LABOR SUPPLY DECISIONS OF THE SENIOR POPULATION: EFFECT OF CHANGES TO THE SOCIAL SECURITY EARNINGS TEST

May 14, 2008

Michael Tamkin

Department of Economics Stanford University Stanford, CA 94305

mtamkin@stanford.edu

under the direction of Professor Michael J. Boskin

ABSTRACT This paper evaluates the effect of the Senior Citizen’s Freedom to Work Act of 2000 on the labor supply of the senior population. The University of Michigan’s Panel Study of Income Dynamics (PSID) 1999 and 2003 waves are used to model and compare the retirement decisions of seniors before and after the passage of the law in 2000. Using analysis based on a life-cycle model of saving developed by Burtless and Moffit (1985), it is found that retirement probabilities fell for seniors aged 65-69 in the 2003 PSID versus the 1999 PSID in particular at ages 66 and 69, however the change in labor supply in terms of hours of work is more mixed. It is also found that female seniors, seniors with dependents, seniors with spouses still working, and nonwhites retire less frequently. Poor health and being married encourage retirement and fewer hours of work Keywords: senior labor supply, aging work force, earnings test, Senior Citizen’s Freedom to Work Act, work after retirement Acknowledgements: I would like to thank my advisor, Professor Michael Boskin, who has inspired me in my study of Economics since my first quarter at Stanford. I appreciate his guidance and countless insights throughout the writing of this thesis. I also want to thank Professor Geoffrey Rothwell for his valuable advice. Finally, I would like to thank my family for their constant support.

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I. Introduction

In many industrialized countries, a demographic shift is occurring that will have

significant effects on the way society operates. While life expectancy continues to rise in

developed countries such as Japan, France, and the United States, birth rates have fallen. As

graph one indicates, the life expectancy from birth has grown from 49.2 years in 1900 to 77.4

years in 2003 (National Vital Statistics Report). Interestingly, for people who reach age 55, life

expectancy has increased from 72.9 years to 81.2 years, and for people who reach 65, life

expectancy has risen from 76.9 years to 83.4 years over this period. This means that the

increased life expectancy is not just due to lower mortality rates for individuals below age 55,

but also due to decreased mortality for the older population. As seen in graph two, the

percentage of the total United States population age 65 and over has steadily risen from 5.8% in

1939 to 9.5% in 1965, 10.5% in 1975, and 12.4% in 2005 (2007 Economic Report of the

President). Since the total United States population has grown from around 120,000,000 in the

1930’s to over 300,000,000 today, the number of seniors has increased tremendously over this

period (Census Bureau). As the Baby Boom generation (those born after 1945) and their

children grow older, the fastest growing demographic group will be those aged 70-85. This

group not only requires the most health care but is also eligible for government provided social

insurance programs such as Social Security and Medicare. The demographic trend is behind the

impending crisis facing these government programs as more people are receiving benefits and

fewer are paying taxes. The pay-as-you-go Social Security system is designed so that current

workers pay for the benefits of current retirees. As table one suggests, the old-age dependency

ratio, defined to be the number of people age 65 and over as a proportion of the working age

population age 18-64, has increased significantly, from 9.1 in 1930 to 20.5 in 2000. According

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to a projection by the Census Bureau, the old-age dependency ratio is forecast to rise to 27.7 in

2020 and 36.5 in 2040 (Population Report Census Bureau). While it is unclear exactly what

changes will be made to Social Security, it seems likely that the increase in the retiree to worker

ratio will require some combination of increasing the retirement age, reducing benefits, and

raising taxes.

Therefore, despite the current labor market’s encouragement of retirement at age 65 or

earlier due to the mandatory retirement plans of companies and the eligibility of workers for full

Social Security benefits at age 65, it is possible that in the future people will be working longer.

Individuals may face pressures to work as they get older to counteract the reduction in Social

Security benefits and to pay for increases in the cost of living. Government policy changes may

also encourage senior labor, such as Shoven and Schultz’s proposal to raise the number of years

of covered employment from 35 to 40 (Shoven and Schultz ).

Increased work may also be necessary as health costs continue to rise and as private

companies, in efforts to become more globally competitive, reduce the generosity of their

pension and retirement plans. It has been an increasingly common occurrence for companies to

reduce their retirement benefits, and many companies have switched from Defined Benefit to

Defined Contribution pension plans, which place more of the burden of saving and risk

management on the individual. As Jennifer Levitz of the Wall Street Journal comments,

“traditional corporate pension plans -- which promised specific, predictable monthly payouts --

are largely a thing of the past” (Levitz). However, the increasing labor force participation of the

senior population is not only due to necessity but also occurs because of a changing economy

and workforce. Improvements in healthcare and the shift in the economy away from jobs

requiring hard labor mean that people be will able to work much later in their lives.

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There is some evidence that the labor force participation rates for the senior population

have already started to increase. According to graph three, the 1985 to 2005 labor force

participation rates of men ages 55-59 stayed flat and for men ages 60-61 declined about 2%;

however, the participation rates for men 62-64 rose 7%, increased from 25.9% to 33.5% for men

65-69, and from 4.4% to 7.1% for men 70 and above. In graph four, depicting female labor force

participation rates from 1985-2005, the trend of increased labor supply is also very strong for

those 65-69, however this trend is evident across all age categories, with increases of 10-13% for

women 55-69. While the employment activity of women will certainly be affected by the forces

already mentioned, it is important to recognize that women began entering the labor force en

masse much later than men and so their participation might not have reached equilibrium.

Women also tend to outlive men, for example the 2000 census revealed that for every 100

women age 65 and over there are 70 men (see graph 5). Women are more likely to retire from a

main job to care for a sick relative, so in modeling retirement decisions gender must be

considered an influential factor (Census 2000).

While demographic trends and the broad retirement decisions of the senior population

have been the focus of much economic research and popular media, less attention has been paid

to the nuances of the senior population’s labor supply decisions. The dichotomy between

working and full retirement often does not capture a senior’s range of choices concerning work.

Many people not only postpone retirement from their primary job but also participate in other

forms of work. Older workers may take what are known as “bridge jobs,” jobs that serve as an

intermediate step between working and full retirement or they might take reduced positions in

their company to allow for more leisure. Seniors may also take early retirement from their main

career and then start a new one, and volunteer work often becomes important at this time.

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Because of this a precise definition of retirement must be used. One important strategy is to look

at hours of work, to see how marginal labor supply changes in response to various factors.

Studying the nature of the work decision for this population can be very instructive because

understanding the capabilities and attitude of seniors towards work can provide insight into how

society will adjust to this demographic shift.

A. Social Security and Retirement Incentives: Eliminating the Earnings Test

in 2000 There are two sides to the analysis of the senior labor force, the supply of senior labor

and the demand for senior labor. On the supply side, the question is what factors make

individuals more likely to work as they grow older. Factors such as age, health, gender,

education, marriage, spouse employment, and status of children as dependents or self-supporting

need to be taken into account. The demand analysis considers the types and availability of jobs

as well as wages and fringe benefits such as health plans offered to senior workers. In this paper

I focus on the supply part of the equation. Perhaps the most important variable in a senior’s

labor supply decision is potential Social Security benefits. With fiscal year 2007 expenditures of

$586.1 billion, 44 million beneficiaries, and 144 million taxpayers, Social Security not only

represents the largest expenditure of the government’s budget, but also impacts a majority of

Americans (Boskin). According to a 2000 Census Bureau Calculation (see graph 6), Social

Security is an extremely important source of income for senior citizens, especially for those with

little personal savings. Enacted in 1935 in the midst of the Great Depression, Social Security has

been successful in reducing poverty rates among senior citizens. Since benefits are calculated

using a complex formula translating lifetime earnings into monthly payments, workers are

potentially responsive to the incentive structures set up by Social Security. Repeated

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amendments and changes to the law have meant that these incentives have been frequently

altered. Some notable changes are highlighted in table 2. Since the 1970’s the trend has been to

reduce benefits, raise their tax liability, and to increase the normal retirement age (NRA), the age

at which a senior is eligible for full benefits.

Perhaps the most striking legislative change in recent years is the removal of the earnings

test for beneficiaries above the NRA and below age 70. Existing in various forms since 1940,

the goal of the earnings test was to lower the cost of Social Security by reducing benefits for

seniors who were earning labor income. For example, a senior who was 65 in 1997 could earn

up to $13,500 without having benefits reduced, but for every $3 of labor earnings above this

level, Social Security benefits were reduced $1, an effective marginal tax rate of 33% (see table

3). Seniors between the ages of 62 and the NRA were also subject to the earnings test, although

at different thresholds and tax rates. This program was not designed as a pure tax however, since

it was intended to compensate seniors whose benefits get reduced by increasing their benefits

through the Delayed Retirement Credit. According to the House of Representatives Report 106-

507:

Seniors who reach the full retirement age and do not receive benefits (either because they Do not file for benefits or because benefits are withheld under the earnings test) receive a delayed retirement credit (DRC) to partially compensate them for the loss. The DRC increases the worker's Social Security benefit for each month that benefits are fully withheld. The DRC is 6 percent per year for workers age 65 in 2000. It will increase by 0.5 percentage points every two years until reaching 8 percent for seniors reaching the full retirement age (then age 66) in 2009, at which point, the DRC will be ‘actuarially fair.' In other words, on average, the DRC should fully compensate workers for benefits withheld under the earnings test.

