the long-term financial and health outcomes of disability insurance applicants kathleen mcgarry and...
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![Page 1: The Long-Term Financial and Health Outcomes of Disability Insurance Applicants Kathleen McGarry and Jonathan Skinner Presentation prepared for “Issues](https://reader033.vdocument.in/reader033/viewer/2022042822/56649e2d5503460f94b1d45e/html5/thumbnails/1.jpg)
The Long-Term Financial and Health Outcomes of Disability
Insurance Applicants
Kathleen McGarry and
Jonathan SkinnerPresentation prepared for
“Issues for Retirement Security”August 10-11, 2009
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Overall Agenda: The Importance of Health Shocks and Health
Expenses on Retirement Well-Being
• “Out-of-Pocket Medical Expenditures and Retirement Security in the United States”▫ Presented at the NBER Aging Conference, May
2009
• “The Long-Term Financial and Health Outcomes of Disability Insurance Applicants”▫ RRC Annual Meeting, August 2009
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Out-of-Pocket Spending Horror Stories
•“…22 million adults with health coverage all year still spent a large chuck of their incomes—at least 10%..—for out-of-pocket medical expenses.” –NYTimes
•One-half of bankruptcies are associated with “catastrophic” health care costs—Himmelstein
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Out-of-Pocket Spending—Not so bad?
•Approximately 70 percent of elderly have insurance in addition to Medicare
•Medicare has recently expanded coverage to include prescription drugs
•Empirical evidence shows far from devastating risk.▫Palumbo found less than 1% of the elderly
spent more than $13,600 per year.▫Hurd average expenditures of $3000-$4000
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Reconciling the Difference
•Risk may lie in upper tail of the distribution•Difficult to measure / defining costs
▫Don’t measure what people can’t afford▫Difficult to separate needed care from
luxuries▫Measurement of non-medical spending
Ramps, special food, helpers•End of life spending difficult to measure
▫Small sample size▫Proxy reports▫Elapsed time recall problems▫Time affects comparisons with survivors
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Reconciling the Difference
•Surveys miss institutionalized population may miss LTC
•Cross section may miss effects of chronic disease
•Miss implicit cost of informal care•Focus on areas where burden might be
especially bad ▫Those near death▫Disabled▫Cumulative spending
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Distribution of Spending by Mortality
0
5,000
10,000
15,000
20,000
25,000
30,000
35,000
40,000
Decedents avg1.2 yrs
Survivors avg~2 yrs
mean
50th
75th
95th
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Distribution of spending by type
0
2000
4000
6000
8000
10000
12000
14000
16000
18000
Hosp/NH Helper Insurance
Mean
Median
75th
95th
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Cumulative spending by mortality status (median)
0
5000
10000
15000
20000
25000
Decedents Survivors
Last obs
Last + Lag
Last+2 Lags
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Summary of Out-of-Pocket Spending
• Particularly high at the end of life ▫ Also where it is most difficult to measure▫ Serious effects on surviving spouse, heirs
• Much spending in the upper tail associated with long term care needs
• Cumulative effects are important▫ Positive correlation over time
• Suggests that in addition to those at the end of life, the disabled could be at risk▫ May need help with ADL limitations▫ Custodial care▫ Care over an extended period of time
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Well-Being of Disabled Population
• Decline in income due to lost earnings▫ Does income rebound over time?
SSDI/SSI, income from other family members, recovery▫ Does health shock permanent negative shock to
income?• Other financial implications:
▫ Foregone pension wealth and retiree health insurance▫ Consistently lower income implies:
Spend down of assets No accumulation of wealth for retirement
Outcomes in retirement could be particularly bad• What role do OOPME play?
▫ Higher spending vs. Medicare / Medicaid coverage
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Sample
• Use 1992-2006 HRS to construct three groups▫ Never applied for SSDI/SSI ▫ Applied and were rejected ▫ Applied and received benefits
At first observation and ever
• Examine differences in:▫ Income▫ Assets▫ Health (self reported, mortality, depression)▫ Out of pocket medical spending
• Particular attention to outcomes after 65+
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Figure 1: Median Household Income by SSDI/SSI Status & Age
$0
$10,000
$20,000
$30,000
$40,000
$50,000
$60,000
$70,000
55-59 60-64 65-69 70-74
Rejected
Accepted
Never App.
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Figure 2: Median Household Assets by SSDI/SSI Status & Age
$0
$50,000
$100,000
$150,000
$200,000
$250,000
55-59 60-64 65-69 70-74
Rejected
Accepted
Never App.
