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A Quarterly Review
of Business and
Economic Conditions
Vol. 23, No. 2

Trade

Role of Contract Enforcement
and of Corruption Controls

President Bullard
Unconventional Policy
in Europe and the U.S.

April 2015

THE FEDERAL RESERVE BANK OF ST. LOUIS
CENTRAL TO AMERICA’S ECONOMY®

Regional vs. Global
How Are Countries’ Business Cycles
Moving Together These Days?

C O N T E N T S

A Quarterly Review
of Business and
Economic Conditions
Vol. 23, No. 2

Regional vs. Global Business Cycles

Trade

Role of Contract Enforcement
and of Corruption Controls

President Bullard
Unconventional Policy
in Europe and the U.S.

April 2015

THE FEDERAL RESERVE BANK OF ST. LOUIS
CENTRAL TO AMERICA’S ECONOMY

By Diana A. Cooke, M. Ayhan Kose, Christopher Otrok and Michael T. Owyang

Some countries’ business cycles are in sync with the world’s, while
other countries’ cycles follow the ups and downs just of their neighbors’. This regional connection is even more prevalent if a region is
defined not by geography but by common cultures and institutions.
Regional vs. Global
How Are Countries’ Business Cycles
Moving Together These Days?

THE REGIONAL

ECONOMIST
APRIL 2015 | VOL. 23, NO. 2

PRESIDENT’S MESSAGE

Trade Researchers Look
at Role of Institutions

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.

By Bill Dupor

Deputy Director of Research
David C. Wheelock

In the past, the study of international trade often focused on
differences in labor, land and
capital, as well as the distance
between trading partners. But
economists are increasingly
looking at the role played by
institutions, specifically those
that enforce contracts and curb
corruption.

Director of Public Affairs
Karen Branding
Editor
Subhayu Bandyopadhyay
Managing Editor
Al Stamborski
Art Director
Joni Williams

Please direct your comments
to Subhayu Bandyopadhyay
at 314-444-7425 or by email at

By Maria E. Canon

The American Recovery and
Reinvestment Act of 2009 provided $64 billion in stimulus
funds to public school districts.
A little over half of the money
went toward expenditures, and
most of that was used for capital
outlays. The impact on employment was negligible.
16

letter to the editor gives us the right
to post it to our website and/or
publish it in The Regional Economist

While the Eighth District’s track
record on business startups is
less impressive than that of the
nation since 2006, the District
performed better than the nation
over the same time period in
regard to business shutdowns.

By Kevin L. Kliesen
The U.S. economy lost some of
its momentum over the winter.
But the weakness did not extend
to the labor markets, where job
gains continued to be strong.

METRO PROFILE

By Georgette Fernandez Laris
and Charles S. Gascon

Your Living Arrangements
Matter to Policymakers

N AT I O N A L O V E R V I E W
Growth Is Modest;
Job Gains Are Strong

Much Is Familiar
in Springfield, Mo.

subhayu.bandyopadhyay@stls.frb.org.

DISTRICT OVERVIEW
District, Nation Differ
in Records on Startups

Senior Policy Adviser
Cletus C. Coughlin

address below. Submission of a

By Subhayu Bandyopadhyay,
Suryadipta Roy and Yang Liu

Director of Research
Christopher J. Waller

You can also write to him at the

How Was Stimulus
Spent by Schools?

RE ADER E XCHANGE

By Guillaume Vandenbroucke

unless the writer states otherwise.

ONLINE EXTRA

We reserve the right to edit letters
for clarity and length.

Read more at www.stlouisfed.org/
publications/re.

Single-copy subscriptions are free
but available only to those with
U.S. addresses. To subscribe, go to
www.stlouisfed.org/publications.
You can also write to The Regional
Economist, Public Affairs Office,
Federal Reserve Bank of St. Louis,

The city with a common name
has an economy with familiar
successes and challenges. The
health care sector is thriving, and
the cost of living is somewhat
low, as are wages. But labor productivity seems to be subpar, and
the poverty rate is above average.

P.O. Box 442, St. Louis, MO 63166-0442.

The Eighth Federal Reserve District includes

all of Arkansas, eastern Missouri, southern
Illinois and Indiana, western Kentucky and
Tennessee, and northern Mississippi. The
Eighth District offices are in Little Rock,
Louisville, Memphis and St. Louis.

The decision to look for a job, as
well as some measures of income
inequality, are closely connected
with the living arrangements
people choose and, therefore,
are important to policymakers.

2 The Regional Economist | April 2015

E C O N O M Y AT A G L A N C E

Costs of Credit Card
Default Depend
on Your “Exit” Strategy
By Juan M. Sánchez

When consumers can’t pay their
credit card bills, they choose
between delinquency and
bankruptcy. A new economic
model indicates that by treating
delinquent borrowers differently according to their current
financial conditions, lenders can
maximize repayment and make
a difference in whether or not a
household chooses bankruptcy.

P R E S I D E N T ’ S

M E S S A G E

A Comparison of Unconventional
Monetary Policy in the U.S. and Europe

he global financial crisis of 2007-09
affected most countries around the
world in a similar way. Deep recessions hit
the U.S., Europe and Japan, and even China
experienced slower growth. During the
early stages of the global economic recovery, the U.S. and the euro area had similar
unemployment rates of roughly 10 percent
in October 2009. Subsequently, monetary
policy in the U.S. and in the euro area took
different paths, as did the economic performance of those two economies.
In the U.S., the Federal Open Market
Committee (FOMC) undertook unconventional monetary policy after it lowered
the federal funds rate target to near zero
in December 2008. The FOMC undertook
three rounds of quantitative easing, or
large-scale asset purchases. The first two
programs were for fixed amounts. The third
one (QE3) was an open-ended program, in
which the FOMC said the purchases would
continue at a certain pace until a particular objective was achieved. In addition to
quantitative easing, the FOMC used forward
guidance, whereby the committee promised to stay at zero beyond the time when it
might otherwise have been expected to raise
the federal funds rate target. Of these two
unconventional approaches to monetary
policy, quantitative easing seems to have
been more effective.
When the FOMC adopted QE3 in September 2012, the objective was substantial
improvement in labor markets. At the time
of the FOMC meeting, the latest reading on
unemployment was 8.1 percent, and the rate
was not expected to drop that rapidly even
with the QE3 program. The actual result,
however, was that unemployment dropped
dramatically faster than anticipated at the
launch of QE3. In October 2014, the FOMC
declared that substantial improvement in
labor markets had occurred and ended QE3.

Meanwhile, the European Central Bank
(ECB) lowered its benchmark rate to 1 percent in May 2009 but was reluctant to adopt
unconventional monetary policy during
and after the 2008-09 recession in the euro
area. Not only was the ECB less inclined
to promise to stay at zero for any length of
time, but it was also less inclined to adopt a
quantitative easing program similar to those
in the U.S., U.K. and Japan—and with good
reason. The ECB is a multinational institution, and the prospect of purchasing sovereign debt of the different nations in the euro
area was not envisioned in the Maastricht
Treaty, which led to the creation of the ECB.
Therefore, the ECB adopted more of a waitand-see approach to see if the historically
low interest rates alone would be enough
to spur recovery. However, the European
sovereign debt crisis hit in late 2009 and
was especially severe in 2011 and 2012, and
Europe went back into recession. Euro area
unemployment, instead of declining as in
the U.S., peaked at 12.1 percent during the
second quarter of 2013. The rate remains
in double digits (11.3 percent in February
2015), a stark contrast with U.S. unemployment (5.5 percent for the same period).
While the Fed has a dual mandate for
maximum sustainable employment and
stable prices, the ECB has a single mandate
for price stability, which it has interpreted as
keeping inflation below but close to 2 percent
via an explicit inflation target. During 2014,
the ECB’s ability to keep inflation close to its
target seemed to be eroding as both actual
and expected inflation drifted down. Inflation has even been below zero since December 2014.1 As a result, ECB policymakers
overcame their reluctance to adopt unconventional monetary policy.2 They decided in
January 2015 to implement an open-ended
quantitative easing program modeled on the
QE3 program in the U.S., with the sovereign

debt purchases beginning in March. The ECB
intends to continue the program at least until
September 2016 but, if necessary, can continue beyond that until inflation moves back
toward target. Based on the U.S. outcomes
from QE3, the ECB has a reasonable chance
at success with this program.
This is not a story only about Europe.
Global yields began to fall during 2014 as
it became more likely that the ECB would
undertake a sovereign-debt quantitative
easing program. From the beginning of 2014
to the end of 2014, yields on 10-year German
bonds declined by about 1.4 percentage
points, and yields on 10-year U.S. Treasury
securities declined by more than 0.8 percentage points. These examples illustrate the
big impact that the expectation of quantitative easing in the euro area had on U.S.
and global markets. In my view, the ECB’s
undertaking of quantitative easing was a
momentous decision and a major milestone
in global monetary policy.

James Bullard, President and CEO
Federal Reserve Bank of St. Louis

ENDNOTES

1 Although U.S. inflation has not been what was

expected, it has not gone down to zero. Headline
inflation has been drifting down in recent months
due largely, in my view, to the decline in oil prices.
U.S. inflation refers to the year-over-year percent
change in the Personal Consumption Expenditures
Price Index, and euro area inflation refers to the yearover-year percent change in the Harmonized Index of
Consumer Prices.
2 After raising its benchmark rate twice in 2011, the
ECB has since lowered it to near zero.

The Regional Economist | www.stlouisfed.org 3

Regional

Global

Business Cycles

Global
4 The Regional Economist | April 2015

Regional

C O N N E C T I O N S

Regional vs. Global
How Are Countries’ Business Cycles
Moving Together These Days?
By Diana A. Cooke, M. Ayhan Kose, Christopher Otrok and Michael T. Owyang

n economy moves between extended periods of positive output growth (expansions) and shorter periods of negative growth (recessions). Shifting between
these phases is typically referred to as the business cycle. This cycle is a prominent feature in economies—both advanced and developing—and can be correlated across countries. The correlation of business cycles implies that groups of
countries are in the same phase for stretches of time. An example of this can be
seen in the figure, which shows the annual gross domestic product (GDP) growth
rates in the United States, Canada and Mexico from 1981 through 2014. Notice
that U.S. and Canadian data moved similarly over the past 30 or so years. In the
past decade, the Mexican economy also fell into sync: The correlation between
U.S. and Mexico increased by over 100 percent.1
An Example of How Countries’ Business Cycles Can Become Correlated
12

Annual GDP Growth Rates

10
8
6

Percent

4
2
0
–2

United States

–4

Canada

–6

Mexico

–8

2014

2011

2008

2005

2002

1999

1996

1993

1990

1987

1984

1981

–10

SOURCE: Organization for Economic Cooperation and Development.

The Regional Economist | www.stlouisfed.org 5

Business cycle synchronicity might occur
because countries experience shocks common to all countries (e.g., oil price shocks
that increase or decrease the price of oil for
everyone) or shocks common to countries
in the same region (e.g., weather disruptions
or regional conflicts). Alternatively, shocks
could occur in one country and propagate
rapidly to nearby countries. The degree to
which business cycles synchronize across
countries might depend on, among other
things, physical distance, the amount of
bilateral trade, similarities in institutions or
language, or historical trade routes.2
One way to think about business cycle
synchronicity is to imagine each country’s
business cycle as having a global component,
a regional component and a country component. The global component captures the
common movements in all countries’ business cycles and represents global synchronicity. The regional component captures the
common movements with a country’s (possibly geographic) neighbors and represents
regional synchronicity. A country component
captures the movements in the business cycle
that are unique to that country and lead to a
more independent business cycle.
The strength of the correlation of countries’
business cycles depends on the relative
importance of these components. For example, if the regional component of a country’s
cycle is larger than the global and country
components, the country may appear more
synchronized with its neighbors than with
the world as a whole. In a 2003 article,
economists Ayhan Kose, Christopher Otrok
and Charles Whiteman assessed the relative importance of the global, regional and
country components of business cycles in
60 countries. In their initial sample (1960 to
1990), they found that the global and country
components explained a substantial portion
of the cyclical movements for most countries;
regional components explained far less.
Over time, determinants of business cycle
synchronicity—institutions, trade patterns,
etc.—can change. For example, the formation
of the European Union and the ratification of
the North American Free Trade Agreement
enabled goods to flow more easily across
borders. Declines in transportation costs
and the ability of more ports to off-load large
shipping containers also may have increased
bilateral trade between countries that pre6 The Regional Economist | April 2015

Two Ways of Looking at Countries’ Business Cycle Synchronization
Latin America

Europe

Africa

North America

Costa Rica

Austria

Cameroon

Canada

Dominican Republic

Belgium

Ivory Coast

Mexico

El Salvador

Denmark

Kenya

U.S.

