The National Retirement Risk Index (NRRI) measures
the percentage of working-age households who
are at risk of being financially unprepared for retirement.
White Paper from the Center for Retirement Research written by Alicia H. Munnell, Wenliang Hou, and Geoffrey T. Sanzenbacher*
This is the 7th World Happiness Report. The first was released in April 2012 in support of a UN High level meeting on “Wel lbeing and Happiness: Defining a New Economic Paradigm”. That report presented the available global data on national
happiness and reviewed related evidence from the emerging science of happiness, showing that the quality of people’s lives can be coherently, reliably, and validly assessed by a variety of subjective well-being measures, collectively referred to then
and in subsequent reports as “happiness.” Each report includes updated evaluations and a range of commissioned chapters on special topics digging deeper into the science of well-being, and
on happiness in specific countries and regions.
Often there is a central theme. This year we focus on happiness and community: how happiness has been changing over the past dozen years, and how information technology, governance and social norms influence communities. The world is a rapidly changing place.
In the course of the last several years, millennials have shown that they are very different from previous generations in a number of ways. Defined as the generation born from 1981 to 1996, they are the largest, most educated, and most connected generation the world has ever seen1. However, recent data also show the beginnings of troubling generational health patterns that could hamper the future prosperity of millennials, and in turn the prosperity of the U.S. If the current pace of decline in millennial health continues unabated, the long-term consequences to the U.S. economy could be severe.
Used for Medical Grand Rounds at several hospitals, this is data based comprehensive review of the shortcomings of the American Medical System and dysfunctional political attempts at reform. Single payer, Medicare for all, with elimination of for profit insurance companies is the best answer.
Shocking study in JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION of 1.4 billion person-years documenting rising death rates among middle aged whites, amounting to over 600,000 lives lost due to alcoholism, drug overdoses and suicides
This is the 7th World Happiness Report. The first was released in April 2012 in support of a UN High level meeting on “Wel lbeing and Happiness: Defining a New Economic Paradigm”. That report presented the available global data on national
happiness and reviewed related evidence from the emerging science of happiness, showing that the quality of people’s lives can be coherently, reliably, and validly assessed by a variety of subjective well-being measures, collectively referred to then
and in subsequent reports as “happiness.” Each report includes updated evaluations and a range of commissioned chapters on special topics digging deeper into the science of well-being, and
on happiness in specific countries and regions.
Often there is a central theme. This year we focus on happiness and community: how happiness has been changing over the past dozen years, and how information technology, governance and social norms influence communities. The world is a rapidly changing place.
In the course of the last several years, millennials have shown that they are very different from previous generations in a number of ways. Defined as the generation born from 1981 to 1996, they are the largest, most educated, and most connected generation the world has ever seen1. However, recent data also show the beginnings of troubling generational health patterns that could hamper the future prosperity of millennials, and in turn the prosperity of the U.S. If the current pace of decline in millennial health continues unabated, the long-term consequences to the U.S. economy could be severe.
Used for Medical Grand Rounds at several hospitals, this is data based comprehensive review of the shortcomings of the American Medical System and dysfunctional political attempts at reform. Single payer, Medicare for all, with elimination of for profit insurance companies is the best answer.
Shocking study in JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION of 1.4 billion person-years documenting rising death rates among middle aged whites, amounting to over 600,000 lives lost due to alcoholism, drug overdoses and suicides
A fact based, detailed analysis of the economic stress on middle American families and the malfunction of democratic institutions, producing distrust, anger, and an epidemic of unnecessary deaths. Explains the dynamics of the 2016 Presidential election.
Observations on the needs for, the contents of, and many of the practical effects of the Affordable care Act or Obamacare. Understanding its benefits and shortcomings
UP Economists- Population, the Real ScoreHarvey Diaz
The country's premier institution demonstrates its clear analysis, basis and support for a modern family planning program and cites the leading global and local stidies that support this.
Link to current Sustainable Healthcare discussion. Summary of factors affecting healthcare costs. Conclusion: status quo untenable. No prescriptive solutions...need to invent future. Sourced from presentation by Colonel Chuck Williams, EURASIA TRICARE Area Office.
An example of a Demographic Data Report for a Neilsen designated market areas or DMAs. These reports contain basic demographics (i.e. population, race, income, etc.). They are print-ready PDF documents with colorful graphs that you can easily include in your presentations and final reports. This option is a typically good fit if you need demographics for a handful of DMAs.
The ubiquity of handheld devices and learning media means that every educator (and student) makes daily choices in how to shape content. The prominence of visual stimuli places a heightened emphasis on the design of information and the broad reach of its effectiveness. The skills of graphicacy help learners see how cognition and perception can have real-world impacts on critical thought and creativity.
Remember last week when we talked about Zoom Video Communications adding live streaming to their webinar platform (article here)? Now the video production software market is looking for a piece of the pie, in a converging industry with a combined worth an estimated $100+ Billion by 2020 (Video Communications & Live Streaming - See sources below)!
So let's look at one of the live streaming industries most innovative video production companies who has slipped in a peer-to-peer video conferencing add-on to their latest release. vMix just announced new feature called "vMix Call" and I think this is a GAME CHANGER for the live streaming market! vMix Call allows users to instantly launch a video conference call inside their professional 4K capable video production software suite. As you will see in this video vMix now supports the ability to add an input specifically for video calling with guests on your live show. This is perhaps one of the most exciting features being released in vMix 19 AND it's already available for BETA testing.
