regional economist - oct. 2014
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A Quarterly Reviewof Business andEconomic Conditions
Vol. 22, No. 4
October 2014
THE FEDERAL RESERVE BANK OF ST. LOUIS
CENTRAL TO AMERICA’S ECONOMY®
errorismTe oll It akes
on Developing Countries
China and the U.S.Why Teir Food Prices
Now Move Along Similar
“Rockets and Feathers”Why Don’t Gasoline Prices
Always Move in Sync with Oil Prices?
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C O N T E N T S
Gas and Oil Prices Don’t Always Move in SyncBy Michael Owyang and E. Katarina Vermann
Given that Americans still spend a considerable portion o their budget
on gasoline (just under 4 percent in 2012), it’s important to understand
why gas prices don’t always move in sync with oil prices. Te latter are
determined in a more-or-less centralized market, but the market or gas
is ofen local, with prices affected by location, season and taxes, among
other actors.
4
THE REGIONAL
ECONOMISTOCTOBER 2014 | VOL. 22, NO. 4
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, interna-
tional and regional economic issues of
the day, particularly as they apply to states
in the Eighth Federal Reserve District. Views
expressed are not necessarily those of the
St. Louis Fed or of the Federal Reserve System.
Director of Research
Christopher J. Waller
Senior Policy Adviser
Cletus C. Coughlin
Deputy Director of Research
David C. Wheelock
Director of Public Affairs
Karen Branding
Editor
Subhayu Bandyopadhyay
Managing Editor
Al Stamborski
Art Director
Joni Williams
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.
Please direct your commentsto Subhayu Bandyopadhyay
at 314-444-7425 or by email at
You can also write to him at the
address below. Submission of a
letter to the editor gives us the right
to post it to our website and/or
publish it in The Regional Economist
unless the writer states otherwise.
We reserve the right to edit letters
for clarity and length.
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,
P.O. Box 442, St. Louis, MO 63166-0442.
3 PRE S I D E N T ’ S M E S S A G E
10 Terrorism Is a Threat
to Foreign Investment
By Subhayu Bandyopadhyayand Javed Younas
Developing countries that are
struck by terrorists lose not
only lives and property but a lso
potential or economic growth,
studies show. Fearul companies
shit t heir operations elsewhere,
or example, taking with them
their capital and technology.
12 Noncorporate BusinessesFind Credit Is Still Tight
By Juan M. Sánchez
Since the inancial crisis o
2008, credit has loosened up
or corporations but not nearly
as much or noncorporate busi-
nesses. Both types are still having
trouble getting credit rom
banks; corporations, however,
have the ability to issue shares
in the stock market a nd borrow
by issuing bonds.
14 Inflation in China, U.S.
Following Similar Paths
By Maria A. Arias and Yi Wen
A look at ood prices in t he two
countries helps to explain the
increasing correlation in their
inlation patterns. One reason
why their ood prices are mov-
ing together is the increased
trade between the countries.
16 MET RO PRO F IL E
Manufacturing Shares the
Stage with Service Sectors
By James D. Eubanksand Charles S. Gascon
oday, Jackson, enn., the center
o activity in the largely rural area
between Memphis and Nashville,
depends less on manuacturing
and more on such service-
oriented employers as health care
and local government.
1 9 E C O N O M Y A T A G L A N C E
20 D I S T R I CT O VE RV I E W
Minimum Wage’s Impac
Varies across Country
By Charles S. Gascon
Because cost-o-living die
ences vary across and withistates, the ederal mini mum
wage goes urther i n some p
than in others. Mississippi
Oregon are examples o the
mer, while Hawaii and New
are two o t he latter. Meanw
some parts o the country a
raising their minimum wag
ar above the current edera
requirement o $7.25 an hou
22 N A T I O N A L O VE RV I E W
Optimism Prevailsas GDP Snaps Back
By Kevin L. Kliesen
Improvements in auto sales
corporate proits, job grow
and housing sales have con
tributed to the rising opti m
among both consumers and
businesses. Analysts are als
saying that the rebound in
in the second quarter had le
do with the irst qua rter’s b
weather than irst thought.
2 3 R E A D E R E X C H A N G E
ONLINE EXTRARead more at www.stlouisfed.org/publications/re.
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AQuarterlyReviewofBusinessandEconomicCondi tions
Vol.22,No.4
October2014
THE FEDERAL RESERVE BANK OF ST.LOUIS
CENTRAL TO AMERICA’S ECONOMY®
errorismTeollItakeson
DevelopingCountries
ChinaandWhyTeirFoo
MoveAlongS
“Rockets and Feathers”Why Don’t Gasoline Prices
Always Move in Sync with Oil Prices?
Looking at Recessions through a Different Lens
By David G. Wiczer
raditionally, research about recessions ocused on the big picture—how the overall economy was perorming. But recent economicstudies have looked at the impact on specific groups. One othe interesting findings is that the highest earners are, by somemeasures, the most affected by recessions. Teir gains during goodtimes, however, more than make up or their recession losses.
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By conventional metrics, the U.S. econ-omy is approaching normal conditionsin terms o the two main macroeconomic
goals assigned to the Federal Reserve—price
stability and maximum sustainable employ-
ment. Te monetary policy stance o the
Federal Open Market Committee (FOMC),
however, has not yet begun to normalize.
Current policy settings are ar rom normal,
and the normalization process will take a
long time. Tereore, normalizing may need
to begin sooner rather than later i macroeco-
nomic conditions continue to improve at the
current pace.1
Over the past five years, U.S. unemployment
has been high, although it has generally beenimproving since it reached 10 percent in Octo-
ber 2009. In September 2014, the unemploy-
ment rate stood at 5.9 percent, down rom
7.2 percent a year earlier. Inflation was surpris-
ingly low rom the second quarter o 2013
through the first quarter o 2014, but recent
readings have moved closer to the FOMC’s
2 percent target. Te inflation rate, as mea-
sured by the year-over-year percent change in
the personal consumption expenditures price
index, was 1.5 percent in August.
In recent years, the FOMC has used twomain tools to achieve its dual mandate—
A Mismatch: Close to Macroeconomic Goals,
Far from Normal Monetary Policy
P R E S I D E N T ’ S M E S S A G E
short-term interest rate policy (the ederal
unds rate) and quantitative easing (QE).
Te target or the ederal unds rate has
remained near zero since December 2008.
Meanwhile, the Fed’s balance sheet is still
large and increasing, although the current
asset purchase program (QE3) is winding
down. Te size o the balance sheet, at more
than $4 trillion, is roughly 25 percent o U.S.
nominal gross domestic product (GDP).
Te figure illustrates a measure o how
ar the economy’s perormance has been
rom the FOMC’s macroeconomic goals
since 1975 and a measure o how ar the
stance o monetary policy has been rom
normal. Te ormer, based on inflation andunemployment, currently shows a low value
that is close to precrisis levels.2 Te latter,
based on the ederal unds rate and the size
o the balance sheet relative to GDP, shows
the opposite. In other words, the macroeco-
nomic goals are close to being met, whereas
monetary policy settings have a long way to
go beore being close to normal.
While this mismatch is not causing mac-
roeconomic problems today, it may cause
problems in the years ahead as the economy
continues to expand. One risk is that infla-tion would return. I that does happen, the
FOMC would have to adjust policy aster
and more aggressively than it usually does,
as inflation tends to be difficult to get under
control. Te other main risk is that financial
market bubbles could develop. Macropru-
dential policies alone are probably not su-ficient to keep a bubble under control; these
policies must be combined with monetary
policy that is consistent with financial sta-
bility, as well as our macroeconomic goals.
Up to now, relatively low inflation and
relatively weak labor markets have suggested
a later start to normalizing monetary policy
but stronger-than-expected data may change
this calculus in the months and quarters
ahead. Over the next ew years, the objective
will be to execute monetary policy normal-
ization without creating excessive inflationor substantial financial stability risks.
James Bullard, President and CEO
Federal Reserve Bank of St. Louis
E N D N O T E S
1 Tis column is based on my presentation onJuly 17, 2014, “Fed Goals and the Policy Stance.”
See http://research.stlouised.org/econ/bullard/
ed-goals-and-the-policy-stance. 2 For a broader measure o the labor market, one
could use the labor market conditions index rom
staff at the Federal Reserve Board. However, the
results would be similar because there is a high
correlation between this index and the unemploy-
ment rate. See Chung, Hess; Fallick, Bruce;
Nekarda, Christopher; and Ratner, David.
