Mortality Improvement:

Transcription

1 Mortality Improvement: Trends and Implications for Pension Plans Andrew Peterson, FSA, EA, MAAA Lisa Schilling, FSA, EA, MAAA Chicago Actuarial Association March 12, 214 How To Use This PPT Deck This deck of slides is intended to be used as a starting point for an educational presentation that you may want to use for your clients and/or your actuarial staff. Given your audience and your time constraints, you will most likely want to pick and choose the specific slides (or even the specific data series on a graph) that you want to include. For your clients, you may also want to add financial impact slides that are specific to the client. The slides are organized in four general sections (identified by red section-divider slides): The first section is a core group of slides that are most likely to be the basis for a higher-level presentation, followed by Two appendices with more detailed and/or technical information (the 2 nd appendix includes more technical/detailed than the 1 st ), and then A bibliography of sources Speakers notes are included throughout and can be helpful in a variety of ways. As you prepare your presentation, please be sure to read them. Sometimes they provide background and context for the slide or provide suggestions for how to talk about a slide. Sometimes they provide key data points shown in the graph in case you are asked a question. Sometimes they include suggestions for how to coordinate a slide s animation and your comments. 2 1

2 nda Brief history of mortality Trends and observations Related factors Observed mortality improvement New assumptions 3 Mortality in the United States,

3 Number of Deaths per 1, Deaths Number of Deaths per 1, Deaths at Death in 1 4, * 3, 3, 2, 2, 1, 1, Life Expectancy 4 At Birth *13,283 Data: SSA Actuarial Study 12 Periods 1-2, % male, % female at Death in 191 4, * 3, 3, 2, 2, 1, 1, *1,916 Data: SSA Actuarial Study 12 Periods 1-2, % male, % female 6 3

4 Number of Deaths per 1, Deaths Number of Deaths per 1, Deaths at Death in 192 4, * 3, 3, 2, 2, 1, 1, *7,684 Data: SSA Actuarial Study 12 Periods 1-2, % male, % female 7 at Death in 193 4, * 3, 3, 2, 2, 1, 1, *7,684 Data: SSA Actuarial Study 12 Periods 1-2, % male, % female 8 4

5 Number of Deaths per 1, Deaths Number of Deaths per 1, Deaths at Death in 194 4, * 3, 3, 2, 2, 1, 1, *4,72 Data: SSA Actuarial Study 12 Periods 1-2, % male, % female 9 at Death in 1 4, 3, 3, 2, 2, 1, 1, Data: SSA Actuarial Study 12 Periods 1-2, % male, % female 1

6 Number of Deaths per 1, Deaths Number of Deaths per 1, Deaths at Death in 196 4, 3, 3, 2, 2, 1, 1, Data: SSA Actuarial Study 12 Periods 1-2, % male, % female 11 at Death in 19 4, 3, 3, 2, 2, 1, 1, Data: SSA Actuarial Study 12 Periods 1-2, % male, % female 12 6

7 Number of Deaths per 1, Deaths Number of Deaths per 1, Deaths at Death in 19 4, 3, 3, 2, 2, 1, 1, Data: SSA Actuarial Study 12 Periods 1-2, % male, % female 13 at Death in 19 4, 3, 3, 2, 2, 1, 1, Data: SSA Actuarial Study 12 Periods 1-2, % male, % female 14 7

8 Number of Deaths per 1, Deaths Number of Deaths per 1, Deaths at Death in 2 4, 3, 3, 2, 2, 1, 1, Data: SSA Actuarial Study 12 Periods 1-2, % male, % female 1 at Death in 21 (Projected) 4, 3, 3, 2, 2, 1, 1, Data: SSA Actuarial Study 12 Periods 1-2, % male, % female 16 8

9 Number of Deaths per 1, Deaths Trends and Observations 17 Changes Over the Century 4, 3, * 3, 2, 2, 1, 1, *13, Data: SSA Actuarial Study 12 Periods 1-2, % male, % female 9

