It is our pleasure to take the
lead this year in planning the 9th Annual Conference of the Social
Security Retirement Research Consortium. This issue of the newsletter
contains the current version of the agenda. Topics will address
challenges and potential solutions to providing financial security in
retirement. Utilizing a model that has been highly successful in past
years, we will have presentations, discussion, and audience question and
We are delighted to welcome Andrew Biggs and Sylvester Schieber as guest
speakers on the first and second days, respectively. As noted
previously, Andrew Biggs now serves as the Deputy Commissioner of Social
Security. Sylvester Schieber was appointed last fall to the Chairmanship
of the Social Security Advisory Board. The RRC conference always affords
stimulating presentations and lively discussion. We look forward to
seeing you there.
Your Calendar for the 9th Annual Meeting of the Retirement Research Consortium
August 9-10, 2007 at the National Press Club, Washington, D.C.
Information about this conference,
including registration information, will be provided and updated as needed
on the MRRC website: www.mrrc.isr.umich.edu.
The conference is being organized by the MRRC in cooperation
with the Retirement Research Center of NBER , the CRR and the SSA Office
FYI: Answers to Frequently Asked Questions about
As American workers prepare for retirement, it is
important for them to have information about the future of Social
Security. In response to many inquiries on this topic, the Social
Security Administration has created a link on its website that provides
answers to some of the most frequently asked questions. Topic areas
include Social Security benefits, Social Securities assets, Social
Security’s future, modernization of the program, and global aging. On
the topic of modernization, the website notes that there are four basic
alternatives being discussed: increasing payroll taxes, decreasing
benefits, using general revenues, and prefunding future benefits through
either personal savings accounts or direct investments of the trust
Visit the SSA website for full question and answers. http://www.socialsecurity.gov/qa.htm
Researcher Q & A
Challenges And Solutions For Retirement
The Federal Interagency Forum on Aging-Related Statistics
(Forum) will hold a half-day workshop on "Estimating Pension
Wealth" Wednesday, August 8, 2007, 1:00-5:30pm, at the Bureau of
Labor Statistics’ (BLS) Conference Center. The purpose of this
workshop is to bring together experts from government and academia
to discuss different methodologies for estimating pension wealth.
More information about the workshop, including the agenda and
background papers, can be found on the Forum’s website
register, please contact Sherry Dockery by email at email@example.com
or by phone at 301-458-4187 and provide her with your name,
agency/organization, and email address. The deadline to register for
this workshop is Wednesday, July 25. There is no charge to attend
the workshop but YOU MUST REGISTER TO ATTEND. Due to Federal
building security procedures, a complete list of attendees must be
submitted to the BLS security office two weeks before the workshop.
You will need to show valid picture identification to enter the
building. Please note that the registration for this workshop is
separate from the registration for the Retirement Research
Consortium, which is being held on August 9-10 at the National Press
If you have any questions about the workshop, or the work of the
Forum, please contact Kristen Robinson by email at firstname.lastname@example.org or
by phone at 301-458-4460.
The visitor's entrance for the Bureau of Labor Statistics is located
on First Street, N.E., near the intersection of First Street, NE and
G Street, NE, (across from Union Station). The closest Metro station
to the Bureau of Labor Statistics is Union Station, which is served
by the Red line. After exiting the train, follow the signs to the
escalator marked “To Trains.” Once you pass through the turnstile,
turn left and exit through the First Street exit. The visitor's
entrance to BLS is directly across the street. Parking is also
available at Union Station.
Losers: 401(k) Trading and Portfolio Performance
By: Takeshi Yamaguchi, Olivia S. Mitchell, Gary R.
Mottola, and Stephen P.Utkus
toward participant-directed defined contribution (DC) accounts is
requiring employees to take an increasingly active role in managing
their retirement assets. Nevertheless, little research has examined how
active workers manage their 401(k) plan assets, and even less is known
about how a critical aspect of investment decision-making, trading
activity, affects DC pension performance. The authors employ a unique
new data set of about one million active 401(k) participants in some
1,500 DC plans, to evaluate in detail the impact of workers’ trading
decisions on the performance of their DC portfolios. They find that, in
aggregate, the risk-adjusted returns of traders are no different than
those of nontraders, but certain types of trading such as periodic
rebalancing are beneficial, while high-turnover trading is costly.
