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FEDERAL
FEDERAL RESERVE
RESERVE BANK OF
QFDALLAS
DALLAS
FIRST
FIRST QUARTER
QUARTER 1995
1995

Sticky Prices:
What Is the Evidence?
Evldenca?
Mark A. Wynne

The
Tha Texas Banking Crisis
And the Payments
PaymelllS System
Robert T
T. Clair, Joanna
joanna O.
O. Ko/son,
}(dgJn,
and Kenneth
fnmelbj.J Robinson

The Role of Merchandise
Exports to Mexico
in the
Maxlco In
Pattern of Texas Employment
Kelly
George and Lori L.
Ke/JyAA.. Gtorgeand
l. Taylor
Tayler

Year
Another Strong Yaar
Eleventh District
For the Elavaath
Fiona D. Sigaflti
Sigalla
Fwno

This publication was digitized and made available by the Federal Reserve Bank of Dallas' Historical Library (FedHistory@dal.frb.org)

Economic Review
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Robert W Gilmer

William C. Gruben
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Robert T Clair
Kooootll M 00y
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Kelly A Georoe

David M Gould
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Mille K Voce!

carlOs E. Zarazaliil

R....n:II Aslocll'"
Professor Nathan S. Balke
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Contents
The Role of Merchandise
Exports to Mexico in the
Pattern of Texas Employment
Kelly A. George and Lori L. Taylor

Page 22

Another Strong Year
For the Eleventh District
Fiona D. Sigalla

Page 31

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6<;;906. Dallas. TX 7526S-'i')(X\ or hy call in).: (214) 922-5257
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In 1987, Texas exported $25 billion worth of
Illt!rchandise TO foreign countries. Twenty-six percent,

or S6.5 billion. of those exports went south to Mexico.
By 1994, Texas merchandise exporls to Mexico had
grmvn to more than SI8.; oillion per year (in 1987
constant dolhrs). Texas merchandise exports to Mexico
(in real terms) have grown more than 10 percent a year
for six of the last seven years.
Using input-output analYSis, Kelly George and
l.ori Taylor find that merchandise exports to Mexico,
while representing only about ; per~cnt of Texas
output, have grown in ways that h,lve substantially
influenced the composition of the state's economy. The
authors auribute a small portion of the st,ne's overall job
gains since 1987 to rising merchandise exports to
Mexico but find that almost all Texas employment
growth in high-tech manufacturing sectors stems from
Wide with Mexico.

The Eleventh District marked its eighth year of
economic expansion in 1994. Employment grew strongly
in :111 three Eleventh District .'>t:ttes - I.ouisiana, New
Mexico. and Texas. Although the past prominence of the
oil and g:.ls sector is well-known, in 1994 the region
prospered despite continued declines in the energy
industry A robust U.s. economy stimulated demand for
District manufacturing and service industries, which
helped drive the economy.
Fiona Sig:llla surveys the 1994 performance of the
Eleventh District economy and finds that a favorable
business climate and expanding trJ<.ie in goods and
services to Mexico helped the Elevcnth District grow
fastcr than the nation. While slower CLonomic growth in
tht.: United States and lInLertainty in Mex icowill be dmgs
on the District economy in the year ahead, 1995 should
Ix· another good year for District states.

Contents
Sticky Prices:
What Is the Evidence?
Mark A. Wynne
Page

The Texas Banking Crisis
And the Payments System
Robert T. Clair, Joanna O. Kolson,
and Kenneth J. Robinson

Page 13

This article reviews the idea that stic ky prices a re
important for under..1anding business cycles. Mark Wynne
begins with a critical survey of the literature docume nt4
ing the stylized facts about prices in individual markets.
His first point is that there is remarkably little evidence
that the actual transactions prices of most prodUc.1s are,
in fact, sticky. Such evidence as there is to support the
notion of widespread price stickiness is heavily biased
toward low-tech products that account for a very small
fraction of total o utput and is a thin reed on which to
base a theory of business fl uctuations. Furthennore, the
observation that posted prices do not c hange vety
frequently cannot always be interpreted as evidence that
markel<; are not clearing. There is some evidence to
suggest that frequently firms alter product characteristics
other than price to allocate goods and services, and that
these changes in product characteristics are unobserved.
In view of the difficulty in interpreting whether
prices arc at other than market-clearing values, Wynne
argues that the only true test of a model in which price
stickiness plays a major role in explaining business
cycles is to look at how well it explains the cycl ical
phenomena it is supposed to explain. One s imple test of
a model along these lines consists of looking at the
various correlations generated by the model and comparing them with the data. Wynne reviews some recent
attempts along these lines and concludes that, while
there may be some role for price stickiness in explaining
business cycles in the u.s. economy, the case remains
unproven.

The federal Reserve System plays a crucial role in
the payments system that is especially important during
periods of financial turmoil. In this a rticle, Robert Clair,
Joanna Kolson, and Kenneth Robinson explain the
process and the risks involved in clearing checks in the
private sector. They compare these processes and risks
with the essentially risk-free check-clearing service the
Federal Reserve System offers. During banking crises,
they hypothesize, banks will increase their checkclearing through the Federal Reserve to minimize their
risk exposure. A model of Federal Reserve checkclearing volume is constructed and estimated. The
empirical results show that during banking crises, Fedeml Reserve check-processing volume rises as banks
seek safer method.:; of clearing checks. Conseque ntly,
Fedeml Reserve.: payment services are important tools in
minimizing the disruptive effects of banking crises on
the economy.

Sticky Prices:
What Is the
Evidence?

