/planni ng/spatial_planning/local_development_framework/annual_monito ring_report.aspx 
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-localdevelopment-framework/annual-monitoring-report/ 
Dec-09 
2005-2024 
Fylde BC 
http://www.fylde.gov.uk/local-plan/local-developmentframework/annual-monitoring-report/ 
Dec-10 
2003-2020 
Halton BC 
http://www2.halton.gov.uk/pdfs/environment/planning/annualmonit oring2009 
Dec-09 
2003-2020 
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/forwardplanning/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 
Dec-09 
2003-2023 
Preston BC 
http://www.preston.gov.uk/environment-andplanning/planning/planning-policies/local-developmentframework/annual-monitoring-report/ 
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/35/2010_ 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 
Dec-10 
2005-2024 
Stockport MBC 
http://stockportconsult.limehouse.co.uk/portal/pp/zzz_adopteddocuments/aaa_lds amrsci/amr_1/amr 
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 
09/10 
2003-2020 
Wirral MBC 
http://www.wirral.gov.uk/my-services/environment-andplanning/planning/local-development-framework/annualmonitoring-reports 
Wyre BC 
http://www.wyrebc.gov.uk/Page.aspx?PgeID=73766 
Dec-10 
2003-2020 
Dec-10 
2003-2025 
Bath & NE Somerset Council 
http://www.bathnes.gov.uk/SiteCollectionDocuments/Environment %20and%20Planning/Planning/planning%20policy/Annual%20Mo nitoring%20Report%202009-10.pdf 
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/cmsservice/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 
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.dartmoornpa.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 
http://www.southglos.gov.uk/NR/rdonlyres/F775B83A-F14A-427D- A5A5-DE9A1CC4C3A9/0/PTE100296.pdf 
Dec-10 
2006-2025 
South Gloucestershire Council 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 
09/10 
2006-2025 
Taunton Deane BC 
http://www.tauntondeane.gov.uk/irj/go/km/docs/CouncilDocuments
/TDBC/Documents/Forward%20Planning/Annual%20Monitoring% 20Report%202010.pdf 
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 
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 
Dec-09 
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 
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 
08/09 
2001-2013 
Birmingham Council 
http://www.birmingham.gov.uk/cs/Satellite?c=Page&childpagenam
e=Development- Planning%2FPageLayout&cid=1223092558807&pagename=BCC %2FCommon%2FWrapper%2FWrapper 
Dec 09, 
Dec 10 
2001-2025 
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 
Cannock Chase DC 
http://www.cannockchasedc.gov.uk/downloads/Annual_Monitoring
_Report_2009-2010.pdf 
Dec-10 
2003-3025 
Oct-09 
2001-2025 
Coventry Council 
http://www.coventry.gov.uk/ccm/navigation/environment/planning/l ocal-development-framework/annual-monitoringreport/;jsessionid=aQOP63Lqqy79 
Dec-10 
2006-2025 
Dudley 
http://www.dudley.gov.uk/environment-- planning/planning/planning-policy/local-developmentframework/annual-monitoring-report 
08/09 
2001-2021 
East Staffordshire BC 
http://www.eaststaffsbc.gov.uk/Services/Planning%20Policy%20A nnual%20Monitoring%20Reports/Annual%20Monitoring%20Repor t%202009.pdf 
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 
Dec-10 
2006-2025 
Newcastle under Lyme 
http://www.newcastlestaffs.gov.uk/Documents/Newcastle%20under%20Lyme%20AMR %202009_10.pdf 
North Warwickshire BC 
http://www.northwarks.gov.uk/site/scripts/documents_info.php?doc umentID=120&pageNumber=4 
Dec-09 
2002-2025 
09/10 
2001-2025 
Nuneaton and Bedworth BC 
http://www.nuneatonandbedworth.gov.uk/environmentplanning/planning/planning-policy/local-developmentframework/annual-monitoring-report 
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 
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/cmsservice/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-andregulatory-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/developmentframework/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/corpdocs/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 
AMR 
2008/2009 
to 25/26 
Kingston upon Hull 
http://hullccconsult.limehouse.co.uk/portal/planning/amr/annual_monitoring_re port_2009?pointId=625831 
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 
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/localdevelopment-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-citydevelopment/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/45053/64877/64880/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/cmsservice/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/planningbuilding/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 
 
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 
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 
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 
Dec-10 
to 25/26 
Hinckley and Bosworth BC 
http://www.hinckleybosworth.gov.uk/downloads/file/1729/annual_monitoring_report_2 009-10 
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.newarksherwooddc.gov.uk/ppimageupload/holding/Image97790.PDF 
Dec-10 
to 25/26 
North East Derbyshire DC 
http://www.nederbyshire.gov.uk/Easysite/admin/AssetManager_ServeAsset.asp 
AMR 
2008/2009 
to 25/26 
Dec-10 
to 25/26 
North Kesteven 
http://www.nkesteven.gov.uk/upload/public/attachments/1323/Annual_Monitori ng_Report_2010.pdf 
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 
AMR 
2008/2009 
to 25/26 
Oadby and Wigston BC 
http://www.oadbywigston.gov.uk/Home/Planning/Forward%20Plans/Local%20Devel opment/AMR%2008-09%20Full.pdf 
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 
AMR 
2008/2009 
no Projection 
West Lindsey 
http://www.westlindsey.gov.uk/upload/public/attachments/1170/West_Lindsey_Dis trict_Council_2009_AMR.pdf 

 

## Planning Documents For Wales

Local Planning 
Authority 
Website 
Document 
Date 
Projection 
years 
2006 
2010-2016 
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 
2008 
2006-2021 
Blaenau Gwent 
http://www.blaenaugwent.gov.uk/documents/Documents_Environment/LDP_Draft_Pr eferred_Strategy.pdf 
2005 
2001-2016 
Bridgend 
http://www.bridgend.gov.uk/web/groups/public/documents/report/0 57945.pdf 
http://www.bridgend.gov.uk/BCBCUDP/english/text/text04.htm 
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 
2003 
2001-2015 
Flintshire 
http://www.flintshire.gov.uk/wps/wcm/connect/8c493800497bc02b 8068bfbfb73e2b74/UDP_DPPReport_Housing_Requirement.pdf? MOD=AJPERES 
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 
2006 
2001-2021 
Monmouthshire 
http://www.monmouthshire.gov.uk/downloads/Preferred_Strategy_ Complete.pdf 
http://www.monmouthshire.gov.uk/downloads/Part_II.pdf 
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 
2006 
2001-2021 
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 
Powys 
http://www.powys.gov.uk/uploads/media/Written_statement_final_ web_en_04.pdf 
Mar-10 
2001-2016 
2009 
2006-2021 
Rhondda, Cynon, Taff 
http://www.rhondda-cynontaf.gov.uk/en/relateddocuments/publications/developmentplanning /localdevelopmentplan2006- 2021/depositdraftlocaldevelopmentplan.pdf 
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 
2005 
2001-2021 
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 
 

## 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: 

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. 