“Assessing the Change in Labor Market Condi-
tions,” FEDS Notes, May 22, 2014.
SOURCES: Federal Reserve Board, Bureau of Economic Analysis, Bureau of Labor Statistics and author’s calculations; data obtained from FRED and Haver Analytics.
NOTES: Details on the functions used to measure these distances can be found in my presentation on July 17, 2014. The figure, which is an updated version of a
chart from that presentation, shows the square root of the function values from January 1975 to June 2014.
For these calculations, the normal policy stance refers to historical averages for the federal funds rate and the size of the balance sheet relative to GDP. The
macroeconomic goals refer to the FOMC’s inflation target and the midpoint of the central tendency of the longer-run projection for unemployment, as of the FOMC’s
September Summary of Economic Projections.
Distance from Goals vs. Distance from Normal Policy
Jan. ’75 Jan. ’80 Jan. ’85 Jan. ’90 Jan. ’95 Jan. ’00 Jan. ’05 Jan. ’10
20
18
16
14
12
10
8
6
4
2
0
Distance of policy stance from normal
Distance from macroeconomic goals
D
i s t a n c e
( s q u a r e
r o o t )
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Why Don’t Gasoline Pric
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By Michael Owyang and E. Katarina Vermann
Always Move in Sync with Oil Prices?
he U.S. Energy Inormation Administrationreported last year that American consum-ers spent, on average, just under 4 percent o their
pretax income on gasoline in 2012—nearly $3,000
per household.
1
In the previous 30 years, thispercentage was this high only once beore—in 2008.
Given the impact on the average American’s
budget, it is important to understand how gasoline
prices are affected by fluctuations in oil prices.
A number o economists have studied the mannerin which changes in oil prices affect changes in gas
prices—the so-called pass-through. Te prevailing
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sentiment is that the pass-through is not
symmetric: Te speed at which gas prices
change differs depending on whether the
price o gasoline is relatively high or rela-
tively low compared with the price o oil.
Both casual and industry observers say
that gas prices adjust to changes in oil pricesaster when gasoline prices are relatively
low compared with oil than when gasoline
prices are relatively high compared with
oil. Tis uneven pass-through can be seen
when oil prices rise afer being steady or
some time—gasoline prices shoot up
quickly. In contrast, when oil prices all
afer being steady or some time, gasoline
prices retreat slowly. In the gasoline indus-
try, this phenomenon is known as “rockets
and eathers.”
Although crude oil prices are determinedin a more-or-less centralized market, retail
gasoline prices vary by season and by
location, depending on supply, demand,
inventories, regulations and—in particu-
lar—taxes. Te ormulation or gasoline
can also vary over time, across seasons and
across locations, depending on environmen-
tal regulation and the average temperatures
during the winter and summer. Tereore,
the sensitivity o gas prices to oil prices may
vary across cities and over the seasons.
We reviewed some o the academic workmeasuring pass-through when gasoline
prices were high relative to oil prices and
vice versa, and we investigated whether
oil price pass-through to national gasoline
prices was different in these cases. We also
considered how the pass-through changes
across the seasons by assessing whether
gasoline prices change more rapidly dur-
ing certain months o the year. Finally, we
considered how the pass-through varies
across the country and whether location can
alter the degree o asymmetry in gasoline’s
responsiveness to oil prices.
Asymmetric Pass-through
Crude oil—the main component o
gasoline—makes up nearly 70 percent o the
pump price o regular gasoline.2 Tereore,
it is not surprising that the per gallon price
o retail gasoline ollows a similar pattern
to the price o crude oil. Figure 1 shows the
monthly national average price o regular
unleaded gasoline per gallon in dollars
(lef axis) rom January 1995 to July 2014,
along with the price o oil per barrel in
dollars (right axis). We plotted the price o
Brent crude instead o the more amiliar
price o West exas Intermediate (WI)
because the two series recently diverged (see
sidebar) and gasoline prices—particularly,
the national average—appear to have been
more closely tied to Brent.
Figure 1 demonstrates the co-movement
between the two series. Fluctuations in oil
prices are closely mimicked in the retail gas-
oline market with a common upward trend
in both series, suggesting that the prices
o oil and gas are related in the long run.
Despite this long-run relationship, the two
prices can independently move around their
long-run ratio in the short run. We estimate
that a $10 rise in the price o a barrel o oil
is correlated with an approximately 25-centincrease in the price o a gallon o gasoline
adjusted or taxes and markups, which are
(relatively) constant over time. I the ratio
between the adjusted price o gasoline to the
crude oil price (25 cents per $10) al ls too
out o line with this long-run relationship,
gasoline prices will tend to adjust to return
to this ratio.
Although oil and gas prices appear to move
together, the speed at which changes in the
upstream price (oil) affects the downstream
price (gasoline) can vary.3
Te adjustmentprocess back to the long-run relationship may
depend on whether gasoline prices are above
or below their long-run ratio with oil prices.
Economists who have studied gasoline prices
have generally ound that gasoline prices
adjust aster when they are low relative to oil
prices than when they are high relative to
oil prices. According to economists Severin
Borenstein, A. Colin Cameron and Richard
Gilbert, two major actors cause asymmetric
FIGURE 1
Oil and Gas Prices
SOURCE: U.S. Energy Information Administration and The Wall Street Journal .
1995 2000 2005 2010
5
4
3
2
1
0
160
140
120
100
80
6040
20
0
Retail Gasoline Price($/Gallon of Regular Gasoline)
Brent Oil Price ($/Barrel)
D o l l a r s
P e r G a l l o n
D o l l a r s
P e r B a r r e l
July 2014
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pass-through: seller market power and supply
chain shocks.
Seller market power implies that retail
gasoline markets are not perectly com-
petitive: Opportunities exist or retailers to
take advantage o price changes to main-
tain a higher overall profit. For example,
Borenstein, Cameron and Gilbert noted
that retailers increased gasoline prices as
oil prices rose to keep a constant margin.
When prices ell, retailers adjusted prices
downward slower because consumers were
already accustomed to the higher prices.
One actor that influences market power
is market concentration: Gas stations that
are physically close together have less
market power than do gas stations that are
arther apart. o illustrate, a 2008 study o
the Southern Caliornia gasoline market by
economist Jeremy A. Verlinda ound that
a rival gas station in “immediate proxim-ity” reduced the difference in the size o the
response o gas prices to positive vs. negative
changes in oil prices. Economist Matthew
Lewis suggested that asymmetric pass-
through is possible because o consumers’
slow processing o gasoline price inorma-
tion. Since people do not tend to observe
gasoline prices until they are ready to reuel
their gas tanks, consumer expectations may
be slow to adjust to pricing changes, allow-
ing prices to remain relatively high.
Supply chain disruptions, such as Hur-ricane Katrina’s effect on refining in the Gul
o Mexico, can also affect oil price pass-
through because refineries can use pricing
to control their inventories. Because gasoline
has a finite supply, refineries can accommo-
date anticipated gasoline shortages by raising
prices in order to cut consumption. For
example, in a 2011 study o weekly national
data, economists Stanislav Radchenko and
Dmitry Shapiro ound that retail gasoline
prices increased 0.52 percent within the first
week o an anticipated increase o 1 percentin oil prices, while they ell 0.24 percent
within the first week o an anticipated
decrease o 1 percent in oil prices.4
We measured the asymmetric response
o gasoline prices to fluctuations in the
pass-through by considering separately
the months in which the adjusted average
national retail gasoline price to oil price
ratio was either above or below 25 cents to
$10. Consistent with much o the literature,
we ound a small difference in the speed at
which gasoline prices were attracted to the
long-run ratio depending on whether prices
were above or below this ratio.
Pass-through during Different Seasons
Gasoline prices vary seasonally. Anec-
dotal evidence suggests gasoline prices in
the United States rise during the spring, up
until Memorial Day weekend. Afer that
point, they remain higher throughout the
summer, typically spike again beore Labor
Day weekend and then retreat in the all.
