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2019:Q4 | VOL. 27 | NO. 4

Insights on economic issues in today’s headlines

How Industrialization
Shaped America’s
Trade Balance

St. Louis Fed President

Efficient and Disruptive

Immigration

Some of James Bullard’s
key policy presentations
during 2019

New technologies are
transforming the payments
and banking systems

What are some of the
demographic characteristics
of green card holders?

PAGE 3

PAGE 12

PAGE 14

4
2019:Q4 | VOL. 27, NO. 4
www.stlouisfed.org/re
The Regional Economist is published
quarterly by the Research and
Public Affairs divisions of the Federal
Reserve Bank of St. Louis. It addresses
the national, international and
regional economic issues of the day,
particularly as they apply to states in
the Eighth Federal Reserve District.
Views expressed are not necessarily
those of the St. Louis Fed or of the
Federal Reserve System.
Director of Research
Christopher J. Waller
Senior Policy Adviser
Cletus C. Coughlin
Deputy Director of Research
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Subhayu Bandyopadhyay
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Gregory Cancelada
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Joni Williams
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Regional Economist
Public Affairs Office
P.O. Box 442
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How Industrialization Shaped
America’s Trade Balance
The U.S. has experienced extended periods of
deficits and surpluses in its goods trade balance.
These trends appear to be closely linked to stages
of U.S. industrialization.

2019:Q4 | VOL. 27 | NO. 4

IN THIS ISSUE

Insights on economic issues in today’s headlines

How Industrialization
Shaped America’s
Trade Balance

St. Louis Fed President

Immigration

Efficient and Disruptive

Some of James Bullard’s
key policy presentations
during 2019

What are some of the
demographic characteristics
of green card holders?

New technologies are
transforming the payments
and banking systems

PAGE 4

PAGE 14

PAGE 16

PRESIDENT’S MESSAGE .................................................................................................................. 3

New Payments Technologies Seen Bringing Efficiency and Disruption
New digital technologies are starting to transform the payments
and banking systems. ..................................................................................................... 12
Immigration: The Characteristics of Green Card Holders
Immigrants with U.S. permanent resident status, on average, are younger
than the U.S. population. ............................................................................................... 14
The Role of Industry Mix in Regional Business Cycles
The business cycles of states can diverge from the U.S. cycle.
Industry mix can help explain why. ............................................................................. 16
DISTRICT OVERVIEW

Debt Developments in the Eighth District during First Half of 2019
Student debt generally grew faster in the U.S. and Eighth District
than any other debt category. ........................................................................................ 19
NATIONAL OVERVIEW

Forecasters See Lower U.S. GDP Growth as Headwinds Continue
The consensus of professional forecasters is that real GDP growth
will dip below 2% in 2020. ............................................................................................. 21
ECONOMY AT A GLANCE................................................................................................ 22

ONLINE EXTRA
Excluding Housing Costs, U.S. Inflation Is Well Below 2%

COVER IMAGE:
© CATNAP72/ISTOCK/GETTY IMAGES PLUS

2 REGIONAL ECONOMIST | Fourth Quarter 2019

Housing costs have been rising fast in recent years. What might this mean for
underlying inflation trends?
Read more at stlouisfed.org/re.

PRESIDENT’S MESSAGE

A Year in Review

S

t. Louis Fed President James Bullard
has been a participant in Federal Open
Market Committee (FOMC) deliberations
since April 2008. Bullard actively engages
with many audiences—including academics, policymakers, business and community
organizations, and the media—to discuss
monetary policy and the U.S. economy and
to help further the regional Reserve bank’s
role as the voice of Main Street.
Some of his key policy presentations
during 2019 and some of his remarks
related to longer-run issues for monetary
policy are summarized below. To see more
of Bullard’s public remarks, please visit
stlouisfed.org/from-the-president.
Some Key Policy Presentations
Perspectives on 2019 Monetary Policy

Remarks on Longer-Run
Issues for Monetary Policy
James Bullard Discusses
Nominal GDP Targeting

President Bullard speaking in Effingham, Ill.,
in September.

trade policy uncertainty. He also noted
that inflation and inflation expectations
remain below the Fed’s 2% target and
that signals from the Treasury yield curve
seem to suggest the policy rate setting is
inappropriately high. “A downward policy
rate adjustment may be warranted soon
to help re-center inflation and inflation
expectations at target and also to provide
some insurance in case of a sharper-thanexpected slowdown,” he said.

Jan. 10, 2019: In Little Rock, Ark., Bullard
noted that U.S. monetary policymakers
reacted to the upside surprise in macroeconomic performance during 2017 and 2018
by taking the opportunity to normalize
U.S. short-term interest rates. “Marketbased signals such as low market-based
inflation expectations and a threatening
yield curve inversion suggest that this
window of opportunity has now closed,” he
said. He added that the FOMC should heed
these signals to keep the U.S. expansion on
track for the next several years.

(Note: While the FOMC left the target range
for the federal funds rate unchanged at its June
2019 meeting, Bullard cast a dissenting vote in
favor of a 0.25 percentage point reduction at
that time. The FOMC did reduce the policy rate
by 0.25 percentage points in July and again in
September. At the September meeting, Bullard
cast a dissenting vote in favor of a 0.5 percentage point reduction instead.)

A Successful Normalization,
With Challenges Ahead

Insurance against Downside Risk for
the U.S. Economy

April 11, 2019: In Tupelo, Miss., Bullard
discussed the end of U.S. monetary policy
normalization. He said, “The campaign has
been largely successful: Nominal shortterm interest rates have been raised from
near-zero levels, and the size of the Fed’s
balance sheet has been reduced as the economic expansion has continued.” He also
discussed the macroeconomic challenges
the FOMC faces in 2019.

Oct. 15, 2019: In London, Bullard noted
that the U.S. economy continues to face
downside risk due to weakness in the
global economy and trade policy uncertainty. This risk may cause a sharper-thanexpected slowdown, which may make it
more difficult for the FOMC to achieve its
2% inflation target. He pointed out that
the FOMC has tried to help insure against
this downside risk by dramatically altering
the path of monetary policy. “The FOMC
has taken actions that have changed the
outlook for shorter-term U.S. interest rates
considerably over the last 11 months, ultimately providing more accommodation to
the economy,” he said.

Remarks on the Current Stance
of U.S. Monetary Policy
June 3, 2019: In Chicago, Bullard noted
that the U.S. economy is expected to grow
more slowly going forward, with some
risk that the slowdown could be sharper
than expected due to ongoing global

(Note: In late October, the FOMC reduced the
policy rate by 0.25 percentage points.)

April 19, 2019: Bullard noted that inflation
targeting has been successful in keeping
inflation low and stable. The question now
is whether a different approach might be
even better. In this podcast, he discussed
some advantages and disadvantages of
using nominal GDP (NGDP) targeting.
“The biggest advantage is this idea that you
would really cement inflation expectations
around the target,” he said.
Nominal GDP Targeting as “Optimal
Monetary Policy for the Masses”
May 3, 2019: During a policy panel at a
conference hosted by the Hoover Institution at Stanford University, Bullard
discussed his working paper (co-authored
with Riccardo DiCecio). The paper
examines whether monetary policy can be
conducted in a way that benefits all households even in a world with substantial
income, financial wealth and consumption
inequality. In the paper, NGDP targeting
constitutes “optimal monetary policy for
the masses.”
“I am hopeful that the results reported
here will stimulate more research and
that ideas related to price-level targeting
and NGDP targeting will continue to gain
influence in actual monetary policy deliberations,” he said.
Bullard Discusses the Fed’s Monetary
Policy Framework Review
Aug. 14, 2019: The Federal Reserve is
reviewing its monetary policy strategies,
tools and communications in 2019. In this
podcast, Bullard explained that it is best
practice among central banks to review
their policymaking framework on a regular
basis. He noted this provides an opportunity
to think about changes that might be made
outside of the normal policy cycle. “I think
it’s very useful to try to do as much as you
can in good times so that when bad times
come again, you’ve at least got some basis to
go ahead and make decisions,” he said.
(This article was published online Nov. 26.)

REGIONAL ECONOMIST | www.stlouisfed.org/re 3

How Industrialization
Shaped America’s
Trade Balance
By Brian Reinbold and Yi Wen

KEY TAKEAWAYS
• The state of the U.S. trade balance
appears closely linked to stages of the
country’s industrialization.
• America’s changing economic structure
affected its comparative advantage
relative to those of other countries,
which is a key determinant of trade
patterns.
• The persistence of trade deficits may
be related to the willingness of foreigners
to hold U.S. financial assets.

M

© ROBERT_FORD/ISTOCK/GETTY IMAGES PLUS

4 REGIONAL ECONOMIST | Fourth Quarter 2019

any Americans worry about the
current size of the U.S. trade
deficit. Yet relatively large trade deficits
have been persistent during much of the
country’s existence.
In an Economic Synopses published by
the Federal Reserve Bank of St. Louis in
May 2019, we broadly examined the link
between industrialization and historical
U.S. trade flows. In this article, we take
a closer look at how industrialization
may have affected the composition of
U.S. trade and why certain trade patterns
persisted in U.S. history.
Figure 1 shows the U.S. goods trade
balance as a percentage of gross domestic
product (GDP) from 1800 to 2018.1 From
1800 to 1870, the U.S. ran a trade deficit
for all but three years, and the trade balance averaged about –2.2% of GDP. Then
from 1870 to 1970, the U.S. ran persistent
trade surpluses that averaged about 1.1%
of GDP. Around 1970, the country began
to run trade deficits again, which have
continued to this day. These shifts in the
long-term U.S. trade balance appear to
correspond well with U.S. industrialization in a global setting.

Figure 1
U.S. Goods Trade Balance as a Percentage of GDP
15%
10%
5%
0%
–5%
–10%
–15%

Exports/GDP

Imports/GDP

Trade Balance/GDP

–20%

1800 1810 1820 1830 1840 1850 1860 1870 1880 1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

SOURCES: U.S. Bureau of Economic Analysis, World Trade Historical Database, measuringworth.com and authors’
calculations.

Historically, industrialization has three
phases: (1) the first industrial revolution
features labor-intensive mass production
of light consumer goods, such as processed food and textiles; (2) the second
industrial revolution features capitalintensive mass production of heavy
industrial goods, such as steel, machinery,
equipment and automobiles; and (3) the
welfare revolution features mass consumption in a service-oriented welfare state.
We hypothesize that different phases
of industrialization lead to structural
changes that cause a nation’s comparative advantage to change relative to those
of other nations. Since countries trade
based on their comparative advantage, we
would expect to see long-term changes to
a country’s trade as it enters a new stage
of development. Therefore, the long-term
trends in Figure 1 can best be understood
in the context of U.S. development.
Phase 1 (1800-1870)
As Europe, led by Great Britain, began
to industrialize in the late 18th century,
the U.S. remained primarily agrarian.
U.S. industrialization began in the early
19th century, focusing on labor-intensive
manufacturing, such as textiles. As a
latecomer to industrialization and thus

playing catch-up with Europe, the U.S.
still had to import many manufactured
goods, including machinery and other
capital goods, and the country relied on
the exports of crude materials, such as
cotton. Europe produced manufactured
goods more cheaply, and the U.S. could
not yet match Europe’s prolific innovations. As a result, the U.S. ran trade
deficits in several classes of manufactured
goods. (See figures in the sidebar on page 6.)
Figure 2 shows the breakdown of U.S.
trade by two aggregate classes of goods:
raw materials and manufactured goods.
The category of raw materials is the sum of
crude materials (e.g., coal, petroleum and
cotton) and crude foodstuffs (e.g., grains,
produce, coffee and tea). The category of
manufactured goods is the sum of manufactured foodstuffs (e.g., meat, sugar and
processed fruits), semimanufactures (e.g.,
lumber, refined copper, and iron and steel
plates) and finished manufactures (e.g.,
textile manufactures, machinery, equipment, automobiles and their parts, metal
and steel, chemicals, and radios).
We see that the U.S. ran large deficits
in manufactured goods throughout most
of the 19th century, although the country
showed a declining trend after the Civil
War. Furthermore, the breakdown of trade

We hypothesize that
different phases of
industrialization lead
to structural changes
that cause a nation’s
comparative advantage
to change relative to
those of other nations.

ABOUT THE AUTHORS
Yi Wen (left) is an economist and assistant vice president at the
Federal Reserve Bank of St. Louis. His research interests include
macroeconomics and the Chinese economy. He joined the
St. Louis Fed in 2005. Read more about the author and his research
at https://research.stlouisfed.org/econ/wen.
Brian Reinbold (right) is a research associate at the Federal
Reserve Bank of St. Louis.

REGIONAL ECONOMIST | www.stlouisfed.org/re 5

Commodities Composition
of U.S. Historical Trade
Figure 2 is the trade balance of
two commodity aggregates: raw
materials and manufactured goods.
Figures 3 and 4 show the U.S. goods
composition of exports and imports
for several classes of commodities:
crude materials, crude foodstuffs,
manufactured foodstuffs, semimanufactures and finished manufactures.
Together these three figures clearly
demonstrate how industrialization
affected the composition of U.S.
trade and the overall trade balance.
The main takeaway is that finished
manufactures drove the U.S. trade
balance from 1821 to 1970. Producing finished manufactures requires
a certain level of manufacturing
sophistication and therefore represents a high level of industrialization.
From 1821 to 1870, the U.S. was less
industrialized, so it imported significantly more finished manufactures
than it exported, driving overall
trade deficits. However, after 1870,
the U.S. became increasingly more
developed relative to Europe and
thus was less reliant on imports of
finished manufactures, and exports
of finished manufactures steadily
increased. Ultimately, finished manufactures drove America’s overall
trade surpluses that persisted until
the 1970s.

Figure 2
U.S. Trade Balances of Raw Materials and Manufactured Goods as a Percentage of GDP
8%
6%
4%
2%
0%
–2%

Raw Materials

–4%
–6%

1820

1830

1840

1850

1860

1870

1880

1890

1900

1910

Manufactured Goods

1920

1930

1940

1950

Figure 3
Goods Composition of U.S. Exports
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%

1821

1831

1841

1851

1861

1871

1881

1891

1901

1911

1921

1931

1941

1951

1961

Crude Foodstuffs
Manufactured Foodstuffs
Crude Materials
Semimanufactures
Finished Manufactures

Figure 4
Goods Composition of U.S. Imports
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%

1821

1831

1841

1851

1861

1870

1880

1891

1901

1911

1921

1931

1941

1951

Crude Materials
Crude Foodstuffs
Manufactured Foodstuffs
Semimanufactures
Finished Manufactures

Sources and notes for Figures 2, 3 and 4
SOURCES: U.S. Census Bureau, 1975; measuringworth.com; and authors’ calculations.
NOTE: Data end in 1970.
6 REGIONAL ECONOMIST | Fourth Quarter 2019

1960

1961

1970

Figure 5
U.S. Goods Trade Balance with Europe as a Percentage of GDP
7%
6%
5%
4%
3%
2%
1%
0%
–1%
–2%
–3%

1820

Total
1830

1840

1850

1860

1870

United Kingdom
1880

1890

1900

1910

France
1920

1930

Germany
1940

1950

Other
1960

1970

SOURCES: U.S. Census Bureau, 1975; measuringworth.com; and authors’ calculations.

in manufactured goods gives us insight
into the progress of U.S. industrialization.
(See Figures 3 and 4.)
From 1821 to 1870, the U.S. posted
slight deficits in manufactured foodstuffs
and semimanufactures and substantial
deficits in finished manufactures. Manufactured foodstuffs (i.e., processed food)
typically is the first sector to industrialize
as it can be accomplished with little
capital and lots of labor—perfect for early
industrialization. Subsequently, semimanufactures generally require more
capital and sophisticated manufacturing
processes to transform raw materials
into products useful for other industrial
processes. Finally, finished manufactures
require significant amounts of capital
and maturation of other manufacturing
processes to be viable; therefore, they
represent a high level of industrial
sophistication.
The U.S. at this time lagged behind
Europe in manufacturing and thus was
more reliant on imports of finished manufactures. So the U.S. stage in development
relative to those of other industrial
nations led the country to run deficits in
manufactured goods. The composition
and size of the manufactured goods trade
deficits exemplify the United States’ relative industrial development.
Since European countries were the
only other industrialized economies at
this time, the U.S. had to import manufactured goods from that continent. This
was particularly true for finished manufactures because European countries were
the only nations further along in their
industrial development to possess the

manufacturing sophistication necessary
to fabricate these goods. Figure 5 shows
the U.S. goods trade balance with Europe
as a percentage of GDP.
Trade with Europe was primarily driven
by trade with Great Britain: The U.K.
represented around 60% of total U.S.
trade (the sum of exports and imports)
with Europe and around 40% of overall
trade throughout most of the 19th century. The close historical ties between
the U.S. and the U.K. made them natural
trading partners.
Furthermore, trade with the U.K. would
be essential for America’s own industrialization. Since the U.K. was the first country to industrialize, that country could
produce more capital-intensive goods at
lower cost than the U.S., so the U.S. would
have to rely on imports to satisfy demand
for manufactured goods.
We see that the U.S., on average, ran
deficits with Europe from 1821 to 1840.
So the U.S. likely imported a significant
amount of capital goods and manufactured goods from the U.K. and the rest
of Europe during this period to spur its
own industrialization. Although the U.S.
initially ran deficits with Europe, the trade
balance fluctuated from deficit to surplus
from 1840 to 1870. The U.S. imported
manufactured goods from Europe, while
Europe relied on raw materials from
the resource-rich U.S. to sustain its own
industrialization.

© GEORGE MARKS/GETTY IMAGES PLUS

Phase 2 (1870-1970)
U.S. consumers benefited from
imported manufactured goods, and
furthermore, the country could import
REGIONAL ECONOMIST | www.stlouisfed.org/re 7

Figure 6
U.S. Services Trade Balance as a Percentage of GDP
5%
4%
3%
2%
1%
0%
–1%
–2%
–3%

Exports

–4%
1929

1939

1949

1959

Imports
1969

Net Exports
1979

1989

1999

2009

SOURCES: U.S. Bureau of Economic Analysis, Haver Analytics and authors’ calculations.

capital goods to facilitate its own industrialization. By 1870, improved manufacturing methods and the proliferation
of railroads propelled the U.S. into the
second phase of industrialization, which
featured capital-intensive mass production of manufactured goods and machinery. This shift corresponds with a turning
point in the U.S. trade balance—from
persistent trade deficits to persistent trade
surpluses. (See Figure 1.)
Increased sophistication and maturation of U.S. manufacturing drove this
change as the country relied less on
imports of manufactured goods, and
exports of manufactured goods increased.
In 1869, the U.S. imported three times
as many manufactured goods as it
exported, but by the turn of the century,
the United States—now a manufacturing
powerhouse—ran a full-fledged surplus
in manufactured goods. (See Figure 2.)
Furthermore, when we look at the composition of manufactured goods, we see how
U.S. industrialization affected the country’s trade balance during this period.
The U.S. began to run persistent trade
surpluses in manufactured foodstuffs by
the mid-1870s. The U.S. at this point had
well-developed labor-intensive manufacturing and thus was less reliant on
imports and could export more of these
goods. Furthermore, the U.S. trade deficit
in finished manufactures shrank considerably in the 1870s, which was exceptionally important in shrinking the country’s
overall trade deficit. The shrinking deficit
in finished manufactures exemplifies
America’s increasing sophistication in
manufacturing capital-intensive goods. In
8 REGIONAL ECONOMIST | Fourth Quarter 2019

1898, the U.S. began to run consistent
surpluses in finished manufactures,
signifying the nation as a global industrial
powerhouse.
Returning to Figure 5, we also see a
noticeable upward shift in the overall U.S.
trade balance with Europe starting in the
early 1870s. The average U.S. trade balance with Europe from 1821 to 1870 was
essentially zero but rose to a surplus of
about 1.7% of GDP from 1870 to 1970.
Although the U.S. began to run trade
surpluses with Europe prior to 1870, the
key takeaway is the shift in level. The
year 1870 marks a turning point in the
country’s relative comparative advantage
with Europe. The U.S. entered the capitalintensive phase of industrializing and
was then quickly catching up to Europe’s
manufacturing prowess. The U.K. capital
per worker was 10% higher than U.S.
capital per worker in the 1870s, but by
1900, the U.S. ratio was 90% higher (i.e.,
more capital intensive) than that of the
U.K. In addition, the U.K. accounted for
43% of world manufactured exports in the
mid-1880s, whereas the U.S. accounted for
only 6%. By 1913, however, the U.K. share
of manufactured exports had fallen to
32%, while the U.S. share had more than
doubled.2
Instead of just following Europe’s industrialization, the U.S. became a leading
innovator, and its manufacturing prowess
rapidly caught up to the rest of Europe.
Ultimately, the U.S. relied less on imports
of manufactured goods from Europe, and
its manufacturing exports flourished,
which resulted in trade surpluses that
persisted until 1970.
Phase 3 (1970-Present)
Since the 1970s, the U.S. has shifted to
the welfare stage, featuring credit-based
mass consumption with financial innovations. This shift implies that the country
became able to consume more tangible
goods than it produced by providing
services (such as consulting and financial
services) to the world.
During the early 1970s, the U.S. goods
trade balance experienced another
inflection point—from trade surpluses to
trade deficits. (See Figure 1.) Again, this
shift also corresponded with a structural
change in the economy as the U.S. entered
this third stage of development.
Figure 6 shows the U.S. trade balance in

© BAONA/E+/GETTY IMAGES PLUS

services from 1929 to 2018.
Starting in 1970, the U.S. services trade
balance qualitatively mirrors the country’s
goods trade balance: The trade balance in
services goes from persistent deficits to
continuously increasing surpluses, while
the trade balance in goods goes in the
opposite direction. Also, the volume of
U.S. trade in services has nearly tripled
since 1970, demonstrating the country’s
global comparative advantage in providing services. In addition, we find that the
U.S. began to run trade deficits in goods
with Europe after 1980 and that the U.S.
has been running trade surpluses in services with Europe since 1999 (the first year
that data are available).
Other Factors Affecting
the Trade Balance
The U.S. ran persistent trade deficits for
long periods of its history, just as it does
today. Yet, trade deficits did not inhibit
U.S. development and may have even
facilitated industrialization as the country
imported capital goods to improve its own
manufacturing during this first phase of
industrialization.
We use our theory of global shifting of
relative comparative advantage to explain
these long-run shifts in the level of the
U.S. trade balance. We saw how industrialization affected the composition of U.S.
exports and imports, and how relative
development could affect trade balances
with other nations (namely Europe). One

caveat to our hypothesis is that it is not
clear how industrialization necessarily
results in deficits or surpluses.
Clearly, industrialization affects the
composition of goods that a nation can
produce, which then affects what goods
that nation can trade (e.g., a country cannot export cars if it cannot produce them).
However, this does not necessarily imply
trade deficits or trade surpluses. According to the national accounting identity, net
exports are the difference between gross
savings and gross investment.3 Therefore,
industrialization has to affect gross savings
or gross investment to affect the trade balance, but this mechanism is not obvious.
Furthermore, it’s clear how comparative
advantage drives the pattern of observed
trade, but comparative advantage does
not necessarily explain why these deficits
or surpluses persisted in each phase. For
example, when the U.S. runs a persistent
trade deficit (as we see in Phase 3), foreigners are willing to exchange goods for U.S.
financial assets, such as U.S. dollars and
U.S. securities, and are willing to hold
these financial assets for prolonged periods
of time. Why are foreigners satisfied with
holding on to U.S. financial assets instead
of exchanging them for U.S. goods?
Phase 3 corresponds with a unique
development in the international financial system: the end of the Bretton Woods
system and the rise of the U.S. dollar as
the world reserve currency. Essentially,
the U.S. dollar became as good as gold,

It’s clear how comparative advantage drives
the pattern of observed
trade, but comparative
advantage does not
necessarily explain
why these deficits or
surpluses persisted in
each phase.

REGIONAL ECONOMIST | www.stlouisfed.org/re 9

© CLAFFRA/ISTOCK/GETTY IMAGES PLUS

and foreigners have been willing to hold
U.S. dollar securities as a safe store of
value, leading to persistent trade deficits
in Phase 3.4 Extending this logic to the
previous phases, gold was useful for settling international transactions, and the
precious metal also served as a safe store
of value.
This logic implies that the U.S. must
have experienced persistent net outflows
of gold during Phase 1 and persistent net
inflows of gold during Phase 2. Indeed,
the historical data reveal net outflows of
gold from the U.S. during the early 19th
century and net inflows of gold to the U.S.
during the early 20th century. So during Phase 2, the U.S. likely accumulated
and maintained large holdings of gold as
a safe store of value, resulting in persistent trade surpluses. Phase 1 mostly saw
gold flowing out of the U.S., and foreigners were willing to hold on to this gold.
Another possible factor that sustained the
U.S. trade deficits during Phase 1 is that
foreigners were willing to hold U.S. land
as a safe store of value.
To summarize, each phase may have
corresponded with a financial asset serving as a safe store of value (gold and land
in Phase 1, gold in Phase 2, and the U.S.
dollar in Phase 3), and others were willing
to hold these assets in each phase, which
ultimately led these trade patterns to persist for many decades.
Conclusion
Trade is complicated, and further
research is needed to better understand
these long-term historical trends. Studying both changes in the U.S. industrial
composition and how this may affect
savings, investment and the holdings of
financial assets can help build a complete
picture of what factors drove the historical
U.S. trade balance.
However, it seems reasonable to expect
that transitioning into different stages
of industrialization will cause structural
changes in an economy, including changes
in a country’s comparative advantage
relative to those of other nations. And
comparative advantage is the driving
force behind international trade. So not all
developing countries will follow the same
pattern (i.e., from trade deficit to surplus,
back to deficit), but we would expect to see
long-run shifts in overall trade balances as
a nation develops.

10 REGIONAL ECONOMIST | Fourth Quarter 2019

(This article was published online Feb. 6.)

ENDNOTES
1
2
3

4

The periods of all graphs are dictated by data
availability.
See Kitson and Michie.
This idea follows from the national account identity
that gross domestic product (GDP) is the sum of
consumption, investment, government spending and
net exports (Y = C + I + G + NX). Gross savings are
defined as GDP minus consumption and government
spending (S = Y – C – G). Then by rearranging the national accounting identity with the definition of gross
savings, we obtain the relationship that net
exports are equal to national savings minus investment
(NX = S – I). Therefore, a nation runs a trade deficit
when savings are less than investment (S < I) and
runs a trade surplus when savings are greater than
investment (S > I).
See Reinbold and Wen, 2018, for more details.

REFERENCES
Kitson, Michael; and Michie, Jonathan. “The Deindustrial
Revolution: The Rise and Fall of U.K. Manufacturing,
1870-2010.” Working Paper No. 459, Centre for Business Research, University of Cambridge, June 2014.
See www.cbr.cam.ac.uk/fileadmin/user_upload/
centre-for-business-research/downloads/workingpapers/wp459.pdf.
Reinbold, Brian; and Wen, Yi. “Understanding the Roots
of the U.S. Trade Deficit.” Regional Economist.
Oct. 9, 2018, Vol. 26, No. 3, pp. 4-9. See stlouisfed.
org/publications/regional-economist/third-quarter-2018/understanding-roots-trade-deficit.
Reinbold, Brian; and Wen, Yi. “Historical U.S. Trade
Deficits.” Federal Reserve Bank of St. Louis
Economic Synopses, No. 13, May 17, 2019.
U.S. Census Bureau. “Chapter U: International Transactions and Foreign Commerce,” in Bicentennial Edition:
Historical Statistics of the United States, Colonial
Times to 1970. Part 2. Washington, D.C.: Government Printing Office, September 1975. See www.
census.gov/library/publications/1975/compendia/
hist_stats_colonial-1970.html.

Insights from the St. Louis Fed’s Blogs
On the Economy blog (stlouisfed.org/on-the-economy)
Rising Student Debt and the Great Recession
Graduate students and four-year undergrads have taken on an increasing fraction of annual
student loans, as tuition and fees have continued to climb and students have spent more
years in college.
“Average annual borrowing among students at two-year colleges increased by nearly 50%
during the recession, double the contemporaneous rise in enrollment levels. Four-year
college students also took on substantially more debt immediately before and during the
recession, thereby also contributing to the overall debt growth.”
—Oksana Leukhina, Senior Economist
© JUPITERIMAGES/STOCKBYTE/GETTY IMAGES PLUS

stlouisfed.org/on-the-economy/2020/january/rising-student-debt-great-recession

Healthier Countries, if Not Wealthier Countries
The gap between rich and poor countries seems to be widening. But the health of these
poorer countries seems to be catching up to their wealthier counterparts.
“In 1960, the [crude death] rate in sub-Saharan countries was more than double that of
the high-income countries. It then declined remarkably faster than in the high-income
countries, which experienced a barely noticeable decline. By 2017, the crude death rate
was the same in both groups of countries.”
—Guillaume Vandenbroucke, Research Officer and Economist
stlouisfed.org/on-the-economy/2019/december/healthier-countries-wealthier-countries
© AL-TRAVELPICTURE/ISTOCK/GETTY IMAGES PLUS

FRED Blog (fredblog.stlouisfed.org)
Working 9 to 5: Women Make Up More of the Workforce
A look at women in the workforce by sector
“It looks like the employment share of women has increased or at least persisted
in sectors where women have achieved a strong presence. But it doesn’t seem like
women are increasing their share in every given sector. Economists call this the
composition effect.”
—Diego Mendez-Carbajo, Senior Economic Education Specialist
fredblog.stlouisfed.org/2020/01/working-9-to-5-women-make-up-more-of-the-workforce

Inside FRASER blog (insidefraser.stlouisfed.org)
Dismal Facts: Invisible Revisions
Policymakers use the best data available to them, which is often revised after the fact.
This Inside FRASER explores how data revisions can complicate research of historical
economic policy.
“Ultimately, the data collection process in economics will always be a little imperfect.
Unlike the physical sciences like chemistry or physics, in economics we typically can’t
gather data from controlled experiments, so our data is inherently a bit messy.”
—Andrew Spewak, Senior Research Associate, and Genevieve Podleski, Senior Analyst
insidefraser.stlouisfed.org/2020/01/invisible-revisions

REGIONAL ECONOMIST | www.stlouisfed.org/re 11

New Payments Technologies Seen
Bringing Efficiency and Disruption
By Alexander Monge-Naranjo
© MSTUDIOIMAGES/E+/VIA GETTY IMAGES

KEY TAKEAWAYS
• Digital technologies have begun to
transform the payments and banking
systems, but the final impact of the
change is far from determined.
• However, faster payments are here to
stay, and the new payments technologies will disrupt legacy deposit and
payments franchises.
• The level of disruption on incumbents
will depend on the structure of their
legacy business and on their response
in adopting the new technologies.

D

igital technologies have changed the
way we buy clothing, book trips, and
schedule our work and social gatherings.
Once considered eccentric and even snobbish alternatives to the established way of
doing business, websites and smartphone
apps have come to dominate our daily
activities and transactions.
Not surprisingly, these same technologies have also begun transforming the
payments and banking systems. As when
shopping for shoes or getting airplane
tickets, consumers are set to benefit from
greater convenience, higher speed and
lower costs when searching for products
and making and receiving payments.
Quite likely, the new payment methods
will trigger greater competition for funds,
and thus households will end up earning
higher returns on their deposits. As for
merchants, their benefits may arise from
faster access to sales revenues and from
lower interchange fees. Some of the existing
banks—and some new entrants as well—
may contribute to the adoption of technologies by offering more open and efficient
access to the payments system.
The identity and even the nature of
the new dominant mechanisms for the
payments and banking systems are far

12 REGIONAL ECONOMIST | Fourth Quarter 2019

from determined yet. Innovation can be
divided broadly along two related dimensions: the adoption of faster, more efficient
payment systems, and the introduction
and adoption of digital currencies or
cryptocurrencies.
For both, as briefly reviewed in this
article, the possibilities are ample. (See,
for example, the accompanying figure,
explained below.) At this point, however,
only two things are certain. The first is that
faster payments are here to stay. The second
is that along with more efficiency, the new
payments technologies will also disrupt
profitable legacy deposit and payments
franchises. These disruptions have already
been seen in the retail industry, where the
adoption of online technologies has led to
the observed widespread closures of brickand-mortar stores.
Banks that are unable or unwilling
to upset their business models may be
doomed to downsize and even be left
behind completely. Central banks around
the globe are increasingly aware of the
potential disruptions to incumbent commercial banks, and they are responding in
different ways.
Evolving Means of Payments
The payments system has been evolving in two broad dimensions: (1) through
changes in the set and efficiency of the
mechanisms available to transfer funds
and (2) through the emergence of crypto
or digital currencies, which has led to a
substantial innovation in the currencies
available to make transactions.
With respect to the first, improved efficiency in the mechanisms for making and
receiving payments has been introduced by
private banking and nonbanking institutions, as well as central banks, resulting in

upgrades and faster speed of bank accountbased payment networks.
As discussed by multiple authors,1 the
world has moved from the standard two
to three business days required to clear a
check to a global standard of fast payments
with near real-time availability of the funds
for payees on a 24/7 basis.
For example, consider a parent who
needs to pay for a child’s violin lessons.
Paying through a traditional bank account,
the parent would write a check to the violin
instructor. For the money to be finally
deposited into the instructor’s account,
the bank of the parent’s account first has
to be debited, and then the money has to
be transferred to the violin teacher’s bank,
which finally has to deposit the money into
the teacher’s account. Such a transaction
could take two or even three days, plus
the time it takes the instructor to go to the
bank. With digital technologies, the payment can be done almost instantaneously
with just a couple of clicks using apps such
as Venmo, PayPal, Apple Pay or Google Pay.
The adoption of those payment systems is widespread, reaching countries in
very different stages of development. For
example, Swedish private mobile payment
system Swish and the Korean Electronic
Banking System are well rooted in these
developed countries. The Mexican SPEI
and the Costa Rican SINPE are both managed seamlessly by the respective central
banks of these two developing countries.
All in all, those payment systems allow
households and businesses that register
and install the required apps to quickly
transfer and receive payments, circumventing the need for commercial banks to clear
their checks.
Relative to using checks or carrying cash, these new technologies offer

ABOUT THE AUTHOR
Alexander Monge-Naranjo is an economist and research officer at the Federal Reserve Bank
of St. Louis. His research interests include growth and development, labor and applied contract
theory. He joined the St. Louis Fed in 2012. Read more about the author and his research at
https://research.stlouisfed.org/econ/monge-naranjo.

Figure 1
The Money Flower
Digital

Central bank-issued
Token-based

Widely
accessible

CB reserves
and
settlement
accounts

Bank
deposits
CB
accounts
(general
purpose)

CB digital
tokens
(wholesale
only)
CB digital
tokens
(general
purpose)

Private digital
tokens
(wholesale
only)

CB = Central Bank
Cash

Private digital tokens (general purpose)

SOURCE: Committee on Payments and Market Infrastructures (CPMI) and Markets Committee.

advantages—such as time savings, logistics
and accounting—that can be substantial
for both the payers and the receivers. For
banks and other intermediaries in the business of clearing payments, these advances
can require a redirection of their activities
and, quite possibly, a reduction in their
employment.
Digital Currencies
Similarly, the development, introduction
and diffusion of multiple cryptocurrencies have received much attention from the
private sector and central banks across the
globe.2 To analyze the emergence of these
new forms of money, economists Morten
Bech and Rodney Garratt have proposed a
typology of money, the so-called “money
flower,” classifying currencies by whether
they are digital, whether they are central
bank-issued, whether they are widely accessible and whether they are token-based.3
The accompanying figure reproduces
a version of Bech and Garratt’s money
flower, as modified by the Committee on
Payments and Market Infrastructures
(CPMI) and the Markets Committee; this
is a simple Venn diagram that summarizes
the different forms of money that can be
arise. While departing from traditional
monetary theory in its focus on the circulation velocity and frequent-use-in-payments
criteria for defining and understanding
money,4 Bech and Garratt’s money flower
helps map the possible forms of money that
will be used in the near future.

On the one hand, we have very traditional categories, such as cash, which are
token-based money that is widely accessible and nondigital. On the other hand,
we have central bank reserves and settlement accounts, which are nontoken-based,
digital, and available only to financial
intermediaries.
A category of particular interest is that
of private digital tokens. As shown by the
figure, they can be either wholesale only
or widely accessible. Also, depending on
the form of their ledger technology, they
can be “permissioned” (i.e., maintained by
a trusted third party), such as Ripple and
Corda, and others can be open or “permissionless,” such as Bitcoin and Ethereum.
Which ones of these cryptocurrencies, if
any, will eventually dominate the global
payments system—or major components of
it—is hard to predict at this point and the
subject of interesting debate.5
Disruption in Payments
and Banking Industries
The improved efficiency brought about
by the new payments technologies will
likely bring some disruption in existing
banking markets. As with other markets,
the level of disruption will depend on the
response of incumbent banks to the new
technologies as well as the structure of
their legacy business.
Using data from a study by consulting firm McKinsey & Co., Darrell Duffie
argues that the disruption for incumbent

banks will be quite different between
North America (U.S. and Canada) and
the rest of the world.6 In North America,
the major sources of disruption will be in
the segments of consumers’ credit cards
and domestic transactions. Much of the
usage of credit cards is for convenience
of payment and not for credit, and U.S.
banks rely more heavily on the credit card
interchange and payment fees than foreign
banks do. For the rest of the world, the
major disruptions will be on the commercial segments, specifically on the revenue
from account-related liquidity and domestic transactions.
In any event, the overall disruption of
the new technologies may be dampened
by two forces. First, the finance industry
has historically been among the fastest in
adopting technological changes. Hence,
it is expected that incumbent banks have
long been preparing themselves. Second,
with the low inflation and low interest rate
environment observed in most countries
lately, the costs of liquidity are also historically low. Hence, the pressure to substitute
away from existing media of payments is
also low.
Qiuhan Sun, a research associate at the Bank,
provided research assistance.
(This article was published online Dec. 17.)

ENDNOTES
1
2
3
4
5

6

For example, see Duffie.
See CPMI and Markets Committee.
See Bech and Garratt.
See the extensive discussion by Townsend.
David Andolfatto of the St. Louis Fed has written
extensively on topics of cryptocurrencies, including
their implications for policy. Interested readers in
the topic should look into his thoughts about these
issues at http://andolfatto.blogspot.com/2017/12/
my-perspective-on-bitcoin-project.html.
See Duffie.

REFERENCES
Bech, Morten; and Garratt, Rodney. “Central Bank
Cryptocurrencies.” BIS Quarterly Review, September
2017, pp. 55-70.
Committee on Payments and Market Infrastructures
(CPMI); and Markets Committee. “Central Bank Digital
Currencies.” CPMI Papers No. 174, Bank for International Settlements, March 2018.
Duffie, Darrell. “Digital Currencies and Fast Payment
Systems: Disruption Is Coming.” Draft presented to
the Asian Monetary Policy Forum in Singapore, May
2019.
McKinsey & Co. “Global Payments 2017: Amid Rapid
Change, an Upward Trajectory.” White paper, October
2017.
Townsend, Robert M. “Distributed Ledgers: Innovation
and Regulation in Financial Infrastructure and Payment Systems.” Working paper, MIT, April 2019.
REGIONAL ECONOMIST | www.stlouisfed.org/re 13

Immigration: The Characteristics
of Green Card Holders
By Subhayu Bandyopadhyay and Asha Bharadwaj
© WELCOMIA/ISTOCK/GETTY IMAGES PLUS

KEY TAKEAWAYS
• From 1989 to 2017, Mexico was the
largest source of U.S. lawful permanent
residents, or green card holders. Other
big sources were China, the Philippines
and India.
• While many green cards are given to
family members of U.S. citizens and
permanent residents, a large number
also go to skilled workers.
• Green card holders, on average, are
younger than the overall U.S. population. They could help support an aging
U.S. population in the future.

O

ne of the pillars of the U.S. immigration system is its permanent
residency program. More commonly,
immigrants in this category are known as
green card holders.1 A key feature of this
program is that the green card holder has
authorization to work and stay indefinitely
in the U.S. as long as certain requirements
are met. A central long-term feature of
this program is that it provides a pathway
to citizenship, in which the person can
apply to become a naturalized U.S. citizen
after a number of years of residence.
In addition to benefiting the immigrant,
these features present costs and benefits
for society at large. For industries suffering
a shortage of workers, a program like this
can provide much-needed relief through
the supply of a permanent and potentially
skilled workforce. On the other hand, if the
program creates a glut in certain labor markets, outcomes for natives could worsen.
Looking into the future, the U.S. sees
a large fraction of its workforce nearing
retirement (i.e., the baby boomers). The
permanent residency program, especially
in the case of green card holders who are
at working age or younger, contributes
workers who can pay into the Social Security system to sustain the elderly.
14 REGIONAL ECONOMIST | Fourth Quarter 2019

Figure 1
Who Obtained Permanent Resident Status?
By Type of Admissions, FY 1986 to FY 2017
Immediate Relatives of U.S. Citizens
Family-Sponsored Preferences
Employment-Based Preferences
Refugees and Asylees
Other
Diversity
0

2

4

6

8

10

12

14

Millions of People

SOURCES: U.S. Department of Homeland Security and authors’ calculations.
NOTES: The annual periods are the U.S. government’s fiscal years. People in the diversity category are randomly
selected from applicants who are from countries with relatively low rates of immigration to the U.S.

Clearly, the more we know about the
characteristics of green card holders that
are relevant to such economic outcomes,
the better we can infer about the effects of
legal immigration on the U.S. economy.
Accordingly, this article looks into some
relevant characteristics of U.S. green card
holders based on available evidence.
The Allocation of Permanent
Resident Status
The U.S. Immigration and Nationality
Act of 1965 and subsequent legislation
established worldwide annual limits on
the number of immigrants to be granted
permanent residency. Immediate relatives
of U.S. citizens (e.g., spouse, parents or
children under the age of 18) and refugees
are exempted from this limit. For the rest,

there are preference categories and annual
national origin limits.2
Figure 1 shows that by far the largest
number of green cards since fiscal year
1986 through fiscal year 2017 was given
to immediate relatives of U.S. citizens.
This is followed by the category of familysponsored preferences, which includes
the adult children of U.S. citizens and the
spouses and children of green card holders. Employment-based preferences garnered the third-largest number of green
cards; this category is designed to attract
a talented and skilled workforce to the
country, with the highest preference given
to outstanding professors and researchers,
among others. This was followed by several other categories, including refugees
and asylees.

ABOUT THE AUTHORS
Subhayu Bandyopadhyay (left) is an economist and research officer at the
Federal Reserve Bank of St. Louis, and editor of the Regional Economist.
His research interests include international trade, development economics
and public economics. He has been at the St. Louis Fed since 2007.
Read more about the author and his research at
https://research.stlouisfed.org/econ/bandyopadhyay.
Asha Bharadwaj (right) is a research associate at the Federal
Reserve Bank of St. Louis.

Origin Nations of Permanent
Residents
Mexico is the largest source nation
of permanent residents, with nearly
171,000 green cards given to people born
in Mexico in 2017.3 Mexico has been
the leading source of lawful permanent
residents (LPRs) every year since fiscal
year 1989, accounting for 20.5% of those
receiving this status; 1989 is the earliest
year for which we could get data related
to source nations. However, the share of
green cards received by Mexican nationals
in the last 10 years, from 2007 to 2017, is
lower (14.4%) compared with the overall
share from 1989 to 2017. China (5.7%), the
Philippines (5.4%), India (5.3%) and the
Dominican Republic (3.6%) follow Mexico
as the major sources of LPRs over the
1989-2017 period.
Occupations of U.S. Permanent
Residents
The accompanying table provides occupational details of the green card holders in
fiscal year 2017. Excluding the “unknown”
category, for which information is absent,
the largest category is students or children at 23.6%, followed by homemakers at
12.7%. This makes sense considering the
fact that immediate relatives of U.S. citizens (i.e., spouses and dependent children)
are automatically eligible for permanent
residency. Furthermore, a green card
holder’s spouse and dependent children get
preference in receiving green cards. The
category of management, professional and
related occupations is 10.1% of the total,
which reflects to some degree the preference given to skills in the allocation of
green cards.
Age Profile of Green Card Holders
The fact that the largest category in
the accompanying table (excluding the
category of unknown) comprises students
and children is encouraging from an
economic dependency standpoint; today’s
students can contribute to a skilled future
workforce that can pay into the Social
Security system. Delving deeper into this
issue, we present Figure 2. Around 22% of
the total number of permanent residents
in fiscal year 2017 were younger than 20,
which is comparable with the 25.2% share
of this age group in the total U.S. population. This group will gradually enter

Permanent Residents by Occupation, FY 2017
People
Students or Children

Percentage

266,526

23.6%

Homemakers

143,149

12.7%

Retirees or Unemployed

115,889

10.3%

Management, Professional and Related Occupations

114,218

10.1%

Production, Transportation and Material-Moving Occupations

42,745

3.8%

Sales and Office Occupations

41,284

3.7%

Service Occupations

28,021

2.5%

Construction, Extraction, Maintenance and Repair Occupations

12,867

1.1%

Farming, Fishing and Forestry Occupations

12,594

1.1%

44

0.0%

Unknown

349,830

31.0%

TOTAL

1,127,167

Military

SOURCES: U.S. Department of Homeland Security and authors’ calculations.
NOTE: The annual period is the U.S. government’s fiscal year.

Figure 2
Age Groups as a Share of Population, FY 2017
Lawful Permanent Resident Population

U.S. Population

75 years and over
65 to 74
60 to 64
55 to 59
50 to 54
45 to 49
40 to 44
35 to 39
30 to 34
25 to 29
20 to 24
15 to 19
10 to 14
5 to 9
Under 5
15

10

5

0
Percentage

5

10

15

SOURCES: U.S. Department of Homeland Security and authors’ calculations.
NOTE: The annual period is the U.S. government’s fiscal year.

working age and contribute to future U.S.
national income.
The group older than 54 represents
around 13.4% of permanent residents,
compared with 25.9% for that age group
within the total U.S. population. The older
members of this group are already retired
or will start retiring in the coming years,
adding—all things being equal—to the

nation’s dependency burden. Therefore,
the fact that the share of this group among
green card holders is smaller than the corresponding share for the U.S. as a whole
is encouraging in terms of the nation’s
future dependency burden.

(continued on Page 23)
REGIONAL ECONOMIST | www.stlouisfed.org/re 15

The Role of Industry Mix in
Regional Business Cycles
By Charles S. Gascon and Jacob Haas
© KALI9/E+/GETTY IMAGES PLUS

Figure 1

KEY TAKEAWAYS
•		The business cycles of individual U.S.
states can diverge from the national
cycle. Industry mix within those states
can help explain why this may happen.
• Certain industries, like construction,
tend to be the more responsive to
national expansions and recessions.
Other sectors, like government, are
less responsive.
• Understanding how differences in
industry composition affect regional
business cycles may help local leaders
better tailor their policies to downturns
and expansions.

T

he U.S. has been in an economic
expansion for more than 10 years,
adding over 21 million workers to payrolls
since June 2009 and seeing a 2.3% average
annualized increase in real gross domestic
product (GDP) each quarter. The expansion was preceded by a recession that lasted
from December 2007 to June 2009, during
which time over 7 million workers were
dropped from payrolls and real GDP fell
by an average annualized rate of 2.6% each
quarter. Expansions and recessions like
these are two stages of what economists call
the business cycle, which is often marked
by coinciding movements in economic
indicators like employment and GDP.1
While the nationwide business cycle
is important, the U.S. is not a uniform
country, and research has shown that different regions have varying business cycles.
Economists Michael Owyang, Jeremy Piger
and Howard Wall found that U.S. states
experience significantly different growth
rates, and sometimes they may not even be
in the same phase of the business cycle as
each other at the same time. The authors
found that some states, like Maryland in
the mid-1990s, fell into a recession not
connected at all with a national recession.
16 REGIONAL ECONOMIST | Fourth Quarter 2019

Responsiveness of State Nonfarm Employment to Changes in U.S. Real GDP

0.08 to 0.19
0.19 to 0.34
0.34 to 0.50
0.50 to 0.65
0.65 to 0.94

SOURCES: Bureau of Labor Statistics, Bureau of Economic Analysis and authors’ calculations.
NOTES: Data are correlations of the change in state employment and the change in U.S. real GDP from the first quarter of
1990 to the second quarter of 2019. Changes in data are annualized and taken from quarter-to-quarter. The average state
employment responsiveness to U.S. real GDP is 0.42, which means the average state would experience a 0.42% change in
employment for every 1% change in U.S. real GDP. Each color grouping represents 1 standard deviation, except for the first
and last groupings, which extend to the minimum and maximum values.

Other states were in recession months
before the national economy reached that
stage, or remained in a recession long after
the nation entered an expansionary phase.
Missouri, for example, switched into a
recession in August 2000, seven months
prior to the start of a national recession.
State Business Cycles and
Industry Mix
A basic way to measure the movements
of state business cycles in relation to the
national cycle is to see how a change in U.S.
GDP or U.S. employment would affect each
state. Figure 1 shows the relation between

a change in U.S. real GDP and each state’s
employment levels.
States whose employment levels fluctuate more when overall GDP changes will
appear as more sensitive or responsive to
the national cycle. For example, when U.S.
real GDP has changed by 1%, Nevada has
seen an average change in employment that
is double the national average change in
employment.2 The District of Columbia,
by comparison, has seen an employment
change less than one-fifth the national
average for every 1% change in U.S. real
GDP. Some states in the western and southeastern parts of the country have higher

ABOUT THE AUTHORS
Charles Gascon (left) is a regional economist and a senior coordinator in
the Research Division at the Federal Reserve Bank of St. Louis. His focus
is studying economic conditions in the Eighth District. He joined the
St. Louis Fed in 2006. Read more about the author and his research at
https://research.stlouisfed.org/econ/gascon.
Jacob Haas (right) is a research associate at the Federal Reserve
Bank of St. Louis.

rates of sensitivity to the national business
cycle, while many states in the Great Plains
seem to be less sensitive.3
One component driving these differences in regional business cycles could be
the types of jobs available in a given area.
Certain industries are more sensitive
to economic expansions and recessions.
Because industries often cluster by geography, there is potential for disparities in
employment growth between areas with different industry makeups. For example, states
with higher employment rates in the energy
industry, like Texas, will react differently to
oil price shocks than other states, which can
result in these states being out of sync with
the national economy. According to a 2016
study by Maria Arias, Charles Gascon and
David Rapach, the technology hubs of San
Francisco and San Jose suffered relatively
severe recessions in the early 2000s after
the dot-com bubble burst, while other
California metro areas like Riverside and
Sacramento avoided recessions altogether
during that period.
The accompanying table gives a simple
measure of the sensitivity or responsiveness of certain industries to the national
business cycle for the 1990-2019 period.
Industries whose employment levels
fluctuate more when overall GDP changes
correspond to higher sensitivity numbers.
When U.S. real GDP changes by 1%, U.S.
construction employment changes by 1.4%
on average, while government employment
sees a much smaller change of 0.1%.
Since 1990, U.S. employment in construction, professional and business
services,4 and manufacturing tends to be
the most responsive to national expansions
and recessions. Meanwhile, employment
in government, education and health care,
and utilities tends to be the least responsive
to U.S. expansions and recessions.
Because states have different industry
mixes, they will have different employment
levels in the more cycle-sensitive industries. Figure 2 displays the percentage of
state employment in the three most sensitive industries: construction, professional
and business services, and manufacturing. In Michigan, these three industries
make up about 33% of all employment,
while they employ only 17% of workers in
Alaska. Many states located in the eastern
part of the Midwest and southeastern parts
of the U.S. have relatively high employment
shares in these sensitive industries.

Responsiveness of U.S. Industry Employment to Changes
in the National Economy
Responsiveness to Change
in U.S. Real GDP

Responsiveness to Change
in Total U.S. Employment

Percentage of Total U.S.
Nonfarm Employment
(2019:Q3)

Construction

1.4

3.0

5.0

Professional and Business Services

0.9

1.8

14.2

Manufacturing

0.7

1.8

8.5

Information

0.6

1.5

1.9

Transportation and Warehousing

0.5

1.5

3.7

Wholesale Trade

0.5

1.2

3.9

Retail Trade

0.5

1.1

10.4

Total Nonfarm

0.4

1.0

100.0

Financial Activities

0.4

0.8

5.7

Leisure and Hospitality

0.4

0.9

11.0

Mining and Logging

0.3

1.1

0.5

Other Services

0.2

0.6

3.9

Government

0.1

0.1

14.9

0.0

0.0

16.1

–0.2

–0.2

0.4

Education and Health Services
Utilities

SOURCES: Bureau of Labor Statistics, Bureau of Economic Analysis and authors’ calculations.
NOTES: The first column indicates the change in employment in an industry that correlates to a percent change in U.S. real
GDP from 1990 to 2019. For example, construction employment will average a 1.4% change for every 1% change in U.S. GDP.
The second column indicates the response of industry employment to a 1% change in total U.S. nonfarm employment for
the same time period. The third column is the percentage of total nonfarm employment for the given industry. Changes in
employment and GDP are annualized and are quarterly-to-quarterly.

Figure 2
Employment Share in Most Responsive Industries by State

16.9% to 20.7%
20.7% to 24.3%
24.3% to 28.0%
28.0% to 31.6%
31.6% to 33.1%

SOURCES: Bureau of Labor Statistics and authors’ calculations.
NOTES: This map displays the state employment share in the three industries whose employment levels are the most sensitive to the change in U.S. real GDP—construction, professional and business services, and manufacturing. Employment data
are for 2018. The average state share of employment in high-responsiveness industries is 26.2%.

Conversely, some states have higher
employment levels in low-sensitivity industries. Figure 3 displays the percentage of

state employment in the three least sensitive
areas: government, education and health
services, and utilities. Many Northeastern
REGIONAL ECONOMIST | www.stlouisfed.org/re 17

but fails to account for other economic
factors. Regions have different education
levels, housing supply characteristics,
urban population shares and establishment
sizes—all of which can affect their local
business cycle or comovement with the
national cycle.7

Figure 3
Employment Share in Least Responsive Industries by State

(This article was published online Jan. 3.)

ENDNOTES
1

21.9% to 26.9%
26.9% to 30.8%
30.8% to 34.7%
34.7% to 38.6%
38.6% to 47.1%
2

SOURCES: Bureau of Labor Statistics and authors’ calculations.
NOTES: This map displays the state employment share in the three industries whose employment levels are the least sensitive
to the change in U.S. real GDP—government, education and health services, and utilities. Employment data are for 2018. The
average state share of employment in low-responsiveness industries is 32.8%.

states have high employment shares in less
sensitive industries, which may subdue these
states’ responses to fluctuations in national
economic conditions. Nevada has the lowest
level of low-sensitivity employment in the
U.S., which might have been one factor in
why its sensitivity rate in Figure 1 is so high.
Taken together, the employment shares of
high-sensitivity and low-sensitivity industries explain about half of the variation in
state responsiveness to changes in U.S. real
GDP,5 indicating that industry mix can play
a significant part in how state economies
move with the national business cycle.
A Closer Look at the Eighth District
The Eighth Federal Reserve District6
has a few states with relatively higher
sensitivities—Indiana, Kentucky and Tennessee are all above the national level of
employment sensitivity to GDP changes.
Arkansas, the least sensitive state in the
District to the business cycle, is about 16%
less sensitive to U.S. real GDP than the
national average in aggregate.
The share of manufacturing employment
in Indiana, Kentucky and Tennessee may
help explain their elevated sensitivity levels.
Indiana employs 17.2% of its workers in
manufacturing, which is more than double
the national level of 8.5%, while Kentucky
and Tennessee have manufacturing employment shares of 13.1% and 11.5%, respectively.
While these three states have relatively high
18 REGIONAL ECONOMIST | Fourth Quarter 2019

employment shares in this highly sensitive
industry, none have a combined employment
share in the lowest-sensitivity industries
above the national level, which may have
furthered the cycle sensitivity of these states.
Conclusion
There are significant differences in
the makeup of employment by industry
across the U.S. Some states will have
much of their economy based in highly
sensitive industries like construction,
professional and business services, and
manufacturing. Other states will rely
more on less sensitive industries, with
more workers in government, education
and health services, and utilities.
It is useful to understand how these
differences in industry mix affect regional
business cycles, especially when trying
to determine which areas may need the
most support during recessions or which
areas will experience more growth during
expansions. Employment shares in highsensitivity and low-sensitivity industries
can help explain some, but not all, of the
variation in state business cycles and their
relation to the national cycle.
Understanding the industry mix in an
area is just one step to being more cognizant of the diversity of the U.S. and its
economic composition. The correlative
analysis done here provides a basic understanding of business cycle responsiveness

3

4

5

6

7

The National Bureau of Economic Research (NBER) researches and establishes exactly when the peaks and
troughs of a business cycle in the U.S. have occurred.
For example, the NBER determined that a trough in
business activity occurred in June 2009, marking the
end of the Great Recession and the beginning of the
subsequent expansionary period.
Since 1990, Nevada has seen an employment change
of 0.93% for every 1% percent change in U.S. GDP,
while the U.S. in aggregate has seen an employment
change of 0.45% for every percent change in U.S. GDP.
Nevada far outpaces the next most responsive state,
Arizona, which has a responsiveness of 0.695%. Nevada
employs over 25% of its workers in the leisure and
hospitality industry, well above the national average of
11%. While this industry is not very responsive to U.S.
GDP on a national level, local conditions in this industry
could make this industry more responsive on a state
level. Nevada leisure and hospitality changes by 0.91%
for each percent change in U.S. GDP, while the national
level of this industry changes by only 0.35%.
The employment levels for every state were positively
correlated with national GDP and employment, indicating the importance of the national business cycle when
looking at state business cycles.
The professional and business services sector includes
areas such as business and legal support services,
temporary-help services, office administrators, building services workers, management workers, and other
professional and support services.
This value was obtained from the adjusted R 2 of a
regression of annualized change in U.S. real GDP on
employment shares in the three highest-sensitivity and
lowest-sensitivity industries.
Headquartered in St. Louis, the Eighth Federal Reserve
District includes all of Arkansas and parts of Illinois,
Indiana, Kentucky, Mississippi, Missouri and Tennessee.
This is according to the 2016 study by Maria Arias,
Charles Gascon and David Rapach, as well as a 2009
study by Michael Owyang, David Rapach and Howard
Wall. Additionally, certain state economies and
business industries will influence the national GDP
trends more than others because of how large they
are, causing a reciprocal relationship between state
employment and U.S. GDP and potentially biasing
our correlative results. For example, a downfall in the
California economy has a high likelihood of affecting
overall U.S. GDP simply because of how large the GDP
and population of the state are, which would lead to a
higher sensitivity measurement.

REFERENCES
Arias, Maria A.; Gascon, Charles S.; and Rapach, David E.
“Metro Business Cycles.” Journal of Urban Economics,
July 2016, Vol. 94, pp. 90–108.
Owyang, Michael T.; Piger, Jeremy; and Wall, Howard J.
“Business Cycle Phases in U.S. States.” The Review of
Economics and Statistics, November 2005, Vol. 87,
No. 4, pp. 604–16.
Owyang, Michael T.; Rapach, David E.; and Wall, Howard
J. “States and the Business Cycle.” Journal of Urban
Economics, March 2009, Vol. 65, No. 2, pp. 181–94.

DISTRICT OVERVIEW

Debt Developments
Developments in
inthe
theEighth
Eighth
District during
during First
FirstHalf
Halfof
of2019
2019
By Ryan Mather and Don Schlagenhauf
By Ryan Mather and Don Schlagenhauf
© KLH49/ISTOCK/GETTY IMAGES

Table 1

KEY TAKEAWAYS
• Inflation-adjusted debt levels in the
U.S. and Eighth District nearly returned
to their Great Recession peaks over
the first half of 2019.
• Student debt generally grew faster in
the U.S. and Eighth District than any
other debt category.
• Among the District’s four largest
metro areas, the delinquency rates
of student loans and auto debt are
historically high.

T

he Great Recession taught us that
developments in household debt
markets need to be monitored. In previous
Regional Economist articles, we have done
so by examining auto, consumer credit
card, mortgage and home equity line of
credit (HELOC) debt using developments
observed in the Federal Reserve Bank of
New York’s Consumer Credit Panel (CCP).1
This present article complements that
work by reporting on updated CCP data
for the first half of 2019. In doing so, we
consider an additional category of debt that
has recently garnered significant attention:
student loans. An important new finding
will be the rise in 90-day delinquency rates
for auto debt across key Eighth District
metro areas.
Debt Developments
in the First Half of 2019
Since 2013, total household debt has
steadily increased in both the U.S. and the
Eighth Federal Reserve District.2 In fact,
midyear debt levels in 2019 for these two

Debt Scorecard for the U.S. and Eighth District
United States
Year-over-Year
Percentage Change
2019:Q1

2019:Q2

Auto

2.93%

Credit Card

2.80%

Eighth District

90-Day
Delinquency Rate

Year-over-Year
Percentage Change

2010:Q1

2019:Q2

2019:Q1

2019:Q2

3.07%

4.59%

4.28%

2.51%

3.44%

12.76%

7.84%

1.99%

–9.32%

–8.78%

3.36%

1.08%

Mortgage

1.29%

2.53%

7.68%

Student Loans

4.41%

4.07%

8.73%

Total (Including
Student Loans)

1.59%

2.47%

Home Equity
Line of Credit

90-Day
Delinquency Rate
2010:Q1

2019:Q2

2.19%

3.98%

4.45%

2.26%

10.89%

7.56%

–8.84%

–6.46%

1.13%

0.63%

0.79%

0.82%

2.48%

3.77%

0.71%

11.18%

3.59%

2.77%

9.39%

13.87%

1.32%

2.20%

SOURCES: Federal Reserve Bank of New York/Equifax Consumer Credit Panel and authors’ calculations.
NOTES: Debt data were adjusted for inflation using the personal consumption expenditures chain-type price index;
data as of Aug. 13, 2019.

areas were at 92.8% and 99.5%, respectively, of
their peak levels during the Great Recession.
Table 1 focuses on the data by type of
debt for the first and second quarters of
2019 as well as the first quarter of 2010; this
2010 reference corresponds to the peak of
mortgage delinquency in our sample.
During the first half of 2019, auto and
credit card debt grew in the range of 2%
to 4% in all cases, with both the U.S. and
Eighth District experiencing slight upticks
in credit card debt accrual from the first
quarter to the second.
Mortgage debt accrual saw stronger
increases over this time frame, which is
significant given that it represents the largest portion of household debt. HELOC debt
has continued its declining trend.
Student debt consistently increased in

ABOUT THE AUTHORS
ABOUT THE AUTHORS

Don Schlagenhauf (left) is an economist at the Federal Reserve Bank of St. Louis. His
Don Schlagenhauf (left) is an economist at the Federal Reserve Bank of St. Louis.
research focuses on macroeconomics and policy, with emphasis on housing. He joined
His research focuses on macroeconomics and policy, with emphasis on housing.
the St. Louis Fed in 2017. Read more about the author and his research.
RyanMather
Mather(right)
(right)isisa aresearch
research
associate
at the Federal Reserve
Ryan
associate
at the
Bank ofReserve
St. Louis.
Federal
Bank of St. Louis.

the U.S. and Eighth District more than
any other debt category. It is interesting
to note, however, that the Eighth District
was taking on student loans at a slower rate
compared with the nation over the first
half of 2019.
Eighth District MSA Developments
From a business perspective, recent
household debt developments in a metropolitan statistical area (MSA) are likely to
be more useful. In this section, we use the
recorded ZIP codes in CCP reports to identify household debt developments in the
Little Rock, Ark.; Louisville, Ky.; Memphis,
Tenn.; and St. Louis MSAs. The resulting
data for the first two quarters of 2019 are
presented in Table 2.
Three things stand out. First, Louisville
was the only MSA we tracked with a
growth rate in auto debt that was higher
than the national average in the second
quarter. This is not a new development;
auto debt growth rates in Louisville

REGIONAL ECONOMIST | www.stlouisfed.org/re 19

Table 2
Debt Scorecard for Eighth District MSAs
Metropolitan
Statistical Area

Little Rock, Ark.

Louisville, Ky.

Memphis, Tenn.

St. Louis

Debt Type

Year–over–Year Percentage
Change in Debt

90–Day Delinquency Rate

2019:Q1

2019:Q2

2019:Q1

2019:Q2

2010:Q1

Mortgage

–0.83%

1.37%

0.78%

0.69%

3.14%

Home Equity
Line of Credit

–2.70%

2.00%

0.56%

0.54%

1.34%

Auto

–0.84%

0.28%

6.04%

5.83%

3.75%

Credit Card

–0.62%

1.21%

9.03%

8.95%

10.28%

Student

3.56%

2.11%

14.49%

14.21%

10.66%

Mortgage

–2.40%

2.54%

0.98%

0.76%

4.13%

Home Equity
Line of Credit

–17.77%

–5.70%

1.03%

0.77%

0.77%

Auto

4.21%

4.68%

4.28%

4.27%

3.20%

Credit Card

2.03%

2.32%

6.16%

6.16%

9.79%

Student

4.70%

3.79%

14.23%

12.81%

7.90%

Mortgage

–0.44%

0.96%

1.23%

0.93%

5.74%

Home Equity
Line of Credit

–11.45%

–10.26%

0.39%

0.47%

0.94%

Auto

2.47%

2.70%

6.75%

6.68%

6.62%

Credit Card

4.88%

5.75%

8.61%

8.36%

12.75%

Student

6.10%

4.42%

14.34%

14.19%

11.71%

Mortgage

1.63%

3.30%

0.69%

0.63%

3.81%

–12.41%

–11.45%

0.87%

0.83%

1.40%

Home Equity
Line of Credit
Auto

3.28%

2.42%

3.73%

3.71%

3.31%

Credit Card

2.35%

2.94%

6.64%

6.44%

10.30%

Student

2.06%

2.19%

12.36%

12.41%

7.97%

SOURCES: Federal Reserve Bank of New York/Equifax Consumer Credit Panel and authors’ calculations.
NOTES: Debt data were adjusted for inflation using the personal consumption expenditures chain-type price index;
data as of Aug. 13, 2019.

have been above the national average each
quarter for the past three years.
Second, all four areas showed stronger
growth in mortgage debt in the second
quarter of 2019 than in the first, mirroring
the national trend.
Finally, the year-to-year growth in
student loans is again generally higher than
other categories of debt presented in Table
2 for each area and quarter. The biggest
exception to this statement is St. Louis, where
the growth rates have slowed somewhat.
The largest increases in student debt
occurred in the Memphis area.

20 REGIONAL ECONOMIST | Fourth Quarter 2019

What is the Message from
Delinquency Rates?
So long as debtors continue to repay their
debt, an increase in any debt category does
not necessarily signal a problem. One way
to measure this ability to repay is to examine 90-day delinquency rates3 in the first
two quarters of 2019 and compare them
with those in the first quarter of 2010.
In Table 2, mortgage delinquency rates
at the peak ranged from 3% to 6%. The
second-quarter mortgage delinquency rates
have not exceeded 1% in any of the four
MSAs, however. In stark contrast, delinquency rates for auto debt have surpassed
the reference rate and prior historical data

in every MSA for each of the last two quarters. More importantly, auto debt levels are
still increasing in most of these MSAs.
Credit card debt has also been on the rise
in the Eighth District. However, the corresponding delinquency rates do not raise as
much concern. Even with a slight increase
in credit card delinquency rates across the
District since 2014, these rates remain low
compared with our 2010 reference point
and prior historical data.
Lastly, student debt delinquency rates
have been on the rise for a number of
years. In the second quarter of 2019,
Table 2 indicates that the 90-day delinquency rates on student debt ranged from
12.41% in St. Louis to 14.21% in Little Rock.
These rates are substantially higher than
the rates observed in the first quarter of
2010 and earlier, especially for St. Louis.4
(This
online Xxxx
Nov. 26.)
(This article
article was
was published
published online
xx.)

ENDNOTES
1

The Federal Reserve Bank of New York’s Consumer
Credit Panel (CCP) is based on an anonymized 5% sample of credit files for the U.S. economy, provided by the
credit monitoring company Equifax. In this article, all
CCP data were adjusted for inflation using the personal
consumption expenditures chain-type price index.
2 Headquartered in St. Louis, the Eighth Federal Reserve
District includes all of Arkansas and parts of Illinois,
Indiana, Kentucky, Mississippi, Missouri and Tennessee.
3 The 90-day delinquency rate is found by dividing the
volume of loan payments 90 or more days past due by
the volume of loan payments.
4 In the third quarter of 2011, the CCP began changing
the way it reported student loans, and we noticed
a seemingly discontinuous increase in student loan
delinquency rates thereafter, which lasted through the
end of 2012. Even if we subtract away the increases
that occurred during that time from current delinquency levels, however, the present delinquency rates
are still higher for student loans in every MSA but
Memphis, which is approximately at the 2010 reference
level. Note also that student loans are unique among
the types of debt we track because the government
is often directly facilitating the loan, so in this case the
Great Recession does not provide as clear a precedent
for how a debt crisis might unravel.

NATIONAL OVERVIEW

Forecasters See Lower U.S. GDP Growth
in 2020 as Headwinds Continue
By Kevin L. Kliesen
© INDUSTRYVIEW/ISTOCK/GETTY IMAGES PLUS

KEY TAKEAWAYS
• Though the pace of real GDP growth
has slowed this year, there are few
signs that the longest U.S. expansion
is on its last legs.
• The consensus of professional forecasters is that real GDP growth will
dip below 2% in 2020.
• Real GDP growth in 2020 could rise
above 2% if the economy’s headwinds
—trade disputes and slowing global
growth—were to diminish.

A

fter showing considerable strength in
the first quarter of 2019, the pace of
real gross domestic product (GDP) growth
has since slowed modestly. Labor market
conditions remain healthy, as the number of job openings continues to outpace
the number of unemployed people. By
contrast, inflation—as measured by the
all-items personal consumption expenditures price index (PCEPI)—has remained
low; through September, the inflation rate
was about 0.5 percentage points below the
2% inflation target of the Federal Open
Market Committee (FOMC).
Although the U.S. economy is exhibiting trend-like growth, many businesses
continue to face brisk headwinds related
to the trade tussle with China and slowing global growth. To help mitigate these
threats, the FOMC has reduced its federal
funds target range by 75 basis points this
year; the range is now 1.50% to 1.75%.
Still, the consensus of professional forecasters is that real GDP growth will dip
below 2% in 2020 and that inflation will

modestly firm closer to the Fed’s target
rate. (See accompanying table.) But if the
headwinds facing the economy diminish,
then modestly stronger growth is possible
in 2020.
Good Times, Unsettled Times
The U.S. economy remains in recordsetting territory, entering its 125th month
of expansion on Nov. 1. The pace of real
GDP growth has slowed from a 3.1%
annual rate in the first quarter to a 2%
growth rate in the second quarter, and
then to a 1.9% growth rate in the third
quarter. But there are few signs that the
expansion is on its last legs. Indeed, if
anything, the current growth rate is
consistent with the economy’s potential
rate of growth—which most economists
estimate to be between 1.75% and 2%.
The economy’s recent performance is
built on some pillars that look reasonably sturdy and some pillars that exhibit
troubling cracks. Worrisomely, the pace
of business capital expenditures (fixed
investment) is the pillar that looks the
shakiest. Weak business fixed investment
tends to be a signal that firms see impediments to profitably deploying their scarce
resources. And since the domestic manufacturing sector is an important provider
of capital goods to firms, slowing business
fixed investment leads to fewer orders and
reduced activity at the nation’s factories.
Thus, weaker capital spending has potentially important implications.
In the current macroeconomic environment, there are two main impediments
facing many manufacturing and nonmanufacturing firms as well as farmers:

ABOUT THE AUTHOR
Kevin L. Kliesen is a business economist and research officer at the Federal Reserve
Bank of St. Louis. His research interests include business economics, and monetary
and fiscal policy analysis. He joined the St. Louis Fed in 1988. Read more about the
author and his research at https://research.stlouisfed.org/econ/kliesen.

What Are Professional Forecasters
Predicting for 2019-2020?
Actual
Percent Change (Q4/Q4)

Forecast

2018

2019

2020

Real GDP

2.5

2.2

1.8

PCE Price Index

1.9

1.5

1.9

3.8

3.6

3.7

Percent (Average, Q4)
Unemployment Rate

SOURCES: Federal Reserve Bank of Philadelphia and
Haver Analytics
NOTE: Forecasts are from the fourth-quarter Survey of
Professional Forecasters.

increased tariffs and slower global growth.
These two developments have increased
costs, trimmed profit margins and
reduced sales to overseas markets (i.e.,
exports).
By contrast, the U.S. consumer remains
the economy’s strongest pillar. The
strength in consumption reflects several
factors—most notably labor market conditions. Monthly gains in nonfarm payrolls
have averaged slightly less than 170,000
thus far in 2019, helping to drive the
unemployment rate to its lowest level in
roughly 50 years. Nominal wage growth
has remained around 3% over the past
year, which translates into solid real wage
gains of about 1.5% after accounting for
inflation. The latter is broadly consistent
with the underlying pace of labor productivity growth. But consumption spending
has also been boosted by continued solid
gains in household wealth—driven by
double-digit gains in equity prices and
steady increases in house prices.
The economy has also received a boost
from other areas. Notably, residential
housing construction (fixed investment)
has rebounded modestly; in the third
quarter, it contributed positively to real
GDP growth for the first time in about
REGIONAL ECONOMIST | www.stlouisfed.org/re 21

ECONOMY AT A GLANCE
All data as of Nov. 14.

Kathryn Bokun, a research associate at the
Bank, provided research assistance.
(This article was published online Nov. 21.)

4

2

0

–2
’14

Q3
’15

’16

’17

’18

Percent Change from a Year Earlier

Percent

4

CPI–All Items
All Items, Less Food and Energy

2

0

–2
’14

’19

October
’15

’16

’17

’18

’19

NOTE: Each bar is a one-quarter growth rate (annualized);
the red line is the 10-year growth rate.

Rates on Federal Funds Futures on Selected Dates

Inflation-Indexed Treasury Yield Spreads
2.50

2.50
10-Year

5-Year

06/19/2019
07/31/2019

20-Year

2.25

2.25

Percent

Percent

1.75
1.50

2.00
1.75
1.50

1.25
1.00
’15

09/18/19
10/30/19
11/13/19

2.00

Nov. 8, 2019
’16

’17

’18

1.25

’19

1st-Expiring
Contract

NOTE: Weekly data.

3-Month

6-Month

12-Month

Contract Settlement Month

Civilian Unemployment Rate

Interest Rates

8

4
10-Year Treasury

7

3
Percent

6
5

2
Fed Funds Target

1

4
3
’14

October
’15

’16

’17

’18

1-Year Treasury
October

0

’19

’14

’15

’16

’17

’18

’19

NOTE: On Dec. 16, 2015, the FOMC set a target range for the
federal funds rate of 0.25% to 0.5%. The observations plotted
since then are the midpoint of the range.

U.S. Agricultural Trade

Average Land Values Across the Eighth District

90

12.5

Exports

75
60
Imports

45

Trade Balance
30
15
0

September
’14

’15

’16

’17

’18

NOTE: Data are aggregated over the past 12 months.

’19

Year-over-Year Percent Change

Inflation pressures and inflation expectations generally remain subdued, thanks
to energy prices declining over the past
year. Measured from four quarters earlier,
the headline (all items) consumer price
index (CPI) was up by 1.8% in the third
quarter, while the headline PCEPI was
up by 1.4%. By contrast, core CPI inflation—which excludes energy and food
prices—rose by 2.3% in the third quarter,
which was the largest increase in 11 years.
However, the core PCEPI increased only
by 1.7% in the third quarter from a year
earlier. Financial market participants, as
well as the St. Louis Fed’s Price Pressures
Measure, continue to see a low probability
of a sizable increase in inflation over the
medium term.

Consumer Price Index (CPI)

6

Percent

Conflicting Inflation Signals

Real GDP Growth

Billions of Dollars

two years. The FOMC’s rate cuts have provided a kick-start to the mortgage market
and the housing industry.
Real GDP growth has also received a
boost from government expenditures, as
federal government outlays are on pace
this year to be the strongest in a decade.
Moreover, the St. Louis Fed’s Financial
Stress Index indicates that financial conditions remain supportive for continued
gains in economic activity.
Available data in October and November point to real GDP growth of around
2% in the fourth quarter of 2019. Thereafter, real GDP growth will slow a bit further
next year and dip below 2%, according to
the Survey of Professional Forecasters consensus. Forecasters also see a roughly 1 in
3 probability of a recession developing in
2020 or 2021, according to the Blue Chip
consensus. But if the impediments noted
earlier diminish, the FOMC’s insurance
cuts could trigger a rebound in economic
activity that pushes real GDP growth back
above 2%.

10.0
7.5

Quality Farmland
Ranchland or
Pastureland

5.0
2.5
0.0
–2.5
–5.0

2018:Q3 2018:Q4 2019:Q1

2019:Q2 2019:Q3

SOURCE: Agricultural Finance Monitor.

On the web version of this issue, 11 more charts are available, with much of those charts’ data specific to the Eighth District. Among the
areas they cover are agriculture, commercial banking, housing permits, income and jobs. To see those charts, go to www.stlouisfed.org/
economyataglance.
22 REGIONAL ECONOMIST | Fourth Quarter 2019

Green Cards
(continued from Page 15)

Conclusion
Our analysis reveals that while a
large fraction of green cards have
been given to family members of both
U.S. citizens and green card holders,
a substantial number have also gone
to employment-based categories. As
demand grows for skills that give the
U.S. a competitive edge in the global
economy, this program may be further
leveraged to attract talented and skilled
foreign workers and students. On the
other hand, this might moderate the
wage increases that would go to the
native population in the absence of
such immigration.
Immigration and trade both raise
income distribution issues, which
pose difficult choices to policymakers.
Unlike trade, immigration involves
international movement of people with
potentially different languages and
cultural backgrounds. This presents
both social concerns and opportunities
for the host nation. That discussion,
although important, is beyond the
scope of this article.
Finally, our analysis shows that green
card holders, on average, are younger
than the national population, with a
substantial number being students or
children. This bodes well for the future,
when an aging U.S. population can
be supported by younger and skilled
entrants into its labor force.
(This article was published online Dec. 23.)

ENDNOTES
1

2

3

We will use the terms “green card holder” and
“permanent resident” interchangeably in the
article.
For details, see www.dhs.gov/sites/default/
files/publications/Lawful_Permanent_
Residents_2017.pdf.
Tables and charts related to this section are
available from the authors on request.

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ECONOMY AT A GLANCE
Data as of Nov. 14, 2019.
FOURTH QUARTER 2019

Real GDP Growth

Percent Change from a Year Earlier

4

Percent

4

2

0
Q3
’15

VOL. 27, NO. 4

Consumer Price Index (CPI)

6

–2
’14

|

’16

’17

’18

CPI–All Items
All Items, Less Food and Energy

2

0

–2
’14

’19

October
’15

’16

’17

’18

’19

NOTE: Each bar is a one-quarter growth rate (annualized);
the red line is the 10-year growth rate.

Inflation-Indexed Treasury Yield Spreads

Rates on Federal Funds Futures on Selected Dates

2.50
10-Year

5-Year

2.50

20-Year

2.25

09/18/19
10/30/19

06/19/2019
07/31/2019

2.25

11/13/19

Percent

Percent

2.00
1.75
1.50

1.75
1.50

1.25
1.00
’15

2.00

Nov. 8, 2019
’16

’17

’18

1.25

’19

1st-Expiring
Contract

NOTE: Weekly data.

3-Month

6-Month

12-Month

Contract Settlement Month

Civilian Unemployment Rate

Interest Rates

8

4
10-Year Treasury
3

6

Percent

Percent

7

5

Fed Funds Target

1

4
3
’14

2

October
’15

’16

’17

’18

1-Year Treasury
October

0

’19

’14

’15

’16

’17

’18

’19

NOTE: On Dec. 16, 2015, the FOMC set a target range for the
federal funds rate of 0.25% to 0.5%. The observations plotted
since then are the midpoint of the range.

U.S. Agricultural Trade

Average Land Values across the Eighth District

90

12.5

Billions of Dollars

75
60
Imports

45

Trade Balance
30
15
0

September
’14

’15

’16

’17

’18

NOTE: Data are aggregated over the past 12 months.

’19

Year-over-Year Percent Change

Exports

10.0
7.5

Quality Farmland
Ranchland or
Pastureland

5.0
2.5
0.0
–2.5
–5.0

2018:Q3 2018:Q4 2019:Q1

2019:Q2 2019:Q3

SOURCE: Agricultural Finance Monitor.

Agriculture data as of Nov. 14, 2019. Banking data as of Nov. 21, 2019.

U.S. Crop and Livestock Prices
140

Index 1990-92=100

120

Crops
Livestock

100
80
60

September

40
’04

’05

’06

’07

’08

’09

’10

’11

’12

’13

’14

’15

’16

’17

’18

’19

COMMERCIAL BANK PERFORMANCE RATIOS

U.S. Banks by Asset Size/Third Quarter 2019
$300 millionLess than
$1 billion
$300 million

Less than
$1 billion

$1 billion$15 billion

Less than
$15 billion

More than
$15 billion

1.35

1.28

1.38

1.34

1.32

3.99

3.96

3.97

3.90

3.93

3.22

0.95

1.00

0.80

0.87

0.71

0.77

0.90

1.33

1.34

1.27

1.30

1.01

1.11

1.20

All

$100 million­$300 million

Return on Average Assets*

1.33

1.21

1.17

Net Interest Margin*

3.34

4.00

Nonperforming Loan Ratio

0.87

Loan Loss Reserve Ratio

1.18

Return on Average Assets*

Net Interest Margin*
1.36
1.41
1.49
1.61
1.12
1.08

0.50

0.75

Third Quarter 2019

1.00

Arkansas
Illinois

1.33
1.23
1.36
1.29
1.29
1.34
1.40
1.37
1.22
0.00 0.25

1.25

Indiana
Kentucky
Mississippi
Missouri
1.54

1.50

1.75

Tennessee
Percent

Third Quarter 2018

Arkansas
0.98
0.89
1.02

Third Quarter 2019

1.10
1.14
0.82
0.86

Mississippi

1.18
1.21

Missouri
0.72
0.78

Tennessee
1.00

1.20

Third Quarter 2018

SOURCE: Federal Financial Institutions Examination Council
Reports of Condition and Income for all Insured U.S.
Commercial Banks.
NOTE: Data include only that portion of the state within
Eighth District boundaries.
*Annualized data.

0.61
0.64

Kentucky

0.49
0.52
0.60
0.69
0.74
0.80

Illinois
Indiana

0.66
0.65
0.67

0.60

0.97
1.00
1.01
0.99
1.03
1.06

Eighth District

1.10

0.40

Third Quarter 2018

Loan Loss Reserve Ratio

0.68
0.68
0.63
0.65

0.20

0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 4.00 4.50
Third Quarter 2019

Nonperforming Loan Ratio

0.00

3.82
3.87
4.12
4.31
3.64
3.71
3.78
3.74
3.94
3.93
3.98
3.94
3.63
3.53
3.51
3.68

Eighth District

Percent

0.00 0.20

0.40

Third Quarter 2019

0.60

0.80

1.00

1.20

Third Quarter 2018

For additional banking and regional data, visit our
website at fred.stlouisfed.org.

1.40

REGIONAL ECONOMIC INDICATORS
Data as of Nov. 14, 2019.

Nonfarm Employment Growth/Third Quarter 2019
Year-over-Year Percent Change
United
States

Eighth
District †

Arkansas

Illinois

Indiana

Kentucky

Total Nonagricultural

1.5%

1.2%

1.4%

1.1%

1.1%

1.2%

Natural Resources/Mining

0.9

–3.3

–2.2

–6.6

0.5

–5.2

–1.9

–1.5

2.3

Construction

2.3

2.4

5.7

1.0

5.6

1.3

0.8

1.2

0.2

Manufacturing

1.0

0.8

1.3

0.5

–0.3

1.6

1.3

0.9

2.1

Trade/Transportation/Utilities

0.5

0.7

0.9

0.9

–0.4

1.2

1.9

–0.1

1.0

Information

0.0

–1.3

–0.6

–4.0

–4.5

0.0

0.6

–0.5

4.6

Financial Activities

1.3

1.2

3.7

0.6

0.0

1.3

3.1

0.8

2.8

Professional & Business Services

2.1

1.2

–0.3

0.9

2.4

–0.2

1.9

0.9

1.9

Educational & Health Services

2.7

2.2

1.1

1.6

4.5

3.6

0.8

2.4

0.7

Leisure & Hospitality

1.9

2.6

4.2

2.9

–0.8

1.7

3.8

2.7

4.7

Other Services

1.7

0.4

–0.6

1.0

–1.2

1.7

–0.1

0.8

0.1

Government

0.7

0.8

0.6

0.8

1.3

–0.5

0.8

0.9

1.1

Mississippi

Missouri

1.6%

Tennessee

1.1%

1.7%

† Eighth District growth rates are calculated from the sums of the seven states. Each state’s data are for the entire state even though parts of six of
the states are not within the District’s borders.

Housing Permits/Third Quarter

Real Personal Income/Second Quarter

Year-over-Year Percent Change in Year-to-Date Levels

Year-over-Year Percent Change

1.3

–15.1

12.7

–4.2
–6.2

10.4

Missouri
3.1

–4.3
–15

–10

–5

2.4
2.2
2.0
2.3
2.0
2.5

Mississippi

–6.3
–4.0

2019

2.3

Kentucky

–3.1

0

5

2.6

2.0

Indiana

6.7

–14.4

–20

Arkansas
Illinois

1.7

–15.7

3.5
3.5

United States

5.2

Tennessee
10

15

2018

Percent

Unemployment Rates
2019:Q3

2019:Q2

2018:Q3

United States

3.6%

3.6%

3.8%

Arkansas

3.4

3.6

3.6

Illinois

4.0

4.4

4.2

Indiana

3.3

3.6

3.5

Kentucky

4.4

4.0

4.4

Mississippi

5.2

5.0

4.7

Missouri

3.2

3.3

3.0

Tennessee

3.5

3.3

3.5

2.8
3.8

2.9
0.0

0.5
2019

NOTE: All data are seasonally adjusted unless otherwise noted.

2.9
2.8

1.0

1.5

2.0

2.5

3.0

3.5

2018

NOTE: Real personal income is personal income divided by the
personal consumption expenditures chained price index.

4.0