Barnsley Demographic Analysis & Forecasts

Assumptions, Methodology & Scenario Results

September 2014

For the attention of: Paula Tweed Barnsley Council

www.edgeanalytics.co.uk

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Contact Details

Edge Analytics Ltd.

Leeds Innovation Centre 103 Clarendon Road Leeds LS2 9DF

0113 384 6087 www.edgeanalytics.co.uk

Acknowledgements

Demographic statistics used in this report have been derived from data from the Office for

National Statistics licensed under the Open Government Licence v.1.0.

The authors of this report do not accept liability for any costs or consequential loss involved following the use of the data and analysis referred to here, which is entirely the responsibility of the users of the information presented in this report.

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Table of Contents

Contact Details ........................................................................................................................ i

Acknowledgements ................................................................................................................. i

Table of Contents ....................................................................................................................ii

1. Introduction .................................................................................................................... 1

2. Barnsley: Area Profile ...................................................................................................... 5

3. Scenario Development ................................................................................................... 11

4. Scenario Outcomes......................................................................................................... 19

5. Summary ....................................................................................................................... 25

POPGROUP Methodology ................................................................................. 28 Appendix A

Data Inputs & Assumptions .............................................................................. 31 Appendix B

Glossary of Terms ............................................................................................. 43 Appendix C

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1. Introduction

Context & Requirements

Context

The adopted Core Strategy1 for Barnsley made provision for 21,500 new homes between 2008 1.1

and 2026. This requirement was based on the now-revoked Regional Spatial Strategy (RSS).

Barnsley Metropolitan Borough Council (BMBC) is in the process of preparing its Local Plan, which

will involve an update to its 2013 Strategic Market Housing Assessment (SHMA).

Since the Core Strategy and the 2013 SHMA were produced, new demographic evidence has 1.2

become available:

2011 Census statistics from the Office for National Statistics (ONS), including economic

activity rates and commuting statistics.

Revised mid-year population estimates for the period 2002–2010.

2011-based household projections from the Department for Communities and Local

Government (DCLG).

2012 and 2013 mid-year population estimates for Barnsley.

The 2012-based sub-national population projection (SNPP) for Barnsley.

Government Planning Practice Guidance (PPG) has also been finalised, providing guidelines on 1.3

the approach to assessing housing need.

1https://www.barnsley.gov.uk/media/Development%20-

%20Planning%20and%20Transportation/Planning%20Policy/LDF/Core%20Strategy%20Submission/Adopted%20Core%20Strategy.pdf

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Requirements

Given the situation with regard to the revocation of the RSS and the availability of new 1.4

demographic information, BMBC has commissioned Edge Analytics to produce an updated suite

of population and household forecasts for the 2014–2033 plan period, using the latest

demographic inputs and updated economic assumptions.

The forecasts should include the latest official population projection, the 2012-based SNPP and 1.5

jobs-led scenarios, in which the demographic implications of jobs growth scenarios are evaluated.

Approach

Official Guidelines

The development and presentation of demographic evidence to support local housing plans is 1.6

subject to an increasing degree of public scrutiny. The National Planning Policy Framework

(NPPF)2 and Planning Practice Guidance (PPG)3 provide guidance on the appropriate approach to

the objective assessment of housing need.

These advocate that ‘official’ statistics should provide a starting point for the evaluation of 1.7

growth scenarios and that local circumstances, alternative assumptions and the most recent

demographic evidence should be considered (PPG paragraphs 2a-015 and 2a-017). Evidence that

links demographic change to forecasts of economic growth should also be assessed (PPG

paragraph 2a-018).

The use of demographic models, which enable a range of growth scenarios to be evaluated, is 1.8

now a key component of the objective assessment process. The POPGROUP suite of demographic

models, which is widely used by local authorities and planners across the UK, provides a robust

and appropriate forecasting methodology (for further information on POPGROUP, refer to

Appendix A).

2 http://planningguidance.planningportal.gov.uk/blog/policy/ 3 http://planningguidance.planningportal.gov.uk/blog/guidance/

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The choice of assumptions used within POPGROUP has an important bearing on scenario 1.9

outcomes. This is particularly the case when trend projections are considered alongside

population and household forecasts that are linked directly to anticipated jobs growth. The

scrutiny of demographic assumptions is now a critical component of the public inspection

process, providing much of the debate around the appropriateness of a particular objective

assessment of housing need.

Edge Analytics Approach

In accordance with the PPG, Edge Analytics has used POPGROUP (v.4) technology to develop a 1.10

range of growth scenarios for Barnsley. As the ‘starting point’ of this assessment, the 2012-based

SNPP for Barnsley District is presented, with an analysis of the ‘components of change’

underlying this new projection; these statistics are compared to previous estimates and to the

historical data on births, deaths and migration.

A number of alternative scenarios have been developed and are compared to the 2012-based 1.11

SNPP ‘benchmark’ and the earlier 2010-based SNPP. The alternative scenarios include ‘trend’

scenarios, based on varying migration assumptions, and ‘jobs-led’ scenarios, which are driven by

growth in the number of jobs.

In all the scenarios, historical data are included for the 2001–2013 period. Scenario results are 1.12

presented for Barnsley’s 2014–2033 plan period.

The household growth implications of each scenario are assessed using assumptions from both 1.13

the 2008-based and 2011-based household projection models from the DCLG.

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Report Structure

The report is structured in the following way: 1.14

In Section 2, a profile of Barnsley is presented. This includes an historical perspective

on population change since the 2001 Census and analysis of the ‘components of

change’ from the 2012-based SNPP.

In Section 3, a definition of each scenario is presented, with the outcome of these

scenarios detailed in Section 4.

Section 5 summarises the analysis and identifies a number of key issues for

consideration in the development of the SHMA and BMBC’s preparation of its Local

Plan.

Appendix A presents an overview of the POPGROUP methodology.

Appendix B provides detail on the data inputs and assumptions used in the

development of the POPGROUP scenarios.

Appendix C provides a glossary of terms.

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2. Barnsley: Area Profile

The development of local housing plans is made considerably more challenging by the dynamic 2.1

nature of key data inputs. Economic and demographic factors, coupled with the continuous

release of new statistics, often undermine the robustness of underpinning evidence. This has

been a particular issue since 2012, with the release of 2011 Census statistics, revisions to

historical population estimates and updated population and household projections.

This section provides an overview of population change in Barnsley since 2001 and the recent 2.2

revisions to the mid-year population estimates (MYEs). Also presented is the most recent

population projection from ONS, the 2012-based SNPP and its constituent ‘components of

change’.

Population Change 2001–2011

Mid-Year Population Estimates

Between successive Censuses, population estimation is necessary. These mid-year population 2.3

estimates (MYEs) are derived by applying the ‘components of change’ (i.e. counts of births and

deaths and estimates of internal and international migration) to the previous year’s MYE.

Following the 2011 Census, the 2002–2010 MYEs were ‘rebased’ to align them with the 2011

MYE4 and to ensure the correct transition of the age profile of the population over the 2001–

2011 decade.

At the 2011 Census, the resident population of Barnsley was 231,221, a 6.0% increase over the 2.4

2001–2011 decade. The 2011 Census population total proved to be higher than that suggested by

the trajectory of growth from the previous MYEs. For this reason, the revised final MYEs are

higher than the ‘previous’ MYEs, with the difference increasing over time (Figure 1).

4 Revised Annual Mid-year Population Estimates, 2001 to 2010. ONS, December 2013

http://www.ons.gov.uk/ons/dcp171778_345500.pdf

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Figure 1: Barnsley – mid-year population estimates (source: ONS)

Components of Change

The rebasing of the MYEs involved the recalibration of the components of change for 2.5

2001/02–2010/11. Between Censuses, births and deaths are accurately recorded in vital statistics

registers and provide a robust measure of ‘natural change’ (the difference between births and

deaths) in a geographical area. Given that births and deaths are robustly recorded, and assuming

that the 2001 Census provided a robust population count, the 'error' in the MYEs is due to the

difficulties associated with the estimation of migration.

