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Nadia Greenhalgh-Stanley

Medicaid and the Housing and Asset Decisions of the Elderly: Evidence from Estate Recovery Programs. Nadia Greenhalgh-Stanley. Medicaid. Medicaid most important provider of long-term care insurance Means-tested Special treatment of owner-occupied housing

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Nadia Greenhalgh-Stanley

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  1. Medicaid and the Housing and Asset Decisions of the Elderly: Evidence from Estate Recovery Programs Nadia Greenhalgh-Stanley

  2. Medicaid • Medicaid most important provider of long-term care insurance • Means-tested • Special treatment of owner-occupied housing • Little evidence of impact of Medicaid on elderly behavior • Relied on cross-state variation • Confounded by other changes • Circumvent by using variation in treatment of housing assets

  3. Differential Treatment of Assets • Medicaid • Imposes a 100% implicit tax on holding financial assets above $2000 • Exempts owner-occupied housing assets from Medicaid eligibility decision • Lower implicit tax on holding owner-occupied housing assets • Potential distortions of housing and bequest decisions • Largest non-pension asset exempt from eligibility decision

  4. Contributions to Literature • Provide new evidence on impact of Medicaid means-testing on elderly behavior • Exploit new state-by-time variation • First empirical evidence on the impact of estate recovery programs on elderly behavior • Exploit exit data to provide useful information describing Medicaid’s impact on end-of-life behavior

  5. Estate Recovery Programs • Large growth in Medicaid in 1980s triggered interest in ERPs • Omnibus Budget Reconciliation Act of 1993 (OBRA93) mandated states adopt ERPs • States have right to reclaim value of Medicaid expenditures on nursing home care • Minimum Recovery • Probate estate • Maximum Recovery • Amount left in an estate

  6. ERP and Housing • Prior to adoption • house was deemed a safe asset • After adoption • house was subject to recovery once the recipient was deemed permanently institutionalized • ERPs changed Medicaid’s implicit tax on holding housing assets • 1993: 26 states had programs already in place • 2004: 47 states had programs in place • 36 Month look back period

  7. TEFRA liens • States were given vast control over type and size of ERP • Tax Equity and Fiscal Responsibility (TEFRA) liens • Only type to be placed on the home while recipient still alive • 1993: 5 states • 2004: 19 states

  8. Treatment by Marital Status • Differential incentives by marital status • Cannot recover against estate when • Surviving Spouse • Minor Child • Disabled Child • Adult child, live in house for 2 years, took care of parent • Sibling, lived in house for 1 year, financial interests

  9. Unmarried Elderly • Before ERP • Spend-down assets and excess income • House jointly serves as residence and store of wealth • At death, can bequeath to anyone • After ERP • Face same asset and income requirements • House still not used to determine eligibility • At death, house eligible for recovery and cannot be bequeathed • Incentives to use trusts as substitute asset shelter • Put house into living trust

  10. ERPs and Housing Assets • State adoption of ERPs makes housing a less attractive asset in the portfolio for unmarried • State can now go after house • Results in bequest motives being less likely to be made through the house • Homeownership is less attractive • Implicit tax on housing assets under Medicaid has risen • Holding of home equity is less attractive overall • State will get value of the home

  11. DATA • Self-collected ERP and TEFRA data • Health and Retirement Study (HRS) • Assets and Health Dynamics of the Elderly (AHEAD) cohort • 1993: 70 and older, homeowners • Follow until death or 2004 • “Exit Interviews” – information gathered on value and asset composition of estates and bequests after a respondent dies (“exits”)

  12. Identification OBRA93 induced state-by-time variation in Medicaid’s treatment of owner-occupied housing assets

  13. Table 2. Linear Probability Estimated Impact of TEFRA Liens and Estate Recovery Programs on Home Ownership Decisions at the Time of Death, (Standard Errors in Parentheses)

  14. Omitted Variable Bias • Worry about omitted variable bias • Biased and inconsistent Estimates

  15. Housing Prices • Worry: local housing prices also affecting the homeownership decision • Source: Office of Federal Housing Enterprise and Oversight (OFHEO) Housing Price Index • Unmarried*ERP: decrease homeownership at death by 19.7% • Unmarried*TEFRA: decrease homeownership at death by 12.8%

