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Archives of Business Research – Vol. 12, No. 4
Publication Date: April 25, 2024
DOI:10.14738/abr.124.16774.
Son, C. H. (2024). The Effects of Increasing the Full Retirement Age from 66 to 67 on the Retirement Decision at the Early Retirement
Age of 62. Archives of Business Research, 12(4). 18-37.
Services for Science and Education – United Kingdom
The Effects of Increasing the Full Retirement Age from 66 to 67
on the Retirement Decision at the Early Retirement Age of 62
Chong Hwan Son
Department of Education and Social Sciences, Hudson Valley Community College
80 Vandenburgh Ave. Troy, New York 12180, U.S.A
ABSTRACT
In the United States, the full retirement age increases in two-month increments each
year until reaching 67 years of age in 2027 for individuals born from 1955 to 1960.
The increase in the full retirement age is equivalent to a decline in the Social
Security benefits for all new retirees. If the full retirement age is increased from 66
to 67 while the early retirement age remains at 62, then the monthly benefit
reduction at age 62 would increase from 25% to 30%. Despite the reduction in
Social Security benefits, a significant portion of newly retired workers claim their
Social Security benefits as soon as they turn 62, which is the earliest age to claim the
benefit. The Social Security Administration predicts that the reduction in Social
Security benefits can encourage workers to delay their retirement and that the
reduction can restore some financial balance to the Social Security system.
Therefore, studying the effects of increasing the full retirement age from 66 to 67
on the retirement decision at 62 is essential for planning future social security
reforms. This study conducts a Two-Stage Least Squares (2SLS) regression, using
cross-sectional and time series data from the Behavioral Risk Factor Surveillance
System (BRFSS) from 2016 to 2021. The empirical results show that the probability
of retirement for individuals at age 62 decreased from 2016 to 2021, indicating a
trend of delaying retirement as their full retirement age rises. During the same
period, the likelihood of men reporting being retired decreases by 35.56%, while
for women, it drops by 16.79%. It implies that if male and female workers choose to
exit the workforce solely based on the Social Security benefits, the increase in full
retirement age appears to have a more significant impact on delaying retirement
decisions for male workers than for female workers.
Keywords: Full Retirement Age, Early Retirement Age, Social Security Benefit, BRFSS, Life
Expectancy.
INTRODUCTION
The global average life expectancy has increased due to advancements in medicine, technology,
and hygiene even though the actual life expectancy for individuals may vary depending on age,
sex, race, ethnicity, geographic location, etc. As a result, people worldwide likely live much
longer and enjoy better health than their earlier generations. According to the study (Cheng et
al., 2020), an aging population is the most dominant global demographic trend, and most
countries are experiencing growth in both the size and the share of older people in their
population. In the United States, the average life expectancy at birth for males (females) had
increased from 74.1 (79.3) years in 2000 to 76.3 (81.4) years in 2019 (National Center for Health
Statistics, 2023). Also, the average life expectancy at age 65 has grown. The aging population
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Son, C. H. (2024). The Effects of Increasing the Full Retirement Age from 66 to 67 on the Retirement Decision at the Early Retirement Age of 62.
Archives of Business Research, 12(4). 18-37.
URL: http://doi.org/10.14738/abr.124.16774
corresponds with the increasing proportion of older people living in retirement (Horner and
Cullen, 2016; Romig, 2023). These increases in longevity and living in retirement contribute to
increases in lifetime Social Security benefits for retirees. Thus, this demographic shift has led
to concerns about the financial stability of Social Security systems. In the United States, Social
Security is facing a long-term financing problem. It is projected that the Social Security program
will only be able to pay the benefits on time until 2037 (Social Security Administration, 2010).
Several developed countries have raised the age at which individuals are eligible to receive
pensions, resulting in workers delaying their retirement to relieve the financial challenges
faced by social security systems. In the United States, individuals born from 1943 to 1954 have
a full retirement age of 66, but the Social Security Amendments of 1983 required a gradual
increase in the full retirement age. Hence, the full retirement age for individuals born between
1955 and 1960 is set to increase by two months each year until it reaches 67 in 2027
(Springstead, 2011). In 2017, the Social Security Administration (SSA) began to increase the full
retirement age from 66 to 67 (Table 1). Consequently, individuals born in 1960 or later receive
the full retirement benefits at age 67 and reach the early retirement age of 62 in 2022. As the
full retirement age increases, the Social Security benefits are reduced for those who claim early,
and the benefits increase relatively small for those who delay (Tables 2 and 3). The SSA predicts
that increasing the full retirement age can encourage workers to postpone their retirement
decisions and remain longer in the labor force even if the early retirement age remains 62
(Bonsang et al., 2012).
Elderly individuals rely on Social Security benefits as a form of financial security in their late
years. Hence, it is beneficial for individuals to delay claiming Social Security benefits to ensure
a higher level of consumption during their later years after they have retired (Guo et al., 2020).
However, according to their study, a substantial portion of individual workers tended to claim
their retirement benefits shortly after becoming eligible for it. They explained that the official
designations of early and full retirement ages may serve as a provision for elderly workers to
retire at these ages. Workers may also interpret these designations as advice from the
government on when to retire from work and claim their benefits (Coile et al., 2002; Behaghel
and Blau, 2012; Eibich, 2015; Hessel, 2016). In the United States, despite a substantial reduction
in Social Security benefits (Table 2), a significant portion of newly retired workers (29.14% in
2021, as per Table 4) claim their Social Security benefits as soon as they turn 62, which is the
earliest age to claim these benefits. Additionally, the second largest share of newly retired
workers (25.47% in 2021, as per Table 4) claims their Social Security benefits at age 66, which
is the full retirement age. These large spikes in retirement at the early and full retirement ages
are well-documented in the literature.
Individuals are eligible to receive Social Security benefits as early as 62 but can wait as late as
70. However, as mentioned earlier, if an individual claims these benefits before the full
retirement age, the monthly benefits are permanently reduced based on the number of months
claimed earlier (Table 2). Before reaching the full retirement age, there is a monthly reduction
rate of five-ninths of 1% for each of the 36 months. It equals a 62⁄3% reduction each year. For
each month earlier than 36 months (3 years) before the full retirement age, the monthly
reduction rate is five-twelfths of 1%, equivalent to a 5% reduction each year (Li, 2022). For
instance, if the full retirement age is increased from 66 to 67 while the early retirement age
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remains at 62, then the monthly benefit reduction at age 62 would increase from 25% to 30%.
