Mortality projections in the United Kingdom Presentation to the 15th International Conference of Social Security Actuaries and Statisticians of ISSA, Helsinki, Finland Chris Daykin, Government Actuary’s Department Adrian Gallop, Government Actuary’s Department
Mortality projections in the United Kingdom Presentation to the 15th International Conference of Social Security Actuaries and Statisticians of ISSA, Helsinki,
Mar 27, 2015
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Mortality projections in the United Kingdom
Presentation to the 15th International Conference of Social Security Actuaries and Statisticians of ISSA, Helsinki, Finland
Chris Daykin, Government Actuary’s Department
Adrian Gallop, Government Actuary’s Department
Period expectation of life at birth, E&W
30
40
50
60
70
80
90
1850 1860 1870 1880 1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000
Year
Exp
ecta
tio
n o
f li
fe (
year
s)
Males
Females
Period expectation of life at age 65, E&W
6
8
10
12
14
16
18
20
1850 1860 1870 1880 1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000
Year
Exp
ecta
tio
n o
f li
fe (
year
s)
Males
Females
Period expectation of life at age 65, E&W
11
13
15
17
19
21
1972-76 1977-81 1982-86 1987-91 1992-96 1997-2001
Life e
xpecta
ncy a
t 65 (
yrs
)
Social Class I Social Class II
Social Class IIIN Social Class IIIM
Social Class IV Social Class V
Life expectancy at age 65 by social class, 1972-2001
Mortality projections for the UK
The “cohort effect”
Faster improvements have been observed for the UK generation born 1925-1945 – centred on 1931This feature has been explicitly allowed for in GAD mortality projections since the early 1990sThe CMI (Continuous Mortality Investigation) have described a similar effect in insurance and pensioner data – centred on 1926
Improvement in smoothed mortality rates – Males, UK
Improvement in smoothed mortality rates – Females, UK
Potential drivers for future mortality change
Reduced levels of deprivation, better housing etc (+)Govt support for increasing wealth, health and incomes (+)Public support for spending on medical advances (+)Decline in smoking prevalence (+)Lifestyles (+ and -)Obesity (-)Emergence of new diseases (eg HIV, SARS) (-)Re-emergence of old diseases (eg TB) (-)Wide spread of opinion as to whether future technical, medical and environmental changes will have greater or lesser impact than in the past
Male mortality by major cause, E&W, 1911-2002
Age standardised mortality rates for selected broad disease groups
0
100
200
300
400
500
600
700
800
900
1000
1911 1921 1931 1941 1951 1961 1971 1981 1991 2001
Year
Rat
es p
er 1
00,0
00 p
op
ula
tio
n
Infectious diseases
Respiratory diseasesCancers
Circulatory diseases
Source: ONS
Female mortality by major cause, E&W, 1911-2002
Age standardised mortality rates for selected broad disease groups
0
100
200
300
400
500
600
700
1911 1921 1931 1941 1951 1961 1971 1981 1991 2001
Year
Rat
es p
er 1
00,0
00 p
op
ula
tio
n
Infectious diseases
Respiratory diseases
Cancers
Circulatory diseases
Source: ONS
Mortality Projections for the UK
Setting future assumptions
Estimate current rates of improvement by age and gender
Set rates of mortality improvement for some future year
- the target year
Make assumptions on method and speed of convergence
from current improvement rates to target rates, and
how improvement rates change after target year
Mortality Projections for the UK
Choosing the target rate
Rates of improvement at older ages most important
Standardised average rate of improvement over 20th century ≈ 1.0% pa
Cohorts exhibiting greatest improvement will be aged 85-105 in 2029!
Debate as to whether future environmental, technical and medical changes will have more or less impact than up to now
Mortality Projections for the UK
Assumptions for latest projections (2004-based)
Target year is 25th year of projection (i.e. 2029)
Mortality improvements in 2029 assumed to be 1% a year
for all ages for both males and females
Converges more rapidly at first for males…
…less rapidly for females
For those born before 1960, convergence assumed along cohort
After 2029 rates of improvement assumed to remain constant at 1% pa
Mortality Projections for the UK
-2
-1
0
1
2
3
4
5
6
7
8
0 10 20 30 40 50 60 70 80 90 100 110
Age
Pe
rce
nta
ge
re
du
cti
on
Males
Females
Projected smoothed percentage changes in death rates by age, 2003-2004
Annual improvement in smoothed mortality rates, Males, UK
Annual improvement in smoothed mortality rates, Females, UK
Mortality projections for the UK
Males Females
Past (Actual)
Future (assumed)
Past (Actual)
Future (assumed)
Last/next 22 years 2.0% 1.9% 1.3% 1.8%
Last/next 42 years 1.5% 1.5% 1.3% 1.4%
Last/next 72 years 1.2% 1.3% 1.2% 1.3%
Note: Historic estimates are based on comparison of 2002-04 Interim Life Tables with English Life Tables for 1930-32, 1960-62 and 1980-82
Actual and assumed overall annual rates of mortality improvement, E&W
Mortality projections for the UK
30
35
40
45
50
55
60
65
70
75
80
85
90
95
100
1850 1900 1950 2000 2050
Year of birth
Ex
pe
cta
tio
n o
f li
fe a
t b
irth
(y
ea
rs)
30
35
40
45
50
55
60
65
70
75
80
85
90
95
100
Females
Males
Cohort expectation of life at birth (experienced and projected), E&W
Mortality projections for the UK
Cohort expectation of life at age 65 (experienced and projected), E&W
10
14
18
22
26
1850 1900 1950 2000 2050
Year age 65 attained
Ex
pe
cta
tio
n o
f li
fe (
ye
ars
)
10
14
18
22
26
Females
Males
Other mortality studies
Continuous Mortality Investigation (CMI)
Mortality data from participating life offices (since 1924) Claims (or annuities ceasing payment by death) during
calendar year In force at end of calendar year Various classes of business Self Administered Pension Schemes (SAPS) investigation
Other mortality studies
General conclusions
Insured pensioner mortality lower than general population Mortality weighted by amounts lower than by lives SAPS mortality higher than in insured pension schemes SAPS mortality differential by amount
Other mortality studies
Probabilistic/stochastic methodologies
Many candidate methodologiesRegression/extrapolation/smoothing (e.g. P-spline)Time-series (e.g. Lee-Carter)Projection of future life tables (c.f. term structures)
What has the CMI done so far?Explored P-spline and Lee-Carter models in detailDeveloped software to use both the above models
The CMI will contribute to research but does not expect to recommend particular models
Mortality projections in the United Kingdom
Presentation to the 15th International Conference of Social Security Actuaries and Statisticians of ISSA, Helsinki, Finland
Chris Daykin, Government Actuary’s Department
Adrian Gallop, Government Actuary’s Department
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