A fact based, detailed analysis of the economic stress on middle American families and the malfunction of democratic institutions, producing distrust, anger, and an epidemic of unnecessary deaths. Explains the dynamics of the 2016 Presidential election.
Observations on the needs for, the contents of, and many of the practical effects of the Affordable care Act or Obamacare. Understanding its benefits and shortcomings
UP Economists- Population, the Real ScoreHarvey Diaz
The country's premier institution demonstrates its clear analysis, basis and support for a modern family planning program and cites the leading global and local stidies that support this.
Link to current Sustainable Healthcare discussion. Summary of factors affecting healthcare costs. Conclusion: status quo untenable. No prescriptive solutions...need to invent future. Sourced from presentation by Colonel Chuck Williams, EURASIA TRICARE Area Office.
An example of a Demographic Data Report for a Neilsen designated market areas or DMAs. These reports contain basic demographics (i.e. population, race, income, etc.). They are print-ready PDF documents with colorful graphs that you can easily include in your presentations and final reports. This option is a typically good fit if you need demographics for a handful of DMAs.
The ubiquity of handheld devices and learning media means that every educator (and student) makes daily choices in how to shape content. The prominence of visual stimuli places a heightened emphasis on the design of information and the broad reach of its effectiveness. The skills of graphicacy help learners see how cognition and perception can have real-world impacts on critical thought and creativity.
Remember last week when we talked about Zoom Video Communications adding live streaming to their webinar platform (article here)? Now the video production software market is looking for a piece of the pie, in a converging industry with a combined worth an estimated $100+ Billion by 2020 (Video Communications & Live Streaming - See sources below)!
So let's look at one of the live streaming industries most innovative video production companies who has slipped in a peer-to-peer video conferencing add-on to their latest release. vMix just announced new feature called "vMix Call" and I think this is a GAME CHANGER for the live streaming market! vMix Call allows users to instantly launch a video conference call inside their professional 4K capable video production software suite. As you will see in this video vMix now supports the ability to add an input specifically for video calling with guests on your live show. This is perhaps one of the most exciting features being released in vMix 19 AND it's already available for BETA testing.
Who needs insurance preparation for the generationsGen Re
Gen Re's newest edition of the Life & Health Fact Book that contains important statistics that demonstrate why any generation - but especially Gen X and Baby Boomers - need to prepare for the unexpected.
Read More: http://www.genre.com/knowledge/blog/who-needs-insurance-preparation-for-the-generations.html
Making your money last in retirement - Aviva's longevity reportAviva plc
In our making your money last in retirement special report we compare and consider consumer attitudes to the facts about longevity, and make some clear recommendations about how the government and the industry must respond.
Making your money last in retirement - Aviva's longevity reportAviva plc
In our making your money last in retirement special report we compare and consider consumer attitudes to the facts about longevity, and make some clear recommendations about how the government and the industry must respond.
The COVID-19 pandemic has thrown American life into chaos and, over the last eight weeks, Consumer Brands’ weekly coronavirus survey has proven that this new normal is anything but. Now, as some states extend stay-at-home orders and others begin to reopen for business, this week’s survey — and the last eight weeks of consumer concerns — show that we may be at a turning point for how Americans feel about coronavirus and its effect on their lives.
Measuring people’s perceptions, evaluations and experiences: Why they matter ...StatsCommunications
First webinar of the series: Measuring people's perceptions, evaluations and experiences, 22 September 2020, More information at: http://www.oecd.org/statistics/lac-well-being-metrics.htm
COVID-19 data configuration and statistical analysisAnshJAIN50
The following report aims to identify the primary factors influencing the spread of Covid-19. To do this, I have analyzed the rate of spread in MEDCs and LEDCs - countries differing significantly in development. MEDCs, being more economically developed, tend to have superior healthcare, higher life expectancy, and generally better infrastructure, contrasting with LEDCs. This report aims to understand whether the characteristics of MEDCs and LEDCs can significantly impact the rate of spread of Covid-19, as well as more obscure factors that could have a greater impact than previously thought. In this report we will be examining 3 different MEDCs and LEDCs to develop a clear conclusion on whether we believe a country's development correlates to the rate of spread of Covid-19.