One of the most important questions in
economics concerns whether and how changes
in the stock of money affect the levels of output
and employment. More specifically, how can
changes in the stock of a nominal quantity,
such as the number of dollar bills outstanding,
affect the level of a real quantity, such as the
total amount of goods and services produced
in any given year or the number of workers to
be employed in the production of that output?
Given that the Federal Reserve’s primary means
of influencing the pace of economic activity in
the United States is through changes in the
stock of money, the question is of immediate
importance for the conduct of monetary policy.1
Yet despite the importance of this question, it
remains one of the great unsettled issues in
economics. After nearly two hundred years of
theorizing, we still do not have a very clear
understanding of the mechanism whereby
changes in the stock of money affect the
economy in the short run. This article reviews
one of the most popular explanations for why
money affects output. This is the idea that
prices are “sticky” at nonmarket-clearing levels, thus creating the potential for changes in
the money stock to influence the real economy.
The intuition for why changes in the
nominal money stock can affect real output in
a sticky-price environment is straightforward.
Consider a situation in which the economy is in
a state of monetary equilibrium. All individuals
are holding their desired levels of cash balances, which typically might be expressed in
terms of some number of weeks of income.
Individuals have arrived at these holdings by
trading off their need for cash to facilitate
transactions with the cost of holding cash
rather than some higher yielding asset. Absent
any change in individuals’ need to finance
transactions or the relative return on cash
versus other assets, they will be willing to hold
their existing stocks of cash indefinitely.
Suppose now that the monetary authority
engineers an increase in the money stock such
that each individual’s cash holdings increase by
exactly 10 percent. Suppose also that the increase
is a one-time occurrence, in the sense that it is
unanticipated and will not be repeated. One way
this might occur would be by means of the
metaphorical helicopter drop employed by Milton
Friedman in his analyses of the effects on real
activity of changes in the stock of money.2 On
average, individuals will now find themselves
holding a larger stock of cash than before. Since
their previous level of cash holdings was optimal,
given their transactions needs and the costs of

Mark A. Wynne
Senior Economist and Policy Advisor
Federal Reserve Bank of Dallas

fter nearly two hundred years

of theorizing, we still do not have a
very clear understanding of the
mechanism whereby changes in the
stock of money affect the economy
in the short run. This article reviews
one of the most popular explanations
for why money affects output.
This is the idea that prices are
“sticky” at nonmarket-clearing
levels, thus creating the potential for
changes in the money stock to
influence the real economy.

FEDERAL RESERVE BANK OF DALLAS

ECONOMIC REVIEW FIRST QUARTER 1995

The facts about price stickiness

holding cash, and since nothing has changed to
alter these determinants of their cash holdings,
individuals, on average, now hold more than their
desired stock of cash. To return to their original
level of money holdings, the individuals will
increase their spending until their cash balances
are back at their original level. However, if all
individuals are simultaneously trying to spend
down their cash balances, and nothing has happened to make people willing to produce more,
the result will be upward pressure on prices. In
the long run, equilibrium will be restored when
the prices of all goods rise in the same proportion
as the initial increase in the money stock.
The more difficult question is what happens during the transition to the new equilibrium.
If the prices of all goods and services increased
immediately in the same proportion as the money
stock, the adjustment would be completed instantaneously and that would be the end of the story.
However, if (for whatever reason) some producers are slow to adjust their prices in the face of the
increase in nominal demand and choose instead
to increase output, we might see an increase in
output during the transition period. This failure to
adjust prices immediately may come about for a
variety of reasons, including, for example, a
misinterpretation on the part of some firms of the
increased demand for their product or the existence of some menu cost associated with changing
prices. Whatever the reason, the failure of prices
to adjust rapidly generates the potential for changes
in the nominal stock of money to affect real
output.
The focus in this article will be on price
stickiness or rigidity rather than wage stickiness.
Sticky prices or wages are both potential sources
of nonneutralities of money, and both may play a
role in propagating nominal shocks. However,
most economists are skeptical of interpretations
that view the failure of nominal weekly or monthly
wage payments to fluctuate with business conditions as evidence of stickiness. A better interpretation, many argue, is that periodic wage payments
are installment payments on a long-term labor
contract (either implicit or explicit) and thus play
relatively little allocative role (see, for example,
Barro 1977). Incentives other than the promise of
higher wages induce workers to work harder
during booms; one example might be the implicit
promise of being allowed to slack off when things
are quieter. Other reasons for being skeptical
about the importance of wage rigidity as a propagation mechanism are recent evidence that wages
are, in fact, remarkably flexible, and the
counterfactual implications of theories with wage
stickiness at their core.3

A common criticism of the raw data used to
construct the widely used consumer and producer price indexes is that the prices that go into
these indexes are list rather than transactions
prices. That is, the raw price series do not reflect
the prices at which actual transactions take place
but rather some irrelevant list price at which
relatively few transactions occur. Wynne and
Sigalla (1993) review some of the evidence on this
problem. The list-transactions problem takes many
forms, depending on whether the prices in question are for intermediate or final goods. Firms may
be reluctant to report actual transactions prices to
the industrial price program that gathers data for
the producer price index (PPI) because of fears
the data may be used in antitrust litigation or fall
into the hands of competitors.4 Thus, some have
argued that price data should be collected from
buyers rather than sellers.
This approach is nearly what is done in the
data collection of prices for the consumer price
index (CPI). Bureau of Labor Statistics (BLS)
reporters visit a variety of stores and collect data
on the various products that are to be priced for
the CPI. The reporters make adjustments to these
products for some but not all discounts. Thus,
when pricing automobiles, the BLS collects the
car’s sticker price; the average discount offered
over the recent past; and the prices for standard
options, dealer preparation, and delivery to get a
measure of car prices that better approximates the
prices the average consumer actually pays. One
form of discounting that is not taken into account
in collecting data for the CPI involves cents-off
coupons. The BLS only discounts products for
those coupons attached to products for redemption at the time of sale. Clearly, the use of coupons
could imply greater price flexibility than is revealed in examinations of the official price statistics, but by how much is uncertain. It is clear,
however, that coupon use varies with the state of
economic activity.
One other aspect of the official price indexes makes them unsuitable for assessing the
overall degree of flexibility of the price of a
product. That is, for a variety of reasons, the prices
that go onto the official indexes are usually
averages of prices obtained from different outlets
or firms. Such averages can fluctuate either more
or less than their constituent price series, making
them unreliable guides to the overall flexibility of
prices. Despite these shortcomings of official
price statistics, the first study I review (Mills 1927)
is based on an analysis of raw BLS data. The
review of the literature begins with this study
because, despite some serious shortcomings, it