Internal migration is adequately measured through the process of GP registration, although data 2.6

robustness may be lower where there is under-registration in certain age-groups (young males in

particular). It is therefore most likely that the ‘error’ in the previous MYEs was associated with

the mis-estimation of international migration, i.e. the balance between immigration and

emigration flows to and from Barnsley.

However, ONS has not explicitly assigned the MYE adjustment to international migration. Instead 2.7

it has identified an additional ‘unattributable population change’ (UPC) component, suggesting it

has not been able to accurately identify the source of the 2001–2011 under-count (Figure 2). The

effect of the UPC adjustment depends upon the scale of population recalibration that has been

required following the 2011 Census results. For Barnsley, the population estimates have been

subject to a consistent annual uplift due to the under-count experienced over the 2001–2011

decade.

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Figure 2: Barnsley – components of population change 2001/02 to 2012/13 (source: ONS). No UPC component is applied to the 2011/12 or 2012/13 statistics as these relate to the 2012 MYE which followed the 2011 Census.

For demographic analysis, the classification of UPC is unhelpful, but given the robustness of 2.8

births, deaths and internal migration statistics compared to international migration estimates, it

is assumed that it is most likely to be associated with the latter. With the assumption that the

UPC element is assigned to international migration (for estimates up to 2011), and with the

inclusion of statistics from the 2012 and 2013 MYEs from ONS, an twelve-year profile of the

‘components of change’ for Barnsley is presented (Figure 3).

Figure 3: Barnsley – components of population change 2001/02 to 2012/13 including the UPC component (source: ONS).

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Between 2001/02 and 2003/04 natural change in Barnsley was negative, however over the 2.9

2004/05–2012/13 period natural change was positive as the number of births exceeded the

number of deaths. Net internal and international migration remained positive throughout the

2001/02–2012/13 historical period.

Official Population Projections

In the development and analysis of population forecasts, it is important to benchmark any 2.10

growth alternatives against the latest ‘official’ population projection. The most recent official

subnational population projection is the ONS 2012-based SNPP, released in May 20145. This

projection is compared to the earlier ONS population projections for Barnsley in Figure 4.

Figure 4: Official Projections for Barnsley (source: ONS).

The 2012-based SNPP has a lower rate of growth than the earlier official projections (apart from 2.11

the 2004-based SNPP). Under the 2012-based SNPP, the population of Barnsley is projected to

increase by 31,037 over the 2012–2037 projection period, a 13.3% increase. Under the 2010-

5 2012-based SNPP for England, ONS, 29th May 2014 http://www.ons.gov.uk/ons/dcp171778_363912.pdf

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September 2014

based SNPP, the population was projected to increase by 15.7% over the 25-year projection

period (2010–2035).

The 2012-based SNPP components of change are presented in Figure 5, with the historical 2.12

components of change for 2001/02 to 2011/12 included for comparison. The annual average

natural change, net migration (internal and international) and population change for the 2012-

based SNPP are compared to the historical 5-year and 10-year averages in Table 1.

Figure 5: Historical and 2012-based SNPP components of change for Barnsley (source: ONS).

Table 1: 2012-based SNPP components comparison (source: ONS)

Historically, over both the 5-year and 10-year periods, average net internal and international 2.13

migration have been positive (Table 1). In the 2012-based SNPP, net internal and net

international migration continue to be dominant components of population change, although the

estimated future impact of international migration is reduced compared to recent historical

Natural Change

Net Internal Migration

Net International Migration

Unattributable Population Change*

Annual Population Change

Annual Population Change (%)

* UPC is only applicable to the years 2001/02 - 2010/11

10-year average

(2002/03–2011/12)

2012-based SNPP

average

(2012/13–2036/37)

573

229

-

5-year average

(2007/08–2011/12)

Historical Projected

558

536

320

123

439

0.68%

313

741

268

163

1,482

0.68%

1,241

0.53%

Component of Change

1,537

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evidence, in line with ONS’ national assumption on immigration and emigration. The projected

reduction in the net effect of international migration means that the 2012-based SNPP’s annual

growth forecast is below the 5-year and 10-year history. Natural change continues to be positive

throughout the forecast period, at a lower rate than over the 5-year historical period, but higher

than over the 10-year period.

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3. Scenario Development

Introduction

There is no single definitive view on the likely level of growth expected in Barnsley; a mix of 3.1

economic, demographic and national/local policy issues ultimately determines the speed and

scale of change. For local planning purposes, it is necessary to evaluate a range of growth

alternatives to establish the most ‘appropriate’ basis for determining future housing provision.

Edge Analytics has used POPGROUP (v.4) technology to develop a range of growth scenarios for 3.2

Barnsley (for detail on the POPGROUP methodology, refer to Appendix A). Eight ‘core’ scenarios

have been produced, including the most recent official population projection from ONS, the

2012-based SNPP. The 2010-based SNPP is also included for comparison. Three alternative trend-

based scenarios have also been developed, together with three jobs-led scenarios, in which

population growth is linked definitively to jobs-growth forecasts.

Additional jobs-led ‘sensitivity’ scenarios have been produced to evaluate how changes to 3.3

Barnsley’s commuting ratio and its overall rate of economic activity might influence dwelling-

growth outcomes.

In the following sections, the core and sensitivity scenarios are described and the broad 3.4

assumptions specified. For further detail on the data inputs and assumptions, please refer to

Appendix B.

Core Scenario Definition

Official Projections

In accordance with the PPG, the alternative scenarios are ‘benchmarked’ against the most recent 3.5

official population projections from the ONS, the ONS 2012-based SNPP. The ‘SNPP-2012’

scenario replicates this official population projection.

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The ‘SNPP-2010’ scenario, which replicates the ONS 2010-based SNPP for Barnsley, is included 3.6

for comparison. The population is re-scaled to the 2012 MYE to ensure consistency with the

2012-based SNPP and the 2010-based growth trajectory is continued thereafter.

Alternative Trend Scenarios

A five year historical period is a typical time-frame from which migration ‘trend’ assumptions are 3.7

derived (this is consistent with the ONS official methodology). Given the unprecedented

economic change that has occurred since 2008, it is important to give due consideration to an

extended historical time period for assumption derivation.

Three alternative trend scenarios have been developed, based upon the latest demographic 3.8

evidence:

‘PG-5yr’: internal migration rates and international migration flow assumptions are

based on the last five years of historical evidence (2008/09 to 2012/13), with the UPC

adjustment included within the international migration assumptions.

‘PG-10yr’: internal migration rates and international migration flow assumptions are

based on the last 10 years of historical evidence (2003/04 to 2012/13), with the UPC

adjustment included within the international migration assumptions.

‘Natural Change’: internal and international migration rates are set to zero. This

scenario is hypothetical, but provides an indication of the degree to which dwelling

growth is driven by natural change (i.e. the balance between births and deaths).

Jobs-led Scenarios

In a ‘jobs-led’ scenario, population growth is determined by the number of jobs available within 3.9

an area. POPGROUP evaluates the impact of a particular jobs growth trajectory by measuring the

relationship between the number of jobs in an area, the size of the labour force and the size of

the resident population. Migration is used to balance the relationship between the size of the

population’s labour force and the forecast number of jobs. A higher level of net in-migration will

occur if there is insufficient population and resident labour force to meet the forecast number of

jobs. A higher level of net out-migration will occur if the population is too high relative to the

forecast number of jobs.

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Three jobs-led scenarios have been developed: 3.10

‘Jobs-led - Policy Off’: BMBC’s ‘Policy Off’ scenario is based on the latest jobs forecast

from the Yorkshire and Humber Regional Econometric Model (REM). Jobs growth

targets are applied from 2013/14, with the number of FTE jobs in Barnsley increasing

by +10,967 to 2032/33.