Single Parenting Essay. Check my Essay: Single parent struggle argumentative ...Mimi Williams
Single Parents 400 Words - PHDessay.com. Single Parent Families Without Father Free Essay Example. 018 Single Parenting In India Essay Example O Mom Thatsnotus. Essay on single parent family. 002 Essay Example Single Parent Communityfair .... Essay outline: Single parent struggle argumentative essay. Growing Up with a Single Parent Free Essay Example. What Are The Effects On Children Of Single Parents? Free Essay Example. Growing Up In A Single-Parent Family - A-Level Psychology - Marked by .... Single Parenting vs Dual Parenting Essay Example GraduateWay. A Study of Single Parenting Research Paper Example Topics and Well .... Single parent households essay topics. Being a parent thesis - Thesis Statement: Being a parent, while it is a .... Growing up with a single parent cause and effect essay. Free Single .... Effects Of Single Parent Families Free Essay Example. Having a single parent Essay Example Topics and Well Written Essays .... Single mom essay. Single Mothers Essays: Examples, Topics, Titles .... Challenges of being a single parent essay - training4thefuture.x.fc2.com. Essay on Single Parenting: Two Parents Or One? SchoolWorkHelper. Argument Essay: Single Parent Struggle Single Parent Stepfamily. Single Parents: Positive Single Parenting - Free Essay Example - 2295 .... Single Parenting Essay Example Topics and Well Written Essays - 2500 .... Sample Essay on Single Parent Essay Free Essay Example. Single parenting essay The Friary School. DISCUSSION ISSUES ON ASSESSMENT PDF. Growing Up in a Single Parent Family: Essay Example, 583 words EssayPay. Single Parents Can Raise Kids As Well As Two Parents Free Essay .... Check my Essay: Single parent struggle argumentative essay. Single parent families - Essay - 997 - writingmap.x.fc2.com. Good Parent Speech Empathy Parenting. Free essay on single parenting Single Parenting Essay Single Parenting Essay. Check my Essay: Single parent struggle argumentative essay
Single Parents (400 Words) - PHDessay.com. Single Parent Families Without Father Free Essay Example. 018 Single Parenting In India Essay Example O Mom ~ Thatsnotus. Essay on single parent family. 002 Essay Example Single Parent Communityfair .... Essay outline: Single parent struggle argumentative essay. Growing Up with a Single Parent Free Essay Example. What Are The Effects On Children Of Single Parents? Free Essay Example. Growing Up In A Single-Parent Family - A-Level Psychology - Marked by .... ⇉Single Parenting vs Dual Parenting Essay Example | GraduateWay. A Study of Single Parenting Research Paper Example | Topics and Well .... Single parent households essay topics. Being a parent thesis - Thesis Statement: Being a parent, while it is a ....
With millions of US households personally directing their retirement savings, the Investment
Company Institute (ICI) has sought to track retirement savers’ actions1 and sentiment.
This report, the 10th in this series, summarizes results from a survey of American adults,
weighted to be representative of US households by age, income, region, and education level.
The survey was designed by ICI research staff and administered by the GfK Group using the
KnowledgePanel®, a proprietary, probability-based web panel.2 This report presents survey
results that reflect households’ responses collected during December 2017.3
The survey polled respondents about their views on defined contribution (DC) retirement
account saving and their confidence in 401(k) and other DC plan accounts. Survey responses
indicated that households value the discipline and investment opportunity that 401(k) plans
represent and that households were largely opposed to changing the tax preferences or
investment control in those accounts. A majority of households also affirmed a preference for
control of their retirement accounts and opposed proposals to require retirement accounts to be
converted into a fair contract promising them income for life from either the government or an
insurance company
In a matter of minutes, you can generate a detailed report with a side-by-side comparison that addresses the opportunities discovered in The Retirement Plan Diagnostic™. Communicate the features, benefits and overall impact of your value proposition in a concise format that's co-branded and customized to your firm's unique investment models and menus.
This tool is fully integrated with PlanFinder SM and The Retirement Plan Diagnostic SM for seamless data transfer from previously collected prospective plans. With the Retirement Plan Efficiency Analysis SM , you can save significant time and money while delivering tangible value in client meetings.
This revolutionary tool uses current and historical Form 5500 data to deliver a comprehensive report on plan health in a format that's easily understood and communicated to plan sponsors. With the power of meaningful metrics in an attractive format, you can benchmark return on investments, participation levels, and utilization against a plan's peer group and industry. The Plan Diagnostic is recognized for its speed of delivery and objectivity - offering a report with independent analysis rather than subjective ratings and hard-to-interpret correlations. Make your next plan conversation a truly consultative one that clearly distinguishes your approach from the "performance and cost" crowd.
how to sell pi coins in South Korea profitably.DOT TECH
Yes. You can sell your pi network coins in South Korea or any other country, by finding a verified pi merchant
What is a verified pi merchant?
Since pi network is not launched yet on any exchange, the only way you can sell pi coins is by selling to a verified pi merchant, and this is because pi network is not launched yet on any exchange and no pre-sale or ico offerings Is done on pi.
Since there is no pre-sale, the only way exchanges can get pi is by buying from miners. So a pi merchant facilitates these transactions by acting as a bridge for both transactions.
How can i find a pi vendor/merchant?
Well for those who haven't traded with a pi merchant or who don't already have one. I will leave the telegram id of my personal pi merchant who i trade pi with.
Tele gram: @Pi_vendor_247
#pi #sell #nigeria #pinetwork #picoins #sellpi #Nigerian #tradepi #pinetworkcoins #sellmypi
how to sell pi coins in all Africa Countries.DOT TECH
Yes. You can sell your pi network for other cryptocurrencies like Bitcoin, usdt , Ethereum and other currencies And this is done easily with the help from a pi merchant.
What is a pi merchant ?
Since pi is not launched yet in any exchange. The only way you can sell right now is through merchants.
A verified Pi merchant is someone who buys pi network coins from miners and resell them to investors looking forward to hold massive quantities of pi coins before mainnet launch in 2026.
I will leave the telegram contact of my personal pi merchant to trade with.