Although seniors are compensated for reduced benefits through the DRC, the DRC is not

considered “actuarially fair” by most workers, at least it would not be until 2009 where the

increases in the DRC begun since 1990 would have reached 8 percent (see table 5). In addition,

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Gruber and Orszag comment that these benefit adjustments are almost entirely unknown to the

working population, resulting in a widespread perception of the earnings test as a simple tax

(Gruber and Orszag 2000). As a result, the earnings test was often viewed to provide strong

disincentives for senior labor, either causing workers to retire earlier or to reduce their hours of

work so as not to incur the reduction in benefits. On April 7, 2000 President Clinton signed

Public Law 106-182, the Senior Citizen's Freedom to Work Act of 2000. This popular law

passed by a vote of 422-0 in the House and 100-0 in the Senate and removed the earnings test for

seniors who reached normal retirement age. It is important to determine how effective this

policy has been in encouraging senior labor (House Report).

In this paper, I evaluate the effect of the Senior Citizen’s Freedom to Work Act of 2000

on the labor supply of the Senior Population. Using the Panel Study of Income Dynamics

(PSID) I model and compare the retirement decisions of seniors before and after this change.

Since this policy eliminated the penalty for labor earnings and occurred at the same time as the

Delayed Retirement Credit was being increased, it could be expected that these two effects

would result in reduced retirement rates and greater hours of work for people 65-69 in the 2003

PSID versus the 1999 PSID. I measure the effects of key factors on the retirement decision, such

as health, race, gender, children, and marriage both as a way to control for their effects and to

help characterize the nature of the work decision. According to Professor Michael Boskin,

“attention is turning not just to the cost of Social Security with the Baby Boomers’ retirement,

but also to the slower potential growth of GDP in the economy, given the slower growth of the

labor force as the Baby Boomers retire” (Boskin). Therefore, these results will provide an

indication of how the senior population is likely to respond to these and other policy changes

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affecting work incentives, with a goal of better understanding the larger economic changes

occurring in the United States and how best to design future retirement policy.

In the Literature Review, I discuss previous research by economists on the work decision

of the senior population and specifically the Social Security earnings test. I first look at various

life-cycle and labor supply models. Concluding the Literature Review will be a discussion of

noteworthy results including estimation of labor supply elasticities, determinants of retirement,

and changing retirement rates caused by the earnings test. Within this context, I then describe

Burtless and Moffit’s (1985) paper in depth and explain how their model serves as the

cornerstone of my Study Design. I explain how I use their model and what modifications I make

in order to test certain hypotheses regarding what makes senior workers more likely to work as

they grow older.

II. Literature Review

The economic literature concerning the senior population’s labor supply focuses most

strongly on the effect of Social Security on retirement decisions. Essays by Boskin and Hurd

(1978) and Blau (1994), for example, study how certain Social Security provisions encourage

early retirement. The ability of aging workers to earn Social Security benefits at age 62 and 65,

along with the earnings test that reduces benefits in response to labor income, have been

consistently shown to encourage early retirement. Individuals often do not simply stop working

from their primary career at age 65 and then retire completely. Seniors may retire from one

career and start a second one, enter a transitional period of continued work at reduced hours,

work past 65, or start new work as a volunteer. Economists have composed models and

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conducted econometric studies to characterize the factors that influence the senior population’s

choice among these options.

A. Models

Burtless and Moffit (1985) develop a model in which individuals make a decision about

when to retire with their desired level of postretirement hours of work in mind. This strategy of

“simultaneous choice” not only eliminates problems of selection bias when trying to compare the

retired with the partially retired, but also captures the idea that seniors have more options than a

simple work or no work decision. Burtless and Moffit expand upon Milton Friedman’s

permanent income hypothesis to outline a life-cycle model of labor and saving. In this model,

individuals’ lifetime choices of labor and consumption are fixed, and they must choose at the

current moment their levels of consumption and labor during retirement. This presents tradeoffs

so that individuals compare the marginal utility of consumption gained by working with the

marginal disutility of working. The usual budget constraint, with consumption constrained by

income and prices, is modified to include two unique effects of Social Security. The earnings

test is applied so that benefits are only given to those who work less than a certain prescribed

amount. Also, individuals consider how current labor affects future Social Security wealth. At

age 62, working an extra year starts to reduce this potential wealth because that is one less year

of potential benefits. It is also found that postponing retirement above age 65 actually makes

workers worse off, a conclusion supported by Eric French (2005). While those who retire before

age 65 face a negative income effect and a positive substitution effect on optimal retirement age,

above age 65 both income and substitution effects favor immediate retirement. In Burtless and

Moffit’s model, Social Security causes the budget constraint to become nonlinear, with kinks at

age 62 and 65.

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French (2005) also uses a life-cycle model of labor and saving where future health and

wage levels are uncertain and individuals want to maximize overall lifetime utility. What is

noteworthy about this paper is that individuals can save for future retirement (to facilitate

consumption smoothing) but cannot borrow against future pension, Social Security, or wage

income. French’s model has choice variables about timing of the decision to apply for Social

Security benefits, consumption, and the labor supply decision. Exogenous variables include

survival, health, and wage uncertainty. The effect of Social Security is first to encourage labor

for the first 35 years of work, since as labor income rises so do future Social Security benefits as

determined by the AIME. French also explains how earnings test causes benefits for those under

70 to be heavily taxed for individuals making more than $6000 of labor income, cascaded with

federal, state, and payroll taxes. French also takes the view that while the benefit recomputation

for individuals age 62-65 is “roughly fair,” he calls it a “common misperception” that the

increases are fair for seniors above the age of 65 (French 5). Finally, French illustrates how

pensions often only increase in value until the normal retirement age, so that there is really no

incentive to keep working beyond that age.

While most authors focus on the senior population’s labor supply by looking at an

individual’s personal characteristics, Osberg’s contribution is to consider the demand side of the

market. Osberg (1993) develops the traditional utility labor-leisure model in a very similar way

to French; however, he modifies the budget constraint to reduce the availability and desirability

of certain jobs. Osberg aims to determine whether many retirees do not work because they are

unable to find appropriate jobs, rather than due to a preference not to work.

Hanoch and Honig (1983) employ a supply model, where seniors are trying to determine

the number of annual hours worked and annual weeks of work. In this model, individuals

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essentially compare their reservation wage with the market wage. Variables for the model

include education, health, experience on current job, total labor force experience, experience on

longest job, father’s education, Social Security earnings, pension, industry dummy variable,

urban, time trend, age trend, and partial retirement.

Finally, Feldman and Kim (2000) add to the traditional life-cycle model by employing

the continuity theory of aging and its applications to bridge employment. Bridge employment is

defined as work that individuals engage in after they retire but before they fully leave the

workforce. The authors reference Atchley’s (1989) continuity theory, which states that seniors

approach retirement by trying to maintain similar lifestyle structures (ie. stress and activity

levels), emphasizing activities that provide the most fulfillment. These may include volunteering

or leisure as well as continuing social contact levels. Kim and Feldman then expand on

Atchley’s theory by explicating various constraints and opportunities, such as diminished health

and increased time for leisure that affect the ability of seniors to maintain continuity.

B. Results

The findings of Burtless and Moffit (1985) are fundamental to understanding why certain

senior individuals work. The results of their regression estimating the choice of retirement age

and postretirement work in the context of maximizing lifetime utility showed that 25.4% of

workers retired at age 65, while 15.3% retired at age 62. Unhealthier workers were more likely

to retire. Less education, higher pre-retirement wage rates, and lack of a pension plan also made

individuals less likely to work. For retirees, the wage elasticity of labor supply was estimated to

be 0.14, while the nonwage-income elasticity was -2.14 and the total income elasticity was -0.40,

indicating that income effects dominate for the senior population. Burtless and Moffit also found

that those with more education and married men worked longer hours after retirement. It is

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estimated that cutting Social Security benefits by 20% would increase labor supply by 0.2 years.

Elimination of the Social Security earnings test would raise postretirement work from 3.2 hours

to 4.4 hours per week.

French (2005) makes similar estimates of how changes to Social Security benefits would

affect labor supply. First, he considers moving the early retirement age (the age at which

individuals can receive Social Security benefits at a reduced rate) from 62 to 63. He determines

that this would have little effect on labor supply since financing that lost year of work out of

retirees’ savings would in most cases not be prohibitive. Second, he analyzes a 20% decrease in

Social Security benefits. French finds that since older workers are more willing or able to

modify their work behavior, those above 62 would push back retirement by .25 years. Finally,

French looks at the effects of removing the Social Security earnings test and determines that

workers would work an extra year. Much like Burtless and Moffit (1985), French finds that

unhealthy individuals not only retire earlier than the healthy but also work less than healthy

people at all ages. He estimates that diminishing health accounts for a 7% decrease in labor

force participation rate between 55 and 70.

Hanoch and Honig (1983) use similar variables as French (2005) and Burtless and Moffit

(1985) but focus instead on the annual hours worked by married senior men and unmarried

senior women. The first major result of this paper is that the participation equations of married

men and unmarried females are almost identical. Age is also a very significant determinant and

its discouraging effect on labor supply increases as individuals rise above 68. Diminished health

and increasing disability also tend to encourage retirement, although more strongly for men than

women. More education encourages work and increasing nonwage income encourages

retirement, both effects which are stronger for women. These authors also note that the self-

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employed are more likely to continue working longer. Lastly, just like in other articles, men

whose wives continue to work are more likely to work longer, suggesting that couples want to

retire together. Hanoch and Honig find that wages for part-time employees are 10% lower for

men and 22% lower for women than wages for full-time employees. Estimates of the supply of

annual hours indicate that while 58 year olds work an average of 2,210 hours for 50.3 weeks, 62

year olds work 2,067 hours for 50.1 weeks, and 65 year olds 1,716 hours for 46.7 weeks.