‘Jobs-led - Policy On’: BMBC’s ‘Policy On’ scenario considers a substantial uplift in the

jobs growth anticipated by the ‘Policy Off’ position; an additional 17,713 to the total

number of jobs over the forecast period. Jobs-growth targets are applied from

2013/14 with the number of FTE jobs in Barnsley increasing by +28,689 to 2032/33.

‘Jobs-led - Mid’: A final jobs-led scenario considers a level of jobs growth that is the

‘average’ of the ‘Policy On’ and ‘Policy Off’ position identified by BMBC. Its growth

targets are applied from 2013/14 with the number of FTE jobs in Barnsley increasing by

+19,833 to 2032/33.

Figure 6: Jobs growth forecasts (FTEs) for Barnsley (source: BMBC)

Three key data inputs are required to run the jobs-led scenario and link jobs growth to 3.11

population change; economic activity rates by age and gender for each year of the forecast

period; a corresponding unemployment rate to estimate that portion of the labour force that

remains out of work; and a commuting ratio, which estimates the balance between the number

of jobs available and the size of the resident labour force.

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In the ‘core’ scenarios, economic activity rates (from the 2011 Census) by 5-year age group and 3.12

sex are applied. Uplifts have been applied in the 60–69 age groups for both men and women to

account for changes to the State Pension Age (SPA).

A commuting ratio of 1.25 is applied, derived from 2011 Census Travel-to-Work statistics. This 3.13

ratio, indicating a net out-commute, is kept fixed throughout the forecast period.

The unemployment rate has been incrementally reduced over the 2014–2033 forecast period to 3.14

account for economic recovery following the recession.

For detail on the economic activity rate, unemployment rate and commuting ratio assumptions 3.15

used in the core scenarios, refer to Appendix B.

Household & Dwelling Growth

In each of the scenarios, the implied number of households is derived using household headship 3.16

rates, from both the 2008-based and 2011-based DCLG household models. This is in recognition

of the uncertainty associated with future rates of household formation, given economic and

demographic conditions.

The 2011-based headship rates were calibrated after a period of unprecedented economic 3.17

change and stagnation in the housing market and thus suggest a lower rate of household

formation than the previous 2008-based rates, calibrated from data collected in a time period

with very different market characteristics. Assessing the household growth implications of a

population projection using solely the 2011-based rates can be criticised as being overly

dependent upon a period where household formation rates have been supressed. Conversely,

exclusive use of 2008-based rates can be criticised as being influenced by rates of household

formation associated with pre-recessionary conditions that are unlikely to be repeated in the

immediate future.

The 2011-based headship rates and the 2008-based headship rates are therefore applied to each 3.18

scenario, producing an ‘Option A’ and an ‘Option B’ outcome:

In ‘Option A’, the DCLG 2011-based headship rates are applied, with the 2011–2021

trend continued after 2021;

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In the ‘Option B’ alternative, the DCLG 2008-based headship rates are applied, scaled

to be consistent with the 2011 DCLG household total but following the original trend

thereafter.

This approach presents a ‘range’ of household growth outcomes for each population forecast. 3.19

The dwelling growth implications of these different household growth trajectories are then

assessed through the application of a ‘vacancy rate’ (refer to Appendix B for further information

on the household and dwelling assumptions). The ‘Option A’ and ‘Option B’ dwelling

requirements are then averaged to provide an annual dwelling requirement for each scenario.

Sensitivity Scenario Definition

In the jobs-led scenarios described above, population and dwelling growth is determined by the 3.20

defined jobs-growth trajectory using key assumptions on economic activity rates, the

unemployment rate and the commuting ratio.

In the ‘core’ jobs-led scenarios, the commuting ratio for Barnsley is fixed (at 1.25) throughout the 3.21

forecast period, indicating a net outflow of workers to surrounding districts (i.e. the size of the

resident labour force is greater than the number of jobs available in the district).

In recognition that jobs-growth in Barnsley will likely lead to changes to commuting patterns, 3.22

three alternative commuting ratio sensitivities on the ‘Jobs-led - Policy On’ scenario have been

developed, in which the commuting ratio is incrementally reduced over the 2013–2033 forecast

period. This results in a more balanced relationship between the number of jobs available in

Barnsley and the size of the resident labour force:

‘Jobs-led CR1’: the commuting ratio reduces incrementally from the 2011 Census ratio

of 1.25 to the 2001 Census ratio of 1.19.

‘Jobs-led CR2’: the commuting ratio reduces incrementally from the 2011 Census ratio

of 1.25 to a ratio of 1.095 (i.e. the mid-point between the 2001 position and a

‘balanced’ commuting ratio).

‘Jobs-led CR3’: the commuting ratio reduces incrementally from the 2011 Census ratio

of 1.25 to a ratio of 1.00 (i.e. a ‘balanced’ commuting ratio).

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In these sensitivities, the economic activity rate and unemployment rate assumptions remain 3.23

consistent with the core scenario.

Additionally, two sensitivity scenarios have been developed in which alternative economic 3.24

activity rate profiles are applied to the ‘Jobs-led - Policy On’ scenario, maintaining a lower

resident labour force in the district over the forecast period. The accompanying commuting ratio

and unemployment rate assumption remain consistent with the ‘core’ alternative scenarios:

‘Jobs-led EA1’: The overall economic activity rate for the labour force (aged 16–74) is

maintained at its base-year level of 66%.

‘Jobs-led EA2’: The overall economic activity rate for the labour force (aged 16–74)

achieves the base-year total for England (70%) by 2020.

A final sensitivity scenario combines the commuting ratio reduction of ‘CR1’ (reducing to its 2001 3.25

position by 2033), with the economic activity rate profile of ‘EA1’ (maintaining the aggregate

2011 rate):

‘Jobs-led CR1 EA1’: the commuting ratio reduces incrementally from the 2011 Census

ratio of 1.25 to the 2001 Census ratio of 1.19, whilst the overall economic activity rate

is maintained at its 2011 level.

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Scenario Summary

To summarise, eight ‘core’ scenarios have been produced (Table 2) under three scenario types; 3.26

official projections, alternative trend-based scenarios and jobs-led scenarios. Six additional

sensitivity scenarios have been developed (Table 3) to evaluate how the ‘Jobs-led - Policy On’

scenario outcomes are influenced by the choice of assumptions on commuting and economic

activity

Table 2: ‘Core’ scenario definition

Scenario Type Scenario Name Scenario Description

Official Projections

‘SNPP-2012’ This scenario mirrors the 2012-based SNPP from ONS for Barnsley. This scenario is the official ‘benchmark’ scenario.

‘SNPP-2010’

This scenario mirrors the 2010-based SNPP from ONS for Barnsley. The population is re-scaled to the 2012 MYE to ensure consistency with the 2012-based SNPP and the 2010-based growth trajectory is continued thereafter.

Alternative trend-based scenarios

‘Natural Change’ In- and out- migration rates are set to zero.

‘PG-5yr’ Internal and international migration assumptions are based on the last five years of historical evidence (2008/09 to 2012/13).

‘PG-10yr’ Internal and international migration assumptions are based on the last 10 years of historical evidence (2003/04 to 2012/13).

Jobs-led scenarios

‘Jobs-led - Policy Off’

Population growth is determined by the annual change in the number of jobs, as defined by the ‘Policy Off’ jobs forecast (a total increase of +10,976 FTE jobs 2013/14–2032/33).

‘Jobs-led - Policy On’

Population growth is determined by the annual change in the number of jobs, as defined by BMBC’s ‘Policy On’ FTE jobs forecast (a total increase of +28,689 FTE jobs 2013/14–2032/33).

‘Jobs-led - Mid’

Population growth is determined by the annual change in the number of jobs, as defined by the ‘mid-point’ between the ‘Policy Off’ and ‘Policy On’ FTE jobs forecast (a total increase of +19,833 jobs 2014/15–2032/33).