@Pi_vendor_247
what is the best method to sell pi coins in 2024DOT TECH
The best way to sell your pi coins safely is trading with an exchange..but since pi is not launched in any exchange, and second option is through a VERIFIED pi merchant.
Who is a pi merchant?
A pi merchant is someone who buys pi coins from miners and pioneers and resell them to Investors looking forward to hold massive amounts before mainnet launch in 2026.
I will leave the telegram contact of my personal pi merchant to trade pi coins with.
@Pi_vendor_247
USDA Loans in California: A Comprehensive Overview.pptxmarketing367770
USDA Loans in California: A Comprehensive Overview
If you're dreaming of owning a home in California's rural or suburban areas, a USDA loan might be the perfect solution. The U.S. Department of Agriculture (USDA) offers these loans to help low-to-moderate-income individuals and families achieve homeownership.
Key Features of USDA Loans:
Zero Down Payment: USDA loans require no down payment, making homeownership more accessible.
Competitive Interest Rates: These loans often come with lower interest rates compared to conventional loans.
Flexible Credit Requirements: USDA loans have more lenient credit score requirements, helping those with less-than-perfect credit.
Guaranteed Loan Program: The USDA guarantees a portion of the loan, reducing risk for lenders and expanding borrowing options.
Eligibility Criteria:
Location: The property must be located in a USDA-designated rural or suburban area. Many areas in California qualify.
Income Limits: Applicants must meet income guidelines, which vary by region and household size.
Primary Residence: The home must be used as the borrower's primary residence.
Application Process:
Find a USDA-Approved Lender: Not all lenders offer USDA loans, so it's essential to choose one approved by the USDA.
Pre-Qualification: Determine your eligibility and the amount you can borrow.
Property Search: Look for properties in eligible rural or suburban areas.
Loan Application: Submit your application, including financial and personal information.
Processing and Approval: The lender and USDA will review your application. If approved, you can proceed to closing.
USDA loans are an excellent option for those looking to buy a home in California's rural and suburban areas. With no down payment and flexible requirements, these loans make homeownership more attainable for many families. Explore your eligibility today and take the first step toward owning your dream home.
Introduction to Indian Financial System ()Avanish Goel
The financial system of a country is an important tool for economic development of the country, as it helps in creation of wealth by linking savings with investments.
It facilitates the flow of funds form the households (savers) to business firms (investors) to aid in wealth creation and development of both the parties
BYD SWOT Analysis and In-Depth Insights 2024.pptxmikemetalprod
Indepth analysis of the BYD 2024
BYD (Build Your Dreams) is a Chinese automaker and battery manufacturer that has snowballed over the past two decades to become a significant player in electric vehicles and global clean energy technology.
This SWOT analysis examines BYD's strengths, weaknesses, opportunities, and threats as it competes in the fast-changing automotive and energy storage industries.
Founded in 1995 and headquartered in Shenzhen, BYD started as a battery company before expanding into automobiles in the early 2000s.
Initially manufacturing gasoline-powered vehicles, BYD focused on plug-in hybrid and fully electric vehicles, leveraging its expertise in battery technology.
Today, BYD is the world’s largest electric vehicle manufacturer, delivering over 1.2 million electric cars globally. The company also produces electric buses, trucks, forklifts, and rail transit.
On the energy side, BYD is a major supplier of rechargeable batteries for cell phones, laptops, electric vehicles, and energy storage systems.
Poonawalla Fincorp and IndusInd Bank Introduce New Co-Branded Credit Cardnickysharmasucks
The unveiling of the IndusInd Bank Poonawalla Fincorp eLITE RuPay Platinum Credit Card marks a notable milestone in the Indian financial landscape, showcasing a successful partnership between two leading institutions, Poonawalla Fincorp and IndusInd Bank. This co-branded credit card not only offers users a plethora of benefits but also reflects a commitment to innovation and adaptation. With a focus on providing value-driven and customer-centric solutions, this launch represents more than just a new product—it signifies a step towards redefining the banking experience for millions. Promising convenience, rewards, and a touch of luxury in everyday financial transactions, this collaboration aims to cater to the evolving needs of customers and set new standards in the industry.
The European Unemployment Puzzle: implications from population agingGRAPE
We study the link between the evolving age structure of the working population and unemployment. We build a large new Keynesian OLG model with a realistic age structure, labor market frictions, sticky prices, and aggregate shocks. Once calibrated to the European economy, we quantify the extent to which demographic changes over the last three decades have contributed to the decline of the unemployment rate. Our findings yield important implications for the future evolution of unemployment given the anticipated further aging of the working population in Europe. We also quantify the implications for optimal monetary policy: lowering inflation volatility becomes less costly in terms of GDP and unemployment volatility, which hints that optimal monetary policy may be more hawkish in an aging society. Finally, our results also propose a partial reversal of the European-US unemployment puzzle due to the fact that the share of young workers is expected to remain robust in the US.
The Evolution of Non-Banking Financial Companies (NBFCs) in India: Challenges...beulahfernandes8
Role in Financial System
NBFCs are critical in bridging the financial inclusion gap.
They provide specialized financial services that cater to segments often neglected by traditional banks.
Economic Impact
NBFCs contribute significantly to India's GDP.
They support sectors like micro, small, and medium enterprises (MSMEs), housing finance, and personal loans.
