SOA 2012 Annual Meeting & Exhibit October 14-17, 2012

Session 39 PD, Modeling Mortality Improvements

in the Pension Arena

Moderator: Andrew J. Peterson, FSA, EA, FCA, MAAA

Presenters:

Robert C. W. Howard, FSA, FCIA Laurence Pinzur, FSA, EA

Primary Competency

Technical Skills & Analytical Problem Solving

1

Session PD 39: Modeling MortalityModeling Mortality Improvements in the Pension Arena

Moderator: Andrew J. Peterson, FSAPresenters: Robert C W Howard FSA FCIA

1

Primary Competency: Primary Competency: Technical Skills & Analytical Problem Solving

Presenters: Robert C.W. Howard, FSA, FCIALaurence Pinzur, Ph.D., FSA

• Basic Concepts

• Historical Mortality Improvement

Agenda

Historical Mortality Improvement

• Future Mortality Improvement

• Example 1: Scale BB

• Example 2: Scale PP04i (draft)

• Financial Implications

• What’s Next

22

• Appendix

2

Basic Concepts

• Historically, SOA mortality improvement (MI) scales have varied only by gender and age; e.g., Scale AA

• More recent models reflect both age and calendar year effects

• Parametric models; e.g., Lee-Carter (L-C) and Cairns, Blake, Dowd (CBD)

• Extrapolative models; e.g., Continuous Mortality Investigation (CMI)

• More recent versions of the parametric models often include a f bi th “ h t” t

33

year-of-birth “cohort” parameter

• Assuming x is the age variable and t is the calendar year variable, the cohort parameter is a function of year-of-birth, (t – x)

Basic Concepts: Scale AA

• Based on SSA and Civil Service mortality data between 1977 – 1993

Scale AA

0.5%

1.0%

1.5%

2.0%

2.5% Max = 2.0%

44

0.0%

0.5%

20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100 105 110

Males Females

Min = 0.5%(pre 80)

Grade to 0% > 100

3

Basic Concepts: 2D MI Models

• Start with a 2-dimensional table of observed mortality rates, qx,t

• qx t = probability that an individual age x at time t dies prior to timeqx,t probability that an individual age x at time t dies prior to time t+1

• For each age, x, and each calendar year, t, calculate the year-over-year change in mortality rates, rx,t

• rx,t = 1 – (qx,t / qx,t-1)

• Example

• q60 1977 = 0.010674; q60 1978 = 0.010329

55

q60,1977 0.010674; q60,1978 0.010329

• r60,1978 = 1- (0.010329 / 0.010674) = 3.23%

• Using rx,t to project mortality rates into the future:

• qx,t+1 = qx,t (1 – rx,t+1)

Basic Concepts: 2D Formulas

)1(

t

basessxbasextx

txtxtx

rqq

rqq

1,,,

,1,,

)1(

)1(

6

4

Historical Mortality Improvement: Heat Maps

Band ColourLess‐1.0%

90 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 # # # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 089 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 # # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 088 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 087 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 086 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Years →

Age Effects

Canada Population: Male 50-90, 1961-2007

1.0%‐0.5%0.0%0.5%1.0%1.5%2.0%2.5%3.0%3 5%

85 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 084 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 083 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 082 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 081 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 080 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 079 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 078 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 077 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 076 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 075 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 074 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 073 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 072 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 071 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 070 # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 069 # # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 068 # # # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 067 # # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0A

ges →

Age Effectss

77

3.5%4.0%4.5%More

67 # # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 066 # # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 065 # # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 064 # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 063 # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 062 # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 061 # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 060 # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 059 # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 058 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 057 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 056 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 055 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 054 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 053 # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 052 # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 051 # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 050 # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Per

iod

Effe

cts

Historical Mortality Improvement; UngraduatedCanada Population: Male 50-90, 1961-2007