## 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. 

## 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).   

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. 

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% 
 
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% 

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. 

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, V*max,* V
ˆ ) 
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. 

 

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.   

## 

|                   |        |       | Full Time    | Part Time    |
|-------------------|--------|-------|--------------|--------------|
|                   | Female | Male  | Female       | Male         |
| Region            | 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. 

## 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. 

# Appendix E Mathematical Specification Of Methodology

## 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.   

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 
P
ˆ  
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. 

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 
 
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
ti
P
 
" 
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 
" 
E
ˆ  
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%) 
" 
c
T  
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 nonworkers). 

## Population And Household Totals For Study Area (Region)

Initial estimate of total population is taken as:

$$\bar{P}_{\beta}^{\beta}=\sum_{c\in\bar{\gamma}}\bar{P}_{c}^{\beta}\quad\text{and}\quad\bar{P}_{bc}^{\beta}=\sum_{m\in\bar{\gamma}}\bar{P}_{bc}^{\beta m}\Big{(}1-\alpha_{n}^{\beta m}\Big{)}\text{and}c\in R$$ (Eq 1)

where 
gm
tc
P
ˆ
 
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:

$$\vec{H}_{\vec{m}}=\sum_{\vec{p}}\hat{H}_{\vec{m}}^{\rm b}$$ (Eq 2)

## 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. 

$$\widetilde{E}_{ic}^{\,new}=E_{(t-1)c}\Bigg{(}\frac{\hat{E}_{ic}}{\hat{E}_{(t-1)c}}\Bigg{)}\frac{E_{(t-1)c}^{\,new}\Bigg{(}\frac{\hat{E}_{ic}^{\,new}}{\max(\hat{E}_{(t-1)c}^{\,new},0.001)}\Bigg{)}}{\sum_{\alpha\neq v}E_{(t-1)c}^{\,new}\Bigg{(}\frac{\hat{E}_{ic}^{\,new}}{\max(\hat{E}_{(t-1)c}^{\,new},0.001)}\Bigg{)}}$$

where $\hat{E}_{ic}=\sum_{\alpha\neq v}\hat{E}_{ic}^{\,new}$ and $\widetilde{E}_{ic}^{\,new}=\sum_{\alpha\in\overline{R}}\widetilde{E}_{ic}^{\,new}$ (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: 

$$W_{\rm fft}^{\rm gtw}=\rho_{\rm fft}^{\rm gtw}\sum_{\alpha}\gamma^{\rm guv}_{\rm fft}\,\tilde{E}_{\rm fft}^{\rm guv}$$ (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. 

P ~ gl tR ¦ child l , g E E d d z   where   1 t min E  and  min max E E !   (Eq 5a)   min H ~   max tR
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. 

1 H ˆ P ~   ¦ h tR l , g gl tR d    where   2 t E ˆ  (specified by user)  (Eq 5b)     2   E ˆ H ˆ h tR
The workforce required to satisfy the employment forecasts should also be compared with the potential workers available from the population forecasts. 

$$\sigma_{t,min}^{sl}\leq\frac{\sum_{w}W_{\mathit{RF}}^{\mathit{RF}}}{\widehat{P}_{\mathit{RF}}^{\mathit{gl}}}\leq\sigma_{t,max}^{sl}\ \ \ \text{where}\ \ 0<\sigma_{t,min}^{\mathit{gl}}<\sigma_{t,max}^{\mathit{gl}}<1$$ (Eq 6)

Ratio of workers to jobs: $\frac{\sum_{\mathit{all}}W_{\mathit{RF}}^{\mathit{MF}}}{\sum_{\mathit{all}}\overline{E}_{\mathit{RF}}^{\mathit{MF}}}$ (Eq 7)

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

$$S_{\mathit{RF}}^{\mathit{max}}\ =\sum_{c\in R}D_{\mathit{tc}}\left(\theta_{c}+\Delta\theta_{\mathit{max}}\left[1-\max\left(\upsilon_{\mathit{min}},\upsilon_{\{t-1\}},\chi\right)\right]-\sum_{c\in R}S_{c}^{\mathit{T}}$$ (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.   

$$1-\frac{\vec{H}_{\vec{\Omega}}}{S_{\vec{\Omega}}^{max}}\Bigg{]}>\psi$$ (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 Region total.

$$H\big{(}1\big{)}_{tc}=\widetilde{H}_{\mathit{at}}\,\frac{H_{\big{(}t-1\big{)}c}\,\sum_{\mathit{gl}}\widetilde{P}_{tc}^{\mathit{gl}}\,\Big{/}\sum_{\mathit{gl}}P_{\big{(}t-1\big{)}c}^{\mathit{gl}}}{\sum_{c\in R}H_{\big{(}t-1\big{)}c}\,\sum_{\mathit{gl}}\widetilde{P}_{tc}^{\mathit{gl}}\,\Big{/}\sum_{\mathit{gl}}P_{\big{(}t-1\big{)}c}^{\mathit{gl}}}$$ (Eq 10a)
 These households must then be split into those with one person (h=1) and those with two or more persons (h=2). 

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 E
ˆ
 is also applied to the 2+ 
person household size parameters. 