Note: Refer to Appendix B for further information on the scenario data inputs and assumptions

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Table 3: ‘Sensitivity’ scenario definition

Scenario Type Scenario Name

Scenario Description

Commuting Ratio Sensitivities

‘Jobs-led CR1’

Commuting ratio incrementally decreases from the 2011 Census commuting ratio (1.25) to the 2001 Census commuting ratio (1.19) over the 2013–2033 forecast period. Economic activity rate and unemployment rate assumptions are consistent with the ‘core’ jobs-led scenarios.

‘Jobs-led CR2’

Commuting ratio incrementally decreases from the 2011 Census commuting ratio (1.25) to 1.095 over the 2013–2033 forecast period. Economic activity rate and unemployment rate assumptions are consistent with the ‘core’ jobs-led scenarios.

‘Jobs-led CR3’

Commuting ratio incrementally decreases from the 2011 Census commuting ratio (1.25) to 1.00 over the 2013–2033 forecast period. Economic activity rate and unemployment rate assumptions are consistent with the ‘core’ jobs-led scenarios.

Economic Activity Rate Sensitivities

‘Jobs-led EA1’

The overall rate of economic activity for the labour force (aged 16–74) is maintained at its base-year level (66%). Commuting ratio and unemployment rate assumptions are consistent with the ‘core’ jobs-led scenarios.

‘Jobs-led EA2’

EA rates are altered to reach England’s base-year economic activity rate (70%) by 2020. Economic activity rates are then fixed for the remainder of the forecast period. Commuting ratio and unemployment rate assumptions are consistent with the ‘core’ jobs-led scenarios.

Commuting Ratio and Economic Activity Rate Sensitivity

‘Jobs-led CR1 EA1’

Commuting ratio incrementally decreases from the 2011 Census commuting ratio to the 2001 Census commuting ratio over the 2013–2033 forecast period. The overall rate of economic activity for the labour force (aged 16–74) is maintained at the base-year level (66%). Unemployment rate assumptions are consistent with the ‘core’ jobs-led scenarios.

Note: Refer to Appendix B for further information on the scenario data inputs and assumptions

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4. Scenario Outcomes

Introduction

Eight ‘core’ scenarios have been developed for Barnsley using POPGROUP technology. All 4.1

scenarios have been run using household growth assumptions from both the 2011-based DCLG

household model and the 2008-based household model. The results are therefore presented

under an ‘Option A’ and an ‘Option B’ outcome:

In ‘Option A’, the DCLG 2011-based headship rates have been applied, with the 2011–

2021 trend continued after 2021;

In the ‘Option B’ alternative, the DCLG 2008-based headship rates have been applied,

scaled to be consistent with the 2011 DCLG household total but following the original

trend thereafter.

The results are presented in the form of a chart and a table for the 2014–2033 plan period. The 4.2

charts illustrate the trajectory of population change resulting from each scenario. The tables

summarise the population and household growth outcomes for each scenario, ranked in order of

population growth. The tables also show the estimated average annual net migration associated

with the population change, the expected average annual jobs growth and the expected dwelling

growth.

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Barnsley: ‘Core’ Scenario Outcomes

Figure 7: Barnsley ‘core’ scenario outcomes: population growth 2001–2033

Table 4: Barnsley ‘Option A’ core scenario outcomes 2014–2033

Table 5: Barnsley 'Option B' core scenario outcomes 2014–2033

Scenario Population

Change

Population

Change %

Households

Change

Households

Change %

Net

MigrationDwellings Jobs

Jobs-led - Policy On (A) 81,366 34.0% 35,438 34.0% 3,342 1,944 1,439

Jobs-led - Mid (A) 59,201 24.7% 26,887 25.8% 2,331 1,475 973

Jobs-led - Policy Off (A) 37,016 15.5% 18,308 17.5% 1,316 1,004 507

PG-10Yr (A) 31,121 13.1% 16,490 15.9% 1,093 904 366

PG-5Yr (A) 28,043 11.8% 15,268 14.7% 958 837 299

SNPP-2010 (A) 28,009 11.8% 14,815 14.3% 1,019 813 385

SNPP-2012 (A) 24,602 10.4% 13,209 12.8% 803 725 256

Natural Change (A) 7,111 3.0% 4,892 4.7% 0 268 -142

Change 2014 –2033 Average per year

Scenario Population

Change

Population

Change %

Households

Change

Households

Change %

Net

MigrationDwellings Jobs

Jobs-led - Policy On (B) 81,366 34.0% 38,756 37.1% 3,342 2,126 1,439

Jobs-led - Mid (B) 59,201 24.7% 30,066 28.7% 2,331 1,649 973

Jobs-led - Policy Off (B) 37,016 15.5% 21,347 20.4% 1,316 1,171 507

PG-10Yr (B) 31,121 13.1% 19,518 18.7% 1,093 1,071 366

PG-5Yr (B) 28,043 11.8% 18,319 17.6% 958 1,005 299

SNPP-2010 (B) 28,009 11.8% 17,644 17.0% 1,019 968 385

SNPP-2012 (B) 24,602 10.4% 16,197 15.6% 803 888 256

Natural Change (B) 7,111 3.0% 7,733 7.5% 0 424 -142

Change 2014–2033 Average per year

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Core Scenario Outcomes

Official Projections & Trend Scenarios

Excluding the hypothetic ‘Natural Change’ scenario, population growth ranges from 10.4% under 4.3

the ‘SNPP-2012’ scenario to 34.0% under the ‘Jobs-led - Policy On’ scenario. These population

growth figures result in a range of dwelling requirements, from 725–1,944 dwellings per year

under ‘Option A’ (using the 2011-based headship rates) to 888–2,126 under ‘Option B’ (using the

2008-based headship rates).

Population growth under the ‘SNPP-2012’ scenario (10.4%) is lower than under the previous 4.4

official projection, the ‘SNPP-2010’ (11.8%). The ‘SNPP-2012’ scenario results in an annual

average dwelling requirement of 725 dwellings per year under ‘Option A’ and 888 dwellings per

year under ‘Option B’. Under the ‘SNPP-2010’ scenario, the dwelling requirement is higher,

ranging from 813 to 968 dwellings per year (‘Option A’ and ‘Option B’ respectively).

The differences between the ‘SNPP-2012’ and the ‘SNPP-2010’ growth trajectories are a 4.5

reflection of the historical data that were used to calculate future assumptions. The 2010-based

SNPP projection from ONS was produced using the now out-dated ‘previous’ MYEs. As it uses

‘old’ data, the age profile of the 2010-based SNPP projection differs from that of the 2012-based

SNPP projection and the other scenarios presented here, which were formulated using the latest,

updated MYEs for Barnsley.

The ‘Natural Change’ scenario, in which net migration is set to zero for each year of the forecast 4.6

period (2014–2033), results in 3.0% population growth, driven solely by the balance between

births and deaths. The ‘Natural Change’ scenario is hypothetical, but does provide an important

indication of the degree to which dwelling growth is driven by natural change in Barnsley. The

annual average dwelling requirement ranges from 268 dwellings per year under ‘Option A’ to 424

dwellings per year under ‘Option B’.

The ‘PG’ scenarios provide alternative ‘trend’ scenarios. Of the two, the highest growth trajectory 4.7

is suggested by the ‘PG-10yr’ scenario, showing 13.1% growth in population over the forecast

period. Under the ‘PG-5yr’ scenario, population growth is lower, at 11.5% over the forecast

period. The ‘PG-10yr’ scenario results in an expected dwelling growth of 904 under ‘Option A’

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and 1,071 under ‘Option B’. The ‘PG-5yr’ scenario results in a lower expected dwelling growth

ranging from 837–1,005 (‘Option A’ and ‘Option B’ respectively).