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Band ColourLess‐1.0%‐0.5%

84 # # # 0 # 0 0 # 0 0 # 0 0 0 0 # 0 0 0 # 0 0 # # # 0 0 # 0 # 0 0 # # 0 0 0 # 0 0 # 0 0 # 0 0 083 # # # 0 # 0 0 # 0 # 0 0 # # 0 # 0 0 0 # 0 # # 0 # 0 # # # 0 # 0 # 0 0 0 # 0 0 0 0 0 # 0 0 0 #82 0 # # 0 # 0 # # 0 0 0 # 0 # # 0 0 # 0 # # 0 0 0 # # 0 # # 0 0 0 # 0 0 # 0 # 0 0 0 # 0 0 0 0 #81 0 0 # 0 # # 0 # 0 0 # # # 0 0 0 # # 0 # # 0 0 # 0 # 0 # 0 0 0 0 # 0 # 0 # 0 0 0 # 0 # 0 0 0 080 0 0 # 0 0 # 0 # 0 # 0 # # 0 0 0 0 # 0 # 0 # 0 # 0 # 0 # # 0 0 0 0 # # 0 0 0 0 # 0 0 0 0 0 0 079 # 0 # 0 # 0 # 0 # 0 0 # # # 0 # 0 0 # 0 0 # 0 # 0 # 0 0 0 0 0 # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 #78 # 0 # 0 0 # # 0 0 # 0 # # 0 0 # 0 0 # 0 # 0 # 0 # 0 0 # 0 0 # 0 # 0 0 0 0 # 0 0 0 # 0 0 0 0 077 0 0 # 0 # 0 # # 0 0 # # # 0 # 0 # 0 0 # 0 # 0 0 0 # 0 # 0 # 0 0 # # 0 0 # 0 0 0 # 0 0 0 0 0 #76 0 # 0 # # 0 0 # # 0 # 0 0 # 0 # 0 0 0 # # 0 0 # 0 # 0 0 0 0 0 0 # 0 # # 0 0 0 0 0 0 0 0 0 0 075 0 # 0 # # 0 # # 0 # # 0 # 0 # 0 0 # 0 # 0 0 # 0 # 0 # 0 0 0 # 0 0 0 # 0 # 0 # 0 0 0 0 0 0 0 #74 0 0 # # 0 0 0 0 # 0 0 # # # 0 0 0 0 0 # 0 # 0 0 # 0 # # 0 0 # 0 # 0 0 # 0 # 0 0 0 0 # 0 # 0 #73 # 0 0 0 # # 0 # # 0 0 # # 0 0 # 0 0 0 # 0 # 0 0 # 0 0 # 0 0 0 0 # # 0 0 0 0 0 0 0 0 # 0 0 0 #72 0 # 0 0 # 0 # # 0 0 0 # 0 0 0 0 0 0 0 0 0 # # 0 # 0 # 0 0 0 0 # 0 0 0 # 0 0 0 0 0 # 0 0 0 0 071 0 # # 0 0 # 0 # 0 # # # 0 # 0 # 0 0 0 0 0 # 0 # 0 0 0 # 0 0 0 # # 0 # # 0 0 0 0 0 0 # 0 0 0 070 0 # # 0 # 0 # 0 # # # 0 # # 0 # # 0 0 # 0 # 0 0 0 # 0 # 0 0 0 0 0 # # 0 0 # 0 0 0 # 0 0 0 0 069 # # 0 0 0 0 0 # # 0 0 # 0 0 0 0 # 0 0 # 0 0 # 0 0 # 0 0 # 0 # 0 0 0 # 0 # 0 # 0 # 0 0 0 # 0 #68 0 0 # # 0 # # # 0 0 0 0 # # 0 # 0 0 # 0 0 # 0 0 # 0 0 # 0 # 0 0 # 0 # 0 0 # 0 0 0 # 0 # 0 0 #67 # # # 0 0 # # # 0 # 0 0 0 # 0 0 # 0 0 0 0 0 0 # 0 0 # 0 0 0 # 0 # 0 0 # 0 0 0 # 0 # 0 0 0 0 066 # 0 0 # 0 # # 0 # 0 0 # 0 # # 0 0 # 0 0 0 0 0 0 # 0 0 # 0 0 # 0 0 0 0 # 0 # 0 0 0 # 0 0 0 0 0