Therefore, age is the most significant determinant of the number of hours worked by seniors.

Feldman and Kim’s (2000) study of bridge work complements many of the above

findings. With regard to the probability of doing bridge work, the probability increases when

workers are in good health and decreases with increasing age and higher salaries. Workers with

dependents were more likely to continue working past 65 and those with spouses were more

likely to try to time their retirement with their spouse. Notably, Feldman and Kim find that

bridge work raised life and retirement satisfaction, while volunteers had higher life satisfaction

scores and leisure raised both measures of satisfaction.

Herz (1995) studies the trend of work after early retirement by focusing on the effect of

pensions, specifically those who receive pensions and continue working. She first notes that the

number of early pensioners who returned to work after early retirement increased from 1984 to

1993. Employers often found in the 1980’s that older workers could be effective in filling labor

shortages in certain sectors; however, by the early 1990’s senior workers were often targeted for

cost-cutting and early retirement. From 1984 to 1993, the labor participation rate of pensioners

increased among all people younger than 65, especially those aged 50 to 54, from 64% in 1984

to 73% in 1993. Workers increased their levels of full and part-time work (fewer than 35 hours a

week), although the majority of workers 50 to 61 were doing part-time work. Herz considers

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several explanations for this trend. One explanation could be that the real value of pensions

declined from 1984 to 1993, especially since many pensions stopped offering automatic cost of

living increases, rendering returns to the workforce necessary. The author refutes this

explanation by citing data showing that the real value of pensions remained flat while Social

Security benefits actually rose over the period. Another explanation is that seniors have gotten

progressively healthier over this period (with life span growing by 1 year in the 7 years). Many

firms have also been offering more early retirement plans (up to 43% in 1991 from 17% in

1984), which means workers have an incentive to retire early (since they are often afraid of being

laid off) and then go work elsewhere. In addition, many pension plans are increasingly using

lump sum payouts instead of monthly payments. This represents a movement from defined-

benefit pensions to defined-contributions. Individuals can be much more independent when their

contributions are based on how much they save rather than a company-specific benefits formula.

Next, retiree health coverage may have declined over this era. Workers who are younger than

Medicare’s threshold of 65 must either rely on their employers’ health plans or purchase an

individual one. If employers reduce their health coverage for pensioners, then the pensioners

may have to work to pay for retirement health care (or at least have a new company to provide a

plan). In 1985, 73% of companies continued health plans into retirement, while in 1993, only

52% did. Finally, the author looks at changes in the labor market. Although the general trend

from 1984 to 1993 was an increase in senior labor participation rates, these rates fell during the

recession of early 1990. Since there is evidence that older workers were the group most heavily

laid off, this data suggests that older workers may be particularly vulnerable to business cycles.

Herz also discusses the evolution of the U.S. economy into a service economy that provides for

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flexible schedules and less physically demanding work than labor-intensive jobs such as

manufacturing. This evolution may make it more likely that seniors can work longer.

Osberg’s (1993) focus on the demand side of the labor market adds new components to

the analysis of the labor participation of seniors: the availability and quality of senior jobs. From

1973-1986, the labor force participation in Canada of men 45-64 fell from 88.5% to 80.7%. The

author wants to distinguish between two explanations of this trend. One is that this decline in

participation is due to a lack of available jobs. The second is that this decline in participation is

due to voluntary decisions to retire. Osberg postulates that satisfaction with the job search for

the senior unemployed depends on the rate of offers and the likely wage. He uses a probit model

of the probability that “an individual who was employed in January 1986 would in January 1987

report having left that job,” because he became retired. While Osberg finds similar results to

other studies on this topic, such as that the more educated are more likely to work, he finds that

the lack of available jobs increases the retirement rate by 0.19% for men 45-54 and by 0.71%

among 55-64, cumulative each year. Individuals earning higher wages were the most satisfied

with their hours of work, most likely because they were able to work part-time and still reach a

target level of savings. On the whole, underemployment was a much bigger problem than

overemployment. The overall result of this paper is that for men 55-64, a lack of available jobs

decreased the labor force participation rate by 10%.

III. Model of Retirement Timing and the Earnings Test

To study the impact of the removal of the earnings test in 2000, I have built upon the

model employed by Burtless and Moffit (1985). Burtless and Moffit’s model begins with the

idea that individuals want to maximize lifetime utility. Utility is defined as U (Ht, Ct), where Ht

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is hours of work at time t, and Ct is consumption at time t. Utility decreases in Ht and increases

in Ct. The simplifying assumption is that since these individuals are at least 50 years old, it is

possible to focus solely on the retirement and post-retirement utility decisions and take previous

labor and consumption decisions over the life cycle as given. Individuals have three choice

variables: retirement age (R), postretirement hours of work (HR), and postretirement

consumption (CR). With U (R, HR, CR) as lifetime utility, and UP (HP, CP) as preretirement

utility based upon fixed H and C, ρ as a discount rate, St as the probability of surviving from

current age to age t, and T as the age where St=0, then the maximization of lifetime utility gives:

This basically means that lifetime utility is a sum of R-1 years of utility pre-retirement

and T-R years of retirement utility. The budget constraint for this maximization is

CR = WHR+NR (2)

where W is hourly wage rate during retirement, HR is hours worked per week during

postretirement, and NR is defined as:

NR is the yearly nonlabor income for the individual who takes retirement age year R. N includes

assets (A) plus lifetime savings. Individuals who work more reduce utility due to less leisure,

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but can also increase utility since they have more consumption available, therefore the choice of

R will depend on this tradeoff. With R fixed, the above equations can be solved for HR=f(W,

NR). Finally, Social Security (Mr) is added to the model as added wealth to the budget

constraint, where st is a discount rate due to survival probability, r is the real interest rate, and

B(R) is the real annual benefit.

(4)

This gives a budget constraint of (5)

Graphically, the age of retirement constraint can be depicted in diagram 1 (Burtless and Moffit

1985, p.215). Note that S(R) represents the potential additional consumption that could be

gained from claiming Social Security (the present value of Social Security benefits). S(R)

increases from age 50-62 because working more can raise a senior’s earnings profile giving

larger future benefits. At age 62, when a senior first becomes eligible for Social Security, albeit

at reduced benefits, the situation becomes complex. Working an additional year means one less

year of Social Security benefits, yet postponing retirement could also increase future Social

Security wealth either due to higher covered lifetime earnings or due to the larger benefits to be

earned upon reaching the Normal Retirement Age. Most strikingly in this model, working from

65 to 72 is believed to reduce the present value of Social Security benefits because the increment

added by the DRC does not outweigh the loss of a year’s full benefits.

A simple way of modeling the effect of the earnings test is to construct the standard hours

of work versus consumption graph. As an example, consider the diagram below, where the red

line represents the consumption-leisure tradeoff under the earnings test, and the dotted black line

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represents the consumption-leisure tradeoff without an earnings test. Assume that an individual

is due to receive yearly Social Security benefits equal to $10,000. If this is the only nonlabor

income available, then an individual with T total hours available could choose to enjoy T hours

of leisure and consume $10,000. Now, if the earnings test exempts labor income up to $17,000 a

year for seniors age 65-69, then a person could take T1 hours of leisure and consume up to

$27,000 ($10,000 from Social Security and $17,000 from labor) a year without incurring any

penalty. However, if earnings are withheld so that $3 of income reduces benefits by $1, then an

individual working more than T-T1 hours is effectively being taxed. By the time this person

earns $47,000 in labor income, under a system with no earnings test, he would be able to

consume $57,000. With the earnings test, the total amount of benefits withheld are equal to

.333*($47,000-$17,000) = $10,000. The entire Social Security benefit is withheld and the

individual can now only consume $47,000. What does this graph predict about the effect of

eliminating the earnings test, ie. shifting the budget line up from H to H’? Three cases are

outlined. For worker 1, with labor earnings below the $17,000 threshold, a removal of the

earnings test would have no effect on his labor supply. For worker 2, who is already working so

much that he lies above the point where all benefits are taxed away, removing the earnings test

functions solely as income effect because it does not change the slope of the budget line

representing the after-tax wage rate. It is predicted that this income effect would reduce the

hours of work for worker 2. Finally, for worker 3, who is working in the range where the

earnings test is most relevant, a repeal of the earnings test would have two effects. A

substitution effect is evident because the effective real wage rate has now gone up; every hour of

work is now more valuable and so the individual has more incentive to work. Conversely, the

upward shift in the budget line also functions as an income effect because for a given amount of

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labor the worker now has more income, and so may cause a reduction in the work hours when

there is no test. Because of this ambiguity, empirical estimation is necessary to determine the

overall effects of the 2000 abolishment of the earnings test.

