1 04/21/23

The Link between Individual Expectations and Savings:

Do nursing home expectations matter?

Kristin J. Kleinjans, University of Aarhus & RAND

Jinkook Lee, Ohio State University

Preliminary – comments and suggestions appreciated

2 04/21/23

Research Questions

1. Are expectations about future nursing home entry linked to actual entry?

2. Is there a relation between these expectations and savings behavior?

3 04/21/23

Why do we care?

In the US :

• 40% chance of entering a nursing home for those who reach age 65

• 10% of those stay for at least 5 years

• high cost of stay per year (average):

US-$60,000 for semi-private room

US-$70,000 for private room

4 04/21/23

Why do we care?

How are nursing home stays financed?

• Medicaid (means tested)

(1/3 of individuals when admitted,

+ 1/3 after savings depleted)

• long-term care insurance (3% of total cost)

• individual savings

5 04/21/23

Then…

• Do individuals form sensitive expectations about stay in NH?

• Do individuals adjust their savings behavior in response to (change in) expectation?

6 04/21/23

Why use Individual Expectations?

• Give additional information otherwise not available

• Have been found to have explanatory power

(e. g. Hurd/ McGarry 2002, subjective survival prob.)

• Have not yet really been linked to economic behavior

(Hurd/ Smith/Zissimopoulus 2004, survival prob. and retirement found only small effects)

7 04/21/23

Our (preliminary) Results

1. Are expectations about future nursing home entry linked to actual entry?

yes

2. Is there a relation between these expectations and savings behavior?

positive for singles with (very) low positive wealth

8 04/21/23

Data

HRS 1992-2002 (6 waves)

Age of initial cohort: 51- 61 + spouses

Sample Size: 7,600 households in 1992

AHEAD 1993-2002 (5 waves)

Age of initial cohort: 70 and older + spouses

Working sample:

15, 089 respondents

9 04/21/23

Survey Question:Probability of Entering Nursing Home

"What is the percentage chance that you will move to a nursing home in the next five years?“

Possible answers:

0 to 100

refuse

don’t know

10 04/21/23

Survey Question:Probability of Entering Nursing Home

"Nursing homes are institutions primarily for people who need constant nursing supervision or are incapable of living independently. Nursing supervision must be provided on a continuous basis for the institution to qualify as a nursing home. Please don't include stays in adult foster care facilities or other short-term stays in a hospital.“

(HRS respondents, and 1996 onwards)

"Of course, nobody wants to go to a nursing home, but sometimes it becomes necessary.“

(AHEAD 1993 and 1995)

11 04/21/23

What influences the probability of entering a nursing home?

(geriatric, medical literature)

Age (+), gender (women + )

Health, ADL, IADL

Marital status, children (-), living siblings (-)

Race (being white +)

Education (+)

Low income (+), net worth (-)

12 04/21/23

Self-reported prob. of NH Entry

- Low non-response rates:

- Refusal: < 1% in all waves

- ”Dont know”: < 10% in all waves

- rounding to the nearest 5% between 15% and 95%

- bunching of answers: 0% and 50%

- Evidence for rounding: health

13 04/21/23

Subjective Prob. of NH Entry

WaveMean

ProbabilityAnswers (in %)

0 >0 & <50 50 >50

4 12.2 62.4 22.6 11.9 3.1

5 14.0 55.0 28.5 12.2 4.2

6 13.7 53.7 30.5 11.9 3.9

14 04/21/23

Subjective Prob. of NH entry

Mean Probability

Wave All Self-reported health

Excellent/ very good

Good Poor or fair

4 12.2 9.5 11.8 15.6

5 14.0 11.6 13.7 18.0

6 13.8 11.1 13.7 17.5

15 04/21/23

How to measure the outcome

• Currently living in NH

• Having been in NH since last interview

Including short-term stays (< 30 days)

Excluding short-term stays

16 04/21/23

How do expectations relate to outcomes* ? Mean Subjective NH Prob. by Entry

Overall Mean

Entry next wave

No entry next wave

Cum. entry as % of initial sample

Wave 2(N=5545) 13.8

19.2(18.9)

13.5(13.6)

4.4%(2.4%)

Wave 3(N=4165) 17.2

23.7(24.4)

16.7(16.9)

9.5%(5.6%)

Wave 4(N=3207) 14.7

20.3(21.9)

14.4(14.4)

14.4%(8.7%)

*Measured as having been in NH since last interview (currently living in NH)

17 04/21/23

How do expectations relate to outcomes ?Random-Effect Probit of Actual Entry (2 waves later)

Variable Coefficient P-Value

NH prob. 0.004 0.03

# living children - 0.184 0.00

# living siblings - 0.101 0.00

Constant - 2.297 0.00

Measure: Currently living in NH.

Additional covariates included.

18 04/21/23

Possible Effects of Expectations on Savings

Differs by (non-housing) wealth:

- Low wealth: No effect (Medicaid)

- In the lower middle: Negative effect (spend down)

- In the upper middle: None or Positive effect

(Too late for saving enough?)

- High wealth: No effect

19 04/21/23

Median Savings Rates by Wealth Range

Singles (2000)

Non-Housing Wealth Range

Neg. 0 *$1-

$5,200$5,200-$32,000

$32,000-$139,000

> $139,000

s rate

-101% (0) - 4.1% - 17.8% - 18.1% - 31.8%

* Median Savings

Average age: 74

20 04/21/23

Measurement of Savings

-difference in (non-housing) wealth

- measured as difference of logs of wealth in period t and t+1

Log of wealth = log(wealth+1) if wealth >= 0

- log(1-wealth) if wealth < 0

21 04/21/23

Other Factors Affecting Savings (Singles)

Age, gender, race

SES - Permanent income: use predicted income given

real income, age, age2, marital status, race, gender, education, region of residence

Health status, health insurance(s), LTC insurance

Bequest motive: use # of children

(endogeneity of bequest intention)

22 04/21/23

Fixed Effect Regression for SavingsSingles, only if NH prob. changed

Coefficient P-Value

NH prob. -0.0004 0.89

log non-housing wealth

- 1.207 0.00

Bad Health - 0.353 0.16

All wealth groups included.

Additional covariates included.

23 04/21/23

Fixed Effect Regression for SavingsSingles, only if NH prob. changed

Wealth range $1-$1,150

Coefficient P-Value

NH prob. 0.072 0.00

log non-hous. wealth - 0.920 0.10

Bad Health - 0.435 0.72

Separate regressions by wealth groups: neg., zero, 10 (positive non-hous. wealth) deciles.

Shown: regression with stat. sign. coefficient on NH prob.

Additional covariates included.

24 04/21/23

Results

- no effect for most wealth groups

- exception: lowest positive wealth decile (+)

- Sensitivity analysis:

- Negative effect for low wealth ranges (2. and 3. pos. wealth decile) for HRS sample and with wave dummies

25 04/21/23

(Preliminary) Conclusions

• Expectations related to risk of nursing home entry and actual entry

• Positive effect on savings for those with very low but positive wealth

• Some evidence for dissaving for those with slightly higher wealth

26 04/21/23

Potential Problems

• Endogenous non-random sample selection through deaths and NH entry

Should bias coefficients downwards (1. decile)

• Endogeneity of wealth

Should be less of a problem since wealth was accumulated during work life

27 04/21/23

Next Steps: Address Sample Selection Issues• Include deceased in sample for Part 1 (expectations versus outcomes)

• Use IV estimation for Part II (effect on savings)

Potential candidate:Number of living children works if death of child affects NH exp but not savings rate