70 Is the New 65
John Mauldin
As some of us know far too well, forecasting the future with any precision is extremely difficult. There’s at least one exception to the rule, though. Population trends show themselves decades and even centuries in advance. If we know how many people were born in a given year, we can extrapolate what the population will look like far in the future.
On the other hand, demographic forecasting still requires assumptions. At what age will people start having children, and how many will they have? How will new medical advances affect life spans? When will people start working, stop working, and enter retirement? Small changes in any of those assumptions can quickly affect population numbers.
Today’s Outside the Box wrestles with that last question. In the United States we allowed the federal government to set 65 as the retirement age by making Social Security available to most workers at that point in their lives. The retirement age is going up to 67 for the younger members of the Baby Boom generation, but even that may be too “young” to retire in the future.
We Baby Boomers were never big on conformity. Voluntarily or not, a large number of us fully intend to stay in the workforce to age 70 and beyond. If 70 is the new 65, we will see significant changes in the ways people spend their money and the kinds of investments they want.
Matthew Tracey and Joachim Fels of PIMCO outline some of the possibilities in this report. I found it very interesting, and I think you will, too.
Speaking of things changing, the weather in Texas has been nothing like anything in the past. It is mid-February and I’m having to turn the air conditioner on at night. The forecasters tell us it’s going to get into the 80s on Friday. Talking with my long-term Texas friends, none of us can remember weather like this. Cooler than normal summers, milder than normal winters. I guess it’s a good thing it’s not like this every year, because then we’d have a wave of tax refugees showing up from California. Then again, this is Texas. If we wait a bit I’m sure we’ll get our usual ice storms and other nasty stuff. Winter is coming. Maybe.
I am struggling to keep up with the research my 20-some teams are developing for the chapters of The Age of Transformation. Thankfully I have a small team helping me review the research, which is on top of the research I’m doing for the five or so chapters that I’m personally writing. Plus, there’s my regular reading for doing the weekly letters and so forth. It is forcing me to sort through the pile of items in my inbox as to what is must-read, what can wait, and what I just don’t have time for. I really am learning to depend on people to make sure the things that I must read get on my radar screen.
I’m going to go ahead and hit the send button, as I have to prepare for an interview with CNBC Asia on Japan and related topics. You have a great week, and I hope that wherever you are, your weather is as good as ours.
Your marveling at the speed of things changing analyst,
John Mauldin, Editor
Outside the Box
70 Is the New 65: Demographics Still Support 'Lower Rates for
Longer'
By Matthew Tracey and Joachim Fels
PIMCO.com, February, 2016
PIMCO.com, February, 2016
The so-called demographic cliff remains at least a
decade away; meanwhile, global demographics should continue fueling the savings
glut.
Is global aging about to end the savings glut?
Some observers think so. More and more baby boomers are reaching retirement
age, and they will soon not only save less but also start to dump their
accumulated assets to fund retirement … or so the story goes. If this were
true, the consequences for interest rates would be profound. The real long-term
equilibrium interest rate, which has been on a secular downtrend for decades
partly due to strong working-age cohorts saving hard for retirement, would
start to rise – and what we here at PIMCO call The New Neutral might soon be
history.
We strongly disagree with that thesis of an
imminent demographics-induced savings drought. Rather, we have argued in recent
work that the global excess supply of saving over investment, which has been
largely responsible for the secular decline in equilibrium interest rates, is
not only here to stay but likely to increase further in the coming years for a
host of reasons including
demographics (see PIMCO Macro
Perspectives, “No End to the Savings Glut,” September 2015).
As a
consequence, we continue to expect the fundamental forces of elevated desired
saving to keep the equilibrium real rate depressed and to limit the extent to
which other (cyclical) factors can drive up market interest rates.
However, given the popularity of the thesis that
demographics will soon end the savings glut, we undertook a deep dive into the
data to investigate the link among demographics, saving behavior and the demand
for fixed income assets – with some surprising results. Here’s what we found.
A ‘demographic
reversal?’ Not so fast!
People of the world, we’re getting old. It’s a
well-known fact that, after decades of decline, the global dependency ratio –
traditionally defined as the ratio of individuals younger than 15 and older
than 64 to the working-age population aged 15-64 – is now rising (see Figure
1).
Some financial market observers argue that this
demographic trend reversal will begin to drive interest rates higher, and soon.