What price will pi network be listed on exchangesDOT TECH
The rate at which pi will be listed is practically unknown. But due to speculations surrounding it the predicted rate is tends to be from 30$ — 50$.
So if you are interested in selling your pi network coins at a high rate tho. Or you can't wait till the mainnet launch in 2026. You can easily trade your pi coins with a merchant.
A merchant is someone who buys pi coins from miners and resell them to Investors looking forward to hold massive quantities till mainnet launch.
I will leave the telegram contact of my personal pi vendor to trade with.
@Pi_vendor_247
DO HOUSEHOLDS HAVE A GOOD SENSE OF THEIR RETIREMENT PREPAREDNESS?
1. February 2017, Number 17-4
DO HOUSEHOLDS HAVE A GOOD SENSE
OF THEIR RETIREMENT PREPAREDNESS?
* Alicia H. Munnell is director of the Center for Retirement Research at Boston College (CRR) and the Peter F. Drucker
Professor of Management Sciences at Boston College’s Carroll School of Management. Wenliang Hou is a senior research
advisor at the CRR. Geoffrey T. Sanzenbacher is a research economist at the CRR. The CRR gratefully acknowledges Pru-
dential Financial for its sponsorship of the National Retirement Risk Index.
Introduction
The National Retirement Risk Index (NRRI) mea-
sures the percentage of working-age households who
are at risk of being financially unprepared for retire-
ment. The calculations show that even if households
work to age 65 and annuitize all their financial assets,
including the receipts from reverse mortgages on
their homes, 52 percent will be at risk of being unable
to maintain their standard of living in retirement.
This brief examines whether households have a
good sense of their own retirement preparedness —
do their retirement expectations match the reality they
face? Do people at risk know they are at risk? Have
perceptions changed before and after the financial
crisis?
The discussion proceeds as follows. The first
section summarizes the NRRI. The second section
compares households’ self-assessed preparedness – at
an aggregate level – to the objective measure provid-
ed by the NRRI in 2004 and 2013. The third section
moves from the aggregate to individual households to
determine the share of households with and without
accurate perceptions. The fourth section identifies
the characteristics of the households with inaccurate
perceptions – those that are either “too worried” or
“not worried enough.” The final section concludes
that, on a household-by-household basis, almost 60
percent of self-assessments agree with the NRRI
predictions and that the 40 percent of households that
get it wrong do so for predictable reasons. The ques-
tion remains, however, whether unprepared house-
holds that recognize their situation are any more
likely to take corrective action than those that do not.
The NRRI
The NRRI is based on the Federal Reserve’s Survey
of Consumer Finances (SCF), a triennial survey of a
nationally representative sample of U.S. households.
The Index calculates for each household in the SCF a
replacement rate – projected retirement income as a
percentage of pre-retirement earnings – and com-
pares that replacement rate with a target replacement
rate derived from a life-cycle consumption smoothing
model. Those who fail to come within 10 percent
of the target are defined as “at risk,” and the Index
reports the percentage of all households at risk.
By Alicia H. Munnell, Wenliang Hou, and Geoffrey T. Sanzenbacher*
R E S E A R C H
RETIREMENT
2. Aggregate Self-Assessment
The NRRI shows that more than half of households
are at risk in retirement. One way to gauge whether
the Index is capturing an accurate picture of the situ-
ation is to compare it to households’ own perceptions
of their retirement preparedness.
The SCF, which is used to construct the NRRI,
asks each household to rate the adequacy of its antici-
pated combined retirement income from traditional
sources: Social Security and employer pensions. The
question’s response scale is from one to five, with
one being “totally inadequate,” three being “enough
to maintain living standards,” and five being “very
satisfactory.” Thus, any household that answers one
or two considers itself to be at risk.
The self-assessment of retirement preparedness in
both 2004 (before the financial crisis) and 2013 (the
most recent year of SCF data) is relatively consistent
with the NRRI calculations (see Table 1 for results by
income and Table 2 for results by age). This finding
lends support to the notion that the NRRI is accu-
rately detecting a widespread problem. In fact, the
Center for Retirement Research2
Figure 1. The National Retirement Risk Index,
1989-2013
The most recent results show that 52 percent of
working-age households in 2013 are at risk of being
unable to maintain their standard of living in retire-
ment. A comparison with earlier years shows that
the situation has become more serious over time (see
Figure 1).
Source: Munnell, Hou, and Webb (2014).
This pattern of increasing risk reflects the chang-
ing retirement landscape.1
The length of retirement
is increasing as the average retirement age hovers
at 63 while life expectancy continues to rise.2
At the
same time, replacement rates are falling for a number
of reasons. First, at any given retirement age, Social
Security benefits will replace a smaller fraction of
pre-retirement earnings as the Full Retirement Age
rises from 65 to 67 and Medicare premiums take a
larger chunk. Second, while the share of the work-
force covered by a pension has not changed over the
last quarter of a century, coverage has shifted from
defined benefit plans to 401(k) plans. In theory,
401(k) plans could provide adequate retirement
income. But individuals make mistakes at every step
along the way, and the median 401(k)/IRA balance for
household heads approaching retirement in 2013 was
only $111,000.3
Finally, interest rates have declined
dramatically, which means that households receive
much less income from their accumulated wealth.