0.0%0.5%1.0%1.5%2.0%2.5%3.0%3.5%4.0%4.5%

88

66 # 0 0 # 0 # # 0 # 0 0 # 0 # # 0 0 # 0 0 0 0 0 0 # 0 0 # 0 0 # 0 0 0 0 # 0 # 0 0 0 # 0 0 0 0 065 # 0 # 0 # 0 0 # 0 # 0 # # 0 0 0 0 0 0 # 0 # 0 0 # 0 0 # 0 0 0 0 # 0 0 0 0 0 0 0 0 # 0 0 0 0 064 0 # # # # 0 # 0 # 0 0 # # 0 0 0 0 # 0 0 0 # 0 # 0 # 0 # 0 0 0 0 0 # 0 # 0 0 0 # 0 # 0 0 0 # 063 0 0 # # 0 # # 0 0 # 0 0 # 0 # 0 # 0 0 0 # 0 0 # 0 0 # # 0 0 0 0 # # 0 0 0 0 0 0 0 # 0 0 0 0 062 0 # 0 0 # # 0 0 0 # 0 # # 0 0 # 0 0 # # 0 0 0 # 0 # 0 0 0 0 0 0 0 0 0 0 0 0 0 # # 0 # 0 0 0 061 # 0 0 # # 0 0 0 # # 0 # 0 # 0 0 0 # 0 0 # 0 0 # 0 0 0 # 0 0 0 0 0 # 0 0 0 0 0 0 0 0 # # 0 0 #60 0 0 # # 0 0 # # 0 # 0 0 # 0 0 0 # 0 0 0 0 0 0 # 0 0 0 # 0 0 0 # 0 # 0 0 # 0 # 0 # 0 0 0 0 # #59 0 # 0 0 # # # 0 # 0 0 # 0 0 0 0 0 0 0 0 0 0 # 0 0 0 # 0 0 0 # 0 # 0 0 0 0 0 0 0 0 0 0 0 0 # 058 0 # # 0 0 # 0 # 0 0 0 # # 0 # 0 0 # 0 0 0 # 0 0 0 # 0 0 # 0 # 0 0 # 0 0 0 0 # 0 0 0 # 0 # 0 #57 0 # # 0 # 0 # 0 0 0 # 0 # 0 0 0 # 0 0 0 0 0 0 0 0 # 0 0 0 0 0 # 0 0 0 0 # # 0 0 0 0 0 # # 0 #56 # 0 # # 0 # 0 # 0 # 0 0 # 0 0 # 0 0 0 0 # 0 0 0 # 0 0 0 0 0 0 # 0 0 0 # 0 0 0 # 0 # 0 0 0 0 #55 0 # # 0 # 0 # 0 # 0 # 0 # 0 # 0 # 0 # 0 0 0 0 0 # 0 0 0 # 0 0 # 0 0 # 0 0 0 # 0 0 # 0 0 # 0 #54 # 0 # # # 0 # 0 # 0 # 0 0 # 0 # 0 # 0 # 0 0 0 0 # 0 0 0 0 0 0 0 # 0 # 0 0 0 # 0 # 0 # 0 0 # 053 # 0 0 # # # 0 0 0 0 # 0 # # 0 0 # 0 0 0 0 0 # 0 0 # 0 0 0 0 # 0 0 0 # 0 0 0 0 # 0 0 # 0 0 0 #52 0 # # 0 # 0 # 0 # # 0 # # 0 # 0 # 0 0 # 0 0 0 0 0 0 0 0 0 # 0 0 # 0 0 0 # 0 # 0 0 0 # 0 0 # #51 # # 0 0 # # 0 0 # 0 # 0 0 # # # 0 0 0 0 0 # 0 0 0 # 0 0 0 # 0 0 # 0 # 0 0 # 0 0 # 0 0 # # 0 #50 0 0 # 0 0 # 0 0 # # 0 0 # # 0 0 # 0 0 0 0 # 0 0 # 0 0 0 0 0 0 0 0 # # 0 0 0 0 # 0 # 0 0 0 # #

More

5

Historical Mortality Improvement; Graduated h=1, v=1Canada Population: Male 50-90, 1961-2007