$\pi_{\rm tc}^{(h=1)g^{l}}=\pi_{\rm tc}^{(h=1)g^{l}}$

$\pi_{\rm tc}^{(h=2)g^{l}}=A_{\rm tc}\pi_{\rm tc}^{(h=2)g^{l}}$ and $\sum_{g^{l}}\pi_{\rm tc}^{(h=2)g^{l}}\geq\hat{\beta}$
The value of the adjustment factor tc A  is calculated iteratively with estimates of the number of 2+ person households (h=2) as follows: 

$$A_{n}^{n+1}=max\left(A_{n}^{n}\,\frac{\sum_{c\in R}H\big{(}1\big{)}^{\left(n-2\right)n}}{\hat{H}_{nR}^{n-2}},\frac{\hat{\beta}}{\sum_{gI}\pi_{c}^{\left(n-2\right)gI}}\right)\text{and}H\big{(}1\big{)}_{nc}^{\left(n-2\right)n}=\frac{\sum_{gI}\widetilde{P}_{tc}^{\,\,\,gI}-H\big{(}1\big{)}_{nc}}{A_{nc}^{n}\left(\sum_{gI}\pi_{c}^{\left(n-2\right)gI}-1\right)}$$ (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: 

· § ·     2 1 §  H ˆ H ˆ P ~ gl tR ¦ ¸ ¸ ¸ ¨ ¨ ¨ h tR h tR gl ¹ © E  
tc
ˆ
,

 
starting with 



·
1
S

gl h c §  H H P gl
 

glw i ) t ( max A 2 2 1 1 1 1   ¦ ¦ ¦ ¦ ¦ ¸ ¸ ¸ ¨ ¨ ¨ ¸ ¸ ¸ ¸ ¸ ¸ ¸ ¨ ¨ ¨ ¨ ¨ ¨ ¨       h i ) t ( glw h i ) t ( R i R i R i ¹ © ¹ ©
where hgl c S
 
is the expected number of persons of type gl in household type h in control area c  
and h tR
H
ˆ
 
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) 

    1
  n
 i
 A
A
                       . 

This iterative process continues until 
                                                           5
                                                       10
                                                    1
                                               1
                                                          
                                                     u
                                                  d
                                              
                                           n
                                          i

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: 
H
H
ˆ

 (ie dwellings and households are forecast to move in the same If  


0
1
!

'

        h
            R
        t
h
tR
    D

pR

direction) then: 

 

'       1 1 2 ˆ   D H H H H ' pc h R t h tR h c t h tc D pR   where    c t tc pc D D D 1     '  and  ¦  '   ' R c pc pR D D   (Eq 11)   H H H ˆ H H

1 1 1 2

otherwise 
             

h c t h R t h tR h c t h tc H

h R t 1

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: 

$\widetilde{H}_{\rm E}^{\rm b}=(1-\zeta)H(1)_{\rm E}^{\rm b}+\zeta H(2)_{\rm E}^{\rm b}$ (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:

$$S_{{}_{E}}=D_{{}_{E}}\theta_{{}_{E}}\left(1-\upsilon_{{}_{E(t-1)}}\right)-S_{{}_{c}}^{Y}$$ (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:

$$S_{{}_{E}}^{\max}=D_{{}_{E}}\left(\theta_{{}_{C}}+\Delta\theta_{{}_{\max}}\right)\left[1-\max\left(\upsilon_{{}_{\min}},\upsilon_{{}_{C(t-1)}}\chi\right)\right]-S_{{}_{c}}^{Y}$$ (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) 
The adjusted vacancy rate for the scenario (required for future dependent scenarios) is calculated as: 

$$\upsilon_{ct}=\max\Biggl{(}\upsilon_{\min},\upsilon_{c(t-1)}\chi,\upsilon_{c(t-1)}-\Biggl{(}\frac{H_{sc}-S_{sc}}{D_{sc}\theta_{c}}\Biggr{)}\Biggr{)}$$ (Eq 15)
 where tc H  is output by Eq 20 
The housing pressure is then calculated as: 

_HPPressure${}_{\rm E}=\frac{\bar{H}_{\rm E}}{S_{\rm E}^{\rm max}}$_ (Eq 16)
~
If any control area in the study area has excess households, ie 
1
!

max tc S
H
 for any c, then tc

identify sparse capacity and reallocate a proportion of the excess households between the control areas within the study area based on the capacity available Excess households: $\widetilde{X}_{\text{tc}}=max\left[\widetilde{H}_{\text{tc}}-\mathcal{S}_{\text{tc}}^{max},0\right]$ and $\widetilde{X}_{\text{ft}}=\sum\limits_{\text{c}\in\text{ft}}\widetilde{X}_{\text{tc}}$ (Eq 17)

Capacity available: $C_{\text{tc}}=max\left[\mathcal{S}_{\text{tc}}^{max}-\widetilde{H}_{\text{tc}},0\right]$ and $C_{\text{ft}}=\sum\limits_{\text{c}\in\text{ft}}C_{\text{tc}}$ (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: $H_{\rm gc}=\widetilde{H}_{\rm gc}-\widetilde{X}_{\rm gc}+\left(min\left(\lambda_{\rm f}\widetilde{X}_{\rm fB},C_{\rm fB}\right)\right)\left(\frac{C_{\rm fE}}{C_{\rm fB}}\right)$ (Eq 19)
Where: 
t O  is the proportion of households willing to move to other parts of the study area.  When 
1

t O
, 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.

 
t O
 (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: 

·         tc X ~ H ~ H tR t t h tc tc t ¨ ¨ § ¸ ¸
§

 
¦

h tc tc h tc h tc C C 1 1 1 1 1 1 1 O O P P O O X ~ , X ~ C min H ~ H ~ H ~ H ~ tR § ¸ ¸ ¹ · ¨ ¨ ©   ¸ ¸ ¹ · ¨ ¨ © §  ¸ ¸ ¹ · ¨ ¨ © tc tR t c tc § ¸ ¸ ¹ · ¨ ¨ © § ¸ ¸ ¹ · ¨ ¨ © © ¹
 And for household type 2:  

~           tc tR ~ ~ 1 , ~ min ~
§

 
¦

1 1 ~ 1 ~ ~ ~ ~ 2 1 2 2 2 O O P O h tc tc h tc h tc C C H H X X C H H X H H X H H ~ tR §  ¸ ¸ ¹ · ¨ ¨ © h tc tc t tc tc h tc tc t tR t c tc · ¨ ¨ ©   ¸ ¸ ¹ § ¸ ¸ ¹ · ¨ ¨ © § ¸ ¸ ¹ · ¨ ¨ ©         (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. 