Also, the delayed benefit credit at age 70 would decrease from 32% to 24%
Table 1: Age to Receive Full Social Security Benefits
Year of Birth Full Retirement Age
(FRA)
Year the individual
Attains Age 62
Year the Individual Attains Full
Retirement Age
1943-1954 66 2005-2016 2009-2020
1955 66 and 2 months 2017 2021 or 2022
1956 66 and 4 months 2018 2022 or 2023
1957 66 and 6 months 2019 2023 or 2024
1958 66 and 8 months 2020 2024 or 2025
1959 66 and 10 months 2021 2025 or 2026
1960 or later 67 2022 or later 2027 or later
Source: Social Security Administration, Annual Statistical Supplement to the Social Security Bulletin, 2022.
https://www.ssa.gov/policy/docs /statcomps/supplement/. Note: Persons born on January 1 of any year should
refer to the previous year of birth.
Table 2: Full Retirement Age (FRA) and Maximum Reduction of Retired-Worker
Benefits, by Year of Birth
Year of
Birth
Year the
individual
Attains Age 62
Full Retirement
Age
Year the Individual
Attains FRA
Maximum
Reduction
Months
Maximum
Reduction at age
62
1943-1954 2005-2016 66 2009-2020 48 25.00%
1955 2017 66 and 2 months 2021 or 2022 50 25.83%
1956 2018 66 and 4 months 2022 or 2023 52 26.67%
1957 2019 66 and 6 months 2023 or 2024 54 27.50%
1958 2020 66 and 8 months 2024 or 2025 56 28.33%
1959 2021 66 and 10 months 2025 or 2026 58 29.17%
1960 or
later
2022 or later 67 2027 or later 60 30.00%
Source: Social Security Administration, Annual Statistical Supplement to the Social Security Bulletin, 2022.
https://www.ssa.gov/policy/docs /statcomps/supplement/. Table 2.A17.1. Note: Persons born on January 1 of
any year should refer to the previous year of birth. For each of the 36 months immediately preceding the FRA,
the monthly rate of reduction from the full retirement benefit is five-ninths of 1%. This equals a 6 2/3%
reduction each year. For each month earlier than three years (36 months) before the FRA, the monthly rate of
reduction is five-twelfths of of 1%. This equals a 5% reduction each year. The earliest a worker can claim
retirement benefits is age 62. For a worker with an FRA of 67, claiming benefits at 62 results in a 30% reduction
in their monthly benefit.
Table 3: Benefit Increase for Delayed Retirement by Birth Year
Year of
Birth
Full Retirement
Age
Year the
Individual
Attains FRA
Monthly
Credit
Annual
Credit
Maximum
Credit
Months
Total Credit
at Age 70+
1943-1954 66 2009-2020 2/3 of 1% 8% 48 32%
1955 66 and 2 months 2021 or 2022 2/3 of 1% 8% 46 30 2/3%
1956 66 and 4 months 2022 or 2023 2/3 of 1% 8% 44 29 1/3%
1957 66 and 6 months 2023 or 2024 2/3 of 1% 8% 42 28%
1958 66 and 8 months 2024 or 2025 2/3 of 1% 8% 40 26 2/3%
1959 66 and 10
months
2025 or 2026 2/3 of 1% 8% 38 25 1/3%
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Son, C. H. (2024). The Effects of Increasing the Full Retirement Age from 66 to 67 on the Retirement Decision at the Early Retirement Age of 62.
Archives of Business Research, 12(4). 18-37.
URL: http://doi.org/10.14738/abr.124.16774
1960 or
later
67 2027 or later 2/3 of 1% 8% 36 24%
Source: Social Security Administration, Annual Statistical Supplement to the Social Security Bulletin, 2022.
https://www.ssa.gov/policy/docs /statcomps/supplement/. Table 2A.17.3. Note: Persons born on January 1 of
any year should refer to the previous year of birth.
Table 4: Distribution of Claiming Ages for Newly Retired Workers in 2021
Total Men Women
Age Number Proportion Number Proportion Number Proportion
Total 2,645,830 100.00% 1,318,462 100.00% 1,327,368 100.00%
62 770,971 29.14% 371,142 28.15% 399,829 30.12%
63 179,341 6.78% 87,359 6.63% 91,982 6.93%
64 203,634 7.70% 95,878 7.27% 107,756 8.12%
65 342,176 12.93% 169,540 12.86% 172,636 13.01%
66 673,808 25.47% 360,536 27.35% 313,272 23.60%
67 107,484 4.06% 59,051 4.48% 48,433 3.65%
68 63,232 2.39% 34,531 2.62% 28,701 2.16%
69 58,151 2.20% 30,619 2.32% 27,532 2.07%
70+ 261,433 9.88% 123,149 9.34% 138,284 10.42%
Source: Social Security Administration, Annual Statistical Supplement to the Social Security Bulletin, 2022.
https://www.ssa.gov/policy/docs /statcomps/supplement/. Table 6.A4. Note: New retired workers in 2021, in
which the full retirement age was 66 years and 10 months. This table excluded the 540,353 beneficiaries who
automatically converted from disability benefits to retirement benefits at the full retirement age. They made up
16.96% of total beneficiaries in 2021.
(Tables 2 and 3). Consequently, the increase in the full retirement age from age 66 to 67 is
equivalent to reducing the Social Security benefits for new retirees, regardless of the age at
which a worker claims the benefits.
The Social Security Administration (SSA) expects the reduction in Social Security benefits might
encourage workers to delay their retirement and stay longer in the labor force. Also, the SSA
predicts that reducing and delaying benefits due to the increase in the full retirement age can
restore some financial balance to the Social Security system. Therefore, studying the effects of
increasing the full retirement age from 66 to 67 on the likelihood of individuals delaying their
retirement decision at the early retirement age of 62 is essential for planning future social
security reforms. It is important because a significant proportion of newly retired workers in
the United States have chosen the retirement decision before or at the early retirement age of
62.
This study employs Two-Stage Least Squares (2SLS) regression analysis, utilizing cross- sectional and time-series data from the Behavioral Risk Factor Surveillance System (BRFSS)
from 2016 to 2021 for adults aged 55-74. The BRFSS is a health survey conducted
collaboratively by the Centers for Disease Control and Prevention (CDC) and all states in the
United States. The BRFSS is a monthly telephone survey designed to collect uniform data on
health-related risk behaviors, chronic diseases, health conditions, access to health care, and use
of preventive services among non-institutionalized adults in the United States. The data is state- specific to each state and relates to the leading causes of death and disability among individuals
aged 18 years or older. Section 3 presents a detailed analysis of the BRFSS data.
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ANALYTICAL FRAMEWORK
Individuals can receive Social Security retirement benefits as early as age 62. However, if they
choose to start receiving the benefits before, they reach their full retirement age, their benefits
are reduced by a small percentage each month. Currently, the full retirement age is gradually
increasing from 66 to 67 by adding two months every year, resulting in a reduction of 25% to
30% in monthly benefits if an individual claims the benefits at age 62 (Table 2). As described in
section 1, a significant portion of newly retired workers choose to retire at or before this age.
