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Retirement Economics
and Aging
Robert J. Willis
University of Michigan
Conference on Neuroeconomics and Aging
Stanford, March 31-April 1, 2006
Outline (30 minute talk)
• HRS Project briefly described
– Basic design and goal
– New content on biomarkers, performance measures, cognition
– International pandemic
• New Directions: Cognition and Biomarkers
– ADAMS project and cognitive aging
– Potential for linkage with imaging studies
• P01 Project—linking survey methods, psychology, economics
• Role of cognition/emotion in complex decisionmaking
– Pensions/Savings
– Portfolio Choice
– Survival Expectations
– Poverty Issues
• Application to Medicare Prescription Drug Program
The Health and Retirement
Study
http://www.umich.edu/~hrswww
Origins of the HRS
• 1985-90:
– National Institute on Aging determined there was
lack of data to study policy or scientific issues
relevant to aging society.
• 1990:
– NIA decided to invest in new longitudinal study of
retirement
• 1990-92
– Institute for Social Research at UM won
competition for HRS
– Interdisciplinary research team from entire U.S.
designed HRS, launched in 1992
Evolution of HRS
• 1992: Original HRS cohort
– Persons age 51-61 in 1992 (born 1931-41)
– Plus spouses of age eligible persons
– N=12,654 at baseline
– Longitudinal follow-up every two years
• 1993: Original AHEAD cohort
– Persons age 70+ in 1993 (born 1890-1923)
– Plus spouses of age eligible persons
– N=8223 at baseline
– Longitudinal follow-up every two years
HRS Steady State Design:
1998-2010 and Beyond
• 1998 Re-design
– Merged HRS/AHEAD into single study
– Add New Cohorts
• Children of Depression entering their 70’s (b.
1924-30)
• War Babies entering 50’s (born 1942-47)
– Add New 6 Year Cohort Each 6 years
• 2004: Add Early Boomers (born 1948-53)
• 2010: Add Mid-Boomers (born 1954-59)
The HRS is a multidisciplinary effort
that began with initial design in 1990
A large and diverse community of researchers actively
participated in the study design and implementation
• Economics • Medicine
• Sociology • Public Health
• Demography • Psychology
HRS Designed to Understand Decisions,
Choices, and Behaviors in Response to Policies
• Study families rather than individuals
• Gather integrated multidisciplinary information about
all aspects of life
• Follow people over time as events happen and their
choices get made
• Make the data available to researchers and policy-
makers as quickly as possible
• Let the full power and creativity of America’s scientific
community address the challenges of an aging
population
HRS Studies All Cohorts Born between
1900 and 1953
Figure 3. Size of Birth Cohorts Represented in HRS
Total Number of Births in U.S. in Year
4000
2000
0
1910 1923 1931 194219481954 1961 1980 2000
year
1890-1923 AHEAD 1924-1930 CODA
1931-1941 HRS 1942-1947 War Baby
1948-1953 Early Boomer 1954-1960 Mid Boomer
1960-2000 Post Boomer
The HRS Data System: Scale of
Measurement during 2000-05
• 59,718 interviews
• 20,129 in HRS-2004 Core
• 4,222 interviews with next of kin of respondents
who died
• 32,138 mail surveys
• 21,228 Social Security linkages
• 18,688 Medicare linkages
• 1,430 in-home neuropsychological assessments
on 850 ADAMS respondents
HRS Longitudinal Sample Design
AGE
90
AHEAD
85
CODA
80
75 HRS
70
War
65 Babies
Early
60
Boomers
55 Mid
Boomers
50
92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10
YEAR
Scientific Productivity of HRS
HRS Publications, 1993-2005:
Cumulative Count by Type
1000
24
Cumulative Count: June 15, 2005
900
Journal Publications 510
800 Books and Book Chapters 83 326
318
Dissertations 59
700
Working Papers 326 281
59
Total 978
Citation Count
600
59
228
500 On average, one new journal article 86
93
54
using HRS is published every 5 185
400 44 81
days 129 72
37
300 66
101 27
485
53 449
200 373
83 37 310
54 23 255
100 12 199
37 152
8 77 102
23
0 41
0 10
1
0 14
0
3
2 17
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005
Year
Journal Article Book/Book Chapter Dissertation Working Paper Forthcoming
Comparable International
Surveys in 17 Countries