, otherwise more 1 person households will be This will work so long as O
P
P

d
1

   tc
H
~
X
~

tc

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: 
    h tc §   ~ ~ 1 1 1 P P O O and.  ~ ~ 1 1 ~    h tc H H X H H X X ~ h tc tc t R c § ¸ ¸ ¹ · ¨ ¨ © R c tc t R c tc   ¦ ¦ ¦ tc   ¸ ¸ ¹ · ¨ ¨ © §    ¸ ¸ ¹ · ¨ ¨ ©     §   ~ ~ 1 2 2 P O   ~ ~ 1 1 1 ~   ¦ ¦ ¦    h tc H H X H H X X ~ h tc tc R c § ¸ ¸ ¹ · ¨ ¨ © h tc tc t R c tc R c tc   ¸ ¸ ¹ · ¨ ¨ © §    ¸ ¸ ¹ · ¨ ¨ ©


h
tc
h
tc
H
H
2
2
~
 were suppressed; and 
" 
Of which 


¦

h
tc
h
tc
H
H
1
1
~
 and 


¦

R
c
R
c

 

h
tc
H
H
X
2
2
2
~
 were 
" 


¦
¦


h
tc
H
H
X
1
1
1
~
 and 


¦
¦


h
tc
h
tc
R
c
R
c
h
tc
h
tc
R
c
R
c
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 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: 

º tR §         X ~ , H ~ H max H     h tc h tR H H   h tc tc t h tc h tc h tc O O  and  ¦  1 0 1 , X ~ C min H ~ H ~ c tc tR t · ¨ ¨ © § ˜ ¸ ¸ ¹ · ¨ ¨ © ª ¸ ¸ ¹ « « ¬ » » ¼    
 

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

$$\Pi_{\iota R}^{h g l}=P_{\iota R}^{h g l^{-}}\Big/H_{\iota R}^{h^{-}}$$
The population moving into control areas is thus: 

tc §   3   ¦ 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    tR h tc tc t tR t c tc     ¸ ¸ ¹ · ¨ ¨ © · ¨ ¨ © § ¸ ¸ ¹ · ¨ ¨ © § ¸ ¸ 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:  

     hgl tc gl tc gl tc P P P P ~    (Eq 21)   ¦ ¦ hgl tc h h

## 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. 

## 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: 

, ~ ˆ max E g 0 '       pi g   if  0 d ' a pc E ~    a pc a pi a E g 0 a i t a pi 1 , ˆ min     ¦   c i , ~ ˆ max E g 0 '   and    pi g   if  0 ! ' a pc E ~   a pc a pi a E g 0 a i t a pi 1 , ˆ max     ¦   c i ~ ~     a i t agw tc a pc E E E 1 where     ¦ ¦      ' gw c i
(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:

$$\mathcal{G}_{pi}^{H}=\frac{max\Big{(}\hat{\mathcal{G}}_{pi}^{H}\Delta H_{pc},0\Big{)}}{\sum_{i\in c}min\Big{(}\hat{\mathcal{G}}_{pi}^{H}H_{(t-1)i},0\Big{)}}\quad\text{if}\ \ \Delta H_{pc}\leq0$$

and

$$\mathcal{G}_{pi}^{H}=\frac{max\Big{(}\hat{\mathcal{G}}_{pi}^{H}\Delta H_{pc},0\Big{)}}{\sum_{i\in c}max\Big{(}\hat{\mathcal{G}}_{pi}^{H}H_{(t-1)i},0\Big{)}}\quad\text{if}\ \ \Delta H_{pc}>0$$

where $\Delta H_{pc}=\sum_{h}H_{tc}^{h}-\sum_{h,i\in c}H_{(t-1)i}^{h}$

## 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: 

$$g_{p i}^{a}=\hat{g}_{p i}^{a}+\frac{\Delta E_{p c}^{a}-\sum_{\stackrel{i\in c}{i\in c}}\hat{g}_{p i}^{a}E_{(t-1)i}^{a}}{\sum_{\stackrel{i\in c}{i\in c}}E_{(t-1)i}^{a}}$$
For households the equivalent adjustment is: 

$$g_{p i}^{H}=\hat{g}_{p i}^{H}+\frac{\Delta H_{p c}-\sum\hat{g}_{p i}^{H}H_{(t-1)i}}{\sum_{i\in c}H_{(t-1)i}}$$

## 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:

$$H_{\rm g}^{\rm b}=H_{\rm g}^{\rm b}\sum_{i\in\rm g}^{H_{\rm(l-1)}^{\rm b}}\Bigl{(}max\Bigl{(}1+g_{gi}^{\rm u},0\Bigr{)}\Bigr{)}A_{i}$$ (Eq 22)
Where the adjustment term i A  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: 

$$A_{i}^{n+1}=H_{(t-1)i}\Bigg/\sum_{h}\left(\frac{H_{i v}^{h}H_{(t-1)i}^{h}}{\sum_{i\in{\cal E}}H_{(t-1)i}^{h}\left(m a x\left(1+g_{p i}^{h},0\right)\right)A_{i}^{n}}\right)$$
until 
01
0
1
.

d

1
n i A
 and where 
1
0  
i A
 
n i A
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. 

$$\tilde{P}_{\rm u}^{\rm d}=\max\Biggl{(}P_{({\rm t}-{\rm l})}^{\rm d}+\sum_{h}\pi_{hc}^{h\nu}\Bigl{(}H_{u}^{\rm h}-H_{({\rm t}-{\rm l})}^{\rm h}\Bigr{)},0\Biggr{)}$$ (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: 

$$P_{\rm g}^{\it gf}=P_{\rm g}^{\it gf}\ \frac{\bar{P}_{\rm g}^{\it gf}}{\sum_{i\in{\cal E}}\bar{P}_{\rm g}^{\it gf}}\ \mbox{to ensure}\ \sum_{i\in{\cal E}}P_{\rm g}^{\it gf}=P_{\rm g}^{\it gf}$$ (Eq 24)
The change in the zonal population from the previous scenario is: 