Interestingly, those who hold only balanced or lifecycle funds, called
passive rebalancers, earn the highest risk-adjusted returns. These
findings should interest participants in such plans, fiduciaries
responsible for designing DC pensions, and regulators of the retirement
The research goal is to examine whether and how trading activity alters
the investment performance of participants’ pension accounts. The
analysis dataset consists of a two-year extract of over one million
participants drawn from the Vanguard recordkeeping systems for 1,500
401(k) plans during 2003-04. The file tracks asset allocation and
trading patterns, permitting the classification of participants
according to their trading activity and rebalancing behavior.
Specifically, those who do not trade their 401(k) assets and hold only
balanced or lifecycle funds are “Passive Rebalancers;” those who always
rebalance their asset allocation are “Active Rabalancers;” those who
trade in their portfolios but are not Active Rebalancers are “Other
Traders;” and those who do not alter their allocations are “Nontraders.”
The authors calculate a variety of raw and risk-adjusted returns
realized by each participant using his beginning-of-the-month asset
allocation. They also compute the difference between what the
participant actually realized given his trading behavior, and what he
would have earned had he always rebalanced his portfolio to the
allocation that he chose for his contributions.
The findings suggest that traders outperform nontraders, and active
rebalancers do better than passive rebalancers, prior to the
risk-adjustment. Further, trading seems to have a positive impact on
investment performance using “raw” data; traders significantly
outperform nontraders by 4 basis points per month or an annualized 55
basis points. However actual returns compared to those that would be
earned by sticking with their own benchmark do not differ significantly
between traders and nontraders. In addition, active rebalancers
outperform nontraders by 15 basis points per month, while passive
rebalancers underperform nontraders by 11 basis points per month,
without correcting for risk. Further, active rebalancers do better than
nontraders, given their own benchmarks, but passive rebalancers
underperform nontraders. Finally, traders with the lowest turnover rates
outperform higher-turnover traders.
By contrast, when the authors analyze risk-adjusted returns, the results
are rather different. Specifically, they find that 401(k) plan trading
overall has virtually no impact on risk-adjusted investor performance;
the gap is between 0 and 2 basis points per month, depending on the
capital market model. Yet there are within-group differences: active
rebalancers outperform other nontraders by 6 basis points per month (72
basis points annualized), while passive rebalancers outperform other
nontraders by 8 basis points per month (over 100 basis points
annualized). Overall, rebalancers outperform all other types of traders,
and those whose portfolios are automatically rebalanced by a third party
money manager realize the best risk-adjusted returns. The authors also
note, those with the highest turnover ratios also earn lower
risk-adjusted returns. Finally, they discover that rebalancers (who earn
better risk-adjusted returns) are on average slightly younger, somewhat
less affluent, and more likely to be women, than other traders. Some
plan design variables are also related to the prevalence of active
rebalancers: for instance, when more funds are offered in the 401(k)
menu, the likelihood of being an active rebalancer decreases. This
suggests that larger plan menus tend to encourage trading beyond
Since the risk-adjusted performance earned by workers who trade in their
portfolios are no different overall from that of nontraders, it remains
true that periodic rebalancing is beneficial but high-turnover trading
is costly. Interestingly, those who hold only balanced or lifecycle
funds, the passive rebalancers, earn the highest risk-adjusted returns.
This is an important finding for plan sponsors and policymakers actively
who seek to improve the performance of DC pension plans. Currently, most
plans do not impose automatic rebalancing on their participants’ asset
allocations; rather, workers must actively elect to rebalance their own
portfolios periodically or select professionally-rebalanced funds.
In view of the rewards from passive rebalancing as an investment
strategy, this research underscores the value of offering a rebalancing
fund or service as an investment default, such as a target maturity date
or life cycle fund, or a managed account. Employers and recordkeepers
overseeing 401(k) plans may also want to consider whether automatic
rebalancing of 401(k) accounts should be the default design.
Furthermore, policies designed to discourage active trading in 401(k)
plans are likely to result in superior risk-adjusted returns and
ultimately higher retirement saving, since high turnover rates harm
investment performance. Round-trip restrictions and early redemption
fees are two examples of policies that have been recently introduced in
the US to deter excessive market-timing trading by investors. These or
similar policies would appear to improve returns and reduce transaction
costs for all participants since, in the commingled investment offerings
of most DC plans, transactions costs are borne by all holders, not just
to the top.
