Stochastic population forecasts for the United Kingdom Emma Wright & Mita Saha Office for National...

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Stochastic population forecasts for the United Kingdom

Emma Wright & Mita Saha

Office for National Statistics

National population projections

• Dependent on assumptions about future levels of fertility, mortality and migration which are reviewed every two years

• Latest projections based on the population at

mid-2006

• Results on GAD website and National Statistics Online

Uncertainty in population projections

• Demographic behaviour is inherently uncertain

• Any set of projections will inevitably be proved wrong to a greater or lesser extent

Past UK population projections

50

55

60

65

70

75

80

1966 1976 1986 1996 2006 2016 2026 2036 2046 2056

Year

Mil

lio

ns

Actual 1971-based 1977-based 1989-based

1998-based 2004-based 2006-based

Mean projection error by age groupPast UK projections

-30%

-20%

-10%

0%

10%

20%

30%

0-4

5-9

10-1

4

15-1

9

20-2

4

25-2

9

30-3

4

35-3

9

40-4

4

45-4

9

50-5

4

55-5

9

60-6

4

65-6

9

70-7

4

75-7

9

80-8

4

85+

Age group

% E

rro

r

-30%

-20%

-10%

0%

10%

20%

30%

5 years ahead 10 years ahead 25 years ahead

Principal & variant projections

• Principal projections - based on assumptions thought to be the best at the time they are adopted

• Variant projections – plausible alternative scenarios, NOT upper or lower limits.

• Limitation - principal and variant projections are deterministic, no measure of probability

Total UK Population2006-based principal and variant projections

56

60

64

68

72

76

80

84

88

92

1981 1991 2001 2011 2021 2031 2041 2051

Year

Mill

ion

s

Principal projection Single component variant Combination variant

H Pop

L Pop

Principal

LLLM

HF

LF

Estimates Projections HLHM

ONS Stochastic forecasting project

• AimTo develop a model that will enable the degree of

uncertainty in UK national population projections to

be specified

• Approach– Express fertility, mortality and migration assumptions in

terms of probability distributions

– Generate random values from these probability distributions to produce predictive distributions for any projection result

Probability distributions

How can we estimate future probability distributions?

Three approaches:• Analysis of accuracy of past projections• Expert opinion• Time series analysis

No ‘right’ answer – subjective judgement

Model Drivers

• Fertility – Total Fertility Rate

• Mortality – Male and female period life expectancy at birth

• Migration – Total net migration

Deriving probability distributionsfor the ONS model

• Expert opinion - NPP expert advisory group questionnaire

• Past projection errors - GAD historic projections database

Expert Opinion

• National Population Projections Expert Advisory Group (set up via BSPS):

David Coleman Phil Rees

Mike Murphy Robert Wright

John Salt John Hollis

• Expressed opinions on the most likely levels and 67% confidence intervals for TFR, period life expectancy at birth and net migration in 2010 and 2030.

Generating sample paths

Random walk with drift model:

Driver(T)=

Driver(T-1) + ValueDriver(T) + DriftDriver(T)

UK TFR250 sample paths with 67% confidence intervals

-

0.50

1.00

1.50

2.00

2.50

3.00

3.50

1971 1981 1991 2001 2011 2021 2031

Year

TF

R

67% confidence interval from test scenario

67% confidence interval from expert opinion

UK TFRProbability distribution v 2006-based assumptions

0.5

1.0

1.5

2.0

2.5

3.0

1971 1981 1991 2001 2011 2021 2031 2041 2051

Year

TF

R

Projections

95% high

67% high

Median

67% low

95% low

Estimates

High fert

Principal

Low fert

UK male period life expectancy at birth Probability distribution

65

70

75

80

85

90

95

1971 1981 1991 2001 2011 2021 2031 2041 2051

Year

Lif

e ex

pec

tan

cy (

year

s)

Projections

95% high

67% high

Median

67% low

95% low

Estimates

UK net migration Probability distribution

-200

0

200

400

600

1971 1981 1991 2001 2011 2021 2031 2041 2051Year

Th

ou

san

ds

Projections

95% high

67% high

Median

67% low

95% low

Estimates

Program

• Based on cohort component model

• UK only

• Random numbers generated

• Age distributions

• 5,000 simulations

• 2006-2056 projection period

Provisional results UK age structure 2031

800 600 400 200 0 200 400 600 800

0

10

20

30

40

50

60

70

80

90

100

110

120A

ge

(ye

ars)

Population (thousands)

95%predictiveinterval

67%predictiveinterval

Median

Males Females

Provisional resultsUK age structure 2056

800 600 400 200 0 200 400 600 800

0

10

20

30

40

50

60

70

80

90

100

110

120A

ge

(ye

ars)

Population (thousands)

95%predictiveinterval

67%predictiveinterval

Median

Males Females

Provisional results: UK total dependency ratioPredictive intervals

400

500

600

700

800

900

1971 1981 1991 2001 2011 2021 2031 2041 2051

Year

Dep

end

ants

per

th

ou

san

d p

erso

ns

of

wo

rkin

g a

ge

Projections95% high

67% high

Median

67% low

95% low

Estimates

Provisional results: Probability of the number of children in the UK exceeding the SPA population

0%

10%

20%

30%

40%

50%

2007 2012 2017 2022 2027 2032 2037 2042 2047 2052

Year

Per

cen

tag

e p

rob

abil

ity

Illustrative probabilities

Based on current provisional assumptions, there is a….

• 48% chance that TFR will exceed replacement level

• 9% chance that male period life expectancy at birth will exceed 90 yrs

• 20% chance that there will be negative annual net migration

• 2% chance that the population will fall below the 2006 base level

… at some point between 2006 and 2056.

Limitations

• Do not know true probability distributions • Validity of results wholly dependent on assumptions

underlying model • Inflated sense of precision• Communicating results and limitations may be a

challenge• BUT….if aware of the limitations, then stochastic

forecasting can be a useful approach

Estimates of the UK TFR in 2049/2050Median and 80% confidence intervals

1.0

1.5

2.0

2.5

3.0

TF

R

ONSUPE VID

Quality Assurance

• Prof Phil Rees (University of Leeds)

• Prof Nico Keilman (University of Oslo)

• Prof Wolfgang Lutz (Vienna Institute of Demography)

• ONS Methodology Directorate

Future plans

• ONS plans to publish a set of 2006-based stochastic forecasts for the UK as ‘Experimental Statistics’ during 2009

• If you would like to feed in any comments on this work, please e-mail:

natpopproj@ons.gov.uk