For example, between 1995 and 2014, retail
gasoline prices rose, on average, 0.4 percent
(1 cent per gallon) during the two weeks
prior to Memorial Day and 1.6 percent
(3 cents per gallon) during the two weeks
prior to Labor Day.
While much o these price changes can
be attributed to increased demand rom
summer driving, gasoline prices may exhibit
some seasonality because o a change in
the cost o production due to changes incomposition: Te gasoline used in many
areas is cheaper in the winter because it
is, essentially, a different product. Average
winter and summer temperatures dictate
some o the changes in gasoline ormula-
tion; environmental regulation is another
determinant. Some areas allow alternative
ingredients in the winter that are cheaper
to produce, but contribute more to pollu-
tion. During the summer, the use o these
alternative ingredients is more restricted.
During the summer in warmer areas,gasoline sometimes requires additives that
reduce the vapor pressure and make the
gasoline less volatile, as well as less suscep-
tible to evaporation in the gas tank. Because
summer gasoline is more costly to produce,
the prices during the spring and summer,
when these products are used, will naturally
be higher.5
We examined whether the pass-through
asymmetry varies over the seasons. o this
Anecdotal evidence suggests gasoline prices in theUnited States rise during the spring, up until Memorial
Day weekend. After that point, they remain higher
throughout the summer, typically spike again before
Labor Day weekend and then retreat in the fall.
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end, we separated the data into observa-
tions occurring during the months o Octo-
ber to March and observations occurring
during the months o April to September.6
We calculated asymmetry or each sample,
thus letting the asymmetry differ both
when gas was above/below the long-run
ratio and across seasons.
By splitting the sample into summer and
winter months, we ound more
evidence o asymmetry. During
the winter, the rate at which
gas prices are pulled down
by oil prices appeared to be
higher than it was during
the summer. Moreover,
splitting the sample by
season appeared to
ampliy the asymmetry,
which appeared to
be higher during thehigh-demand summer season
and when the cost o gasoline production
was higher.
Pass-through across Cities
Gasoline prices differ by location or
a number o reasons. Variation in taxes
accounts or a substantial portion o the
difference. Differences in supply can vary
because o the costs o moving gasoline
rom the refinery to the retail location.
Demand can vary because o commutingpatterns, a city’s population density, the
quality and use o public transportation,
total population, and other actors. We
suggested above that production costs can
cause pricing differentials; thus, variations
in weather—in particular, average summer
and winter temperatures—across cities can
cause differences in the price o gasoline.
In a 2012 paper, economist Matthew
Chesnes studied 27 cities and confirmed
the existence o asymmetric pass-through
in the gasoline market. He ound that thetype o uel used in each city was impor-
tant or determining the magnitude o the
asymmetry: Cities selling predominantly
conventional gasoline (St. Louis and Lou-
isvil le, Ky., or example) were less asym-
metric in adjusting to the long-run ratio
than were other cities where reormulated
gasoline was sold.
Te sensitivity o gas prices to oil prices
may also vary across cities depending on
West Texas Intermediate and Brent:
Two Benchmarks for the Price of Crude Oil
In the United States, there are two main benchmark measures of crude oil prices.One is the price of West Texas Intermediate (WTI), which is a grade of crude oil thatis both low in density and low in sulfur. It is often referred to as Texas sweet light
crude. The low sulfur content of WTI allows more oil to be extracted from the crude.
WTI crude is both sourced and refined in the United States; its price is used as abenchmark only in the United States. Futures contracts for WTI are traded on the New
York and Chicago Mercantile exchanges, among other exchanges, and are settled
in Cushing, Okla.
The second important benchmark price for crude
oil is Brent. Brent oil was originally sourced from 15 oil
fields in the North Sea but has become the international
benchmark for pricing crude oil. It is much more widely
used than is the price of WTI as a benchmark, especially
outside of the United States. There are slight differences
in the density and sulfur content between Brent and
WTI, but the differences are relatively small.
Prior to 2011, the two spot oil prices moved almostin lockstep. This is perhaps not surprising because
WTI and Brent crude oil are essentially the same
product. Standard economic models of commodity
pricing would predict that arbitrage would eliminate price differentials
between the two oil prices. If the price of a commodity is higher in one market
(say, market A) than another (market B), one could, in principle, buy the good
in market B and resell it in market A. This would yield a profit if the two prices
were different. It would also put upward pressure on the price in B and down-
ward pressure on the price in A, making the two prices eventually converge. In
practice, the two prices may not completely converge because of, for example,
the cost of transporting the commodity from B to A. However, after 2011, the
two spot oil prices diverged. The explanation for their divergence might lie in
how—or perhaps where—the two prices are determined.
In early 2011, Cushing reached its storage capacity, causing a difference
between the two spot oil prices that could not be eliminated by arbitrage. In
September 2011, for example, the Brent spot price was $27.31 per barrel higher
than the WTI spot price. This differential is large considering that, prior to 2011,
a typical differential was on the order of $1.37. No arbitrage opportunity existed
because of the inability to move oil from Cushing to another location in the Gulf
Coast where it could be sold for prices closer to the settlement price of Brent
crude. This also meant that the regional variation in gas prices increased; oil
prices (and, thus, gasoline prices) near the coasts were more closely tied to
Brent, while prices in the Midwest were more closely tied to WTI.
Recently, however, the difference between the two spot oil prices has declined.
The decline was due, in part, to the reversal of the oil flow in the Seaway Pipeline,
which normally moves oil from the Gulf Coast to Cushing. The reversal allowed oil
to travel from Cushing to the Gulf Coast, where it could be sold at the Brent price.
During the summer of 2013, the difference between the two spot prices had
declined substantially, to about $3.30 in July 2013. Since then, the difference
peaked at $13.93 in November 2013 and drifted back to $3.18 in July 2014.
These differences are still considerably less than $17, the average difference from
the beginning of 2011 and the end of 2012. In August 2014, the price differential
was $5.07.
© T
H I N K S T O
C K
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E N D N O T E S
1 See www.eia.gov/todayinenergy/detail.
cm?id=9831. 2 See www.eia.gov/petroleum/gasdiesel. 3 Te total effect o oil price fluctuations on gasoline
prices cannot vary lest the long-run relationship
between the two prices breaks down. 4 Te evidence or asymmetr y is by no means con-
clusive. In two studies, one by economists Lance J.
Bachmeier and James M. Griffen and the other by
economist Christopher C. Douglas, no evidencewas ound that gasoline prices adjust back to the
long-run relationship asymmetrically. 5 See http://blog.gasbuddy.com/posts/A-crash-
course-on-seasonal-gasoline/1715-401024-239.
aspx or a good summary o the differences in the
composition o gasoline across the seasons. 6 Tese cutoffs are airly arbitrary and may not
reflect the true differences in the seasonality. 7 Te St. Louis metro area includes parts o South-
ern Illinois. As such, taxes have been removed
using a weighted average o the tax rates across the
states and local municipalities.
R E F E R E N C E S
Bachmeier, Lance J.; and Griffen, James M. “New Evi-
dence on Asymmetric Gasoline Price Responses.”
Te Review of Economics and Statistics, August
2003, Vol. 85, No. 3, pp. 772–76.
Borenstein, Severin; Cameron, A. Colin; and Gilbert,
Richard. “Do Gasoline Prices Respond Asym-
metrically to Crude Oil Price Changes?” Te
Quarterly Journal of Economics, February 1997,
Vol. 112, No. 1, pp. 305-99.
Chesnes, Matthew. “Asymmetric Pass-through in
U.S. Gasoline Prices.” U.S. Federal rade Commis
sion Bureau o Economics Working Paper No. 302
September 2012.
Deltas, George. “Retail Gasoline Price Dynamics and
Local Market Power.” Te Journal of Industrial
Economics, September 2008, Vol. 56, No. 3,
pp. 613-28.
Douglas, Christopher C. “Do Gasoline Prices Exhibi
Asymmetry? Not Usually!” Energy Economics, July 2010, Vol. 32, No. 4, pp. 918–25.
Lewis, Matthew S. “Asymmetric Price Adjustment
and Consumer Search: An Examination o the
Retail Gasoline Market.” Journal of Economic s
and Management Strategy, Summer 2011, Vol. 20,
No. 2, pp. 409-49.
Radchenko, Stanislav; and Shapiro, Dmitry.
