1 Health Status and The Retirement Decision Among the Early-Retirement-Age Population Shailesh...

21
1 Health Status and The Retirement Decision Among the Early-Retirement-Age Population Shailesh Bhandari Economist Labor Force Statistics Branch Housing and Household Economic Statistics Division US Census Bureau Presented at The PAA Meeting Detroit, MI April 29 – May 2, 2009

Transcript of 1 Health Status and The Retirement Decision Among the Early-Retirement-Age Population Shailesh...

Page 1: 1 Health Status and The Retirement Decision Among the Early-Retirement-Age Population Shailesh Bhandari Economist Labor Force Statistics Branch Housing.

1

Health Status and The Retirement Decision Among the Early-Retirement-Age Population

Shailesh BhandariEconomist

Labor Force Statistics BranchHousing and Household Economic Statistics Division

US Census Bureau

Presented atThe PAA Meeting

Detroit, MIApril 29 – May 2, 2009

Page 2: 1 Health Status and The Retirement Decision Among the Early-Retirement-Age Population Shailesh Bhandari Economist Labor Force Statistics Branch Housing.

2

Labor Market Facts• The U.S. population is aging• Baby-boomers are nearing retirement age• Early retirement has an impact on the

economy – As the number of Social Security beneficiaries tends

to increase,– The ratio of workers to beneficiaries tends to decrease

• The retirement decision is a personal decision:– When is the right time for me to retire?

• Older work force– Why do some people continue working beyond 65?

Page 3: 1 Health Status and The Retirement Decision Among the Early-Retirement-Age Population Shailesh Bhandari Economist Labor Force Statistics Branch Housing.

3

Good Health at Age 65?

• What level of health is good? Bad? • Direct measure: ask people directly

(as in Survey of Income and Program Participation (SIPP) and Medical Expenditure Panel Survey (MEPS))

• Relative measure: compare the respondent’s health status at two different points in time, one-year apart

• Does a person’s health status determine whether they retire early?

Page 4: 1 Health Status and The Retirement Decision Among the Early-Retirement-Age Population Shailesh Bhandari Economist Labor Force Statistics Branch Housing.

4

Research Question and Data

• Research questionWhat is the role of health status in early retirement decision?

• Data– 2004 SIPP Panel, Waves 1-6– Population: Those aged 50-64 with job in wave1– Sample size:

• Unweighted: 7,714• Weighted: 20,155 thousand

Page 5: 1 Health Status and The Retirement Decision Among the Early-Retirement-Age Population Shailesh Bhandari Economist Labor Force Statistics Branch Housing.

5

SIPP: A Longitudinal Survey

• Households are interviewed every four months for 3-4 years

• Everyone aged 15+ is interviewed

• Detailed information on demographics, program participation, income, and employment

• Current panel is 2008, began September 2008

• The latest completed panel is 2004, February 2004 to January 2008

Page 6: 1 Health Status and The Retirement Decision Among the Early-Retirement-Age Population Shailesh Bhandari Economist Labor Force Statistics Branch Housing.

6

Methods: Logistic Regression

• Universe: Those aged 50-64 with a job in wave 1– Tracked until Wave 6 to see their retirement decision– Does not include those already retired in Wave 1– Does not include those who turn 65 at retirement

• Dependent Variable (Retirement indicator): – If a person with a job in Wave 1 retires in one of the

later waves, this variable equals 1.

• Independent variables:– Person level: age, gender, race and Hispanic origin,

marital status, education, geography, and health status– Job level: Class of work, occupation of the current job or

the job the person retired from– Information on retired people is as of the time of retirement

• If a person retires in Wave 3, all the person-job data are as of Wave 3

Page 7: 1 Health Status and The Retirement Decision Among the Early-Retirement-Age Population Shailesh Bhandari Economist Labor Force Statistics Branch Housing.

7

Limitations• Assumption: Retirement age is 65

• Issues relating to retirement age– Full retirement benefits at age 65 applies to

those born before 1938

– For those born in 1938 or later, the full retirement benefits age increases by 2 months every year (negligible effect on our universe)

– New retirement age for those born in 1960 or later is 67

Page 8: 1 Health Status and The Retirement Decision Among the Early-Retirement-Age Population Shailesh Bhandari Economist Labor Force Statistics Branch Housing.

8

Defining the Labor Force, Retirement Status, and Health Status

•In Labor Force– Previously retired (re-entrants)

– Never retired

•Not in Labor Force– Retired (fully retired)

– Not retired

• SIPP questions used to create these groups:• Has ... ever retired, for any reason, from a job or business?• Employment status recode for month 4.

– Working, not working/looking for work, not looking for work, etc…

• Would you say your health in general is excellent, very good, good, fair, or poor?

••Self-reported Health StatusSelf-reported Health Status

-- Excellent, Very Good, Good, Fair, Poor

Page 9: 1 Health Status and The Retirement Decision Among the Early-Retirement-Age Population Shailesh Bhandari Economist Labor Force Statistics Branch Housing.

