Mortality Improvement: Trends and Implications for Pension Plans

© 2014 Society of Actuaries, All Rights Reserved

Mortality Improvement:Trends and Implications for Pension Plans

A Resource Guide for Pension ActuariesSponsored by the SOA Pension Section Council

Last revision: April 25, 2014

22 © 2014 Society of Actuaries, All Rights Reserved© 2014 Society of Actuaries, All Rights Reserved

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Agenda Brief history of mortality Trends and observations Related factors Observed mortality improvement New assumptions

44 © 2014 Society of Actuaries, All Rights Reserved

Mortality in theUnited States, 1900-2000


Age at Death in 1900

Data: SSA Actuarial Study 120 – Periods 1900-2000, 50% male, 50% female

*13,283

*

0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102

108

1140

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Age

Num

ber o

f Dea

ths

per 1

00,0

00 D

eath

s

Life Expectancy Age 65 Age 40 At Birth


0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102

108

1140

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Age

Num

ber o

f Dea

ths

per 1

00,0

00 D

eath

s

*10,916

*




0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102

108

1140

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Age

Num

ber o

f Dea

ths

per 1

00,0

00 D

eath

s

*7,684

*




0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102

108

1140

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Age

Num

ber o

f Dea

ths

per 1

00,0

00 D

eath

s

*5,837

*




0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102

108

1140

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Age

Num

ber o

f Dea

ths

per 1

00,0

00 D

eath

s

*4,725

*




0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102

108

1140

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Age

Num

ber o

f Dea

ths

per 1

00,0

00 D

eath

sAge at Death in 1950



0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102

108

1140

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Age

Num

ber o

f Dea

ths

per 1

00,0

00 D

eath




0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102

108

1140

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Age

Num

ber o

f Dea

ths

per 1

00,0

00 D

eath




0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102

108

1140

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Age

Num

ber o

f Dea

ths

per 1

00,0

00 D

eath




0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102

108

1140

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Age

Num

ber o

f Dea

ths

per 1

00,0

00 D

eath




0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102

108

1140

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Age

Num

ber o

f Dea

ths

per 1

00,0

00 D

eath




0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102

108

1140

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Age

Num

ber o

f Dea

ths

per 1

00,0

00 D

eath

sAge at Death in 2010 (Projected)



Trends and Observations


Changes Over the Century

0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102

108

1140

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Age

Num

ber o

f Dea

ths

per 1

00,0

00 D

eath

s

*

*13,283

20001900 1950



20th Century Life Expectancy Improvements

1900

1910

1920

1930

1940

1950

1960

1970

1980

1990

2000

0102030405060708090

100

BirthAt 40At 65



Life Expectancy At 6519

7019

7219

7419

7619

7819

8019

8219

8419

8619

8819

9019

9219

9419

9619

9820

0020

0220

0420

0620

0820

1020

1220

14

0

10

20

30

40

50

60

70

80

9082.3 84.0 84.0 83.9

Age

Population Data: SSA Actuarial Study 120 – Periods 1900-2000, 50% male, 50% female, non-decade years interpolatedMortality Tables: 71GAT, 83GAM, RP-2000 unprojected, RP-2000 (AA generational); 50% male, 50% female

RP 2000

83GAM

71 GAT

General Population

Pension Plan

Mortality Tables

UP94


Remaining Life Exp. At 6519

7019

7219

7419

7619

7819

8019

8219

8419

8619

8819

9019

9219

9419

9619

9820

0020

0220

0420

0620

0820

1020

1220

14

65

70

75

80

85

90

0

5

10

15

20

25

17.3 19.0 19.0 18.9

Age

Year

s Fr

om A

ge 6

5

RP 2000

83GAM

71 GAT

General Population

UP94

Population Data: SSA Actuarial Study 120 – Periods 1900-2000, non-decade years interpolated. Mortality Tables: 71GAT, 83GAM, UP-94,RP-2000 unprojected, RP-2000 (AA generational), RP-2014 (MP-2014 generational). All 50% male, 50% female.


20th Century Mortality Observations Life expectancy continually increased

• At birth: dramatic increases, especially pre-1950

• At “middle age”: slower, steadier increases Most current forecasts assume slower life

expectancy increases in the future, including at older ages*

Undervaluing future mortality improvement understates pension liabilities

* IMF Global Financial Stability Report, 2012


Related Factors


Associated Factors

Longevity Factors

Gender

Genetics

Prenatal & childhood conditions

Marital status

EducationSocio-

economic status

Ethnicity / migrant status

Lifestyle

Medical technology

Source: Variation in Longevity, Longevity Bulletin, IFA, May 2012

Various factors influence mortality. Some may be reflected to some extent in pension plan valuations.


