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Health and Lapse of Long-Term Care Insurance. R. Tamara Konetzka, PhD University of Chicago Ye Luo, PhD University of North Florida June 2008 Funding: NORC and University of Chicago Center on Aging. Background.

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health and lapse of long term care insurance

Health and Lapse of Long-Term Care Insurance

R. Tamara Konetzka, PhD

University of Chicago

Ye Luo, PhD

University of North Florida

June 2008

Funding: NORC and University of Chicago Center on Aging

background
Background
  • Despite high cost of LTC and substantial probability of need, LTC insurance market remains small.
  • Most LTC financing proposals include expansion of LTC insurance.
  • Policies becoming more standardized and awareness increasing.
  • Issues of affordability, adverse selection, and moral hazard remain.
  • Lapse rates are high, especially soon after purchase.
why study lapse
Why study lapse?
  • Consumers who lapse lose the investment they made in insurance premiums paid.
  • Thus lapse = renewed risk of the financial burden of LTC, but with less income.
  • We know very little about the attributes of people who lapse.
research questions
Research Questions
  • What is the probability of lapsing a LTC insurance policy, controlling for competing risks?
  • What are the health characteristics of people who are likely to let a LTC insurance policy lapse?
  • Can income or health shocks explain lapse?
prior research
Prior Research
  • Vast majority of studies were cross-sectional, focus on prevalence.
  • Important factors associated with having LTC insurance: middle income, middle assets, good health, higher education.
  • Purchase and retention of LTCI is an inherently dynamic process.
  • Only one rigorous study of policy lapse.
prior studies using longitudinal data
Prior studies using longitudinal data
  • Cramer and Jenson 2006
    • Study of purchase using HRS
    • Predictors of purchase similar to prevalence studies
  • Finkelstein, McGarry, and Sufi 2005
    • Study of lapse using HRS
    • “dynamic inefficiency” in LTC markets
    • Lapsers are ex-post less likely to use a nursing home, though they are poorer and less educated
conceptual framework
Conceptual Framework
  • Purchasers assess value of LTC insurance policy in terms of cost, probability of needing LTC, and payout if LTC needs arise.
  • Must weigh cost of LTCI against other uses
  • Revisit decision over time as health and financial shocks are introduced
slide8
Data
  • Health and Retirement Study, 5 waves 1996 – 2004.
  • Respondents born between 1924 and 1947 (age 49-72 in 1996).
  • 55,663 two-wave intervals, pooled.
  • Examined smaller subgroups for lapse analysis (up to 5,067)
determining insurance status
Determining Insurance Status
  • Used the question each wave: “Do you have any LTC insurance which specifically covers nursing home care for a year or more or any part of personal or medical care in your home?
  • Lapse = “yes” at time 1 and “no” at time 2.
  • “Have you ever cancelled/lapsed” question is very inconsistent over time; also unable to identify timing of lapse; also subject to recall bias.
potential data issues
Potential Data Issues
  • Measurement error
    • Do people really know if they have LTCI?
    • Some inconsistent patterns over time
  • Solution: Group data by likely extent of measurement error and run sensitivity analyses
    • Lapse rates are sensitive to these groupings
    • However the predictors of lapse appear to be robust to this measurement error
transition framework
Transition Framework

Status at time 1 = one of 2 discrete states:

  • In community without LTC insurance
  • In community with LTC insurance

Outcome at time 2 = one of 4 discrete states:

  • In community without LTC insurance
  • In community with LTC insurance
  • Institutionalization
  • Death
methods
Methods

Multinomial logit estimation of:

  • Transition probabilities from time 1 to time 2
  • Effects of demographics, health, and financial characteristics at time 1 on lapse in time 2

Change Model-- Logit estimation of:

  • Effects of changes in health status between time 1 and time 2 on lapse in time 2.
potential predictors
age

gender

race

self-rated health

education

marital status

income

assets

has kid

has daughter

number of kids

number of nearby kids

whether kids own home

expect to leave a bequest

Potential Predictors
results predictors of lapse
More likely to lapse:

Poor self-rated health status

Black

Hispanic

Lower income

Lower assets

Less educated

More children

Less likely to lapse:

Very good health

Female

Retired & not working at all

Kids work full-time

Kids own homes

Expect to leave a bequest

Results: Predictors of Lapse
preliminary conclusions implications
Preliminary Conclusions/Implications
  • Sicker individuals less likely to buy LTCI but also more likely to lapse if they do buy it.
  • Unlikely that reassessment of risk can explain most lapse – more likely that affordability is the issue.
  • Expansions of the LTC insurance market to those who can marginally afford it may be inefficient and leave frail elderly worse off.
caveats limitations
Caveats/Limitations
  • Little information on attributes of policies, most importantly prices
  • Remaining measurement error
  • Still need to analyze 3-period transitions to assess the effects of changes in health and income over time