9

Health Status: Direct Measure versus Relative Measure

• Direct measure: Self-report of the current health status – Concern of uniformity:

• Among people in reporting own health status• Across surveys (e.g., SIPP vs MEPS)

Excellent Very good Good Fair PoorSIPP 35.6 29.9 22.7 8.2 3.6MEPS 29.9 34.1 25.5 7.6 2.8

(numbers in percent)Source: Bhandari (2004)

• Relative measure: Current health status compared with last year’s health status - Controls person specific fixed, unmeasured characteristics - Controls the effects of longstanding health conditions

Page 10: 1 Health Status and The Retirement Decision Among the Early-Retirement-Age Population Shailesh Bhandari Economist Labor Force Statistics Branch Housing.

10

Findings: Descriptive Statistics Relating to Health Status and Early Retirement

• 11.4% of the workers aged 50 to 64 reported fair or poor health, and 12.3% of them retired early

• 7.1% of workers reporting good or better health retired early

Workers Aged 50-64 by Health Status(N= 20,155 thousands)

88.6%

11.4%

Good or Better Fair or Poor

People Who Retired Anytime Between Wave 2 and Wave 6(Numbers in thousand)

7.1% 12.3%

92.9% 87.7%

Good or Better Health (N = 17,845)

Fair or Poor Health (N = 2,310)

Retired Not retired

Page 11: 1 Health Status and The Retirement Decision Among the Early-Retirement-Age Population Shailesh Bhandari Economist Labor Force Statistics Branch Housing.

11

Findings: Descriptive Statistics Relating to Health Status and Early Retirement (Contd.)

• Workers aged 50-64 were tracked from Wave1 to 6 • 92.3% of all and 87.7% of those with fair or poor health

were not retired by Wave 6

Percent of Workers Not Yet Retired in Successive Waves (People Aged 50-64 with Job in Wave 1)

100.098.3

96.7 95.493.9

92.3

96.993.9

91.089.1 87.7

100.0

Wave 1 Wave 2 Wave 3 Wave 4 Wave 5 Wave 6

All Fair or Poor Health

Page 12: 1 Health Status and The Retirement Decision Among the Early-Retirement-Age Population Shailesh Bhandari Economist Labor Force Statistics Branch Housing.

12

Findings: Descriptive Statistics Relating to Health Status and Early Retirement (Contd.)

* Asian and other races not shown above due smaller sample size

•The early retirement rates by race and Hispanic origin do not reflect the differences in health status

– Whites have better chance of good or better health than Blacks and Hispanics, but do not have lower chance of early retirement

Health Status by Race and Hispanic Origin (Workers aged 50-64 with Job in Wave 1)

(Numbers in thousand)

10.5% 19.3% 16.0%

89.5% 80.7% 84.0%

White Alone (N = 17,385)

Black Alone (N = 1,774)

Hispanic (of any race) (N = 1,396)

Fair or Poor Health Good or Better Health

Early Retirement by Race and Hispanic Origin (Workers aged 50-64 with Job in Wave 1)

(Numbers in thousand)

7.6% 8.9% 6.6%

92.4% 91.1% 93.4%

White Alone (N = 17,385)

Black Alone (N = 1,774)

Hispanic (of any race) (N = 1,396)

Retired Not Retired

Page 13: 1 Health Status and The Retirement Decision Among the Early-Retirement-Age Population Shailesh Bhandari Economist Labor Force Statistics Branch Housing.

13

Findings: Descriptive Statistics Relating to Health Status and Early Retirement (Contd.)

• The early retirement rates by marital status do not reflect the differences in health status

– Married workers have higher chances of good or better health, and also the higher chances of early retirement

Health Status by Marital Status (Workers aged 50-64 with job in Wave 1)

(Numbers in thousand)

9.8% 15.9% 13.1%

90.2% 84.1% 86.9%

Married (N=13,967)

Previously Married(N=4,814)

Never Married(N=1,374)

Fair or Poor Health Good or Better Health

Early Retirement by Marital Status (Workers aged 50-64 with Job in Wave 1)

(Numbers in thousand)

8.2% 6.8% 4.9%

91.8% 93.2% 95.1%

Married (N=13,967)

Previously Married(N=4,814)

Never Married(N=1,374)

Retired Not Retired

Page 14: 1 Health Status and The Retirement Decision Among the Early-Retirement-Age Population Shailesh Bhandari Economist Labor Force Statistics Branch Housing.

14

Findings: Descriptive Statistics Relating to Health Status and Early Retirement (Contd.)

• The early retirement rates by education do not reflect the differences in health status

• Those with Master’s/professional degree have the highest chances of good or better health, but do not have the lowest lower retirement rates

Health Status by Education (Workers aged 50-64 with Jobs in Wave 1)

(Numbers in thousand)

24.8%13.6% 9.3% 5.8%

75.2%86.4% 90.7% 94.2%

Less than HighSchool Diploma

(N=1,069)

High School /Some College

(N=8,723)

Associate /Bachelor Degree

(N=7,371)

Master orProfessional

Degree (N=2,992)

Fair or Poor Health Good or Better Health

Early Retirement by Education (Workers aged 50-64 with Job in Wave 1)

(Numbers in thousand)

9.8% 8.0% 6.9% 7.9%

90.2% 92.0% 93.1% 92.1%

Less than HighSchool Diploma

(N=1,069)

High School /Some College

(N=8,723)

Associate /Bachelor Degree

(N=7,371)

Master orProfessional

Degree (N=2,992)

Retired Not Retired

Page 15: 1 Health Status and The Retirement Decision Among the Early-Retirement-Age Population Shailesh Bhandari Economist Labor Force Statistics Branch Housing.