Gender

Longevity Factors

Gender

Genetics


Marital status

EducationSocio-

economic status


Lifestyle

Medical technology


Different mortality by gender has long been reflected in pension plan valuations.


Female Compared to Male Life Expectancy Over the 20th Century in the U.S.

1900

1910

1920

1930

1940

1950

1960

1970

1980

1990

2000

100%101%102%103%104%105%106%107%108%109%110%

At Age 65

Data: SSA Actuarial Study 120 – Periods 1900-2000

At Age 40


Life Expectancy by County: Males

1985 2010

62 64 66 68 70 72 74 76 78 80 82

Source: Institute for Health Metrics and Evaluation, 2013


Life Expectancy by County: Females

1985 2010

62 64 66 68 70 72 74 76 78 80 82

Source: Institute for Health Metrics and Evaluation, 2013


Lifestyle

Longevity Factors

Gender

Genetics


Marital status

EducationSocio-

economic status


Lifestyle

Medical technology

Historical examples:• Tobacco use• Food safety• Work place

safety• Motor

vehicle safety

Obesity is one current issue



U.S. Adult Obesity 1962-200819

6219

6419

6619

6819

7019

7219

7419

7619

7819

8019

8219

8419

8619

8819

9019

9219

9419

9619

9820

0020

0220

0420

0620

08

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Not over-weight BMI≤30Overweight (not obese) 30<BMI≤35

Obese (not extremely so) 35<BMI≤40

Extremely obese BMI>40

Source: NHANES, Flegal et al (2012); results prior to 2000 have been smoothed


Longevity Factors

Gender

Genetics


Marital status

EducationSocio-

economic status


Lifestyle

Medical technologyMortality

differences for blue vs. white collar workers can also be reflected in a pension plan valuation.


Socioeconomics & Education


U.S. Mortality Varies by Education

<12 12 13-15 16+0.0%

0.2%

0.4%

0.6%

0.8%

1.0%

1.2%

1.4%

Years of Education

Ave

rage

Mor

talit

y R

ate

in 2

001

for A

ges

25-6

4

White WomenWhite MenBlack WomenBlack Men

Source: Jemal A, Ward E, Anderson RN, Murray T, et al. (2008) Widening of Socioeconomic Inequalities in U.S. Death Rates, 1993–2001. PLoS ONE 3(5): e2181. doi:10.1371/journal.pone.0002181

Higher education levels are linked to higher

socio-economic status. Both are linked to

improved longevity.


Medicine

Longevity Factors

Gender

Genetics


Marital status

EducationSocio-

economic status


Lifestyle

Medical technology

Historical examples:• Antibiotics,

immunization, vaccination

• Imaging (X-ray, CT scan, MRI)

• Cardiac care and surgery

• Organ transplants

What will future advances bring?



Longevity Factors

Gender

Genetics


Marital status

EducationSocio-

economic status


Lifestyle

Medical technology

Some of these factors might be evident (or likely) in pension plan’s population and can be reflected in the valuation of liabilities.


Pension Plan Relevance


Pension Valuations Around the Globe

Japa

n

Austra

lia US

Canad

a

German

y UK

Austria

Irelan

d0.00.51.01.52.02.53.03.54.04.5

Assumed Mortality Improvement in 2010 vs. Observed Mortality Improvement Since 1990

Observed Assumed

Yea

rs

Source: IMF Global Financial Stability Report, 2012


Observed Mortality Improvement and Previous Assumptions


Mortality Improvement Rates

100969288848076726864605652484440

100 99 9897 96 9594 93 9291 90 8988 87 8685 84 8382 81 8079 78 7776 75 7473 72 7170 69 6867 66 6564 63 6261 60 5958 57 5655 54 53

Age

Calendar YearHistorical data source: US(SSA) Male 50-100; 1950-2005

Year

Age

Move th

rough

time (

cohort)

Mortality for 65-year-olds improved (decreased) by 2.5% between 1974-1975


Males: MI Rates

100969288848076726864605652484440

100 99 9897 96 9594 93 9291 90 8988 87 8685 84 8382 81 8079 78 7776 75 7473 72 7170 69 6867 66 6564 63 6261 60 5958 57 5655 54 53

Age

Calendar YearHistorical data source: US(SSA) Male 50-100; 1950-2005

HIV/AIDS reduced longevity

Medicare began in 1966; mortality improved for all ages.