• ELSA (English Longitudinal Study of Ageing)
– Two waves completed (2002, 2004)
• SHARE (Survey of Health, Ageing and
Retirement in Europe) supported by EU
– 11 Countries Completed first wave in 2004
• Belgium, Denmark, France, Germany, Greece, Italy,
Netherlands, Spain, Sweden, Switzerland
– 4 Countries will begin in 2006
• Czech Republic, Israel, Ireland, Poland
• MHAS (Mexican Health and Aging Study)
– Two waves completed (2001, 2003)
• KLoSA (Korean Longitudinal Study of Aging)
• Japan and China may be next
New Directions for HRS:
1. Biomarkers and Physical Performance
• New measures
– Biomarkers
• Dried blood spots
• Collect and store genetic material
– Physical Performance Measures
• Measure grip strength, timed walk, lung capacity
• Measure blood pressure
• Collected in ―Enhanced Face-to-Face
Interviews for half of sample each wave
– Each person measured once every 4 years
Selecting Biomarkers for HRS:
• Multi-dimensional predictors of disease and
dysfunction:
– Genes; C-reactive protein
• Major predictors of disease and death among
elders:
– Blood pressure; cholesterol, HbA1c
• Candidates for assessing stress, and reflecting
mental illness and some behaviors
– genes
New Directions for HRS:
2. Measurement of Cognition and
Psychosocial Variables
Growing Complexity of Decisions Facing
Older Americans
• Examples
– Shift from defined benefit to defined
contribution pension plans
• Contribution rates: how much to save
• Portfolio choice: how much risk to take
• Post-retirement Income: Annuitize or not?
– Introduction of Medicare Prescription Drug
Plan
• Choose among 40 or so alternative plans: which is
best?
ADAMS Study of Dementia
• ADAMS has established baseline measures of
dementia and CIND (cognitive impairment, not
demented) in substratified subsample of 850
HRS respondents
– In-home clinical assessment
– Plan to use longitudinal data to measure transitions
into dementia and CIND
• Longitudinal data in HRS will allow
measurement of costs and burdens of disease to
individual, family and society
Langa,K, et. al., ―The Aging, Demographics and Memory Study: Study Design
and Methods‖ Neuroepidemiology, vol. 25, pp. 181-191, 2005
“Assessing and Improving Cognitive
Measurements in the HRS”
(AG-07407-14) John J. McArdle, USC
• Experimental measures in HRS
– Adaptive number series test in 2004 (Woodcock-Johnson)
– repeat number series, add vocabulary, prospective memory
• How Do HRS Cognitive Measures Relate to Woodcock-
Johnsnon?
– Use independent sample of 1000 people age 57+ from HRS
screening survey in two wave longitudinal survey
– Administer HRS cognitive items, full Woodcock-Johnson (3hrs)
• Use results to ―re-engineer‖ HRS cognitive measures,
beginning in 2008
―Behavior on Surveys and in the Economy
Using HRS‖
(P01 AG02657) R. Willis, PI
– Goal to link psychology, survey methods,
econometrics and economic theory
• Three Projects
– ―Probabilistic Thinking and Economic Behavior‖ Willis,
PI, Hurd, Manski
– ―Well Being and Utility in Psychology and Economics‖
Kimball, PI; Schwarz, Willis
– Explaining Household Portfolio Choice in Saving for
Retirement (T. Shumay, PI; Miles Kimball, Matthew
Shapiro
• Data Innovation Core
• Networking Core
Psychosocial “Leave Behind”
• Psychosocial
– ELSA measures administered in HRS-2004
as ―leave-behind‖ self-administered
questionnaire
– Design new leave-behind SAQ based on
advice from planned conference
• Vignettes
– Work-relate vignettes in 2004
– Health vignettes similar to SHARE
Retirement Behavior In
International Perspective?
Retirement Patterns of the Men in the
Original HRS Cohort: 1992-2002
By age 70 just under 80 percent Retirement of Original HRS Cohort
Married Men Born 1931-41, Age 51-61 in 1992
were fully retired and another
40
80
6-7 percent were partly retired
30
60
Hazard Rate
The process of retirement begins
Percent
20
in the early 50’s, accelerates
40
about 60, reaches a sharp
10
20
spike at age 62 and another
sub-spike at age 65
0
0
50 55 60 65 70
Age
Retired from Full Time Work Retirement Hazard
Completely Retired
Source: Gustman and Steinmeier (2004)
What Will Happen to Retirement for the Early
Boomers?