15

Findings: Descriptive Statistics Relating to Health Status and Early Retirement (Contd.)

Relative Health Status: Wave 6 Versus Wave 3

•25.4% of the workers reported worse health in Wave 6 than in Wave 3, and 8.2% percent of them retired early

• 7.5% of those reporting unchanged or better health retired early, not different from the rate for those reporting worse health

Relative Health Status in Wave 6 Compared with Wave 3 (N = 20,155 thousand)

25.4%

74.6%

Health Status Worsened Health Status did not Worsen

Retirement Decision by Relative Hearlth Status(Wave 6 Data Compared with Wave 3)

(Numbers in thousand)

8.2% 7.5%

91.8% 92.5%

Health Status Worsened (N = 5,125)

Health Status did not Worsen (N = 15,029)

Retired Did not retire

Page 16: 1 Health Status and The Retirement Decision Among the Early-Retirement-Age Population Shailesh Bhandari Economist Labor Force Statistics Branch Housing.

16

Findings: Regression Results

Variables Model 1 Model 2 Model 3

Intercept -2.09 -2.12 -2.12

Health Status N/A 0.68 0.09

How is Health Status Measured?

Health status not controlled

Self-reported fair/poor health

Worse health in Wave 6 than 3

Likelihood Ratio (Model Robustness Measure) 5.41E+09 6.071E+09 5.429E+09

•Source: SIPP 2004 Panel Waves 1- 6; •All models and estimates are significant at 99%

• Full regression results are available upon request

Page 17: 1 Health Status and The Retirement Decision Among the Early-Retirement-Age Population Shailesh Bhandari Economist Labor Force Statistics Branch Housing.

17

Findings: Regression Results (Contd.)

• Using self-reported fair/poor health status: • Coefficient = 0.68; probability of retirement = 64%• Captures the effects of longstanding health condition• Subject to person specific reporting bias

• Using relative measure (Worse health in Wave 6):• Coefficient = 0.09; probability of retirement = 52%• Captures only the changes in health over one year• Person specific reporting bias is controlled

Page 18: 1 Health Status and The Retirement Decision Among the Early-Retirement-Age Population Shailesh Bhandari Economist Labor Force Statistics Branch Housing.

18

Summary

• Findings: Descriptive statistics– Direct measure showed: 11% of the workers aged 50-

to-64 reported fair or poor health in Wave 6– Relative measure showed: 25% of the workers reported

worse health in Wave 6 compared to Wave 3– Early retirement is more prevalent among people

reporting fair or poor health, as well as those reporting worsening health

– Early retirement rates and the reported health status are not consistent among races and Hispanic origin, among marital status groups, and among education groups

Page 19: 1 Health Status and The Retirement Decision Among the Early-Retirement-Age Population Shailesh Bhandari Economist Labor Force Statistics Branch Housing.

19

Summary (contd.)

• Findings: Regression results– Self-report (64% probability): Large effects on retirement

decision; probably an over-estimate due to:• Personal bias in reporting the health status• Long standing bad health prior to the interview

– Difference in reported health status (52% probability): An estimate akin to controlling fixed, unmeasured characteristics; theoretically more plausible and intuitive

– There is no benchmark value that represents the true coefficient value, so it is difficult to compare the two coefficients and conclude which coefficient is better

Page 20: 1 Health Status and The Retirement Decision Among the Early-Retirement-Age Population Shailesh Bhandari Economist Labor Force Statistics Branch Housing.

20

Some Thoughts for Future Work• Investigate what workers do after early-retirement

to understand:– Relative importance of waiting for full retirement age

• Decompose the income effect and substitution effects of among retirement age workers to see:– Relative importance of leisure (compared to the forgone

income due to retirement)

• Build theoretical model to understand:– Relative importance of demand and supply forces in the

labor market for those aged 65+

Page 21: 1 Health Status and The Retirement Decision Among the Early-Retirement-Age Population Shailesh Bhandari Economist Labor Force Statistics Branch Housing.

21

The estimates in this report (which may be shown in text, figures, and tables) are based on responses from a sample of the population and may differ from actual values because of sampling variability or other factors. As a result, apparent differences between the estimates for two or more groups may not be statistically significant. All comparative statements have undergone statistical testing and are significant at the 90-percent confidence level unless otherwise noted.

Contact Information:

Shailesh BhandariLabor Force Statistics Branch

Housing and Household Economic Statistics DivisionUS Census Bureau

E-mail: [email protected]: 301-763-5621