Lagged effect of 1960’s anti-smoking campaigns

Statin drugs reduced cardiovascular disease


Females: MI Rates

100969288848076726864605652484440

100 99 9897 96 9594 93 9291 90 8988 87 8685 84 8382 81 8079 78 7776 75 7473 72 7170 69 6867 66 6564 63 6261 60 5958 57 5655 54 53

Age

Calendar YearHistorical data source: US(SSA) Female 50-100; 1950-2005

Less improvement for baby boomers

(esp. born ~1955)

Medicare “Mountain Range”

“Silent generation” enjoyed relatively high improvement rates

Statins


Males: Observed MI and AA

100959085807570656055504540

100 99 9897 96 9594 93 9291 90 8988 87 8685 84 8382 81 8079 78 7776 75 7473 72 7170 69 6867 66 6564 63 6261 60 5958 57 5655 54 53

Age

Historical data source: US(SSA) Male 50-100; 1950-2005 Data for AA


Females: Observed MI and AA

100959085807570656055504540

100 9998 9796 9594 9392 9190 8988 8786 8584 8382 8180 7978 7776 7574 7372 7170 6968 6766 6564 6362 6160 5958 5756 5554 53

Age

Historical data source: US(SSA) Female 50-100; 1950-2005 Data for AA


New Mortality and Mortality Improvement Assumptions


New Mortality Table for Pension Plans

Base table RP-2014 replaces RP-2000• Private pension plan experience over 2004 –

2008 totaling 10.2 million life-years• Rates adjusted to 2014 using the new MP-2014

projection scale Variations for blue/white collar employees

and annuitants, by benefit amount and disabled persons

Intended for use with pension plans; may not be appropriate for insured products


New Mortality Improvement Scale for Pension Plans Scale MP-2014 replaces Scales AA and BB Two dimensions for each gender reflect

cohort variations in mortality improvement:• Age• Calendar year

Intended for use with pension plans; may not be appropriate for insured products


Males: Observed MI and MP-2014

100959085807570656055504540

100 9998 9796 9594 9392 9190 8988 8786 8584 8382 8180 7978 7776 7574 7372 7170 6968 6766 6564 6362 6160 5958 5756 5554 5352 5150 49

Age

Historical data source: US(SSA) Male 50-100; 1950-2005


Females: Observed and MP-2014

100969288848076726864605652

100 9998 9796 9594 9392 9190 8988 8786 8584 8382 8180 7978 7776 7574 7372 7170 6968 6766 6564 6362 6160 5958 5756 5554 5352 51

Age

Calendar Year



7019

7219

7419

7619

7819

8019

8219

8419

8619

8819

9019

9219

9419

9619

9820

0020

0220

0420

0620

0820

1020

1220

14

65

70

75

80

85

90

0

5

10

15

20

25

17.3 19.0 19.0 18.9 20.5

22.7

Age

Year

s Fr

om A

ge 6

5

RP 2000

83GAM

71

GAT

RP2014 w/MP2014

General Population

RP 2000 w/AA

UP94

Population Data: SSA Actuarial Study 120 – Periods 1900-2000, non-decade years interpolated. Mortality Tables: 71GAT, 83GAM, UP-94,RP-2000 unprojected, RP-2000 (AA generational), RP-2014 (MP-2014 generational). All 50% male, 50% female.


Financial Impact of New Tables From RP2000 (AA) Percentage Increase in Liability*

25 35 45 55 65 75 850%2%4%6%8%

10%12%14%16%18%

M RP00 & AA F RP00 & AA

Age* Monthly deferred-to-62 annuity due values at 6.0% interest; for RP-2014, Total Employee Rates through age 61 and Healthy Annuitant Rates for ages 65 and above; RP-2000 combined rates with generational projection


Financial Impact of New Tables From RP2000 (BB) Percentage Increase in Liability*

25 35 45 55 65 75 850%2%4%6%8%

10%12%14%16%18%

M RP00 & BB F RP00 & BB



Financial Impact of New Tables From UP94 (AA) Percentage Increase in Liability*

25 35 45 55 65 75 850%2%4%6%8%

10%12%14%16%18%

M UP94 & AA F UP94 & AA



Liability* Comparison of RP-2014 Specialized Tables: Male

25 35 45 55 65 75 85-6%-4%-2%0%2%4%6%8%

Increase Compared to Total Dataset TableBottom Quartile Amt Blue Collar White Collar Top Quartile Amt