Figure 1

Distribution of 206 Commodities
(Classified by Frequency of Monthly Price Changes )
Value
1890–1897

1898–1905

30
30

20
20

.00 to .11 to .21 to .31 to .41 to .51 to .61 to .71 to .81 to .91 to
.10
.20
.30
.40
.50
.60
.70
.80
.90
1.00

1906–1913

1914–1921

40
30
30
20
20
10

10
0

0
.00 to .11 to .21 to .31 to .41 to .51 to .61 to .71 to .81 to .91 to
.10
.20
.30
.40
.50
.60
.70
.80
.90
1.00

.00 to .11 to .21 to .31 to .41 to .51 to .61 to .71 to .81 to .91 to
.10
.20
.30
.40
.50
.60
.70
.80
.90
1.00

1922–1925

1890–1925 (excluding 1914–1921)

50
40

20
10

.00 to .11 to .21 to .31 to .41 to .51 to .61 to .71 to .81 to .91 to
.10
.20
.30
.40
.50
.60
.70
.80
.90
1.00

Frequency

remains one of the most comprehensive assessments of price flexibility, and it also establishes
certain results about the frequency of price changes
that later studies confirm.

in 119 of those months the price changed, then
the index would take on a value of one (119/119).
Alternatively, if there were no price changes over
the ten-year period, the index would take on a
value of zero (0/119). Mills constructs this measure for each of the 206 commodities in his data
set for six different periods. The resulting class
frequencies are plotted in Figure 1. The value of
Mills’ index is plotted in interval increments on the
horizontal axis, while the frequency of each
interval value is plotted on the vertical axis. If
every product in the sample exhibited a price
change in every month of a particular sample
period, the rightmost bar on the graph would
equal 206 (the number of commodities in the
sample), with zeros elsewhere. Likewise, if no
commodity exhibited a price change during any
month of the sample, all the mass of the distribu-

The behavior of wholesale
prices, 1890–1924
The earliest study of the frequency of price
changes for individual products is probably Mills
(1927). Mills studied data collected by the BLS for
the purposes of constructing the wholesale price
index (WPI) and constructed a measure of the
frequency of price changes for an individual
commodity by dividing the number of months in
which a change in price is recorded by the total
number of months for which a price is quoted,
less one. Thus, if we have price data for, say,
wheat for a ten-year period (120 months), and if

FEDERAL RESERVE BANK OF DALLAS

ECONOMIC REVIEW FIRST QUARTER 1995

tion would be concentrated in the leftmost bar on
the graph, with zeros everywhere else.
The most striking feature of these graphs is
the uniformity of the U-shaped distribution of
price changes. That is, there are a lot of products
for which prices change relatively infrequently,
and there are a lot of products for which prices
change frequently. Perhaps not surprisingly, the
only products with an index value of one in all the
sample periods are farm products (hogs and
sheep). For a lot of other products, prices change
almost every month (that is, index values for these
products are close to one). Another point to note
about Figure 1 is how the distribution of price
changes shifted during the period including the
years of World War I (1914 –21).
While Mills’ results are of great interest,
there are at least two important problems with the
data he uses. First, despite his claims that the data
are not averages, it is not clear that this is the case.
Examination of Table 1 of the appendix to his
book reveals many commodities for which it
seems likely that the data used are, in fact,
averages over several price quotations. The second problem is that data collected for the BLS’s
industrial price program have often been criticized as reflecting list prices rather than transactions prices. Both the Stigler report (NBER 1961)
and the Ruggles report (U.S. Executive Office of
the President: Council on Wage and Price Stability
1977) make this point forcefully. Finally, some of
the criticisms of later studies that will be noted
below are probably also applicable to Mills’ study.
Specifically, adjustment for quality change was
essentially nonexistent in the early years of the
BLS, which raises the possibility that some of the
price stickiness found by Mills may have been
accompanied by quality deteriorations.
The newsstand prices of magazines. Cecchetti’s
(1986) study of the newsstand prices of magazines is probably the most widely cited and
influential piece of evidence that prices are sticky.
Cecchetti looked at the prices of thirty-eight
magazines over the period 1953 to 1979. One
virtue of this data set is that the prices are known
to be transactions prices rather that just list prices.
The use of discounts for newsstand magazine
purchases is rare.5 The main stylized facts about
price stickiness presented by Cecchetti are shown
in Figure 2. Two points are noteworthy. First, the
prices of the magazines in the sample change
relatively infrequently. At most, only half the
magazines in the sample change price in any one
year (the peak year being 1974). Second, note the
increased frequency of price changes and decline
in the average number of years since the last price
change as inflation accelerated in the late 1970s.

Figure 2

Magazine Price Changes, 1953–79
Number of magazines

Average number of years

20
18

14
Average number of years
since last change

16
10

14
12

10
6

8
6

4
2

Number of magazines
changing prices

2
0

’53 ’55 ’57 ’59 ’61 ’63 ’65 ’67 ’69 ’71 ’73 ’75 ’77 ’79

Cecchetti also observes that the average decline in
real price between nominal price changes increased dramatically during the 1970s. He interprets this as evidence of “incredible” price
stickiness, which can only be explained by high
fixed costs of price changes.
Nevertheless, the Cecchetti study raises
numerous questions that undermine the broader
inferences that can be drawn from it. For a start,
one has to note the small size of the sample of
prices studied. Cecchetti himself concedes that a
mere one-third of all magazine sales in his sample
are single-copy (newsstand) sales. Most people
buy magazines through subscriptions. What do
we know about the prices of magazines purchased through subscriptions? Obviously, when
one enters a subscription for a magazine, one
obtains (typically) a year’s worth of issues of the
magazine at some fixed average price over the
period of the subscription. Yet frequently magazines offer various discounts for subscribing,
either in the form of “professional courtesy”
discounts or reduced rates for longer subscription
periods.6
A potentially more serious shortcoming of
the Cecchetti study is the absence of any control
for quality. In view of Blinder’s recent survey
findings (discussed below), one wonders whether
magazine publishers effectively raise the price of
their magazines by changing such aspects of
product quality as the publication’s size, the ratio
of advertising to nonadvertising pages, or the
number of color versus black-and-white pages.
Are stockouts at newsstands more common as the
real price of magazines declines with rising inflation? 7
This is essentially the point Koelln and Rush
(1993) make. Echoing an earlier argument by
Carlton (1983), Koelln and Rush note that magazine publishers may alter some aspect of their