90 0 0 0 0 0 0 0 0 0 0 0 # 0 0 0 0 0 0 0 0 0 # # # # # 0 0 0 0 0 0 0 # # # # 0 0 0 0 0 0 0 0 0 089 # # 0 0 0 0 0 0 0 0 0 # 0 0 0 0 0 0 0 0 0 # # # # # 0 0 0 0 0 0 # # # # 0 0 0 0 0 0 0 0 0 0 088 # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 # # # # # 0 0 0 0 0 # # # # 0 0 0 0 0 0 0 0 0 0 087 # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 086 # # # 0 0 0 0 0 0 0 0 # 0 0 0 0 0 0 0 0 0 0 0 0 # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 085 # # # 0 0 0 0 0 0 0 0 # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 084 # # # 0 0 0 0 0 0 0 # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Band ColourLess‐1.0%‐0.5%

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0.0%0.5%1.0%1.5%2.0%2.5%3.0%3.5%4.0%4.5%

99

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More

90 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 # # # # # # 0 0 0 # # # # 0 0 0 0 0 0 0 0 0 0 0 089 # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 # # # # # 0 0 0 # # # 0 0 0 0 0 0 0 0 0 0 0 0 088 # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 087 # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 086 # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 085 # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

# # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Band ColourLess‐1.0%‐0.5%

Historical Mortality Improvement; Graduated h=10, v=10Canada Population: Male 50-90, 1961-2007

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0.0%0.5%1.0%1.5%2.0%2.5%3.0%3.5%4.0%4.5%

1010

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Band ColourLess‐1.0%‐0.5%

Historical Mortality Improvement; Graduated h=100, v=100 Canada Population: Male 50-90, 1961-2007

85 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 084 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 083 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 082 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 081 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 080 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 079 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 078 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 077 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 076 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 075 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 074 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 073 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 072 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 071 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 070 0 0 0 0 # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 069 # # # # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 068 # # # # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 067 # # # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0.0%0.5%1.0%1.5%2.0%2.5%3.0%3.5%4.0%4.5%

1111

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Band ColourLess‐1.0%‐0.5%

Historical Mortality Improvement; Graduated h=1k, v=1k Canada Population: Male 50-90, 1961-2007

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0.0%0.5%1.0%1.5%2.0%2.5%3.0%3.5%4.0%4.5%

1212

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7

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Band ColourLess‐1.0%‐0.5%

Historical Mortality Improvement; Graduated h=10k, v=10k Canada Population: Male 50-90, 1961-2007

84 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 083 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 082 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 081 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 080 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 079 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 078 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 077 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 076 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 075 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 074 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 073 # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 072 # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 071 # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 070 # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 069 # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 068 # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 067 # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 066 # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0.0%0.5%1.0%1.5%2.0%2.5%3.0%3.5%4.0%4.5%

1313

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Band ColourLess‐1.0%‐0.5%

Historical Mortality Improvement; Graduated h=400, v=150 Canada Population: Male 50-90, 1961-2007

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Band ColourLess‐1.0%‐0.5%

Historical Mortality Improvement; Graduated h=400, v=150 Canada Population: Female 50-90, 1961-2007

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Historical Mortality Improvement; Graduated h=400, v=150 Canada Population: Male / Female Comparison

81 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 080 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 079 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 078 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 077 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 076 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 075 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 074 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 073 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 072 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 071 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 070 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 069 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 068 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 067 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 066 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 065 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 064 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 063 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 062 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 061 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 060 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 059 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 058 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 057 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 056 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 055 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

81 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 080 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 079 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 078 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 077 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 076 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 075 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 074 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 073 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 072 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 071 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 070 # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 069 # # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 068 # # # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 067 # # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 066 # # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 065 # # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 064 # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 063 # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 062 # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 061 # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 060 # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 059 # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 058 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 057 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 056 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 055 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

1616

55 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 054 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 053 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 052 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 051 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 050 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

55 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 054 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 053 # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 052 # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 051 # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 050 # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

9

Canada Pension PlanMale / Female, 65-95, 1976-2007

95 # # # # # # # # # # # # # # # # # # # # # # # # # 0 0 0 0 0 0 094 # # # # # # # # # # # # # # # # # # # # # # # 0 0 0 0 0 0 0 0 093 # # # # # # # # # # # # # # # # # # # # # # # 0 0 0 0 0 0 0 0 092 # # # # # # # # # # # # # # # # # # # # # # 0 0 0 0 0 0 0 0 0 091 # # # # # # # # # # # # # # # # # # # # # 0 0 0 0 0 0 0 0 0 0 090 # # # # # # # # # # # # # # # # # # # # 0 0 0 0 0 0 0 0 0 0 0 0