Age

*Monthly deferred-to-62 annuity due values using RP-2014 with MP-2014 generational projection and 6% interest


Liability* Comparison of RP-2014 Specialized Tables: Female

25 35 45 55 65 75 85-6%-4%-2%0%2%4%6%8%

Increase Compared to Total Dataset TableBottom Quartile Amt Blue Collar White Collar Top Quartile Amt

Age

*Monthly deferred-to-62 annuity due values using RP-2014 with MP-2014 generational projection and 6% interest


Summary

Updated assumptions better reflect the way that longevity has been improving

New tables enable more effective valuation and modeling

Specialized tables enable reflection of certain specific characteristics that may be present in a pension plan population


Appendix 1: Additional Information For Actuaries and Highly Technical Clients


Terminology: New and Review


Terminology: Term DefinitionMortality rate Probability that a person age x will die

before attaining age x+1 (denoted qx)Mortality table Mortality rates for all ages 0 to 120,

typically separate rates for males and females

Period (mortality) table

Assumes that its mortality rates will apply for the remainder of each person’s life

Cohort or generational (mortality) table

Assumes mortality rates will change in the future at paces that vary for each group (cohort) of individuals; typically cohorts are defined by sex and year of birth


Terminology: Term DefinitionMortality improvement*

The percentage by which mortality rates improved (declined) from the prior year to the current year: qx:2013 = qx:2012 * (1 – improvement rate)

Base table Period mortality table to which mortality improvement is intended to be applied

Table margin or load

Adjustments or improvements to mortality rates that are applied to all rates for all ages:

qx = qx(published) * (1 – margin)

Prior to 1990, this was the generally accepted method for applying mortality improvement.

* Developing improvement rates is science + art + educated guess


Terminology: Term DefinitionProjection scale Set of improvement rates that vary by

age (typically separate male & female rates)

One dimensional*: ageTwo dimensional**: age & calendar year

One dimensional* Improvement rates very by ageTwo dimensional** Improvement rates very by age and

calendar year

* Plus another dimension for sex, for a total of two dimensions** Plus another dimension for sex, for a total of three dimensions


20th Century U.S. Mortality History by Gender



Data: SSA Actuarial Study 120 – Periods 1900-2000, male

*13,283

*

0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102

108

1140

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Age

Num

ber o

f Dea

ths

per 1

00,0

00 D

eath

s


MALE



0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102

108

1140

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Age

Num

ber o

f Dea

ths

per 1

00,0

00 D

eath

s

*10,916

*


MALE



0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102

108

1140

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Age

Num

ber o

f Dea

ths

per 1

00,0

00 D

eath

s

*7,684

*


MALE



0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102

108

1140

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Age

Num

ber o

f Dea

ths

per 1

00,0

00 D

eath

s

*7,684

*


MALE



0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102

108

1140

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Age

Num

ber o

f Dea

ths

per 1

00,0

00 D

eath

s

*4,725

*


MALE



0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102

108

1140

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Age

Num

ber o

f Dea

ths

per 1

00,0

00 D

eath

s


MALE



0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102

108

1140

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Age

Num

ber o

f Dea

ths

per 1

00,0

00 D

eath

s


MALE



0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102

108

1140

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Age

Num

ber o

f Dea

ths

per 1

00,0

00 D

eath

s


MALE



0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102

108

1140

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Age

Num

ber o

f Dea

ths

per 1

00,0

00 D

eath

s


MALE



0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102

108

1140

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Age

Num

ber o

f Dea

ths

per 1

00,0

00 D

eath

s


MALE



0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102

108

1140

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Age

Num

ber o

f Dea

ths

per 1

00,0

00 D

eath

s


MALE


Age at Death in 2010 (Projected)