10 th Century Life Expectancy Improvements At At 4 Birth Data: SSA Actuarial Study 12 Periods 1-2, % male, % female 19 Life Expectancy At UP RP GAT GAM General Population Pension Plan Mortality Tables Population Data: SSA Actuarial Study 12 Periods 1-2, % male, % female, non-decade years interpolated Mortality Tables: 71GAT, 83GAM, RP-2 unprojected, RP-2 (AA generational); % male, % female 2 1

11 Years From Remaining Life Exp. At 71 GAT UP RP GAM General Population Population Data: SSA Actuarial Study 12 Periods 1-2, non-decade years interpolated. Mortality Tables: 71GAT, 83GAM, UP-94,RP-2 unprojected, RP-2 (AA generational), RP-214 (MP-214 generational). All % male, % female th Century Mortality Observations Life expectancy continually increased At birth: dramatic increases, especially pre- 1 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,

12 Related Factors 23 Associated Factors Gender Various factors influence mortality. Some may be reflected to some extent in pension plan valuations. Medical technology Lifestyle Ethnicity / migrant Socioeconomic Longevity Factors Education Genetics Prenatal & childhood conditions Marital Source: Variation in Longevity, Longevity Bulletin, IFA, May

13 Gender Gender Different mortality by gender has long been reflected in pension plan valuations. Lifestyle Medical technology Ethnicity / migrant Longevity Factors Genetics Prenatal & childhood conditions Marital Socioeconomic Education Source: Variation in Longevity, Longevity Bulletin, IFA, May Female Compared to Male Life Expectancy Over the 2 th Century in the U.S. 11% 19% At 4 18% 17% 16% 1% 14% 13% At 12% 11% 1% Data: SSA Actuarial Study 12 Periods

14 Life Expectancy by County: Males Source: Institute for Health Metrics and Evaluation, Life Expectancy by County: Females Source: Institute for Health Metrics and Evaluation,

15 Lifestyle Historical examples: Tobacco use Food safety Work place safety Motor vehicle safety Obesity is one current issue Lifestyle Medical technology Ethnicity / migrant Socioeconomic Gender Longevity Factors Education Genetics Prenatal & childhood conditions Marital Source: Variation in Longevity, Longevity Bulletin, IFA, May U.S. Adult Obesity % % % % 6% % 4% 3% 2% 1% % Not overweight BMI 3 Overweight (not obese) 3<BMI 3 Obese (not extremely so) 3<BMI 4 Extremely obese BMI>4 Source: NHANES, Flegal et al (212); results prior to 2 have been smoothed 3 1

16 Average Mortality Rate in 21 for s 2-64 Socioeconomics & Education Gender Mortality differences for blue vs. white collar workers can also be reflected in a pension plan valuation. Lifestyle Medical technology Ethnicity / migrant Longevity Factors Genetics Prenatal & childhood conditions Marital Socioeconomic Education Source: Variation in Longevity, Longevity Bulletin, IFA, May U.S. Mortality Varies by Education 1.4% 1.2% 1.%.8%.6%.4%.2%.% Higher education levels are linked to higher socio-economic. Both are linked to improved longevity. < Years of Education Black Men Black Women White Men White Women Source: Jemal A, Ward E, Anderson RN, Murray T, et al. (28) Widening of Socioeconomic Inequalities in U.S. Death Rates, PLoS ONE 3(): e2181. doi:1.1371/journal.pone

17 Medicine Historical examples: Antibiotics, immunization, vaccination Imaging (X-ray, CT scan, MRI) Cardiac care and surgery Organ transplants What will future advances bring? Medical technology Lifestyle Ethnicity / migrant Socioeconomic Gender Longevity Factors Education Genetics Prenatal & childhood conditions Marital Source: Variation in Longevity, Longevity Bulletin, IFA, May Pension Plan Relevance Gender Some of these factors might be evident (or likely) in pension plan s population and can be reflected in the valuation of liabilities. Medical technology Lifestyle Ethnicity / migrant Socioeconomic Longevity Factors Education Genetics Prenatal & childhood conditions Marital Source: Variation in Longevity, Longevity Bulletin, IFA, May