The ‘PG’ scenarios result in higher population growth than the ‘SNPP-2012’. The ‘PG’ scenarios 4.8

incorporate fertility and mortality assumptions that are consistent with the ‘SNPP-2012’ but

differ in their calibration of future migration assumptions. For internal migration, both a five-year

(‘PG-5yr’) and a ten-year (‘PG-10yr’) history is used to calibrate migration assumptions, compared

to the five years typically used in the ‘SNPP-2012’. In addition, the ‘PG’ scenarios use the latest,

2013 MYE in the calibration process, an additional year of historical evidence compared to the

‘SNPP-2012’.

With regard to future international migration assumptions, the ‘PG’ scenarios consider both a 4.9

five-year and a ten-year perspective, plus they also incorporate the UPC adjustment to the

international migration estimates. ONS typically uses a five-year history for the calibration of

assumptions on international migration but this is scaled to ensure that the aggregate long-term

assumption on international migration for England, in total, is achieved. Significantly, the 2012-

based NPP for England has assumed a lower rate of long-term growth due to international

migration than has been recorded in the last five or ten years, even without the UPC adjustment.

Jobs-led Scenario

In the jobs-led scenarios, population growth is determined by the defined jobs-growth 4.10

trajectories using the key assumptions on economic activity rates, the unemployment rate and

the commuting ratio. Of the three jobs-led scenarios, population growth is highest under the

‘Jobs-led - Policy On’ scenario, at 34.0% over the forecast period. This level of population growth

results in a dwelling requirement of 1,944 dwellings per year under ‘Option A’ and 2,126

dwellings per year under ‘Option B’. Under the ‘Jobs-led - Mid’ scenario, population growth is

24.7%, resulting in expected dwelling growth ranging from 1,475–1,649 (‘Option A’ and ‘Option

B’ respectively). Under the ‘Jobs-led - Policy Off’ scenario, population growth is lower at 15.5%

over the forecast period. This results in lower expected annual dwelling growth of 1,004 under

‘Option A’ and 1,171 under ‘Option B’.

For each of the ‘core’ jobs-led scenarios the growth in the number of jobs results in more 4.11

substantial population growth, with higher net in-migration required to meet the labour force

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requirements, given the assumptions made on economic activity rates, unemployment and

commuting.

Sensitivity Scenario Outcomes

Given the scale of the population and dwelling growth implied by the jobs-led scenarios, it is 4.12

important to consider the sensitivity of these outcomes to changes in the key assumptions on

economic activity and commuting.

Six sensitivity scenarios have been produced with ‘Option A’ and ‘Option B’ dwelling 4.13

requirements presented for each, together with an average of the two.

Under the core ‘Jobs-led - Policy On’ alternative scenario, the average annual dwelling 4.14

requirement is 2,035 dwellings per year. This reduces to 1,758 dwellings per year under the ‘CR1’

sensitivity which reduces its commuting ratio to its 2001 Census level by the end of the forecast

period (Table 6). Reducing the net out-commute from Barnsley over the forecast period reduces

the need for additional net in-migration to satisfy the jobs-growth target, thereby reducing

population growth and the overall dwelling requirement.

More substantial changes to the commuting ratio reduce estimated dwelling growth further; to 4.15

an average of 1,319 in the ‘CR2’ sensitivity and to just 878 in the ‘CR3’ alternative. For the latter,

a balanced commuting ratio is implied by the end of the forecast period, with the number of jobs

in the district equivalent to the size of the resident labour force.

Table 6: Barnsley commuting ratio sensitivity scenarios: dwelling outcomes

Under the economic activity rate sensitivity scenarios (Table 7), increasing the overall rate of 4.16

economic activity again reduces the average annual dwelling requirement. By maintaining the

overall economic activity rate at its base-year level (66%), the ‘EA1’ scenario reduces the average

Option A Option B Average

Jobs-led - Policy On 1,944 2,126 2,035

Jobs-led - Policy On CR1 1,669 1,847 1,758

Jobs-led - Policy On CR2 1,233 1,405 1,319

Jobs-led - Policy On CR3 796 961 878

Average annual dwelling requirement (2014–2033)Scenario

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annual dwelling requirement to 1,920 dwellings per year. With higher rates of economic activity

the size of the labour force is maintained, reducing the need for additional net in-migration to

satisfy the defined jobs-growth target. Increasing the overall rate of economic activity to 70%

further reduces the dwelling requirement to 1,682 dwellings per year.

Table 7: Barnsley economic activity rate sensitivity scenarios: dwelling outcomes.

Combining the commuting ratio assumption from the ‘CR1’ scenario with the economic activity 4.17

rate assumptions from the ‘EA1’ scenario; results in an average annual dwelling requirement of

1,645 per year. Both the changing commuting ratio and the higher economic activity rates are

maintaining a larger local labour force, with a higher population living and working in Barnsley;

this reduces the overall dwelling growth requirement.

Table 8: Barnsley commuting ratio and economic activity rate sensitivity scenario: dwelling outcomes.

Option A Option B Average

Jobs-led - Policy On 1,944 2,126 2,035

Jobs-led - Policy On EA1 1,829 2,010 1,920

Jobs-led - Policy On EA2 1,591 1,773 1,682

ScenarioAverage annual dwelling requirement (2014–2033)

Option A Option B Average

Jobs-led - Policy On 1,944 2,126 2,035

Jobs-led - Policy On CR1 EA1 1,557 1,734 1,645

ScenarioAverage annual dwelling requirement (2014–2033)

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5. Summary

Requirements Summary & Approach

BMBC has commissioned Edge Analytics to provide an updated range of demographic scenarios 5.1

for Barnsley, using the latest demographic and economic assumptions.

Edge Analytics has produced a range of scenarios using POPGROUP v.4 technology; eight core 5.2

scenarios and six sensitivity scenarios. The 2012-based SNPP is included within this range of core

scenarios as the official benchmark scenario. Alternative trend-based scenarios have also been

developed, together with three ‘jobs-led’ scenarios, in which population growth is determined by

growth in the number of jobs.

In the ‘core’ scenarios, 2011 Census economic activity rates have been applied, with adjustments 5.3

made in the older age groups to account for changes to the SPA. A fixed commuting ratio (2011

Census) has been applied throughout the 2013–2033 forecast period. In all scenarios an

unemployment rate assumption has been applied to account for economic recovery following

the recession.

Three commuting ratio sensitivities have been produced to evaluate the potential impact of a 5.4

reduced net out-commute upon the dwelling growth anticipated with the ‘Jobs-led - Policy On’

scenario. The impact of an increase in the overall level of economic activity has also been

assessed in two further sensitivity scenarios.

In all scenarios (both core and sensitivity), household growth has been assessed using household 5.5

formation rates from the 2011-based and the 2008-based DCLG household models. Output for

each scenario has been presented under an ‘Option A’ and ‘Option B’ alternative, using the 2011-

based and 2008-based headship rates respectively.

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Scenario Outcomes

A summary of the annual average dwelling requirements for each of the scenarios (both core and 5.6

sensitivity) is presented in Table 9. In light of the uncertainty associated with future rates of

household formation, and the criticisms that can be applied when assessing household growth

using only the 2008-based or only the 2011-based rates, the resulting ‘Option A’ and ‘Option B’

dwelling requirements for each scenario are averaged.

Excluding the natural change outcome, this produces a dwelling requirement range of 806 under 5.7

the ‘SNPP-2012’ scenario to 2,035 under the ‘Jobs-led - Policy On’ scenario.

The sensitivity scenarios, applied to the core ‘Jobs-led - Policy On’ scenario, indicate the degree 5.8

to which changes to the assumptions on both commuting and economic activity might influence

dwelling growth outcomes.

Table 9: Barnsley scenario dwelling requirement summary. Sensitivity scenarios shaded in grey.

Note: ‘Option A’ shows the dwelling requirement derived using the 2011-based headship rates; ‘Option B’ using

the 2008-based headship rates. Scenarios are ranked in order of the average dwelling requirement.