0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102

108

1140

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Age

Num

ber o

f Dea

ths

per 1

00,0

00 D

eath

s


MALE


Summary of ChangesAge at Death in 1900, 1950 and 2000

0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102

108

1140

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

190019502000

Age

Num

ber o

f Dea

ths

per 1

00,0

00 D

eath

s

*

*13,283Data: SSA Actuarial Study 120 – Periods 1900-2000, male

MALE



1900

1910

1920

1930

1940

1950

1960

1970

1980

1990

2000

0102030405060708090

100

Birth

At 65At 40


MALE



7019

7219

7419

7619

7819

8019

8219

8419

8619

8819

9019

9219

9419

9619

9820

0020

0220

0420

0620

0820

1020

1220

14

65

70

75

80

85

90

0

5

10

15

20

25

15.2 16.7 17.3 17.6

19.6 21.6

Age

Year

s Fr

om A

ge 6

5

RP 2000

83GAM

71

GAT

RP 2000 w/AA

General Population

MALE

UP94

RP2014w/MP2014

Population Data: SSA Actuarial Study 120 – Periods 1900-2000, non-decade years interpolated. Mortality Tables: 71GAT, 83GAM, UP-94,RP-2000 unprojected, RP-2000 (AA generational), RP-2014 (MP-2014 generational)



Data: SSA Actuarial Study 120 – Periods 1900-2000, female

*13,283

*

0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102

108

1140

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Age

Num

ber o

f Dea

ths

per 1

00,0

00 D

eath

s


FEMALE



0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102

108

1140

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Age

Num

ber o

f Dea

ths

per 1

00,0

00 D

eath

s

*10,916

*

FEMALE




0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102

108

1140

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Age

Num

ber o

f Dea

ths

per 1

00,0

00 D

eath

s

*7,684

*

FEMALE




0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102

108

1140

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Age

Num

ber o

f Dea

ths

per 1

00,0

00 D

eath

s

*7,684

*

FEMALE




0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102

108

1140

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Age

Num

ber o

f Dea

ths

per 1

00,0

00 D

eath

s

*4,725

*

FEMALE




0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102

108

1140

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Age

Num

ber o

f Dea

ths

per 1

00,0

00 D

eath

s

FEMALE




0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102

108

1140

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Age

Num

ber o

f Dea

ths

per 1

00,0

00 D

eath

s

FEMALE




0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102

108

1140

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Age

Num

ber o

f Dea

ths

per 1

00,0

00 D

eath

s

FEMALE




0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102

108

1140

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Age

Num

ber o

f Dea

ths

per 1

00,0

00 D

eath

s

FEMALE




0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102

108

1140

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Age

Num

ber o

f Dea

ths

per 1

00,0

00 D

eath

s

FEMALE




0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102

108

1140

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Age

Num

ber o

f Dea

ths

per 1

00,0

00 D

eath

s

FEMALE



Age at Death in 2010 (Projected)

0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102

108

1140

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Age

Num

ber o

f Dea

ths

per 1

00,0

00 D

eath

s

FEMALE



Summary of ChangesAge at Death in 1900, 1950 and 2000

0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102

108

1140

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

190019502000

Age

Num

ber o

f Dea

ths

per 1

00,0

00 D

eath

s

*

*13,283

FEMALE




1900

1910

1920

1930

1940

1950

1960

1970

1980

1990

2000

0102030405060708090

100

Birth

At 65At 40

FEMALE




7019

7219

7419

7619

7819

8019

8219

8419

8619

8819

9019

9219

9419

9619

9820

0020

0220

0420

0620

0820

1020

1220

14

65

70

75

80

85

90

0

5

10

15

20

25

19.3 21.3 20.7 20.1 21.4 23.8

Age

Year

s Fr

om A

ge 6

5

RP 2000

83GAM

71

GAT

RP 2000 w/AA

General Population

FEMALEUP94

RP2014 w/MP2014

Population Data: SSA Actuarial Study 120 – Periods 1900-2000, non-decade years interpolated. Mortality Tables: 71GAT, 83GAM, UP-94,RP-2000 unprojected, RP-2000 (AA generational), RP-2014 (MP-2014 generational)



1900

1910

1920

1930

1940

1950

1960

1970

1980

1990

2000

0102030405060708090

100

F65M65F40M40F0M0

MALE &FEMALE

Data: SSA Actuarial Study 120 – Periods 1900-2000


Current Mortality Assumptions Review


Mortality Assumptions Most common mortality assumptions in U.S.

pension plans• Base mortality rates: RP-2000 Combined Healthy

or 94 GAM tables• Mortality improvement scale: Scale AA

Used to extend a table of mortality rates as of a specific “base” year into the future

Typically described as the annual percentage decrease in mortality rates

Two types of projection• Generational• Static


Scale AA Refresher Scale AA was released in connection with

the 1994 series of mortality tables• Based on SSA and Civil Service mortality

improvement data between 1977 and 1993• Reaffirmed in the RP-2000 Mortality Tables