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Figure 3: Percent Currently Depressed by SSDI/SSI Status and Age Group
0
0.1
0.2
0.3
0.4
0.5
55-59 60-64 65-69 70-74
Rejected
Accepted
Never App.
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0.00
0.25
0.50
0.75
1.00
40 60 80 100Age
Did Not Apply ReceivedRejected
Kaplan-Meier survival estimates, by Status
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0.2
.4.6
.81
Sur
viva
l
50 60 70 80 90 100analysis time
receive=0 reject=0 reject=1receive=1
Cox proportional hazards regression
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Regression Analyses• Model Income / assets as a function of Disability
status• Control for:
▫ Age, race / ethnicity, schooling level, marital status, blue collar occupation
▫ With and w/o self reported health, depression • Focus on indicators for SSDI / SSI status
▫ Indicator for whether they have applied for benefits ▫ Indicator for whether they have received benefits
• Same results as in simple cross tabulations: ▫ Application indicator is significant and negative▫ Benefit indicator is insignificant and small
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Summary:
•Those who applied ▫Lower incomes▫Lower asset levels▫Greater mortality▫Higher depression scores
•Economically (and statistically) insignificant difference between accepted and rejected applicants in most specifications▫In cases with a significant difference,
difference is small (e.g. $10,000 in wealth)
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What about OOPME?
•SSDI recipients have Medicare coverage•SSI recipients have Medicaid coverage Even if they are less healthy, may not
have significantly higher spending
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Figure 4A: Median OOPME SSDI/SSI Status & Age
$0
$200
$400
$600
$800
$1,000
$1,200
$1,400
$1,600
55-59 60-64 65-69 70-74
Rejected
Accepted
Never App.
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Figure 4B: Mean OOPME SSDI/SSI Status & Age
$0
$1,000
$2,000
$3,000
$4,000
$5,000
$6,000
55-59 60-64 65-69 70-74
Rejected
Accepted
Never App.
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In regression context:
•Disability application is associated with higher out-of-pocket medical spending
•Offset by receipt of benefits.▫Likely due to associated health insurance
coverage▫Medicaid indicator significant (negative) in
regressions lowers out of pocket costs
•How important are costs long term?
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Cumulative Spending Disabled--Median
0
5000
10000
15000
Received Rejected
Last obs
Last + Lag
Last+2 Lags
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Cumulative Spending disabled--mean
0
5000
10000
15000
20000
Received Rejected
Last obs
Last + Lag
Last+2 Lags
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Cumulative Spending Disabled Couples--Median
0
10000
20000
30000
Received Rejected
Last obs
Last + Lag
Last+2 Lags
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Cumulative Spending Couples--Mean
0
10000
20000
30000
40000
Received Rejected
Last obs
Last + Lag
Last+2 Lags
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Summary
•Disabled (rejected & accepted) are significantly worse off than non-disabled in numerous dimensions▫Income, wealth, and health▫Not significantly different from each other
•Increased health care costs for applicants, offset for those receiving disability benefits
•OOP burden accumulates quickly over years
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What might we infer about eligibility process?
• Doesn’t work: ▫ Those denied benefits appear to be in just as poor
health as recipients• Does work:
▫ Those denied benefits manage to do as well as those receive assistance
▫ Work, family / spouse helps smooth consumption• Does work:
▫ May be able to screen correctly but rejected applicants are scarred by time out of the labor force Deterioration of human capital Sends poor signal to employers
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Conclusions
•Little difference in out of pocket medical spending by disabled status
•But sizable expenditures when aggregated over time, particularly relative to income and wealth
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Figure 1J: Median Household Income by SSDI/SSI Status & Age
$0
$10,000
$20,000
$30,000
$40,000
$50,000
$60,000
$70,000
55-59 60-64 65-69 70-74
Rejected
Accepted
Never App.
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Figure 2J: Median Household Assets by SSDI/SSI Status & Age
$0
$50,000
$100,000
$150,000
$200,000
$250,000
55-59 60-64 65-69 70-74
Rejected
Accepted
Never App.
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Figure 3J: Percent Currently Depressed by SSDI/SSI Status and Age Group
0
0.1
0.2
0.3
0.4
0.5
0.6
55-59 60-64 65-69 70-74
Rejected
Accepted
Never App.
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Avg OOP spending disabled decedents
0
5000
10000
15000
20000
Received Rejected
Last obs
Last + Lag
Last+2 Lags
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Avg OOPME disabled decedent--couples
0
10000
20000
30000
40000
Received Rejected
Last obs
Last + Lag
Last+2 Lags