By: Pierre-Carl Michaud, Industrial Alliance Research Chair on the Economics of Demographic Change At Sherbrooke International Life Sciences Summit - 2nd edition | September 28/29/30 2015 www.sils-sherbrooke.com

1. FUTURE LONGEVITYAND POPULATION
HEALTH IMPROVEMENTS: AN ECONOMIC
PERSPECTIVE
Pierre-Carl Michaud, ESG UQAM and CIRANO
Industrielle Alliance Research Chair on the Economics
of Demographic Change

2. Evolution of Life Expectancy, 1980-2010
72
74
76
78
80
82
84
1980 1985 1990 1995 2000 2005 2010
Life Expectancy at Birth, OECD
Germany Australia Canada United States
France Japan United Kongdom
Source: OECD
2

3. Evolution of Life Expectancy, Canada
Source: OECD
72
74
76
78
80
82
84
86
88
90
1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050
Trend in Life Expectancy (years)
Observed
Projected
Lots of
Uncertainty
3

4. Cause for Optimism: Medical Progress
• Medical research had important impact on life expectancy
4

5. But Concentrated Improvement: Cardiovascular Disease
Source : Cutler et al. (NEJM, 2006)
5
Causes of Increases in Life Expectancy among Newborns, 1960-2000

6. Cause for Optimism: Medical Progress
• Most medical research remains focused on combating
individual diseases
• Recent scientific advances suggest that slowing the aging
process is now a realistic goal
6

7. Cause for Pessimism: Recent Evolution…
7

8. The Rise of Obesity
• The World Health Organization (WHO) estimates in 2014 that, worldwide:
• More than 1.9 billion adults are overweight
• 600 million are obese
• In the U.S., the prevalence of obesity has more than doubled
• 15% in 1971-1975 (Cutler, Glaeser and Shapiro, 2003)
• 35% in 2012 (Ogden et al.; JAMA 2014)
• In Europe, obesity rates are generally lower than in the U.S (Sanz-de-
Galdeano, 2007; Andreyeva et al., 2007)
• But the rising trend in obesity is seen as a serious threat to public health
8

9. Prevalence of Obesity Among Adults (18+ y.o.), 2004
Source: OECD (2005)
0%
5%
10%
15%
20%
25%
30%
35%
Austria (1999) Denmark
(2000)
France (2002) Germany Italy Netherlands Spain Sweden U.K. U.S.
Prevalence of Obesity (%)
9

10. Health Disparities Between Europe and the U.S.
3.9
5.1
1.5
2.9 3.0
18.2
10.5
11.8
2.5
5.5 5.0
35.4
0
10
20
30
40
Heart Diabetes Stroke Lung Cancer Hypertension
Prevalence of Disease (%)
Among population aged 50-53 y.o.
Europe USU.S.
Heart Lung
Diseases
Notes: Comparing populations aged 50-53 in the U.S. Health and Retirement Study of 2004 and in the Survey of Health, Ageing and Retirement
(SHARE) of 2004 (Denmark, France, Germany, Greece, Italy, The Netherlands, Spain, Sweden). Data from Austria and Switzerland not included
because of lack of appropriate population weights and of low response rate and small sample, respectively. Sample weights used.
10

11. 26
27
28
29
30
31
32
33
1975 2005
Remaining Life Years at Age 50
Europe
USU.S.
Life Expectancy at 50 y.o.
Notes: Data come from the Human Mortality Database period life tables for 1975 and 2005. European countries are Denmark, France,
Italy, The Netherlands, Spain and Sweden. Weighted average using population size at age 50.
1.5 years
gap
**27.1
27.2
32.5
31.0
11

12. What are the Economic Implications of These Trends?
• Improving health:
• Higher productivity, longer careers
• Reduced health spending and dependence on welfare
programs
• Improving longevity:
• Larger retired population
• Pension benefits paid out over longer periods
• Improving well-being:
• Living longer and healthier has other non-monetary
benefits for which monetary value can be calculated
12

13. Illustration 1: What These differences in Health Between
U.S. and Europe Mean in Economic Terms
• Appropriate model to answer this type of questions:
• Microsimulation model
• Simulation of individuals aged 50 years old in 2004
• Using the Future Elderly Model (FEM)
• 2 scenarios:
• Status quo Americans
• Americans with Health of the Europeans
• All others characteristics are kept constant
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14. Health Explains an Important Part of the Difference
1.3
-0.1
1.2
-0,4
0,0
0,4
0,8
1,2
1,6
Healthy Disabled Net
Additional Life-Years Under “Healthy European
Scenario”
Relative to status quo
Source: Michaud et al. (Social Science & Medicine, 2011) 14

15. 138 123 144 716
73 391 68 674
21 745 18 058
0
50 000
100 000
150 000
200 000
250 000
Status Quo Healthier
Scenario
Expenditures
Effects on Public Finances in the U.S. ($ per capita)
15
46 289
0
47 637
16 035 16 535
16 566 17 031
0
20 000
40 000
60 000
80 000
100 000
Status Quo Healthier
Scenario
Revenues
Federal Tax
State Tax
SS Payroll Tax
Medicare
Payroll Tax
OASI
Medicare
Medicaid
Source: Michaud et al. (Social Science & Medicine, 2011)
Δ = +$2,425
per capita
Δ = -$2,477
per capita
82,910 85,335
243,069 240,592
SSI DI