Guatemala

Finland

Morocco

Honduras

France

Senegal

Asia (Developing)

Jamaica

Germany

South Africa

Bangladesh

Panama

Greece

Zimbabwe

India

Trinidad

Iceland

Argentina

Ireland

Asia (Developed)

Pakistan

Bolivia

Italy

Hong Kong SAR

Philippines

Brazil

Luxembourg

Japan

Sri Lanka

Chile

Netherlands

Malaysia

Colombia

Norway

Singapore

Oceania

Ecuador

Portugal

South Korea

Australia

Paraguay

Spain

Thailand

New Zealand

Peru

Sweden

Uruguay

Switzerland

Venezuela

United Kingdom

Indonesia

NOTE: The continent headings show how economists Ayhan Kose, Christopher Otrok and Charles Whiteman divided countries by geography in 2003. An
alternative (and more recent) classification groups countries not by geography but by common interests, institutions, values and the like; this classification
groups the countries into three nongeographic “regions,” shown in red, green and blue. This system was developed by economists Neville Francis, Michael
Owyang and Ozge Savascin.

viously may not have traded. In the past,
more openness in trade led to globalization;
more recently, regional trade agreements
may have shifted the landscape toward more
regionalized—rather than globalized—
business cycle synchronicity.
In a more recent paper, economists
Hideaki Hirata, Kose and Otrok found
that the importance of regional cycles—
especially in Europe and Asia—had risen
substantially. Understanding synchronicity—and, in particular, which countries
are synchronized—can be an important
component for implementing countercyclical policy. Downturns in other countries
that have synchronous cycles can forecast
domestic downturns, leading to more timely
policy. Understanding synchronicity can
also provide insight into the impact of trade
diversification, of the increase in financial
flows and of regional trade agreements, all
of which have helped to define the global
economy in the 21st century.
In this article, we document some facts
about business cycle synchronicity—in
particular for countries in the Organization
for Economic Cooperation and Development (OECD). We focus on the global and

regional components, which indicate crosscountry comovement, rather than the country components, which indicate how data
within the country move. We first consider
the importance of these components for
each country’s cycle over a 30-year period
beginning in 1960. Countries are sorted
into seven “continental” regions based on
geographic proximity.3 We then consider
whether geographically defined regions
are optimal and provide some evidence for
using economic institutions, in addition to
physical distance, as a measure of forming
regions. Finally, we document whether the
regional component of countries’ cycles has
become more important.
Documenting International
Business Cycles

Although business cycles are most commonly used to describe the state of a single
country’s economy, globalization and the
proliferation of regional trade agreements
have prompted economists to study common
movements of these cycles across multiple
countries. The eurozone, for example, is an
economic and monetary union consisting
of 19 European countries. These countries

are in close geographic proximity, have
adopted the euro as their form of currency
and are members of the European Union,
which facilitates freer flow of trade among
member countries. Changes in the European
Central Bank’s monetary policy, then, can
affect all of the countries in the monetary
union and make their business cycles move
together. This interconnectedness means that
shocks—good or bad—will be experienced by
all member countries. The European Central
Bank’s quantitative easing has already played
a role in increasing forecasts of GDP growth
across all member countries. On the other
hand, the uncertainty surrounding the
rumored exit by Greece from the eurozone
could destabilize the European economy.
In the aforementioned 2003 article,
Kose, Otrok and Whiteman examined how
60 countries’ business cycles were related.
The countries and their continental regions
are shown in the accompanying table.
In particular, they considered whether
the countries moved together as a whole,
whether countries on the same continent
moved together or whether each country
moved independently of the others. Using
the growth rates of output, consumption
and investment, they measured the fraction
of each country’s business cycle attributable
to global, regional and country components.
Although each of these components is
unobserved, they can be inferred from the
data, and the sum of these components is a
proxy for the business cycle.
The relative importance of each component suggests the degree of that country’s
interconnectedness. The comovement of all
60 countries is significant, indicating that
there is a world business cycle: Fifteen percent of the deviation in world output growth
away from the norm was experienced by
all 60 countries in the sample. Similarly,
9 percent and 7 percent of deviation in
world consumption and investment growth,
respectively, were commonly experienced
by all countries. However, the importance
of the global component varies across
countries, indicating that some countries
are more interconnected than others. The
global component is more important for
explaining economic activity of advanced,
industrialized countries than of developing
nations. When considering only the countries in the so-called Group of 7, the share of

The Determinants of Trade Range from
Comparative Advantage to “Iceberg” Costs

he amount of trade between countries can be determined by a variety of
things. One is comparative advantage. One country trades a good for which

it has a comparative advantage in producing for another country’s “comparative
advantage” good. Comparative advantages in production can be generated by,
among other things, differences in the skill sets of the labor forces of the countries,
differences in the quality of the physical capital, and differences in the quality or
abundance of natural resources used as inputs.
Another determinant of trade is policy. Policies that act to deter trade by imposing large barriers are deemed to “increase the size of the border” between the
respective countries. Monetary policy rules that target the exchange rate can shift
relative prices in the two countries and make trading more or less favorable. These
types of policies tend to change the flows of trade but may not affect the overall
level of trade.
Tariffs or trade agreements can affect the prevalence of trade. For example,
the Transatlantic Trade and Investment Partnership (TTIP) is a trade agreement
currently in negotiation between the European Union and the United States. Among
other things, the TTIP would standardize regulations in the production of goods so
that, for example, the safety features of cars would not have to be approved by
both countries involved.
In his 1954 article, economist Paul Samuelson argued that one of the primary
determinants of the amount of bilateral trade between countries was the cost
of transporting goods. These “iceberg” costs increase as the physical distance
between the trading countries increases. Since the transport costs are paid for in
units of that good, the amount of tradable good decreases as the physical distance
between the trading countries increases, just as an iceberg grows smaller as it
continues to melt the farther it has floated from its origin. The implication is that the
iceberg (which is a metaphor for the tradable good) melts the farther it sails from
the country of origin. Iceberg costs provide economic motivation for the regional
component of the business cycle: Trade within regions is less costly because of the
physical proximity between countries. Distance, in an economic sense, can refer
to more than simply physical distance. The cost of transporting goods can change
with terrain; with distance from and access to ports, rail, highway and airports; and
with a country’s infrastructure.
Recently, some economists have conjectured that bilateral trade between
countries may also be related to a more broadly defined economic distance. For
example, the similarity in those countries’ institutions, including language and
laws, might also facilitate trade. Companies in one country might be more inclined
to do business with another country if they have some familiarity with the laws.
If firms understand the manner in which conflicts are resolved, they may be more
willing to risk overseas ventures, produce goods intended for sale in other countries
or move production offshore.6
In our rapidly globalizing and technologically advancing world, country-specific
characteristics, such as common language spoken and laws regarding conflict
resolution, supersede the significance of physical distance in determining the prevalence of trade between countries. We can continue to expect the determinants of
bilateral trade to fluctuate, especially with the rise in regional trade agreements.
The Regional Economist | www.stlouisfed.org 7

the fluctuations in output growth explained
by the global component more than doubles
and the share of the fluctuations in consumption growth explained by the global
component more than quadruples.4
The importance of the global component
suggests some interconnectedness across
all of the countries during world economic
downturns. The regional components, however, appear to explain only a small percentage of business cycle fluctuations, suggesting
that regional interconnectedness is very
limited for most countries. In particular,
the regional component for (pre-European
Union) Europe explains only 2 percent of
the variation in the three economic variables
(output, consumption and investment). The
regional component for North American
countries, on the other hand, explains a
larger proportion of output variation than
that for Europe, roughly equal to the contribution of the global component.
The business cycles of most African and
Asian (developed and developing) countries
do not appear to comove with either their
regional neighbors or the rest of the world.
In these regions, the country component
plays the dominant role in explaining
movements in the economic variables; the
contributions from both the global and
regional components are small. This lack of
synchronicity may result from these countries’ having relatively small international
trade sectors or from the compositions of
their economies. For example, many of the
African countries in the sample have relatively large agricultural sectors.
What Is a Region?

It is puzzling why the regional component’s contribution to the business cycle is
small compared with the contributions of
the other components. If trade is a substantial determinant of interconnectedness,
low regional correlation may suggest that
intraregional trade is not important compared with overall trade. If true, this finding
confounds the notion that iceberg costs—
transportation costs that increase over
geographic distance—decrease the propensity to trade.5 (See sidebar.) Instead, other
factors—e.g., language or institutions—may
play a more important role.
In a 2012 paper, economists Neville Francis, Michael Owyang and Ozge Savascin
8 The Regional Economist | April 2015

found that the regional component is more
important when the “region” is defined
differently from simple geography. Regions
based solely on geographic distance may
mute the regional comovement, especially
if iceberg costs are not the primary determinant of trade. Rather than choose the
regions based on location, regions are created based on country-specific factors, such
as the degree of economic openness to trade,
the investment share of real gross domestic
product, the method of conflict resolution,
the legal system, language, and composition
of trade and production.
The data suggest that the countries can be
sorted into three groups. The accompanying
table highlights the differences in the geographic regions of Kose, Otrok and Whiteman and the alternative regions of Francis,
Owyang and Savascin. The latter regions are
organized by color. The first group consists
of the many industrialized nations, including Japan and most of Europe. The second
group consists of the United Kingdom and
many of its former British Commonwealth
countries: Australia, Canada, India, New
Zealand, South Africa and the United
States. A few other countries in Africa and
Asia are included in this second group. The
final cluster consists of South American
countries, along with Mexico, Morocco,
Senegal and the Philippines. Consistent with
the findings of Kose, Otrok and Whiteman,
African countries’ business cycles were
primarily driven by the country-level component and not assigned to any region with
any level of confidence.
Analysis of the formation of groups
of countries into regions highlights the
important features of international business cycles. While there is a role for a
geographic component of regional business
cycle synchronization—most European
countries were grouped together, and most
South American countries were grouped
together—other country-specific characteristics appear to also determine business
cycle synchronization within regions.
Countries with common cultures—
especially, languages—and common legal
systems tend to have similar business cycles.
Thus, Mexico is grouped with its sharedlanguage South American neighbors, and
the United States and the United Kingdom
are grouped together.

Regions defined in this manner increase
the share of output growth fluctuations
attributable to the regional component,
raising its importance relative to the global
and country-specific components. Defining
regions based solely on location, the regional
component explains just over 2 percent of
the fluctuations in output growth; these new
regional components explain over 22 percent
of the fluctuations in output growth. This
dramatic increase in the significance of the
regional component indicates that the importance of the regional factor may be misrepresented when countries are sorted into purely
geographic regions. National policy is less
effective if the nature of economic linkages
between countries is misunderstood; thus,
classification of countries into “regions”
continues to evolve to match trends in trade
and financial flows.
A Rise in Regionalization?

In the past 30 years, regional linkages
and trade agreements have increased
substantially. If trade and financial flows
across countries are becoming increasingly
regional, the regional component may also
find a rise in importance. In a 2013 article,
Hirata, Kose and Otrok studied whether
economic linkages are becoming increasingly global or increasingly regional. Globalization of trade and finance might lead to
stronger economic linkages among all countries, regardless of regions. But the resilience
of the Asian economy during the 2008-2009
financial crisis suggests a potential increase
in regional versus global linkages.
In order to assess whether the regional
components of business cycles have
increased in importance, the sample can be
split into two periods, 1960-1984 and 19852010, during which the number of regional
trade agreements increased from five to 200
and during which global and financial flows
increased substantially. When the sample
is split, more importance is found in the
regional component in the second period.
For example, the average contribution of
the global component to fluctuations in the
output growth rate fell from 13 percent in
1960-1984 to 9 percent in 1985-2010. On the
other hand, the average contribution of the
regional component to fluctuations in the
output growth rate rose from 11 percent in
1960-1984 to 19 percent in 1985-2010.