95 # # # # # # # # # # # # # # # # # # # # # # # # # 0 0 0 0 0 0 094 # # # # # # # # # # # # # # # # # # # # # # # # # 0 0 0 0 0 0 093 # # # # # # # # # # # # # # # # # # # # # # # # 0 0 0 0 0 0 0 092 # # # # # # # # # # # # # # # # # # # # # # # # 0 0 0 0 0 0 0 091 # # # # # # # # # # # # # # # # # # # # # # # # 0 0 0 0 0 0 0 090 # # # # # # # # # # # # # # # # # # # # # # # 0 0 0 0 0 0 0 0 090 # # # # # # # # # # # # # # # # # # # # 0 0 0 0 0 0 0 0 0 0 0 0

89 # # # # # # # # # # # # # # # # # # # # 0 0 0 0 0 0 0 0 0 0 0 088 # # # # # # # # # # # # # # # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 087 # # # # # # # # # # # # # # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 086 # # # # # # # # # # # # # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 085 # # # # # # # # # # # # # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 084 # # # # # # # # # # # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 083 # # # # # # # # # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 082 # # # # # # # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 081 # # # # # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 080 # # # # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 079 # # # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 078 # # # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 077 # # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 076 # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 075 # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 074 # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 073 # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 072 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

90 # # # # # # # # # # # # # # # # # # # # # # # 0 0 0 0 0 0 0 0 089 # # # # # # # # # # # # # # # # # # # # # # 0 0 0 0 0 0 0 0 0 088 # # # # # # # # # # # # # # # # # # # # # # 0 0 0 0 0 0 0 0 0 087 # # # # # # # # # # # # # # # # # # # # # 0 0 0 0 0 0 0 0 0 0 086 # # # # # # # # # # # # # # # # # # # # # 0 0 0 0 0 0 0 0 0 0 085 # # # # # # # # # # # # # # # # # # # # 0 0 0 0 0 0 0 0 0 0 0 084 # # # # # # # # # # # # # # # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 083 # # # # # # # # # # # # # # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 082 # # # # # # # # # # # # # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 081 # # # # # # # # # # # # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 080 # # # # # # # # # # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 079 # # # # # # # # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 078 # # # # # # # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 077 # # # # # # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 076 # # # # # # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 075 # # # # # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 074 # # # # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 073 # # # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 072 # # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

1717

71 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 070 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 069 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 068 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 067 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 066 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 065 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

71 # # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 070 # # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 069 # # 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 068 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 067 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 066 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 065 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Canada Pension Plan, Income ClassesMale 65-95, 1988-2007

1818

0-30% Max Pension 30-95% Max Pension 95%+ Max Pension

10

Canada Pension Plan, Income ClassesFemale 65-95, 1988-2007

1919

0-30% Max Pension 30-95% Max Pension 95%+ Max Pension

Historical Mortality Improvement Rates*US (SSA) Male 50-100; 1950-2005

2020

* Graduated using P-spline methodology

11

Historical Mortality Improvement Rates*US (SSA) Female 50-100; 1950-2005

2121

* Graduated using P-spline methodology

England & Wales Canada US

Historical Mortality Improvement Comparison

• Comparison of Heat Maps for Males

England & Wales Canada US

2222

12

• Comparison of Heat Maps for Females

England & Wales Canada US

Historical Mortality Improvement Comparison

England & Wales Canada US

2323

• The challenge: How to extend these rates to the right?

Future Mortality Improvement

?

