Probabilistic Thinking and Early
Social Security Claiming
Adeline Delavande
Mike Perry
Robert J. Willis
RAND Corp.
Univ. Nova de Lisboa
CEPR
University of Michigan
University of Michigan
8th Annual Joint Conference of the Retirement Research Consortium
“Pathways to a Secure Retirement”
August 10-11, 2006
Washington, D.C.
Motivation
• Do people claim SS based on their survival
expectations?
• Hurd, Smith and Zissimopoulos - HSZ (2004)
– Use direct measures of survival expectations
– Findings: subjective survival of 0 associated with
early claiming; otherwise, no effect
• Is the effect found by HSZ too small?
– Survey measures of survival expectations capture
much individual heterogeneity in risk
– But also have a lot of measurement error
This Paper
• We reexamine whether people claim SS based on
their survival expectations
• Correct measurement error in elicited subjective
survival probabilities using rich set of risk factors as
instruments
• Findings: People act on their subjective survival
beliefs
– Statistically and economically significant effect of
subjective survival on SS claiming for people
working at 62
-elasticity of claiming probability with respect to
survival probability = -1.24
This Paper (cont.)
• Compare with predictions of objective
survival probability based on same risk
factors
– Similar effect on SS claiming
– Do not contain more information than
subjective survival to explain SS claiming
• Our findings suggest that people
– have highly hetereogenous mortality expectations
– their expectations are largely rational
– they act on these beliefs in deciding when to
claim Social Security benefits
The Analytical Samples
• Use data from the Health and Retirement
Study (HRS)
• Follow HSZ and study 2 groups
1. People who are retired by age 62
– Analyze SS claiming by age 64
2. People who are NOT retired by age 62
– Analyze joint decision to retire and claim by
age 64
(all specifications)
30
20
10
• No effect of
survival
expectations
0
P e rc e n t
• 79.2% claim in
first year of
eligibility
• 89.6% claim by
third year
40
Early Retiree Sample:
Claiming by those retired by age 62
0
12
24
36
48
60
Months since 62nd birthday
Months since 62nd birthday
72
84
Age 65 spike
10
N=1801
0
5
P e rc e n t
• 21.2% claim in first
year of eligibility
• 62.2% claim by
third year
• Significant effects
of survival
expectations when
corrected for
measurement error
15
Late Retiree Sample:
Claiming by those not retired by age 62
0
12
24
36
48
60
Months since 62nd birthday
72
Months since 62nd birthday
84
96
Correcting for Measurement Errors
•
Probabilistic beliefs about survival in HRS
(On a scale from 0 to 100)
What are the chances that you will live to be age 75 or more?
•
•
Measurement error: rounding and heaping at ‘50’
and ‘100’
Use Instrumental Variable methods to correct for
measurement error
Four sets of instruments:
(I) Basic demographic characteristics
(II) Health variables (self-reported health and conditions)
(III) Dummy variables on parental mortality (own and
spouse)
(IV) Optimism index
20
15
10
5
– many focal
answers at “0”,
“50” and “100”
0
P e rc e n t
• Survey
measure of
survival beliefs
are quite noisy
25
Heterogeneity of Survival Beliefs
and Measurement Error
0
25
50
subjective survival to age 75
75
Subjective Probability of Survival to Age 75
100
Heterogeneity of Survival Beliefs
and Measurement Error (cont.)
.02
.03
.04
.05
Predicted Subjective Survival Probability
0
.01
Density
• But there is a
lot of individual
variability in
subjective
mortality risk
based on risk
factors
(see Table 5)
40
50
60
70
Linear prediction
80
90
The effects of subjective survival expectations
on claiming behavior
•
Bivariate probit model with demographics, health and wealth variables
Claim by 64 specification
Without correction
Subjective Prob.
IV Subjective
Prob.
Coef.
P value
-0.002
0.132
With Correction
Coef.
-0.016
P value
0.004
Effect of subjective survivals on claiming
•correction for measurement error increases magnitude of
Predicted probability
effectIV
bysubjective
eight-fold prob.
of surviving until age 75
of claiming by age 64
•instrumented59
coefficient is highly significant based on
26 boot-strapped
standard errors
69
30
79
34
The effects of subjective survival expectations
on claiming behavior
•
Bivariate probit model with demographics, health and wealth variables
Claim by 64 specification
Without correction
Subjective Prob.
With Correction
Coef.
P value
-0.002
0.132
IV Subjective
Prob.
Coef.
P value
-0.016
0.004
Effect of subjective survival probability on claiming
IV subjective prob.
of surviving until age 75
Predicted probability
of claiming by age 64
59
26
69
30
79
34
The effects of objective survival expectations
on claiming behavior
• Use data on 8 to 12 years actual mortality to estimate and
“objective” probability of survival to age 75 using same variables
as for IV
• Bivariate probit model
Claim by 64 Specification
IV Subjective Prob
Objective probability
Subj – Obj probability
•
Coef.
P
value
-0.016
0.004
Coef.
-0.013
P value
Coef.
P
value
-0.019
0.003
0.006
0.234
0.007
Similar effects of subjective and objective expectations on SS
claiming
• Objective expectations do not contain more information than
subjective survivals to explain SS claiming
Conclusion
• Measurement errors in subjective probability are
important
• Mortality expectations have significant effect on SS
claiming
• People who expect to be long-lived delay claiming
and enjoy larger benefits
– Positive effect for the well-being of the elderly
– Higher cost for tax payers
– Ambiguous welfare effects on the whole
population