Why? First, a declining share of high-saving workers and a rising share of
dissaving elderly will (the argument goes) erode the demand for saving – and
drive interest rates higher via the savings-investment equilibrium. Second,
these observers argue, a rapidly growing share of retirees will have to consume
(i.e., sell down) their financial asset holdings to fund spending in
retirement, and these drawdowns will create selling pressure in financial
markets that pushes asset prices down and interest rates up.
Our core thesis in a nutshell: Yes, global aging
may someday drive U.S. interest rates structurally higher. But “someday”
remains at least a decade away – for two reasons. First, we proffer that
global saving will remain stronger than many expect, supporting a low global
neutral interest rate. (As investors, we care about the neutral rate because it
anchors fixed income yields in the market.) Second, U.S. demographic demand for
fixed income assets should remain robust until at least 2025 – and in the
meantime should continue to put downward pressure on market yields, all else
equal. Combine a low global “anchor” and strong domestic fixed income demand,
and what do you get? Lower rates for longer in the U.S.
Continuing robust demographic demand for
saving
Remember the link between saving and interest
rates: In the savings-investment equilibrium, rising demand for saving pushes
down the equilibrium (or neutral, or natural) rate of interest, all else equal,
and vice-versa. Our task, then, is to assess how demographic changes affect
aggregate saving. We find that the traditional “dependency ratio,” used in many
other studies on this topic, is flawed. We suggest two modifications to address
those flaws. First, the young, considered “dependents,” contribute very little
to global saving and dissaving in dollar terms (they’re “non-savers”). We
therefore prefer to focus on the ratio of “Peak Savers” (mature adult workers
who earn and save a lot) to “Elderly” (who save less as they age and ultimately
consume their savings in retirement). Let’s preliminarily define “Peak Savers”
as individuals aged 35 to 64, for two reasons:
·
People
35–64 have generally exhibited much higher savings rates than people in younger
and older age groups;
·
People
35–64 earn considerably more income than people younger and older – so for any
given savings rate, this age group’s saving behavior will have an outsized
effect on saving and investment flows in dollar terms.
Let’s preliminarily define “Elderly” as everyone
65 and older (the traditional definition). Thus, the global Peak Savers versus
Elderly ratio in Figure 2 reflects a static
35–64 Peak Saver cohort – and reveals what appears
to be a demographic cliff in about year 2010. Those who argue that demographic
support for saving will fall sharply in the coming years typically will try to
prove their point using a ratio like this one.
But we ask: Is it sensible to define the Peak
Saver and Elderly groups by the same static
age ranges over long periods of time? Put differently: Might working and saving
behavior evolve over time, warranting a dynamically
modified dependency ratio? Seniors’ ability to work (and save)
later in life should continue to rise; in our increasingly services-based
“knowledge economy,” jobs are becoming less physically demanding and often
require more experience, while advances in health technology boost functional
age in life’s later stages. Seniors’ willingness (and incentives) to work
longer also should rise along with their ability.
True, the retirement age, globally, has not kept
pace with rising longevity. But policymakers are slowly catching on. In the
U.S., the Social Security full-benefit retirement age is increasing to 67 and
will go higher still – a government incentive telling people to stay in the
workforce. Meanwhile, years of low interest rates have left impending retirees
playing catch-up in retirement saving. More generally, around the world, longer
lives must ultimately be supported by longer working
lives. Anything less will prove unsustainable. Our colleague Jim Moore summed
up the state of affairs (in the U.S.) in a PIMCO Viewpoint from 2012: “Work a little longer. Save a
little more. Get by with a little less.1
We think this insight applies abroad as well. In
fact, global trends already underway support our argument that people will work
later and later in life. In many economically important geographies – notably
the U.S., eurozone, UK and Japan – senior (age 65+) labor force participation
has been trending higher. And China is contemplating steadily raising its retirement
age in the coming years.
However, what matters most for global saving
demand are those who earn the most income. Consider the U.S. as an example.
Top-income-quintile households control nearly two-thirds of U.S. household
income, three-quarters of household wealth and more than 80% of household
financial assets. Apart from the major social ramifications of wide (and
widening) income and wealth inequality, the implications for aggregate saving
are critical: Rather obviously, high earners’ working and saving behavior has
an outsized effect on global saving in dollar terms. If the highest earners are
working (and saving) later in life, we should pay attention. Witness the
dramatic rise in labor force participation within the top income quintile
(Figure 3): Over 60% of top-quintile individuals in the 65–74 age group are
employed or seeking work, a 19-percentage-point increase in participation over
the 15 years through 2013. 2 Moreover, participation among
top-income-quintil e seniors 75 and older has more than doubled over the same period.4,/sup>
What about seniors’ late-life saving behavior?