Report


The Financial Impact of Longevity RiskUK Actuaries Leading the World

Continuous Mortality Institute• Part of Institute and Faculty of Actuaries• Ongoing mortality research

2D models of mortality improvements• Variations by cohort

Variations by population subgroups Regular reviews against actual


More Details on RP-2014 and MP-2014


About RP-2014 Significant modernization of the corresponding

RP-2000 RP for Retirement Plans 2014 for the calendar year that the table’s

mortality rates are intended to represent Rates were adjusted from the central year

of the data, 2006, to 2014 using the new MP-2014 projection scale


About RP-2014 Higher representation of Blue Collar data in

RP-2014 than in RP-2000 • RP-2000: represented 23% of employee and 26%

of healthy annuitant data• RP-2014: 51% and 54%, respectively


More About RP-2014 Tables that combine non-annuitant and

annuitant rates based on a single universal retirement age assumption are no longer necessary

Separate base tables by gender for:• Healthy employee • Healthy annuitants• Distinctions by collar and by benefit amount• Disabled lives• No Combined Healthy table


About MP-2014 MP for Mortality Projection 2014 for base calendar year to which it

applies Also replaces Scale BB-2D Long-term improvement rates are phased

in over 20 years (by calendar year 2027:• 1.0% through age 85,• Grading down to 0.85% at age 95,• Steeply declining to 0.0% at age 115


Financial Impact of RP-2014 and MP-2014


Financial Impact of New Tables From RP2000 (AA) Percentage Increase in Liability*

25 35 45 55 65 75 850%2%4%6%8%

10%12%14%16%18%

M RP00 & AA F RP00 & AA

Age* Monthly deferred-to-62 annuity due values at 6.0% interest; for RP-2014, Total Employee Rates through age 61 and Healthy Annuitant Rates for ages 65 and above; RP-2000 combined rates


Financial Impact of New Tables From RP2000 (BB) Percentage Increase in Liability*

25 35 45 55 65 75 850%2%4%6%8%

10%12%14%16%18%

M RP00 & BB F RP00 & BB



Financial Impact of New Tables From UP94 (AA) Percentage Increase in Liability*

25 35 45 55 65 75 850%2%4%6%8%

10%12%14%16%18%

M UP94 & AA F UP94 & AA



Financial Impact of RP-2014 & MP-2014

Base Rates UP-94 RP-2000 RP-2000 RP-2014** UP-94 RP-2000 RP-2000Proj. Scale AA AA BB MP-2014 AA AA BB

Age25 1.3944 1.4029 1.4135 1.4379 3.1% 2.5% 1.7%35 2.4577 2.4688 2.4881 2.5363 3.2% 2.7% 1.9%45 4.3316 4.3569 4.3963 4.4770 3.4% 2.8% 1.8%55 7.6981 7.7400 7.8408 7.9755 3.6% 3.0% 1.7%65 11.0033 10.9891 11.2209 11.4734 4.3% 4.4% 2.3%75 8.0551 7.8708 8.2088 8.6994 8.0% 10.5% 6.0%85 4.9888 4.6687 5.0048 5.4797 9.8% 17.4% 9.5%25 1.4336 1.4060 1.4816 1.5195 6.0% 8.1% 2.6%35 2.5465 2.4931 2.6145 2.6853 5.5% 7.7% 2.7%45 4.5337 4.4340 4.6264 4.7497 4.8% 7.1% 2.7%55 8.1245 7.9541 8.2532 8.4544 4.1% 6.3% 2.4%65 11.7294 11.4644 11.8344 12.0932 3.1% 5.5% 2.2%75 8.9849 8.6971 9.0650 9.3995 4.6% 8.1% 3.7%85 5.7375 5.5923 5.9525 6.1785 7.7% 10.5% 3.8%

Mal

esFe

mal

es

RP-2014 with MP-2014 Percentage Increase From:Generational @ 2014

Deferred Annuity Factor*

* Monthly deferred-to-62 annuity due values at 6.0% interest** Total Employee Rates through age 61 and Healthy Annuitant Rates for ages 62 and above


Appendix 2: Even More Details and Technical Information


Squaring of the Life Curve, 1900-20000 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100

105

110

115

1200

10,00020,00030,00040,00050,00060,00070,00080,00090,000

100,000

Number of Persons Living at Each Age (lx)

190019101920193019401950196019701980

AgeData: SSA Actuarial Study 120 – Periods 1900-2000, 50% male, 50% female

?