30%
37% 38%
40%
38%
45% 44%
53% 52%
0%
20%
40%
60%
1989 1992 1995 1998 2001 2004 2007 2010 2013
Table 1. Percentage “At Risk” in NRRI versus
Self-Reported “At Risk” by Income, 2004 and 2013
Source: Authors’ calculations and 2004, 2013 SCF.
Low 58% 54% 62% 60%
Middle 46 41 58 52
High 41 36 51 43
All 48 44 57 52
Income
group
At risk, 2004 At risk, 2013
Self-reported NRRI Self-reported NRRI
Table 2. Percentage “At Risk” in NRRI versus Self-
Reported “At Risk” by Age, 2004 and 2013
Source: Authors’ calculations and 2004, 2013 SCF.
30-39 51% 48% 59% 59%
40-49 50 44 57 52
50-59 44 35 55 45
All 48 44 57 52
Age
group
At risk, 2004 At risk, 2013
Self-reported NRRI Self-reported NRRI
3. Issue in Brief 3
percentage of households that self-report being at risk
is a bit higher than the NRRI. The difference might
be due to two factors. First, NRRI households are not
considered at risk if their replacement rate is within
10 percent of their target – the replacement rate
needed to maintain their standard-of-living – whereas
no such cushion exists for the self-reported responses.
Second, the SCF does not prompt people to consider
their housing wealth, while the NRRI assumes house-
holds will tap this wealth through a reverse mortgage.
In terms of patterns by group, lower-income and
younger households are more likely to be at risk.
Interestingly, high-income and older households have
the greatest gap between self-reported and NRRI per-
centages at risk. Nevertheless, despite shortcomings
in financial knowledge as reported in the literature,
households in the aggregate seem to have a good “gut
sense” of their financial situation.4
Household Self-Assessments
vs. the NRRI
Even if aggregate perceptions match the NRRI, it
does not mean that individual households have a
correct assessment. For example, all of the individual
households could get it wrong, but their errors could
offset each other – i.e., half of households could
incorrectly think they are at risk while the other half
incorrectly think they are not at risk. Thus, the fol-
lowing exercise examines how well individual house-
holds perceive their retirement risk by matching their
self-reported status to their NRRI results in 2004 and
2013.
Quadrants I and IV in Tables 3 and 4 show the
households whose self-assessment agrees with the
NRRI – they report not having enough to maintain
living standards and the NRRI says they are at risk, or
they report being adequately prepared and the NRRI
says they are not at risk. In both years, 57 percent of
households appear to have realistic expectations about
how they will fare in retirement.5
The consistency of
these results is surprising given that the SCF survey
is not longitudinal, so the interview responses in the
two time periods do not come from the same house-
holds. The only difference between the 2004 and
2013 results is that, as conditions deteriorated after
the financial crisis, 8 percent of households moved
from a correct assessment that they were not at risk
(Quadrant IV) to a correct assessment that they were
at risk (Quadrant I).
Quadrant II shows households that appear to be
overly concerned – they report being inadequately
prepared but the NRRI says that they are not at risk.
Twenty-four percent of the households fall into this
category in both 2004 and 2013. Quadrant III shows
that only 19 percent of households in both years
seem to be less worried than they should be. That
is, they report having enough resources to maintain
living standards when the NRRI says they are at risk.
Overall, then, 43 percent of households in 2013 (24
percent + 19 percent) do not have a good sense of
their preparedness.6
And, among this group, a larger
share is too pessimistic rather than too optimistic.
Table 3. Households “At Risk” and “Not at Risk,”
NRRI and Individual Perceptions, 2004
Source: Authors’ calculations and 2004 SCF.
At risk 25%
(Quadrant I)
24%
(Quadrant II)
Not at risk 19%
(Quadrant III)
32%
(Quadrant IV)
Household
response
NRRI
At risk Not at risk
Table 4. Households “At Risk” and “Not at Risk,”
NRRI and Individual Perceptions, 2013
Source: Authors’ calculations and SCF 2013.
At risk 33%
(Quadrant I)
24%
(Quadrant II)
Not at risk 19%
(Quadrant III)
24%
(Quadrant IV)
Household
response
NRRI
At risk Not at risk
What Explains Misperceptions?
The question is what characteristics cause a house-
hold to be “too worried” or “not worried enough,”
as opposed to getting it right. The analysis uses a
multinomial logit regression to explain the probability
of households ending up in one category or another.7
The explanatory variables include: risk aversion,
home ownership, type of retirement plan, education,
household type, and income and age group. The intu-
ition for selecting each variable is explained below.
4. • Risk aversion. If a household is not willing to take
any financial risk, it is classified as risk averse.
One would expect that a risk-averse household is
more likely to end up as “too worried,” and less
likely to end up as “not worried enough.”
• Own house. One would expect that owning a
house would increase the likelihood of being in
the “too worried” group and reduce the likeli-
hood of not being worried enough, because most
households do not plan to tap their home equity
to support general consumption in retirement.
• Have defined benefit plan. A household with
the prospect of a guaranteed lifetime income is
probably going to be secure in retirement. Thus,
households with a defined benefit plan should be
less likely to be “not worried enough” and more
likely to be “too worried.”