T1T2

$57,000

Source: De Giorgi (2007)

IV. Data and Study Design

A. PSID Background and 2005 Study of Important Variables

To study the labor supply decisions of seniors and model the effect of the 2000 Earnings

test change empirically, I used the Panel Study of Income Dynamics data set. This longitudinal

data set is run by Survey Research Center at the University of Michigan and represents a cross-

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section of United States families. The panel data was started in 1968 with a core group of

families and contains information about income status, health, and employment. In particular, I

focused on the family data section surveying heads of households. Household heads include

both men and women, and are defined to be the primary wage earner and decision maker for a

family unit. A family unit includes everyone living together as a family and can include people

who are not blood relatives. The sample currently represents about 8000 heads who are

reinterviewed every two years. It was updated in 1997 to include recent immigrants so as to

make the data more representative. I have primarily looked at data from three waves; 1999,

2003, and 2005, the latter which was just released last May. A multi-step process was used to

determine which household heads to count as retired. Each individual was asked three times

about their current employment status, the year they retired, whether they were currently

working for money, and several times about yearly labor income. Every effort was made to

accurately characterize a senior’s status. One strategy that became apparent was the need to

include certain people who self-identify as permanently disabled as retired, because often

individuals would self-identify as disabled when in reality they had removed themselves from

the labor force and were living off retirement income. In later comparisons, a difference will

also be registered between individuals who are retired in a given year (the stock dependent

variable) and seniors who transition from working to retired (the flow dependent variable). I use

the 2005 data set to provide an up-to-date picture of the population age 55 and older and to test

basic assumptions about key variables. I then test specific hypotheses about the effect of the

earnings test change with the aid of the 1999 and 2003 datasets.

In the 2005 dataset, there are 2018 heads of family units aged 55-99, with 1345 men and

673 women. When looking at the age categories in table 6, it can be seen that the percentage of

Tamkin 21

seniors who are retired by a certain age in 2005 increases in almost every sequential age category

(ie. the 76-80 year old group is more retired than the 71-75 year group which is more retired than

the 66-70 year old group etc). It would be expected that a larger percentage of retirement

occurred for each successive category, so this is a good first indicator that the data is reliable.

Retirement percentages seem to rise significantly from the 20% level for 55-59 year olds up to

the 40% level for 62 and 63 year olds. A large jump in this sample also occurs from 63 to 64 for

both men and women, representing a 20% increase. For heads aged 55-61, more women than

men are retired at these ages; however, for each age category above this a higher percentage of

men than women are retired. The differences in life expectancy are evident here as well because

among the elderly, ie. people above 70, a much lower percentage of women are retired than men.

An important variable of interest to consider in the 2005 sample is health status. One

way to model this variable is to look at health impairments, defined to be a “physical or nervous

condition that limits the type of work or the amount of work” (PSID 2005). In Graph 7, the

effect of health impairments are quite striking, giving much greater retirement percentages at

every age category. In particular, it is noticeable how high the retirement rates are at relatively

younger ages. For example, the retirement rate for 60 year old men without health impairments

is 20.3%, but 63.6% for men with health impairments. While it is necessary to be cautious

about reading too much into this result, given that a self-reported sample is likely capturing the

responses of people who are quite seriously impaired, this hypothesis will be checked in the

regressions to come. A second way of modeling health is looking at people’s responses to a

general question about their health, with possible responses of “excellent, very good, good, fair

and poor.” One potential problem with this strategy is its subjectivity and the inherent problem

of comparing the responses across individuals. One person’s “fair” might be another person’s

Tamkin 22

“excellent,” so a legitimate question is whether this variable represents a consistent measure of

health. However, when looking at Graph 8, the health categories do seem to fit with the

expected hypothesis that heads with better health have lower retirement percentages. In fact, the

retirement rates increase for each successively worse health measure, especially from the ages of

55-70.

Another important variable that might be expected to affect a senior’s labor supply

decision is whether or not there is a dependent (person age 5-18) in the family unit. Seniors with

dependents in the family unit may be less likely to retire because they would need larger incomes

to support the dependent and so would be more likely to need labor income and less likely to be

able to live off of retirement benefits alone. As seen in Graph 9, heads with dependents seem to

have lower retirement percentages than heads without dependents, especially between the ages of

55-70. There were 250 heads with dependents in this sample and in looking at the data, 60 year

olds with dependents retired 9% less, 61-63 year olds actually retired 6% more frequently, 64

year olds retired 27% less, 65 year olds 3% less, and 66-70 about the same.

Finally, the effect of race on retirement probabilities can be considered. The PSID

contains a diverse sample of heads, and the largest two groups are whites and African-

Americans. Graph 10 illustrates the trend that African-American head of households have higher

percentages retired in each age category from 55-70. The increased rate is most pronounced at

the earliest ages, such as 60, 61, and 63, where the gap ranges from 10-20%. However, when

one looks at the overall retirement percentages for all seniors aged 55-99, the white retirement

rate is 55.4% while the African-American rate is only slightly higher at 58.3%. This can be

partially explained by noticing that at the oldest ages, such as 81-99, there are many more white

Tamkin 23

seniors than African-American seniors. As a result, controlling for age will be important in the

subsequent regressions.

B. Descriptive Data for 1999 versus 2003 PSID

The first way to compare the 1999 and 2003 PSID samples is to look at the percent of

senior heads of households retired for given age categories. The 1999 sample contains 1581

heads of households, with 976 men and 605 women. The 2003 sample contains 1860 heads,

with 1213 men and 647 women. In graph 11, seniors aged 55-59 from the 1999 PSID had nearly

equal retirement rates with the same age category in the 2003 PSID. The 1999 group begins to

have higher percentages retired from ages 60-64, with particularly large differences at 60 (9%

higher for 1999) and 62 (10% higher in 1999). Age 65 presents an interesting case because the

1999 cohort actually has lower retirement percentages, with 61.8% retired versus 73% in 2003.

Retirement rates drop for the 2003 cohort relative to 1999 in the 66-70 age category, with

74.21% of seniors retired in 2003 versus 80.74% of seniors retired in 1999. The lower rates of

retirement in 2003 for 66-70 year olds is consistent with the hypothesis that eliminating the

earnings test creates added incentives to work. Finally, the retirement percentages equalize at

71-75, and for every age category above this, 2003 has higher retirement percentages.

The second method of comparing the 1999 and 2003 PSID is to look at a measure of

marginal labor supply, in particular hours of work. If the hours of work in 1999 are compared

with those in 2003 (see graph 12), the 2003 sample has higher hours of work at every age except

81-85, in particular at ages 60 (38.5 hours in 2003 vs. 26.5), 61, and 64. This gap narrows

greatly starting with the 66-70 category (with 2003 only 1 hour more per week) and beyond this

there is almost no difference between the years. However, this comparison is including retired

individuals who are doing 0 hours of work. Manchester and Song (2006) suggest that the

Tamkin 24

earnings test removal has the greatest impact by encouraging those already working to work

more. If retirees are removed and then the 1999 and 2003 PSID waves are compared based on

hours of work for heads not identified as retired, the picture changes (see graph 13). Now, the

gap between 1999 and 2003 narrows at earlier ages, with the 1999 cohort working more per

week at ages 62 and 63. Most importantly, the gaps at 65 and 66-70 grow tremendously, with

the 2003 66-70 cohort working 32.3 hours/week and the 1999 cohort working 23.5 hours.

Finally, it is also helpful to look at the yearly retirement probabilities, the probability of a

previously employed senior transitioning to retired in a given year. For the 1999 PSID, I have

included transitions to retirement occurring in 1997, 1998, and 1999 and for the 2003 PSID, I

have include transitions occurring in 2001, 2002, and 2003. This three year time frame aims to

remove some of the sampling error that occurs when using one year and also allows for seniors

to respond to the earnings test change over a longer period of time. In graph 14, the probability

of a retirement transition occuring is greater for the 1999 cohort from ages 60-63. The

probability is higher for the 2003 cohort at age 64 by 1%, and at age 65 by 32% compared with

16%. Notably, the retirement transition probabilities are dramatically higher in 1999 at the ages

of 66 and 69, with probabilities of 52.9% versus 14% and 30% versus 9% respectively. Finally,

by age 70, the 2003 probability rises again to nearly double the 1999 rate. Having looked at the

data using simple crosstabulations and probabilities, it is now informative to conduct

econometric analysis comparing the 1999 and 2003 PSID cohorts.

V. Regression Methodology

The econometric analysis of the 1999 and 2003 cohorts involves looking at four different

dependent variables with multiple specifications for each. I use probit models to characterize the

probability of a senior being retired by a given year and also the probability that a previously

Tamkin 25

employed senior will retire in a given year. The aim of these regressions is to give some

indication about the earnings test’s effect on the decision to leave the labor force and retire. To

look at the marginal effects of the earnings test, the third and fourth regressions have hours

worked per week as the dependent variable. Using OLS, I estimate the hours per work equation

twice. The first run includes the entire 1510 person sample aged 60-73. The second form

removes those individuals working 0 hours per week, giving a sample of 630 seniors aged 60-73.

The independent variables used are nearly identical for each of the regressions. These include

dummy variables for ages 60-73 (withholding age 64 to avoid multicollinearity), interaction

terms between the ages and the year 2003 (the year 2003 functions as a kind of treatment effect

relative to 1999), and then control dummy variables such as gender, health, dependents, married,

spouse working, and nonwhite. An example of the OLS regression is below:

Hours Per Week = x0 + β1 age60+ β2 age61+ β3 age62 + β4 age63 + β5 age64 + β6

age65 + β7age 66 + β8 age67 + β9 age68 + β10 age69 + β11age70+ β12 age71+ β13 age

72 + β14 age73 + β15 age 60*year03 +…+ β27 age73 *year03 + β28 year 03 + β29 female +

β29 very good health + β30 good health+ β31 fair health + β32 poor health + β33 dependent

+ β34 married + β35 spouse still working + β36 nonwhite + ε.