16. Illustration 2: What is the Economic Value of Investing in
Research That “Delays Aging”?
• Research that has the potential to extend life while reducing
the prevalence of comorbidities over the entire lifetime
• At the practical level, delayed aging means having the body
and mind of someone who is years younger than the majority
of today’s population at one’s chronological age
• There is evidence that centenarians (whose longevity is at
least partially inheritable) often have delayed onset of age-
related diseases and disabilities, which suggests that they
senesce (grow old biologically) more slowly than the rest of
the population
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17. Possible Consequences
• Delayed aging could increase life expectancy by an additional
2.2 years, most of which would be spent in good health
(Goldman et al 2013)
• The economic value of delayed aging is estimated to be
$7.1 trillion over 50 years
• Delayed aging would greatly increase entitlement outlays,
especially for Social Security
• However, these changes could be offset by increasing the
Medicare eligibility age and the normal retirement age for Social
Security
17

18. We Developed Four Scenarios
• Baseline Scenario
• Delayed Cancer Scenario
• We reduced the incidence of cancer over time. We phased in a
linear 25% reduction in cancer incidence over the period 2010-30
• Delayed Heart Disease Scenario
• We reduced the incidence of heart disease over time. We assumed
a linear reduction in the incidence of 25% between 2010 and 2030
• Delayed Aging Scenario
• We assumed that improvements in mortality and health started
earlier in life than they did in the disease-specific scenarios
• We assumed that the slope of the mortality curve observed in 2000
will decline by 20%
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19. Delayed Aging vs. Single-Disease Approach
0
20
40
60
80
100
120
2010 2020 2030 2040 2050 2060
Population 65 and Older
(millions)
Baseline
Delayed Heart
Disease
Delayed Aging
SOURCE: Authors’ calculations using the Future Elderly Model.
Notes: Population 65 years of age and older under various medical progress scenarios. Delayed aging results in substantially
higher population projections relative to reductions in heart disease or cancer alone.
Delayed aging increases the
number of persons aged 65+, with
an economic value of $4.3 trillion
19

20. Delayed Aging Increases Government Medical Spending
-50
0
50
100
150
200
250
300
350
2010
2020
2030
2040
2050
2060
Change in Medical Spending Relative to Baseline
(billions of $, 2010)
Medical under
Delayed Cancer
Medical under
Delayed Heart
Disease
Medical under
Delayed Aging
SOURCE: Authors’ calculations using the Future Elderly Model
Notes: Projected government medical spending under various medical progress scenarios, relative to baseline. Medical spending includes all
Medicare and Medicaid spending on Americans aged 51+. Medical spending is much higher under the delayed aging scenario because of the larger
increase in the total population, even though per period costs for Medicare are lower.
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21. Effect of Changing the age of Medicare Eligibility
-500
0
500
1000
1500
2000
2500
3000
3500
2010
2020
2030
2040
2050
2060
Change in Government Spending Relative to Baseline
(billions of $, 2010)
Delayed Cancer
Delayed Heart Disease
Delayed Aging without
Eligibility Fix
Delayed Aging with
Eligibility Fix
SOURCE: Authors’ calculations using the Future Elderly Model
Notes: Cumulative fiscal impact of delayed aging scenario, with and without Medicare eligibility changes, with a 3% annual discount rate. The
inclusion of this eligibility fix would result in no additional government spending relative to the current baseline, despite much larger increases in the
older population.
• The eligibility fix refers to a gradual increase in the eligibility age for
Medicare from 65 to 68, and for Social Security from 67 to 68 (i.e. extending
the existing trend for about 10 years)
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22. Conclusion
• There is great uncertainty as to the likely course of life expectancy:
two key forces at play
• From an economic standpoint, the rise of obesity and increase in
various health conditions is bad news with large impacts on the
capacity of our governments to fund other valuable programs (e.g.
education, climate change)
• The potential of medical innovation to deliver large increases in life
expectancy/health will depend on whether or not it is targeted
towards diseases or towards aging itself
• The argument that improvements in health will run the government
bankrupt assumes programs cannot be adjusted. Modest changes
can be implemented so that medical progress delivers large welfare
benefits while remaining “revenue-neutral”.
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23. Collaborators
• From the U.S.
• Dana Goldman, Darius Lakdawalla & Yuhui Zheng, University of Southern
California
• Adam Gailey & Frederico Girosi, RAND Corporation
• Jeffrey Sullivan, Precision Health Economics
• David Cutler, Harvard University
• John Rowe, Columbia University
• S. Jay Olshansky, University of Illinois at Chicago
• From Canada
• David Boisclair, Yann Décarie and François Laliberté-Auger, ESG UQAM
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