“Anticipated and Unanticipated Effects o Crude
Oil Prices and Gasoline Inventory Changes on
Gasoline Prices.” Energy Economics, July 2011,
Vol. 33, No. 5, pp. 758- 69.
Verlinda, Jeremy A. “Do Rockets Rise Faster and
Feathers Fall Slower in an Atmosphere o Local
Market Power? Evidence rom the Retail Gasoline
Market.” Te Journal of Industrial Economics,
September 2008, Vol. 56, No. 3, pp. 581-612.
market power (or concentration). In a 2008
study, economist George Deltas argued that
states with higher average seller margins on
gasoline (which implies ewer sellers) had
more asymmetric pass-through in levels
and a slower speed o adjustment to the
long-run ratio.
We calculated pass-through across 162
cities using weekly pretax retail gasoline
prices and the Brent oil price rom 2005-
2013. Because taxes are ofen assumed to
be the principal source o the variation in
gasoline prices across cities, we constructed
the pretax retail price o gasoline to measure
pass-through at the city level. Tus, our
local retail gasoline price series excludes
national, state and local gasoline-specificexcise taxes, as well as local environmental
regulation ees and sales taxes imposed on
gasoline. Figure 2 shows the time series
o pretax gasoline prices or three cities in
our sample: New York, San Diego and
St. Louis.7 Te cities were chosen to high-
light the regional differences in gasoline
price dynamics. As one might expect, the
gasoline prices in different cities had similar
fluctuations, induced, or the most part, by
fluctuations in oil prices. However, there
were also notable differences: Even aferadjusting or taxes, San Diego and New York
had higher prices than cities in the Midwest
(e.g., St. Louis) possibly due to differences
in proximity to Cushing, Okla., (the source
or WI crude oil) or due to differences in
gasoline composition.
When we analyzed the relationship
between retail gasoline prices and crude oil
prices at the city level, we ound two main
differences. First, the long-run relationship
between gasoline and oil could vary across
cities. Second, the effect o changes in oil
prices on gasoline could vary across cities.
As to the ormer, we ound relatively similar
long-run relationships between gasoline
and oil across cities. Te main difference
across cities was in how gasoline prices were
adjusted or different taxes in the long-run
ratio. Cities exhibited a variety o degrees
o asymmetry; among the most asymmetric
were Anchorage, Alaska; Bakersfield, Cali.;
and Colorado Springs, Colo. In addition, the
responsiveness o gas prices in the various
cities differed. For example, Sacramento,
Cali., was about three times aster to adjust
to the long-run ratio than was Boise, Idaho.
Conclusion
Te market or gasoline is local, with vari-
ations in market concentration, demand,
regulation and taxation. Tus, it may not be
surprising that we ound more asymmetry
at the local level than at the national level.
What does the presence o the asymmetry
mean or consumers and policymakers?
Awareness o the apparent asymmetry can
help consumers better orecast (and budget
or) gasoline expenditures. Further study
is needed to understand the origin o theasymmetry and its consequences or the
overall welare o the economy.
Michael Owyang is an economist and E. KatarinaVermann is a senior research associate, both atthe Federal Reserve Bank of St. Louis. For moreon Owyang’s work, see http://research.stlouis- fed.org/econ/owyang.
FIGURE 2
Gas Prices across Select Cities
SOURCES: The Wall Street Journal , Gas Buddy and author’s calculations.
M a r c h ’ 0 5
S e p t .
’ 0 5
M a r c h ’ 0 6
S e p t .
’ 0 6
M a r c h ’ 0 7
S e p t .
’ 0 7
M a r c h ’ 0 8
S e p t .
’ 0 8
M a r c h ’ 0 9
S e p t .
’ 0 9
M a r c h ’ 1 0
S e p t .
’ 1 0
M a r c h ’ 1 1
S e p t .
’ 1 1
M a r c h ’ 1 2
S e p t .
’ 1 2
M a r c h ’ 1 3
5
4
3
2
1
0
160
140
120
100
80
6040
20
0
San DiegoSt. Louis
D o l l a r s P e r G a l l o n
D o l l a r s P e r B a r r e l
New York City
Brent August 2013
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errorism around the world is a problemor oreign direct investment (FDI). Forexample, a multinational corporation based
in the U.S. may find a location in India to
be attractive or setting up a plant because
o the abundance o cheap and well-trained
labor there. However, i that area is also apotential location or insurgency and ter-
rorism, the multinational will have to weigh
the benefits rom lower wage costs against
the possibility o loss o plant, manpower
and equipment rom terrorist attacks. On
aggregate, a higher incidence o terrorism(as perceived by potential investors) will
tend to reduce their willingness to invest in
a terrorism-inested area.1
Let us consider the case o Colombia,
which was notorious or drug violence and
terrorism in the 1980s and 1990s. In more
recent years, Colombia has seen significant
declines on these ronts. Te figure shows
that as terrorism has allen, FDI has risen.
Without careul analysis, we cannot sug-
gest this apparent relationship as causal;
however, a link is possible. Fortunately,the literature in this area includes careul
studies on the link between terrorism and
FDI, studies that have employed rigorous
economic theory and econometric methods.
Te rest o this article provides a sample o
this research.
Impact in Spain, Greece
A 1996 study by economists Walter
Enders and odd Sandler is one o the first
to quantiy the effect o terrorism on FDI.
Teir study investigated how transnational
terrorism had affected FDI flows into Spain
and Greece.2 Using net annual oreign direct
investment (NFDI) data rom the mid-1970s
through 1991, they ound that terrorist inci-
dents reduced NFDI in Spain by 13.5 percentand in Greece by 11.9 percent. Te authors
noted that these reductions amounted to
7.6 percent and 34.8 percent o annual gross
fixed capital ormation or Spain and Greece,
respectively. Clearly, this means that terror-
ism had a major negative effect on capitalormation in these nations and, in turn, on
their potential or economic growth.
Impact on FDI from the U.S.
A large number o transnational terrorist
attacks on the U.S. are conducted against
U.S. interests in oreign nations. Tis is
likely to raise the risks or U.S. corpora-
tions doing business abroad. In a 2006
study, Enders, Sandler and ellow economist
Adolo Sachsida investigated how terror-
ism in other nations may have affectedFDI rom the U.S. into these nations. Tey
ound that terrorist attacks lowered U.S.
FDI by 1 percent in nations that belong to
the Organization or Economic Coopera-
tion and Development (OECD) but had
no statistically significant effect in non-
OECD nations. Greece and urkey (OECD
members) suffered relatively large damages,
amounting to U.S. FDI reductions o
5.7 percent and 6.5 percent, respectively.
Diversion of FDI
Some studies have argued that terrorist
attacks usually destroy only a small raction
o the capital stock o a nation and, there-
ore, are unlikely to cause major economic
damage. A 2008 study by economists
Alberto Abadie and Javier Gardeazabal
ound otherwise. Tey showed that even
when the direct damage to a nation’s capital
stock is not large, the eventual, overall
impact may be large because, or example,
earul oreign investors divert their money
to other nations. Tis diversion can result in
a large loss o investment. Using a cross-
sectional study, the economists ound that
a one-standard-deviation increase in the
intensity o terrorism in a particular nation
can reduce the net FDI position o that
nation by approximately 5 percent o itsGDP, a large impact.
Threat to Developing Nations
FDI is considered to be a major source o
oreign capital and technology to support
economic growth in developing countries.
I terrorism reduces FDI flows into these
nations, their growth and development
can be stymied. Tis poses a challenge
or economists who provide policy advice
to international donor agencies like U.S.
Agency or International Development andthe World Bank.
In their 2014 study on this issue, econo-
mists Subhayu Bandyopadhyay, Javed
Younas and the aorementioned Sandler
ocused on 78 developing countries over the
period 1984-2008. Te authors ound that
both domestic and transnational terrorism
significantly depressed FDI in develop-
ing countries. A one-standard-deviation
increase in domestic terrorist incidents per
Terrorism: A Threat
to Foreign Direct Investment
D O I N G B U S I N E S S A B R O A D
By Subhayu Bandyopadhyay and Javed Younas
Many of the terrorism-afflicted nations are poor and lack vital
resources that can be used for counterterrorism. This problem
can be partly alleviated by foreign aid.
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E N D N O T E S
1 Among others, a 2008 paper by economists Abadie
and Gardeazabal shows that a greater intensity
o terrorism increases the variance o the return
to investment while reducing its mean. Clearly,
a lower average rate o return to investment in a
nation will tend to reduce potential FDI into that
nation.
2 When a terroris t incident in a certain country
involves citizens or property o another country, it
is considered to be transnational terrorism.
3 Te Bandyopadhyay et al. analysi s presents a
theoretical model in which aggregate aid has
unconditional aid and aid tied to counterterrorism
as its two components. Te theoretical analysis
shows that tied aid can reduce the adverse effect
o terrorism on FDI. Te econometric analysis
motivated by this model finds significant benefits
o oreign aid in terms o reducing the damages to
FDI rom terrorism.4 For details on securit y concerns as a donor
motive, see the 2013 study by Bandyopadhyay
and Vermann.
R E F E R E N C E S
Abadie, Alberto; and Gardeazabal, Javier. “errorism
and the World Economy,” European Economic
Review, January 2008, Vol. 52, No. 1, pp. 1-27.
Bandyopadhyay, Subhayu; Sandler, odd; and
Younas, Javed. “Foreign Direct Investment,
Aid, and errorism,” Oxford Economic Papers,
January 2014, Vol. 66, No. 1, pp. 25-50.
Bandyopadhyay, Subhayu; Vermann, E. Katarina.
“Donor Motives or Foreign Aid,” Federal Reserve
Bank o St. Louis Review, July/August 2013,
Vol. 95, No. 4, pp. 327-36.
Enders, Walter; Sachsida, Adolo; and Sandler, odd.
“Te Impact o ransnational errorism on U.S.
Foreign Direct Investment,” Political Research
Quarterly, December 2006, Vol. 59, No. 4,
pp. 517-31.
Enders, Walter; and Sandler, odd. “errorism and
Foreign Direct Investment in Spain and Greece,”
Kyklos, August 1996, Vol. 49, No. 3, pp. 331-52.
100,000 people reduced net FDI between
approximately $324 million and $513 mil-
lion or the average sample country, whose
GDP totaled $70 billion. A one-standard-
deviation increase in transnational terroristincidents per 100,000 people reduced net
FDI between approximately $296 million
and $736 mil lion at the same level o GDP.
Te loss o FDI, however, was much smaller
when it was calculated at the median value
o GDP ($10.4 bill ion) in the sample.
Many o the terrorism-afflicted nations
are poor and lack vital resources that can be
used or counterterrorism. Tis problem can
be partly alleviated by oreign aid. Bandyo-
padhyay et al. ound in their study earlier
this year that oreign aid can help in thisregard and that the evidence suggests sig-
nificant terror-mitigating effects on FDI.
For example, the aorementioned lower
estimate o FDI loss rom domestic terror-
ism o $324 million is reduced to about
$113 million or the average aid-receiving
nation, while the lower estimate or trans-
national terrorism is reduced to about
$45 million rom $296 million.3
As the World Shrinks
In an integrated global economy, ter-rorism presents policy challenges both at
home and abroad. Te July 2014 downing
over Ukraine o a Malaysian jet carrying
Dutch passengers (or the most part) was a
stark reminder o this interconnectedness.
Accordingly, U.S. policymakers involved
with counterterrorism remain vigilant
about terrorism in the U.S. and abroad.
By ocusing on the existing literature on
FDI and terrorism, we can see that policy
efforts targeted at reducing terrorism can
provide substantial economic benefits to the
terrorism-afflicted nations.
Te literature also points to the impor-
tant role that oreign aid may play in termso containing terrorism and boosting the
growth potential o developing nations. Te
literature on oreign aid has increasingly
ocused on security concerns rather than
on a recipient nation’s economic need as a
motive behind giving oreign aid.4 Along
similar lines, the aorementioned 2014
study by Bandyopadhyay et al. suggests that
oreign aid may be motivated by, among
other things, substantial economic benefits
in terms o greater FDI flows to nations with
reduced terrorism.
Subhayu Bandyopadhyay is an economist at theFederal Reserve Bank of St. Louis, and JavedYounas is an associate professor of economics at American University of Sharjah, United ArabEmirates. For more on Bandyopadhyay’s work,see http://research.stlouisfed.org/econ/bandyo- padhyay.
Foreign Direct Investment (FDI) and Terrorism in Colombia
NOTE: Data are averaged over six-year nonoverlapping periods from 1988 to 2011, which gives us four time periods. Terrorism incidents include domestic,
transnational and other acts of terrorism that cannot be unambiguously assigned to either of these two categories.
SOURCES: FDI-World Development Indicators (2013); Terrorism-Global Terrorism Database, University of Maryland, College Park.
1988-1993 1994-1999 2000-2005 2006-2011
6
5
4
3
2
1
0
F D I , T e r r o r i s m
Terrorism incidents (hundreds) FDI as % of GDP
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Firms use credit to finance production,working capital, investment in physicalcapital, and research and development. All
these activities are important or the unc-
tioning o the economy. In act, as argued in
recent research, there is a strong connection
between the development o credit marketsand that o the economy.1
On June 5, the Board o Governors o the
Federal Reserve System published the Finan-
cial Accounts o the United States or the first
quarter o 2014. Tis article uses data rom
that publication to analyze the use o credit
by nonfinancial businesses since the financial
crisis o 2008. Te main finding is that the
evolution o outstanding liabilities has been
very different or corporate and noncorporate
businesses, with a remarkable stagnation in
credit to noncorporate businesses.Figure 1 displays the value o outstand-
ing liabilities o corporate and noncorporate
businesses. Since their previous peak (during
the financial crisis), liabilities o corporate
businesses increased about 20 percent,
while liabilities o noncorporate businesses
increased only 4 percent. Tese patterns may
be important to understand the strength
o the recovery i we take into account the
well-established connection between the
unctioning o credit markets and that o the
aggregate economy. Recent research showsthat disturbances in financial markets may
be an important cause o business-cycle
fluctuations.2
Corporations are distinguished rom
noncorporations in two critical ways: (i) the
financial sources to which they have access
(corporations can issue shares in the stock
market and can borrow and lend by issuing
bonds, while noncorporations can’t do either)
and (ii) the ownership and control structure
(a corporation is owned by shareholders but
is typically run by a separate group o man-
agers, while noncorporations are typically
owned by one or two individuals who alsoperorm as managers).3 Te first element is
important to understand the differences in
the type o liabilities available or these two
groups o firms.
Te main components o liabilities or both
corporate and noncorporate businesses are
credit instruments (e.g., commercial paper,
corporate bonds, depository institution loans
and mortgages). Tey represent about 60
percent and 70 percent o the liabilities o
corporations and noncorporations, respec-
tively. Te rest are trade payables, which areliabilities owed to suppliers or purchases or
services rendered; tax payables, which are
taxes that a company owes as o the balance
sheet date; and others.
Figure 2 displays the evolution o credit
market instruments. Te difference between
corporations and noncorporations is quite
striking. Since the financial crisis, corpora-
tions increased the value o outstanding
credit market instruments by 27 percent,
while the same variable increased by only
3 percent or noncorporations.
o understand the evolution o credit mar-
ket instruments, consider their composition,as shown in Figure 3. For noncorporate busi-
nesses, most o the debt is composed o mort-
gages (69 percent) and loans rom depository
institutions (27 percent). In contrast, 68
percent o the credit market liabilities o cor-
porations are corporate bonds, which are not
available to noncorporate businesses.
Te table displays the growth o loans
rom depository institutions, mortgages and
corporate bonds. Recall that the first two are
the most important credit instruments used
by noncorporate businesses, while the lastone is available only or corporations. Te
trend in loans rom depository institutions
and in mortgages since the financial crisis
is very sluggish or both types o businesses.
Actually, or these two instruments, growth
was negative or corporate businesses and
slightly positive or noncorporate businesses.
Te key difference is that noncorporate busi-
nesses rely on these instruments, while these
instruments are much less important or
2006:Q1 2007:Q1 2008:Q1 2009:Q1 2010:Q1 2011:Q1 2012:Q1 2013:Q1 2014:Q1
Noncorporate (Right Axis)
Corporate (Left Axis)
B i l l i o n s
o f D
o l l a r s
6500
6000
5500
5000
4500
4000
B i l l i o n s
o f D
o l l a r s
17000
16000
15000
14000
13000
12000
11000
10000
FIGURE 1
Total Liabilities of Nonfinancial Businesses
SOURCE: Financial Accounts of the United States, published by the Board of Governors of the Federal Reserve System.
Credit to Noncorporate
Businesses Remains Tight
P O S T - F I N A N C I A L C R I S I S
By Juan M. Sánchez
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FIGURE 3
Components of Credit Market Liabilities, by Instruments, 2013
SOURCE: Financial Accounts of the United States, published by the Board of Governors of the Federal Reserve System.
For Nonfinancial Noncorporate Business For Nonfinancial Corporate Business
Mortgages
Depository institution loans
Other loans and advances
Corporate bonds
Municipal securities
Commercial paper
Mortgages
Depository institution loans
Other loans and advances
69%
27%
4%
68%11%
6%
2%
corporations, as shown in Figure 3. Actually,
the strong recovery o credit or corporationsis due to the ast growth o corporate bonds;
their growth has increased at an average
annual rate o 10 percent since 2008:Q4.
Overall, credit to noncorporate businesses
remains tight. Tis phenomenon is mostly
accounted or by the sluggish recovery o
loans rom depository institutions and mort-
gages, which are very important or this type
o business. ight credit may be affecting
the day-to-day operations o noncorporate
E N D N O T E S
1 See, or example, Greenwood, Sánchez and Wang. 2 See Shourideh and Zetlin-Jones. 3 See Magill and Quinzii, Chapter 6, Section 31, or
a thorough discussion.
R E F E R E N C E S
Greenwood, Jeremy; Sánchez, Juan M.; and Wang,
Cheng. “Quantiying the Impact o Financial
Development on Economic Development,” Review
of Economic Dynamics, January 2013, Vol. 16,
No. 20, pp. 194-215.
Magill, Michael; and Quinzii, Martine. Teory of
Incomplete Markets, Vol. 1. Cambridge: MI
Press, 1996.
Shourideh, Ali; and Zetlin-Jones, Ariel. “External
Financing and the Role o Financial Frictions over
the Business Cycle: Measurement and Teory.”
Working Paper, University o Pennsylvania’s
Wharton School, December 2012.
businesses since credit is important or
growth. Future research should ocus ontrying to find out the reasons or the weak
recovery o lending by banks and other
depository institutions.
Juan M. Sánchez is an economist at the FederalReserve Bank of St. Louis. For more on hiswork, see http://research.stlouisfed.org/econ/ sanchez. Lijun Zhu, a technical research associ-ate at the Bank, provided research assistance.
SOURCE: Financial Accounts of the United States, published by the Board of Governors of the Federal Reserve System.
Corporate Noncorporate
Depository institution loans –3.3% 1.5%
Mortgages –7.3% 0.2%
Corporate bonds 10.3% n.a.
Growth Rates of Key Credit Instruments since 2008:Q4, Annualized
2006:Q1 2007:Q1 2008:Q1 2009:Q1 2010:Q1 2011:Q1 2012:Q1 2013:Q1 2014:Q1
Noncorporate
Corporate I n d e x
( 1 0 0 =
2 0 0 6 : Q
1 )
170
160
150
140
130
120
110
100
90
80
FIGURE 2
Value of Outstanding Credit Market Instruments
SOURCE: Financial Accounts of the United States, published by the Board of Governors of the Federal Reserve System.
7%
6%
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Food Prices and Inflationin China and the U.S.
Are Following Similar PathsBy Maria A. Arias and Yi Wen
I N T E R N A T I O N A L T R A D E
Inflation, as measured by growth in theconsumer price index (CPI), has beenrelatively stable during the past two years
in both the U.S. and China. Both countries
also shared a period o price volatility in the
years beore and afer the Great Recession—
a time when commodity prices werefluctuating around the globe. Beore 2000,
however, prices in China and the U.S. did
not always behave similarly. (See Figure 1.)
Food prices, an important component
in the CPI, can help explain the relation-
ship between the two countries’ overall
price co-movements. Fluctuations in ood
prices in China started to become more
strongly correlated to those in the U.S. afer
China joined the World rade Organization
(WO) in 2001. Between 1994 and 2001, the
correlation1
was 41 percent; between 2002and 2013, it rose to 62 percent. (See Figure 2
and the table.)
But what drives the co-movement in ood
prices o the two countries? Are there expla-
nations other than this co-movement or
the increased synchronization o inflation
in China and the U.S.? Let’s look at some
possible answers to these questions.
World Food and Commodity Prices
Some people think that prices in general
and ood prices in particular are highly cor-related in the U.S. and China because both
sets o prices are affected by some world-
wide actors, such as movements in world
ood prices. Data show that this is true or
China, but not or the U.S.
China’s ood prices were strongly cor-
related with world ood prices between 2002
and 2013 (80 percent correlation), while U.S.
ood prices during the same period were not
that highly correlated to world ood prices
(34 percent). Similarly, Chinese ood prices
were strongly and significantly correlated
with the S&P Goldman Sachs CommodityIndex between 2002 and 2013 (49 percent),
while the correlation between U.S. ood
prices and the S&P GSCI was low (10 per-
cent) and not statistically significant.
Exchange Rates and Money Supply
Looking at ood prices rom a monetary
standpoint, another likely explanation could
be related to currency exchange rates. China
has a targeted floating exchange rate with
the dollar; so, higher money supply in the
U.S. should lead to higher money supply
in China. I this were true, CPI inflationin China and the U.S. should fluctuate in
similar patterns.2
Te data are not conclusive regarding this
explanation. Te correlation between CPI
inflation in the U.S. and China more than
doubled, rom 24 percent between 1994 and
2001 to 57 percent between 2002 and 2013.
But the correlation between M1 money sup-
ply in the U.S. and China is negative, and it
weakened rom –59 percent between 1994
FIGURE 1
CPI Inflation
SOURCES: Organization for Economic Cooperation and Development, Federal Reserve Economic Data (FRED).
1994 1996 1998 2000 2002 2004
United States
China
2006 2008 2010 2012
30
25
20
15
10
5
0
–5
P e r c e n t C h a n g e f r o m Y
e a r A g o
U.S. Recessions
China Joined WTO
FIGURE 2
Food Price Growth
SOURCES: Organization for Economic Cooperation and Development, Federal Reserve Economic Data (FRED).
1994 1996 1998 2000 2002 2004
U.S. Recessions
China Joined WTO
United StatesChina
2006 2008 2010 2012
45
35
25
15
5
–5
–15
P e r c e n t C h a n g e f r o m Y
e a r
A g o
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E N D N O T E S
1 Correlation is a measure o the statistical relation-
ship between two random variables. I they are
perectly synchronized in movements, the correla-
tion is 1; i they have no relationship or similaritie
at all, then the correlation is 0.
2 I the money supply in the U.S. increases, there
is more money chasing the same amount o
goods, putting upward pressure on U.S. prices.
Tereore, China’s money supply has to increase
in order to maintain the same exchange rate level,
which should also lead to higher prices in China.
Troughout this article, we use M1 money stock as
a measure o the money supply; M1 includes notes
and coins in circulation, traveler’s checks, demand
deposits and checkable deposits.
3 Even though U.S. ood prices are not as highly
correlated with international soybean prices, the
correlation strengthened in the period afer 20 02.
and 2001 to –28 percent between 2002 and
2013. Moreover, there has not been any sig-
nificant shif in monetary and exchange rate
policy toward closer policy coordination. I
anything, China has relaxed the yuan’s link
to the U.S. dollar in recent years.
Agricultural Trade Volumes
Given that the price correlations are
markedly stronger afer China joined the
WO, and since the other two possible
explanations are not very conclusive, the
structural change can likely be explained
by the strong increase in trade, particularly
agricultural trade, between China and the
U.S. From 1991 until 2001, when China
joined the WO, agricultural exports rom
the U.S. to China grew 168 percent and agri-
cultural imports grew 146 percent. During
the 10 years afer China joined the WO,
agricultural exports rom the U.S. to China
and imports rom China to the U.S. grew
874 percent and 388 percent, respectively.
(See Figure 3.)
In 2013 alone, about 18 percent o total
U.S. agricultural exports went to China
($25.9 bill ion), including $13.4 bill ion in
soybeans, $4.7 billion in grain and eed
cereal, $3.7 billion in livestock and ani-
mal products, and $2.2 billion in cotton.
However, only about 4 percent o U.S.
agricultural imports in 2013 came rom
China ($4.4 bil lion), including $1.7 billionin ruit and vegetable products, $0.6 billion
in livestock and animal products, and
$0.5 billion in grain and eed cereal, in addi-
tion to $2.7 bil lion o fish (which is consid-
ered a nonagricultural commodity).
Soybean trade is particularly interest-
ing. International prices or soybeans are
highly correlated with ood prices around
the world. Te correlations strengthened
afer 2002 or China, the U.S. and the entire
world.3 (See the table.) Since the early 2000s,
soybeans have accounted or 40 to 60 per-cent o U.S. agricultural exports to China,
peaking at 70 percent in 2009. Soybeans
drove most o the surge in agricultural trade
between both countries afer 2002.
Intersecting Needs
Agricultural trade between China and
the U.S.—the two largest economies in the
world—is substantial and has been increas-
ing rapidly and steadily, making not only
China’s ood prices sensitive to those in the
U.S., but also vice versa. Urbanization and
higher incomes have helped shif Chinese
people toward more protein-based diets,
thus ueling demand or eed cereal and live-
stock and putting upward pressure on U.S.
agricultural products. Te heavy reliance by
Americans on consumer goods rom China
may also make the U.S. cost o living sensi-
tive to that in China, and Chinese produc-
tion costs, especially wages, have been rising
rapidly in recent years. Such developments
can only imply stronger cross-country cor-
relations in ood prices and CPI inflation
between the two countries.
Yi Wen is an economist and Maria A. Arias is aresearch associate, both at the Federal ReserveBank of St. Louis. For more on Wen’s work, seehttp://research.stlouisfed.org/econ/wen.
FIGURE 3
Agricultural Trade between China and the U.S.
SOURCES: U.S. Census Bureau, U.S. Department of Agriculture Foreign Agricultural Service.
1 9 9 1
1 9 9 2
1 9 9 3
1 9 9 4
1 9 9 5
1 9 9 6
1 9 9 7
1 9 9 8
1 9 9 9
2 0 0 0
2 0 0 1
2 0 0 2
2 0 0 3
2 0 0 4
2 0 0 5
2 0 0 6
2 0 0 7
2 0 0 8
2 0 0 9
2 0 1 0
2 0 1 1
2 0 1 2
2 0 1 3
U.S. Recessions
China Joined WTO
Exports to China (Left Axis)
Imports from China (Right Axis)
30
25
20
15
10
5
0
B i l l i o n s
o f D o l l a r s
6
5
4
3
2
1
0
B i l l i o n s
o f D o l l a r s
Food Prices inU.S. and China
CPI in
U.S. and China
International Soybean Prices
U.S. Food Prices China Food Prices World Food Prices
1994-2001 0.41 0.24 0.25 0.14 0.45
2002-2013 0.62 0.57 0.38 0.65 0.76
Selected Correlations
SOURCES: Organization for Economic Cooperation and Development, International Monetary Fund, Food and Agriculture Organization of the United Nations,Federal Reserve Economic Data (FRED) and Haver Analytics.
NOTE: The first two columns in the table show the correlation in food price fluctuations, as well as that of CPI inflation, in both countries (columns) during therespective periods (rows). Likewise, the right-hand side of the table shows the correlation between international soybean prices and food prices in each of thethree regions during the respective periods. (See endnote 1 for an explanation of correlation.)
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Jackson experienced a manuacturingboom in the 1990s that set the stage oreconomic growth in the ollowing decade
and beyond. From 1990 to 2000, manu-
acturing employment in the two largest
counties in the area—Chester and Madi-son—increased by more than a third, even
as manuacturing employment nationwide
ell slightly. Both population and nonarm
payrolls in Jackson grew aster than the
national average during this period.
Jackson’s road and rail connections, as
well as its low rates o unionization and
numerous state and local incentives, made
it an attractive location or manuacturers;
Jackson’s position on Interstate 40 between
Memphis and Nashville gives local com-
panies access to the logistics and distribu-tion network in Memphis and the growing
markets and industrial base o the Nashville
area. While manuacturing is still vital to
Jackson’s economy, in recent years the city
has emerged as the center or services in this
otherwise rural area.
Te Jackson metropolitan statistical area
(MSA), which now includes Chester, Crock-
ett and Madison counties, has a population
o about 130,650 people and a labor orce o
about 63,190. Between 2000 and 2013, the
population o the MSA increased 7 per-
cent, slower than the growth rates in both
ennessee (13.9 percent) and the nation
(15.6 percent). Chester County, home to
13.3 percent o the MSA’s population, grewthe astest (11.6 percent), ollowed by Madi-
son County (7.2 percent), where the majority
o the Jackson-area population resides.
Crockett County registered growth o just
0.3 percent.
Te borders o Jackson’s MSA are in flux.
Last year, the U.S. Office o Management
and Budget added Crockett County to the
area based on its increasing economic ties
to Jackson. However, the Bureau o Labor
Statistics (BLS) has yet to make the change,
still considering the MSA to be made up o just Chester and Madison counties. Unless
otherwise indicated in this article, the use
o Jackson reers to the three-county area.
In 2013, Jackson’s gross metropolitan
product was $5.77 billion, about 8.5 percent
o the size o the nearby Memphis economy
and 5.7 percent o the size o the Nash-
ville economy. Per capita personal income
in Jackson grew 41.4 percent to $36,721
between 2002 and 2012, aster than the
37.6 percent growth rate or the nation.
Although per capita personal income in
Jackson is 16 percent lower than the national
average, the cost o living is 18 percent lower.
In Madison County, 23.8 percent o
those 25 and older hold a bachelor’s degreeor higher. In Chester and Crockett coun-
ties, 15.4 and 12.3 percent hold a bachelor’s
degree or higher, respectively. Te average
or the U.S. is 28.5 percent.
Economic Drivers
In 2000, manuacturing was the largest
sector (by employment) in Madison and
Chester counties, employing more than
20 percent o workers.1 oday, manuactur-
ing is the third-largest sector by employ-
ment in this area and makes up 13.3 percento total employment. (Still, the percentage
is higher than the nation’s 8.7 percent.)
Manuacturers Delta Faucet, Kellogg,
Pinnacle Foods, and Stanley Black and
Decker are among the 10 largest employers
in Madison County. Te area continues to
attract investment in manuacturing: Te
Jackson Chamber o Commerce reports that
there was more than $1 billion in industrial
investment between 2003 and 2013.
M E T R O P R O F I L E
ManufacturingShares the Stagewith Service Sectorsin Jackson, Tenn.
By James D. Eubanks and Charles S. Gascon
In western ennessee, the area around Jackson has leveraged
its manuacturing base to evolve into a center or services in
the largely rural stretch between Memphis and Nashville.
West Tennessee Healt
employs more than 5,0
PHOTO COURTESY OF WEST TENNESS
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Te education and health services sector
has become increasingly important to the
local economy. In late 2009, this sector
surpassed manuacturing to become the
largest private sector by employment in
Madison and Chester counties. Te major-
ity o employees in this sector work in
health care and social services. Jackson’s
health care providers have grown to serve
the entire region between Memphis and
Nashville: Te Jackson chamber reports
that more than 60 percent o the patients
at Jackson’s largest hospital are not rom
Madison County, where Jackson is the
county seat. Te largest employer by ar
in Madison County is West ennessee
Healthcare, which employs more than
5,000. Other top-10 employers in Madison
County include Union University and the
Regional Hospital o Jackson.
Although the rising importance oeducation and health care reflects Jack-
son’s emergence as the hub or services in
the area, it is also part o a national trend.
Between 2003 and 2013, the sector grew
28 percent in Jackson’s two largest counties
and 25.6 percent nationwide. Te sector
accounts or about the same share o
employment in the area (15.9 percent)
as in the U.S. (15.5 percent).
Meanwhile, the public sector has been
an important source o employment in
Jackson or decades. Government becamethe largest sector by employment in Mad-
ison and Chester counties in late 2003,
largely because o declines in manuact-
uring employment rather than increases
in government employment. At the start
o the recession in late 2007, government
employment was 12,300; in March 2014,
it was 12,700. Te majority o government
employees in the area work or local gov-
ernment. Tree o the 10 largest employers
in Madison County are in the public sector:
the city o Jackson, Madison County gov-
ernment and the Jackson-Madison County
School System. Te ennessee Supreme
Court’s courthouse or West ennessee is
also located in Jackson.
Current Conditions
At 7.8 percent in July 2014, the unem-
ployment rate in the three-county MSA
is higher than the nation’s (6.2) and en-
nessee’s (7.1). However, the rate has allen
more quickly in Jackson than in the nation
as a result o both increasing employmentand a declining labor orce. Between May
2013 and May 2014, Jackson’s rate declined
rom 8.9 percent to 7.0 percent, while the
U.S. rate declined rom 7.5 percent to
6.3 percent. Te unemployment rate in
Jackson increased during the summer as the
labor orce grew aster than employment.
Nonarm payrolls in Jackson’s two largest
counties grew much more quickly than the
national average rom October 2010 to Febru-
ary 2013. Most jobs added during this time
were in the proessional and business servicessector. Te education and health services
sector also steadily added jobs during this
time, as did the wholesale trade sector. Later
Jackson, Tenn.
Population 130,645
Labor Force 63,190
Unemployment Rate 7.8%
Personal Income (per capita) $36,721
Gross Metropolitan Product $5.77 billion
MSA Snapshot
LARGEST LOCAL EMPLOYERS
1. West Tennessee Healthcare 5,368
2. Jackson-Madison County School System 2,019
3. Delta Faucet 880
4. Union University 835
5. Kellogg 735
Retail Trade Manufacturing
Wholesale Trade
Other Services and
Information
Professional and
Business Services
Financial Activities 3%Construction, Natural
Resources and Mining
Leisure and
Hospitality Education and
Health Services
Government
10%
13%
16%
20%5%
5%
9%
12%
4%
Transport, Warehousing
and Utilities 3%
NONFARM EMPLOYMENT BY SECTOR
For a long time, manufacturing drove the economy of the Jackson area, thanks to the area’sroad and rail connections, low rates of unionization, and numerous state and local incentives.The sector is still important, what with major employers such as Delta Faucet, Kellogg, PinnacleFoods, and Stanley Black and Decker, and productivity is still rising. However, employment inthis sector is declining.
Today, more people in the area work in service sectors than in manufacturing. The governmentsector is No. 1 in employment, largely because of declines in manufacturing employment ratherthan increases in government workers. The majority of these employees work for local governmentincluding the city of Jackson, Madison County and the Jackson-Madison County School System.The private sector that employs the most is education and health services.
PHOTO COURTESY OF DELTA FAUCET PHOTO COURTESY OF TENNESSEE COURT
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2004 2006 2008 2010 2012 2014
101
100
99
98
97
96
9594
93
92
91
Jackson
U.S.
Tennessee I n d e x ,
D e c e m b e r 2 0 0 7 =
1 0 0
July
FIGURE 3
Nonfarm Payrolls
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
160
150
140
130
120
110
100
90
80
70
60
Real Manufacturing Output
Manufacturing Employment
Output per Employee
I n d e x ,
2 0 0 1 =
1 0 0
FIGURE 4
Jackson Manufacturing Productivity
NOTE: Real manufacturing output is the dollar value of manufacturing output in inflation-adjusted terms. Output per employee is real manufacturing outputdivided by the number of employees in manufacturing.
To see these charts with the latest data, as well as to see other data on the Jackson MSA, check out our data dashboard at
http://research.stlouisfed.org/dashboard/872. In each of the four charts above, the gray bars represent recessions. The Bureau
of Labor Statistics was a source for data in all four charts; in addition, Figure 4 used data from the Bureau of Economic Analysis.Employment data from the BLS Establishment Survey do not cover Crockett County.
in 2013, nonarm payroll growth slowed to the
national rate and has since dropped below that
rate. otal employment has not quite recov-
ered to its prerecession peak: In July 2014, tota
nonarm employment was 0.3 percent below
its level in December 2007.
Manuacturing employment in Chester
and Madison counties has declined in year-
over-year terms or the past six years. Tis
mirrors the national trend. Te declines in
manuacturing employment could partly be
a result o increases in efficiency: Jackson’s
manuacturing output in real terms in
2012 was only 2.4 percent below its level in
2001, when manuacturing employment
in Jackson was near its peak. Although
manuacturing employment has decreased
significantly, Jackson continues to attract
industrial businesses. According to figures
rom the Jackson chamber, new investment
rom existing industry in 2012 was aboveits 2003-2012 average. wo manuacturing
companies have recently announced plans
to expand or open new acilities in Jack-
son. Still, total business investment, which
includes investment by newly recruited
companies, has allen over the past decade.
Te education and health services sector
experienced sustained growth between 2010
and 2012, but this growth has since slowed
considerably. West ennessee Healthcare
has announced plans to cut positions, offer
early retirement packages to hundreds oemployees and reduce paid time off.
Going Forward
Te diversification o Jackson’s economy
since 2000 has positioned it or moderate
growth over the next 10 years, with the
majority o employment growth likely to
come rom service industries.
Employment in Jackson’s second-largest
sector, education and health services, is
expected to continue to grow nationally.
Te Bureau o Labor Statistics projectseducation services employment to grow by
1.9 percent and health care and social assis-
tance employment to grow by 2.6 percent
rom 2012 to 2022. Over the past decade,
Jackson’s growth in these sectors has been
consistently higher than national growth. I
this trend continues, these sectors will pro-
vide many o the new jobs in Jackson over
the next 10 years.
FIGURE 1
Manufacturing Employment
1990 1995 2000 2005 2010
150
140
130
120
110
100
90
80
70
60
50
JacksonU.S.
Tennessee I n d e x , J a n u a r y 1 9 9 0 =
1 0 0
July 2014
1990 1995 2000 2005 2010
26
24
22
20
18
16
14
12
10
8
Manufacturing
Education and Health Services P e r c e n t o f T o t
a l J a c k s o n E m p l o y m e n t
Government
July 2014
FIGURE 2
Jackson Employment Shares
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Eleven more charts are available on the web version of this issue. Among the areas they cover are agriculture, commercialbanking, housing permits, income and jobs. Much of the data are specific to the Eighth District. To see these charts, go towww.stlouisfed.org/economyataglance.
U . S . A G R I C U L T U R A L T R A D E AVERAGE LAND VALUES ACROSS THE EIGHTH DISTRICT
’09 ’10 ’11 ’12 ’13 ’14
90
75
60
45
30
15
0
NOTE: Data are aggregated over the past 12 months.
Exports
Imports
JulyTrade Balance
B I L L I O N S
O F
D O L L A R S
2013:Q2 2013:Q3 2013:Q4 2014:Q1 2014:Q2
7,000
6,000
5,000
4,000
3,000
2,000
1,000
0
D O L L A R S
P E R
A C R E
Quality Farmland Ranchland or Pastureland
SOURCE: Agricultural Finance Monitor .
C I V I L I A N U N E M P L O Y M E N T R A T E I N T E R E S T R AT E S
’09 ’10 ’11 ’12 ’13 ’14
11
10
9
8
7
6
5
4
P E R C E N T
September
’09 ’10 ’11 ’12 ’13 ’14
4
3
2
1
0
10-Year Treasury
Fed Funds Target
August1-Year Treasury
P E R C E N T
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).
I N F L A T I O N - I N D E X E D T R E A S U R Y Y I E L D S P R E A D S R AT ES ON FE DE RA L F UN DS FU TU RE S O N S EL EC TE D D AT ES
3.00
2.75
2.50
2.25
2.00
1.75
1.50
1.25
1.00
NOTE: Weekly data.
5-Year
10-Year
20-Year
P E R C E N T
Sept. 26
’10 ’11 ’12 ’13 ’14 1st-ExpiringContract
3-Month 6-Month 12-Month
0.50
0.45
0.40
0.35
0.30
0.25
0.20
0.15
0.10
0.05
0.00
CONTRACT SETTLEMENT MONTH
P E