VI. Empirical Results

The empirical results can be seen in tables 1-4 in the appendix. Regression 1 (see

table 1) is the probit regression with the dependent variable of a senior being retired in a given

year. This regression gives several interesting results. First, eight of the age dummies are

statistically significant. The dummies for ages 60-62 all have large negative coefficients,

showing that a senior much less likely to be retired at younger ages before age 64. All of the

Tamkin 26

coefficients on the age dummies above age 65 are positive, with large coefficients attached to

age 66 and 69, and also 71-73. With regards to the 2003 interaction terms, the strongest result is

the large negative coefficient on the age 66 interaction term, suggesting that the probability of a

senior age 66 being retired in 2003 is much less than in 1999. The signs on the age interaction

terms from the 60’s are mostly negative while those in the 70’s are positive, but not as many

were significant. In looking at the control variables, it is striking how well the specification

provided significant results. The coefficient on the women dummy was negative and significant

at the 1% level. While being married seemed to slightly raise the retirement probability, having

a spouse still working lowered the probability greatly, with a coefficient of -0.442, significant at

1%. This is in keeping with the hypothesis found in the literature indicating that working

spouses often try to time their retirements together. In looking at the health measures, not much

difference was registered between the omitted “excellent variable” and the “very good” and

“good measures,” perhaps because these measures were too similar to compare across

indviduals. Large and significant to 1% effects were recorded for the “fair” and “poor” dummies

(poor’s coefficient was 1), both strongly increasing the probability of being retired. Finally, the

“nonwhite” variable was negative and significant at the 10% level, indicating a reduced

probability of being retired, however it’s effect was relatively small (only -0.145) compared with

some of the other controls.

The second probit regression (see table 2) contains the dependent variable of a senior

transitioning from employment to retirement. Five different specifications of this regression

were run giving mostly similar results. In comparison with the last regression, it is interesting

how the signs were different on the age 62 and age 63 dummy variables, this time giving larger

coefficients. Since 62 is the age at which Social Security benefits can first be acquired, this

Tamkin 27

might be suggestive of Burtless and Moffit’s indication that the Earnings Test causes bunching at

the Social Security eligibility point. Interestingly, the interaction term between age 62 and 2003

is negative, perhaps indicating that there is a reduced incentive to fully retire at age 62 now that

the Earnings Test is abolished. Again, the strongest result for the interaction terms is the large

negative coefficient for the age 66 term. While the signs are mostly as might be predicted for the

other interaction terms (negative in the 60’s ages including a large negative coefficient for age 69

interaction), the z scores are lower for this regression than the last. This is most likely caused by

the much fewer cases of “1” for the binary dependent variable in this regression measuring the

flow of retirement versus the last one which measured the stock levels of retirement. Women

again seem to retire at lower rates than men. Interestingly for this regression are the results for

the health variables. The signs for the poor health and impairment variables are negative and

significant, suggesting a reduced tendency to transition to retirement. A possible explanation for

this is that for individuals being asked in a given year about their health status, those with the

worst health and most severe impairments might have retired more than three years before the

current wave, and so would not register as transitioning. Another possibility is that the most

unhealthy workers want to stay working to remain covered by their employer’s health insurance

plan. Finally, this regression also gives nearly identical results for the variables reflecting

marriage and working spouse, with a large positive coefficient for the former and a negative

impact on retirement rates for the latter.

The third regression is the OLS estimation with hours of work as the dependent variable.

This regression includes the entire 1510 observation sample, including those with 0 hours of

work. The age dummy variables follow a predictable trend, with ages below 66 increasing the

hours of work, in particular age 60, 61, and 62 which are significant at the 1% and 5% level, and

Tamkin 28

ages 66 and above reducing the hours of work. Particularly strong is the year 2003 dummy

variable, which adds more than 6 hours of work per week, significant at 1%. Among the

interaction terms 65-70, only at age 66 do we see an indication of increased marginal labor,

adding roughly 12 hours relative to 1999. The age 68 interaction term is large and significant at

5% but negative suggesting that the 2003 cohort of 68 year olds did less work than those in 1999.

The age 70 and 70 interaction terms are also significant and negative, and this is in accordance

with the results of the previous regressions. Interpreting the 2003 versus 1999 marginal labor

supply then is complex because the year 2003 term is strongly positive, but several of the

interactions do not follow this pattern. The control variables again confirm the expected results.

Women work about 3 hours less than men, those in poor and fair health work 7 and 11 hours less

per week, respectively, heads with dependents work three hours more, and the presence of a

working spouse is estimated to add 5 hours of work.

The final regression looks at the hours of work of seniors, excluding those with zero

hours of work. The normal age dummies function as expected with large and significant hours

of work in the early 60’s and reduced hours by ages 68 and 69. The age interaction terms are

actually negative from age 60-65, but none are statistically significant. Notably, unlike the

previous regression where the age 68 group in 2003 did much less work, now that effect is

greatly reduced, and not significant. A possible explanation is that while many of the 68 year

olds reduced their hours to zero in 2003, those who stayed in the labor force did not reduce their

hours as dramatically. For the age 68 interaction term, the coefficient changes from a positive 2

hours to a positive 10 hours at 20% significance. Much like before, the coefficients on the age

70, 71, and 73 interaction terms are very large and negative. This indicates that many seniors

sharply reduced their hours upon reaching these years in 2003. Finally, this regression

Tamkin 29

reinforced the hypotheses that women work less hours than men and that the presence of

dependents increase work hours.

VII. Conclusion

The results from this analysis reinforce many of the main hypotheses about the effect of

certain demographic factors and offer hints about the effects of the 2000 removal of the earnings

test. After the four regressions were run it was found that women have lower retirement

probabilities than men, married heads have greater retirement probabilities than the unmarried,

and that heads with spouses who are still working have lower retirement probabilities.

Consensus views from the literature about dependents, namely that heads with dependents have

lower retirement probabilities and work longer hours, were also reinforced in the PSID sample.

Nonwhites were found to have lower retirement probabilities than whites, athough this result was

not seen as strongly in the hours of work regression. One factor that could be influencing this

result could be the large influx of recent immigrants added to the PSID in 1997, so repeating this

analysis with later waves of the study could prove useful. Similarly, the regressions largely

reinforced the expected hypothesis that heads with poor health have larger probabilities of

retirement and seemed to work less hours, although the transition regression suggests that the

decision to leave the labor force permanently is more complex for the unhealthy. Further

research into the labor force participation of unhealthy seniors, perhaps including medical

expenses and information about health insurance coverage, could prove helpful.

Looking at the 2003 versus 1999 waves suggests that the earnings test removal in 2000

did influence retirement probabilities; however, the results concerning marginal labor supply are

more complicated. Regressions 1 and 2 show that people who reached age 66 in 2003 were

much less likely to be retired or transition to retirement. This group in theory might be the most

Tamkin 30

influenced by the lack of an earnings test and the increase in the Delayed Retirement Credit over

that period because delaying retirement one year at age 66 to gain more benefits is a less costly

tradeoff than for older seniors. Similar effects are seen for the transition probabilities in 2003 for

68 and 69 year olds. Regression 1, along with regressions 3 and 4 both show large increases in

retirement probability and much less hours of work for the 70-73 age group in 2003 versus 1999.

This finding is interesting because this group was not directly affected by legislative action

during this period. When the coefficients on retirement probabilities for 65-69 year olds in 2003

are summed and the cumulative retirement probability coefficients for the same group in 1999 is

subtracted, the 2003 cohort has a combined coefficient that is 1.03 lower. When a similar

calculation is done for the regression 2, the 2003 cohort has a combined coefficient that is 0.515

lower than the 1999 cohort. More complicated, however, is the comparison of 1999 versus 2003

using the hours of work regressions. The regression including the entire sample has interaction

terms suggesting much lower hours of work for 68 year olds, and almost negligible impacts of

any specific age. The strongest influence is the overall year 2003 variable, however, so when

this variable is included and the coefficients for ages 65-69 in 2003 are summed and the hours

coefficients for ages 65-69 in 1999 are subtracted, the 2003 cohort nets nearly 28 hours more

over 1999. This trend is seen again in the truncated sample in regression 4, as a similar

calculation leaves 2003 17 hours ahead of 1999. These results are suggestive, yet the lack of

significance for several of the variables and the need to weight these results for accurate

interpretation means further study is necessary to make a complete determination. These results

concur with the findings by Burtless and Moffit as well as French, suggesting that removing the

earnings test would increase hours per week, but the magnitudes are quite different.

Tamkin 31

It is important to recognize the larger macroeconomic conditions during this period.

While 1997-1999 saw a large economic expansion, the economy was in recession during 2001

and 2002 and aggregate unemployment rates rose from 4.5% in 1998, 4.2% in 1999 and 4.0% in

2000, to 4.7% in 2001, 5.8% in 2002, and 6.0% in 2003 (Bureau Labor Statistics). The fact that

the 2003 cohort was experiencing a recession at the time of their interview is interesting because

it removes macroeconomic conditions as the reason for 2003’s reduced retirement probabilities.