product’s quality to adjust the effective price
during the period between nominal price changes.
Koelln and Rush specifically identify the possibility of altering the number of pages of text as a
potential means of offsetting declines in real price
during the interval between price changes. Koelln
and Rush look at “net page” and price data over
the 1950–89 period for seven magazines (five of
which were included in Cecchetti’s sample). The
authors note that the magazine with the most
inflexible size over this period also had by far
the largest number of nominal price changes.
They interpret this observation as supporting the
hypothesis that variation in quality (magazine
size, in this case) is a potentially important alternative to variation in price. Koelln and Rush also
find a statistically significant (positive) relationship between the number of text pages in a
magazine and the real price of the magazine. That
is, as inflation erodes the real price of a magazine
during the interval between nominal price changes,
the number of text pages tends to decline. Koelln
and Rush conclude that the price rigidity Cecchetti’s
study uncovered is significantly overstated.8
A third potential objection to Cecchetti’s
findings has to do with potential sample selection
bias. Since the primary objective of Cecchetti’s
study was to investigate the determinants of the
frequency of nominal prices changes, he explicitly chose to study prices that were not determined in auction markets but rather were known
a priori to remain fixed for relatively long periods.
Thus, Cecchetti (1986, 256) notes that the newsstand prices of magazines “exhibit the desired
property of discrete and infrequent adjustment”
(emphasis added). This, of course, raises the
question of how representative the sample of
prices Cecchetti examined is of all prices in the
economy.
The prices of industrial commodities. Carlton (1986)
revisits the data collected by Stigler and Kindahl
(1970) in their monumental study of the behavior
of industrial prices. Part of the objective of the
Stigler –Kindahl study is to collect accurate data
on transactions rather than list prices for industrial
commodities. As noted above, it has long been
suspected that the aggregate price indexes the
BLS publishes are based on list rather than transactions prices. To get around the list–transactions
price problem, Stigler and Kindahl collect data
from buyers rather than sellers, the presumption
being that buyers have less of an incentive to
report list rather than transactions prices than do
sellers.9 Stigler and Kindahl also make corrections
for discounting and for changes in product specification. Their sample period is January 1, 1957,
through December 31, 1966.

FEDERAL RESERVE BANK OF DALLAS

The commodities for which price data were
collected were intermediate products used in
manufacturing and were preselected to satisfy
two important criteria. First, Stigler and Kindahl
focus on the prices of those commodities “for
which the charge of inflexible prices has been
heard most frequently” (Stigler and Kindahl 1970,
23). The reason for this focus is the authors’
interest in testing certain theories of administered
prices. Thus, the prices they collected were
preselected to exhibit some degree of price rigidity. Stigler and Kindahl’s second criterion for price
data is the absence of rapid quality change in the
products, which helps avoid the difficulty of
disentangling quality from price changes. Stigler
and Kindahl note that “the problem of measuring
change in the quality of products is the major
unresolved task of all price collection” (Stigler and
Kindahl 1970, 23), and this remains as true today
as it was when they wrote their book twenty-five
years ago.
Carlton concludes on the basis of his analysis of the Stigler –Kindahl data that there is significant price rigidity in many industries. For industries
like steel, chemicals, and cement, Carlton finds
that prices are, on average, unchanged for more
than one year. Furthermore, there is a positive
correlation between price rigidity and the size of
price changes. In other words, the longer prices
are rigid, the greater the eventual price change.
But just as there are many examples of products
and transactions for which prices remain fixed for
long periods, so too are there many instances of
small price changes (meaning a change of less
than 1 percent). This observation suggests that
either the costs of changing price are very small
or that the costs of being at the wrong price are
very high. With either explanation, the observation of long periods of price rigidity is difficult to
explain. Interestingly, Carlton finds a negative
relationship between price rigidity and the length
of association between buyers and sellers, making an installment payment interpretation of the
observed price rigidity implausible. Finally, Carlton
finds no evidence that prices downward are more
rigid than upward.
Of all the studies of price flexibility, the
Carlton–Stigler –Kindahl study is the most comprehensive in that it looks at the prices of the
largest number of products. Nevertheless, the
findings need to be interpreted with caution. As
noted, Stigler and Kindahl’s preselection criteria
make the prices of the products they study
unrepresentative of prices of all products. Another point to note about Carlton’s results is that
during the period covered by his data, WPI
inflation averaged only 1.1 percent a year.10 It

ECONOMIC REVIEW FIRST QUARTER 1995

would be interesting to have a study as comprehensive as the Stigler –Kindahl exercise repeated
for a period of higher inflation.
Prices in retail catalogs. The most recent study
documenting the behavior of transactions prices
is Kashyap (1991). Kashyap looks at the behavior
of the transactions prices of twelve retail goods
over the period 1953 to 1987 from the retail
catalogs of three firms: L. L. Bean, Inc.; The Orvis
Company, Inc.; and Recreational Equipment, Inc.
(REI). Kashyap sidesteps the problem of dealing
with quality change by looking only at the prices
of products that are homogeneous over long
periods. The specific products are a pair of
hunting boots, pair of moccasins, chamois shirt,
blanket, and duffel bag from L. L. Bean; a bamboo
fly rod, fly, poplin fishing hat, pair of binoculars,
chamois shirt, and blanket from Orvis; and a
chamois shirt from REI. All three of the companies
in the study fix their prices for six-month intervals, implying that there are at most two price
changes that can be observed each year. Kashyap
collected data by copying prices from old catalogs. Prices are list prices for one unit of an item:
no account is taken of discounts for bulk purchases that each company has occasionally
offered. Kashyap provides no data on the size
of these discounts (he simply asserts that they
are “very slight”) or on their frequency. He also
ignores “sales prices which may have been
available for very short periods” (Kashyap 1991,
6 –7).11 One key advantage of Kashyap’s data over
that analyzed by Cecchetti is that the goods are
high-volume goods for which even small changes
in price produce nontrivial changes in revenue.
By contrast, subscriptions and advertising are far
more important sources of revenue for magazine
publishers than are newsstand sales.
Kashyap draws three main conclusions from
his empirical analysis:

keep the size of the change in each direction fixed
are rejected by the finding that the size of price
changes, when they do occur, is highly variable.
Furthermore, the absence of any correlation between the average size of price changes and the
(core) rate of inflation poses serious problems for
simple tractable versions of (S,s) models.12
Kashyap addresses the possibility that catalog prices might be suspected of being artificially
sticky by citing Rees’ (1961) finding that catalog
prices tend to closely track prices in retail outlets.
However, Rees (1961, 138) explicitly notes the
following:
There is a problem in the determination of the period during which catalog
prices are in effect. Special sales and in some
cases price increases may be announced
shortly after catalogs are issued, and we
have no collection of such announcements.
Changes in the proportion of all sales made
through special sales catalogs and changes
in the difference between general catalog
and sales catalog prices could introduce
bias into our indexes.

Furthermore, the sample of products Rees examined was in no sense random. Specifically, the
sample of goods Rees looked at was a judgment
sample of nondurable goods, although he made
a deliberate effort to include both goods that were
little influenced by innovation or technical change
over the sample period and goods that were
subject to significant quality changes. It would be
interesting to know whether today, with the
growth of catalog shopping, Rees’ results still hold
up. The problem remains that the products Rees
looked at are not in any sense representative of
the wide range of products consumers typically
buy. As for the possibility of changes in delivery
lags as prices become more out of line, Kashyap
asserts that since most of the products in his
sample are popular and have been carried by the
different retailers for long periods, the retailers
have a good sense of what demand for the
products looks like, thus rendering stockouts less
common.
Evidence from interviews. Blinder (1991) proposed interviewing actual price setters in business
firms to gain insights into the factors that underlie
decisions to change prices. The primary objective
of Blinder’s study was to find evidence that would
allow us to discriminate between competing
theories of price stickiness, rather than document
how frequently the firms in his sample changed
their prices. Blinder notes that testing the notion
that prices are sticky is probably impossible, as

1. Nominal prices are typically fixed for
periods longer than one year, and the
time between price changes is very
irregular.
2. Prices change more often during periods
of high inflation but not by larger amounts
than during periods of low inflation.
3. When prices do change, the sizes of the
changes are widely dispersed.
Kashyap notes that his data strongly contradict simple versions of (S,s) pricing models. For
example, the simple versions of these models that
assume that price changes should always be in
one direction are rejected by the frequency of
price reductions. Two-sided (S,s) models that

price stickiness usually means nothing more than
that prices change less rapidly than their unobservable Walrasian market-clearing values. While
Blinder does not report raw data on price changes
for the firms in his survey, he does report two
findings relevant to this survey of the literature.
First, most firms in Blinder’s sample (55 percent)
claim to change their prices no more than once a
year, with only 10 percent of companies changing
price as often as once a month. Blinder interprets
this observation as evidence of significant price
rigidity. Of even more importance in the interpretation of this result is the finding that three-fourths
of the sample firms, when asked to rank the
underlying factors in their decision not to change
prices when demand is high or low, said they
changed some other aspect or quality of their
product instead. Specifically, 76 percent of the
firms in the sample accepted the notion that
delivery lags could be lengthened or quality of
auxiliary service reduced as alternatives to raising
prices when demand is tight.13 These findings
echo Carlton’s earlier hypothesis that price may
be only one of several mechanisms firms use to
allocate output and raise serious questions about
the interpretation of observed nominal rigidities.

cuts) and that experience suggests these are the
goods for which prices are most sticky.
The third observation about the evidence is
that, in many cases, the sample of prices studied
is biased toward the inclusion of prices that were
known a priori to be relatively inflexible. Thus,
Cecchetti was primarily interested in estimating
models of price adjustment rather than documenting facts about price changes when he
compiled his data on the newsstand prices of
magazines. Likewise, Stigler and Kindahl were
primarily interested in testing theories of administered pricing (and thus biased their sample
toward products for which administered [or rigid]
prices were thought to be particularly prevalent)
when they assembled the price data later analyzed by Carlton (1986). Finally, despite Kashyap’s
citing earlier work by Rees (1961) that found that
prices in catalogs tend to mimic prices at retail
outlets remarkably well, the fact remains that
there is potentially a lot more flexibility in catalog
prices than Kashyap documented.15
Another way in which the prices documented as being relatively sticky fail to represent
all products is the homogeneity of the documented products over time. Because of the difficulty of separating price changes due to changes
in the quality of a product from pure price
changes, most of the studies focus only on
products for which this is not likely to be a
problem. Thus, the Stigler –Kindahl data set contains a lot of low-tech products like steel and
lumber, and Kashyap focuses on consumer goods
like shirts and shoes that exhibit little or no quality
changes over time. But the fact remains that many
high-tech products have remarkably flexible prices.
Would anyone seriously suggest that the appropriate (quality-adjusted) prices of personal computers stay fixed for very long? Indeed, durable
goods in general tend to have very flexible prices,
as witnessed by the frequent sales for electronic
equipment. Returning to the more basic end of the
consumer products spectrum, food prices (especially those of fresh fruit and vegetables) fluctuate
in line with market conditions.16 As for services,
barbers may not change the price of a haircut very
often, but the same cannot be said for airfares.
Carlton (1983) raised an important point
concerning the interpretation of findings that the
prices of some or many products are sticky or
inflexible. He notes that the observation that the
price of a product is inflexible for long periods is
meaningless if the product changes over time.
The specific example he considered was one in
which delivery lags could be lengthened in lieu of
raising price when demand is tight. As evidence
for the potential importance of this mechanism for