Option A Option B Average

Jobs-led - Policy On 1,944 2,126 2,035

Jobs-led - Policy On EA1 1,829 2,010 1,920

Jobs-led - Policy On CR1 1,669 1,847 1,758

Jobs-led - Policy On EA2 1,591 1,773 1,682

Jobs-led - Policy On CR1 EA1 1,557 1,734 1,645

Jobs-led - Mid 1,475 1,649 1,562

Jobs-led - Policy On CR2 1,233 1,405 1,319

Jobs-led - Policy Off 1,004 1,171 1,087

PG-10Yr 904 1,071 987

PG-5Yr 837 1,005 921

SNPP-2010 813 968 890

Jobs-led - Policy On CR3 796 961 878

SNPP-2012 725 888 806

Natural Change 268 424 346

Average annual dwelling requirement (2014–2033)Scenario

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Issues for Consideration

This report provides a suite of demographic growth scenarios for BMBC to consider as it updates 5.9

its Strategic Housing Market Assessment (SHMA) and formulates the housing growth

requirements of its Local Plan.

Whilst the ‘SNPP-2012’ scenario provides the suggested starting point for the objective 5.10

assessment of housing need, the alternative ‘trend-based’ outcomes presented by the ‘PG-5yr’

and ‘PG-10yr’ scenarios should be given due consideration, given the likely impact of the

recession upon recent migration flows and given the continuing uncertainty with regard to future

international migration impacts.

Dwelling growth outcomes linked to Barnsley’s jobs growth forecasts have been presented, 5.11

including sensitivity scenario variants to illustrate the significant influence of commuting and

economic activity rate assumptions upon estimated future dwelling growth. It is recommended

that the full range of ‘Jobs-led’ scenario outcomes is considered when evaluating the additional

impact of economic change upon the objective assessment of housing need.

DCLG intends to release a 2012-based household model for English local authorities in autumn 5.12

2014. The implications of these new data and assumptions upon the household and dwelling

growth outcomes presented here will need to form part of the housing requirements evidence.

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Appendix A

POPGROUP Methodology

Forecasting Methodology

A.1 Evidence is often challenged on the basis of the appropriateness of the methodology that has

been employed to develop growth forecasts. The use of a recognised forecasting product which

incorporates an industry-standard methodology (a cohort component model) removes this

obstacle and enables a focus on assumptions and output, rather than methods.

A.2 Demographic forecasts have been developed using the POPGROUP suite of products. POPGROUP

is a family of demographic models that enables forecasts to be derived for population,

households and the labour force, for areas and social groups. The main POPGROUP model (Figure

8) is a cohort component model, which enables the development of population forecasts based

on births, deaths and migration inputs and assumptions.

A.3 The Derived Forecast (DF) model (Figure 9) sits alongside the population model, providing a

headship rate model for household projections and an economic activity rate model for labour-

force projections.

A.4 The latest development in the POPGROUP suite of demographic models is POPGROUP v.4, which

was released in January 2014. A number of changes have been made to the POPGROUP model to

improve its operation and to ensure greater consistency with ONS forecasting methods.

A.5 The most significant methodological change relates to the handling of internal migration in the

POPGROUP forecasting model. The level of internal in-migration to an area is now calculated as a

rate of migration relative to a defined ‘reference population’ (by default the UK population),

rather than as a rate of migration relative to the population of the area itself (as in POPGROUP

v3.1). This approach ensures a closer alignment with the ‘multi-regional’ approach to modelling

migration that is used by ONS.

A.6 For detail on the POPGROUP methodology, please refer to the POPGROUP v.4 user manual,

which can be found at the POPGROUP website: http://www.ccsr.ac.uk/popgroup/index.html

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Figure 8: POPGROUP population projection methodology.

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Figure 9: Derived Forecast (DF) methodology

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Appendix B

Data Inputs & Assumptions

Introduction

B.1 Edge Analytics has developed a suite of demographic scenarios for Barnsley using POPGROUP.

B.2 The POPGROUP model draws data from a number of sources, building an historical picture of

population, households, fertility, mortality and migration on which to base its scenario forecasts.

Using the historical data evidence for 2001–2013, in conjunction with information from ONS sub-

national projections, a series of assumptions have been derived which drive the scenario

forecasts.

B.3 In the following sections, a narrative on the data inputs and assumptions underpinning the

scenarios is presented.

Population, Births & Deaths

Population

B.4 In each scenario, historical population statistics are provided by the mid-year population

estimates for 2001–2013, with all data recorded by single-year of age and sex. These data include

the revised mid-year population estimates for 2002–2010, which were released by the ONS in

May 2013. The revised mid-year population estimates provide consistency in the measurement

of the components of change (i.e. births, deaths, internal migration and international migration)

between the 2001 and 2011 Censuses.

B.5 In the ‘SNPP-2010’ scenario, future population counts are provided by single-year of age and sex

to ensure consistency with the trajectory of the ONS 2010-based SNPP. The ‘SNPP-2010’ scenario

is scaled to ensure consistency with the 2012-based SNPP, following its designated growth trend

thereafter. This does not alter the underlying assumptions or growth trajectory.

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B.6 In the ‘SNPP-2012’ scenario, future population counts are provided by single-year of age and sex

to ensure consistency with the trajectory of the ONS 2012-based SNPP.

Births & Fertility

B.7 In each scenario, historical mid-year to mid-year counts of births by sex from 2001/02 to 2012/13

have been sourced from ONS Vital Statistics.

B.8 In the ‘SNPP-2010’ and ‘SNPP-2012’ scenarios, future counts of births are specified to ensure

consistency with the official projections.

B.9 In the other scenarios, a ‘local’ (i.e. area-specific) age-specific fertility rate (ASFR) schedule, which

measures the expected fertility rates by age in 2013/14, is included in the POPGROUP model

assumptions. This is derived from the ONS 2012-based SNPP.

B.10 Long-term assumptions on changes in age-specific fertility rates are taken from the ONS 2012-

based SNPP.

B.11 In combination with the ‘population-at-risk’ (i.e. all women between the ages of 15–49), the

area-specific ASFR and future fertility rate assumptions provide the basis for the calculation of

births in each year of the forecast period.

Deaths & Mortality

B.12 In each scenario, historical mid-year to mid-year counts of deaths by age and sex from 2001/02

to 2012/13 have been sourced from ONS Vital Statistics.

B.13 In the ‘SNPP-2010’ and ‘SNPP-2012’ scenarios, future counts of deaths are specified to ensure

consistency with the official projections.

B.14 In the other scenarios, a ‘local’ (i.e. area-specific) age-specific mortality rate (ASMR) schedule,

which measures the expected mortality rates by age and sex in 2013/14 is included in the

POPGROUP model assumptions. This is derived from the ONS 2012-based SNPP.

B.15 Long-term assumptions on changes in age-specific mortality rates are taken from the ONS 2012-

based SNPP.

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B.16 In combination with the ‘population-at-risk’ (i.e. the total population), the area-specific ASMR

and future mortality rate assumptions provide the basis for the calculation of deaths in each year

of the forecast period.

Migration

Internal Migration

B.17 In all scenarios, historical mid-year to mid-year estimates of in- and out-migration by five year

age group and sex from 2001/02 to 2012/13 have been sourced from the ‘components of

population change’ files that underpin the ONS mid-year population estimates. These internal

migration flows are estimated using data from the Patient Register (PR), the National Health

Service Central Register (NHSCR) and Higher Education Statistics Agency (HESA).

B.18 In the ‘SNPP-2010’ and ‘SNPP-2012’ scenarios, future counts of internal migrants are specified, to

ensure consistency with the official projections.

B.19 In the alternative ‘trend’ scenarios, age-specific migration rate (ASMigR) schedules are derived

from the area-specific historical migration data. In the ‘PG-5yr’ scenario, a five year internal

migration history is used (2008/09 to 2012/13). In the ‘PG-10yr’ scenario, a ten year history is

used (2003/04 to 2012/13).