  16. State Medicaid Expenditure • Worry: States changing generosity of Medicaid simultaneously with adopting ERPs • Proxy: State Medicaid Expenditure • Sources • Medicaid Statistics, Programs and Financial Statistics 1993 • Bureau of Census • Kaiser Commission • Unmarried*ERP: decrease homeownership at death by 19.8% • Unmarried*TEFRA: decrease homeownership at death by 13.3%

  17. Linear State by Time Trends • Worry: Trends over time in states may be correlated with elderly portfolio behavior and other laws passed in these states • Unmarried*ERP: decrease homeownership at death by 21% • Unmarried*TEFRA: decrease homeownership at death by 13.2% • Clearly: ERPs and TEFRA liens are impacting elderly housing decisions

  18. Trust Incentives at Death • Unmarried • Increase trust participation as a way to save assets for heirs • Put house into living trust • Avoid ERP/Medicaid implicit tax of holding housing • House no longer serves as store of wealth for bequests • Married • Already have guaranteed asset protection for heirs through house

  19. Table 3. Linear Probability Estimated Impact of TEFRA Liens and Estate Recovery Programs on Trust Participation at the Time of Death, (Standard Errors in Parentheses)

  20. Trust Participation at Death • With Housing Price Index • Unmarried*ERP: Increase by 10.2% • Unmarried*TEFRA: Increase by 46.5% • With Medicaid generosity • Unmarried*ERP: Increase by 9.5% • Unmarried*TEFRA: Increase by 46.5% • With linear State-by-time trends • Unmarried*ERP: Increase by 8.3% • Unmarried*TEFRA: Increase by 36.9%

  21. Housing Decisions • Homeownership Decision • Unmarried*ERP: Decrease by 1.8% • Unmarried*TEFRA: Decrease by 2.7% • Home Equity Decision • Unmarried*ERP: Decrease by $24,813 • Unmarried*ERP: Decrease by $2900 • Mean home equity for sample: $119,124

  22. Asset Portfolio • Examine whether decrease in home equity is due to • Decrease in total assets • Shift in portfolio assets • Use housing share of total portfolio wealth as dependent variable • Unmarried*ERP: Decrease by 0.4% • Unmarried*TEFRA: Decrease by 14.8%

  23. Conclusions • Clear behavioral response among the elderly to changes in the Medicaid implicit tax of holding housing • Evidence that unmarried elderly use trusts as a substitute way to carry out bequest motives • Changes in asset portfolio composition

  24. Medicaid Spend Down • Supplemental Security Income (SSI) • Income below $488/month, assets below $2000 • 209(b) States • Determine eligibility after deduct medical costs from income • 300 Percent Rule • Income within 300% of SSI levels • Qualified Medicare Beneficiaries • Medically Needy • Higher income elderly can spend down income and assets on medical care

  25. 2000 • Spending on long term care services in year 2000 • Total - $71 billion • Private LTC - $300 million • Medicaid - $31 billion • Kaiser Foundation – 52% of Medicaid spending but only 7% Medicaid recipients • Medicaid most important provider • Special treatment of housing

  26. Spousal Impoverishment • After federal adoption of MCCA in 1988 • Community spouse entitled to • 1992 could keep assets in $13,740-$68,700 range • Income greater than 150% of poverty line or $1662/month in 1992 • 2008 protection levels • Assets: $20,880-$104,400 • Income: $1711-$2610/month

  27. Table 1. Sample Size, Properties, and Statistics Note: The portfolio share is the percent of total wealth comprised of home equity. All home equity and total wealth measures are reported in 2005 adjusted real dollars.