$\Delta P^{gl}_{\mu}=P^{gl}_{\mu}-P^{gl}_{(t-1)i}$ (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: 

$$E(1)^{\rm gap}_{\rm f_{i}}=E^{\rm gap}_{(i-1)i}\frac{H_{\rm f_{i}}}{H_{(i-1)i}}$$ (Eq 26)
A single scalar adjustment is then applied to ensure the control totals are met 

      agw tc agw ti E E ~ ~   (Eq 27)   1 ~ ~  so that ¦    c i agw ti agw tc agw ti E E E E 1 agw ti   ¦  c i
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:

$$\widetilde{E}_{\text{g}}^{\text{avg}}=\widetilde{E}_{\text{g}}^{\text{avg}}\frac{E_{\text{g}}^{\text{avg}}}{\sum_{l_{\text{g}}\in C}^{\text{avg}}\left(max\left(1+g_{\text{g}}^{\text{g}},0\right)\right)}$$ (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: 

$$\tilde{W}_{\rm B}^{\rm Bw}=\sum_{i\in B}\rho_{i\rm B}^{\rm Bw}\left(\sum_{a}\gamma_{i\rm B}^{\rm Bw}\tilde{E}_{i\rm F}^{\rm Bw}\right)\ \mbox{for w=F,P}$$ (Eq 29)

The change in the demand for workers from the previous scenario is:

$$\Delta\tilde{W}_{\rm B}^{\rm Bw}=\tilde{W}_{\rm B}^{\rm Bw}-W_{(l-1)\rm B}^{\rm Bw}\ \mbox{for w=F,P}$$ (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 $\Delta P_{\rho}^{\rm gf}<0$ then $P(1)_{\rm f}^{\rm gw}=P_{(t-1)}^{\rm gw}+\Delta P_{\rho}^{\rm gf}\left(\begin{array}{c}P_{(t-1)}^{\rm gw}\\ P_{(t-1)}^{\rm gw}\end{array}\right)$ otherwise $P(1)_{\rm f}^{\rm gw}=P_{(t-1)}^{\rm gw}$ (Eq 31) and $P(1)_{\rm f}^{\rm gw}=\sum_{i\in\mathcal{B}}P(1)_{\rm f}^{\rm gw}$ (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 : 

$$P(2)^{\beta(w=F,P)}_{\beta}=P(1)^{\beta(w=F,P)}_{\beta}\frac{W^{\beta(w=F,P)}_{\beta}}{\sum_{i\in\beta}P(1)^{\beta(w=F,P)}_{\beta}}\ \ \text{for w=F,P}$$ (Eq 33)
At this stage the total population by gender and age remains as above so that: 

$P(2)^{\beta}_{\rm f}=P(1)^{\beta}_{\rm f}=\sum_{w}P(1)^{\beta w}_{\rm f}$ (Eq 34a)
with the non working population (not required at this stage) being the difference:  

$$P(2)^{\beta(w=S,O)}_{\beta}=P(2)^{\beta}_{S}-\sum_{\eta=F,P}P(2)^{\beta(w=F,P)}_{\beta}$$ (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 $\widetilde{P}\big{(}3\big{)}_{ii}^{giv}=P\big{(}2\big{)}_{ii}^{giv}+\Delta P_{pi}^{giv}\Bigg{(}\frac{P\big{(}2\big{)}_{ii}^{giv}}{P\big{(}2\big{)}_{ii}^{giv}}\Bigg{)}$ 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   glw ti glw tB P P 3 3  for w= F, P     (Eq 36)         ¦    B i  

## 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 : 

$$\sigma^{gl}_{\mu,\max}=\min\Biggl{(}\sum_{w}\bigl{(}\Delta\sigma^{\mu w}_{\max}+\sigma^{\mu w}_{(l-1)\mu}\bigr{)}\sigma^{gl}_{\max}\Biggr{)}$$ (Eq 37)

Or  
                   
                       gl
            gl
           ti
                      max
             max
            ,
                    V
         V
                  
                            when there is no existing data 

Giving a maximum supply of employees: 

$$P(2)^{\beta}_{\beta,max}=\sigma^{\beta}_{\beta,max}P(2)^{\beta}_{\beta}$$ (Eq 38)

and a possible maximum for each working status type of:

$$\tilde{P}(2)^{\beta\alpha}_{\beta,max}=\left(\sigma^{\beta\alpha}_{\beta\left(1-1\right)\lambda}+\Delta\sigma^{\beta\alpha}_{max}\right)P(2)^{\beta}_{\beta}$$

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

We let it is possible that $P(2)^{\beta\alpha}_{\beta,max}=\sum_{\eta}\tilde{P}(2)^{\beta\alpha}_{\beta,max}$ or $P(2)^{\beta}_{\beta,max}\neq\sum_{\eta}\tilde{P}(2)^{\beta\alpha}_{\beta,max}$.

The two estimates  
~ 2
 are used in separate stages of the gl ti P
max
,
2
 and  

       glw
       ti
P
         max
         ,

remaining forecasting steps. For the "new" population the maximum number of employees by gender is: 

New population: $\Delta P\big{(}3\big{)}^{\beta}_{\beta,max}=\Delta P^{\beta}_{\beta}\sigma^{\beta}_{1,max}$ (Eq 39)

Thus the maximum workers in zone: $P\big{(}3\big{)}^{\beta}_{\beta,max}=P\big{(}2\big{)}^{\beta}_{\beta,max}+\Delta P\big{(}3\big{)}^{\beta}_{\beta,max}$ (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:  

$$P\big{(}3\big{)}^{\beta}_{\beta,max}=\sum_{i\in\mathcal{B}}P\big{(}3\big{)}^{\beta}_{i,max}$$ (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:

$$\Delta P\big{(}3\big{)}^{\beta\text{inv}}_{\beta,max}=\Delta P\big{(}3\big{)}^{\beta}_{\beta,max}\frac{max\big{(}\Delta W^{\beta\text{inv}}_{\beta\beta},1\big{)}}{\sum_{w}max\big{(}\Delta W^{\beta\text{inv}}_{\beta\beta},1\big{)}}$$ (Eq 42)
The maximum number of workers by gender and working status available in the population is then calculated as: 

$$P\big{(}4\big{)}_{\beta,max}^{\beta\mu}=\left(\widetilde{P}\big{(}2\big{)}_{\beta,max}^{\beta\mu}+\Delta P\big{(}3\big{)}_{\beta,max}^{\beta\mu}\right)\text{and}P\big{(}4\big{)}_{\beta,max}^{\beta\mu}=\sum_{i\in\widetilde{P}}P\big{(}4\big{)}_{\beta,max}^{\beta\mu}\quad(\text{Eq43})$$
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 $\sum_{w}P(4)^{glw}_{l,\,max}\leq P(3)^{gl}_{l,\,max}$, then $P(5)^{glw}_{l,\,max}=P(4)^{glw}_{l,\,max}$