B.20 In the ‘Natural Change’ scenario, internal in- and out-migration flows are set to zero for each year

in the forecast period (i.e. no in- or out-migration occurs).

B.21 The jobs-led scenarios calculate their own internal migration assumptions to ensure an

appropriate balance between the population and the targeted increase in the number of jobs

that is defined in each year of the forecast period. In the jobs-led scenarios, a higher level of net

internal migration will occur if there is insufficient population and resident labour force to meet

the forecast number of jobs. In the jobs-led scenarios, the profile of internal migrants is defined

by an ASMigR schedule, derived from the ONS 2012-based SNPP.

B.22 In the case of internal in-migration, the ASMigR schedule of rates is applied to an external

‘reference’ population (i.e. the population ‘at-risk’ of migrating into the area). This is different to

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the other components (i.e. births, deaths and international migration), where the schedule of

rates is applied to the area-specific population. In the case of Barnsley, the reference population

is derived through an analysis of migration into the Leeds City Region Local Enterprise

Partnership (LEP), which Barnsley is a member of. The reference population is defined by

considering the areas which have historically contributed the majority of migrants into the LEP. In

this case, it comprises all districts which cumulatively contributed 70% of migrants into the Leeds

City Region LEP over the 2007/08–2011/12 period.

International Migration

B.23 Historical mid-year to mid-year counts of total immigration and emigration from 2001/02 to

2012/13 have been sourced from the ‘components of population change’ files that underpin the

ONS mid-year population estimates. Any ‘adjustments’ made to the mid-year population

estimates to account for asylum cases are included in the international migration balance.

B.24 Implied within the international migration component of change in all scenarios is an

'unattributable population change' (UPC) figure, which ONS identified within its latest mid-year

estimate revisions. The POPGROUP model has assigned the UPC to international migration as it is

the component with the greatest uncertainty associated with its estimation.

B.25 In all scenarios, future international migration assumptions are defined as ‘counts’ of migration.

In the ‘SNPP-2010’ and ‘SNPP-2012’ scenarios, the international in- and out-migration counts are

drawn directly from the official projections.

B.26 In the alternative ‘trend’ scenarios, the international in- and out-migration counts are derived

from the area-specific historical migration data. In the ‘PG-5yr’ scenario, a five year international

migration history is used (2008/09 to 2012/13). In the ‘PG-10yr’ scenario, a ten year history is

used (2003/04 to 2012/13). An ASMigR schedule of rates is derived from either a five year or ten

year migration history and is used to distribute future counts by single year of age.

B.27 In the ‘Natural Change’ scenario, the future migration counts set the in- and out-migration flows

to zero for each year in the forecast period (i.e. no in- or out-migration occurs).

B.28 In the ‘jobs-led’ scenarios, international migration counts are taken from the ONS 2012-based

SNPP (i.e. counts are consistent with the ‘SNPP-2012’ scenario). An ASMigR schedule of rates

from the ONS 2012-based SNPP is used to distribute future counts by single year of age.

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Household & Dwellings

B.29 The 2011 Census defines a household as:

“one person living alone, or a group of people (not necessarily related) living at the same

address who share cooking facilities and share a living room or sitting room or dining

area.”6

B.30 A dwelling is defined as a unit of accommodation which may comprise one or more household

spaces (a household space is the accommodation used or available for use by an individual

household).

B.31 For each scenario, the household and dwelling implications of the population growth trajectory

have been evaluated through the application of headship rate statistics, communal population

statistics and a dwelling vacancy rate. These data assumptions have been sourced from the 2001

and 2011 Censuses and the 2008-based and 2011-based household projection models from the

DCLG.

Household Headship Rates

Household headship rates define the likelihood of a particular household type being formed in a 5.13

particular year, given the age-sex profile of the population in that year. Household-types are

modelled within a 17-fold classification (Table 10).

B.32 The household headship rates used in the POPGROUP modelling have been taken from the DCLG

2008-based and 2011-based household projections. The 2011-based household projections were

released for local authority districts in England in April 2013, superseding the 2008-based model.

However, as the 2011-based household model is underpinned by the 2011-based SNPP, the

headship rate assumptions have only been published for the 2011–2021 period. Therefore, the

headship rates have been trended after 2021 to extend the rates to the end of the forecast

period.

6 http://www.ons.gov.uk/ons/guide-method/census/2011/census-data/2011-census-user-guide/glossary/index.html

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Table 10: Household type classification

ONS Code DF Label Household Type

OPM OPMAL One person households: Male

OPF OPFEM One person households: Female

OCZZP FAMC0 One family and no others: Couple: No dependent children

OC1P FAMC1 One family and no others: Couple: 1 dependent child

OC2P FAMC2 One family and no others: Couple: 2 dependent children

OC3P FAMC3 One family and no others: Couple: 3+ dependent children

OL1P FAML1 One family and no others: Lone parent: 1 dependent child

OL2P FAML2 One family and no others: Lone parent: 2 dependent children

OL3P FAML3 One family and no others: Lone parent: 3+ dependent children

MCZDP MIX C0 A couple and one or more other adults: No dependent children

MC1P MIX C1 A couple and one or more other adults: 1 dependent child

MC2P MIX C2 A couple and one or more other adults: 2 dependent children

MC3P MIX C3 A couple and one or more other adults: 3+ dependent children

ML1P MIX L1 A lone parent and one or more other adults: 1 dependent child

ML2P MIX L2 A lone parent and one or more other adults: 2 dependent children

ML3P MIX L3 A lone parent and one or more other adults: 3+ dependent children

OTAP OTHHH Other households

TOT TOTHH Total

B.33 Edge Analytics assesses household growth using the 2008-based and the 2011-based headship

rates, in recognition of the uncertainties surrounding future rates of household formation.

B.34 Both the 2008-based and 2011-based headship rates have been applied, producing two

alternative outcomes for each scenario:

‘Option A’: DCLG 2011-based headship rates, with the 2011–2021 trend continued

after 2021.

‘Option B’: DCLG 2008-based headship rates, scaled to be consistent with the 2011

DCLG household total, but following the original trend thereafter.

Communal Population

B.35 Household projections in POPGROUP exclude the population ‘not-in-households’ (i.e. the

communal/institutional population). These data are drawn from the DCLG 2011-based household

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projection, which uses statistics from the 2011 Census. Examples of communal establishments

include prisons, residential care homes and student halls of residence.

B.36 For ages 0–74, the number of people in each age group ‘not-in-households’ is kept fixed

throughout the forecast period. For ages 75–85+, the proportion of the population ‘not-in-

households’ is recorded. Therefore, the population not-in-households for ages 75–85+ varies

across the forecast period depending on the size of the population.

Vacancy Rate

B.37 The relationship between households and dwellings is modelled using a ‘vacancy rate’, sourced

from the 2011 Census. A vacancy rate of 4% for Barnsley has been applied, fixed throughout the

forecast period.

B.38 Using this vacancy rate, the ‘dwelling requirement’ of each household growth trajectory (i.e.

‘Option A’ and ‘Option B’ – see paragraph B.34) has been evaluated. The resulting ‘Option A’ and

‘Option B’ dwelling requirements are then averaged to provide an average dwelling requirement

for each scenario.

Labour Force & Jobs

B.39 For each scenario (apart from the jobs-led scenarios), the labour force and jobs implications of

the population growth trajectory have been evaluated through the application of three key data

items: economic activity rates, an unemployment rate and a commuting ratio.

B.40 In the jobs-led scenarios, these three data items are used to determine the population growth

required by a particular jobs growth trajectory.

Economic Activity Rates

B.41 The level of labour force participation is recorded in the economic activity rates. Economic

activity rates by five year age group (ages 16-74) and sex have been derived from 2001 and 2011

Census statistics. The 2011 Census statistics include an open-ended 65+ age categorisation, so

economic activity rates for the 65–69 and 70–74 age groups have been estimated using a

combination of Census 2011 tables, disaggregated using evidence from the 2001 Census.

