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

2 Labor Market Facts The U.S. p opulation 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?

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?

4 Research Question and Data Research question What is the role of health status in early retirement decision? Data –2004 SIPP Panel, Waves 1-6 –Population: Those aged with job in wave1 –Sample size: Unweighted: 7,714 Weighted: 20,155 thousand

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

6 Methods: Logistic Regression Universe: Those aged 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

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

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

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) (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

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

11 Findings: Descriptive Statistics Relating to Health Status and Early Retirement (Contd.) Workers aged were tracked from Wave1 to % of all and 87.7% of those with fair or poor health were not retired by Wave 6

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

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

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

15 Findings: Descriptive Statistics Relating to Health Status and Early Retirement (Contd.) Relative Health Status: Wave 6 Versus Wave % 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

16 Findings: Regression Results Source: SIPP 2004 Panel Waves 1- 6; All models and estimates are significant at 99% Full regression results are available upon request

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

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

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

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+

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 Bhandari Labor Force Statistics Branch Housing and Household Economic Statistics Division US Census Bureau Phone: