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Economic Brief

July 2016, EB16-07

A “New Normal”? The Prospects for Long-Term
Growth in the United States
By Aaron Steelman and John A. Weinberg

Economic growth in the United States following the Great Recession has been
well below the post-World War II average. Some observers have called this the
“new normal.” They argue, among other things, that innovation has slowed
and is unlikely to improve and that demographic trends pose serious problems
for fiscal policy that will hinder the economy. Such issues are significant, but
the “new normal” is not a given. Continued innovation, as well as good policy,
could yield improvements in economic performance.1
From 1947 through 2007, the economy grew
at roughly 3.4 percent annually. While growth
is often expressed in terms of total economic
output, a growing population will bring with
it some amount of overall growth. To measure
improvement in average standards of living,
growth of GDP per capita is the standard yardstick. The post-war average of 3.4 percent overall
growth translated to an average growth rate per
capita of about 2.1 percent. During that period,
the United States experienced a few significant
recessions and several milder downturns. Such
fluctuations can be acutely felt by many people
when they occur, but against the longer-run
performance, they look relatively insignificant.
Since the financial crisis and Great Recession,
though, many people’s perception of the strength
of the U.S. economy and its prospects for the
future have dimmed. These skeptics point to the
slowed pace of growth: since 2010, the U.S. economy has grown at a rate of roughly 2.1 percent
annually, which translates to an average growth
rate per capita of about 1.3 percent, both well
below the post-World War II rates prior to the
Great Recession and, perhaps more notably, far
EB16-07 - Federal Reserve Bank of Richmond

below what has been seen in “catch-up” periods
following previous significant downturns. For
instance, following the 1981–82 recession, the
U.S. economy rebounded sharply, growing 7.8
percent in 1983 and 5.7 percent in 1984. Some
observers believe the United States has entered a
period characterized by a “new normal” or even a
“new mediocre.”2 Proponents of the new-normal
hypothesis maintain that the United States is
likely to grow at a substantially slower rate than
it did prior to the Great Recession, with many
predicting growth rates of roughly 1.5 percent to
2 percent.3
Some commentators who generally would place
themselves in the skeptics camp argue that the
new normal had already started, in a sense, prior
to the Great Recession – that, the U.S. economy
already was experiencing lower productivity and
growth rates due to several important long-term
trends. For instance, in a series of papers and
his recently published book, The Rise and Fall
of American Growth, Northwestern University
economist Robert J. Gordon argues that the
U.S. economy is likely to grow more slowly. He
traces this deceleration to a slowdown of innoPage 1

vation that began around 1970, particularly compared with the middle of the 20th century.
Gordon describes the century following the Civil War
as the period of great economic liberation, when a
large portion of the United States was freed from
“an unremitting daily grind of painful manual labor,
household drudgery, darkness, isolation, and early
death.” What is more, these stark changes in Americans’ way of life were broadly enjoyed, with virtually
every American benefiting from the development of
public waterworks, electricity, and antibiotics, and
most seeing their workweeks become shorter and
less physically onerous while their take-home pay
increased. Leisure time and retirement, once abstract
concepts, became the norm. As a result, Gordon
dubs the period 1920-70 as the “Second Industrial
Revolution” or “IR #2.”
There has been innovation since 1970, Gordon
concedes, but it can hardly be compared to IR #2.
He argues that the effects of the digital revolution,
or “IR #3,” which started with innovations that can
be traced to the late 1970s and early 1980s but did
not produce major changes in the way business was
done until the mid-1990s, have been “felt in a limited
sphere of human activity, in contrast to IR #2, which
changed everything.” Moreover, the productivity
gains produced by IR #3 were felt most acutely for
only about a decade, with advances coming much
more slowly since 2004.4
In addition to a slowing rate of innovation, Gordon
argues that the U.S. economy faces four big headwinds. First, there’s rising income inequality, which
has reduced the share of economic gains going to
the middle and working classes. Second, growth
in educational attainment as measured by years of
schooling completed has slowed and, among some
parts of the population, decreased since 1970. In addition, the quality of primary and secondary education has become more stratified and the costs of
higher education have increased. Such trends in education are themselves a contributor to the first headwind, growing income inequality. Third, the United
States is experiencing significant demographic
changes, most significantly many baby boomers are

reaching traditional retirement age. That has reduced
the number of hours worked per person. In addition,
labor force participation among people who have
not yet reached retirement age has dropped. Fourth,
federal, state, and local governments face mounting
debt, in large measure due to the aging of the population, as spending on “entitlement” programs, such
as Social Security and Medicare, increases and pension obligations to public-sector employees grow.
Gordon identifies two additional headwinds, which
he thinks could be barriers to growth, though they
are hard to quantify: “globalization,” which could add
to growing income inequality, and global warming
and other environmental issues, which could require
significant resources to address.5
Accounting for Growth – The Neoclassical Model
During the 1950s, economist Robert M. Solow of the
Massachusetts Institute of Technology (MIT) developed what came to be known as either the “neoclassical growth model” or the “Solow growth model.”6 His
model was quite elegant in its simplicity. Output was
determined by three factors: capital, labor, and technology. That measure of technology was later dubbed
the “Solow residual” or “total factor productivity” (TFP)
and includes a variety of things beyond technological
progress, strictly speaking. And the evolution of labor
and technology was taken as given.
The model has an important implication for longrun per-capita growth: since capital suffers from
diminishing returns, capital accumulation can drive
growth only in the short run, and, with no technological improvements, per-capita output stagnates
in the long run. So long-run growth (in output per
worker) is due only to technological progress, or TFP,
and that progress is exogenous, meaning it comes
from forces outside the economic system. Early
measurements done by Solow and others suggested
that a very large share of growth was not driven by
capital accumulation but by TFP. Indeed, Solow concluded that during the first part of the 20th century
in the United States, about 80 percent of nonfarm
output growth was due to TFP.7
A line of the neoclassical growth literature in the late
1960s attempted to better understand and measure

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the factors of production. As New York Fed economist Kevin J. Stiroh has put it, economists working
in this period “sought to develop better measures of
investment, capital, labor, and other omitted inputs
in order to reduce the magnitude of the unexplained
residual.”8 That area of research enriched the neoclassical growth model and pioneering work was done
by Dale W. Jorgenson and Zvi Griliches, then of the
University of California, Berkeley and the University
of Chicago, respectively.9
Growth theorists in the 1980s and 1990s built on the
neoclassical model but changed an important assumption: in their models, technological growth was
endogenous rather than exogenous. Endogenous
technical change is change that is determined within
the economic system, meaning that it is the consequence of the decisions and actions of people in the
economy. Still, it is important to note that both neoclassical growth theorists and endogenous growth
theorists focus on technology as one of the factors
– if not the principal factor – driving long-run economic growth. Indeed, Harvard University economist
Elhanan Helpman, a major contributor to the endogenous growth literature, notes that “there is convincing
evidence that total factor productivity plays a major
role” in accounting for cross-country variations in
per-capita income and patterns of economic growth.
But while careful growth accounting can help us understand the relative “contribution of inputs and the
contribution of total factor productivity, it does not
unveil the causes of economic growth.”10
Explaining Growth – The New Growth Theory
Among the implications of the neoclassical growth
model is that economic convergence between countries would occur over time, with poorer countries
catching up with richer countries. However, that is
not observed in the data. While the cross-country
variation in per-capita wealth has been shrinking
somewhat in recent decades, as some of the poorest
countries in the world have made significant relative
gains, there can be no doubt that the gap between
what is generally considered the developed world
and the developing world remains very large. This
observation motivated economists Paul M. Romer,
now of New York University, and Robert E. Lucas Jr.

of the University of Chicago to, as Romer has put it,
“drop the two central assumptions of the neoclassical model: that technological change is exogenous
and that the same technological opportunities are
available in all countries in the world.”11
Lucas argued that if the same technology were
available everywhere, resources, such as human
capital, would not tend to move from where they are
scarce to where they are plentiful and substantial
differences in the level and growth of income would
not persist. Yet both things are true. Lucas’ theory
is that there are “external effects” of human capital.
Economists had long argued that improvements in a
worker’s human capital had “internal effects” – meaning benefits from building human capital accrued
to the worker (and perhaps his or her family). But
Lucas, building on the work of sociologist and urban
theorist Jane Jacobs, posited that there were spillover effects associated with human capital. As Lucas
succinctly noted: “Most of what we know we learn
from other people.”12
Lucas’ work was complementary to work being done
by Romer in a series of papers at roughly the same
time.13 At the heart of Romer’s work is the importance
of ideas and their role in innovation and productivity
improvements, which he argues is the prime driver of
economic growth.
Romer focuses on the technological change that
arises because of intentional actions of people responding to market incentives. That is, technology
advances because people seek to profit from new
ways of producing goods and services. To be sure,
there are some people who come up with technological breakthroughs without any commercial
applications in mind. But even in those cases, those
innovations spur related innovations that do have
market value. In this regard, a country’s institutions
are crucial to providing the proper incentives for
innovation and thus growth.
Particularly importantly, ideas are inherently nonrivalrous, meaning they can be used and built upon
by multiple people simultaneously. Commenting on
Romer’s work, Stanford University economist Charles I.

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Jones provides a useful example: “If you add one computer, you make one worker more productive. If you
add a new idea – think of the computer code for the
first spreadsheet or word processor or even the Internet itself – you can make any number of workers more
productive.”14 Moreover, in a world of relatively fast
transmission of ideas across space, ideas are no longer
country or region specific. They can be “imported”
from any part of the world fairly easily and cheaply.
Thinking about the Future
Given what we know from both theory and evidence,
how should we evaluate the “new normal” hypothesis regarding sluggish future U.S. growth? Gordon
presents a plausible outlook. It is true that TFP growth
associated with the digital revolution – or, as he puts
it, IR #3 – appears to have been relatively short lived
relative to TFP growth associated with IR #1 and IR
#2. His interpretation for the rise from 1994 to 2004
and the drop thereafter is fairly straightforward: the
introduction of the personal computer in the 1980s
did not generate major productivity gains until the
“invention of the Internet, web browsing, search
engines, and e-commerce produced a pervasive
change in every aspect of business practice.” However, those changes have largely been exploited,
and we are unlikely to see major additional changes
from those technologies – and the prospect for new
technological development that was as revolutionary as what we saw in the middle of the 20th century
is unlikely. Yes, we will see more ingenuous apps for
our mobile devices but, as he frequently quips in
public lectures, “What would you rather have: your
iPhone or indoor plumbing?”
Arguably the biggest problem with Gordon’s analysis is that trying to predict the future is inevitably
fraught with trouble. That is true in nearly every
aspect of life. But it is perhaps particularly true when
it comes to predicting innovation, which as we know
comes in fits and starts.
Gordon’s colleague at Northwestern, economic historian Joel Mokyr, argues that there are many areas of
science in which significant discoveries seem promising, among them molecular microbiology, astronomy, nanochemistry, and genetic engineering. And

while it is true that there is no guarantee that better
science will generate improved technology, “there is
one reason to believe that in the near future it will do
so better and more efficiently than ever before. The
reason is access.” In other words, searching for vast
amounts of information has become fast, easy, and
nearly costless. Not only is the era of “Big Data” here
but the ability to parse through the most arcane of
data is no longer burdensome for people working on
the frontiers of knowledge.
Similarly, MIT economist Daron Acemoglu writes:
“[T]he macropicture is clear: there is little evidence
we are running out of innovations. This is not only
because there are literally millions of ideas that can
be recombined into new ones to generate new
processes and products, but also because every innovation poses new problems and opens the way
for yet more innovations.” In addition, he argues that
in societies with good governance, market signals
are sent to innovators to guide their work toward areas where societal benefits are large. As an example,
he points to the U.S. pharmaceutical industry, where
the production of drugs aimed to address problems
faced by aging baby boomers has increased and the
quality has improved.15
What’s more, even if we accept Gordon’s hypothesis
that technological growth is slowing and is likely to
remain sluggish, as measured by TFP, that doesn’t
necessarily mean that we should discount the importance of recent innovations to human well-being.
Princeton University economist Angus Deaton has
made this point in an elegant essay that is worth
quoting at length:
I … challenge the proposition that the information revolution and its associated devices do little
for human well-being. Many have documented
the importance of spending time and socializing
with friends and family, but this is exactly the feature of everyday life that the new communication
methods work to enhance. All of us can remain in
touch with our children and friends throughout
every day, videoconferencing is essentially free,
and we can cultivate close relationships with
people who live thousands of miles away. When
my parents said good-bye to relatives and friends

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who left Scotland to look for better lives in Canada
and Australia, they never expected to see or talk to
them again, except perhaps for a brief and astronomically expensive phone call when someone
died. Today, we often do not even know where
people are physically located when we work with
them, talk to them, or play with them. We can also
enjoy the great human achievements of the past
and the present, cheaply accessing literature, music, and movies at any time and in any place. That
these joys are not captured in growth statistics
tells us about the growth statistics, not about the
technology. If they are belittled by those who do
not use them, it tells us only to pay no attention
to those who purport to use their own preference
to pass judgments on the pleasures of others.16

On balance, there is reason to be sanguine about
the prospects for future technological innovation.
There is also reason to celebrate recent innovations
that may not immediately appear as fundamentally
transforming as, say, the development and widespread use of automobiles during the middle part of
the 20th century, but that have nonetheless brought
great gains to millions of Americans and billions of
people worldwide, gains that arguably are not fully
captured in many standard measures of well-being.
It would be rash to attempt to predict with precision
the pace at which future innovation will take place
or how important those innovations will be, but it
would also be premature to say that America’s best
days are behind us and that future generations will
not live much better than we do today. In the next
section, we raise several policy issues that might be
addressed to help provide an environment in which
innovation can continue to occur and economic
growth can be robust. We acknowledge that some
of these ideas may be difficult to achieve politically
and that some could have adverse economic consequences for segments of the population. Insofar as
the latter is true, policymakers may wish to consider
ways to compensate those who are made worse off.
Implications for Policy
Perhaps the first thing that policymakers ought to
acknowledge when confronting policy issues aimed
at boosting innovation and economic growth is that
there are factors related to long-term economic

growth that are largely beyond their control. One of
them is the domestic birth rate. A fact that seems to
hold true across nearly all countries is that as they
get richer, the fertility rate declines. In 2013, University of Chicago economist Gary S. Becker estimated
that more than 80 countries have fewer births annually than are required to replace the number of individuals who die each year, including China, Japan,
Russia, Canada, and every country in Western Europe.17 In the United States, the fertility rate was only
slightly above the replacement rate. The United Nations predicts that many of these countries will have
smaller populations in 2050 than they do today.18
Such trends have significant economic implications.
As noted earlier, Gordon argues that demographic
trends are one of the four major “headwinds” that the
U.S. economy faces. In particular, the declining fertility
rate (accompanied by lower overall labor force participation) will make it more difficult to fund entitlement
programs such as Social Security and Medicare, which
depend on payroll taxes to distribute benefits.
In the neoclassical model, declining population has a
very clear and direct effect on output. As the amount
of labor falls, so does output. In endogenous growth
models, population has the same direct effect on
labor input, but many also feature an indirect effect.
Growth in such models is largely a function of ideas
and the more people in a country, the more ideas
they will create. As Charles Jones argues:
First, just as the total output of any good depends
on the total number of workers producing the
good, more researchers produce more ideas. A
larger population means more Mozarts and Newtons, and more Wright brothers, Sam Waltons,
and William Shockleys. Second, the nonrivalry of
knowledge means that per capita output depends
on the total stock of ideas, not on ideas per person.
Each person in the economy benefits from the new
ideas created by the Isaac Newtons and William
Shockleys of the world, and this benefit is not degraded by the presence of a larger population.19

So how might policymakers address the issue of declining fertility rates in the United States? As noted
above, this seems to be an issue that is largely out

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of their control, at least directly. One could imagine
schemes that would subsidize births but, as Becker,
who viewed population growth as a net positive, argued, those programs could be expensive and hard
to administer. An obvious alternative to domestic
population growth is to look abroad and effectively
import ideas through more liberalized immigration
policies. Consistent with Lucas’ theory of economic
growth, people can be more productive when
placed in close proximity to others, jointly working
on projects, than in isolation, though arguably the
importance of proximity has declined somewhat as
long-distance communication has improved and
become cheaper. Policies that would increase the
level of skills by making it easier for workers to come
to the United States would benefit the immigrants
themselves and native-born Americans, on average.
Closely tied to the issue of immigration is that of trade.
At least since Adam Smith published The Wealth of
Nations in 1776, economists have been generally
supportive of liberal trade policies. Such policies permit countries to specialize in the production of goods
where they have a comparative advantage, as classical economist David Ricardo noted, leading to an increase in output per worker. But Romer points out
that the benefits of trade extend beyond increasing
the efficiency of the production of goods that already
exist. Trade also introduces new or improved types of
goods and services from abroad.20
Similarly, economists Gene Grossman of Princeton
University and Elhanan Helpman of Harvard University posit a theory of integration and growth, where
trade may help the process of technological dissemination if foreign exporters suggest ways that their
goods can be used more productively or foreign
importers indicate how local products can be made
more attractive to consumers in their country. In
addition, exposure to international competition may
mitigate redundancy in industrial research. Thus,
policymakers ought to be wary of imposing barriers
that would impede such transactions and make most
people worse off than they otherwise would be.21
Education is also clearly important to the future of
economic growth in the United States. In particular,

it appears that there are significant returns to early
childhood education. Skills that are acquired early in
life tend to build on each other over time.22 Relatedly,
we ought to take a broad view of what we mean by
the term “skills.” Some skills may not be easily measurable through standardized tests but seem to have
important long-run effects. For instance, noncognitive skills such as following instructions, patience,
and work ethic can lay the foundation for mastering
more complex cognitive skills later in life.23
The cumulative effects of economic regulation
appear to be exerting a drag on the U.S. economy.
While some regulations – for instance, those that
require firms to effectively internalize the costs
they impose on others – arguably promote both
efficiency and equity, many regulations serve little
aggregate economic purpose but instead deliver
concentrated benefits for certain groups, often by
helping to protect them from competition. Gordon
dubs these barriers to entry as “regressive regulation”
and identifies excessive monopoly privileges granted
under intellectual property law, protection of incumbent service providers through occupational licensing, and artificial scarcity through land-use regulation as areas ripe for reform.24
In sum, there can be little doubt that the U.S. economy does face some significant challenges. However,
the “new normal” is far from a given. The prospects
for continued innovation that improves measured as
well as unmeasured standards of living remain stronger than the skeptics maintain. And there are policy
areas that, if addressed thoughtfully, likely could
yield improvement in economic performance and
human welfare. It might be hard for many people to
imagine the U.S. economy growing like it did in, say,
the 1950s, but how many Americans in 1930 would
have thought that the rest of the 20th century would
have produced such massive gains for such a huge
swath of the population?
Aaron Steelman is director of publications and John
A. Weinberg is senior vice president and special
advisor to the president at the Federal Reserve Bank
of Richmond.

Page 6


 harles I. Jones, “On the 25th Anniversary of Romer (1990),”
Manuscript, Stanford University, October 22, 2015.


 aron Acemoglu, “The World Our Grandchildren Will Inherit,” In
In 100 Years: Leading Economists Predict the Future, edited by
Ignacio Palacios-Huerta, Cambridge, Mass.: MIT Press, 2013,
pp. 25–26.


Angus Deaton, “Through the Darkness to a Brighter Future,” In
In 100 Years: Leading Economists Predict the Future, edited by
Palacios-Huerta, p. 41.


Gary S. Becker, “Low Birth Rates: Causes, Consequences, and

This article is based on an essay that appeared in the Federal
Reserve Bank of Richmond’s 2015 Annual Report.



See Mohamed A. El-Erian, “Navigating the New Normal in
Industrial Countries,” Per Jacobsson Foundation Lecture at the
International Monetary Fund, Washington, D.C., October 10,
2010; and Christine Lagarde, “The Challenge Facing the Global
Economy: New Momentum to Overcome a New Mediocre,”
Speech at the School of Foreign Service, Georgetown University, Washington, D.C., October 2, 2014.



Remedies,” Becker-Posner Blog, August 18, 2013.

See Dale W. Jorgenson, Mun S. Ho, and Jon D. Samuels, “Long-


Term Estimates of U.S. Productivity and Growth,” Presented at
the Third World KLEMS Conference, May 19–20, 2014, Tokyo.

 nited Nations, “World Population Prospects: 2015 Revision,”
New York, July 29, 2015.


 harles I. Jones, “Growth and Ideas,” In Handbook of Economic
Growth, Volume 1B, edited by Philippe Aghion and Steven N.

 obert J. Gordon, The Rise and Fall of American Growth: The U.S.
Standard of Living Since the Civil War, Princeton, N.J.: Princeton

Durlauf, Amsterdam: Elsevier, 2005, p. 1073. A working paper

University Press, 2016, pp. 566–579. The first chapter and a
related TED talk are available online.

Gordon, pp. 605–639.


S ee, in particular, the following two papers by Robert M.
Solow: “A Contribution to the Theory of Economic Growth,”
Quarterly Journal of Economics, February 1956, vol. 70, no. 1,
pp. 65–94; and “Technical Change and the Aggregate Production Function,” Review of Economics and Statistics, August 1957,
vol. 39, no. 3, pp. 312–320.


Solow, p. 314–316


 evin J. Stiroh, “What Drives Productivity Growth?” Federal
Reserve Bank of New York Economic Policy Review, March 2001,
vol. 7, no. 1, p 41.


S ee Dale W. Jorgenson and Zvi Griliches, “The Explanation of
Productivity Change,” Review of Economic Studies, July 1967,
vol. 34, no. 3, pp. 249–283.


E lhanan Helpman, The Mystery of Economic Growth, Cambridge,
Mass.: Harvard University Press, 2004, pp. 26–33.


 aul M. Romer, “The Origins of Endogenous Growth,” Journal
of Economic Perspectives, Winter 1994, vol. 8, no. 1, p. 4.


S ee Robert E. Lucas Jr., “On the Mechanics of Economic Development,” Journal of Monetary Economics, July 1988, vol. 22,
no. 1, pp. 3–42.


S ee, in particular, the following three papers by Romer: “Increasing Returns and Long-Run Growth,” Journal of Political
Economy, October 1986, vol. 94, no. 5, pp 1002–1037; “Growth
Based on Increasing Returns Due to Specialization,” American
Economic Review Papers and Proceedings, May 1987, vol 77,
no. 2, pp 56–62; and “Endogenous Technical Change,” Journal
of Political Economy, vol. 98, no. 5, part 2, October 1990,
pp. S71-S102. A working paper version is available online.

Richmond Baltimore Charlotte

version is available online.

 aul M. Romer, “New Goods, Old Theory, and the Welfare Costs
of Trade Restrictions,” Journal of Development Economics, February 1994, vol. 43, no. 1, pp. 5–38. A working paper version is
available online.


I t is true that liberal trade policies do produce some net losers.
For instance, those people formerly employed in industries
that are now partly or largely located in other countries may
be worse off due to international trade. But rather than trying
to restrict the free flow of ideas and goods – thereby blunting the substantial economic benefits that result – a more
desirable alternative, insofar as any action is taken, would be
to provide financial compensation for those who have been
harmed economically. For an overview of the merits of different policies that would achieve that end, see Earl L. Grinols,
“Pure and Mixed Price and Income Compensation Schemes:
Breaking Political Roadblocks to Trade Reform,” In The Political
Economy of Trade Policy: Papers in Honor of Jagdish Bhagwati,
edited by Robert C. Feenstra, Gene M. Grossman, and Douglas
A. Irwin, Cambridge, Mass.: MIT Press, 1996, pp. 129–144.


James J. Heckman, “Schools, Skills, and Synapses,” Economic
Inquiry, July 2008, vol. 46, no. 3, pp. 289–324. A working paper
version is available online.


Samuel Bowles, Herbert Gintis, and Melissa Osborne Groves,
“Intergenerational Inequality Matters,” In Unequal Chances:
Family Background and Economic Success, edited by Samuel
Bowles, Herbert Gintis, and Melissa Osborne Groves, Princeton,
N.J.: Princeton University Press, 2008, pp 1–22.


See Gordon, p. 649

This article may be photocopied or reprinted in its
entirety. Please credit the authors, source, and the
Federal Reserve Bank of Richmond and include the
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Views expressed in this article are those of the authors
and not necessarily those of the Federal Reserve Bank
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