Consider the top two income
quintiles, collectively accounting for about 80% of U.S. personal income. Based
on 2014 data from the BLS’s Consumer Expenditure Survey, these high earners
exhibit no decline in savings rates as they enter retirement (due in part to a
strong bequest motive and high conservatism). In Figure 4, note how high and
consistent these top earners’ savings rates remain even in their late 60s and
70s.
(Aside: We find it curious that savings rates,
based on the BLS’s Consumer Expenditure Survey, do not become negative for
lower-income-quintile seniors even in their late 70s. We suspect that other
data sources may show a negative savings rate for these elderly groups, likely
due to methodological differences in data collection. Our focus here, however,
is on age-related trends
in saving behavior rather than savings rates
themselves.)
To recap: The most impactful seniors are working
(and saving) later in life as functional age and the duration of retirement
both increase.3 Therefore, our preferred measure of the demographic
support for saving is a dynamic, not static, ratio that accounts for the trend
toward longer working lives. Let’s revisit our Peak Savers versus Elderly ratio
from Figure 2. In decades past, age 64 may well have been the sensible upper
bound for the Peak Saver group. But what about the coming decades? In Figure 5,
we have added a dynamic ratio (red line) that assumes seniors work roughly five
years later in life in 2050 than they did in 2000.
In other words, our age
definition of “Peak Saver” evolves dynamically from 35–64 in 2000 to 35–69 by
2050, and consequently our definition of “Elderly” evolves dynamically from 65+
to 70+ over the same period.
What a different picture the dynamic ratio paints!
It suggests that demographic support for saving could well be as strong a
decade from now as it has been in recent decades – and illustrates the extent
to which traditional static ratios may be flawed.
We concede that our dynamic ratio forecast is only
a guess as to what the future may look like if current trends persist. But
there is some method to the madness.
For example, the reason we start to phase
the 65- to 69-year-olds into our Peak Saver group specifically in 2000 is that
senior labor force participation began to rise rapidly in that year (after two
stagnant decades). Our five-years-later-in-life-by-2050 employment assumption
is slightly more arbitrary, but reasonable given that, globally, the largest
increases in retirement age likely lie ahead of us. And our dynamic ratio does
not account for the rising share of seniors 70+ who remain working, introducing
an element of conservatism to our assumptions. So while our dynamic ratio
embeds some simplifying assumptions, to be more scientific risks missing the
forest for the trees. Almost regardless of the assumptions used, if you define
a dependency ratio dynamically – based even loosely on observable tr ends – you
are likely to paint a very different (and more accurate) picture of the future
than you will paint using a static ratio.
What about the rest of the world? It appears we’ve
made an argument about global demographics supported mainly with U.S. data. However,
publicly available data for other economically significant regions does not
permit as granular an analysis as we have shown for the U.S. We do have reason
to believe similar trends are occurring outside the U.S.: Elderly labor force
participation is rising in Europe, the UK and Japan, and some countries –
including China – are contemplating raising the retirement age. In Japan, whose
demographic cliff materialized many years ago, senior labor force participation
has been trending higher, and as a result the labor force shrank only about
0.8% over the past decade even as the “working-age population” (aged 15 to 64)
fell almost 9%. Patterns like this one are likely to repeat in other aging
countries as societies adapt to meet their demographic challenges.
Bottom line: The people who move the needle most
in saving demand, the highest earners, are the people working and saving later
in life. This trend should be a tailwind for saving demand in the years to come
that will push the global demographic cliff at least a decade into the future –
and support a low global neutral interest rate, per the savings-investment
equilibrium. 70 is the new 65!
U.S. household (demographic) demand for fixed
income assets: a decade-long tailwind for bonds
We’ve just argued that demographics should help
keep the global neutral rate low over the coming decade – which means that
market yields in the U.S. should have a low “anchor.” But waves of baby boomers
are retiring (albeit, as we have argued above, increasingly later), and many
will eventually draw down (i.e., sell) their financial asset holdings to fund
late-life consumption. Are we fast approaching the point when boomer drawdowns
create selling pressure in fixed income markets that pushes interest rates
higher? Or might U.S. aging (boomers included) actually bolster the (net)
demand for bonds and help maintain a low ceiling for market yields?
