regional economist - oct. 2014

8/9/2019 Regional Economist - Oct. 2014

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l a r

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?


2/24

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

[email protected].

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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338 9PremiumPlus

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R eg u la r

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


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.

2 The Regional Economist | October 2014


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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 )

The Regional Economist | www.stlouisfed.org 3


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Why Don’t Gasoline Pric

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5/24

By Michael Owyang and E. Katarina Vermann


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.stlouisfed.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



10/24

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.



11/24

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/bandyopadhyay.

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



12/24

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



13/24

FIGURE 3

Components of Credit Market Liabilities, by Instruments, 2013


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.


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


7%

6%



14/24

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



15/24

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.)



16/24

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



17/24

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



18/24

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



19/24

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

regional economist - oct. 2014

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