Population forecasting of small areas or ethnic

groups

Stockholm, 21st November 2008Ludi Simpson

University of Manchester

www.ccsr.ac.uk/popgroup

Population forecasting: 2 practical dilemmas

• Theory without software– Cohort component framework– Multi-regional, probabilistic, socially disaggregated– Academic research– Project-specific

• Priority problems without stable data– Sub-national and non-standard areas– Ethnic or national groups– Non-cohort, non-component methods un-informative

• Version 1 (1999) – version 3 (2005)

• Local/Regional government concerns– Replicate and develop

national agency work– Population, housing, and

labour force– Impact of local development

policies– Ethnically diverse populations– Large populations and

systems of small populations

• Standard national methods– applied to 1 or more ‘groups’,

named by the user

POPGROUP designPrinciples and practice

• Excel input files

• Excel output files

• Macros do work of structuring files, validating data, projections and most interrogation

• Easy start, then develop– the future is not what it used to be

• Integrate estimates and forecasts

Each component of population change is one input file

Pt+1 = Pt + B – D + IUK – OUK + IOV – OOV

Seven input files, plus:Constraints : population, housing and employmentSpecial populations (students, armed forces)Dwellings (vacancy, second homes, sharing

households)Jobs (commuting, unemployment)

Natural change

MigrationBase popul-ation

Future popul-ation

Each input file represents a collection of assumptions for one component

Mathematical approach to combine the varied availability of demographic rates,

past counts, and targets

Initial population and one age-schedule each for rates of fertility, mortality, migration

The only required inputs

Differentials for groups, years, age-sex groups

Used to create initial projections for year y+1

Counts of births, deaths, migration flows in period

Used to constrain the initial projection

Population, housing or labour force

Used to further constrain the migration flows

Projecting small populations (areas or ethnic groups)

• Few data for non-standard areas• Time series are unstable

– Recent past may not indicate an underlying level of fertility, mortality, migration

• Alternatives provide neither age nor components– Mathematical extrapolation– Shift share– Housing units

Example 1: replicating District population and household projections.

Detailed data available

Household outputs

Household outputsBlinkforthHousehold Types 1991 1996 2001 2006 2011 2016 2021Married couple 23,600 22,750 21,700 20,850 20,200 19,750 19,350Cohabiting couple 2,550 3,100 3,650 4,100 4,500 4,700 4,700Lone parent 1,800 2,050 2,050 2,050 1,950 1,900 1,850Other multi-person 2,300 2,500 2,600 2,650 2,700 2,750 2,700One person 10,000 11,350 12,350 13,200 14,050 14,950 15,700

All Households 40,250 41,750 42,350 42,850 43,450 44,000 44,300

Private household population 100,150 100,500 99,450 98,250 97,250 96,650 96,100Average household size 2.49 2.41 2.35 2.29 2.24 2.20 2.17

Concealed married couple 50 50 50 0 0 0 0Concealed cohabiting couple 50 50 50 100 100 100 100Concealed lone parent 200 200 150 200 200 200 200

All concealed families 250 250 250 300 300 300 300

Decomposition of Household Change

2001-2021Population

EffectHeadship

Effect Change

All groups 6,500 1,350 7,900

Abbafield 4,700 1,150 5,900Blinkforth 1,800 200 2,000

Each figure has been independently rounded to the nearest 50

Blinkforth

Married couple 23,600 22,750 21,700 20,850 20,200 19,750 19,350Cohabiting couple 2,550 3,100 3,650 4,100 4,500 4,700 4,700Lone parent 1,800 2,050 2,050 2,050 1,950 1,900 1,850Other multi-person 2,300 2,500 2,600 2,650 2,700 2,750 2,700One person 10,000 11,350 12,350 13,200 14,050 14,950 15,700

All Households 40,250 41,750 42,350 42,850 43,450 44,000 44,300

Private household population 100,150 100,500 99,450 98,250 97,250 96,650 96,100Average household size 2.49 2.41 2.35 2.29 2.24 2.20 2.17

Concealed married couple 50 50 50 0 0 0 0Concealed cohabiting couple 50 50 50 100 100 100 100Concealed lone parent 200 200 150 200 200 200 200

Decomposition of Household Change

2001-2021Population

EffectHeadship

Effect Change

All groups 6,500 1,350 7,900

Abbafield 4,700 1,150 5,900Blinkforth 1,800 200 2,000

Each figure has been independently rounded to the nearest 50

Example 2: Wards of Bradford.Births, deaths and population available for recent years

• Each area’s counts of births indicate its past level of fertility.