Therefore, it is crucial to investigate the likelihood of workers delaying their retirement
decisions at age 62 due to the increase in the full retirement age. The impacts of increasing the
full retirement age on older workers’ retirement decisions at age 62 are developed as follows.
R = f(d, z) (1)
The retirement status of respondents at the time of the survey interview is denoted by ‘R’. ‘d’
represents health status, socio-demographic variables (income level, marital status,
race/ethnicity, and educational achievement), and age of respondents who are 62 years old. ‘z’
is a vector of all other relevant factors that affect retirement decisions. As described earlier, if
the full retirement age increases, then workers face financial disincentives to retire at the early
retirement age of 62. If a worker expects to receive a certain amount of the monthly Social
Security benefits, the worker likely delays his/her retirement. Therefore, the probability of
retiring at the early retirement age of 62 would decrease as the full retirement age increases by
two months each year. The following is a linear probability model to estimate retirement
decisions.
Rijt = β0 + hijtβh + xijtkβk + age62tβa + sjδj + ttδt + uijt (2)
The subscript i denotes each observation. The binary variable Rijt indicates the retirement
status of an individual respondent i in state j during the interview year t. Individual workers’
health status is one of the important determinants to make a retirement decision (Horner and
Cullen, 2016; Zhu, 2016; Son, 2020). hijt represents the poor physical or mental health days of
individual i in state j at interview year t. The vector xijtk comprises personal characteristics,
including demographic variables, where k represents the number of explanatory variables, and
age62t is a binary variable and equals 1 if the respondent’s age is 62 years at interview year t.
sj is a state fixed-effect, and tt represents the interview year. β0 is a fixed non-random constant,
and βh is the coefficient of the poor health status. βk is a coefficient matrix of the personal
characteristics with a dimension k x 1, and βa is a coefficient matrix of the respondents aged 62
years with a dimension t x 1. δj is the coefficient of the individual state j, and δt represents the
coefficient of the interview year t. uijt is an error term of the ith observation in state j at year t.
It is an independent random variable with mean zero and constant standard error σu, and that
is generally assumed that Cov (rijt, uijt) = 0 and Cov (xijtk, uijt) = 0 (Mesbah, 2004; Jia and Lubetkin,
2009; Son and Lee, 2014) with expected value of uijt, E(uijt) = 0.
In the above Ordinary Least Squares (OLS) estimation, equation (2), if the poor health status
(hijt) is correlated with the error term (uijt) due to endogeneity, the OLS estimator of βh is
inconsistent. Theoretically, the poor health status (hijt) could be endogenous in equation (2)
because of omitted variables, such as unobserved individual heterogeneities (i.e., genetics, life
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Son, C. H. (2024). The Effects of Increasing the Full Retirement Age from 66 to 67 on the Retirement Decision at the Early Retirement Age of 62.
Archives of Business Research, 12(4). 18-37.
URL: http://doi.org/10.14738/abr.124.16774
history, time preference, financial stability, or unobservable health status) that could have an
impact on both retirement and health outcomes. In addition, the econometric concern, of
whether retirement is associated with health status, could result in reverse causality in the
relationship between retirement and health status in equation (2). It means that poor health
could influence people to retire early, whereas retirement could affect the retirees’ health,
leading to endogeneity (Motegi et al., 2016; Zhu, 2016; Son, 2020). As a result, the estimates of
the effects of poor health status on retirement are likely to be biased upward, overestimating
the negative effects of poor health on retirement. Therefore, the OLS regression coefficient (βh)
from equation (2) is likely inconsistent.
To account for the issues of endogeneity and potential reverse causality in equation (2), this
study utilizes the Instrumental Variable (IV) estimation method. This method is a well- established and proven approach in the literature and is relevant to the data analyzed in this
paper. Previous studies (Eibich, 2015; Godard, 2016; Hessel, 2016; Motegi et al., 2016; Zhu,
2016) have suggested that health status is a core factor affecting retirement decisions and that
instrumental variables could be used to estimate its impact. A good instrument should be
strongly correlated with poor health status, but it should not directly influence the retirement
decision. To this end, this paper uses the health behaviors of individual respondents, such as
exercise, smoking, and drinking, as the identifying instruments for poor health status in IV
estimation.
In the first stage, the health outcomes are estimated using the following equation.
hijt = β0 + hbijtβhb + xijtkβk + sjδj + ttδt + uijt (3)
The instrument used for measuring health outcomes (hijt) is hbijt, which is equal to 1 if an
individual respondent i reported participating in physical exercise, smoking, or drinking at
interview year t. The coefficient of individual state j is δj, and the coefficient of interview year t
is δt. This study replaces the poor health status (hijt) in equation (2) with the predicted value of
poor health outcomes (hijt) from equation (3). As a result, the empirical model becomes the
following.
Rijt = β0 + (predicted hijt)βh + xijtkβk + age62tβa + sjδj + ttδt + uijt (4)
In equation (4), the predicted hijt is exogenous to all observed and unobserved individual-level
characteristics. The state-fixed model controls for all time-invariant differences that remain
constant over time in the states, eliminates the impact of variations associated with other
relevant independent variables among states on the dependent variables, and accounts for the
effects of unobserved state-specific variables. For instance, according to the study (Knoll, 2011),
individuals in good health with higher socioeconomic status tend to work longer than those
who are less healthy and wealthy because financial concerns play a significant role in
retirement decisions. Hence, residents in states with different income levels exhibit distinct
behavioral aspects of retirement decisions. The year dummy variables control for the factors
that vary uniformly across the states a year.
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Table 5: Definition, Mean, and Standard Deviations of Variables
Variable Definition
Retirees Dichotomous variable that equals 1 if respondent is retired.
Poorhealth Number of days of poor physical health or mental health keep respondents from
doing their usual activities, such as self-care, work, or recreation during the past
30 days.
Income
Income 35 Respondent’s annual household income from all sources < $35,000.
Income 35-75 $35,000 ≤ respondent’s annual household income from all sources < $75,000.
Income 75+ Respondent’s annual household income from all sources ≥ $75,000.
Marital Status
Married Respondent is married or a member of an unmarried couple.
Divorced Respondent was divorced or separated.
Widowed Respondent was widowed.
Never married Respondent is never married.
Races
White, non-Hispanic Respondent is white only, non-Hispanic.
Black, non-Hispanic Respondent is black only, non-Hispanic.
Hispanic Respondent is Hispanic.
Others, non- Hispanic
Respondent is other race, non-white, non-black, and non-Hispanic.