• Have a defined contribution plan. The danger with
defined contribution plans is “wealth illusion.”
That is, $100,000 looks like a lot of money to
many people even though it provides only about
$400 per month in retirement income. There-
fore, having a defined contribution plan would
be expected to increase the probability of being
“not worried enough” and have little effect on the
likelihood of being “too worried.”
• College degree. Education increases a household’s
time horizon and, thus, the probability of think-
ing ahead about well-being in retirement. Hence,
having a college degree would increase the
probability of falling into the “too worried” group
and reduce the probability of being in the “not
worried enough” group.
• Household type. Social Security provides a
spouse’s benefit equal to 50 percent of the benefit
of the higher-earning spouse, and couples may
not be aware of it before they claim benefits.
Thus, one would expect that being a married one-
earner household – compared to other household
types – would increase the probability of being in
the “too worried” group and reduce the probabil-
ity of being in the “not worried enough” group.
• Income group. High-income households receive
lower replacement rates from Social Security and
must save more on their own. If they underes-
timate this challenge, they may be “not worried
enough.” In contrast, Social Security provides
predictable income and a relatively high level of
replacement for low-income households, so this
group is less likely to misperceive their financial
circumstances.
• Age. Households that are closer to retirement
may better understand their situation, making
them less likely to be either “too worried” or “not
worried enough.”
The regression results presented below are for
2013 only, as the results for 2004 were very similar.8
Overall, the results in Figures 2 and 3 suggest that
Center for Retirement Research4
Figure 2. Effect of Each Variable on Being in the “Too Worried” Group, 2013
Note: Solid bars are statistically significant at least at the 10-percent level.
Source: Authors’ calculations.
-0.2%
-1.7%
-7.4%
-9.5%
5.0%
5.5%
1.6%
7.5%
16.3%
-1.3%
-20% -10% 0% 10% 20%
Age group
Age group
Middle income
High income
Married one-earner household
College degree
Have defined contribution plan
Have defined benefit plan
Own house
Risk averse
50-59
40-49
5. -1.9%
-4.4%
1.3%
2.2%
-5.6%
-7.1%
4.9%
-14.7%
-9.4%
-3.4%
-20% -10% 0% 10% 20%
Age group
Age group
Middle income
High income
Married one-earner household
College degree
Have defined contribution plan
Have defined benefit plan
Own house
Risk averse
Issue in Brief 5
those households with incorrect perceptions do so for
predictable reasons.9
The likelihood of being in the
“too worried” group stems mainly from not fully rec-
ognizing the value of potential income from owning
a home, being covered by a defined benefit plan, and
being eligible for a 50-percent spousal benefit from
Social Security (see Figure 2, on the previous page). A
little education about the value of various sources of
retirement income could reduce the size of the “too
worried” group.
The real danger in terms of misperceptions is
being in the “not worried enough” group. The key
drivers here are having a defined contribution plan
and being in the high-income group (see Figure
3). As noted, households with a 401(k) may suffer
from “wealth illusion,” not recognizing how little
income can be derived from their defined contribu-
tion balances. In addition, high-income households
may not recognize how much wealth accumulation is
required to maintain their standard of living. The 19
percent of households that do not recognize that they
are at risk are unlikely to undertake remedial action.
Perhaps better educational efforts could help here too,
such as focusing more on the amount of retirement
income that a given 401(k) balance could produce
rather than the total account balance. Unfortunately,
it is not clear that the 33 percent that correctly per-
ceive themselves to be at risk will take action either,
because of shortsightedness or pressing immediate
financial needs.
Conclusion
Despite recent literature indicating that households
suffer large gaps in their financial knowledge, nearly
three out of five have a good gut sense of their finan-
cial situation, and this finding holds both before and
after the financial crisis. In the aggregate, house-
holds’ self-assessments closely mirror the results
produced by the NRRI, suggesting that inadequate
retirement preparedness is indeed a widespread prob-
lem. Even on a household-by-household basis, almost
60 percent of households’ self-assessments agree with
their NRRI predictions. Moreover, households that
get it wrong do so for predictable reasons.
However, classifying households by the accuracy
of their perceptions about retirement security does
not answer the question of whether they are likely to
take remedial action. Under any circumstance, those
households that “worry too little” are the least likely to
change their saving or retirement plans. This group
accounts for 19 percent of households, which means
that a significant portion of the population needs to
get a better assessment of their retirement income
needs. The additional one-third of households that do
understand their plight may need less convincing to
act, but they still must act.
Figure 3. Effect of Each Variable on Being in the “Not Worried Enough” Group, 2013
Note: Solid bars are statistically significant at least at the 10-percent level.
Source: Authors’ calculations.
50-59
40-49
6. Center for Retirement Research6
Endnotes
1 For details on the changing landscape, see Ellis,
Munnell, and Eschtruth (2014).
2 Munnell (2015).
3 This amount includes Individual Retirement Ac-
count (IRA) balances because most of the money in
IRAs is rolled over from 401(k) plans. For details on
401(k) missteps, see Munnell (2014). Munnell et al.
(2016) shows that the shift from defined benefit plans
to 401(k)s has reduced replacement rates.
4 For studies on individuals’ financial knowledge, see
Gustman and Steinmeier (2004), Van Rooij, Lusardi
and Alessie (2012) and Lusardi and Mitchell (2011a)
and (2011b).
