The Long-Term Financial and Health Outcomes of Disability Insurance Applicants Kathleen McGarry and Jonathan Skinner Presentation prepared for “Issues for Retirement Security” August 10-11, 2009

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

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

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

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

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

Distribution of Spending by Mortality

Distribution of spending by type

Cumulative spending by mortality status (median)

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

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

Sample Use 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+

Figure 1: Median Household Income by SSDI/SSI Status & Age

Figure 2: Median Household Assets by SSDI/SSI Status & Age

Figure 3: Percent Currently Depressed by SSDI/SSI Status and Age Group

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

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)

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

Figure 4A: Median OOPME SSDI/SSI Status & Age

Figure 4B: Mean OOPME SSDI/SSI Status & Age

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?

Cumulative Spending Disabled--Median

Cumulative Spending disabled--mean

Cumulative Spending Disabled Couples--Median

Cumulative Spending Couples--Mean

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

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

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

Figure 1J: Median Household Income by SSDI/SSI Status & Age

Figure 2J: Median Household Assets by SSDI/SSI Status & Age

Figure 3J: Percent Currently Depressed by SSDI/SSI Status and Age Group

Avg OOP spending disabled decedents

Avg OOPME disabled decedent--couples