Education
Less high school Respondent did not graduate high school
High school Respondent completed grade 12 or GED (high school graduate).
Some college Respondent completed college 1 year to 3 years (some college or technical
school).
College graduation Respondent completed college 4 years or more (college graduate).
Health behaviors
Exercise Dichotomous variable that equals 1 if respondent participates in any physical
activities or exercises such as running, calisthenics, golf, gardening, or walking for
exercise during the past month.
Current smoker Dichotomous variable that equals 1 if respondent now smokes cigarettes every
day or some days.
Current drinker Dichotomous variable that equals 1 if respondent had at least one drink of
alcohol in the past 30 days.
Age variables
Age62y2016 Respondent aged 62 years in 2016.
Age62y2017 Respondent aged 62 years in 2017.
Age62y2018 Respondent aged 62 years in 2018.
Age62y2019 Respondent aged 62 years in 2019.
Age62y2020 Respondent aged 62 years in 2020.
Age62y2021 Respondent aged 62 years in 2021.
Ageunder62y2016 Respondent aged 62 years or under in 2016.
Ageunder62y2017 Respondent aged 62 years or under in 2017.
Ageunder62y2018 Respondent aged 62 years or under in 2018.
Ageunder62y2019 Respondent aged 62 years or under in 2019.
Ageunder62y2020 Respondent aged 62 years or under in 2020.
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Son, C. H. (2024). The Effects of Increasing the Full Retirement Age from 66 to 67 on the Retirement Decision at the Early Retirement Age of 62.
Archives of Business Research, 12(4). 18-37.
URL: http://doi.org/10.14738/abr.124.16774
Ageunder62y2021 Respondent aged 62 years or under in 2021.
Source: 2016-2021 Behavioral Risk Factor Surveillance System (BRFSS) at https://www.cdc.gov/brfss/. Notes:
One drink is equivalent to a 12-ounce beer, a 5-ounce glass of wine, or a drink with one shot of liquor.
EMPIRICAL IMPLEMENTATION
The data used in the analysis was obtained from the Behavioral Risk Factor Surveillance System
(BRFSS) from 2016-2021, a nationwide health survey. The BRFSS is a uniform, state-specific
system of ongoing health-related telephone surveys. It collects data on health-related risk
behaviors, chronic diseases, health conditions, access to healthcare, and the use of preventive
services for non-institutionalized adults aged 18 or older residing in the United States. The
BRFSS is a collaborated project by the Center for Disease and Prevention (CDC) and all states in
the United States. The state health department manages the BRFSS operations and conducts the
interviews themselves or uses contractors. During the survey development, state health
departments collaborate with the CDC and follow guidelines provided by the states, with
technical assistance from the CDC. The BRFSS data is used by state health departments for
various purposes, including identifying demographic variations in health-related behaviors,
designing, implementing, and evaluating public health programs, addressing emergent and
critical health issues, proposing legislation for health initiatives, and measuring progress
toward state health objectives. This study uses the BRFSS data for adults aged 55-74 across all
50 states and Washington D.C. However, observations with missing values, unanswered
questions, don’t know/not sure responses, questions not asked, or refusals were excluded. Out
of the 2,145,061 observations, only 405,031 survey participants (18.88%) completed all the
questions about retirement status, physical or mental health status, socio-demographic
variables, and health behavior variables. The observations were analyzed separately in male
and female subgroups to study retirement decisions. Tables 5 and 6 contain descriptions and
summary statistics.
Table 6: Descriptive Statistics
Variable Overall (n = 405,031) Male (n = 163,685) Female (n = 241,346)
Retirees 0.359 (0.480) 0.364 (0.481) 0.356 (0.479)
Poor health 6.450 (10.222) 6.690 (10.516) 6.270 (9.983)
Income
Income 35 0.416 (0.493) 0.402 (0.490) 0.427 (0.495)
Income 35-75 0.290 (0.454) 0.2857 (0.452) 0.293 (0.455)
Income 75+ 0.294 (0.456) 0.312 (0.463) 0.280 (0.449)
Marital Status
Married 0.589 (0.492) 0.632 (0.482) 0.555 (0.497)
Divorced 0.219 (0.413) 0.209 (0.407) 0.226 (0.418)
Widowed 0.107 (0.308) 0.060 (0.238) 0.143 (0.350)
Never married 0.086 (0.280) 0.099 (0.298) 0.076 (0.265)
Races
White, non-Hispanic 0.736 (0.441) 0.728 (0.445) 0.743 (0.437)
Black, non-Hispanic 0.111 (0.314) 0.111 (0.314) 0.111 (0.315)
Hispanic 0.095 (0.293) 0.101 (0.301) 0.091 (0.287)
Others, non-Hispanic 0.058 (0.233) 0.061 (0.238) 0.055 (0.228)
Education
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Less high school 0.129 (0.335) 0.146 (0.353) 0.115 (0.319)
High school 0.272 (0.445) 0.280 (0.449) 0.267 (0.442)
Some college 0.333 (0.471) 0.311 (0.463) 0.351 (0.477)
College graduation 0.266 (0.442) 0.263 (0.441) 0.268 (0.443)
Health behaviors
Exercise 0.666 (0.472) 0.681 (0.466) 0.654 (0.476)
Current smoker 0.179 (0.384) 0.197 (0.398) 0.166 (0.372)
Current drinker 0.473 (0.499) 0.523 (0.450) 0.434 (0.496)
Age variables
Age62y2016 0.011 (0.105) 0.012 (0.108) 0.011 (0.102)
Age62y2017 0.011 (0.102) 0.010 (0.101) 0.011 (0.103)
Age62y2018 0.011 (0.103) 0.011 (0.104) 0.011 (0.102)
Age62y2019 0.012 (0.108) 0.012 (0.110) 0.012 (0.107)
Age62y2020 0.010 (0.099) 0.010 (0.099) 0.010 (0.100)
Age62y2021 0.010 (0.100) 0.010 (0.101) 0.010 (0.100)
Ageunder62y2016 0.082 (0.275) 0.086 (0.281) 0.079 (0.270
Ageunder62y2017 0.085 (0.279) 0.086 (0.280) 0.085 (0.278)
Ageunder62y2018 0.084 (0.278) 0.088 (0.284) 0.081 (0.273)
Ageunder62y2019 0.085 (0.279) 0.083 (0.277) 0.086 (0.281)
Ageunder62y2020 0.077 (0.266) 0.075 (0.263) 0.078 (0.268)
Ageunder62y2021 0.073 (0.261) 0.072 (0.259) 0.074 (0.262)
Notes: Percentages are calculated with the BRFSS sample weight factor. All percentages are statistically
significant using two tailed t-test with 95% confidence interval (CI).