Consider two key observations.
·
First,
as we should expect, investors generally de-risk away from equities and toward
fixed income with age – most aggressively once they reach their 60s (and
beyond).5
·
Second,
individual asset accumulation and drawdown patterns vary significantly by
income level. In the U.S., individuals in the lowest income quintile tend to
sell their limited financial assets beginning in their 50s and completely
exhaust their assets by, or before, death (relying on social assistance to meet
their basic needs in life’s latest stages). Middle-income individuals tend to
draw down financial assets beginning in their 60s but not at a rate that would
deplete their assets before death. Individuals in the highest income quintile,
however, are shown to have rising
financial asset balances until roughly age 80 (after which they decline only
very gradually).
In other words,
for top-income-quintile individuals, portfolio drawdowns don’t tend to begin
until roughly age 80 (an important point). The highest earners have
historically been able to fund retirement consumption from income (generally employment
income, invest ment portfolio income and annuitized income), “leaving their
financial assets virtually untouched.”6
Here’s the key: Top-income-quintile households own over 80% of
U.S. household financial assets. Consider how significantly this
group’s future asset accumulation and drawdown profile will impact financial
markets!
Back to our question about whether U.S.
demographics will be a headwind or tailwind for bond flows in the years ahead.
For starters, we assess when (demographics-driven) bond buying might peak
relative to bond selling. We define “Bond Buyers” as individuals aged 60–74 and
“Bond Sellers” as individuals 80 and older. These age definitions are somewhat
arbitrary, but they’re based on the two previously introduced empirical
observations about households in the top quintile of the U.S. income
distribution (which hold over 80% of U.S. household financial assets):
1. Bond buying tends to peak
during individuals’ 60s and early 70s (aggressive de-risking);
2. Bond selling tends to peak
in the years after age 80 (as individuals sell down their financial assets to
fund consumption in retirement).
Figure 6 shows the ratio of Bond Buyers to Bond
Sellers, which we use to gauge when net demographic buying demand might
theoretically peak. On this metric, U.S. demographic demand for bonds should
continue to rise in the next five years or so before peaking and may still be
as strong in 2025 as it is today. (Our age definitions are based on patterns
observed among U.S. households, so we focus primarily on the blue U.S. line in
the figure. We include a global version of the Buyers versus Sellers ratio as
well – the green line – which reveals an even later potential peak in global demographic demand for
bonds.7
Our interpretation of this Buyers versus Sellers
ratio assumes that each buyer exerts about the same influence on markets as
each seller, an assumption that may be conservative given high-earning sellers
draw down their portfolios only very gradually, whereas buyers likely will be
de-risking aggressively in their 60s and early 70s. We “stress test” this
assumption and result with scenario analysis in the Appendix.
Next, we explore the demographics of U.S.
financial asset ownership at a very high level. Figure 7 shows household
financial asset holdings by both age and income.8
The lion’s share of the $31 trillion in U.S.
household financial assets9 ($21 trillion, or about 70%) is held
within – or over the next 10 years will be held within – age cohorts that typically
need to grow their fixed income allocation. This $21 trillion, outlined in
green in Figure 7, is expected to remain in an accumulation or de-risking phase
and won’t enter a drawdown phase within the next decade (based on the
age-related asset drawdown patterns we described earlier). This $21 trillion
will likely be a demographic tailwind
for bonds over the next decade (especially for municipal bonds given high
earners’ need for tax-free income). Conversely, only about $5 trillion
(approximately 15%) of household financial assets seems likely to be a headwind
for bonds during this period (outlined in red).
One caveat: Many factors other than demographics
influence investors’ asset allocation decisions – among them changes in
valuations, evolving expectations about future asset returns, individual risk
preferences, U.S. investor preference for domestic versus foreign assets,
foreign investor preference for U.S. assets, and market disruptions that may
trigger significant portfolio rebalancing. Our analysis here focuses only on
demographic effects, holding all else equal.