For future work building upon the results of this paper, it would be helpful to have a larger

sample and accurate measures of past earnings, pensions, Social Security benefits, and wages.

Earnings information would be important in looking at seniors who were either slightly above or

below the earnings test threshold. Another technique would be to look at women more closely,

maybe including interactions with women and the 2003 wave cohort, since there is some

evidence that the earnings test is affecting women differently than men. The removal of the

earnings test was intended to encourage senior labor, and studies of this and alternative policy

inducements will be valuable in understanding the long-term effects of the aging of society.

Tamkin 32

APPENDIX:

i. Graph 1:

Source: National Vital Statistics Report of CDC Volume 54, Number 14. March 28, 2007

Life Expectancy in the United States 1900-2003

0.00

5.00

10.00

15.00

20.00

25.00

30.00

35.00

40.00

45.00

50.00

55.00

60.00

65.00

70.00

75.00

80.00

1900-1902

1909-1911

1919-1921

1929-1931

1939-1941

1949-1951

1959-1961

1969-1971

1979-1981

1989-1991

2003

Time Period

Year

s

Life expectancy at birth life expectancy from age 55 life expectancy at age 65

Source: National Vital Statistics Report of CDC Volume 54, Number 14. March 28, 2007

Tamkin 33

ii. Graph 2:

Percentage of Total Population in the United States age 65 and over from 1929 to 2005

0

1

2

3

4

5

6

7

8

9

10

11

12

13

14

1925 1930 1935 1940 1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

Year

Perc

enta

ge o

f Tot

al P

opul

atio

n ov

er th

e ag

e of

65

(%)

Source: 2007 Economic Report of the President

iii. Table 1: Number of Dependents Per 100 Persons Age 18 to 64 Years: 1930 to 2050 [middle series estimate]

Tamkin 34

Year Age 65 and over

1930 9.1 1940 10.9 1980 18.7 1990 20.3 2000 20.5 2010 21.2 2020 27.7 2030 35.7 2040 36.5 2050 36

Sources: Current Population Reports, Series P-25, Nos. 311, 519, 917, 1095, 1127; and table 2. Bureau of the Census.

iv.. Graph 3:

Male Labor Force Participation of Senior Population 1985-2005

05

10152025303540455055606570758085

1985 1995 2000 2005

Year

Labo

r For

ce P

artic

ipat

ion

(%)

55-59 Males60-61 Males62-64 Males65-69 Males70+ Males

Source: Bureau of Labor Statistics "The Recent Decline in Labor Force , Participation and its Implications for Potential Labor Supply," Aaronson, Fallilck, Figura, Pingle, Wascher. 2006.

Tamkin 35

v. Graph 4: Female Labor Force Participation Rate of Senior Population 1985-2005

05

10152025303540455055606570

1985 1995 2000 2005Year

Labo

r For

ce P

artic

ipat

ion(

%)

55-59 Female60-61 Female62-64 Female65-69 Female70+ Female

Source: Bureau of Labor Statistics "The Recent Decline in Labor Force , Participation and its Implications for Potential Labor Supply," Aaronson, Fallilck, Figura, Pingle, Wascher. 2006.

vi. Graph 5:

Tamkin 36

vii. Graph 6:

viii. Table 2: Recent Changes to Social Security

1935 Social Security Law Passed 1937 First payroll taxes collected and first benefits paid out 1940 Monthly Payments added to the system 1950 First cost of living increase added to the system 1961 Workers now allowed to retire at age 62 at reduced benefits 1965 Medicare added 1972 Supplemental Security Income added to SSA

1972 Amendments provided for minimum benefit level, Delayed Retirement Credit introduced

1975 Benefits increase automatically based on Cost of Living Increases 1972 1977 Double indexing to inflation and high inflation greatly increase benefits 1977 Payroll tax increased from 6.45% to 7.65%, benefits went down slightly, People age 70 and above exempted from the Retirement Earnings Test 1983 Security benefits taxed for the first time, up to 50%

Tamkin 37

Normal Retirement Age slated to increase, beginning in 2003 1994 Portion of benefits subject to tax rose to 85% 2000 Earnings Test for beneficiaries above the Normal Retirement Age eliminated by Senior Citizen’s Right to Work Act of 2000 (still applies for those below NRA). ix. Table 3: Earnings test 1990-1999

Source: Annual Statistical Supplement of Social Security , 2003 Table 2.A29

Tamkin 38

x. Table 4: Social Security Earnings Test 2000-2003

Source: Annual Statistical Supplement of Social Security, 2003 Table 2.A29

xi. Table 5: Delayed Retirement Credit Increases

Increases in Benefits for Delayed Retirement Credit People 65-70

ing NRA Yearly rate of increase for each year dYear Reach elay 1990-1991 3.50% 1992-1993 4.0% 1994-1995 4.5% 1996-1997 5.00% 1998-1999 5.50% 2000-2001 6.00% 2002-2003 6.50% 2004-2005 7.00% 2006-2007 7.50% 2007+ 8.0%

Source: SSA

Tamkin 39

xii. Diagram 1:

xiii. Table 6: The Percentage of Male and Female Head of Households Retired or Permanently Disabled by a Certain Ages in 2005

Age Category # of Heads # Male

% male retired or disabled # Female

% Female Retired or disabled

55-99 2018 1345 53.01% 673 60.62%55-59 613 484 20.25% 129 20.93%60 90 70 27.14% 20 35.00%61 88 61 34.43% 27 40.74%62 64 50 46.00% 14 28.57%63 61 48 45.83% 13 38.46%64 60 42 66.67% 18 61.11%65 53 36 72.22% 17 35.29%66-70 263 176 74.43% 87 64.37%71-75 228 136 87.50% 92 79.35%76-80 237 131 89.31% 106 86.79%81-85 158 71 95.77% 87 77.01%86-90 64 28 100.00% 36 72.22%91-95 34 11 100.00% 23 82.61%96-99 5 1 100.00% 4 100.00%

Source: (Burtless and Moffit)

Tamkin 40

Source: 2005 PSID

xiv. Graph 7:

Source: 2005 PSID

Effect of Health Impairment on Male Retirement Rates in 2005

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

55-59 60 61 62 63 64 65 66-70 71-75 76-80 81-85 86-90 91-95Age Category in 2005

% re

tired

(or p

erm

anen

tly d

isab

led)

by

cert

ain

age

in 2

005

Non-Health ImpairedMen

Health Impaired Men

Tamkin 41

xv. Graph 8: Various Self-Reported Health Measures

Age Retirement Rates for 2005 Heads of Varying Self-Reported Health Measures

0.000

10.000

20.000

30.000

40.000

50.000

60.000

70.000

80.000

90.000

100.000

55-59 60 61 62 63 64 65 66-70 71-75 76-80 81-85 86-90 91-95 96-99

Age Category in 2005

Perc

enta

ge re

tired

(or p

erm

anen

tly d

isab

led)

by

age

in 2

005

Poor HealthFair HealthGood HealthVery Good HealthExcellent Health

Source: 2005 PSID

Tamkin 42

Effect of Dependents on Head Retirement Rates

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

55-59 60 61-63 64 65 66-70 71-75 76-80 81-85 86-90 91-95 96-99

Age Category in 2005

% re

tired

(or p

erm

anen

tly d

isab

led)

by

cert

ain

age

in 2

005

Heads with DependentsHeads without Dependents

xvi. Graph 9: Effect of Dependents

Source: 2005 PSID

Tamkin 43

xvii. Graph 10: Percent Retired White and African-American Heads of Households

Retirement Rates by Age for White and African-American Heads of Households

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

45.0

50.0

55.0

60.0

65.0

70.0

75.0

80.0

85.0

90.0

95.0

55-59 60 61 62 63 64 65 66-70 71-75 76-80 81-85 86-90 91-95 96-99Age Category in 2005

% R

etire

d (o

r per

man

ently

dis

able

d) b

y ag

e in

200

5

WhiteHeads ofHouseholds

African-AmericanHeads ofHouseholds

Source: 2005 PSID

Tamkin 44

xviii. Graph 11: Comparing Percent Retired for 1999 and 2003 PSID

Age Retirement Rates 1999 and 2003

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

8

90.0

100.0

55-59 60 61 62 63 64 65 66-70 71-75 76-80 81-85 86-90 91-95 96-98

% R

etire

d( o

r per

man

ently

)dis

able

d by

age

0.0

2003 Retirement Rates

Age Category

1999 Retirement Rates

Source: 1999 and 2003 PSID

Tamkin 45

xix. Graph 12: Comparing Hours of Work, 1999 and 2003 PSID

Average Hours of Work per Week for Household Heads in 1999 and 2003

0.00

5.00

10.00

15.00

20.00

25.00

30.00

35.00

40.00

55-59 60 61 62 63 64 65 66-70 71-75 76-80 81-85 86-90

Age Category

Ave

rage

Hou

rs o

f Wor

kk P

er w

eek

2003 Hours/Week1999 Hours/week

Source: 1999 and 2003 PSID

Tamkin 46

xx. Graph 13: 1999 vs. 2003 Hours of Work for Non-Retired Heads

Hours of Work for Heads not identified as Retired 2003 and 1999

0.00

5.00

10.00

15.00

20.00

25.00

30.00

35.00

40.00

45.00

50.00

55-59 60 61 62 63 64 65 66-70 71-75 76-80 81-85

Age Category in 1999 or 2003

Ave

rage

Hou

rs o

f Wor

k/W

eek

19992003

Source: 1999 and 2003 PSID

Tamkin 47

xxi.. Graph 14: Probability of transitions to Retirement 1999 vs. 2003

Probability of retiring at a certain age in the 1999 versus 2003 PSID dataset

0.0055-59 60 61 62 63 64 65 66 67 68 69 70

10.00

20.00

30.00

40.00

50.00

60.00

Age category in 2003 or 1999

Prob

abili

ty o

f a p

revi

ousl

y em

ploy

ed h

ead

of h

ouse

hold

retir

ing

in a

giv

en y

ear

2003 PSID1999 PSID

Source: 1999 and 2003 PSID

Tamkin 48

xxii. Regressions

Table 1: Probit Model. Dependent Variable = senior is retired in a given year 1510 obs. Probit Pseudo r^2=.174 1 2