Retirement Status
The retirement decision is one of the most crucial decisions an individual makes in their lifetime
because it can significantly impact their well-being for years to come, especially given the
increase in life expectancy. Retirement decisions are highly personal and consider health and
financial factors due to the significant loss of income (Knoll, 2011). Thus, most individuals
consider the eligible age for Social Security benefits when deciding whether to retire or not
since it has a significant impact on their financial situation. In this study, the retirement status
of the survey respondents was self-reported in the employment status section of the BRFSS
demographic data. The survey asked respondents about eight categories of employment status:
employed for wages, self-employed, out of work for one year or more, out of work less than one
year, a homemaker, a student, retired, and unable to work. Respondents were classified as
retired if they reported being retired at the interview. 36.40% of male respondents and 35.60%
of female respondents reported being retired (Table 6).
Explanatory Variables
Poor health status, socio-demographic variables (income level, marital status, race/ethnicity,
and education level), health behavioral variables (exercise, current smoker, and current
drinker), and year-age-related variables are independent variables.
Health Status:
A study conducted in 2016 by Leinonen et al. found that health was the primary concern for
individuals when deciding to retire, particularly in the case of early retirement. The present
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Son, C. H. (2024). The Effects of Increasing the Full Retirement Age from 66 to 67 on the Retirement Decision at the Early Retirement Age of 62.
Archives of Business Research, 12(4). 18-37.
URL: http://doi.org/10.14738/abr.124.16774
study drew information about physical and mental health from the health-days section of the
BRFSS. The survey included questions about the number of days in the last 30 days when
respondents experienced poor physical health, including physical illness and injury, and poor
mental health, which encompassed stress, depression, and emotional problems. The survey
then inquired about the number of days during the previous month when poor physical or
mental health prevented individuals from performing their regular activities, such as self-care,
work, or recreation. Participants reported the number of poor healthy days ranging from 0 to
30 days, with 30 days being the logical maximum per month. The average poor health days for
overalls, males, and females were 6.45, 6.69, and 6.27 days, respectively, in the last 30 days.
Socio-demographic Variables:
The study conducted by Gough et al. in 2008 analyzed the relationship between income and
retirement decisions in the UK and Italy from 1992 to 2002. They revealed that income was a
strong predictor of retirement decisions. Their results showed that people from high-income
groups in both countries tended to retire earlier, while those from low-income groups retired
later. The BRFSS asked participants about their annual household income from all sources,
ranging from less than $10,000 to $75,000 or more (2016 BRFSS – 2020 BRFSS) and from less
than $10,000 to $200,000 or more (2021 BRFSS). This study re-categorized the income levels
into three groups: less than $35,000, $35,000 to less than $75,000, and $75,000 or over. In the
income category, 41.60% of respondents reported an annual household income of less than
$35,000, 29.00% reported an income of $35,000 to less than $75,000, and 29.40% reported an
annual household income of $75,000 or more. The proportion of male respondents reporting a
household income of $75,000 or over was higher than the proportion of female respondents
reporting the same income level, as shown in Table 6.
The female labor force participation rate has significantly increased in recent decades, leading
to changes in retirement planning for couples (Boehnke and Gay, 2022). In the past, couples
typically focused on the husband’s retirement benefits, and his retirement decision would
impact the couple’s future benefits as a single decision unit. However, with women at present
accumulating substantial benefits in their names, retirement decisions have become more
challenging to coordinate. More than two-thirds of individuals of retirement age live as couples,
and the majority of the couples are dual-earners. As a result, many couples now need to
consider the impact of one spouse stopping work on both income and retirement benefits.
According to a study (Stancanelli, 2017), couples tend to retire at similar time, within a year of
each other. Since husbands are generally older than their wives, the increased female labor
force participation may lead to later retirement for men. Therefore, marital status would be an
important factor in an individual’s retirement decision. In the BRFSS, survey participants are
asked about six categories of marital status: married, divorced, widowed, separated, never
married, and a member of an unmarried couple. They are then classified into four marital
subgroups: married (married or a member of an unmarried couple), divorced (divorced or
separated), widowed, and never married. After regrouping, 58.9%, 21.9%, 10.7%, and 8.6% of
survey participants are married, divorced, widowed, and never married, respectively. The
proportion of married respondents is higher among males than among females, whereas the
proportion of widowed respondents is significantly lower among males than among females
(Table 6).
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According to a study conducted by Francis and Weller in 2021, there are disparities in
retirement security among households of different races and ethnicities. These disparities arise
due to factors, such as market discrimination, occupational segregation, and lower wages,
which lead to limited access to retirement savings and contributions. Furthermore, households
belonging to ethnic minorities have fewer chances of receiving intergenerational wealth
transfers, which could help alleviate debt burdens and enable access to education and
homeownership. These pathways are crucial for building wealth and retirement savings. This
study uses two questions from the BRFSS to determine race/ethnicity: “Which one of these
groups would you say best represents your race? (With seven response choices)” and “Are you
Hispanic or Latino? (yes/no)”. The BRFSS’s ‘calculated race variables’ section listed five
categories of race/ethnicity, which this study reduces to four: White, non-Hispanic; Black, non- Hispanic; Hispanic; and others (multi-racial or other race, non-Hispanic).
A study conducted by Venti and Wise in 2015 found that both men and women with less than a
high school degree were more likely to participate in Social Security Disability Insurance and
to claim Social Security benefits at an early age. In contrast, individuals with a college degree or
higher were less likely to rely on these benefits. In this study, the respondents are classified into
four levels of educational attainment: less than high school graduation, high school graduation,
attended some college or technical school, and four-year college graduation or more. 12.9%
have completed less than high school. In contrast, 27.2% have completed high school, 33.3%
attended some college, and 26.6% completed a four-year college degree or higher (Table 6).
Health Behavioral Variables:
It is well known that health behaviors are strongly associated with health outcomes. In the first
stage of the 2SLS regression model, three health behavioral factors (exercise, smoking, and
drinking) are independent variables. Exercise was defined as participating in any physical
activities or exercises other than job-related regular activities during the past month, including
running, calisthenics, golf, gardening, or walking for exercise. 66.6% of survey respondents
reported participating in such activities. Smoking was defined as those who smoked cigarettes
every day or some days. 17.9% of the respondents reported being current smokers. Drinking
was defined as a respondent who had at least one drink of alcohol in the past 30 days. One drink
was equivalent to a 12-ounce beer, a 5-ounce glass of wine, or a drink with one shot of liquor.
47.3% of the respondents reported being current drinkers.