The proliferation of regional trade
agreements over the past 30 years might
help explain the increasing significance of
economic linkages. For example, Canada,
Mexico and the United States implemented
the North American Free Trade Agreement
in 1994 to eliminate barriers to trade and
investment. Subsequently, intraregional
trade flows in North America accounted for
nearly 55 percent of total trade during the
past decade. Similarly, the establishment of
the European Union and the creation of the
eurozone increased intraregional trade flows
in Europe to roughly 75 percent of total
trade during the past decade.
The increase in regional synchronization
might be attributed to the diversification of
industry and the acceleration of trade in the
second period. For example, the diversification of trade increases the degree of sectoral
similarity across countries, increasing the
likelihood that countries are exposed to
similar shocks and contributing to the convergence of business cycles.
Business cycles track movements in the
economy. With the rise in openness to trade,
business cycles have become increasingly
interconnected. Understanding the nature of
comovement of business cycles is important
for the formulation of domestic policies to
stabilize business cycles. If business cycles are
largely global in nature, then domestic policy
within one country will have little impact on
the nation’s economy, unless accompanied by
global economic reform. If business cycles are
largely regional in response to trade agreements, one should consider coordinating
macroeconomic stabilization policies as part
of the formulation of a free-trade zone. Lastly,
domestic policy should focus on smoothing
business cycle fluctuations that are primarily determined by the country-specific cycle
rather than those determined by the global
and regional components.
M. Ayhan Kose is the director of the Development Prospects Group at the World Bank.
Christopher Otrok is Sam B. Cook Professor of
Economics at the University of Missouri and
research fellow at the Federal Reserve Bank of
St. Louis. Michael T. Owyang is an economist
at the Federal Reserve Bank of St. Louis. Diana
A. Cooke is a senior research associate at the
Federal Reserve Bank of St. Louis. For more on
Owyang’s work, see http://research.stlouisfed.
org/econ/owyang.

ENDNOTES
1

Correlation coefficients between the U.S. and
Canada, the U.S. and Mexico, and Canada and
Mexico from 1984:Q3 to 2014:Q3 were 0.80, 0.42
and 0.33, respectively. Correlation coefficients between the U.S. and Canada, the U.S. and Mexico,
and Canada and Mexico from 2004:Q3 to 2014:Q3
were 0.90, 0.86 and 0.90, respectively.
Business cycle synchronization is often attributed
to the prevalence of bilateral trade between the
two countries. Bilateral trade was often thought
to be higher the shorter the physical distance
between two countries. More recent theories have
conjectured that distance can also measure culture
and institutional similarity.
Kose, Otrok and Whiteman define seven regions
based on geography. The seven regions are Africa,
developing Asia, developed Asia, Europe, Latin
America, North America and Oceania. They split
the Asian countries into two regions consisting
of (1) Bangladesh, India, Indonesia, Pakistan, the
Philippines and Sri Lanka and (2) Hong Kong,
Japan, Malaysia, Singapore, South Korea and
Thailand.
The Group of 7 (also known as the G7) consists of
Canada, France, Germany, Italy, Japan, the United
Kingdom and the United States.
In the iceberg transport cost model, the cost of
transporting a good is in the depletion of the good
itself, rather than in the use of other resources.
This idea is based on floating an iceberg; there is
no cost as the distance between the origin and
destination locations increases, except for in the
amount of the iceberg that melts.
See Levchenko for further discussion of institutional differences as a determinant in trade flows
and Melitz for the influence of common language
in bilateral trade.

REFERENCES
Francis, Neville; Owyang, Michael T.; and Savascin,
Ozge. “An Endogenously Clustered Factor
Approach to International Business Cycles,”
Working Paper 2012-014A, Federal Reserve Bank
of St. Louis, 2012.
Hirata, Hideaki; Kose, M.A.; and Otrok, Christopher.
“Closer to Home,” Finance and Development,
International Monetary Fund, September 2013,
Vol. 50, No. 3, pp. 40-43.
Kose, M.A.; Otrok, Christopher; and Whiteman,
Charles H. “International Business Cycles: World,
Region, and Country-Specific Factors,” The American Economic Review, September 2003, Vol. 93,
No. 4, pp. 1,216-39.
Levchenko, Andrei A. “Institutional Quality and
International Trade,” The Review of Economic
Studies, 2007, Vol. 74, No. 3, pp. 791-819.
Melitz, Jacques. “Language and Foreign Trade,”
European Economic Review, May 2008, Vol. 52,
No. 4, pp. 667-99.
Samuelson, Paul A. “The Transfer Problem and
Transport Costs, II: Analysis of Effects of Trade
Impediments,” Economic Journal, 1954, Vol. 64,
pp. 264-89.

The Regional Economist | www.stlouisfed.org 9

I N T E R N A T I O N A L

Contract Enforcement,
Corruption Controls
and Other Institutions
Affect Trade, Too
By Subhayu Bandyopadhyay, Suryadipta Roy and Yang Liu
© THINKSTOCK

he role of institutions in international
trade has been getting increasing attention from economists. While traditional
theories have focused on differences in labor,
land, capital and other factor endowments
in explaining international trade patterns,
recent research has highlighted the role of
institutions. Well-established and highquality institutions that lay down the rules,
procedures and guidelines for trade in a clear
and transparent manner, as well as institutions that protect traders from predation, are
now viewed to be essential requirements for
prosperous trade. For example, a 2003 study
by economists James Anderson and Eric
van Wincoop showed that higher trading
costs due to weak institutions quantitatively
affected trade more than barriers such as
tariffs, quotas and natural impediments like
the distance between the trade partners.
A number of private institutions and
think tanks—such as the Political Risk
Services Group, Transparency International
and the World Bank—have constructed
indicators of institutional quality that are
used to assess the relative risk of carrying
out businesses in different countries. These
institutional-quality indices use measures of
contract enforcement, control of corruption
and the rule of law, among other indicators. To sharpen the focus of our discussion,
the rest of this article discusses two of the
indicators, namely the contract enforcement
and corruption indicators. We do this first
by explaining how each of these institutional
factors may affect trade and then by discussing an empirical study that relates to each
factor, respectively.
Absence of contract enforcement can
hinder trade in situations in which exporters are likely to incur substantial fixed costs
10 The Regional Economist | April 2015

before they get paid by importers. Exporters
who are unable to recover these costs due to
weak contract enforcement in the importers’
nations will not enter into trade at all.
A similar problem can afflict investments
by upstream producers who are needed to
supply customized products to the downstream producers, products that otherwise
have no value outside the relationship
between the two parties. Researchers have
found that institutions that promote contract
enforcement, for example, international
treaties like the New York Convention on
the Recognition and Enforcement of Foreign
Arbitral Awards, are able to mitigate such
costs and promote trade.
In addition to hindering the overall
volume of trade, international differences in
contracting institutions have an important
bearing on the “pattern of trade”—that is,
which countries export which types of goods.
One would expect that nations which have
superior institutions to enforce contracts
should have a comparative advantage in
goods that are more “contract intensive,”
and, therefore, export these goods in
exchange for less contract-intensive goods.
Contract Intensity

One way to think about contract intensity is
the following. Some goods require widely available intermediate inputs that may be available
from a variety of suppliers. These goods are
not contract-intensive. On the other hand,
some other goods may require some special
intermediate inputs in their production (e.g.,
some specialized parts for a high-end luxury
car), the terms for the delivery of which may
have to be negotiated in a contract between
the final good producer and the intermediate
input supplier. In this case, satisfaction of the

terms of the contract becomes important in
ensuring timely and efficient production of the
final good.
If a nation’s judicial system is weak, such
contracts may not be properly enforced and,
hence, the costs of producing such contractintensive goods will be higher. Accordingly,
nations with weak judicial systems will have
a comparative disadvantage in producing
such contract-intensive goods and will end
up importing these goods, while exporting
other goods.
Following this line of logic, a 2007 study by
Harvard economist Nathan Nunn analyzed
judicial quality’s impact on the global trading
patterns and found that countries with high
contract-enforcement quality have a comparative advantage in industries in which relationship-specific investments are important.
The author designed a variable to measure the
relationship-specific investments needed in
goods produced in 182 industries. Combining
this relationship investment ratio with trade
volume and contract-enforcement quality, the
author found that countries with good contract enforcement specialize in the production
(and export) of goods for which relationshipspecific investments are most important. The
author also found that differences in contractenforcement abilities of nations affect the
global trade pattern to a greater extent than
differences in physical and human capital.
Along similar lines, a 2014 study by
economists Nunn and Daniel Trefler showed
that advanced countries, which usually have
better institutions, undertake production
and exports of sophisticated, high-quality
products (which are more contract-intensive
by their very nature) to a greater extent
compared with low-income countries.
Moreover, the high-income countries with

Corruption and Trade

ENDNOTE

Corruption and Export Relationship

Corruption and Import Relationship

250

150

100

Least

–3

Most

–2

–1

Corruption
Export/GDP

Fitted Values

100

Corruption measure is obtained from the International Country Risk Guide, and the level of exports
and imports from the World Bank’s World Development Indicators.

REFERENCES

150
Import/GDP Level 1982-1997

Export/GDP Level 1982-1997

200

Least

–3

Most

–2

–1

Corruption
Import/GDP

Fitted Values

SOURCE: Authors’ calculations.

Anderson, James E.; and van Wincoop, Eric. “Gravity
with Gravitas: A Solution to the Border Puzzle,”
American Economic Review, March 2003, Vol. 93,
No. 1, pp. 170-92.
Bandyopadhyay, Subhayu; and Roy, Suryadipta. “Corruption and Trade Protection: Evidence from Panel
Data,” Federal Reserve Bank of St. Louis Working
Paper 2007-022A, May 2007. See http://research.
stlouisfed.org/wp/2007/2007-022.pdf.
Nunn, Nathan. “Relationship-Specificity, Incomplete
Contracts and the Pattern of Trade,” The Quarterly
Journal of Economics, May 2007, Vol. 122, No. 2,
pp. 569-600.
Nunn, Nathan; and Trefler, Daniel. “Domestic Institutions as a Source of Comparative Advantage” in
Gopinath, Gita; Helpman, Elhanan; Rogoff, Kenneth (eds.), Handbook of International Economics,
April 2014, Vol. 4, pp. 263-315, North Holland.

NOTE: The scatterplots show that corruption reduces both exports and imports of countries as a percentage of their respective GDPs. Each blue dot represents
one of the 171 countries that were part of this study. Dots that appear to the right and bottom of the scatterplot represent countries with high corruption levels
that are associated with reduced levels of exports and imports as a fraction of the nations’ respective GDPs. The red line shows the fitted relationship between
corruption and exports/ imports based on an Ordinary Least Square Regression. See the endnote for sources of the corruption and trade data.

similar institutional structures were found
to trade disproportionately more with one
another than with low-income countries.
Corruption

Turning to corruption, countries with high
levels of it are characterized by burdensome
regulations, which are exploited by dishonest
officials to extract bribes from traders, thereby driving up the costs of trade. Among other
studies, a 2007 study by economists Subhayu
Bandyopadhyay and Suryadipta Roy investigated the effect of corruption in impeding
trade. Using time-series and cross-section data
for a group of 88 countries over the period
1982-1997, they found that greater corruption significantly increased import duties and
other related taxes, while reducing the tradegross domestic product (GDP) ratios of the
respective nations. Using their dataset,
we constructed two graphs (above); they
show the relationship between an index of
corruption and the level of exports/imports
across 171 countries during the period
1982-1997.1 The graphs indicate a negative
relationship between corruption and export/
GDP and import/GDP ratios, suggesting that
corruption is an impediment to trade.
What is clear from our discussion is
that the literature in international trade
has reached a consensus that improved

institutions facilitate trade and that production of more-sophisticated products requires
better institutions. Keeping these two issues
in mind, developing nations have to find
ways to improve their institutions. This is a
complex problem, especially for developing
nations facing resource constraints.
Reforming policy through measures like
relaxation of licensing requirements or reductions in import taxes is one way to improve on
the current situation. For example, if there is
no import restriction on a certain good, there
is also no possibility for a corrupt customs
official to take a bribe to allow its importation.
In other words, streamlining rules and liberalizing trade will likely reduce incentives for
corruption. In turn, this should help increase
the volume of trade.
On the other hand, improving the quality
of judicial institutions in a nation is a much
more difficult proposition and will depend on
a variety of factors, including but not limited
to the political systems in these nations.
Subhayu Bandyopadhyay is an economist at the
Federal Reserve Bank of St. Louis. Suryadipta
Roy is assistant professor of economics at High
Point University, High Point, N.C., and Yang
Liu is a senior research associate at the Bank.
For more on Bandyopadhyay’s work, see http://
research.stlouisfed.org/econ/bandyopadhyay.
The Regional Economist | www.stlouisfed.org 11

ECONOMIC LIFE

Living Arrangements Matter
Not Just to Your Parents
but Also to Policymakers
By Guillaume Vandenbroucke
© THINKSTOCK

he United States has 115 million households, the makeup of which varies across
the board. Some people live alone. In other
households, many people reside—the average
is 2.6. Some occupants are married. Some
are cohabiting. Some have never married.
Should the composition of U.S. households
and the living arrangements of people in
them matter to economists and policymakers? Yes. Think of unemployment and
income inequality, for example. No question,
these are issues of interest to policymakers.
The decision to look for a job, as well as some

The possible indicators are many. Consider
the decision to be a member of the labor force
or not. Being a member of the labor force
does not always mean that one is employed.
One may be unemployed and looking for a
job and still be included in the “labor force
participation” data. However, if one does not
even look for employment, then one is not
part of the labor force.
A person who is sufficiently economically
secure may choose not to participate in the
labor market. Figure 1, Panel A shows that
more than 90 percent of married men between

When comparing married men and married women, the gap in
earnings tends to be large, albeit decreasing over time. … What
is remarkable, however, is that there was almost no difference
between never-married men and never-married women.
measures of income inequality, are closely
connected with the living arrangements
people choose, as I will show in this article
with a few statistics.
First, let’s take a look at how the composition of U.S. households has changed over the
years. According to the Current Population
Survey, the fraction of households headed
by a married couple has decreased since the
1970s from 70 to 50 percent. Over the same
period, the fraction of households made up
of men or women living alone has increased,
from just below 20 to just below 30 percent.
These trends reveal another set of trends: The
marriage rate of Americans has decreased,
and the divorce rate has increased. Another
phenomenon is the increasing number of
people cohabiting but not getting married.1
So, how does economic life differ for
people in different living arrangements?
12 The Regional Economist | April 2015

the ages of 18 and 50 who live with their
spouses have participated in the labor market
since at least the 1970s. Quite different are the
numbers for married women living with their
spouses. In 1970, fewer than half were in the
labor force; that percentage grew by 1990 to 70
percent, where it remains, more or less, today.
This trend has been the object of many studies
and, in fact, was under way before the 1970s.
The picture of labor force participation
changes when one looks at never-married
individuals, as in Figure 1, Panel B. There, the
difference between men and women appears
insignificant compared with Panel A. About
75 percent of never-married men and women
participate in the labor force today; this figure
has been remarkably steady since the 1970s.
To be sure, Figure 1 does not answer the
“which comes first” question, that is, are
people deciding to participate in the labor

force based on their living arrangement, or
are they choosing their living arrangement
based on whether they are members of the
labor force? These are interesting questions,
but not the ones I am trying to answer here.
My point is that living arrangements and
economic lives are correlated.
Let’s turn to another indicator of economic
performance: income. More precisely, let us
look at the income received from labor and
exclude other sources of income, such as
financial assets, Social Security payments,
etc. It is well-known, and often discussed,
that income inequality is large. One form of
inequality is the so-called gender gap in labor
income, that is, the fact that men tend to be
paid more than women. Panel A of Figure 2
shows the ratio between men’s and women’s
labor income. When this number is close to 1,
men and women have similar levels of income.
When the number is far above 1, men earn
more than women. The people considered
here are similar in age (between 30 and 40)
and education (they have at least a high school
diploma). Also, they are all working.
The figure reveals that, when comparing
married men and married women, the gap in
earnings tends to be large, albeit decreasing
over time. In the 1970s, a married man of this
type made 2.5 times more money working
than a married woman of the same age and
with the same education. What is remarkable, however, is that there was almost no
difference between never-married men and
never-married women. The ratio is much
closer to 1, which, again, means that they
earn the same amount of money at work.
This is more evidence that the arrangement
in which people spend their lives has important implications for their economic lives;
this is particularly true for women.

FIGURE 1

ENDNOTE
Panel B

100

2015

1970

2015

2010

2005

2000

1995

1985

1980

1975

10
1970

Never-married female

1985

Never-married male

2010

Female, spouse present

1980

2005

Male, spouse present

1975

2000

Population Survey, Annual Social and Economic
Supplement, selected years, 1970 to 2012.

1995

1 The source is the U.S. Census Bureau, Current

1990

Percent in Labor Force

Panel A

1990

Percent in Labor Force

Labor Force Participation of Men and Women, by Marital Status

SOURCE: IPUMS-CPS (Integrated Public Use Microdata Series—Current Population Survey), University of Minnesota. See www.ipums.org.
NOTE: A high percentage of married men have always been in the labor force, as can be seen in Panel A; the percentage of married women was less than half of
that of men in 1970 but has since grown dramatically. Panel B shows that the percentages of never-married men and never-married women in the labor force have
been close since 1970.

FIGURE 2
Panel B

3.0

2.5

2015

2010

Female

2005

0.0

Male

2000

2015

2010

2005

2000

1985

1980

1975

1970

0.0

1995

Never married

0.5

1995

Married, spouse present

1990

0.5

1.0

1985

1.0

1.5

1980

1.5

2.0

1970

2.0

1975

Married-to-Never-Married Earnings

Panel A

3.0

1990

Male-to-Female Earnings

Relative Earnings

SOURCE: IPUMS-CPS (Integrated Public Use Microdata Series—Current Population Survey), University of Minnesota. See www.ipums.org.
NOTE: Panel A shows that married men still make more than married women, although the gap isn’t nearly as large as it was in 1970; meanwhile, the gap in earnings between never-married men and never-married women has been small—or even nonexistent—over the entire period. Panel B shows that married men have
always earned more than never-married men. The panel also shows that never-married women earned more than married women from 1970 until sometime after
2005; for most of the time since then, married women have earned more.

Panel B of Figure 2 reveals another aspect
of the data that is interesting. It shows the
relative earnings between married and
never-married people. Again, they are all
between 30 and 40, have at least a high school
diploma and work. Clearly, for men it is better financially to be married. Married men
make about 50 percent more money than
never-married men. However, for most of
the sample period, it is exactly the opposite
for women: Married women tend to make
less money (50 percent less in the 1970s)
than never-married women (at least until the
end of the sample period). Once again, the

question of causality is not addressed here:
Are the married men making more money
than the single men because they are married, or is it the case that more-productive
men are better at getting married?
In the end, the lesson from this discussion
is that living arrangements are informative
about people’s economic lives.
Guillaume Vandenbroucke is an economist at
the Federal Reserve Bank of St. Louis. For more
on his work, see http://research.stlouisfed.org/
econ/vandenbroucke.
The Regional Economist | www.stlouisfed.org 13

F I S C A L

P O L I C Y

Stimulus Grants and Schools:
How Was the Money Spent?
By Bill Dupor
© THINKSTOCK

he ability of the Federal Reserve to
stimulate the economy through monetary policy has been hampered in recent
years because the federal funds rate, the
Fed’s primary policy instrument, has been
effectively “stuck” at zero. Once reached, the
“zero lower bound” limits a central bank’s
ability to provide additional monetary
stimulus. In this situation, fiscal policy takes
center stage as a potential tool to combat
an economic downturn. Stimulative fiscal
policy consists of lowering taxes, increasing
transfers to individuals, increasing government purchases, or some combination of
the three. The federal government pursued
all three of these strategies as part of the
American Recovery and Reinvestment Act
of 2009 (ARRA). The law’s total price tag
was $840 billion, making it the largest countercyclical fiscal intervention in the U.S.
since FDR’s New Deal.
A large share of the ARRA’s funding was
made as grants to state, local and other governments below the federal level, as well
as to public institutions. Public school
districts were one of the largest groups of
these recipients, receiving over $64 billion
in Department of Education ARRA dollars.
This injection of funds translated into
greater spending at the district level. The
figure displays the median value of total
expenditures relative to enrollment for
public school districts by school year. As the
figure indicates, expenditures per pupil rose
substantially following the act’s passage.
Moreover, the ARRA’s education component has been touted as one of the success
stories by supporters of the law. For example, according to the Executive Office of the
President in 2009, “The rapid distribution
of SFSF [State Fiscal Stabilization Fund]
14 The Regional Economist | April 2015

funding helped fill the gaps and avert layoffs
of essential personnel in school districts and
universities across the nation.”
The three immediate goals of the act were:
• to create new jobs and save existing ones,
• to spur economic activity and invest in
long-term growth, and
• to foster unprecedented levels of accountability and transparency in government
spending.
As a bonus for researchers, the ARRA
provided a great deal of detailed data to
analyze the effectiveness of countercyclical
fiscal policy.
A Research Challenge

From a public policy perspective, it is
important to quantify the effects of the
ARRA’s components, including education.
To answer this question for the act’s education component, one must address the
counterfactual: What would school districts
have done with spending and hiring decisions in absence of the act’s funds? M. Saif
Mehkari, a University of Richmond economics professor, and I answered this question
in a study this year by exploiting the heterogeneity in how these ARRA grant dollars
were allocated across school districts, that
is, how did districts that were receiving
relatively little grant money adjust their
spending choices relative to districts
receiving plenty of grant money? From this
comparison, Mehkari and I inferred how all
districts would have performed had ARRA
funds not been available.
To conduct this study, we used data on
expenditures, both ARRA and non-ARRA
revenue, and staffing levels for over 6,700
school districts from both before and during
the ARRA period. We found that, during

the first two years following the act’s passage, each $1 million of grants to a district
increased education employment by 1.5
persons relative to a no-stimulus baseline.1
Moreover, all of this increase came in the
form of nonteaching staff. The jobs effect
was also not statistically different from zero.
One potential explanation for not changing the number of teachers may be the
districts’ own preference for maintaining
student-teacher ratios in the classroom. If
this was a top priority for district administrators, then even districts with relatively
small ARRA grants and large budget gaps
may have found ways to meet budget shortfalls other than laying off teachers. In fact,
surveys of school administrators found
that, in response to the recession, administrators took exactly these types of steps,
including furloughing personnel, eliminating or delaying instructional improvement
initiatives, deferring textbook purchases
and reducing high-cost course offerings.2
The positive, but seemingly small, effect on
nonteaching staff may be similarly due to
a desire to maintain student-staff ratios at
close to their pre-act levels.
Moreover, districts that received relatively
generous ARRA grants may have been less
willing to hire new staff for risk that, once
the short-lived grants were spent, the new
staff would need to be let go.
We also found that each $1 million of
grants increased expenditures at the district
by $570,000 relative to a no-ARRA baseline.
Approximately 70 percent of the expenditures took the form of capital outlays, such
as construction, land purchases and equipment acquisition. The gap between the two
numbers, $430,000, might be accounted for
by states’ cutting their own contributions to

ENDNOTES

Median Expenditure per Pupil by School District
12,000

1 In their study, one job refers to one job-year, that

is, one year of employment for a person.

11,800

2 See American Association of School Administrators.
3 If state governments did cut their contributions

11,600

to districts upon the districts’ receipt of ARRA
grants, then an interesting, and more complicated,
issue is how state governments might have used
these freed-up dollars.

11,400
Dollars

11,200
11,000

REFERENCES

10,800
10,600
10,400
10,200
10,000

2007

2008

2009

2010

2011

SOURCE: National Public Education Financial Survey.
NOTE: The American Recovery and Reinvestment Act of 2009 provided $64 billion in grants to public school districts around the country.
As can be seen in the chart, the median spending per pupil rose after the act’s passage.

school districts upon the districts’ receipt of
ARRA grants.3
Explaining a Puzzle

At first pass, it may seem puzzling that
school districts used a substantial part of
their grant dollars for capital outlays at a time
when the economy was in a deep downturn.
To address whether this behavior would

It may seem puzzling that
school districts used a substantial part of their grant
dollars for capital outlays at
a time when the economy
was in a deep downturn.
be rational on the part of the districts, we
developed a model of the dynamic budgeting problem faced by a school district. In the
model, a district uses revenue to hire workers
and purchase capital, that is, equipment and
structures, to provide a flow of educational
services over time. The district chooses its
inputs to maximize the expected flow of
educational services, both now and in the
future, that it can generate. The model also
assumes that the district can make rational
predictions of how much revenue, on average,
it will receive in the future, despite considerable levels of uncertainty.
Next, suppose the district receives a onetime injection of funds, such as the ARRA
money. The district could choose either to

increase employment substantially, causing a temporary improvement in teacherstudent and staff-student ratios, or make
investments in capital. Interestingly, and
perhaps intuitively, the model implies that
most of the revenue increase is spent on
capital investment because it allows the
district to smooth the benefits of additional
educational services provided by the capital
over many years, benefiting not only today’s
students but those in the future. Only a
small amount of revenue is used to increase
the number of employees in the district.
Thus, the model is capable of explaining
two of our empirical findings: the small, but
positive, education jobs effect and the relatively large increase in capital expenditures
resulting from ARRA grants. Our model
does not address the result that districts
used only about one-half of their grants on
expenditures. In summary, our research
shows that the education component of
the Recovery Act was only partly successful at boosting spending on public education in the U.S. The extent to which other
intergovernmental grants, such as those for
high-speed rail and home weatherization,
financed by the act actually translated into
greater spending on their intended objectives remains an open question.

American Association of School Administrators.
“Weathering the Storm: How the Economic Recession Continues to Impact School Districts.” Report
of Findings, March 2012. See http://aasa.org/
uploadedFiles/Policy_and_Advocacy/files/
Weathering_the_Storm_Mar_2012_FINAL.pdf.
Council of Economic Advisers. “Estimates of Job
Creation from the American Recovery and
Reinvestment Act of 2009.” Executive Office of
the President of the United States. May 2009. See
www.whitehouse.gov/administration/eop/cea/
Estimate-of-Job-Creation.
Dupor, Bill; and Mehkari, M. Saif. “Schools and
Stimulus.” Federal Reserve Bank of St. Louis
Working Paper 2015-004A. See http://research.
stlouisfed.org/wp/more/2015-004.
Executive Office of the President of the United States.
“Educational Impact of the American Recovery
and Reinvestment Act.” A report issued by the
Domestic Policy Council in cooperation with the
U.S. Department of Education, October 2009. See
www.whitehouse.gov/assets/documents/DPC_
Education_Report.pdf.

Bill Dupor is an economist at the Federal
Reserve Bank of St. Louis. For more on his work,
see http://research.stlouisfed.org/econ/dupor.

The Regional Economist | www.stlouisfed.org 15

M E T R O

P R O F I L E

A Familiar Name
with an Economy
Facing Familiar Challenges
By Georgette Fernandez Laris and Charles S. Gascon
At a recent Route 66 festival in downtown Springfield, classic cars were a big draw.

PHOTO BY DAVID J. ESLICK

Springfield, Mo., as well as the area around it, has the air of Americana, with it being the
birthplace of the legendary Route 66 and sharing a name with other medium-sized cities that
seem to reflect the heartland of the country. While the origin of the city’s name is contested,
some presume it resulted from early settlers’ remembrances of distant Springfields.

he city of Springfield, Mo., is the largest of
the eight cities that share the Springfield
name.1 It is also the second-largest of the four
metropolitan statistical areas (MSAs) sharing
the name, having about three-quarters the
population of Springfield, Mass., almost twice
as many residents as Springfield, Ill., and three
times as many as Springfield, Ohio.
The Springfield, Mo., MSA extends across
five counties in southwestern Missouri:
Christian, Dallas, Greene, Polk and Webster.
Robust population growth over the past few
decades reflects the region’s relative prosperity. Since 1970, annual growth has averaged
over 1.8 percent, about three times the state
average (0.6 percent) and higher than the
national rate (1 percent).
The area’s educational attainment closely
aligns with the state’s. In the MSA, 87.8 percent of the 2009-2013 population had at least
a high school diploma and 26 percent held a
bachelor’s degree or higher. Springfield’s
percentage of those with a high school
diploma is slightly higher than the national
percentage (86 percent), and the collegeeducated population share is slightly below
the U.S. average (28.8 percent).
Springfield’s real gross domestic product
(real GDP) growth has been modest during
16 The Regional Economist | April 2015

the postcrisis recovery period, averaging
1 percent between 2010 and 2013. Based on a
survey we conducted among local businesses,
Springfield’s low cost of living is perceived as
one of the region’s strengths. In 2012, Springfield’s price level was 10.8 percent lower than
the U.S. average. Its relative affordability
is most pronounced in terms of the cost of
housing. As of 2012, Springfield’s rents were
31.3 percent lower than the U.S. average,
5.4 percent lower than the state average and
approximately 14.6 percent lower than the
average in nearby metropolitan areas, such as
St. Louis. Springfield, Mo., also has the lowest
cost of living of the four Springfield MSAs in
the country.
“Springfield isn’t tied to one major employer,
but diversified geographically by many smalland medium-sized employers.”
—Springfield-area retailer 2

In many ways, the region’s distribution of
workers among different sectors mirrors ongoing national trends. Seventy-five percent of
the MSA’s workers are employed in the private
service sector, slightly higher than the national
average (70 percent). The MSA’s service sector
workers tend to be employed in the health
care, transportation and retail sectors.

The diverse industry mix, coupled with a
strong base of health care employment, has
afforded the region strong job growth over
the past few decades. The area was relatively
stable economically even during the Great
Recession and financial crisis.
The Role of Health Care

More than 17 percent (about 34,000)
of the region’s workforce is employed in
health care. Almost half of these workers
are employed by the region’s two largest employers: Mercy Health (9,004) and
Cox Health Systems (7,891). Relative to the
national average, this represents about
1.3 times as many workers in the health
care sector. The strong health care presence
helped buffer job losses during the Great
Recession; while the other sectors lost about
12,000 jobs between 2007 and 2009, the
local health care sector added 2,600 jobs.
As one of the fastest-growing sectors
nationally, this has been a boon for the
region since the recession ended: Almost a
quarter of the MSA’s employment growth
during this period has come from the health
care sector.
The sector is thought to employ relatively
high-paid people; almost 14,000 workers are

employed in “practitioner and technical”
occupations, earning an average of $58,000
per year, about 60 percent above the MSA
average wage across all industries, which is
about $37,000. On the other hand, Springfield also has about 7,200 workers in health
care support occupations; these workers earn
an average wage of about $24,000.
Beyond health care, Springfield is headquarters for two major national retailers:
Bass Pro Shops and O’Reilly Auto Parts,
employing 2,600 people and 1,500, respectively. While not headquartered in the
MSA, Wal-Mart is also a major employer in
the region, employing 3,567 people. These
firms, along with many other retailers in the
region, employ close to 25,000 people or 12
percent of the total MSA workforce. Still,
the retail sector has not, thus far, reached its
prerecession peak.
“We do not have enough manufacturing jobs that
have sufficient pay. We have a labor force based
on service and fast food.”
—Springfield-area construction contact3

Unlike many Midwestern cities that have
relied heavily on manufacturing, Springfield has actually employed a smaller share
of workers in manufacturing than both
Missouri and the nation since the 1980s.
At the same time, the region has closely
followed the nationwide prolonged decline
in manufacturing jobs: While in 1980,
roughly 16 percent of the MSA’s workforce
was employed in manufacturing (21 percent
nationally), by 2013, only 7 percent of the
MSA’s workforce was employed in the sector
(9 percent nationally).
Despite this steady decline and the
smaller share of employment, manufacturing
remains an important sector in the region,
accounting for 12 percent of the region’s output in 2013. Multiple contacts we surveyed
expressed the desire for more manufacturing
jobs because of the higher wages associated
with the industry. In Springfield, manufacturing jobs pay, on average, close to $42,000,
which is almost 20 percent above the average
pay for workers in the MSA.
“Paying more than a living wage would help with
poverty issues in the area.”
—Springfield-area nonprofit contact

Few higher-paying manufacturing jobs
may explain some of the lower-wage bias in

the region. Wages across all major occupational groups are relatively low when
compared with those of other MSAs in Missouri. In St. Louis, where the cost of living
is nearly the same (a fact that may surprise
many), average wages (across all industries)
are 35 percent higher, or $47,800 per year.
While Springfield’s low wages can be seen
as a comparative advantage relative to what
is being paid in other MSAs, they are not
without a hitch. While contacts noted that
the relatively low wages in the Springfield
area were important in driving job growth,
regional poverty is a concern, as well, since
almost 19 percent of the MSA population
lives below the poverty level, higher than the
national rate of 14.5 percent. The poverty
rate is even more pronounced in counties
such as Dallas and Polk, where it is over
20 percent.
While many factors can fuel wage discrepancies among MSAs, these discrepancies
can be most directly accounted for by cityspecific differences in labor productivity.4
For example, in 2013, an average worker in
Springfield produced about $79,000 worth of
output, while the average value of output per
worker in St. Louis was $103,800, approximately 30 percent more. Differences in labor
productivity, in turn, depend on multiple
factors; these include workers’ skill levels,
often measured by educational attainment,
and prior work experience. In Springfield,
nearly 26 percent of the population has at
least a bachelor’s degree and 8.6 percent has
a graduate degree or higher, compared with
31 percent and 12 percent, respectively, in
St. Louis. Similarly, researchers have found a
positive relationship between wages and city
size—a 1 percent increase in wages for each
additional 100,000 people.5 Based on this
relationship alone, one would expect wages
in St. Louis to be about 24 percent higher
than in Springfield.
Current Economic Conditions
“Low labor costs make it easier for businesses to
survive, grow and increase jobs.”
—Springfield-area service-sector contact
“I see wages are lower here than in some other
parts of the country, but I believe unemployment
is less here.”
—Springfield-area Realtor

Mercy Health is the largest employer in the area, with
more than 9,000 employees. The health care sector
employs more people (18 percent of the total) than any
other sector.
PHOTO ©MERCY HEALTH

MSA Snapshot
Springfield, Mo.
Population.............................................................................................448,744
Population Growth (2009-2013).................................................. 3%
Population (Age 25+)
w/Bachelor’s Degree or Higher................................................. 26%
Population in Poverty...................................................................... 18.7%
Real Per Capita Personal Income......................................$36,121
Real Per Capita Personal Income Growth
(2009-2012)...............................................................................................1.5%
Cost of Living........................................................................................–10.8%
Rents.........................................................................................................–31.3%
Unemployment Rate............................................................................4.6%
Real GDP (2013)..................................................................... $15.7 billion
Real GDP Growth (2010-2013)...................................................... 1%
NOTE: Population estimates come from the U.S. Census
Bureau. Cost of living data come from the Bureau of
Economic Analysis’ Regional Price Parities series.

LARGEST EMPLOYERS

1. Mercy Health Springfield...........................................................9,004
2. Cox Health Systems.......................................................................7,891
3. Wal-Mart Stores.................................................................................3,567
4. Springfield Public Schools........................................................3,206
5. Missouri State University..........................................................2,583
SOURCE: www.springfieldregion.com.

2013 Per Capita Personal Income

Polk
$29.520
$29,520K

Dallas
$31.460
$31,460K

Greene
Greene
$36,870
$36.870 K

Webster
$29,380

Christian
$34,430
Springfield

SOURCE: GeoFRED with data from the
U.S. Bureau of Economic Analysis.

The Regional Economist | www.stlouisfed.org 17

Missouri Metropolitan Statistical Areas’ Price Parities: All Items (2012)
ENDNOTES

80.8

Jefferson City
Cape Girardeau
Joplin
St. Joseph
Missouri
St. Louis
Springfield
Fayetteville-Springdale-Rogers
Columbia
Kansas City
U.S. Median

82.8

1 According to the Census Bureau, cities named

87.8
88.1
88.1
88.9
89.2
90.3

92.2
92.7
93.2
70

Regional Price Parities (U.S.=100)
SOURCE: Bureau of Economic Analysis, Regional Data.
NOTE: The Regional Price Parities (RPPs) presented in the table above measure the differences in the price levels of goods and services across states and
metropolitan areas for a given year. RPPs are expressed as a percentage of the overall national price level for each year, which is equal to 100. Springfield’s
broad Regional Price Parity of 89.2 indicates the area’s price level is 10.8 percent lower than the U.S. aggregate (equal to 100). In the figure, the U.S. median
statistic suggests that 50 percent of the MSAs in the country have a cost of living (as measured by the RPPs) lower than 93.2 and 50 percent above it. The
median is very close to, yet below, the mean RPP of 94.6, indicating a slightly higher concentration of more-expensive cities. Roughly 25 percent of the country’s
MSAs have RPPs ranging between 97 and 122.9. Springfield falls into the least expensive 25th percentile.

4
5
6

Missouri Metropolitan Statistical Areas’
Real Per Capita Personal Income (2012)

REFERENCES
Baum-Snow, Nathaniel; and Pavan, Ronni. “Understanding the City Size Wage Gap.” Review of
Economic Studies, January 2012, Vol. 79, No. 1,
pp. 88-127.
Eubanks, James D.; and Wiczer, David. “Where’s
the Wage Pressure?” Federal Reserve Bank of
St. Louis The Regional Economist, January 2015,
Vol. 23, No. 1, an online-only article. See www.
stlouisfed.org/publications/regional-economist/
january-2015/wage-pressure.

$35.8

Joplin
Springfield
Fayetteville-Springdale-Rogers
St. Joseph
U.S. Average
Columbia
Average
Cape Girardeau
Jefferson City
Kansas City
St. Louis

$37.8
$38.9
$39.6
$40.7
$40.7
$40.8
$42.9
$45.8
$47.6
0

Springfield are in Florida, Illinois, Massachusetts, Michigan, Missouri, Ohio, Oregon and
Tennessee. As of July 2013, Springfield, Mo.,
had a population of 164,122, about 10,000 more
than Springfield, Mass. In addition to those eight
cities, there are 12 smaller localities around the
country sharing the Springfield name.
Anecdotal information in this report was
obtained from a voluntary survey of business
contacts in Springfield between Feb. 4 and Feb. 13.
In total, 114 contacts completed the survey,
conducted by the Federal Reserve Bank of
St. Louis. The results should be interpreted
with caution because the sample of respondents
may not be fully representative of businesses in
Springfield. Some quotes were lightly edited to
improve readability.
About 9.7 percent of workers are employed in
food preparation and serving-related occupations, just slightly above the national rate.
Measured by GDP per worker, adjusting for
differences in average hours worked.
See Baum-Snow and Pavan.
See Eubanks and Wiczer.

Thousands
SOURCE: Bureau of Economic Analysis, Regional Data.
NOTE: Real per capita income is total real personal income divided by total midyear population. In the figure, the U.S. average corresponds to the mean real per
capita personal income across all the MSAs in the country.

Springfield, Mo.,
Springfield,
Mo., Employment
Employment Industry
IndustryMix
Mix
Construction
(LQ=0.8)

Other Services
(LQ=0.9) 4%

Education
(LQ=0.6) 1%

Wholesale Trade
(LQ=1.2)

Much like the nation, Springfield has
enjoyed steady job growth and a falling
unemployment rate. As of December 2014,
the unemployment rate stood at 4.6 percent,
about a percentage point below the national
average and well below the state average of
5.4 percent. The local housing market has
shown signs of improvement. As of the fourth
quarter in 2014, home prices were up
2.4 percent from one year ago, the number
of building permits had increased slightly
and anecdotes have been generally upbeat.
Early indicators, including our survey
results, suggest that growth has continued
into the first part of 2015. Almost 60 percent
18 The Regional Economist | April 2015

of the businesses surveyed noted that January
sales met or exceeded their expectations.
However, many contacts said they did not
expect a short-term uptick in business to
change their hiring plans. For example, one
contact noted that his company has held off
hiring for the past couple of years to ensure
the stability of the recovery, reiterating that
hires will be made only for long-term growth.
Looking Ahead

According to our survey results, the
perceived economic outlook for Springfield
is positive. With several national employers in the area, the region is expected to

Transportation
(LQ=1.4)

Information
(LQ=1.0) 2%

5%
5%

18%

Financial
Activities
(LQ=1)

Health Care
(LQ=1.3)
14%

7%
10%

Government
(LQ=0.9)

12%

Manufacturing
(LQ=0.8)

12%

Leisure and Hospitality
(LQ=0.9)

Retail Trade
(LQ=1.1)

Prof. and Bus. Services
(LQ=0.9)

NOTE: The figure shows the share of total employment by industry in 2014.
Industries shaded in the blue scale employ a larger share of workers than the
national average, meaning they have quotients (LQ) greater than 1. Industries
shaded in the red scale employ a smaller share of workers than the national
average, meaning they have an LQ less than 1. The darkness of the shading
indicates the magnitude of the difference. For example, the health care sector
employs 18 percent of the region’s workforce, which is 1.4 times the national
average of 13 percent, hence the dark-blue shade. The financial activities sector
employs 6 percent of the region’s workforce, which is only slightly greater than
(1.01 times) the national average of 5.8 percent, hence the light-blue shade.

E C O N O M Y

G L A N C E

REAL GDP GROWTH

CONSUMER PRICE INDEX (CPI)

8
4
PERCENT

2
0
–2
–4
–6
–8
–10

Q4
’09

’10

’11

’12

’13

PERCENT CHANGE FROM A YEAR EARLIER

’14

CPI–All Items
All Items, Less Food and Energy

–3

February

’10

’11

’12

’13

’14

’15

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

I N F L AT I O N - I N D E X E D T R E A S U RY Y I E L D S P R E A D S

RATES ON FEDERAL FUNDS FUTURES ON SELECTED DATES

3.00

0.60

2.75

0.50

2.50
PERCENT

PERCENT

12/17/14

03/18/15

01/28/15

04/07/15

0.40

2.25
2.00
1.75

10-Year

1.25

0.10

20-Year

1.00

’11

’12

’13

0.30
0.20

5-Year

1.50

April 3
’14

0.00

’15

1st-Expiring
Contract

NOTE: Weekly data.

C I V I L I A N U N E M P L O Y M E N T R AT E

3-Month

6-Month

12-Month

CONTRACT SETTLEMENT MONTH

I N T E R E S T R AT E S
4

10-Year Treasury

10
3

PERCENT

7
6

Fed Funds Target
1-Year Treasury

5
4

March

’10

’11

’12

’13

’14

’15

’10

’11

’12

’13

March

’14

’15

NOTE: On Dec. 16, 2008, the FOMC set a target range for
the federal funds rate of 0 to 0.25 percent. The observations
plotted since then are the midpoint of the range (0.125 percent).

U.S. AGRICULTURAL TRADE

AVERAGE LAND VALUES ACROSS THE EIGHTH DISTRICT
Exports

75
Imports

60
45
30
15
0

Trade Balance

’10

’11

’12

’13

’14

NOTE: Data are aggregated over the past 12 months.

February

’15

YEAR-OVER-YEAR-PERCENT CHANGE

Charles S. Gascon is a regional economist,
and Georgette Fernandez Laris is an industry
relations specialist, both at the Federal Reserve
Bank of St. Louis. For more on Gascon’s work,
see http://research.stlouisfed.org/econ/gascon.

Eleven more charts are available on the web version of this issue. Among the areas they cover are agriculture, commercial
banking, housing permits, income and jobs. Much of the data are specific to the Eighth District. To see these charts, go to
www.stlouisfed.org/economyataglance.

BILLIONS OF DOLLARS

benefit from strong national growth. Seventy
percent of contacts surveyed expect the local
economy to be better or somewhat better
during the next 12 months, and fewer than
10 percent of contacts expect conditions to
worsen. Respondents also carefully follow
policies that might have an impact on the
region. As expected, contacts mentioned a
wide range of policy issues; the most important factors influencing their outlook include
changes in interest rates, the Affordable Care
Act and state funding for highway projects
and for other municipal programs.
In addition to the survey respondents’
widespread perception of Springfield’s low
labor costs, contacts noted that the unemployment rate is lower than in nearby areas
and wondered how this may impact job
growth and wages. Some mentioned facing
difficulties in finding qualified workers,
which ultimately affects their hiring strategies. Intuitively, the already low unemployment rate, paired with employers’ difficulties
in finding adequately skilled workers, could
cause an uptick in wages. However, the
relationship between wages and unemployment is not as direct. In fact, average hourly
earnings (adjusted for inflation) in the region
have been on a slow and steady decline. Some
of this reflects long-term, nationwide changes
in the country’s wage structure, most of
which started even prior to the 2007-09 Great
Recession. Recent research has shown that
improvements in labor market conditions are
more likely to affect the bargaining power
and wages of workers earning less than the
median wage than those of higher earners.6
While this could mean good news for lowincome earners in Springfield, the majority of
businesses surveyed don’t anticipate a significant increase in wages. Rather, most survey
respondents expect wages to remain the
same or increase only slightly. This is because
firms typically adjust wages based on labor
productivity growth, which has been weak,
and inflation expectations, which have been
lower recently. Should these factors improve,
wage growth should pick up.

A T

14
12
10
8
6
4
2
0
–2
–4
–6
–8

Quality Farmland
Ranchland or Pastureland

2013:Q4 2014:Q1 2014:Q2 2014:Q3 2014:Q4
SOURCE: Agricultural Finance Monitor.

The Regional Economist | www.stlouisfed.org 19

D I S T R I C T

O V E R V I E W

Track Records for District, Nation
Differ on Startups, Which Are
an Important Driver of Job Growth
By Maria E. Canon

he creation of new businesses, the
so-called startups, is important for
job growth, as research has shown. Economists John Haltiwanger, Ron Jarmin and
Javier Miranda, using data from the Census
Bureau’s Business Dynamics Statistics (BDS),1
showed that the annual job creation rate in
the U.S. is 18 percent, that is, every year 18
percent of total employment stems from jobs
created during that year.2 About a fifth to a
third of that annual job creation happens at
startups, they found.3 This high rate of creation is balanced with high job-destruction
rates of about 16 percent of total employment per year, according to Haltiwanger,

During the recovery from
the Great Recession,
establishments’ births were
significantly higher in the
nation than in the District,
which explains lower jobcreation rates in the District.
Jarmin and Miranda4; about a third of this
job destruction happens at establishments
that shut down. Using the same data, economist Tim Kane found that during recessions
job creation at startups remains stable, while
net job growth (job creation minus job
destruction) at existing firms is highly sensitive to the business cycle.5
Studying the dynamics of establishments’
births and deaths gives important information about labor market performance. We
compare the dynamics of such flows in
the states of the Eighth District (excluding
Illinois6) relative to the nation since the early
20 The Regional Economist | April 2015

1990s. BDS data measure
establishment births
and deaths, as well as
the subsequent creation
and destruction of jobs.
Births and deaths of
businesses do not include
temporary shutdowns
or seasonal reopenings.
Thus, a business must
be closed for a year to be
considered as a death.
This, in turn, restricts the
availability of business
death data up to the second quarter of 2013.

The Eighth Federal Reserve District
is composed of four zones, each of
which is centered around one of
the four main cities: Little Rock,
Louisville, Memphis and St. Louis.

©CL AYCO

Business incubators play an important role in many communities in encouraging
people to start businesses. Cortex (above) is one of those in St. Louis.

Dynamics during the Great Recession

The chart shows establishments’ births and
deaths for the states in the Eighth District and
the nation since late 2006. Births and deaths
are normalized to 100 in each quarter of 1993;
therefore, each index reflects establishments’
births/deaths relative to the same quarter of
1993. New establishments (births) decreased
significantly during the Great Recession for
both the states in the Eighth District and the
nation. In the fourth quarter of 2007, establishment births in the states of the Eighth
District were 8.1 percentage points higher
than in the fourth quarter of 1993, but these
births decreased 13.9 percentage points by the
third quarter of 2009, the first quarter after
the recession officially ended. The pattern was
similar for the nation: While establishment
births were 19.2 percentage points higher in
the fourth quarter of 2007 than in the fourth
quarter of 1993, they decreased by 18.4 percentage points by the third quarter of 2009.
Establishment deaths, or shutdowns,
increased significantly during the Great

Recession. Shutdowns in the states of the
Eighth District were 12.5 percentage points
higher in the first quarter of 2009 relative
to the fourth quarter of 2007. For the nation,
shutdowns were 13.9 percentage points
higher in the first quarter of 2009 relative
to the fourth quarter of 2007.
Consistent with the findings in the 2013
study by Haltiwanger, Jarmin and Miranda,
the decrease in establishments’ births and
the increase in establishments’ deaths were
accompanied by an increase in job losses
and a sharp decrease in job creation. (See
the table.) Job losses increased 15.15 percent
for the Eighth District states and 9.85
percent for the nation between the fourth
quarter of 2007 and the second quarter of
2009. Newly created jobs decreased 16.3
percent for the Eighth District states and
16.63 percent for the nation between the
fourth quarter of 2007 and the second quarter of 2009. Therefore, the Eighth District
states experienced more volatile employment dynamics during the Great Recession

Establishments’ Employment Gains and Losses

ENDNOTES
Growth rates (percent)

Job Gains

Dec. 2007-June 2009

June 2009-June 2013

U.S.

–16.63

12.71

Eighth District

–16.30

8.09

9.85

–19.11

15.15

–21.97

U.S.

Job Losses

1 The Business Dynamics Statistics data series, pub-

Eighth District

2
3

Business Births and Deaths
150
Eighth District Births

U.S. Births

Eighth District Deaths

U.S. Deaths

4
5
6

140

Index 1993=100

130
120
110
7

June 2013

Dec. 2012

June 2012

Dec. 2011

June 2011

Dec. 2010

June 2010

Dec. 2009

June 2009

Dec. 2008

June 2008

Dec. 2007

Dec. 2006

June 2007

100

SOURCES: Bureau of Labor Statistics and National Bureau of Economic Research.
NOTE: Each reading on the horizontal axis corresponds to the same quarter in 1993. The shaded bar shows the span of the Great Recession.

than did the nation as a whole. This higher
variability in employment can be explained
by a larger decrease in establishments’ birth
rates in the financial activities and “other
services” sectors, combined with a larger
increase in establishments’ death rates in
the manufacturing sector in the District,
relative to the nation.
Dynamics in the Recovery

In the second quarter of 2013, four years
after the Great Recession ended, employment gains in the U.S. were 12.71 percent
higher than in the second quarter of 2009;
in the District states, the gains were 8.09
percent higher. Total employment reflects
lower employment losses in the District
relative to the nation over the same period.
(Employment losses in the second quarter
of 2013 were 21.97 percentage points lower
than in the same quarter of 2009 for the
District, while they were 19.11 percentage
points lower for the nation.)
Similar to what happened during the
Great Recession, establishments’ birth and
death rates help explain these dissimilar
employment dynamics. During the recovery

from the Great Recession, establishments’
births were significantly higher in the nation
than in the District, which explains lower
job-creation rates in the District. In the
second quarter of 2013, business birth rates
were 14.5 percentage points higher in the
nation than in the same quarter of 2009, but
birth rates were only 11.7 percentage points
higher in the District. In the postrecession
period, total birth rates in the District continued to be lower in the financial activities
and “other services” sectors, as well as in the
information, retail and transportation sectors, helping to explain lower job-creation
rates in the District.7 Differences in establishments’ deaths in the four years after
the end of the Great Recession are not as
significant (12.8 percentage points lower in
the District and 11.9 percentage points lower
in the nation).

lished by the Census Bureau, decomposes the U.S.
net employment change into gross job gains and
gross job losses. The quarterly data series includes
the number and percent of gross jobs gained by
opening and expanding establishments, and the
number and percent of gross jobs lost by closing
and contracting establishments. The data also
include the number and percent of establishments
that are classified as openings, closings, expansions and contractions.
See Haltiwanger, Jarmin and Miranda (a) and (b).
The BDS calls a startup an establishment of age
zero, and calls an existing firm an establishment
that is at least 1 year old.
See Haltiwanger, Jarmin and Miranda (a).
See Kane.
Illinois is excluded because Chicago, where
much of the state’s economic activity takes
places, is not part of the Eighth District. BDS data
cannot be broken down for the Eighth District’s
portion of the state, the southern part. More
details on the Eighth District region can be found
at http://research.stlouisfed.org/regecon.
Some exceptions are observed in the professional
services sector, in which birth rates have been
increasing in Missouri since the first quarter of
2009; since the third quarter of 2011, these rates
have been above prerecession levels. Startups in
the education and health sector in Missouri also
showed a significant spike in the first quarter
of 2013.

REFERENCES
Haltiwanger, John; Jarmin, Ron; and Miranda, Javier
(a). “Business Formation and Dynamics by Business Age: Results from the New Business Dynamics
Statistics,” CES working paper, May 2008. See
http://www.census.gov/ces/pdf/BDS_Business_
Formation_CAED_May2008.pdf.
Haltiwanger, John; Jarmin, Ron; and Miranda, Javier
(b). “Who Creates Jobs? Small versus Large versus
Young,” Review of Economics and Statistics, May
2013, Vol. 95, No. 2, pp. 347-61.
Kane, Tim. “The Importance of Startups in Job Creation and Job Destruction,” Kauffman Foundation
Research Series: Firm Formation and Economic
Growth, July 2010. See www.kauffman.org/~/
media/kauffman_org/research%20reports%20
and%20covers/2010/07/firm_formation_importance_of_startups.pdf.

Maria E. Canon is an economist at the Federal
Reserve Bank of St. Louis. For more on her work,
see http://research.stlouisfed.org/econ/canon.

The Regional Economist | www.stlouisfed.org 21

O V E R V I E W

Growth Is Modest
in GDP but Strong
in Labor Markets
By Kevin L. Kliesen

he U.S. economy appears to have lost
some momentum during the winter
months of 2014 and 2015. Although it is
often difficult to gauge the underlying
strength of the economy in real time, it
appears that temporary factors have worked
to slow the pace of economic activity in the
first quarter. By contrast, U.S. labor market
conditions remain strong despite a weakerthan-expected March employment report.
Over the six months ending in March 2015,
nonfarm payroll employment increased by
about 1.6 million. Thus, with the slowdown
viewed as temporary and inflation having
been temporarily reduced because of the
recent plunge in oil prices, the Federal
Open Market Committee (FOMC) signaled
at its March meeting that it remains on
track to begin normalizing monetary policy
this year.
The Pause That Refreshes

The U.S. economy lost a bit of momentum
at the end of last year. According to the
Bureau of Economic Analysis, real gross
domestic product (real GDP) rose at a 2.2
percent annual rate in the fourth quarter of
2014 after increasing at about a 4.75 percent
annual rate during the previous two quarters. Weaker growth in the fourth quarter
of 2014 largely reflected sizable declines in
businesses’ equipment expenditures and
federal defense outlays.
By contrast, the growth of real personal
consumption expenditures (PCE) remained
vibrant over the second half of 2014. Households continued to benefit from the plunge in
crude oil prices, spurring a noticeable increase
in their real after-tax personal income.
Although the advance estimate for real
GDP growth in the first quarter of 2015 will
not be published until late April, forecasters have been modestly marking down their
estimates because of weaker-than-expected
data. In mid-March, the consensus of
professional forecasters was that real GDP
was likely to increase by a little less than
22 The Regional Economist | April 2015

The FOMC’s March 2015 Economic Projections for 2015 and 2016
5.7

5.1

2014 (Actual)

5.0

2015
2016

4
Percent

N A T I O N A L

2.4

2.5

2.5
1.8

2
1.1
0

Real GDP Growth

Unemployment Rate

0.7
PCE Inflation

NOTE: Projections are the midpoints of the central tendencies. The projections for real GDP growth and inflation are the percentage change
from the fourth quarter of the previous year to the fourth quarter of the indicated year. Inflation is measured by the personal consumption
expenditures (PCE) chain-price index. The projection for the unemployment rate is the average for the fourth quarter of year indicated.

2.5 percent; however, some forecasters are
predicting that real GDP growth will slow to
2 percent or less.
Adverse weather in January and February explains part of the slowing in the
first quarter. For example, January and
February retail sales were much weaker
than expected; however, supportive of the
weather story, online sales posted healthy
gains during this period. Thus, despite some
recent firming in gasoline prices in February and early March, the household sector
remains a bright spot in the outlook—a
sentiment noted in the March Beige Book.
Other temporary factors contributing to
the expected first-quarter slowdown include
a likely drop in business inventory investment, cutbacks in capital spending in the oilexploration industry and the recent slowing
in shipments from West Coast ports, a development that has hampered supply chains.
Despite modest growth in the overall
economy, firms continue to add jobs at a
brisk pace. Although nonfarm payrolls rose
by only 126,000 in March, the unemployment remained at 5.5 percent. If the expected
slowdown reflects temporary factors, then
the economy should strengthen over the
remainder of 2015. If job growth remains
brisk, then it is likely that the unemployment
rate will fall below 5 percent sometime during the second half of 2015.
The combination of robust labor market
conditions and the prospect of continued
low mortgage rates in 2015 should also
benefit the housing industry. Industry
forecasters expect that new home construction will increase by about 11 percent in

2015, although the consensus of professional
forecasters is a bit less optimistic.
Business surveys suggest that optimism
among large and small firms is on the rise.
However, a sizable percentage of large firms
are worried about the recent strengthening
of the dollar and some softening of growth in
Europe and Asia. Thus, while a strengthening
domestic economy should help the manufacturing sector, the near-term outlook for
business capital spending is more mixed.
Temporary Decline in Inflation

Headline inflation, as measured by the
PCE price index, was about 0.75 percent
in 2014, lower than 2013’s 1.25 percent
increase. Inflation edged further downward
in February, as the PCE price index was up
by only 0.3 percent over the previous
12 months. Besides weaker oil prices, the
recent strengthening of the trade-weighted
dollar has intensified the downward pressure on prices of nonpetroleum imported
goods. But with inflation excluding energy
prices measuring 1.5 percent in February, it
is highly likely that headline inflation rates
(including food and energy) will rise modestly over the remainder of 2015 as oil prices
begin to stabilize. Still, most forecasters
expect that headline PCE price inflation will
remain below 2 percent in 2015. That also is
the consensus of the FOMC.
Kevin L. Kliesen is an economist at the Federal
Reserve Bank of St. Louis. Lowell R. Ricketts, a
senior research associate at the Bank, provided
research assistance. See http://research.stlouisfed.
org/econ/kliesen/for more on Kliesen’s work.

R E A D E R

E X C H A N G E

ASK AN ECONOMIST

accumulation of experience over time helps to overcome the informational,

Ana Maria Santacreu is an economist at the
Federal Reserve Bank of St. Louis, where she
has worked since September. Her research
focuses on international trade, international
macroeconomics and economic growth. She
enjoys outdoor activities, especially hiking,
biking and sailing. For more on her research,
see http://research.stlouisfed.org/econ/
santacreu.

Q: What’s behind the dramatic increase in international
trade? What can be done to increase it even further?

contractual and cultural barriers involved in trade.3 Our finding clarifies the large
difference between trade flows among existing partners and new partners. The
accumulated experience of countries that have been trading since before 1948
effectively makes trade with that country much cheaper.
The benefits of experience tend to be shared among firms and industries; so,
this is where there is opportunity to help increase international trade: by supporting the entry of early exporters—those first few companies that start trading with
a new country. This would lower the trade costs and encourage entry by new firms
and products into export markets.

Decomposition of World Exports into Trade between Country
Pairs That Traded Prior to 1950 and Emergence of New Trade
16
14

be surprising to some people is that less than one-quarter of the growth in trade

between 1948 and 2006 was due to the emergence of new trading partners. The
large majority of the increase in world trade came from countries that had traded
with one another since before the first year in the sample.
When discussing barriers to trade, people usually think of transportation costs,

Trillions of Dollars

A: World trade has increased dramatically over the past few decades. What may

market access and tariffs. However, a survey of firms1 found that the biggest bar-

World Trade

Country Pairs with Positive Trade before 1950
Trade between New Pairs

8
6
4
2

riers to trade actually are:

0
1951 1956 1961 1966 1971 1976 1981 1986 1991 1996 2001 2006

i) identifying contacts,

SOURCE: Dutt, Santacreu and Traca.

ii) understanding customers in the destination,

Year

iii) coping with regulations and the legal environment, and

ENDNOTES

iv) building networks and relationships.
In a recent paper, my co-authors, Pushan Dutt and Daniel Traca, and I built on
this insight and looked at the role of experience in international trade. We found
2

that more experience between a particular exporter-importer pair of countries
lowers bilateral trade costs and increases bilateral exports. This is because the

1 See Telephone Survey of UKTI Inward Investment and Trade Development

Customers and Non-Users: Summary Report, OMB Research: London, 2005.

2 Read the working paper, “The Gravity of Experience,” at http://research.stlouisfed.

org/wp/more/2014-041.

3 Experience is measured as the number of years for which a pair of countries has been trading.

St. Louis Fed’s Free Resources on Personal Finance and Economics Grow in Popularity

pril is National Financial Literacy Month, a good time for the Federal Reserve

uct, monetary policy and money. The St. Louis Fed also offers free, face-to-face

Bank of St. Louis to remind teachers and others of the many educational re-

professional development for educators within its District.

sources it has offered for years, first on paper and now online, too, all at no charge.
In 2011, the St. Louis Fed began providing economic and financial education
materials online for use in the full range of classrooms—from kindergarten through
college. That year, Bank economic education staff developed 23 online courses.

The data below show growth in the use of the St. Louis Fed’s free online
resources from 2013 to 2014.

Item

2013

2014

327,227

540,948

Percent Change
65

4,423,965

7,544,677

Today, the Bank has 43 online courses (17 of which are available in Span-

Enrollments in Online Courses

ish), 70 videos and 123 lessons. Many lessons have complementary activities

Pageviews of Education Websites

for interactive whiteboards.

Visits to Education Websites

543,930

916,467

Downloads of Educational Materials

304,585

334,504

The subject matter includes personal finance topics, such as credit, budgeting and saving; also covered are economic topics, such as supply and demand,
opportunity cost, comparative advantage, and present value. The online courses

The St. Louis Fed’s efforts to teach others about personal finance and economics

allow teachers to enroll their students, who can then take the pre- and post-tests

have received many accolades. Last month, the St. Louis Fed was chosen by the

and receive grades from the program. This system allows teachers to track student

Institute for Financial Literacy as its Organization of the Year in its EIFLE awards

progress and address any areas of concern.

(Excellence In Financial Literacy Education).

The Bank’s educational materials are specifically designed to be used in eco-

Besides teachers, students and the general public are welcome to use the

nomics, personal finance, history, civics, mathematics or language arts

Bank’s educational resources on personal finance and economics. Many are

classes and are aligned with national standards in those fields. All materials also

designed for parents and their children to use together. To get started, go to

align with the Common Core State Standards. All materials are free.

www.stlouisfed.org/education.

The Federal Reserve Bank of St. Louis also cooperates with the Federal Reserve

Meanwhile, the Bank has a new educational resource on site that is open to one

banks of Atlanta, Boston and Philadelphia to administer an online professional

and all: the Inside the EconomyTM Museum. Located inside the Bank, in downtown

development program for educators. This program allows teachers, at their

St. Louis, the museum features nearly 100 exhibits, games, sculptures and videos.

convenience, to receive continuing education credit, Federal Reserve certification

In a fun and interactive way, visitors learn how the economy works. For hours and

or graduate credit for five topics: inflation, unemployment, gross domestic prod-

more information, see stlouisfed.org/economymuseum.
The Regional Economist | www.stlouisfed.org 23

Change Service Requested

Chasing Bubbles
How Do You Define, Detect and Deal with Them?

n the July issue of The Regional Economist,
read about recent research on bubbles—

those price run-ups that don’t seem to be
warranted by the fundamentals. Bubbles
are usually difficult to define and detect—
at least until after they’ve burst. See how
the research has developed in this area.
A historical perspective will be given, and
bubbles’ connection to financial crises also
will be explored.

ECONOMY

THE REGIONAL

GLANCE

ECONOMIST

APRIL 2015

REAL GDP GROWTH

4
2
0
–2
–4
–6
–8

Q4
’09

’10

’11

’12

’13

PERCENT CHANGE FROM A YEAR EARLIER

PERCENT

VOL. 23, NO. 2

CONSUMER PRICE INDEX

–10

’14

CPI–All Items
All Items, Less Food and Energy

–3

February

’10

’11

’12

’13

’14

’15

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

I N F L AT I O N - I N D E X E D T R E A S U RY Y I E L D S P R E A D S

RATES ON FEDERAL FUNDS FUTURES ON SELECTED DATES

3.00

0.60

2.75

0.50

2.50
PERCENT

2.25
PERCENT

12/17/14

03/18/15

01/28/15

04/07/15

0.40

2.00
1.75

0.20

5-Year

1.50

0.10

10-Year

1.25

20-Year

1.00

’11

’12

’13

0.30

April 3
’14

0.00

1st-Expiring
Contract

’15

NOTE: Weekly data.

C I V I L I A N U N E M P L O Y M E N T R AT E

3-Month

6-Month

12-Month

CONTRACT SETTLEMENT MONTH

I N T E R E S T R AT E S

10-Year Treasury

10
3

PERCENT

7
6

Fed Funds Target
1-Year Treasury

5
4

March

’10

’11

’12

’13

’14

’15

’10

’11

’12

’13

March

’14

’15

NOTE: On Dec. 16, 2008, the FOMC set a target range for
the federal funds rate of 0 to 0.25 percent. The observations
plotted since then are the midpoint of the range (0.125 percent).

U . S . A G R I C U LT U R A L T R A D E

AVERAGE LAND VALUES ACROSS THE EIGHTH DISTRICT

YEAR-OVER-YEAR-PERCENT CHANGE

Exports

BILLIONS OF DOLLARS

75
Imports

60
45
30
15
0

Trade Balance

’10

’11

’12

’13

’14

NOTE: Data are aggregated over the past 12 months.

February

’15

14
12
10
8
6
4
2
0
–2
–4
–6
–8

Quality Farmland
Ranchland or Pastureland

2013:Q4 2014:Q1 2014:Q2 2014:Q3 2014:Q4
SOURCE: Agricultural Finance Monitor.

U.S. CROP AND LIVESTOCK PRICES / INDEX 1990-92=100
140
120

Crops
Livestock

100
80
60

February

40
’00

’01

’02

’03

’04

’05

’06

’07

’08

’09

’10

’11

’12

’13

’14

’15

YEAR

COMMERCIAL BANK PERFORMANCE RATIOS
U.S. BANKS BY ASSET SIZE / FOURTH QUARTER 2014

All

$100 million$300 million

Less than
$300 million

$300 million$1 billion

Less than
$1 billion

$1 billion$15 billion

Less than
$15 billion

More than
$15 billion

Return on Average Assets*

1.00

0.99

0.95

1.03

1.00

1.04

1.02

0.99

Net Interest Margin*

3.11

3.82

3.83

3.82

3.87

3.85

2.94

Nonperforming Loan Ratio

1.96

1.34

1.36

1.30

1.33

2.15

Loan Loss Reserve Ratio

1.49

1.51

1.53

1.47

1.50

1.34

1.41

1.51

R E T U R N O N AV E R A G E A S S E T S *

NET INTEREST MARGIN*
1.09
1.02
1.27
1.22

1.00
0.96

0.84

0.96
1.06

.00

.20

.40

.80

Fourth Quarter 2014

1.00

1.20

Kentucky

3.78
3.82

Mississippi

3.81
3.70

1.40

PERCENT

Fourth Quarter 2014

1.28

2.08

1.43

1.37
1.36

1.56
1.55
1.61

Missouri

2.00

1.44

Tennessee

2.08

2.50

PERCENT

Fourth Quarter 2013

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

1.77

1.11

Mississippi

1.44

1.50

0.94

Kentucky

1.99

1.43

1.00

1.28

Indiana

1.75

1.63

1.52

Arkansas

1.32

1.16

1.44

Illinois
1.50

1.03

Fourth Quarter 2013

Eighth District

1.72

1.12
1.20

Fourth Quarter 2014

0.0 0.50 1.00 1.50 2.00 2.50 3.00 3.50 4.00 4.50

L O A N L O S S R E S E RV E R AT I O

1.38

.50

3.45
3.44

Fourth Quarter 2013

1.27

4.25

3.66
3.65

Tennessee

N O N P E R F O R M I N G L O A N R AT I O

.00

3.94

Missouri

1.21

1.08

.60

3.60
3.47

Indiana

0.99

0.60

4.28
4.24

Arkansas
Illinois

1.11
1.09
0.90

3.82
3.77

Eighth District

.00

.30

.60

Fourth Quarter 2014

.90

1.20

1.50

1.80

1.60

1.80

Fourth Quarter 2013

For additional banking and regional data, visit our website at:
www.research.stlouis.org/fred/data/regional.html.

2.10

REGIONAL ECONOMIC INDICATORS
N O N FA R M E M P L O Y M E N T G R O W T H / F O U RT H Q U A RT E R 2 0 1 4
YEAR-OVER-YEAR PERCENT CHANGE
United
States

Eighth
District †

Arkansas

Illinois

Indiana

Kentucky

Mississippi

Missouri

Tennessee

0.1%

1.7%

2.2%

Total Nonagricultural

2.2%

1.4%

1.6%

0.8%

1.9%

Natural Resources/Mining

5.0

1.8

4.2

2.7

1.9

–1.0

4.0

0.8

Construction

5.1

3.3

9.4

8.6

3.2

–5.0

–8.0

2.4

Manufacturing

1.7

2.2

3.4

–0.2

4.6

1.4

2.9

2.3

2.5

Trade/Transportation/Utilities

2.1

0.3

–0.1

–0.5

0.5

2.0

–1.4

–0.6

2.1

Information

1.4

–1.8

–4.5

–2.1

–2.8

3.7

–3.7

–2.5

–1.5

Financial Activities

1.6

0.7

–0.1

–0.4

2.1

–2.0

–0.2

2.6

2.1

Professional & Business Services

3.5

3.1

1.2

2.5

2.8

5.4

1.4

3.1

4.6

Educational & Health Services

2.1

1.4

2.2

1.1

0.3

2.3

1.4

2.7

0.9

Leisure & Hospitality

3.2

2.5

4.6

0.6

1.2

6.6

1.3

3.7

3.4

Other Services

1.6

0.5

0.2

3.4

–0.2

–1.4

–1.2

0.8

Government

0.3

0.5

–0.1

0.2

1.5

0.5

0.1

1.5

–0.2

2.0%

† Eighth District growth rates are calculated from the sums of the seven states. For Natural Resources/Mining and Construction categories, the data exclude
Tennessee (for which data on these individual sectors are no longer available).

EIGHTH DISTRICT PAYROLL EMPLOYMENT BY INDUSTRY-2014

U N E M P L O Y M E N T R AT E S
IV/2014

III/2014

IV/2013

United States

5.7%

6.1%

7.0%

Information 1.5%
Trade,
Transportation
and Utilities

Arkansas

5.7

5.9

6.9

Manufacturing

Illinois

6.2

6.5

8.5

Indiana

5.9

5.8

6.5

Kentucky

5.5

6.0

7.7

Mississippi

7.2

7.4

8.0

Missouri

5.5

5.7

6.3

Tennessee

6.6

7.1

Financial Activities
5.3%

15.8%

Natural Resources
and Mining 0.3%

Education and
Health Services

14.8%

11.8%

Construction
3.8%

Professional and
Business Services

12.9%

19.8%

10.0%

Leisure and
Hospitality

Government

Other Services 4.0%

HOUSING PERMITS / FOURTH QUARTER

REAL PERSONAL INCOME* / FOURTH QUARTER

YEAR-OVER-YEAR PERCENT CHANGE IN YEAR-TO-DATE LEVELS

YEAR-OVER-YEAR PERCENT CHANGE

6.4

United States

19.7
10.1

–8.8

Arkansas
29.4

12.2
1.1
1.0

13.9
19.6

2014

–5

–1.6

1.1

–0.9

All data are seasonally adjusted unless otherwise noted.

PERCENT

2.1

–0.9

3.0

Tennessee

2013

4.2

–0.8

Missouri

13.7
16.8

–15 –10

3.1

Indiana

Mississippi

11.6

1.7

–0.5

Kentucky

6.7
6.0

3.3

–2.9

Illinois

30.6

3.4

–0.9

–0.3

–4.00 –3.00 –2.00 –1.00 0.00 1.00 2.00 3.00 4.00 5.00
2014

2013

*NOTE: Real personal income is personal income divided by the PCE
chained price index.

Full text of Regional Economist : A Quarterly Review of Business and Economic Conditions : April 2015, Vol. 23, No. 2

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