Assessment of the evidence
In assessing the evidence on price stickiness, one cannot help but be struck by the
scant documentation of how frequently prices
actually change. I have been able to find only
three studies (Cecchetti, Carlton, and Kashyap)
that make a serious attempt to document price
stickiness in the postwar United States. Although this review of the literature includes the
earlier work by Mills, his is probably the most
suspect study cited.
Another striking aspect of price stickiness
documentation is the very small fraction of gross
domestic product (GDP) it covers. It is remarkable
that Cecchetti’s results on the newsstand prices of
magazines should receive such widespread attention in view of the trivial fraction of GDP those
sales represent.14 The most comprehensive of the
modern studies is Carlton (1986), but the products
in that study were all intermediate rather than final
goods. However, Ball and Mankiw (1994) argue
that when it comes to assessing the importance of
sticky prices as an explanation for monetary
neutrality, it is necessary only that those goods
purchased with money (by which they seem to
mean currency) exhibit stickiness, since the prices
of goods bought with credit do not directly affect
the demand for money. Ball and Mankiw note that
goods purchased with currency are typically
small retail items (such as newspapers and hair-

FEDERAL RESERVE BANK OF DALLAS

ECONOMIC REVIEW FIRST QUARTER 1995

allocating output, Table 1 shows the standard
deviations of price and delivery lags in selected
industries. In each case, delivery lags are more
variable than price, in some cases considerably
so. But Carlton’s point applies more generally and
to aspects of the product other than time to
delivery. Thus, to note that the price of a magazine stays fixed for, say, a year is not very
interesting if the magazine changes its ratio of
advertising to text during the year. Koelln and
Rush (1993) note such a possibility in connection
with Cecchetti’s study of magazine prices. Similarly, to note that the price of a piece of apparel
stays fixed for a long period is not very informative if instead the fabric content of the item
changes. Indeed, just such a phenomenon occurred during WWII when price controls held the
nominal price of various consumer goods constant. Manufacturers skirted these price controls
and effectively raised prices by lowering the
quality of the goods.17 Blinder’s interview study
lends further credence to this possibility with the
finding that most firms in his sample accepted that
changes in delivery lags or other aspects of the
product were a common alternative to nominal
price increases.
While these studies document many cases
in which prices stay fixed for long periods, they
also find many instances in which prices are very
flexible, changing frequently and often by small
amounts. The earliest evidence on this is the Ushaped distributions plotted by Mills for wholesale prices in the pre-World War II period. Carlton
also finds many instances of frequent and small
price changes in the Stigler –Kindahl data set, and
Blinder observes that about 10 percent of the
firms in his sample change their prices as often as
once a month.
Finally, there is evidence that price changes

are more frequent during periods of high inflation
than during periods of low inflation. This is one
of the main findings of Cecchetti’s study, and is
also reported by Kashyap. Additional evidence on
the frequency of price adjustment during periods
of high inflation in Israel is presented in Sheshinski,
Tishler, and Weiss (1981); Lach and Tsiddon
(1992); and Eden (1994). The importance of this
result is that it demonstrates that firms’ pricing
policies are not unresponsive to changes in the
environment. Thus, a monetary policy aimed at
stabilizing output and predicated on the notion
that price changes occur at fixed intervals would
be based on a false assumption.
Blinder (1991, 1990) writes that attempts to
test the notion that prices are sticky are hindered
by the ambiguity of the terms “sticky” and “flexible.” To say that prices are sticky often means no
more than that they are less flexible or adjust less
rapidly than Walrasian market-clearing prices.
However, this is a rather amorphous benchmark,
since Walrasian market-clearing prices are themselves unobservable. Of course, the sensible thing
to do then is to test the other predictions of the
theory. Do models with sticky prices do a better
job at explaining business cycles that do models
with perfect price flexibility?
Ball and Mankiw (1994, 35–36) note that “A
scientific theory should be judged not only by the
intrinsic appeal of its assumptions, but also by its
ability to explain observed facts—especially ones
that it was not explicitly designed to explain.” In
view of the scant evidence on price rigidity and
the inherent difficulties in augmenting such evidence as there is, perhaps the best way to assess
the quantitative importance of price rigidities for
understanding fluctuations in economic activity is
to compare the performance of models with price
rigidities with that of models with fully flexible
prices to see which does better in explaining the
stylized facts of the business cycle.
Cho and Cooley (1990) explore the quantitative implications of nominal price contracts (or
sticky prices) for the transmission and propagation of shocks in a standard business-cycle model.
The model they study is a variant of the onesector, neoclassical growth model augmented
with a cash-in-advance constraint. They study the
effects of nominal price contracts that vary in
length from one to eight periods on the propagation of both monetary and technology shocks,
with prices set each period on the basis of
expected marginal costs. Cho and Cooley show
that only a small amount of price stickiness is
needed in their model to generate output volatility of the same magnitude as observed in the U.S.
data. Monetary shocks propagated by nominal

Table 1

Price and Delivery Lag Fluctuations

SIC code
22
26
331
34
35
36

Industry
Textile mill products
Paper and allied products
Steel
Fabricated metals
Nonelectrical machinery
Electrical machinery

Standard
deviation
of log
of price

Standard
deviation
of log of
delivery lag

Median
delivery lag
in months

.06
.05
.03
.03
.04
.05

.17
.08
.25
.18
.25
.10

1.26
.46
1.95
3.06
3.63
3.86

SOURCE: Carlton (1983, Table 1).