Year-Age Group Variables:
During the survey, the participants were asked about their age, and the response was recorded
as a continuous variable. Two age-year variables were used in the empirical models: one for the
respondents who were 62 years old and the other for those who were 62 years old or younger.
ANALYSIS AND RESULTS
Descriptive Analysis
Table 6 presents descriptive statistics for the overall observations as well as for men and
women separately. The survey participants reported an average of 6.45 poor health days over
the past 30 days, taking into account the BRFSS sampling weighting factor. Interestingly, men
reported slightly more poor health days than women on average. Regarding annual household
income, 31.2% of male respondents reported an income of $75,000 or more, while 28.0% of
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Son, C. H. (2024). The Effects of Increasing the Full Retirement Age from 66 to 67 on the Retirement Decision at the Early Retirement Age of 62.
Archives of Business Research, 12(4). 18-37.
URL: http://doi.org/10.14738/abr.124.16774
female respondents reported the same income level. The table shows that 63.2% of male
respondents were married, compared with 55.5% of female respondents. Of those not married,
6% of male respondents were widowed, whereas 14.3% of female respondents were widowed.
Educational attainment did not show any significant gender differences. Finally, a high
proportion of male respondents engaged in all three health behaviors compared with female
respondents: exercise (68.1% vs. 65.4%), smoking (19.7% vs. 16.6%), and drinking (52.3% vs.
43.4%).
Table 7 displays the percentage of retirees among survey respondents who are 62 years old, 62
years old or under, 66 years old, and 66 years old or under. The table shows that the
proportions of retirees, who are 62 years old, for males and females are similar. However, for
all other age groups, the proportions of retirees among males are higher than the fractions of
retirees among females. In other words, males are more likely than females to retire at ages 62
or under, 66 years old, and 66 years old or under. It implies that females tend to stay in the
labor force longer than males. Regarding the overall observations, the descriptive analysis
demonstrates that the direction of the proportions of retirees for each age group from 2016 to
2021 is unclear. It means that the impact of the increases in the full retirement age on delaying
retirement decisions is ambiguous based on descriptive analysis.
Table 7: Proportion of Retirees in Age Group Each Year
Overall Male Female
Aged 62 years
2016 0.250 (0.433) 0.267 (0.442) 0.234 (0.424)
2017 0.270 (0.444) 0.261 (0.439) 0.276 (0.447)
2018 0.242 (0.429) 0.266 (0.442) 0.223 (0.416)
2019 0.231 (0.421) 0.251 (0.434) 0.213 (0.410)
2020 0.215 (0.411) 0.211 (0.408) 0.219 (0.413)
2021 0.233 (0.423) 0.209 (0.407) 0.252 (0.434)
Aged 62 years or under
2016 0.122 (0.328) 0.134 (0.340) 0.113 (0.317)
2017 0.122 (0.327) 0.126 (0.332) 0.119 (0.324)
2018 0.124 (0.330) 0.132 (0.338) 0.118 (0.323)
2019 0.120 (0.325) 0.130 (0.336) 0.112 (0.315)
2020 0.122 (0.327) 0.140 (0.347) 0.108 (0.310)
2021 0.116 (0.320) 0.112 (0.316) 0.118 (0.323)
Aged 66 years
2016 0.577 (0.494) 0.558 (0.497) 0.593 (0.491)
2017 0.537 (0.499) 0.588 (0.492) 0.499 (0.500)
2018 0.563 (0.496) 0.606 (0.489) 0.528 (0.499)
2019 0.579 (0.494) 0.584 (0.493) 0.574 (0.495)
2020 0.599 (0.490) 0.603 (0.489) 0.596 (0.491)
2021 0.527 (0.499) 0.519 (0.500) 0.533 (0.499)
Aged 66 years or under
2016 0.214 (0.410) 0.220 (0.414) 0.209 (0.406)
2017 0.206 (0.404) 0.212 (0.409) 0.200 (0.400)
2018 0.213 (0.409) 0.223 (0.416) 0.205 (0.404)
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2019 0.206 (0.404) 0.216 (0.411) 0.199 (0.399)
2020 0.215 (0.411) 0.225 (0.417) 0.208 (0.406)
2021 0.200 (0.400) 0.194 (0.396) 0.204 (0.403)
Notes: Percentages are calculated with the BRFSS sample weight factor. All percentages are statistically
significant using two tailed t-test with 95% confidence interval (CI).
Second Stage Regression Results
Table 8 presents the empirical results obtained from the 2SLS regression analysis with respect
to the probability of retirement for adults aged between 55 and 74. The empirical models
include poor health status, socio-demographic variables, age variables, state-fixed effects, and
year-fixed effects. The t-statistics, shown in the parenthesis for each coefficient, indicate that
all estimated coefficients are statistically significant at a 95 percent confidence interval for the
two-tailed test. The last row of the table displays the R-squared values, which indicate the
overall model fit, i.e., how well the estimated equation explains the observations in the sample.
Since the core determinants of retirement decisions, such as job characteristics, retirement
preferences, social participation, functional limitation, etc. (Venti and Wise, 2015; Boehnke and
Gay, 2022; Oduro et al., 2023) are absent in the models, lower R-squared values are expected.
The R-squared values, ranging from 0.047 to 0.261, are relatively low, suggesting that the
regression models are not a good fit for the data based on conventional regression analysis.
However, this study primarily focused on examining the retirement decisions for retirement- aged adults at the early retirement age of 62 due to the increase in full retirement age rather
than investigating the impact of the key factors on retirement decisions.
Poor Health:
Individual workers who have experienced poor health throughout their lifetime may retire
earlier or later than their plan. If the workers anticipate declines in expected annual earnings,
they might pursue early retirement. Conversely, if they expect an increase in expected income,
they might decide to stay longer in the labor market and retire later to compensate for their
past loss of earnings.
A systematic review conducted by Homaie Rad et al. in 2017 examined the effects of poor health
on early retirement. Their results showed a strong association between poor health and early
retirement, indicating that poor health increased the likelihood of early retirement. However,
from the results of the 2SLS regression analysis in Table 8, the signs of the estimated coefficients
for poor health are negative. It implies that poor health lowers the likelihood of reporting being
retired at the time of the interview. Although the magnitude of the effects is small, with the
estimated coefficients ranging from -0.009 to -0.01, the adverse effects remain consistent
across six empirical models.
Table 8: Second Stage Regression Results for Retirement Decision
Overall Male Female
Poorhealth -0.010
(-30.195)
-0.009
(-31.618)
-0.009
(-17.475)
-0.009
(-19.029)
-0.010
(-23.276)
-0.009
(-24.256)
Income
Income 35 - - - - - -
Income 35-75 -0.019
(-8.436)
-0.014
(-6.901)
-0.014
(-3.751)
-0.014
(-4.377)
-0.022
(-7.687)
-0.015
(-5.874)
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Son, C. H. (2024). The Effects of Increasing the Full Retirement Age from 66 to 67 on the Retirement Decision at the Early Retirement Age of 62.