105

110

115

1200

10,00020,00030,00040,00050,00060,00070,00080,00090,000

100,000

Number of Males Living at Each Age (lx)

19001910192019301940195019601970198019902000Square

AgeData: SSA Actuarial Study 120 – Periods 1900-2000, male



105

1100

10,00020,00030,00040,00050,00060,00070,00080,00090,000

100,000

Number of Females Living at Each Age (lx)

19001910192019301940195019601970198019902000Square

AgeData: SSA Actuarial Study 120 – Periods 1900-2000, female


Over-weight Obese

Obesity and U.S. Mortality

Sources: Berrington de Gonzalez et al, NEJM, December 2, 2010. Flegal et al, February 1, 2012.

Flagel et al, 2012

Berrington de Gonzalez et al, 2010

15 17.5 20 22.5 25 27.5 30 32.5 35 37.5 40 42.5 45 47.50.50

0.75

1.00

1.25

1.50

1.75

2.00

2.25

2.50

Body Mass Index (BMI)

Haz

ard

Rat

io


Global Life Expectancy ImprovementLife Expectancy at Age 65

76

78

80

82

84

86

88

Source: OECD Health Statistics 2013; 50% male

JapanAustraliaCanadaUKUSA

There is clear evidence that U.S. and Canadian life expectancy

can continue to improve.


Comparison of Mortality Table Rates


RP-2014 vs. RP-2000 Base Rates: Ages 50-80

-0.5%

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

4.0% Probability of Death (qx) RP2000 M Com-binedRP2000 F Com-binedRP2014 M Em-ployeeRP2014 F Em-ployeeRP2014 M Annui-tant Healthy


RP-2014 vs. RP-2000 Base Rates Ages 30-60

-0.1%

0.0%

0.1%

0.2%

0.3%

0.4%

0.5%

0.6%

0.7% Probability of Death (qx)RP2000 M Com-binedRP2000 F Com-bined

RP2014 M Em-ployee



0%

5%

10%

15%

20%

25%

30%

35% Probability of Death (qx)RP2000 M Combined

RP2000 F Combined

RP2014 M Annuitant Healthy

RP2014 F Annuitant Healthy



0%5%

10%15%20%25%30%35%40%45%50% Probability of Death (qx)

RP2000 M Combined

RP2000 F Combined

RP2014 M Annuitant Healthy

RP2014 F Annuitant Healthy


RP-2014 Employees vs. AnnuitantsMale Base Rates

-0.5%

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

4.0% Probability of Death (qx)RP2000 M Com-binedRP2014 M Em-ployee


RP-2014 Employees vs. Annuitants Female Base Rates

-0.5%

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

4.0% Probability of Death (qx)RP2000 F Com-bined

RP2014 F Em-ployee


Comparison of Mortality Projection Scales


Shape of Scale AA

0 7 14 21 28 35 42 49 56 63 70 77 84 91 98 105 112 1190.0%

0.5%

1.0%

1.5%

2.0%

2.5%

MaleFemale

AgeMin (pre85)