Researcher Q & A
In this issue
Richard V. Burkhauser and John H. Cawley discuss their MRRC-supported
Q: Describe your MRRC-supported work on the causes and consequences of
labor force exit.
In our society, the economic well-being of the vast majority of
households is dependent on work. So over the life cycle, the greatest
threat to their economic security comes when the primary wage earner
permanently transitions out of the labor force. Hence it is not
surprising that the most important United States social insurance
program--Old-Age, Survivors and Disability Insurance (OASDI)—focuses on
providing insurance against the three most common causes of these
permanent labor force exits: retirement, death, and disability.
My MRRC-supported work focuses on questions related to these exits: What
are the economic consequences on the household of the death or
disability of the primary earner? What determines the timing of exit
from the work force following the onset of a disability? And, what role
does public policy play in these outcomes?
Two early papers for MRRC (WP 2001-014 and WP 2002-033) ask the
questions: what happens to the economic well-being of a woman following
the death of her husband and how does this vary across countries? Using
Cross-National Equivalent File panel data we are able to look at
household income and its sources before and after the husband’s death in
the United States, Great Britain, Germany, and Canada. We find that
these economic consequences are remarkably similar across the four
countries. Most widows experience a decline in income. However, when we
adjust for the reduction in household size, there is, on average, no
decrease in their overall economic well-being.
While the U.S. Social Security system does not replace as large a share
of the husband’s income as the Social Security systems in the other
countries we studied, this is offset by the much bigger role played by
private sector income, especially from employer pensions. Once you look
at how total household size-adjusted income changes, it turns out that
widows in the U.S. do about as well as widows in the other countries.
My first paper for MRRC (WP 2001-009) looks at how household income
changes in the years prior to and after application for Social Security
Disability Insurance (DI). John Bound and I had access to matched SIPP
and Social Security administrative records data that allowed us to
followed people for three years before and three years after they
applied for DI benefits. A major concern among policymakers was that
people were falling through the cracks while waiting to receive their DI
disability benefits. The time between application and receipt of DI
benefits can be quite long, and there is a minimum five month waiting
period from the time of onset even for those who are judged to be
otherwise eligible for benefits. So we wanted to see if applicants’
household income severely declined in the run up to application and
prior to acceptance because they weren’t working.
Again, the good news is that on average the decline in wage earnings was
offset by short-term disability benefits, workers compensation, or
private insurance over this period. So on average we didn’t find a great
decline in their household’s economic well-being. The system, as a
whole, seems to work fairly well.
Q: What about behavioral effects of policy?
In addition to asking questions about what happens to economic
well-being, we’ve looked at how the system affects behavior. The
employment of men with disabilities in the United States has declined
fairly substantially in the 1990s relative to men without disabilities.
There’s a large literature examining this phenomenon: is it real? what’s
Mathis Schroeder and I (WP 2004-071), using data from the Current
Population Survey and from the German Socio-Economic Panel, estimated
trends in the employment of working-age men with disabilities relative
to those without disabilities in the U.S. and Germany, two countries
with very similar level of health but quite different social
institutions with respect to the employment of those with disabilities.
After creating a variable to determine disability in the German data
consistent with our U.S. variable we were able to see if they
experienced similar trends over the 1990s.
We find that there was no decline in the relative employment rate of men
with disabilities over this period in Germany, which suggests that
social policy changes in the U.S. are responsible for the difference in
trends. This study demonstrates the value of cross-national comparisons
to try to separate policy outcomes.
In another study (WP 2006-145), Ludmila Rovba and I addressed a broader
public policy question: what’s been happening to income inequality in
the U.S. over the last twenty years and how does it compare with changes
in other countries? We observed that income inequality increased
dramatically in the 1980s in the U.S. but not in the 1990s as the entire
income distribution improved over the business cycle 1989-2000. During
that period, everybody became better off, in part because more of the
fruits of economic growth reached the lower end of the income
distribution. Surprisingly, the U.S. did better than Germany and
Japan—two countries with a much greater social safety net—in this
respect in the 1990s. Our findings are especially relevant for the
Social Security Administration because they show that from 1989-2000,
economic well-being improved for older Americans as well.