Now let’s go a level deeper. In the Appendix we
model the potential demographics-related asset flows we might see over time
from the gradual de-risking and drawdown of household financial assets. We
analyze 10 unique scenarios in order to test a range of assumptions. Our
“baseline” scenario reflects a set of assumptions about de-risking behavior and
asset decumulation that we think is realistic (and possibly conservative) based
on historical patterns. Our modeling suggests that U.S. demographics-driven
fixed income inflows are likely to be almost as strong 10 years from now as we
project them to be today – and that demographics may not be a material headwind
for bonds until the 2030s. How can we explain these conclusions? In our
analysis, for at least the next decade, de-risking flows and rebalancing flows
into fixed income more than compensate for seniors’ portfolio drawdowns. In
stress testing our baseline assumptions we found it hard to come up with a
plausible scenario in which U.S. demographics become a fixed income headwind
within 10 years. Yet we found it easy to imagine realistic scenarios in which
demographic demand for bonds remains robust for the next 15 years or more.
Consider as an example the high-earning elderly,
for whom longevity risk is rising rapidly as life-extending medical
technologies proliferate. High earners, historically, have been overly cautious
in recalibrating their spending to meet anticipated future needs – a finding
that could warrant an even more gradual asset-drawdown trajectory for this next
generation of retirees than we have modeled based on historical experience. See
the Appendix for our assumptions, baseline scenario modeling and alternative
scenarios.
A brief aside: Our focus here has been U.S.
demographics and, implicitly, U.S. fixed income. However, U.S. demographics are
likely to influence global fixed income markets given U.S. households account
for over 40% of global household financial assets. For context, Western Europe
and Asia each account for about 25%.10
Finally, a quick note on changes in the
composition of household retirement savings. The shift from defined benefit
(DB) to defined contribution (DC) plans in the U.S. persists, and in our
estimation U.S. DB plans hold a lower allocation to bonds than a market-average
glide path suggests is optimal for DC participants.11 In aggregate,
therefore, the continued shift toward DC may represent an additional tailwind
for bonds in the coming years.
Bottom line on U.S. aging and the demand for
bonds: Persistent demographic support for fixed income should, all else equal,
drive net flows into bonds and help maintain low yields over the next decade.
‘Speed read’ and
key conclusions
Some financial market observers believe in the
following dramatic scenario:
·
We’ve
just gone over a demographic cliff; globally, the ratio of high-saving adult
workers to dissaving elderly is now declining. This demographic reversal will
erode the demand for saving.
·
The
global savings glut will reverse as the demand for saving falls, pushing the
global neutral interest rate higher.
·
Baby
boomers in the U.S. will compound the problem as they sell their financial
assets (including bonds) to fund retirement consumption, driving U.S. fixed
income yields higher.
In this note, we challenge traditional thinking
about the timing of the feared “demographic cliff.” A demographics-induced structural rise in U.S. interest rates
remains at least a decade away:
- Global demand for saving will
remain robust, supporting a low global neutral interest rate (the “anchor”
for U.S. fixed income yields):
o Traditional dependency
ratios – which use fixed, static age definitions – are flawed because they fail
to account for how the world is changing.
o U.S. elderly, especially
the highest earners, are working and saving later in life. High earners matter
a lot because they drive the lion’s share of global saving. 70 is the new 65.
o Similar trends can be
observed in economically significant economies outside the U.S.
o We argue for a dynamic,
not static, ratio of mature adults to elderly that does account for how working
and saving behaviors are changing. Our dynamic ratio suggests that demographic
support for saving may be as strong over the next decade as it has been over
the past several. Possibly stronger.
o Strong saving demand
should support a low global neutral interest rate in the coming years – and
should continue fueling the global savings glut.
- In financial markets, strong
U.S. demographic demand for fixed income assets should – all else equal –
help maintain low U.S. bond yields over the next decade:
o The lion’s share of U.S.
household financial assets is held within age cohorts that will need to grow
their fixed income allocation over the next ten years.
o Top-income-quintile
households own over 80% of these assets, and high earners sell financial assets
only very gradually in retirement to fund consumption.
o For another decade or
more, demographics should remain a net contributor to fixed income flows, as
high earners’ de-risking into bonds should dominate bond outflows due to
portfolio drawdowns.
Combine a low global neutral interest rate and
strong domestic demand for bonds, and what do you get? Lower rates for longer in the
U.S.
The authors would like to thank PIMCO colleague
Jim Moore for his contributions.
Appendix: U.S. household financial assets and fixed
income
flows – scenario analysis
This Appendix details the assumptions used in our
baseline scenario for U.S. (demographics-driven) fixed income flows and offers
a number of alternative scenarios.