18 Years Pension Valuations Around the Globe Assumed Mortality Improvement in 21 vs. Observed Mortality Improvement Since Observed Assumed Source: IMF Global Financial Stability Report, Current Best Practice Assume mortality will continue to improve

19 Observed Mortality Improvement and Previous Assumptions 37 Mortality Improvement Rates Mortality for -year-olds improved (decreased) by 2.% between Historical data source: US (SSA) Male -1; Year Calendar Year

20 Males: MI Rates Medicare began in 1966; mortality improved for all ages. Lagged effect of 196 s antismoking campaigns Historical data source: US (SSA) Male -1; Calendar Year 39 Statin drugs reduced cardiovascular disease HIV/AIDS reduced longevity Females: MI Rates Medicare Mountain Range Silent generation enjoyed relatively high improvement rates Historical data source: US (SSA) Female -1; Calendar Year 4 Statins Less improvement for baby boomers (esp. born ~19) 2

21 Males: Observed MI and AA Data for AA Females: Observed MI and AA Historical data source: US (SSA) Female -1; Data for AA 42 Historical data source: US (SSA) Male - 1;

22 New Mortality and Mortality Improvement Assumptions 43 New Mortality Table for Pension Plans Base table RP-214 replaces RP-2 Private pension plan experience over totaling 1.2 million life-years Rates adjusted to 214 using the new MP-214 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 44 22

23 New Mortality Improvement Scale for Pension Plans Scale MP-214 replaces Scales AA and BB Two dimensions for each gender reflect cohort variations in mortality improvement: Calendar year Intended for use with pension plans; may not be appropriate for insured products Males: Observed MI and MP-214 Historical data source: US (SSA) Male -1;

24 Years From Females: Observed and MP Calendar Year Remaining Life Exp. At 71 GAT UP RP GAM RP 2 w/aa 2. RP214 w/mp General Population 1 Population Data: SSA Actuarial Study 12 Periods 1-2, non-decade years interpolated. Mortality Tables: 71GAT, 83GAM, UP-94,RP-2 unprojected, RP-2 (AA generational), RP-214 (MP-214 generational). All % male, % female

25 Financial Impact of New Tables From RP2 (AA) Percentage Increase in Liability* 18% 16% 14% 12% 1% 8% 6% 4% 2% % M RP & AA F RP & AA 2 3 * Monthly deferred-to-62 annuity due values at 6.% interest; for RP-214, Total Employee Rates through age 61 and Healthy Annuitant Rates for ages and above; RP-2 combined rates with generational projection 49 Financial Impact of New Tables From RP2 (BB) Percentage Increase in Liability* 18% 16% 14% 12% 1% 8% 6% 4% 2% % M RP & BB F RP & BB 2 3 * Monthly deferred-to-62 annuity due values at 6.% interest; for RP-214, Total Employee Rates through age 61 and Healthy Annuitant Rates for ages and above; RP-2 combined rates with generational projection 2

26 Financial Impact of New Tables From UP94 (AA) Percentage Increase in Liability* 18% 16% 14% 12% 1% 8% 6% 4% 2% % M UP94 & AA F UP94 & AA 2 3 * Monthly deferred-to-62 annuity due values at 6.% interest; for RP-214, Total Employee Rates through age 61 and Healthy Annuitant Rates for ages and above; RP-2 combined rates with generational projection 1 Liability* Comparison of RP-214 Specialized Tables: Male 8% 6% 4% 2% % -2% -4% -6% Increase Compared to Total Dataset Table Bottom Quartile Amt Blue Collar White Collar Top Quartile Amt 2 3 *Monthly deferred-to-62 annuity due values using RP-214 with MP-214 generational projection and 6% interest 2 26

27 Liability* Comparison of RP-214 Specialized Tables: Female 8% 6% 4% 2% % -2% -4% -6% Increase Compared to Total Dataset Table Bottom Quartile Amt Blue Collar White Collar Top Quartile Amt 2 3 *Monthly deferred-to-62 annuity due values using RP-214 with MP-214 generational projection and 6% interest 3 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 4 27