Archives of Business Research, 12(4). 18-37.
URL: http://doi.org/10.14738/abr.124.16774
Income 75+ -0.187
(-68.159)
-0.115
(-47.443)
-0.213
(-48.363)
-0.145
(-37.051)
-0.167
(-47.558)
-0.093
(-30.047)
Marital Status
Married - - - - - -
Divorced -0.071
(-35.036)
-0.049
(-27.323)
-0.072
(-22.637)
-0.038
(-13.556)
-0.069
(-25.805)
-0.057
(-24.226)
Widowed 0.102
(41.118)
0.030
(13.619)
0.115
(23.896)
0.056
(13.050)
0.110
(37.284)
0.028
(10.743)
Never married -0.101
(-35.819)
-0.043
(-17.303)
-0.129
(-30.988)
-0.055
(-14.825)
-0.081
(-20.944)
-0.039
(-11.355)
Races
White, non-Hispanic - - - - - -
Black, non-Hispanic -0.038
(-12.476)
-0.015
(-5.556)
-0.038
(-7.708)
-0.016
(-3.699)
-0.037
(-9.714)
-0.013
(-3.898)
Hispanic -0.110
(-27.507)
-0.055
(-15.576)
-0.107
(-17.295)
-0.054
(-9.754)
-0.113
(-21.406)
-0.056
(-12.063)
Others, non- Hispanic
-0.060
(-17.398)
-0.027
(-8.893)
-0.054
(-10.314)
-0.022
(-4.804)
-0.069
(-15.005)
-0.034
(-8.347)
Education
Less high school - - - - - -
High school 0.077
(22.568)
0.067
(22.393)
0.061
(11.978)
0.053
(11.750)
0.096
(20.949)
0.085
(21.126)
Some college 0.117
(34.394)
0.088
(29.404)
0.115
(22.311)
0.074
(16.102)
0.130
(28.598)
0.110
(27.369))
College graduation 0.159
(44.827)
0.107
(34.187)
0.151
(28.062)
0.079
(16.538)
0.177
(37.209)
0.138
(33.101)
Age variables
Age62y2016 -0.132
(-18.305)
-0.135
(-11.777)
-0.131
(-14.041)
Age62y2017 -0.140
(-18.657)
-0.152
(-12.717)
-0.133
(-13.712)
Age62y2018 -0.152
(-19.493)
-0.138
(-11.525)
-0.162
(-15.810)
Age62y2019 -0.159
(-20.191)
-0.158
(-13.080
-0.160
(-15.453)
Age62y2020 -0.159
(-18.304)
-0.145
(-10.745)
-0.169
(-14.882)
Age62y2021 -0.165
(-19.603)
-0.183
(-13.957)
-0.153
(-13.906)
Ageunder62y2016 -0.462
(-150.292)
-0.468
(-95.132)
-0.461
(-116.983)
Ageunder62y2017 -0.462
(-145.760)
-0.457
(-90.750)
-0.466
(-114.655)
Ageunder62y2018 -0.468
(-143.983)
-0.464
(-91.552)
-0.473
(-111.619)
Ageunder62y2019 -0.470
(-141.235)
-0.459
(-88.253)
-0.479
(-110.675)
Ageunder62y2020 -0.473
(-131.476)
-0.458
(-80.268)
-0.483
(-104.584)
Ageunder62y2021 -0.481
(-137.826)
-0.469
(-85.635)
-0.491
(-108.383)
Year dummy yes yes yes yes yes Yes
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State dummy yes yes yes yes yes Yes
R-square 0.048 0.257 0.052 0.254 0.047 0.261
F-statistics 278.089 1916.878 122.716 764.389 164.009 1168.035
Observation 405,031 405,031 163,685 163,685 241,346 241,346
Notes: The t-statistics are in parentheses. All estimated coefficients are statistically significant at 95 percent level
of confidence except.
Demographic Variables:
Three levels of annual household income are in the empirical models, with an annual household
income of less than $35,000 serving as the reference for the models. The estimated coefficients
of the two other income levels, higher than $35,000, have negative signs and larger magnitudes
as the income level increases. It suggests that high-earning individuals likely stay in the labor
force longer and delay retirement. Especially respondents with an annual household income of
$75,000 or more are 18.7% less likely to report being retired than those with an annual
household income of less than $35,000. For men, the probability gap is even wider. Based on
the results, male respondents with an annual household income of $75,000 or more are 21.3%
less likely to report being retired than those with an annual household income of less than
$35,000.
The study (Whitaker and Bokemeier, 2018) examined the expected retirement age in the
United States due to demographic changes, such as an increase in life expectancy, a decline in
fertility rates, and decreased marriage rates. They explained that these changes have resulted
in the elderly population being more likely to spend a significant portion of their retirement
alone. The research found that the expected retirement age was significantly associated with
personal and family characteristics, especially marital status. In this study, the regression
results in Table 8 demonstrate that divorced or never married respondents, both men and
women, are less likely to be retired at the interview, whereas widowed respondents are more
likely to be retired than married respondents. However, the average age for the marital
category may bring in these results if age is positively associated with retirement. Based on the
estimated coefficients, respondents in higher average age categories of marital status (married:
62.23 years; divorced: 62.86 years; widowed: 65.91 years; and never married: 61.72 years) are
more likely to be retired at the interview. Especially the average age for widowed respondents
is 2.5 years higher than the average age for married respondents.
In a recent study conducted by Kim et al. in 2021, racial and ethnic differences in retirement
resources could be attributed to holding a retirement savings account. The study identified
homeownership, objective financial knowledge, planning horizon, and age as the main factors
that explained these differences. Their results showed that White respondents were more likely
to hold a retirement savings account compared with other racial and ethnic groups. It suggests
that racial disparities in retirement savings likely exist in the United States, affecting retirement
decisions. The estimated probabilities from the 2SLS regression analysis in Table 8 indicate that
White respondents are more likely to report being retired compared with other races, while
Hispanic respondents are the least likely to report being retired.
According to a study conducted by Hardy in 1984, the impact of education on occupational
status, career-entry position, and subsequent locations within the occupational structure was
significant. The study reported that workers with higher levels of education were more likely
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Son, C. H. (2024). The Effects of Increasing the Full Retirement Age from 66 to 67 on the Retirement Decision at the Early Retirement Age of 62.
Archives of Business Research, 12(4). 18-37.
URL: http://doi.org/10.14738/abr.124.16774
to delay retirement compared with those with lower levels of educational achievement.