Baseline scenario assumptions:
- Financial asset portfolios consist
of two asset types (for simplicity): “risk assets” (excluding fixed
income) and fixed income.
o Long-term annual risk
asset return: 5% nominal.
o Long-term annual fixed
income return: 2.5% nominal.
·
Investors
de-risk their portfolios into fixed income over time according to a
market-average glide path,12 interpolated as necessary. (We
conservatively assume that de-risking into fixed income ceases at age 75 and
that investors’ asset allocations remain constant thereafter. This assumption
is driven by a lack of available data on market-average glide path allocations
for ages older than about 75.)
·
Each
year, top-income-quintile households re-optimize to draw down 50% of their
financial assets by the end of their planning horizon, beginning at age 80 and
ending at age 95. (50% may be a conservatively high drawdown percentage.)
·
Each
year, households in the bottom four income quintiles re-optimize to draw down
75% of their financial assets by the end of their planning horizon, beginning
at age 65 and ending at age 90. (75% may be a conservatively high drawdown
percentage.)
·
Financial
asset drawdowns occur proportionally across risk assets and fixed income. (This
assumption is fair to conservative, given there is evidence that people draw
down their riskiest assets first.13)
·
Financial
asset portfolios do not exist in perpetuity; mortality effects (based on the
most recent mortality tables from the Society of Actuaries) lead to bequests
that generate “re-risking” flows from fixed income into risk assets.14
Alternative scenarios:
Each alternative scenario represents a
modification relative to our baseline scenario.
·
Alternative
1: De-risking into fixed income proves significantly faster than expected (ultimate
fixed income allocation of 50% is reached 10 years earlier than baseline glide
path suggests).
·
Alternative
2: De-risking into fixed income proves significantly slower than expected (ultimate
fixed income allocation of 50% is not reached until 10 years after baseline
glide path suggests).
·
Alternative
3: Seniors 50+ ultimately de-risk much less significantly than baseline glide
path suggests (fixed income allocation reaches 15% at age 50, per glide path,
but then flat-lines for 10 years before gradually increasing to a level only half that suggested by baseline
glide path, i.e., a terminal allocation of 25% instead of 50%).
·
Alternative
4: Annual fixed income returns equal annual risk asset returns, such that market-return-driven
rebalancing flows no longer support fixed income (5% annual nominal return
assumed for both asset types). (This scenario has a natural hedge property; if
ex ante fixed income returns ever were expected to equal ex ante risk asset
returns, the relative attractiveness of fixed income probably would increase on
a risk-adjusted basis, likely triggering non-demographics-related reallocations
into fixed income – which we have not
modeled here.)
·
Alternative
5: Top-income-quintile households re-optimize each year to ultimately draw down
75% of their financial assets by the end of their planning horizon, while
households in the bottom four quintiles re-optimize to draw down 100% (for both
groups, a far higher drawdown percentage than is likely).
·
Alternative
6: Top-income-quintile households commence drawdowns a full decade earlier than
history suggests is likely, i.e., at age 70 (if anything, as life expectancies
and planning horizons lengthen, one might expect drawdowns to begin later).
·
Alternative
7: A combination of alternatives 5 and 6 (i.e., a highly conservative mix of
assumptions).
·
Alternative
8: Households commence drawdowns five years later and lengthen their planning
horizon by five years (optimistic, but plausible given rising longevity risk
and rising labor force participation among the high-earning elderly).
·
Alternative
9: Top-income-quintile households re-optimize to draw down 25% of their
financial assets by the end of their planning horizon (instead of 50%),
consistent with a high bequest motive and historical excess conservatism during
retirement.
The chart below shows our estimate of future
demographics-driven U.S. household fixed income flows by scenario. These projections are NOT meant to be
interpreted as forecasts of the actual dollar volume of flows,
in part because the $31 trillion stock of household financial assets used to
model these flows omits certain large asset pools (see our technical note
further on). So
focus on the trends
depicted, not on the dollars.
As you can see in the chart, across almost all of
our scenarios demographics remain a fixed income tailwind for the next 10
years, and in most scenarios longer. Note that this analysis may lean
conservative in that we have modeled potential flows based only on the existing stock of financial
assets. Yet every year, mature adult workers (especially the high income
earners) will invest some portion of their savings in financial assets, including
bonds, both inside and outside their retirement plans. These flows, all else
equal, represent a tailwind for all financial assets that we haven’t attempted
to model.