2424

13

• Here’s what Scale AA (males) looks like

Future Mortality Improvement

Historic SSA Male MI Rates Scale AA (male)

2525

• Here’s what Scale AA (females) looks like

Future Mortality Improvement

Scale AA (female)Historic SSA Female MI Rates

2626

14

• CMI, part of the Institute and Faculty of Actuaries in the UK, carries out ongoing mortality/morbidity research

Future Mortality Improvement Overview of the CMI Model

• CMI_2009 projection model released in June 2009; Working Paper (WP) 41

• Core model

• Advanced model

• Annual updates…

• CMI 2010 released in November 2010 (WP 49)

2727

CMI_2010 released in November 2010 (WP 49)

• CMI_2011 released in September 2011 (WP 55)

• … but no substantive changes to underlying methodology

• Initial MI rates are based on recent historical trends

• The long-term MI rate is an open parameter in the model (both Core

Future Mortality Improvement Overview of the CMI Model

g p p (and Advanced)

• The methodology for grading (up or down) from the initial set of MI rates to the selected long-term rate can get quite complex

Ra

tes

2828

?

Lo

ng

-Te

rm R

?

15

Assumption Core Model Advanced Model

Future Mortality ImprovementOverview of the CMI Model: Key Assumptions

Long-Term RateUser-specified flat %

(up to age 90)User-specified flat % or table of gender/age %’s

Cohort Convergence Period (in years)

User-specified

Age/Period Convergence Period (in years)

User-specified

2929

Percentage of Cohort and Age/Period Effects Remaining at Midpoint of Convergence Period

50% User-specified

Example 1: Scale BB

RPEC’s Three Primary Objectives for Current Releaseof Scale BB

• To share the results that show that the rates of mortality improvement in the US over the recent past have differed quite substantially from those predicted by Scale AA

• To provide an alternative to Scale AA that is based on more recent data and newly developed techniques, and that can be used immediately without any changes to existing valuation software; and

3030

• To provide users and developers of actuarial software lead time prior to the release of the next generation of pension mortality improvement scales, which, in keeping with newer techniques, are likely to be two dimensional

16

Scale BB: RPEC’s Process

• Collect/review historic (2D) US mortality rates

• RPEC used US general population mortality data from the Social g p p ySecurity Administration (SSA)

• Develop 2D table of historic mortality improvement rates

• Consistent with other large public plan MI results

• Test/select MI methodology and assumptions

• CMI model applied to SSA data

• Select model assumptions (see next page)

3131

• Select model assumptions (see next page)

• Develop smoothed 2D arrays of MI rates (Scale “BB-2D”)

• Convert Scale BB-2D rates to “age-only” Scale BB

Assumption Scale BB-2D

Scale BB: Key Assumptions

Long-Term RateFlat 1.0% to age 90; grades linearly to 0% at age 120

Cohort Convergence Period 10 years (up to age 90)

Age/Period Convergence Period CMI Core (max 20 years)

3232

Percentage of Cohort and Age/Period Effects Remaining at Midpoint of Convergence Period

CMI Core (50%)

17

Scale BB: RPEC’s 2D Model (Scale BB-2D(M))

• Resulting RPEC 2D MI rates for males

3333

• Resulting RPEC 2D MI rates for females

Scale BB: RPEC’s 2D Model (Scale BB-2D(F))

3434

18

Scale BB: Conversion of 2D to Age-Only Rates

• RPEC recognized that there are practical issues with using 2D MI tables in current pension valuations

• Most pension software cannot easily accommodate 2D MI scales

• Some applications might not warrant using 2D MI scales

• Therefore, the committee converted the 2D rates to age-only rates; this is Scale BB

• Age-only rates were developed to approximately match annuity values determined using full set of 2D rates

• Scale BB can be used immediately!

3535

y

• RPEC still encourages generational application of all MI rates

Scale BB (Males)

I t ti ll l ft bl k iti SOA B d lMale Mortality Improvement Scales

<Intentionally left blank; awaiting SOA Board approval>

0 2%0.4%

0.6%0.8%

1.0%

1.2%1.4%

1.6%1.8%

2.0%

3636

0.0%

0.2%

20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100 105 110

BB AA

19

Scale BB (Females)

I t ti ll l ft bl k iti SOA B d lFemale Mortality Improvement Scales

<Intentionally left blank; awaiting SOA Board approval>

0 2%0.4%

0.6%

0.8%

1.0%1.2%

1.4%

1.6%1.8%

2.0%

3737

0.0%

0.2%

20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100 105 110

BB AA

• Example: Grade to 80% of BB-2D between 2005 and 2045

h(y) = 1.0 for y ≤ 2005;