Q: Talk about how your recent work on obesity
fits with that interest.
I am very pleased to be able to work with John Cawley, who is one of the
leading experts on the economics of obesity, and to be able to wed our
work to my interests in exits from the labor force to tackle a question
that is very important for the country as a whole and also for Social
Security policy. Obesity has been rising in the U.S. at least since the
1970s. The medical literature has established that obesity is a
significant risk factor for heart disease, diabetes, and other medical
conditions that have significant impact on people’s ability to work,
their impairment levels, and eventually whether they have disabilities.
In our first MRRC project on this topic, we used data from the Panel
Study of Income Dynamics (PSID) to examine whether there was a link
between obesity and reported disability and between disability and
enrollment in DI. Indeed, we found that obesity was a strong risk factor
for disability. However, that work convinced us that the major variable
that social scientists used to measure obesity, body mass index (BMI),
was a very crude measure of fatness.
Why is it important to measure fatness?
BMI is just a measure of total body mass, and it ignores the composition
of that mass. Medical research is really zeroing in on fatness—as
measured, for example, by percent body fat—as the critical risk factor
in the outcomes I’ve mentioned. One way to measure percent body fat is
through bioelectrical impedance analysis (BIA). BIA measures body fat by
passing a safe electric current through the body; the logic is that fat
is an insulator and water (which is what composes much of muscle mass)
is a conductor, so resistance to the electric charge is informative
about the quantity of fat and lean mass in the body.
In our work with the National Health and Nutrition Examination Survey (NHANES)
III, which contains data on both measured weight and height (to
calculate BMI) and BIA readings (to calculate percent body fat) we show
that BMI is not highly correlated with percent body fat and that BMI is
a noisy measure of fatness.
There are multiple definitions of obesity. The most commonly-used one is
based on BMI; specifically, a BMI greater than 30. However, an alternate
definition of obesity is based on percent body fat: greater than 25
percent for men or greater than 30 percent for women. Which of these two
definitions of obesity you use makes an enormous difference. For
example, if you define obesity using BMI, there is no difference in the
prevalence of obesity of white and black men. However, when we use
obesity defined using percent body fat, we find that white men have a
higher rate of obesity than black men. Which definition of obesity you
use also matters for women. If one defines obesity using BMI,
African-American women appear to have a much higher prevalence of
obesity than white women, but when you define obesity using percent body
fat the gap is much smaller.
Q: Why is BIA a better measure for economic
In the past, economists in particular and social scientists in general
have used BMI pretty unquestioningly. Social scientists have not kept
pace with the medical research, in which researchers have demonstrated
that various measures of fatness differ in their ability to predict
health outcomes like heart attack. Our major point is that each measure
of fatness and obesity has its unique strengths and weaknesses, and that
social scientists should consider other measures of fatness than BMI and
other measures of obesity than that defined by BMI.
For example, in our forthcoming paper in the Journal of Health Economics
we report the correlation between employment and fatness, measured both
by BMI and percent body fat (calculated using BIA), in NHANES III data.
Our research confirms that there is a correlation between BMI and
employment--obese people are less likely to work. However, when total
body mass is disaggregated into fat versus lean body mass (which
includes muscle, bone, and fluids), we find that only fat is correlated
with unemployment, not lean mass.
That suggests that the use of BMI, which lumps together both fat and
lean mass, can obscure important relationships between fatness and
social science outcomes. This has convinced us that it is very important
to use more accurate measures of fatness in economic analyses in
particular and in social science in general.
Q: Where are you headed with this line of
In our MRRC research proposed for next year, we would take advantage of
an exciting and rich new dataset. In the last six months, the NHANES III
data have been linked to Social Security administrative records. That
will allow us to revisit some of the work we did with the PSID data,
which relies on self-reported Social Security disability benefit
receipt. The NHANES III linked to administrative records is a major
improvement over the data used in previous research by us and others
because it includes much more accurate measures of both the outcome of
interest (application for DI) and the regressors of interest (various
measures of fatness collected through medical examination). This will
vastly increase the precision of our estimates.