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B.42 For Barnsley, rates of economic activity decreased for men and women in the youngest age group

(16–19) between the 2001 and 2011 Censuses (Figure 10). Economic activity rates increased

amongst the older age groups for both men and women.

B.43 In all scenarios (excluding the ‘Jobs-led - Policy On EA1’, ‘Jobs-led Policy On EA2’, and ‘Jobs-led

Policy On CR1 EA1’ sensitivity scenarios, see below for further detail), the 2011 Census economic

activity rates have been applied, with changes made to the age-sex specific economic activity

rates to take account of changes to the State Pension Age (SPA) and to accommodate potential

changes in economic participation which might result from an ageing but healthier population in

the older labour-force age-groups.

Figure 10: Barnsley economic activity rates: 2001 and 2011 Census comparison (source: ONS)

B.44 The SPA for women is increasing from 60 to 65 by 2018, bringing it in line with that for men.

Between December 2018 and April 2020, the SPA for both men and women will then rise to 66.

Under current legislation, the SPA will be increased to 67 between 2026 and 20287.

B.45 ONS published its last set of economic activity rate forecasts from a 2006 base8. These

incorporated an increase in SPA for women to 65 by 2020 but this has since been altered to an

accelerated transition by 2018 plus a further extension to 66 by 2020. Over the 2011–2020

period, the ONS forecasts suggested that male economic activity rates would rise by 5.6% and

7 https://www.gov.uk/state-pension 8 ONS January 2006, Projections of the UK labour force, 2006 to 2020 http://www.ons.gov.uk/ons/rel/lms/labour-market-trends--discontinued-/volume-114--no--1/projections-of-the-uk-labour-force--2006-to-2020.pdf

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11.9% in the 60-64 and 65-69 age groups respectively. Corresponding female rates would rise by

33.4% and 16.3% (Figure 11).

Figure 11: ONS Labour Force Projection 2006 – Economic Activity Rates 2011–2020. Source: ONS

B.46 To take account of planned changes to the SPA, the following modifications have been made to

the economic activity rates:

Women aged 60–64: 40% increase from 2011 to 2020

Women aged 65–69: 20% increase from 2011 to 2020

Men aged 60–64: 5% increase from 2011 to 2020

Men aged 65–69: 10% increase from 2011 to 2020.

B.47 Note that the rates for women in the 60–64 age and 65–69 age-groups are higher than the

original ONS figures (Figure 11), accounting for the accelerated pace of change in the SPA. No

changes have been applied to other age-groups. In addition, no changes have been applied to

economic activity rates beyond 2020. This is an appropriately prudent approach given the

uncertainty associated with forecasting future rates of economic participation. Given the

Males -3.1% -0.8% -0.7% 0.3% 5.6% 11.9% -5.6%

Females -1.2% 1.8% 0.4% 3.9% 33.4% 16.3% 0.0%

Age

Sex

% Change 2011 - 2020

16-24 25-34 35-44 45-59 60-64 65-69 70-74

0%

20%

40%

60%

80%

100%

16

-24

25

-34

35

-44

45

-59

60

-64

65

-69

70

-74

Eco

no

mic

Act

ivit

y R

ate

Males

2011

2020

Age

0%

20%

40%

60%

80%

100%

16

-24

25

-34

35

-44

45

-59

60

-64

65

-69

70

-74

Females

2011

2020

Age

40

September 2014

accelerated pace of change in the female SPA and the clear trends for increased female labour

force participation across nearly all age-groups in the last decade (Figure 10), these 2011–2020

rate increases (Figure 12) would appear to be relatively conservative assumptions.

Figure 12: Edge Analytics economic activity rate profiles, 2011 and 2020 comparison.

B.48 In the ‘Jobs-led - Policy On EA1’ sensitivity scenario, the overall economic activity rate for the

labour force (aged 16–74) is maintained at the base-year level, which for Barnsley is 66%.

B.49 In the ‘Jobs-led Policy On EA2’ the overall economic activity rate for the labour force (aged 16–

74) reaches the level seen in the base-year for England (70%) by 2020.

Unemployment Rate

B.50 The unemployment rate, together with the commuting ratio, controls the balance between the

size of the labour force and the number of jobs available within an area. The same

unemployment rate profile is applied in all the scenarios (both core and sensitivity).

An average ‘recession’ unemployment rate (2008/09–2011/12) of 10.0% is applied in 2013 (

B.51 Table 11). The unemployment rate then incrementally decreases to the ‘pre-recession’ average

(2004/05–2007/08) of 5.6% by 2033. These improvements in the unemployment rate provide an

appropriate basis for what is likely to be a gradual recovery from current economic conditions.

41

September 2014

Table 11: Historical unemployment rates 2004–2012 for Barnsley

Note: Unemployment rates are for April to May (source: Annual Population Survey, NOMIS)

Commuting Ratio

B.52 The commuting ratio, together with the unemployment rate, controls the balance between the

number of workers living in a district (i.e. the resident labour force) and the number of jobs

available in the district.

B.53 A commuting ratio greater than 1.0 indicates that the size of the resident workforce exceeds the

number of jobs available in the district, resulting in a net out-commute. A commuting ratio less

than 1.0 indicates that the number of jobs in the district exceeds the size of the labour force,

resulting in a net in-commute.

B.54 From the 2011 Census Travel to Work statistics, published by ONS in July 2014, a commuting ratio

of 1.25 has been derived for Barnsley, indicating a net out-commute. Comparison with the

corresponding value from the 2001 Census (Table 12) shows that in 2001, there was a lower net

out-commute from Barnsley (Table 12).

Table 12: 2001 and 2011 Census commuting ratio comparison

Note: 2001 data from Census Table T101 – UK Travel Flows; 2011 data from Census Table WU02UK - Location of

usual residence and place of work by age.

In the core scenarios, the commuting ratio is fixed at 1.25 throughout the forecast period. 5.14

Barnsley 0 2001 Census 2011 Census

Workers a 88,760 103,579

Jobs b 74,520 82,981

Commuting Ratio a/b 1.19 1.25

42

September 2014

In the ‘CR’ sensitivity scenarios, the commuting ratio is incrementally reduced over the 2013–5.15

2033 forecast period (Table 13). In ‘Jobs-led - Policy On CR1’ the commuting ratio is incrementally

reduced from 2011 Census to 2001 census commuting ratio by 2033. In ‘Jobs-led - Policy On CR2’

the commuting ratio is incrementally reduced from the 2011 Census commuting ratio to 1.095 by

2033. In ‘Jobs-led - Policy On CR3’ the commuting ratio is incrementally reduced from the 2011

Census commuting ratio to a balanced commuting ratio of 1.0 by 2033.

Table 13: Barnsley commuting ratio sensitivities

2013 2033

Core scenario 1.250 1.250

'CR1' 1.250 1.190

'CR2' 1.250 1.095

'CR3' 1.250 1.000

Commuting ratio changesCommuting Ratio Sensitivities

43

September 2014

Appendix C

Glossary of Terms

Glossary of Terms

ASFR Age-specific Fertility Rate

ASMigR Age-specific Migration Rate

ASMR Age-specific Mortality Rate

CR Commuting Ratio

DCLG Department for Communities and Local Government

DF Derived Forecast

EA Economic Activity

FTE Full Time Equivalent

HESA Higher Education Statistics Agency

LEP Local Enterprise Partnership

MYEs Mid-Year Estimates

NHSCR National Health Service Central Register

NOMIS National Online Manpower Information System

NPPF National Planning Policy Framework

ONS Office for National Statistics

PG POPGROUP model

PPG Planning Practice Guidance

PR Patient Register

REM Regional Econometric Model

SHMA Strategic Housing Market Assessment

SNPP Sub-National Population Projections

SPA State Pension Age

UPC Unattributable Population Change