Modifying Scale BB-2D

(y) 0 o y 005;h(y) = 1.0 – 0.2 * [(y-2005)/40] for 2006 ≤ y <2045 h(y) = 0.8 for y ≥ 2045

3838

50

100

20

• Example: Grade to 80% of BB-2D between 2005 and 2045

Modifying Scale BB-2D

2004 2005 2006 2007 … 2024 2025 … 2043 2044 2045 2046h(y) 1.00000 1.00000 0.99500 0.99000 … 0.90500 0.90000 … 0.81000 0.80500 0.80000 0.80000

Unmodified BB-2D Female Rates At Ages 64, 65, and 66

64 2.140% 2.260% 2.100% 2.000% … 1.000% 1.000% … 1.000% 1.000% 1.000% 1.000%65 2.330% 2.470% 2.260% 2.060% … 1.000% 1.000% … 1.000% 1.000% 1.000% 1.000%66 2.430% 2.620% 2.460% 2.210% … 1.000% 1.000% … 1.000% 1.000% 1.000% 1.000%

Modified BB-2D Female Rates At Ages 64, 65, and 66 (per Section 7.4 Suggested Approach)

64 2.140% 2.260% 2.090% 1.980% … 0.905% 0.900% … 0.810% 0.805% 0.800% 0.800%65 2.330% 2.470% 2.249% 2.039% … 0.905% 0.900% … 0.810% 0.805% 0.800% 0.800%66 2.430% 2.620% 2.448% 2.188% … 0.905% 0.900% … 0.810% 0.805% 0.800% 0.800%

Calendar Year, y

3939

• Note: Modified rates are 2D; not “age-only” like Scale BB

• Start with HMD (to 2007)

• Minor adjustment for CCPME experience

Example 2: Scale PP04i (draft)

Minor adjustment for CCPME experience

• Ultimate (2027+) is 75% of 30-yr unisex average

• Intermediate (2017) is 20-yr average of HMD

• Linear interpolation 2018-2026

• Cubic interpolation 2008-2016

4040

21

PP04i (draft)Male / Female 50-95, 1999-2027

95 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 094 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 093 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 092 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 091 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 090 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

95 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 094 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 093 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 092 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 091 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 090 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Band ColourLess‐1.0%‐0.5%0.0%

89 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 088 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 087 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 086 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 085 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 084 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 083 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 082 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 081 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 080 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 079 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 078 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 077 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 076 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 075 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 074 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 073 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 072 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 071 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

89 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 088 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 087 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 086 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 085 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 084 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 083 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 082 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 081 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 080 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 079 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 078 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 077 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 076 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 075 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 074 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 073 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 072 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 071 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0.5%1.0%1.5%2.0%2.5%3.0%3.5%4.0%4.5%More

41

71 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 070 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 069 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 068 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 067 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 066 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 065 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 064 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 063 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 062 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 061 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 060 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

71 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 070 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 069 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 068 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 067 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 066 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 065 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 064 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 063 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 062 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 061 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 060 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Compare scales ‐Male 2007

Comparison of Improvement Scales

1%

2%

3%

4242

0%

65 70 75 80 85 90 95

AA BB‐2D CPP PP04i

22

Compare scales ‐Male 2017

Comparison of Improvement Scales

1%

2%

3%

4343

0%

65 70 75 80 85 90 95

AA BB‐2D CPP PP04i

Compare scales ‐Male 2027

Comparison of Improvement Scales

1%

2%

3%

4444

0%

65 70 75 80 85 90 95

AA BB‐2D CPP PP04i

23

Compare scales ‐Male 2037

Comparison of Improvement Scales

1%

2%

3%

4545

0%

65 70 75 80 85 90 95

AA BB‐2D CPP PP04i

Financial ImplicationsAnnuity of $1 Starting in 2013; 4% Interest Rate

• RP-2000 Combined Healthy base table• Project mortality improvement generationally under different scales