price stickiness for a small number of products
thus may be an important element in furthering
our understanding of the business cycle under
certain price-setting rules. However, nominal
shocks by themselves propagated by nominal
contracts are not a viable alternative to technology shocks as a source of business cycles: while
monetary shocks propagated by nominal contracts can generate output volatility of the right
order of magnitude, other features of such a
model are inconsistent with the facts of U.S.
business cycles.
The consequences of price stickiness in a
general equilibrium model have also been investigated by Ohanian and Stockman (1994a, b), who
examine an economy in which some prices are set
in advance and some are free to change instantaneously. Prices in the sticky-price sector are
assumed to be set at their expected marketclearing level. Ohanian and Stockman show that
only a small degree of price stickiness may be
sufficient to generate big effects from nominal
shocks. However, as the model studied by Ohanian
and Stockman abstracts from capital accumulation, it is not clear how robust their results are. In
particular, the inclusion of capital accumulation
would introduce an additional margin along which
substitution could occur in response to exogenous disturbances, necessitating the existence of
a larger sticky price sector to generate plausible
liquidity effects. Just how much larger is an open
question.
A key shortcoming of the Cho–Cooley and
Ohanian–Stockman analyses is that they graft ad
hoc price-setting rules onto otherwise standard
general equilibrium models. Beaudry and
Devereux (1993) overcome this problem by examining a model in which intermediate goodsproducing firms find it optimal to preset prices,
and do so in a way that maximizes expected
profits.18 Beaudry and Devereux find that their
model is able to match key features of the data
reasonably well, in the sense that the impulse
responses computed for the model for monetary
and technology shocks are similar to those generated by U.S. data. In particular, the endogenously
sticky prices generate a quantitatively important
propagation mechanism for nominal shocks.
In contrast to the studies just mentioned, the
results of Kydland (1991) suggest that sticky
prices may have little role to play in explaining
output fluctuations. Kydland finds that an equilibrium business-cycle model with price flexibility
can account for about two-thirds of the fluctuations in output and the price level as a response
to technology shocks alone. All movements in the
price level come about as a result of real shocks;

FEDERAL RESERVE BANK OF DALLAS

there are no fluctuations in the money stock.
Since prices in the real world are more volatile
than prices in the model, sticky prices may
explain little about the remaining one-third of
volatility that cannot stem from technology shocks
alone.

Conclusions
The notion that nominal price rigidities play
an important role in the transmission and propagation of nominal shocks to the real economy is
one of the oldest ideas in economics, dating back
at least to the work of David Hume in the
eighteenth century. In this article, I make two
points about this literature. First, despite its widespread acceptance among economists, there is
remarkably little evidence to support the notion
that prices are sticky. The only way to determine
how frequently prices change is to collect and
examine data on the prices paid in individual
product transactions. To date, I have been able to
uncover only three studies that document the
frequency of price adjustment in the U.S. economy.
Given the importance of price stickiness to much
of contemporary macroeconomic thinking, one
would have thought that there would be a lot
more evidence to support this assumption.
My second major point in this article is that
the evidence, in many cases, must be interpreted
with caution. If buyers and sellers are able to alter
product characteristics other than price to arrive
at market-clearing outcomes, it is not clear that
the observation that posted prices are sticky
implies a role for interventionist policy. If private
markets are achieving efficient outcomes without the aid of the government, the government
would do best by doing nothing. Carlton (1989)
concludes his survey of how markets clear with
this comment:
The importance of price diminishes
once one recognizes that price alone may
not be clearing markets and, instead, that
price in conjunction with other mechanisms, such as a seller’s knowledge of a
buyer’s needs, is performing that function.
Indeed, if price is not the sole mechanism
used to allocate goods, it becomes less
interesting to observe whether price remains rigid. Although a rigid price does
imply inefficiency under any of the simple
models in which price alone is the exclusive
mechanism used to achieve efficient resource allocation, a rigid price does not
imply inefficiency in a world in which price
is but one of the many methods firms are
using to allocate goods to customers.

ECONOMIC REVIEW FIRST QUARTER 1995

Despite the caveats about evidence of price
stickiness, it may well be that only a small degree
of genuine price stickiness is needed for nominal
or monetary shocks to generate a quantitatively
significant role as a source of business cycles. The
recent results of Cho and Cooley and Ohanian
and Stockman are particularly suggestive in this
regard. Can models that assume nominal rigidities
are an optimal response to some aspect of the
economic environment reproduce the key facts of
the U.S. business cycle? The question remains
open.
Even if prices are fully flexible, this does not
imply that monetary policy has no role in affecting
the level of output. Sticky prices are only one
mechanism whereby changes in the stock of
nominal money can affect the real economy.
Recent literature has sought to explain the real
effects of monetary policy by invoking the notion
of market incompleteness. Thus, the outcome of
the debate on whether sticky prices matter for
understanding business cycles may have little to
do with how effectively the Federal Reserve can
contribute to smoothing the business cycle.

Notes

2
3

This article originated in a set of comments on
“A Sticky-Price Manifesto” by Laurence Ball and N.
Gregory Mankiw, presented at the Second Annual
Texas Conference on Monetary Economics. I am
grateful to reviewers John Duca, Evan Koenig, and
Carlos Zarazaga for comments. I also thank Peter
Hartley and Finn Kydland for useful comments.
The Fed also influences the level of economic activity
through changes in reserve requirements. Such
changes affect the real opportunities for borrowing
and lending and are thus considered more likely to
have an influence on real economic activity.
See, for example, chapter 2 of Friedman (1992).
See, for example, Gordon (1990), who notes that only
price stickiness is needed to generate cycles in real
output, given a path of nominal aggregate demand.
Gordon adds that price flexibility is fully consistent with
nominal wage rigidity as long as profits are sufficiently
flexible.
Foss (1993) discusses how the threat of antitrust
litigation discourages accurate reporting of transactions prices by firms.
Although not anymore: it is now quite common for
bookstores to offer discounts of 10 percent on the
purchase of books or magazines when the customer
joins the store’s “frequent buyer” program.
For example, the average price per issue of The
Economist is lower for a two-year subscription than for
a one-year subscription.
It is worth noting that insofar as changes in the real
characteristics of a product result from nominal

shocks, this supports the notion that money does have
an effect on real output, even though prices, when
properly measured, may be completely flexible.
Koelln and Rush also note that advertising further
complicates the interpretation of sticky magazine
prices. Insofar as revenue from advertising is more
important to the magazine publisher than revenue
from newsstand sales, the appropriate interpretation
of observed sticky cover prices is not clear. The
authors note that prior to the inclusion of advertising in

