Alicia H. Munnell, Geoffrey T. Sanzenbacher, and Matthew S. Rutledge Center for Retirement Research at Boston College

17th Annual Meeting of the Retirement Research ConsortiumWashington, DCAugust 6, 2015

What Causes Workers to Retire Before They Plan?

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Introduction

• Workers are internalizing the message to work longer.o Between 1991 and 2014, one survey found the number of

workers planning to work past age 65 tripled from 11 to 33 percent.

• But, an analysis of the Health and Retirement Study (HRS) finds that 41 percent of workers retired earlier than planned.

• What are most important factors driving earlier-than-planned retirements?

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What we know

• The literature points to several correlates of earlier-than-planned retirement:o Deterioration in health (e.g., Őrestig, Strandh, and Stattin

2013, Dwyer and Hu 2000, and Disney and Tanner 1999);o Marital changes (Disney and Tanner 1999);o Changes in finances (Andersen 1985); ando Changes in employer (Munnell, Jivan, and Triest 2004).

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What we don’t know

• Most studies focus on a subset of the following “shocks”:o Health and its interaction with retiree health insurance

(RHI);o Employer change and job loss;o Spousal retirement and other familial changes; ando Changes in finances.

• This project will address this gap by including all these shocks in a model of earlier-than-planned retirement.o Allows analysis of relative importance of shocks.

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The data

• To estimate a model of earlier-than-planned retirement, data from the 1992-2012 waves of the original HRS cohort is used.

• Sample consists of individuals who are working at the interview closest to their 58th birthday.

• HRS poses questions related to planned retirement for all workers.

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The dependent variable

• Dependent variable equals one if worker retires earlier-than-planned.

• The planned retirement year is obtained in one of two ways:1. A person’s answer to when they “plan” or “think” they are

going to retire as of their age-58 interview.2. If a person says “never” at their age-58 interview, the

answer to those same questions at the next closest interview is used.

• The individual’s actual retirement year is the first year the individual claims to be “fully” retired.

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Most of the sample has a planned retirement age near their age-58 interview.

Age reported Share of sample Avg. planned retirement age Percent retiring early

55 3.0% 63.7 52.3%56 11.2 63.3 45.557 22.4 63.3 42.458 23.4 63.3 39.759 15.0 63.8 39.460 11.6 64.2 39.361 7.8 64.6 40.162+ 5.7 68.1 42.0

Distribution of Reporting Ages of Expected Retirement Age and Percent Retiring Early

Source: Authors’ calculations from the Health and Retirement Study 1992-2012 waves.

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Independent variables: health shocks

• Paper uses an objective health index that sums 13 indicators for whether an individual has certain health conditions.o These include conditions like “activity limiting lung

disease,” “heart condition,” “arthritis with medication.”o And limitations like “needs help walking.”

• The max change in health between when plans are made and the planned retirement year (or retirement) is the “health shock.”o This change is also interacted with RHI to see if having

outside health insurance increases effect of shocks.

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Independent variables: other shocks

• Other shocks also represent changes between the time the plan is made and the planned retirement year (or retirement), including:o A change in employer;o Job loss through layoff or business closing;o Spouse’s retirement;o Spouse’s deteriorating health;o A child leaving home;o A divorce or new marriage; ando Large changes in financial wealth.

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Health shocks are common, job changes and familial changes are less common.

Shock Share experiencing shock Share retiring earlyIncrease health index 38.2% 44.8%

Switch employer 10.7 35.0

Laid off/business close 12.3 54.9

Spouse retires 19.5 46.1

Spouse health worsens 7.8 44.5

Resident child leaves 16.8 41.3

Marital change 7.7 44.6

Wealth declines 50% 32.4 43.5

Average regardless of shock: 41.5

Frequency of Shocks, Original HRS Cohort

Source: Authors’ calculations from the Health and Retirement Study 1992-2012 waves.

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Independent variables: inclusion of demographic and initial characteristics

• Individuals implicitly take into account their own characteristics when making plans – so shouldn’t impact early retirement.

• At the same time, some characteristics may be correlated with planning ability and prevalence of shocks.o For example, the less educated may overestimate working

life and underestimate likelihood of worsening health.o This could cause an overstatement of the impact of shocks.

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Worsening health, job loss, spousal retirement associated with early retirement.

Health Effect (%) Employment Effect (%)

Increase in index of 1 2.9** Change employer, no job loss -2.5

Increase with RHI 2.1 Change employer, with job loss -7.9

Initial index 2.9*** Job loss with no new employer 27.2***

Familial Effect (%) Wealth Effect (%)

Spouse retires 5.0* Decrease wealth 50% 1.2

Spouse worse health 4.8 Increase wealth 50% 0.1

Marital change 0.0

Resident child leaves 1.4

Marginal Effect on Probability of Retiring before Plan

Note: Coefficients are significant at the 10-percent (*), 5-percent (**), or 1-percent (***) level. Regression includes full set of demographic controls and initial conditions for all shocks.Source: Authors’ calculations from the Health and Retirement Study 1992-2012 waves.

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Interpreting the regression results

• For effect size, losing a job through layoff or business closing is most important, followed by spousal retirement.

• Worsening health and poor initial health also have statistically significant results.o Interestingly, retiree health insurance does not significantly

increase the likelihood of early retirement.

• But the importance of these variables depends on two things: 1) the size of the effect; and 2) the frequency with which shocks occur.

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A counterfactual exercise

• We can use the regression results to perform “counterfactuals” seeing how many people would retire early if:o No one’s health got worse;o Everyone was healthy (Index = 0) to start with;o No one lost their job;o No one’s spouse retired; ando Nothing “bad” happened (i.e., no one had anything happen

to them that increases the probability of early retirement).

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In counterfactuals, health is the most important factor, but much is unexplained.

Source: Authors’ calculations from the Health and Retirement Study 1992-2012 waves.

Actual

No spouse

retir

es

No hea

lth sh

ocks

No job lo

ss

No initi

al hea

lth p

roblem

s

No hea

lth sh

ocks/a

ll in

itiall

y hea

lthy

No "bad

" effe

cts30%

35%

40%

45%

41.3% 40.4% 39.6%39.4% 38.5%

36.8%35.0%

0.9% 1.7% 1.9% 2.8%4.5%

6.3%

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Conclusion

• Health is the most important driver of early retirement – both changes in health and poor initial health.o RHI does not have a significant effect on early retirement

in response to a health shock.

• Job loss and then spousal retirement are next biggest causes of early retirement.

• Much remains unexplained – even eliminating all “bad” shocks in the model and assuming all are healthy, 35 percent retire early.

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Next steps

• Investigating why much remains unexplained:o Is there a way to proxy planning accuracy that we are

missing?o Are shocks being measured in the right way?o Any major shocks we are missing?

• Exploring the option of making the analysis a “survivor” type regression.o An advantageous approach is that it more accurately

models the timing of shocks.