• Long term trend in
U.S. from 1850 to
1990 has been
toward earlier
retirement.
International Trends Toward Earlier Retirement
• Trend toward lower
labor force
participation at
older ages is much
sharper in a
number of
European countries
than in US
Source: J. Gruber and D. Wise, Social Security Programs and Retirement Around the World,
U. Chicago Press, 1999.
Retirement Policy Shapes Retirement Behavior
70
Belgium
Percent Early Retirement
60 France Italy
Holland
UK
50 Germany
Spain
Canada
40
US
Sweden
30
20 40 60 80 100
Percent Penalty for Continued Work
Source: J. Gruber and D. Wise, Social Security and Retirement Around the World (NBER, 2000)
Downward Trend in Labor Force Participation
in U.S. Began to Reverse Itself around 1985.
Is the Reversal Permanent?
Males Females
Source: Technical Panel for the Social Security Administration, 2003, based on research by
Joseph Quinn, Boston College.
What Do the Early Boomers Expect?
• HRS has pioneered asking questions about expectations
on a wide variety of topics including survival to a given
age, bequests, stock market returns and work and
retirement expectations
• Researchers have used the work expectation questions
in earlier waves and have found them to be useful
predictors of actual work and retirement in later waves
• We can now obtain a look at what the Early Boomers,
aged 51-56 in 2004 say they will be doing at age 62, 65
and their age at retirement as compared to earlier
cohorts at the same age.
• Note that these questions offer a window into the future
about ten years hence!
Signs of Reversal of Long Term Trend
toward Early Retirement
•Historical trend toward earlier
Expectations of Working After Age 65
Males and Females Age 51-56 Retirement from 1850’s
42.4
through mid-1980’s
40
36.4
33.0
29.5 •Labor force participation
30
24.5 at older ages flat since then
22.7
20
•Possible reversal:
Early boomer cohort in HRS
10
(born 1948-53) expects to
work more than earlier
0
1992 1998 2004 1992 1998 2004 Cohorts
Male Female
Source: Health and Retirement Study
Are Retirement Savings
Adequate?
Distribution of Wealth: HRS1992
Source: Scholz, Seshadri and Khitatrakun “Are Americans Saving `Optimally’” JPE (forthcoming)
Predicted Wealth Based on Dynamic
Optimization Model vs. Actual Wealth
Optimal
Net Worth
Most people
have more
net worth
than ―optimal‖!
Observed
Net Worth
Source:Scholz, Seshadri and Khitatrakun (forthcoming)
Inequality in Health, Wealth and
Cognition
Strong Correlation Between Health
and Wealth
Mean Net Worth by Health of Husband and Wife
Understanding this
correlation requires 500
longitudinal data from
(in Thousands)
400
Net Worth
•Economics
300
•Health
200 Excellent
•Sociology/Demography V Good
100 Good
•Psychology
0 Fair Husband's
Poor Health
n t
d
lle
oo
d
ce
oo
ir
G
Fa
Ex
or
G
V
Po
Wife's Health
Source: Robert J. Willis, “Theory confronts data: how the HRS is shaped by the economics of aging and how the
economics of aging will be shaped by the HRS,” Labour Economics, Volume 6, No. 2, page 119, June, 1999.
“Economic Consequences
of a Husband’s Death”
Source: P. Sevak, D. Weir and R. Willis, ―The Economic Consequences of a Husband’s Death:
Evidence from the HRS and AHEAD.‖ Social Security Bulletin (2003/2004).
Probability of Poverty Highest
for those who are widowed
earliest
Poverty probability increases
with age/duration of widowhood
Underlying causation could be
from various sources; e.g.,
• poor selected into widowhood
• early death of husband is
negative shock to income,
saving
Source: P. Sevak, D. Weir and R. Willis, ―The Economic Consequences of a Husband’s Death:
Evidence from the HRS and AHEAD.‖ Social Security Bulletin (2003/2004).
Monitoring a Social Experiment:
The Medicare Prescription Drug
Program, Part D
CMS (Center for Medicare and Medicare Administration) began
publicizing new program in Fall 2005.
Enrollment began Jan. 15, 2006, ends May 15, 2006. Substantial
lifetime penalty if plan not chosen before May 15
Potentially Highly Complex Choices
• Each enrollee has choice of about 40 different plan providers from
own state, each with three tiers of coverage and level of premium.