Log pseudolikelihood -802.21 -792.76 wald chi square 271.88 286.10

Prob >chi square 0.00 0.00 -0.832*** -0.828*** age60 (3.30) (3.28)

age61 -0.692*** -0.709*** (2.92) (2.98)

age62 -0.435* -0.447* (1.72) (1.75)

age63 -0.190 -0.163 (0.72) (0.63)

age65 -0.222 -0.238 (0.90) (0.96)

age66 0.648** 0.644** (2.40) (2.35)

age67 0.326 0.287 (1.21) (1.07)

age68 0.184 0.107 (0.70) (0.41)

age69 0.599** 0.552* (2.08) (1.92)

age70 0.340 0.285 (1.35) (1.13)

age71 0.467* 0.391 (1.84) (1.52)

age72 0.692*** 0.623*** (3.26) (2.91)

age73 0.627* 0.548* (1.92) (1.67)

age60*year2003 -0.180 -0.163 (0.56) (0.49)

age61*year2003 -0.0354 0.000 (0.12) (0.00)

age62*year2003 -0.109 -0.095 (0.34) (0.29)

age63*year2003 -0.078 -0.159 (0.24) (0.48)

age65*year2003 0.481 0.388 (1.50) (1.20)

age66*year2003 -0.739** -0.796** (2.14) (2.28)

age67*year2003 -0.101 -0.083 (0.29) (0.23)

Tamkin 49

age68*year2003 0.065 0.093 (0.19) (0.27)

age69*year2003 -0.176 -0.189 (0.47) (0.50)

age70*year2003 0.337 0.338 (0.99) (0.98)

age71*year2003 0.341 0.308 (0.95) (0.85)

age73*year2003 -0.076 -0.088 (0.18) (0.21)

year 2003 -0.112 -0.080 (0.54) (0.38)

female -0.302*** -0.304** (3.81) (2.39)

very good health -0.088 -0.071 (0.74) (0.59)

good health -0.022 -0.006 (0.19) (0.05)

fair health 0.385*** 0.399*** (2.96) (3.05)

poor health 1.04*** 1.04*** (5.91) (5.93)

dependent -0.139 -0.120 (1.13) (0.97)

married 0.164 (1.31)

spouse working -0.442*** (4.36)

nonwhite -0.145* -0.148* (1.76) (1.78)

constant 0.506** 0.515* (2.54) (2.24)

Nsi

ote: Absolute value of z-statistics in parenthesis. *** = 1% significance ** = 5 % gnificance * = 10% significance. Heteroskedastic Standard Errors assumed.

Tamkin 50

Table 2: Probit Model: Dependent Variable = A senior transitions from employment to tirement in a given year

1 1 2 3 4 5 re

510 obs. Probit pseudolike -414 -418.623 .88 -409.91 Log

lihood -423.03 .752 -412wald chi squ 62.0 57.54 67.99 71.84 are 40.7 0

Prob >chi s 0.001 0.0008 0.0005 0.0002 quare 0.033 -0.046 -0.0 -0.0848 -0.0752 -.0386 67 age60

) (0.2 (0.25) (0.11) (0.140 0) (0.22)age61 -0.0 -.0172 -0.0296 -0.043 0.122 23

) (0.0 (0.05) (0.09) (0.13) (0.040 7) age62 0.19 0.188 0.166 0.159 0.214 2

) (0.5 (0.57) (0.51) (0.49) (0.660 9) age63 0.37 0.339 0.346 0.349 0.345

) (1.1 (1.04) (1.06) (1.07) (1.07 4) age65 -0.1 -0.174 -0.164 -0.121 -0.187 50

) (0.4 (0.50) (0.47) (0.34) (0.540 3) age66 0.23 0.230 0.206 0.233 0.243 9

) (0.7 (0.74) (0.67) (0.75) (0.790 7) age67 -0.2 -0.302 -0.321 -0.330 -0.325 78

) (0.7 (0.82) (0.87) (0.89) ( .8900 5) age68 -0.0 -0.132 -0.115 -0.152 -0.125 73

) (0.2 (0.37) (0.32) (0.42) (0.360 1) age69 -0.2 -0.264 -0.299 -0.290 -0.244 41

) (0.6 (0.70) ) (0.77) (0.660 4) (0.79age70 -0.3 -0.397 -0.448 -0.462 -0.392 95

) (1.0 (1.10) (1.24) (1.27) (1.090 9) age71 -0.3 -0.348 -0.380 -0.382 -0.318 14

(0.9 (1.03) (1.12) (1.12) (0.94) 2) age72 -0.9 -0.923*** -0.973*** -0.993*** -0.932*** 01***

) (2.6 (2.76) (2.90) (2.97) (2.830 6) age73 -0.6 -0.673 -0.749 -0.770 -0.681 91

) (1.4 (1.39) (1.53) (1.56) (1.40 1) age60*year -0.5 -0.553 89 -0.615 2003 -0.565 92 -0.5

(1.34) (1.26) 34) (1.39) (1.29) (1.age61*year -0.4 -0.471 493 -0.457 2003 - .500 0 83 -0.

(1.1 (1.13) (1.17) (1.09) (1.21) 5) age62*year2003 -0.3 -0.337 -0.346 -0.321 -0.371 53

(0.8 (0.82) (0.83) (0.78) (0.91) 5) age63*year -0.4 -0.355 -0.428 -0.397 2003 -0.394 16

) (1.0 (0.86) (1.03) (0.96) (0.97 0) age65*year -0.0 0.00 -0.04 -0.111 2003 0.00 17

Tamkin 51

(0.0 (0.00) (0.09) (0.25) (0.00) 4) age66*year -0.8 -0.829* -0.869* -0.873** 2003 -0.833* 48*

(1.8 (1.86) (1.94) (1.93) (1.88) 9) age67*year2003 -0.0 0.037 -0.016 -0.012 0.021 23

(0.0 (0.08) (0.03) (0.03) (0.04) 5) age68*year2003 -0.49 -0.466 -0.497 -0.476 -0.456 8

(1.05 (0.98) (1.03) (1.00) (0.98) ) age69*year2003 -0.84 -0.783 -0.815 -0.852 -0.812 4

(1.46 (1.35) (1.41) (1.47) (1.41) ) age70*year 0.07 0.100 0.067 0.086 2003 0.055 8

(0.17 (0.22) (0.15) (0.19) (0.12) ) age71*year2003 -0.51 -0.455 -0.540 -0.563 -0.523 5

(1.06 (0.94) ) (1.16) (1.08) ) (1.11age73*year2003 -0.03 -0.036 -0.067 -0.026 -0.034 5

(0.06 (0.06) (0.11) (0.04) (0.06) ) year 2003 0.30 0.287 0.332 0.343 0.313 9

(1.09 (1.02) (1.18) (1.21) (1.14) ) female -0.159 -0.176* -0.175 0.148

(1.50) (1.67) (0.83) (1.52)very good he -0.035 -0.028 -0.0297 alth

(0.23 (0.151) (0.20) ) good health 0.02 0.049 0.060 3

(0.16 (0.33) (0.41) ) fair health -0.282* -0.227 -0.224

(1.71) (1.36) (1.34) poor health -0.61*** -0.563** -0.545**

(2.63) (2.41) (2.32) impairment -0.247*

(2.33) dependent -0.168 -0.185

(0.90) (0.99) married 0.412**

(2.45) spouse working -0.125 -0.197

(1.00) (1.54) nonwhite -0.136 -0.116

(1.22) (1.02) constant -1.268*** -1.1237*** -1.13*** -1.04*** -1.393

(-5.36) (-4.18) (4.63) (3.81) (4.40) Note: Absolute value of z-statistics in parenthesis. *** = 1% significance ** = 5 % sign* = 10% significance. Heteroskedastic Standard Errors assumed.