Finally, a technical note on our primary source
for U.S. household financial asset data: the Federal Reserve’s 2013 Survey of
Consumer Finances. To our knowledge, there are two primary sources for U.S.
household balance sheet detail: the Federal Reserve’s Survey of Consumer
Finances (“SCF”), a triennial survey of a cross-section of U.S. households, and
the U.S. national flow of funds accounts. We use the SCF, which is widely used
in Federal Reserve analysis, academic research at major economic research
centers, and private financial industry analysis and writings. The SCF is, to
our knowledge, unparalleled in its demographic granularity across age groups,
income quintiles and other key variables.
Significant differences are worth highlighting
between the SCF and the household balance sheet data contained in the U.S.
national accounts. Of note, the 2013 SCF excludes about $19 trillion in DB
pension entitlements and $2.4 trillion in assets of nonprofit institutions. As
a result of these and certain other omissions, the SCF identifies a materially
lower total value for U.S. household financial assets than the national
accounts identify. The question,
for us, is whether there is any reason to think that the omissions made by the
SCF, notably DB pension entitlements, will bias our results. We see
no obvious bias. At a high level, DB pension plan asset allocations tend to be
a function more of the level of interest rates and plan funding status than of
the age profile of plan beneficiaries. Also, as we’ve argued in the body of our
note, as the U.S. shifts from defined benefit to defined contribution schemes
we may see additional support for fixed inc ome given that DB plans seem to
allocate less to bonds than a market-average glide path suggests is optimal for
DC participants. For these reasons, we think using a source that excludes DB
pension entitlements likely leads us – if anything – to underestimate
demographics-related fixed income demand over the next decade.
See the recent research paper linked below, from
the Federal Reserve, for a more detailed explanation of the differences between
SCF data and data from the U.S. national flow of funds accounts, as well as a
defense of the use of SCF data in economic research:
Works consulted
·
Mercedes
Aguirre and Brendan McFarland, “2014 Asset Allocations in Fortune 1000 Pension Plans,”
Towers Watson, October 2015.
·
Robert
Arnott and Denis Chaves, “Demographic Changes, Financial Markets, and the
Economy,” Financial Analysts Journal Volume 68 Number 1, 2012.
·
Charles
Bean et al., “Low for Long? Causes and Consequences of Persistently Low
Interest Rates,” Geneva Reports on the World Economy 17, International Center
for Monetary and Banking Studies, October 2015.
·
Lisa
Dettling et al., “Comparing Micro and Macro Sources for Household Accounts in
the United States: Evidence from the Survey of Consumer Finances,” Finance and
Economics Discussion Series 2015-086, Washington: Board of Governors of the
Federal Reserve System, 2015.
·
“The
Eurosystem Household Finance and Consumption Survey,” Statistical Paper Series
No 2, European Central Bank, April 2013.
·
“2013
Survey of Consumer Finances (SCF),” Federal Reserve, September 2014.
·
Michael
Gapen, “Demand for safe havens to remain robust,” Barclays Equity Gilt Study,
February 2013.
·
Michael
Gavin, “Population dynamics and the (soon-to-be-disappearing) global ‘savings
glut,’” Barclays, February 2015.
·
Charles
Goodhart et al., “Could Demographics Reverse Three Multi-Decade Trends?” Morgan
Stanley, September 2015.
·
Dr.
Michaela Grimm et al., “Allianz Global Wealth Report 2015,” Allianz SE, August
2015.
·
Markus
Lorenz et al., “Man and Machine in Industry 4.0: How Will Technology Transform
the Industrial Workforce Through 2025?” Boston Consulting Group, September
2015.
·
Dr.
Susan Lund, “The Impact of Demographic Shifts on Financial Markets,” McKinsey
Global Institute, June 2012.
·
“Pension
Markets in Focus,” The Organisation for Economic Co-operation and Development,
2015.
·
James
Poterba et al., “The Composition and Draw-Down of Wealth in Retirement,” NBER
Working Paper 17536, October 2011.
·
Karen
Smith et al., “How Seniors Change Their Asset Holdings During Retirement,”
Center for Retirement Research at Boston College Working Paper 2009-31,
December 2009.
1 PIMCO Viewpoint
“What’s Your Number at the Zero Bound”, by Dr. James Moore, 2012.
2 2013 represents most current data available.