AA BB BB‐2D BB BB‐2D

M55 16.15 16.37 16.42 1.3% 1.6%

M65 12.44 12.80 12.94 2.9% 4.0%

M80 6.24 6.68 6.83 7.1% 9.4%

F55 16.57 17.10 17.21 3.2% 3.8%

Annuity Value  over AA

4646

F65 13.17 13.72 13.89 4.1% 5.4%

F80 7.41 7.86 7.97 6.0% 7.5%

24

Financial ImplicationsAnnuity of $1 Starting in 2013; 4% Interest Rate

• PP04 (draft) base table• Project mortality improvement generationally under different scales

AA BB‐2D CPP PP04i BB‐2D CPP PP04i

M55 16.73 16.94 17.03 17.35 1.2% 1.8% 3.6%

M65 13.19 13.55 13.62 14.00 2.8% 3.3% 6.2%

M80 6.77 7.23 7.18 7.60 6.8% 6.0% 12.3%

F55 17.44 17.92 17.71 18.00 2.8% 1.6% 3.3%

F65 14 23 14 78 14 54 14 86 3 9% 2 2% 4 4%

 over AAAnnuity Value

4747

F65 14.23 14.78 14.54 14.86 3.9% 2.2% 4.4%

F80 7.98 8.46 8.21 8.58 6.0% 2.9% 7.5%

Financial ImplicationsAnnuity of $1 Starting in 2013; 4% Interest Rate

• Change both base table and projection scales

UP94 on AA PP04 on PP04i

M55 16.11 17.35 7.7%

M65 12.49 14.00 12.1%

M80 6.52 7.60 16.5%

F55 16.86 18.00 6.8%

F65 13 55 14 86 9 7%

Annuity Value

4848

F65 13.55 14.86 9.7%

F80 7.67 8.58 11.9%

25

What’s Next – CIA’s CCPME

• Two papers in draft form

• First tables based on Canadian pensionersFirst tables based on Canadian pensioners

• Improvement scales along with base tables

• Working toward a single proposal

• Need to publish by the end of the year

4949

What’s Next – SOA’s RPEC

• RPEC’s larger Pension Mortality Project is still in progress

• Targeted for late 2013; exposure drafts of:Targeted for late 2013; exposure drafts of:

• New base mortality tables for pension plans (replacements for RP-2000), and

• New mortality improvement scale (replacement for Scale BB); likely 2D

• Final reports for both targeted for early 2014

• Current research project to find out more about US mortality

5050

Current research project to find out more about US mortality improvement patterns, especially

• Extent and persistence of cohort effects

• Variations due to socio-economic factors

26

What’s Next for Pension Actuaries in N.A.

• Keep abreast of latest research

It’s time to “get up to speed” on mortality/longevity topics

Keep abreast of latest research

• Reread ASOP 35 and other relevant guidance

• Review current mortality assumptions in light of new research

• When was the last time you performed a mortality experience study?

• Assess financial impact of updating mortality assumptions

• 2012 year-end disclosures and 2013 budgets

5151

• Start discussions regarding implications of longer life expectancies with plan sponsors

Appendix

5252

27

Pace of Future Mortality Improvements

Faster Slower

• Lifestyle changes

• Medical research

• Breakthroughs

• Japanese

• Smoker prevalence

• Obesity

• Health care funding

• Geriatrics

53

Scale BB: 1.0% Long-Term Rate (LTR)

• Wide range of opinion regarding long-term rate of MI in the US

• “Optimists” and “Pessimists”

• Between 1950 and 2000, the age-sex-adjusted SSA death rates in the US declined at an average rate of 1.06% per year

• 2011 SSA age-sex-adjusted LTR for age 65 and over was 0.72%

• SSA assumes an “age gradient” in their long-term rates

• RPEC assigned particular credence to the Technical Panel on Assumptions and Methods appointed every four years by the Social Security Advisory Board

5454

Social Security Advisory Board

• 2007 Technical Panel: Recommended LTR = 1.0%

• 2011 Technical Panel: Recommended an even higher LTR

28

CMI Model Applied to Canada HMD Data (M)

• Using same assumptions as BB-2D (including 1.0% long-term rate)

Males

5555

CMI Model Applied to Canada HMD Data (F)

• Using same assumptions as BB-2D (including 1.0% long-term rate)

Females

5656