Else: $P(5)^{gl(w=F)}_{l,\,max}=P(4)^{gl(w=F)}_{l,\,max}$ if

$$\left(P(4)^{gl(w=F)}_{l,\,max}-P(3)^{gl(w=F)}_{l,\,max}\right)<\left(P(4)^{gl(w=P)}_{l,\,max}-P(3)^{gl(w=P)}_{l}\right)$$

Else $P(5)^{gl(w=F)}_{l,\,max}=P(3)^{gl}_{l,\,max}-P(4)^{gl(w=P)}_{l,\,max}$
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 

gl tB l tB Z Z   (Eq 44)   Excess workers are:        0 , 3 ~ max , max , P F w gl tB gl tB gl tB P W Z       and  ¦   g Capacity for workers is: $V_{\rm g}^{\rm gf}=max\left(P(3)^{p^{\prime}(w,\pi,P)}_{\rm B,max}-\tilde{W}_{\rm g}^{\rm g^{\prime}},0\right)$ (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:

$$W^{g^{l}}_{i\bar{B}}=\tilde{W}^{g^{l}}_{i\bar{B}}-Z^{g^{l}}_{i\bar{B}}+min\Big{(}V^{g^{l}}_{i\bar{B}},Z^{l}_{i\bar{B}}\Big{)}$$ (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: 

$$W(1)^{\beta\alpha}_{\beta}=W^{\beta}_{\beta}\frac{\tilde{W}^{\beta\alpha}_{\beta}}{\tilde{W}^{\beta}_{\beta}}$$ (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: $Z_{\rm IB}^{low}=max\Big{(}W(1)_{\rm IB}^{low}-P\big{(}5\big{)}_{\rm IB,max}^{low},0\Big{)}$

and $Z_{\rm IB}^{\rm SI}=\sum_{w}Z_{\rm IB}^{low}$ (Eq 48)

Theoretical capacity for workers is: $Y_{\rm IB}^{low}=max\Big{(}P\big{(}5\big{)}_{\rm IB,max}^{\rm SI}-W\big{(}1\big{)}_{\rm IB}^{\rm SI},0\Big{)}$ (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: 

$$W_{\rm B}^{\rm dw}=W(1)_{\rm B}^{\rm dw}-Z_{\rm B}^{\rm dw}+min\Big{(}Y_{\rm B}^{\rm dw},Z_{\rm B}^{\rm d}\Big{)}$$ (Eq 50)
And a revised set of employment rates: 

$$\sigma^{\rm{\it bw}}_{\rm{\it B}}=\frac{W^{\rm{\it bw}}_{\rm{\it B}}}{P^{\rm{\it S}}_{\rm{\it B}}}$$ (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 

" 
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: 

$$W_{i}^{g h w}=\frac{W_{i B}^{g h w}}{P(3)_{i B}^{g h w}}P(3)_{i B}^{g h w}$$
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:  

P W   3    W  

$$\dot{\mathrm{\boldmath~\nabla~}}_{t B}^{g h w}=\frac{\dot{W}_{t B}^{g h w}-P(3)_{t B}^{\dot{g}h w}}{P(5)_{t B,m a x}^{g l w}-P(3)_{t B}^{g l w}}$$
the zonal forecasts of workers by zone are calculated as: 

$W_{ij}^{\rm ghw}=P_{ij}^{\rm ghw}=P(3)_{ij}^{\rm ghw}+\tau_{iB}^{\rm ghw}(P(5)_{ij,max}^{\rm ghw}-P(3)_{ij}^{\rm ghw})$
These two cases can be combined into the single equation: 

$$W_{i i}^{\sigma w}=m i n\left(1,\frac{W_{i i}^{\sigma w}}{P\!\left(3\right)_{i i}^{\sigma w}}\right)P\!\left(3\right)_{i i}^{\sigma w}+m a x\!\left(\tau_{i i}^{\sigma w},0\right)\!\left(P\!\left(5\right)_{i i,m a x}^{\sigma w}-P\!\left(3\right)_{i i}^{\sigma w}\right)\quad(\mathrm{Eq\,52})$$

                   glw
                  ti
    gl
   ti
               W
W
                        

with the total number of workers being 
¦
 
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. 

$$N_{\rm f}^{\rm dw}=\left(P_{\rm f}^{\rm d\!f}-W_{\rm f}^{\rm d\!f}\right)\frac{N_{\rm f-1,1}^{\rm dw}}{N_{\rm f}^{\rm d\!f}}\ \ \ {\rm for\ w=S,O}$$ (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:

$$E_{\bar{v}}^{a}=\sum_{g^{\mu}}\bar{E}_{\bar{v}}^{g^{\mu\nu}}$$
The revised split is then estimated as: 

~ ~ ¦ ¦ l glw tB l     (Eq 54)   §   W W E E E ~ ~ glw tB agw ti a ti agw ti W W E glw tB agw ti ¦ ¦ ¦ gw l glw tB l · ¨ © ¸ ¹  
# Appendix F Employment Forecasting Methodology

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. 

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. 

 

## 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                                                                      | .                                                                   |
| 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                                                                      | .                                                                   |
| 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                                                                      | .                                                                   |
| 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. So, for example: 

| Y                                                                   | .            | E   |
|---------------------------------------------------------------------|--------------|-----|
| a                                                                   |              |     |
| EA                                                                  |              |     |
|                                                                     | represents   |     |
| E                                                                   |              |     |
| xogenous Employment (total over all sectors), for Local             |              |     |
| Authority a and year Y.                                             |              |     |
| 1                                                                   |              |     |
| This 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   |     |
| P                                                                   |              |     |
| opulation-based Employment (total over all sectors) for region      |              |     |
| r and year Y.                                                       |              |     |
| Y                                                                   | .            | C   |
| s                                                                   | .            |     |
| EN                                                                  |              |     |
|                                                                     | represents a |     |
| C                                                                   |              |     |
| ustomer-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 |     |
| W                                                                   |              |     |
| orkforce-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 |     |
| L                                                                   |              |     |
| ocal-data-based employment forecast, for Region r, year Y           |              |     |
| and employment sector s.                                            |              |     |
| Y                                                                   | .            | L   |
| s                                                                   | .            | a   |
| EA                                                                  |              |     |
|                                                                     | represents a |     |
| L                                                                   |              |     |
| ocal-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. 