3 Our argument would be even stronger if we could show that the personal savings rate among high-earning seniors in their late 60s and early 70s has been increasing over time (parallel to the rise in labor force participation). However, the BLS has advised us that a comparison between 2014 data and prior-year data may be misleading due to recent changes in survey methodology.
4 From 2000 to 2050, our dynamic ratio – mechanically – is a weighted average of two individual static ratios (35–64 versus 65+ and, separately, 35–69 versus 70+); the weights change each year to reflect our assumption about rising longevity.
5 See, for instance, “The Impact of Demographic Shifts on Financial Markets” (McKinsey Global Institute, 2012).
6 “How Seniors Change Their Asset Holdings During Retirement” (Smith et al, 2009).
7Validity of global Buyers versus Sellers Ratio depends on the extent to which asset accumulation-drawdown patterns among the high-earning elderly outside the U.S. mirror the patterns observed among U.S. elderly. We have not explored this question empirically and include the global ratio only for interest and context.
8 See Appendix for a technical note on our choice of the Federal Reserve’s Survey of Consumer Finances for U.S. household financial asset detail.
9 U.S. household financial assets, as depicted in the Federal Reserve’s 2013 Survey of Consumer Finances, total $31 trillion across all age groups.
10 Source: Allianz Global Wealth Report, 2015.
11 For color on U.S. DB pension plan asset allocations, see, for example, the OECD’s “Pension Markets in Focus” (2015) and Towers Watson’s “2014 Asset Allocations in Fortune 1000 Pension Plans” (2015).
12 Source: NextCapital.
13 See “Demographic Changes, Financial Markets, and the Economy” (Arnott and Chaves / CFA Institute, 2012).
14 For simplicity, we assume that anyone who dies younger than age 65 bequeaths assets to a spouse of comparable age (i.e., no change in asset allocation) while those who die at or after age 65 bequeath assets to someone (presumably children) 30 years younger (i.e., a generation earlier in risk tolerance). We recognize that not every elderly person bequeaths assets to a younger heir; some assets are passed on to charitable organizations and friends or other family members of comparable age, for instance. We assume, arbitrarily, that 50% of financial assets are passed to younger heirs. Our general results are not particularly sensitive to changes in these assumptions.
2 2013 represents most current data available.
3 Our argument would be even stronger if we could show that the personal savings rate among high-earning seniors in their late 60s and early 70s has been increasing over time (parallel to the rise in labor force participation). However, the BLS has advised us that a comparison between 2014 data and prior-year data may be misleading due to recent changes in survey methodology.
4 From 2000 to 2050, our dynamic ratio – mechanically – is a weighted average of two individual static ratios (35–64 versus 65+ and, separately, 35–69 versus 70+); the weights change each year to reflect our assumption about rising longevity.
5 See, for instance, “The Impact of Demographic Shifts on Financial Markets” (McKinsey Global Institute, 2012).
6 “How Seniors Change Their Asset Holdings During Retirement” (Smith et al, 2009).
7Validity of global Buyers versus Sellers Ratio depends on the extent to which asset accumulation-drawdown patterns among the high-earning elderly outside the U.S. mirror the patterns observed among U.S. elderly. We have not explored this question empirically and include the global ratio only for interest and context.
8 See Appendix for a technical note on our choice of the Federal Reserve’s Survey of Consumer Finances for U.S. household financial asset detail.
9 U.S. household financial assets, as depicted in the Federal Reserve’s 2013 Survey of Consumer Finances, total $31 trillion across all age groups.
10 Source: Allianz Global Wealth Report, 2015.
11 For color on U.S. DB pension plan asset allocations, see, for example, the OECD’s “Pension Markets in Focus” (2015) and Towers Watson’s “2014 Asset Allocations in Fortune 1000 Pension Plans” (2015).
12 Source: NextCapital.
13 See “Demographic Changes, Financial Markets, and the Economy” (Arnott and Chaves / CFA Institute, 2012).
14 For simplicity, we assume that anyone who dies younger than age 65 bequeaths assets to a spouse of comparable age (i.e., no change in asset allocation) while those who die at or after age 65 bequeath assets to someone (presumably children) 30 years younger (i.e., a generation earlier in risk tolerance). We recognize that not every elderly person bequeaths assets to a younger heir; some assets are passed on to charitable organizations and friends or other family members of comparable age, for instance. We assume, arbitrarily, that 50% of financial assets are passed to younger heirs. Our general results are not particularly sensitive to changes in these assumptions.
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