Similarly, the empirical results of this study explain a negative correlation between education
achievement and retirement, meaning that an increase in education achievement leads to a
decrease in the probability of being retired. The average ages of respondents across different
education levels are similar (not shown in tables - less high school: 63.09 years; high school:
63.20 years; some college: 63.42 years; college graduation: 63.39 years).
Age-Year Variables:
This study investigates the retirement decision based on two age groups: respondents aged 62
years and respondents aged 62 years or under, as the full retirement age increases. The results
of the empirical analysis for respondents aged 62 years are presented in the first column of
Table 8. The probability of reporting being retired at age 62 decreased from 2016 to 2021,
indicating that individuals were choosing to delay retirement at age 62 as the full retirement
age increases. For overall observations, the probability of reporting themselves as retired for
respondents aged 62 years in 2016 is 0.132 less than the probability for other aged respondents
and 0.165 less than in 2021. For men aged 62 years, the estimated coefficient of the likelihood
of reporting being retired in 2016 is -0.135, and in 2021 it is -0.183. It implies that the likelihood
of reporting being retired decreased by 35.56% during the period. For women, the estimated
coefficient of the probability of reporting being retired in 2016 is -0.131, and in 2021 it is -
0.153. It explains the probability dropped by 16.79%. If both male and female workers exit from
the labor force only based on the Social Security benefits, the effects of the increase in full
retirement age on delaying retirement decisions for males appear to be greater than the effects
for females. These results suggest that the decline in the monetary value of Social Security
benefits due to the increase in the full retirement age can discourage individuals from retiring
at 62.
Table 8 also presents the estimated probabilities of being retired at the interview for
respondents aged 62 years or under in the second column. Signs of all estimated coefficients
are negatives, and the magnitude of these coefficients increases each year from 2016 to 2021.
It implies a gradual decline in the probability of reporting being retired at 62 or under since the
full retirement age increased by two months each year. For men, the estimated coefficient of
the likelihood of reporting being retired for this age category in 2016 is -0.462, and in 2021 it
is -0.481. The results also show no clear trend of changing the probability for men from 2016
to 2021, whereas the estimated coefficients for women consistently increase as the year passes.
DISCUSSION
In the United States, individuals born from 1943 to 1954 have a full retirement age of 66.
However, the Social Security Amendments of 1983 mandates a gradual increase in the full
retirement age. Currently, the full retirement age for individuals born from 1955 to 1960
increases by two-month increments each year until it reaches 67 years of age in 2027
(Springstead, 2011). Individuals are eligible for Social Security benefits anytime as early as 62
or as late as 70, with unreduced benefits available at the full retirement age. If an individual
files for Social Security benefits before reaching the full retirement age, the individual will
receive a permanently reduced monthly benefit based on the number of months claimed before
the full retirement age (Table 2). As a result, the increase in the full retirement age is equivalent
to a decline in the Social Security benefits for all new retirees. The Social Security
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Administration predicts that reducing Social Security benefits can encourage workers to
postpone their retirement and stay longer in the labor force. These could help to restore some
financial balance to the Social Security system. Therefore, studying the effects of increasing the
full retirement age from 66 to 67 on retirement decisions at 62 becomes essential for planning
future social security reforms. That is important because a significant proportion of workers
tend to exit the labor force at the age or even earlier.
This study conducts a Two-Stage Least Squares (2SLS) regression analysis to investigate the
likelihood of retirement for adults aged 62 years and adults aged 62 years or under, using cross- sectional and time-series data from 2016 to 2021. The full retirement age increases by two
months each year, beginning in 2017. Hence, Social Security benefits would be reduced by a
certain amount for individuals who claim the benefits at 62 after 2016. The empirical results
show that the probability of retirement for individuals at age 62 decreased from 2016 to 2021,
suggesting a trend of delaying retirement. During the same period, the likelihood of men
reporting being retired decreases by 35.56%, while for women, it drops by 16.79%. It indicates
that if male and female workers choose to exit the labor force solely based on the Social Security
benefits, the increase in full retirement age appears to have a more significant impact on
delaying retirement decisions for male workers than for female workers. The additional
findings regarding retirement decisions for adults aged 62 or under yield similar. In summary,
the empirical outcomes demonstrate that the decrease in the monetary value of Social Security
benefits due to the increase in the full retirement age can discourage individuals from retiring
at age 62 as well as age 62 or under.
It has been well documented that there are large spikes in retirement rates at both the early
and full retirement ages. Studies show that social security financial incentives have a significant
impact on these spikes, particularly at the age of 62 (Behaghel and Blau, 2012; Bonsang et al.,
2012; Eibich, 2015; Hessel, 2016). Similarly, in the United States, despite a large reduction in
Social Security benefits (Table 2), a significant proportion of newly retired workers (29.14% in
2021, as per Table 4) claim their Social Security benefits as soon as they turn 62, which is the
earliest age to claim these benefits. Remarkably, the empirical findings reveal that workers tend
to delay their retirement at 62 since the full retirement age started to increase. It appears that
the current social security reform has effectively achieved the goal of delaying individuals’
retirement decisions. Reducing benefits and delaying retirement-aged workers from claiming
benefits can provide financial respite to the Social Security program. Thus, given the current
trend of increasing life expectancy and Social Security imbalance, there may be proposals for
Social Security reforms to make further raise the retirement age.
The following are the reasonable supports for increasing the retirement age. First, recent
decades have seen an increase in the average life expectancy, implying that people can work up
until an older age. Second, older workers are now in better health conditions, which mean they
can continue working even at an older age. Third, the job characteristics in many industries
have become more suitable for older workers. However, there are concerns regarding the
increase in the retirement age due to differences in life expectancy among different
socioeconomic groups (Singh and Lee, 2021). Additionally, improvements in health status, job
characteristics, and an increase in life expectancy may not be equally distributed among
individuals with different attributes, such as sex, race, educational attainment, or income level.
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Son, C. H. (2024). The Effects of Increasing the Full Retirement Age from 66 to 67 on the Retirement Decision at the Early Retirement Age of 62.
Archives of Business Research, 12(4). 18-37.
URL: http://doi.org/10.14738/abr.124.16774
Furthermore, workers with health problems may be encouraged to apply for Social Security
disability benefits, leading to higher enrollment and costs for the program. Lastly, older
workers may become more vulnerable to the risk of unemployment as they would no longer be
eligible for Social Security retirement benefits.
References
Behaghel, Luc and Blau, David M. (2012). Framing social security reform: behavioral responses to changes in the
full retirement age. American Economic Journal: Economic Policy, Vol. 4 (4), pp. 41-67.
http://dx.doi.org/10.1257/pol.4.4.41.
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