## Step 0: Total Employment, National Level

Total employment for year Y, at a National level, is calculated from the previous year Y-1 by: 

$$\mathrm{EN}^{\cdot\mathrm{Y}}=\mathrm{EN}^{\cdot\mathrm{Y}-1}\times\mathrm{g}_{\mathrm{N}}^{\mathrm{E.Y}-1.\mathrm{Y}}$$
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: 

$${\mathsf{g_{N}^{\mathrm{E.Y-1.Y}}}}={\frac{{\mathsf{g_{N}^{\mathrm{G.Y-1.Y}}}}}{{\mathsf{g_{N}^{\mathrm{R.Y-1.Y}}}}}}$$
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: 

$${\mathsf{g_{N}^{R.X.Y}=(1.02)^{(X-B)}}}$$

## 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: 

$$\sum_{\mathrm{r\in N}}\mathrm{ER}_{\mathrm{r}}^{\mathrm{E.Y}}\neq\mathrm{EN}^{\cdot\mathrm{Y}}$$
whereas it is necessary that: 

$$\sum_{\mathrm{r\in N}}\mathrm{ER}_{\mathrm{r}}^{\cdot\mathrm{Y}}=\mathrm{EN}^{\cdot\mathrm{Y}}$$
In NTEM 6.2 we used a simple approach to adjust the exogenous forecast by applying a global scaling factor, ie: 

$$\mathrm{ER}_{\mathrm{r}}^{\mathrm{.Y}}=\mathrm{ER}_{\mathrm{r}}^{\mathrm{E.Y}}\times\frac{\mathrm{EN}^{\mathrm{.Y}}}{\sum_{\mathrm{reN}}\mathrm{ER}_{\mathrm{r}}^{\mathrm{E.Y}}}\ ,$$
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: 

$$\frac{\mathrm{EN}^{\cdot\mathrm{Y}}}{\sum_{\mathrm{r}\in\mathrm{N}}\mathrm{ER}_{\mathrm{r}}^{\mathrm{E.Y}}}$$
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:  

$$\mathbf{ER}_{\mathrm{r}}^{\mathrm{\scriptsize{\scriptsize{\boldmath~Y~}}}}=\lambda^{\mathrm{\scriptsize{\boldmath~Y~}}}(\alpha_{\mathrm{E}}^{\mathrm{\scriptsize{\scriptsize{\boldmath~E R}}}}{}_{\mathrm{r}}^{\mathrm{\scriptsize{\scriptsize{\boldmath~Y~}}}}+\alpha_{\mathrm{P}}^{\mathrm{\scriptsize{\scriptsize{\boldmath~Y~}}}}\mathbf{ER}_{\mathrm{r}}^{\mathrm{\scriptsize{\scriptsize{\boldmath~P.Y~}}}})$$
                                                        
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 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    |   Population aged 16 to 64  |   Exogenous Employment  |
|-----------|-----------------------------|-------------------------|
| number    |                             |                         |
| 1         |                        100  |                    110  |
| 2         |                        100  |                    110  |
| 3         |                        100  |                    110  |
| Total     |                        300  |                    330  |

 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    |   Population aged 16 to 64  |   Employment Forecast  |
|-----------|-----------------------------|------------------------|
| number    |                             |                        |
| 1         |                        100  |                   110  |
| 2         |                        100  |                   110  |
| 3         |                        100  |                   110  |
| Total     |                        300  |                   330  |

 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 "populationbased" forecast. By scaling the difference between the exogenous and population-based forecast, a new forecast is produced as follows: 

|   2001  |   2011  |   2001  |   2011  |
|---------|---------|---------|---------|
|   2001  |   2011  |   2001  |   2011  |
| Region    |   Population aged 16 to 64  |   Employment Forecast  |
|-----------|-----------------------------|------------------------|
| number    |                             |                        |
| 1         |                        100  |                   110  |
| 2         |                        100  |                   110  |
| 3         |                        100  |                   110  |
| Total     |                        300  |                   330  |

 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    |   Population aged 16 to 64  |   Employment Forecast  |
|-----------|-----------------------------|------------------------|
| number    |                             |                        |
| 1         |                        100  |                   110  |
| 2         |                        100  |                   110  |
| 3         |                        100  |                   110  |
| Total     |                        300  |                   330  |

 
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. 

|   2001  |   2011  |   2001  |   2011  |
|---------|---------|---------|---------|
|   2001  |   2011  |   2001  |   2011  |

## 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: 

$$\mathrm{EA}_{\mathrm{a}}^{\mathrm{Y}}=\lambda(\alpha_{\mathrm{E}}\mathrm{EA}_{\mathrm{a}}^{\mathrm{E.Y}}+\alpha_{\mathrm{p}}\mathrm{EA}_{\mathrm{a}}^{\mathrm{P.Y}})$$
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: 

$$\mathrm{E}\mathrm{A}_{\mathrm{a}}^{\mathrm{P.Y}}=\mathrm{E}\mathrm{A}_{\mathrm{a}}^{\mathrm{P.B}}\times{\frac{\mathrm{PR}_{\mathrm{r}}^{\mathrm{Y}}}{\mathrm{PR}_{\mathrm{r}}^{\mathrm{B}}}}{\mathrm{~for~each~a\inr~}}$$
This means that: 

$\sum\text{EA}_{\text{a}}^{\text{P},\text{Y}}=\sum\text{EA}_{\text{a}}^{\text{P},\text{B}}\times\frac{\text{PR}_{\text{r}}^{\text{Y}}}{\text{PR}_{\text{r}}^{\text{B}}}=\text{ER}_{\text{r}}^{\text{P},\text{B}}\times\frac{\text{PR}_{\text{r}}^{\text{Y}}}{\text{PR}_{\text{r}}^{\text{B}}}=\text{ER}_{\text{r}}^{\text{P},\text{Y}}$
and, given that also: 

$$\sum_{\mathrm{aer}}\mathrm{EA}_{\mathrm{a}}^{\mathrm{E.Y}}=\mathrm{ER}_{\mathrm{r}}^{\mathrm{E.Y}}$$
then: 

$$\sum_{\mathrm{a\in{\bf r}}}\mathrm{E}\mathrm{A}_{\mathrm{a}}^{\mathrm{.Y}}=\mathrm{E}\mathrm{R}_{\mathrm{r}}^{\mathrm{.Y}}$$
 

## 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. 

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. 