Our findings should provide the most accurate information to date on the
correlation between obesity and application for DI. Because increases in
obesity are likely to be associated with increases in the probability of
application for DI, our findings will help the SSA to better predict
program application and enrollment and hence overall OASDI costs.
of Objective Health Measures in Predicting Early Receipt of Social
Security Benefits: The case of Fatness by Richard V. Burkhauser and John
H. Cawley WP 2006-148, December 2006.
How the Distribution of After-Tax Income Changed Over the 1990s Business
Cycle: A Comparison of the United States, Great Britain, Germany, and
Japan by Richard V. Burkhauser, Takashi Oshio, and Ludmila Rovba WP
2006-145, December 2006.
Obesity, Disability and Movement Onto the Disability Insurance Rolls by
Richard V. Burkhauser and John H. Cawley WP 2004-089, October 2004.
A Cross-National Comparison of the Employment for Men With Disabilities:
The United States and Germany in the 1980s and 1990s by Richard V.
Burkhauser and Johan Mathis Schröder WP 2004-071, January 2004.
How Exits from the Labor Force or Death Impact Household Incomes: A Four
Country Comparison of Public and Private Income Support by Richard V.
Burkhauser, Phil Giles, and Dean Lillard WP 2002-033, July 2002.
Long-Term Labor Force Exit and Economic Well-Being: A Cross-National
Comparison of Public and Private Income Support by Richard V. Burkhauser,
Dean Lillard, and Paola Maria Valenti WP 2001-014, May 2001.
Tracking the Household Income of SSDI and SSI Applicants by John Bound,
Richard V. Burkhauser, and Austin Nichols WP 2001-009, May 2001.
Beyond BMI: The Value of More Accurate Measures of Fatness and Obesity
in Social Science Research by Ricahrd V. Burkhauser and John Cawley
Journal of Health Economics (forthcoming).
Richard V. Burkhauser is the
Sarah Gibson Blanding Professor of Policy Analysis in the Department of
Policy Analysis and Management in the College of Human Ecology at
Cornell University. Burkhauser has published widely in the area of
United States and European social security retirement and disability
policy. His most recent publications include a co-author textbook, The
Economics of Aging (2004) and a co-editor book, The Decline in
Employment of People with Disabilities: A Policy Puzzle (2003). He was a
member of the 2003 Technical Panel on Assumptions and Methods of the
Social Security Administration Actuaries, a U.S. Senate appointee to the
Ticket to Work/Work Incentives Improvement Act Advisory Board
(2000-2002), as well as a member of the Technical Panel of the 1994-1996
Advisory Council on Social Security and the 1994-1995 National Academy
of Social Insurance Panel on Disability Policy Reform. He received his
Ph.D. in economics from the University of Chicago.
John H. Cawley is associate
professor in Cornell’s Department of Policy Analysis and Management as
an assistant professor. His recent research focuses on the economics of
health behaviors and evaluating U.S. health policies. He is
investigating the effect of body weight on labor market outcomes such as
wage rates, unemployment, and employment disability; the role of body
weight in the decision of adolescents to initiate smoking; and the
extent to which consumption of calories can be considered addictive.
Cawley is a Faculty Research Fellow with NBER and a Research Affiliate
of the Northwestern University/University of Chicago Joint Center for
Poverty Research. He currently serves on an advisory board to the
Centers for Disease Control for an initiative on the economics of
He received his Ph.D. in economics from the University of Chicago in
1999 and graduated magna cum laude from Harvard in 1993.
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Challenges And Solutions For Retirement Security
Press Club – 529 14th St. NW, 13th Floor - Washington, DC 20045 | August
the Office of Policy, Social Security Administration
and the Retirement Research Consortium
Contact: Becky Bahlibi (email@example.com)
John P. Laitner, Director, University of Michigan Retirement Research
I: Recent Empirical Evidence on Retirement and Retiree Behavior
8:35 a.m. Chair:
Take-up of the Social Security Administration’s Low-Income Subsidy
Program for Part D of Medicare in 2006.
David Weir and Helen Levy
Disscussant: Paul Van de Water
The Welfare Cost of Assymetric Information: Evidence from the U.K.
Liran Einav and Amy Finkelstein
Disscussant: Mark Warshawsky
Labor Market Effects of Public Health Insurance: Evidence from the US
Department of Veterans Affairs.
Joanna N. Lahey and Melissa A. Boyle
Discussant: Julie Zissimopoulos
9:55 a.m. Break
II: Demographic Changes and Family Behavior
10:10 a.m. Chair:
The Future of American Fertility.