ificance

Tamkin 52

Table 3: OLS Regression: Dependent Variable = Hours of Work (note includes entire sample)

g 1 1510 obs. OLS Re . 2

F(26,1483) 12.77 4 16.6Prob >F 0 0

Root MSE 18.753 6 18.0

12.78*** 6*** 12.7age60 (3.39) (3.60)

age61 13.05*** 5*** 12.8 (3.74) (3.86)

age62 10.33** 9** 10.4 (2.53) (2.66)

age63 2.055 2.61 (0.53) (0.71)

age65 3.19 4.72 (0.96) (1.46)

age66 -2.51 -1.77 (0.84) (0.58)

age67 -4.59 -2.42 (1.52) (0.80)

age68 -1.66 0.97 (0.54) (0.32)

age69 -6.183** 2** -5.72 (2.31) (2.14)

age70 -2.63 1 -0.98 (0.89) (0.33)

age71 -2.25 -0.328 0.76) (0.11( )

age72 -8.94*** -6.76*** (3.86) (2.91)

age73 -8.34*** 7** -6.3 (2.98) (2.27)

age60*year200 2.086 0 3 1.07 (0.46) (0.25)

age61*year200 0.67 53 3 -0.0 (0.14) (0.01)

age62*year200 -3.37 8 3 -3.8 (0.66) (0.78)

age63*year200 0.276 3 3 0.65 (0.06) (0.14)

age65*year200 -4.74 6 3 -4.9 (1.08) (1.19)

age66*year200 6.38* * 3 5.84

Tamkin 53

(1.70) (1.67) age67*year200 1.044 7 3 0.15

(0.24) (0.04) age68*year200 -8.905** -9.71*** 3

(2.34) (2.64) age69*year2003 2.014 6 2.0

(0.47) (0.49) age70*year200 -9.21** -9.49*** 3

(2.54) (2.64) age71*year200 -8.90** 3** 3 -7.7

(2.30) (2.02) age73*year200 -3.53 9 3 -4.3

(0.96) (1.20) year 2003 6.56*** 3*** 6.3

(2.74) (2.67) female 3** -3.3

(2.05) very good health 0.903

(0.52) good health -0.820

(0.50) fair health *** -7.023

(3.94) poor health -11.70***

(6.43)dependent 3.23*

(1.93) married -0.286

(.18) spouse working 5.123***

(3.46) nonwhite 0.584

(0.54) constant 11.90*** 13.57***

.62) (5 (4.64) Note: Absolute value of z-statistics in parenthesis. *** = 1% significance ** = 5 % significance * = 10% significance. Heteroskedastic Standard Errors assumed.

Tamkin 54

Table 4: ssion: D nt Variable = Hours of Work (note does not include people with hours of work equal to 0)

630 obs. OLS 1 4 5 6 7 8

OLS Regre epende

2 3 F(26,603) 4.48 5.54 5.10 5.36 5.73 5.18 5.01 5.53 Prob >F 0.000 0.0 0.000 0.000 0.000 00 0.000 0.000 0.000 Root MSE 14.773 14. 14.609 14.695 14.583 14.579 14.58 589 14.60

8.93** 9.27** 9.176** 9.89** 9.81** 9.32** 9.04** 8.30** age6(2.18) (2.3 (2.46) (2.45) (2.32) (2.22) (2.05)

0 (2.32) 0)

age6 9.85** 9.414 9.98** 9.93** 9.41** 9.40** 8.87** 1 9.43** ** (2.55) (2.4 (2.57) (2.56) (2.46) (2.41) (2.31) (2.47) 7)

age62 9.09* 8.55* 8.5 8.80* 8.73* 8.40* 8.42* 8.30* 9* (1.91) (1.79) (1.8 (1.83) (1.81) (1.75) 1.74 (1.74) 1)

age63 7.30 7.30 7.18 7.90 7.87 7.48 7.79 7.09 (1.33) (1.3 (1.46) (1.45) (1.38) (1.43) (1.30) (1.36) 4)

age65 2.63 3.10 3.14 3.56 3.50 2.86 2.94 2.58 (0.64) (0.7 (0.85) (0.84) (0.70) (0.70) (0.64) (0.76) 7)

age66 -1.17 -0.83 -0.58 -0.47 -1.14 -0.95 -1.16 -1.02 (0.26) (0.22 (0.18 (0.12) (0.10) (0.25) (0.20) (0.25) ) )

age6 0.97 0.97 0.91 1.03 1.08 0.78 0.74 0.72 7 (0.17) (0.1 (0.19) (0.20) (0.14) (0.14) (0.13) (0.18) 7)

age6 -2.42 -2.83 -2.8 -2.85 -3.10 -3.65 -3.62 8 5 -2.83 (0.58) (0.670 (0.6 (0.66) (0.67) (0.73) (0.84) (0.85) 8)

age6 -8.04* -7.41* -7.3 -6.90* -6.90* -7.55* -7.43* -7.90* 9 9* (1.89) (1.8 (1.65) (1.67) (1.84) (1.75) (1.93) (1.80) )

age7 1.87 3.10 3.1 3.30 3.30 2.96 2.61 2.51 0 6 (0.43) (0.7 (0.76) (0.76) (0.69) (0.60) (0.59) (0.72) 4)

age7 0.67 0.07 -0.0 88 -0.28 0.014 -0.77 1 1 0.78 0. (0.14) (0.0 ) (0.18) (0.06) (0.00) (0.16) (0.01) 0) (0.16

age7 -4.62 -4.77 -4.891 -4.36 -4.29 -5.03 -4.68 -5.16 2 (0.69) (0.7 (0.64) (0.63) (0.74) (0.69) (0.76) (0.71) 3)

age60*year2 3 -4.30 -4.75 -4.94 -4.86 -4.73 -4.73 -4.72 -4.69 00 (0.60) (0.6 (0.68) (0.66) (0.65) (0.65) (0.65) (0.66) 9)

age61*year2 3 0.18 0.16 -0.11 -0.178 -0.09 0.22 0.051 0.20 00 0.03 ) (0.0 (0.02) (0.01) (0.03) (0.01) (0.03) (0.02 2)

age62*year2 3 -6.80 -6.27 -6.57 -6.28 -6.11 -6.14 -6.63 -6.84 00 (0.87) (0.8 (0.80) (0.70) (0.77) (0.84) (0.86) (0.79) 4)

age6 -4.19 -4.55 -4.44 -4.44 -5.19 -4.76 3*year2003 -4.91 -4.15 ) (0.5 (0.57) (0.56) (0.56) (0.65) (0.60) (0.62 (0.52) 3)

age6 4 0.1 1.08 1.06 0.50 0.23 -0.67 4*year2003 -0.2 0.41 0 (0.03) (0.0 (0.14) (0.13) (0.06) (0.03) (0.09) (0.05) 1)

age6 9 -6.28 -6.11 -6.02 -5.95 -6.37 -6.40 5*year2003 -5.1 -6.00 (0.68) (0.8 (0.80) (0.79) (0.78) (0.83) (0.85) (0.79) 3)

age6 1.27 1.48 1.43 1.64 1.53 1.37 6*year2003 1.80 1.74 (0.22) (0.1 (0.18) (0.17) (0.20) (0.18) (0.16) (0.21) 5)

age6 10 -2.8 -2.29 -2.21 -2.54 -2.49 -2.97 7*year2003 -2.7 -2.78 1 (0.30) (0.3 (0.26) (0.25) (0.29) (0.28) (0.33) (0.31) 2)

age68*year2 3 -5.78 -4.77 -5.08 -4.54 -4.46 -4.58 -3.92 -4.42 00

Tamkin 55

(0.76) (0.6 ) (0.58) (0.58) (0.50) (0.56) (0.62) 6) (0.58age69*year2 3 10.03 9.46 9.35 9.37 9.56 9.075 9.27 00 9.64

(1.25) (1.2) (1.17) (1.18) (1.2) (1.14) (1.17) (1.21) age70*year2003 -12.46 * -14 -13.77* -13.63* -14.10* -13.4* -13.80* -14.04 .24*

(1.53) (1.7 ) (1.68) (1.74) (1.65) (1.70) (1.74) 6) (1.69age7 1 -1.6 -2.11 -1.54 -2.23 -1.59 1*year2003 -3.0 -1.48 0 -2.09

) (0.1 (0.22) (0.23) (0.16) (0.24) (0.17) (0.32 (0.16) 7) age7 76 -12 -11.76 -11.59 -12.02 12.47 12.58 3*year2003 -12. -11.83 .02

(1.48) (1.4 (1.37) (1.35) (1.41) (1.46) (1.48) (1.39) 2) y 4.16 3.87 3.77 3.85 3.94 4.15 ear 2003 3.89 3.89

(0.6) (0.6 (0.59) (.57) (.57) (0.59) (0.63) (0.59) 3) fem -5.5 -5.48*** -5.58*** -6.51*** -6.30*** -6.28*** ale -5.57*** 4***

(4.3 (4.21) (4.27) (3.31) (3.15) (3.14) (4.31) 0) very good 0.83 0.85 0.69 health

(0.42) (0.43) (0.35) good h -0.92 -0.97 -1.34 eal th

(0.49) (0.52) (0.72) fair health 1.409 1.27 1.18

(0.59) (0.52) (0.48) poor healt 1.923 1.64 1.41 h

.47) (0.4) (0.33) (0impairmen -0.801 -0.91 t

(0.4 (0.52) 7) depend 4.33*** 4.14** ent

(2.35) (2.28) ma -0.66 -0.59 -0.50 rried

(0.33) (0.30) (0.25) spouse w -0.97 -1.02 -0.99 orking

(0.62) (0.65) (0.25) n -0.17 -0.05 onwhite 0.61

(0.48) (0.09) (0.04) cons 31.95*** 33.34*** 33.45*** 32.79*** 32.69*** 34.39*** 34.07*** 34.39*** tant

(9.6) ) (10 (8.75) (8.66) (9.49) (8.55) (9.43) (9.94 .00) N te: Ab ue of z-st par *** = 1% significance ** = 5 % significance

10% significance. Hete ed. o =

solute val atisticsroskedastic Standard Errors assum

in enthesis. *

Tamkin 56

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