## 

Components of Growth Rates 
Additional Growth pa 
Employment Type and Description 
Short-term 
Long-term 
Underlying Data Category used (Age group/GDP) 
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% 

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); 

" 
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: 

$$\mathbf{EN}_{s}^{\mathrm{W.Y}}=\mathbf{EN}_{s}^{\mathrm{W.B}}\times{\frac{\mathbf{PN}^{\mathrm{Y}}}{\mathbf{PN}^{\mathrm{B}}}}\times\mathbf{K}_{.s}^{\mathrm{B.Y}}$$
where: 

B 
is the base year; 
Y
Y
PN
 
is national working-age population, hence 
B
PN
PN
 is growth in working age 
population between the base year B and year Y.   
Y
The factor 
B
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 workforcebased 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 longterm 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. 

Components of Growth Rates 
Additional Growth pa 
Employment Type and Description 
Short-term 
Long-term 
Underlying Data Category used 
(Age group) 
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 populationbased 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: 

$$\mathrm{EN}_{s}^{\mathrm{Y}}=\mu^{\mathrm{Y}}\!\left({\frac{\mathrm{d}^{\mathrm{W.Y}}\mathrm{EN}_{s}^{\mathrm{C.Y}}+\mathrm{d}^{\mathrm{C.Y}}\mathrm{EN}_{s}^{\mathrm{W.Y}}}{\mathrm{d}^{\mathrm{W.Y}}+\mathrm{d}^{\mathrm{C.Y}}}}\right)$$

$$\mathbf{\mu}_{s}^{\mathrm{{.Y}}}=\mu^{\mathrm{{Y}}}{\Bigg(}{\frac{\mathbf{d}^{\mathrm{{W.Y}}}\mathbf{E N}_{s}^{\mathrm{{C.Y}}}+\mathbf{d}^{\mathrm{{C.Y}}}\mathbf{E N}_{s}^{\mathrm{{W.Y}}}}{\mathbf{d}^{\mathrm{{W.Y}}}+\mathbf{d}^{\mathrm{{C.Y}}}}}{\Bigg)}$$
where: 

Y
.
C
d
 
This is the absolute "distance" of the Customer employment forecasts, 
aggregated over all sectors, from 
Y
.
EN
, ie: 
Y
.

            Y
            .
           C
           s
           .
  Y
 .
 C
               EN
        EN
d
              
    ¦
                     

s

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

 ¦
 
s
Y
.
s
.
Y
.
EN
EN
. It is analogous to 
Y
O  in 
Y
P  
is a scaling parameter to ensure that 
¦
 
s
Step 1. 

## 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: 

$$\mathbf{E}\mathbf{R}_{\mathrm{r.s}}^{\mathrm{L.Y}}=\mathbf{E}\mathbf{R}_{\mathrm{r.s}}^{\mathrm{B}}\times\mathbf{V}\mathbf{R}_{\mathrm{r.s}}^{\mathrm{B.Y}}\times\mathbf{M}_{\mathrm{s}}^{\mathrm{B.Y}}$$
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 customerbased 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. 

Components of Growth Rates 
Additional Growth pa 
Employment Type and Description 
Customer/ Employee Forecast used 
Underlying Data Category used (Age group/GDP) 
Shortterm 
Longterm 
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: 

$$\mathbf{E}\mathbf{R}_{\mathrm{r.s}}^{\cdot\mathrm{Y(n,1)}}=\mathbf{E}\mathbf{R}_{\mathrm{r.s}}^{\cdot\mathrm{Y(n-1,2)}}\times{\frac{\mathbf{E}\mathbf{N}_{\mathrm{s}}^{\cdot\mathrm{Y}}}{\sum_{\mathrm{r},\mathrm{s}}\mathbf{E}\mathbf{R}_{\mathrm{r.s}}^{\cdot\mathrm{Y(n-1,2)}}}}$$

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

$\begin{array}{c}\mbox{ER}_{\rm r,s}^{\rm Y(n,2)}=\mbox{ER}_{\rm r,s}^{\rm Y(n,1)}\times\mbox{ER}_{\rm r}^{\rm Y}\\ \mbox{ER}_{\rm r,s}^{\rm Y(n,1)}\end{array}$
This Furnessing procedure reaches a tight tolerance level in very few iterations. 

## 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: 

$$\mathrm{E}\mathrm{A}_{\mathrm{a.s}}^{\mathrm{L.Y}}=\mathrm{E}\mathrm{A}_{\mathrm{a.s}}^{\mathrm{B}}\times\mathrm{V}\mathrm{A}_{\mathrm{a.s}}^{\mathrm{B.Y}}\times\mathrm{M}_{\mathrm{s}}^{\mathrm{B.Y}}$$
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: 

$$\mathrm{{EA}}_{\mathrm{a.s}}^{\mathrm{{\scriptsize{Y(0,2)}}}}=\mathrm{{EA}}_{\mathrm{a.s}}^{\mathrm{{\scriptsize{L.Y}}}}$$
Then for n=1,2,3…, two new employment forecasts are constructed as follows: 

$$\mathrm{EA}_{a.s}^{.Y(n,1)}=\mathrm{EA}_{a.s}^{.Y(n-1,2)}\times{\frac{\mathrm{ER}_{r,s}^{.Y}}{\sum_{a\in r}\mathrm{EA}_{a.s}^{.Y(n-1,2)}}}$$

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

$$\mathrm{EA}_{\mathrm{a.s}}^{\mathrm{\scriptsize{Y(n,2)}}}=\mathrm{EA}_{\mathrm{a.s}}^{\mathrm{\scriptsize{Y(n,1)}}}\times\frac{\mathrm{EA}_{\mathrm{a}}^{\mathrm{\scriptsize{Y}}}}{\sum_{\mathrm{s}}\mathrm{EA}_{\mathrm{a.s}}^{\mathrm{\scriptsize{Y(n,1)}}}}$$