  28. Identification • OBRA93 induced state-by-time variation in Medicaid’s treatment of owner-occupied housing assets

  29. Married Elderly • After ERP, • No incentive to change home ownership while alive • May face small incentives to “save” for spouse by increasing home equity • Incentives to retain homeownership at death • Prior to ERP, could bequeath • After ERP, home only safe if die owning it with spouse

  30. End-of-life Decisions • Trust Participation at Death • Suggests: unmarried view trusts as substitutes to protect assets • Avoid implicit tax of house by putting assets in trusts

  31. Housing Decisions While Alive • Married as control group • Do not face incentives to change housing tenure • Unmarried incentives to • Decrease housing assets • Sell house • Decrease home equity

  32. Time Trends • Find large results at death and small results while alive • See when response is occurring • Advantage of Data • Can look to see trends as approach death • Unbalanced and Balanced estimation • Balanced sample selection issue

  33. Table 4 Time Trends – Unbalanced Panel Estimated Impact of TEFRA Liens and Estate Recovery Programs (ERPs) on Home Ownership Decisions at death, interview prior to death, two interviews prior to death, and while alive, (Standard Errors in Parentheses)

  34. Table 5 Time Trends – Balanced Panel Estimated Impact of TEFRA Liens and Estate Recovery Programs (ERPs) on Home Ownership Decisions at death, interview prior to death, two interviews prior to death, (Standard Errors in Parentheses)

  35. Home Equity Decisions • ERPs increase implicit tax of holding owner-occupied housing assets • Elderly can choose to decrease housing by decreasing homeownership or decreasing home equity • Davidoff (2004)

  36. Table 6. Linear Probability Estimated Impact of TEFRA liens and Estate Recovery Programs (ERPs) on Home Equity Decisions while alive, (Standard Errors in Parentheses)

  37. Home Equity • Housing Price Index • Unmarried*ERP: -2.7% • Unmarried*TEFRA: -18.7% • Medicaid State Generosity • Unmarried*ERP: -0.3% • Unmarried*TEFRA: -18.5% • Linear state-by-time trend • Unmarried*ERP: -2.4% • Unmarried*TEFRA: -17.1%

  38. Table 7. Linear Probability Estimated Impact of TEFRA liens and Estate Recovery Programs (ERPs) on Portfolio Decisions while alive, (Standard Errors in Parentheses)

  39. Portfolio Decisions • Housing Price Index • Unmarried*ERP: -0.6% • Unmarried*TEFRA: -14.6% • Medicaid generosity • Unmarried*ERP: -0.4% • Unmarried*TEFRA: -14.9% • Linear state-by-time trend • Unmarried*ERP: -0.6% • Unmarried*TEFRA: -14.8%

  40. Table 2. Linear Probability Estimated Impact of TEFRA Liens and Estate Recovery Programs on Home Ownership Decisions at the Time of Death, (Standard Errors in Parentheses)

  41. Table 3. Linear Probability Estimated Impact of TEFRA Liens and Estate Recovery Programs on Trust Participation at the Time of Death, (Standard Errors in Parentheses)

  42. Table 4 Time Trends – Unbalanced Panel Estimated Impact of TEFRA Liens and Estate Recovery Programs (ERPs) on Home Ownership Decisions at death, interview prior to death, two interviews prior to death, and while alive, (Standard Errors in Parentheses)

  43. Table 5 Time Trends – Balanced Panel Estimated Impact of TEFRA Liens and Estate Recovery Programs (ERPs) on Home Ownership Decisions at death, interview prior to death, two interviews prior to death, (Standard Errors in Parentheses)

  44. Table 6. Linear Probability Estimated Impact of TEFRA liens and Estate Recovery Programs (ERPs) on Home Equity Decisions while alive, (Standard Errors in Parentheses)

  45. Table 7. Linear Probability Estimated Impact of TEFRA liens and Estate Recovery Programs (ERPs) on Portfolio Decisions while alive, (Standard Errors in Parentheses)

  46. Preview of Results • State adoption of Estate Recovery Programs and TEFRA liens • Elderly 33% less likely to own their homes at death • Elderly 59% more likely to have a trust at death • Elderly 4% less likely to own home while alive • Some evidence of changes in asset composition of elderly wealth portfolio

  47. Presentation Plan • Background Information • Medicaid Eligibility • Estate Recovery Programs • Estimation Strategy • Results • Conclusions and Extensions

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