• Trends that are expected to affect all areas are entered on the ‘All-groups’ sheet

• Expressed as a differential to a standard schedule, the area level is continued to the future

• Local trends may be identified and used in assumptions for the future

The impact of fertility file options on the Total Fertility Rate

chart

Total Fertility Rate

1.00

1.50

2.00

2.50

3.00

3.50

1991 1996 2001 2006 2011 2016

BradMoor

Eccleshi

Ilkley

Osdal

Toller

Univrsty

Forecasts, anchored in the average training phase experience

Training phase including birth counts

4. Unusual trends may be continued in future

Forecasts

Training phase

Total Fertility Rate

1. Each area’scounts of births

2. Age-trend on All-areas sheet, from GAD projections

3. Each area’s differential, maintained in future

The impact of migration file and constraint options on migration

Net migration in year after June 30th

-400

-300

-200

-100

0

+100

+200

+300

1991 1996 2001 2006 2011 2016

BradMoor

Eccleshi

Ilkley

Osdal

Toller

Univrsty

Training phase, including population estimates at 1996 and 2000

Forecasts, anchored in the experience of the training phase

A cohort component projection allows understanding of population dynamics

from incomplete information

Percentage change since 2001

Birm-ingham White

Carib-bean African Indian

Pak-istani

Bangla-deshi Chinese Other

Population 2001 (000s) 985 690 48 7 56 106 21 5 51 Total population change 2001-2026 +12% -23% -15% +599% +11% +119% +125% +155% +164%

Impact by 2026 of each factor:

(a) Age momentum +16% +6% +17% +39% +31% +44% +49% +31% +50%

(b) Fertility Impact -4% -9% -18% +7% -12% +23% +27% -27% +21%

(c) Migration within the UK -16% -22% -8% +206% -16% -1% -16% +7% -3%

(d) Migration overseas +9% -1% -11% +280% +1% +31% +41% +105% +59% (e) Constraint to ONS total +8% +2% +5% +67% +7% +21% +23% +40% +37%

• Birmingham city: eight ethnic groups– Estimate components of change for each group

– Estimate population change due to each component

– Present the decomposition of expected population change

Example 3: The impact of housing plans on population

• Population and housing change, a two-way relationship

• Regional planners are interested– Large areas: how much land should be released for

house-building?– Small areas: what is the impact on services of

planned house-building? • Greater numbers of houses built may result in…

– More in-migration– Less out-migration– Lower household size– Higher proportion of vacancies, or of holiday-homes

POPGROUP alters migration to meet housing constraints

(running HOUSEGROUP in the background)

60/65 -74 21,274 21,361 21,484 21,554 21,183

75-84 9,484 9,363 9,155 8,951 9,187

85+ 2,611 2,751 2,892 2,926 3,039

Total 196,269 196,970 197,610 197,886 198,029

Population impact of constraintNumber of persons +56 +38 -267 -351

HousingNumber of households 76,554 77,240 77,958 78,479 79,067

Change over previous year +686 +718 +521 +588

Concealed families 800 786 771 754 737

What’s the impact on population of planned housing developments?

What’s the change in number of households and dwellings each year?

National Parks: ageing populations

Decomposition of household change 2001-2016

 Population

size

Population age

structure HeadshipTotal

change

Peak District -896 1090 109 303

Cairngorms 478 732 149 1359

Peak District National Park: new housing will not create a workforce

(unless the migration age structure changes)

Population change – Dwelling led projections (2001-25)

Scenario% Population change % Working age pop

change

Recent migration continues

-14% -35%

48 dwellings p/a -6.3% -29%

95 dwellings p/a 1.1% -22%

150 dwellings p/a 9.9% -13%

Milton Keynes spill-over to Aylesbury Vale (2 wards selected)

0

5,000

10,000

15,000

20,000

25,000

30,000

Populationin 1991

Populationin 2001

Populationin 2006

Populationin 2026

KEY

Green: migration as estimated for 2001-2006. (‘Trend-based’)

Red: Zero new dwellings.

Black: alternative planned house-building

Discussion

• www.ccsr.ac.uk/popgroup

• Good forecasts incorporate good estimates

• Detailed small area forecasts are possible with few data, if they are relevant data