0.5%

Grade to 0% > 100

Max2.0%


MP-2014 Average vs AA: Male

30 33 36 39 42 45 48 51 54 57 60 63 66 69 72 75 78 81 84 87 90-0.5%

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

Age

AA

MP-2014

Average annualized mortality improvement rates for the period 2000-2014


MP-2014 Average vs AA: Female

30 33 36 39 42 45 48 51 54 57 60 63 66 69 72 75 78 81 84 87 90-0.5%

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

Age

AA

MP-2014

Average annualized mortality improvement rates for the period 2000-2014


MP-2014 vs Scale AAMale Age 40

40 45 50 55 60 65 70 75 80 85 90 95 100

105

110

115

120

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%40 @201440 @202440 @2034AA

Age


MP-2014 vs Scale BBMale Age 40

40 45 50 55 60 65 70 75 80 85 90 95 100

105

110

115

120

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%40 @201440 @202440 @2034BB

Age


MP-2014 vs Scale AAFemale Age 40

40 45 50 55 60 65 70 75 80 85 90 95 100

105

110

115

120

-0.5%

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%40 @201440 @202440 @2034AA

Age


MP-2014 vs Scale BBFemale Age 40

40 45 50 55 60 65 70 75 80 85 90 95 100

105

110

115

120

-0.5%

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%40 @201440 @202440 @2034BB

Age


MP-2014 vs Scale AAMale Age 65

65 68 71 74 77 80 83 86 89 92 95 98 101

104

107

110

113

116

119

-0.5%

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%65 @201465 @202465 @2034AA

Age


MP-2014 vs Scale BBMale Age 65

65 68 71 74 77 80 83 86 89 92 95 98 101

104

107

110

113

116

119

-0.5%

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%65 @201465 @202465 @2034BB

Age


MP-2014 vs Scale AAFemale Age 65

65 68 71 74 77 80 83 86 89 92 95 98 101

104

107

110

113

116

119

-0.5%

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%65 @201465 @202465 @2034AA

Age


MP-2014 vs Scale BBFemale Age 65

65 68 71 74 77 80 83 86 89 92 95 98 101

104

107

110

113

116

119

-0.5%

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%65 @201465 @202465 @2034BB

Age


MP-2014 vs Scales AA & BBMale Age 40

40 45 50 55 60 65 70 75 80 85 90 95 100

105

110

115

120

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0% 40 @201440 @202440 @2034BBAA

Age


MP-2014 vs Scales AA & BBFemale Age 40

40 45 50 55 60 65 70 75 80 85 90 95 100

105

110

115

120

-0.5%

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0% 40 @201440 @202440 @2034BBAA

Age


MP-2014 vs Scales AA & BBMale Age 65

65 68 71 74 77 80 83 86 89 92 95 98 101

104

107

110

113

116

119

-0.5%

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%65 @201465 @202465 @2034BBAA

Age


MP-2014 vs Scales AA & BBFemale Age 65

65 68 71 74 77 80 83 86 89 92 95 98 101

104

107

110

113

116

119

-0.5%

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0% 65 @201465 @202465 @2034BBAA

Age


MP-2014 vs Scales AA & BBMale & Female

40 45 50 55 60 65 70 75 80 85 90 95 100

105

110

115

120

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0% M AA M BB M40 @2014 M40 @2024F AA F BB F40 @2014 F40 @2024

Age


Bibliography


Bell, Felicitie and Michael Miller, "Life Tables for the United States Social Security Area 1900-2100," Actuarial Study No. 120, http://www.ssa.gov/oact/NOTES/as120/LifeTables_Body.html

Berrington de Gonzalez, A., P. Hartge, J.R. Cerhan, 2010, et al, "Body-Mass Index and Mortality Among 1.46 Million White Adults," New England Journal of Medicine, December 2, 2010.

Center for Disease Control (CDC), National Health and Nutrition Examination Study (NHANES), 2009-2010

David A. Kindig, David A. and Erika R. Cheng, 2013, "Even As Mortality Fell In Most US Counties, Female Mortality Nonetheless Rose In 42.8 Percent Of Counties From 1992 To 2006," Health Affairs, Vol. 32, No. 3, pp. 3451-458.

Flegel, Katherine, Margaret Carroll, Brian Kit and Cynthia Ogden, 2012, "Prevalence of Obesity and Trends in the Distribution of Body Mass Index Among US Adults, 1990-2010," JAMA, February 1, 2012.


Institute for Health Metrics and Evaluation (2013), University of Washington, http://www.healthmetricsandevaluation.org/tools/data-visualization/us-health-map

Institute and Faculty of Actuaries (May 2012), "Variation in Longevity", Longevity Bulletin, Vol. 3.

International Monetary Fund, 2012, “The Financial Impact of Longevity Risk,” Chapter 4 in Global Financial Stability Report, World Economic and Financial Surveys, p. 6 (Washington, April).

Jemal Ahmedin, Elizabeth Ward,Robert N. Anderson, Taylor Murray, Michael J. Thun (2008), "Widening of Socioeconomic Inequalities in U.S. Death Rates, 1993–2001," PLoS ONE, Vol. 3, Issue 5.

Organisation for Economic Co-operation and Development (OECD), OECD Health Statistics 2013, June 27, 2013, http://stats.oecd.org/Index.aspx?DataSetCode=HEALTH_STAT


Sithole, T., S. Haberman, and R. Verrall, June 20, 2011, "Second International Comparative Study of Mortality Tables for Pension Fund Retirees," British Actuarial Journal.

Society of Actuaries, “Mortality Improvement Scale MP-2014,” Exposure Draft, February 2014

Society of Actuaries, “RP-2014 Mortality Tables,” Exposure Draft, February 2014

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Mortality Improvement: Trends and Implications for Pension Plans

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