5 The NRRI relies on self-reported income and
wealth data to determine whether households are at
risk. Many studies have shown that these data ag-
gregate well to national averages. But an unknown
percentage of households may misreport income
or wealth, and the NRRI may therefore incorrectly
assign their “at risk” status, and thus their sense of
their retirement preparedness, while at the same
time correctly measuring the overall percentage at
risk. Another explanation for the discrepancy is that
individual households may apply a different yardstick
in assessing their financial preparedness than the one
embodied in the NRRI.
6 A recent study of New Zealanders found a broadly
similar result; about one-third of households had an
inaccurate perception of their retirement prepared-
ness (Lissington, Matthews, and Naylor 2016).
7 The multinomial logit model allows the analysis to
compare the “too worried” group (and, separately, the
“not worried enough” group) only to the two groups
with an accurate perception. A probit model could be
used instead, but it would compare the one group of
interest to all three remaining groups in the sample,
rather than just the two groups with accurate percep-
tions.
8 Interestingly, one result that was different for the
“too worried” group was having a defined contribu-
tion (DC) plan. In 2004, having a DC plan reduced
the probability that a household would be “too wor-
ried.” In other words, having the account seemed
to provide a degree of security about retirement
preparedness. In 2013, however, having a DC plan
increased the likelihood of being “too worried,” which
suggests that the financial crisis made these house-
holds much more concerned about the stability and
sufficiency of their 401(k) balances.
9 The effect of each variable listed in Figures 2 and
3 is the marginal effect from the multinomial logit
model. It shows the effect of a 1-percent change in the
independent variable on the change in the probability
of the dependent variable. See the Appendix for full
results.
7. Issue in Brief 7
References
Ellis, Charles D., Alicia H. Munnell, and Andrew D.
Eschtruth. 2014. Falling Short: The Coming Retire-
ment Crisis and What to Do About It. New York,
NY: Oxford University Press.
Gustman, Alan and Tom Steinmeier. 2004. “What
People Don’t Know about Their Pensions and
Social Security.” In Private Pensions and Public
Policies, eds. William Gale, John Shoven and Mark
Warshawsky, 57-125. Washington, DC: Brookings
Institution.
Lissington, Bob, Claire D. Matthews, and Michael
Naylor. 2016. “Self-Assessment of Retirement
Preparedness.” Working Paper. Palmerston North,
New Zealand: Massey University.
Lusardi, Annamaria and Olivia S. Mitchell. 2011a.
“Financial Literacy and Retirement Planning in
the United States.” Journal of Pension Economics
and Finance 10(4): 509-525.
Lusardi, Annamaria and Olivia S. Mitchell. 2011b.
“Financial Literacy and Planning for Retirement
Wellbeing.” Working Paper 17078. Cambridge,
MA: National Bureau of Economic Research.
Munnell, Alicia H. 2015. “The Average Retirement
Age – An Update.” Issue in Brief 15-4. Chestnut
Hill, MA: Center for Retirement Research at Bos-
ton College.
Munnell, Alicia H. 2014. “401(k)/IRA Holdings in
2013: An Update from the SCF.” Issue in Brief
14-15. Chestnut Hill, MA: Center for Retirement
Research at Boston College.
Munnell, Alicia H., Wenliang Hou, Anthony Webb,
and Yinji Li. 2016. “Pension Participation, Wealth
and Income: 1992-2010.” Working Paper 2016-3.
Chestnut Hill, MA: Center for Retirement Re-
search at Boston College.
Munnell, Alicia H., Wenliang Hou and Anthony
Webb. 2014. “NRRI Update Shows Half Still Fall-
ing Short.” Issue in Brief 14-20. Chestnut Hill, MA:
Center for Retirement Research at Boston College.
U.S. Board of Governors of the Federal Reserve Sys-
tem. Survey of Consumer Finances, 2004 and 2013.
Washington, DC.
Van Rooij, Maarten, Annamaria Lusardi, and Rob
J. Alessie. 2012. “Financial Literacy, Retirement
Planning and Household Wealth.” The Economic
Journal 122.560 (2012): 449-478.
9. Table A1. Marginal Effect of Selected Variables on
Being in the Indicated Group
Note: Robust standard errors in parentheses. Marginal effects
are significant at the 1-percent level (***), 5-percent level
(**), or 10-percent level.
Source: Authors’ calculations.
Variables
Risk averse -0.013 -0.034***
(0.008) (0.008)
Own house 0.163*** -0.094***
(0.009) (0.007)
Have defined benefit plan 0.075*** -0.147***
(0.009) (0.010)
Have defined contribution plan 0.016* 0.049***
(0.008) (0.008)
College degree 0.055*** -0.071***
(0.008) (0.008)
Married one-earner household 0.050*** -0.056***
(0.015) (0.014)
High income -0.095*** 0.022**
(0.011) (0.010)
Middle income -0.074*** 0.013
(0.109) (0.009)
Age group 50-59 -0.017* -0.044***
(0.010) (0.009)
Age group 40-49 -0.002 -0.019**
(0.010) (0.009)
Number of observations 15,643
Pseudo R-squared 0.039
“Too worried”
group
“Not worried”
enough group
Issue in Brief 9