• Coverage has ―doughnut hole‖ $2250 and $3600 of out-of-pocket cost
in which there is no coverage.
• Formulary of plan may not match person’s needs
HRS Prescription Drug Survey
1. Mail Survey, mid-October to mid-December
2005
– Collect detailed med data, prior to implementation of
Part D
– Link meds to external databases to get prices
– Assess state of knowledge, attitudes, and intentions
about Part D
2. Core Survey for HRS-2006
– Determine enrollment, premiums
– Name of plan, information used in choosing
– Confidence about making right decision
HRS Prescription Drug Survey
(cont.)
3. HRS/RAND Internet Survey, Phase 2
• Design meeting 3/20/06 sponsored by Willis P01
and HRS/RAND Internet project to design
questionnaire module
• Will go in field following core interview around
November, 2006
• Can look choices during new enrollment period
• Can study help given by R’s <65 to their parents
• Could do experiments
4. HRS Mail Survey, 2007
• New Roster of Prescription Drugs to detect changes
Early Results from PDS-2005 Mail Survey
Based on David Weir, ―The Unbalanced Distribution of
Cognitive Demands and Cognitive Resources for Part D
Decision-Making,‖ (in progress)
PDS 2005 Response Rates
by Race/Ethnicity, and by Type of Contact
100
90
80
70
Percent Responding
60
Phone
50
Mail
40
30
20
10
0
White AfrAm Hisp
Source: D. Weir, ―The Unbalanced Distribution of Cognitive Demands and
Cognitive Resources for Part D Decision-Making.‖
People Love Their Meds:
4600 respondents listed 15,000+ drugs
For each drug, we asked:
• Is this medication very important for your health?
– 91% Agree
– 1% Disagree
– 8% Don’t Know
Source: D. Weir, ―The Unbalanced Distribution of Cognitive Demands and
Cognitive Resources for Part D Decision-Making.‖
To understand who needs to do what, you need
to separate out five main categories of people.
CMS Outreach: Five Target Groups
1. Retiree Rx coverage
• Short term, stay put
2. Medicaid
• Short term, automatic enroll, maybe wrong meds
3. Medicare Advantage (HMO)
• Short term, don’t need to do anything
4. Other Low-income
• Have to apply for “extra help,” choose plan
5. Other
• Need to decide whether to enroll, choose plan
Source: D. Weir, ―The Unbalanced Distribution of Cognitive Demands and
Cognitive Resources for Part D Decision-Making.‖
Groups Differ Widely by Economic Resources
(Median values, HRS2004)
Income Wealth
Retiree $39,512 $274,200
Other 34,592 315,800
HMO 27,754 185,000
Low Inc 12,288 21,500
Medicaid 9,888 3,005
All $29,804 $200,000
Source: D. Weir, ―The Unbalanced Distribution of Cognitive Demands and
Cognitive Resources for Part D Decision-Making.‖
Groups Differ Widely in Cognitive
Resources
Education Numeracy Memory Internet
Retiree 13.0 1.8 9.7 32%
Other 12.5 1.6 9.5 26%
HMO 11.9 1.6 9.1 25%
Low Inc 10.3 0.9 7.7 7%
Medicaid 8.7 0.7 7.1 5%
All 12.0 1.5 9.2 25%
Source: D. Weir, ―The Unbalanced Distribution of Cognitive Demands and
Cognitive Resources for Part D Decision-Making.‖
Groups Differ Widely in Health Status
Any Fair or
ADL/IADL poor
Retiree 20.7% 24.6%
Other 23.0% 21.8%
HMO 27.5% 30.0%
Low Inc 41.4% 44.9%
Medicaid 57.4% 57.1%
All 28.0% 29.9%
Source: D. Weir, ―The Unbalanced Distribution of Cognitive Demands and
Cognitive Resources for Part D Decision-Making.‖
Stress Associated with High Demands,
Low Resources for Decision-Making
Know little Favorable
about it Stressed to Part D
Retiree 49.8% 38.0% 13.7%
Other 54.0% 43.1% 16.5%
HMO 60.6% 41.4% 17.7%
Low Inc 69.0% 50.2% 21.8%
Medicaid 72.2% 35.7% 21.7%
All 56.5% 40.6% 16.6%
Source: D. Weir, ―The Unbalanced Distribution of Cognitive Demands and
Cognitive Resources for Part D Decision-Making.‖