Samuel Preston and Caroline Sten
Discussant: John Sabelhaus
Children and Household Wealth.
John Karl Scholz and Ananth Seshadri
Discussant: Barry Bosworth
Implications of Career Paths for Social Security.
Melissa M. Favreault and C. Eugene Steuerle
Discussant: David Blau
11:30 a.m. Break
Andrew Biggs, Deputy Commissioner, Social Security Administration
III: Preparedness for Retirement: Managing Financial and Mortality Risk
12:45 p.m. Chair: Joyce
Annuities and Life Cycle Asset Allocation.
Raimond H. Maurer
Discussant: James Poterba
Inflation Bets or Deflation Hedges? Understanding the Risks of Nominal
John Campbell, Adi Sunderam and Luis Viceira
Discussant: James Poterba
Retiree Perceptions and Decision-Making Concerning Longevity, Inflation,
and Investment Risk in the Early Years of the Post-Retirement Phase.
Discussant: John Karl Scholz
2:05 p.m. Break
IV: Preparedness for Retirement: Private Pensions
2:20 p.m. Chair:
Paul Van de Water
The Impact of Employer Matching on Savings Plan Participation under
David Laibson, Brigitte Madrian, and James Choi
Discussant: Olivia S. Mitchell
Which Companies Will Freeze Their Pensions?
Alicia H. Munnell and Mauricio Soto
Discussant: Alan Gustman
The Role of Governance in Retirement Investments: Evidence from Variable
Richard Evans and Rüdiger Fahlenbrach
Discussant: John Campbell
3:40 p.m. Break
Measuring Well-being in Retirement
3:55 p.m. Chair: Paul
Improved Poverty Measures for the Elderly.
Bruce Meyer and James X. Sullivan
Discussant: Richard V. Burkhauser
Future Beneficiary Expectations of the Returns to Delayed Social
Security Benefit Claiming and Choice Behavior.
Jeffrey Dominitz, Angela Hung, Arthur van Soest and Arie Kapteyn
Discussant: John Phillips
Capital Income Flows and the Relative Well-Being of the Elderly.
Barry P. Bosworth and Gary Burtless
Discussant: David Weir
8:30 a.m. Welcome
Alicia Munnell, Director, Center for Retirement Research at Boston
VI: Examining the Motives and Reasons for Retirement
8:35 a.m. Chair: Howard Iams
Trends in EU Pension Reform.
George Fischer and Oliver Bontout (European Commission)
Discussant: John Shoven
The Impact of Late-Career Health and Employment Shocks on Social
Security and Pension Benefits.
Richard W. Johnson and Gordon Mermin
Discussant: Dick Woodbury
Outsourcing, Deindustrialization, and Technological Change: The Effect
of Changes in Labor Demand on Retirement Outcomes of Older Workers.
Till von Wachter
Discussant: Joe Quinn
10:00 a.m. Break
Session VII: How Health Influences Retiree Well-Being
10:15 a.m. Chair: Joe
11:35 a.m. Break
How Should Changes in Population Health Affect Retirement Ages?
David Cutler and Jeff Liebman
Discussant: Helen Levy
Estimating the Health Effects of Retirement.
John Bound and Timothy Waidmann
Discussant: Joanna Lahey
Modeling the Effects of Out-of-Pocket Medical Expenses on the Retirement
Richard W. Johnson and Rudolph G. Penner
Discussant: Liran Einav
Session VIII Retirement Behavior Now and In the Future.
Sylvester Schieber, Social Security Advisory Board
12:50 p.m. Chair: John
2:30 p.m. Adjourn
Private Pensions and Decisions of When to Retire.
John P. Laitner and Daniel Silverman
Discussant: Jeffrey Brown
Social Security Eligibility and the Labor Supply of Elderly Immigrants.
Discussant: Jay Stewart
A Cross-National Comparison of Self-Employment Dynamics at Older Ages.
Julie Zissimopoulos, Nicole Maestas, and Lynn Karoly
Discussant: Gary Burtless
What Makes Retirees Happier: A Gradual Retirement or ‘Cold Turkey’
Esteban Calvo, Kelly Haverstick, and Steven A. Sass
Discussant: Estelle James
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