Reader’s Digest in 1956, the number of pages in each
issue had declined in several steps from 180 pages in
January 1950 to 168 pages in January 1955. To limit
the complications introduced by advertising, Koelln
and Rush focus on magazines for which they think
advertising is relatively unimportant.
Stigler and Kindahl do, in fact, find that their measures
of transactions prices were substantially more flexible
than the BLS price indexes.
CPI inflation averaged 1.8 percent a year over the
same period.
Kashyap also ignores any postage and handling
charges. He claims that this factor is less serious than
it might seem, as all Bean prices include these charges,
and the Bean prices can be used to establish all the
results reported in the study.
Simple menu-cost arguments cannot explain the
infrequency of price changes in catalogs. The menu
cost in such a case is just the cost of printing the
catalog, and this cost is the same whether none or all
of the prices change.
Again, the question relevant to an understanding of
potential transmission or propagation mechanisms for
monetary policy is whether “tight” demand can result
from a nominal shock. See note 8.
The closest way to assess the relative importance of
magazine sales in GDP is to look at the ratio of consumer spending in the category “Magazines, newspapers, and sheet music” to GDP. Over the period
covered by Cecchetti’s study, spending in this category amounted to less than one-half of 1 percent of
GDP (0.41 percent to be precise)!
It is also worth asking how representative catalog sales
are of all retail sales in terms of the demographics of
the buyers. One suspects that most catalog sales
covered in Kashyap’s study were to relatively prosperous consumers with relatively high opportunity
costs of time.
Levi, Bergen, and Dutta (1994) look at the price of
selected brands of orange juice in a retail outlet and
find that the prices of some brands change, on
average, every two weeks.
For a discussion of quality deterioration in connection
with price controls during wartime, see Rockoff (1984).
Ireland (1994) also shows that in an economy in which
some firms must set prices one period in advance, the
optimal pricing rule does not equate the preset price

Friedman, Milton (1992), Money Mischief: Episodes in
Monetary History (New York: Harcourt Brace Jovanovich).

with expected marginal costs, except when shocks are
serially uncorrelated.

References

Gordon, Robert J. (1990), “What Is New Keynesian
Economics?” Journal of Economic Literature 28 (September): 1115–1171.

Ball, Laurence, and N. Gregory Mankiw (1994), “A StickyPrice Manifesto” (Paper presented at the Federal Reserve
Bank of Dallas Texas Conference on Monetary Economics, Dallas, April 23–24).

Ireland, Peter (1994), “Monetary Policy with Nominal Price
Rigidity,” (Federal Reserve Bank of Richmond, May, mimeo).

Barro, Robert J. (1977), “Long-Term Contracting, Sticky
Prices, and Monetary Policy,” Journal of Monetary

Economics 3 (July): 305–16.

Kashyap, Anil K. (1991), “Sticky Prices: New Evidence
from Retail Catalogs,” Federal Reserve Bank of Chicago
Working Paper WP–91–26 (December).

Beaudry, Paul, and Michael B. Devereux (1993), “Monopolistic Competition, Price Setting, and the Effects of Real
and Monetary Shocks,” Discussion Paper no. 93–34,
University of British Columbia (September).

Koelln, Kenneth A., and Mark Rush (1993), “Rigid Prices
and Flexible Products,” Journal of Economics 19 (Spring):

Blinder, Alan S. (1991), “Why Are Prices Sticky? Preliminary Results from an Interview Study,” American Economic Review 81 (May): 89–96.

Kydland, Finn E. (1991), “The Role of Money in a Business
Cycle Model,” Institute for Empirical Macroeconomics
Discussion Paper no. 23.

——— (1990), “Learning by Asking Those Who Are Doing,”
Eastern Economic Journal 16 (October–December):
297–306.

Lach, Saul, and Daniel Tsiddon (1992), “The Behavior of
Prices and Inflation: An Empirical Analysis of Disaggregated Price Data,” Journal of Political Economy 100
(April): 349–89.

57–64.

Carlton, Dennis W. (1989), “The Theory and the Facts of
How Markets Clear: Is Industrial Organization Important
for Understanding Macroeconomics?” in vol. 1 of Handbook of Industrial Organization, ed. Richard Schmalensee
and Richard D. Willig (Amsterdam: North Holland).

Levi, Daniel, Mark Bergen, and Shantanu Dutta (1994),
“Price Rigidity: Evidence from Scanner Data” (Paper presented at the Southern Economic Association Meeting,
Orlando, Florida, November 20–22).

——— (1986), “The Rigidity of Prices,” American Economic Review 76 (September): 637–58.

Mills, Frederick C. (1927), The Behavior of Prices (New
York: National Bureau of Economic Research, Inc.).

——— (1983), “Equilibrium Fluctuations When Price and
Delivery Lags Clear the Market,” Bell Journal of Economics 14 (Autumn): 562–72.

NBER (1961), The Price Statistics of the Federal Government: Review, Appraisal and Recommendations, General
Research Series 73 (New York: National Bureau of
Economic Research).

Cecchetti, Stephen G. (1986), “The Frequency of Price
Adjustment: A Study of the Newsstand Prices of Magazines,” Journal of Econometrics 31 (April): 255–74.

Ohanian, Lee, and Alan Stockman (1994a), “Short-Run
Effects of Money When Some Prices Are Sticky,” Federal
Reserve Bank of Richmond Economic Quarterly 80
(Summer): 1–23.

Cho, Jang-Ok, and Thomas F. Cooley (1990), “The
Business Cycle with Nominal Contracts” (University of
Rochester, mimeo).

———, and ——— (1994b), “How Much Price Stickiness
Is Necessary for Reasonable Liquidity Effects?” (University of Rochester, February, mimeo).

Eden, Benjamin (1994), “Inflation and Price Adjustment:
An Analysis of Micro Data,” Working Paper no. 94–13,
University of Iowa (April).

Rees, Albert (1961), “Alternative Retail Price Indexes for
Selected Non-Durable Goods, 1947–59,” in The Price
Statistics of the Federal Government: Review, Appraisal,
and Recommendations, ed. George Stigler (New York:
National Bureau of Economic Research).

Foss, Murray F. (1993), “Does Government Regulation
Inhibit the Reporting of Transactions Prices by Business?”
in vol. 57 of Price Measurements and Their Uses, NBER
Studies in Income and Wealth, ed. Murray F. Foss,
Marilyn E. Manser, and Allan H. Young (Chicago: University of Chicago Press).

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Rockoff, Hugh (1984), Drastic Measures: A History of
Wage and Price Controls in the United States (New York:

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Cambridge University Press).

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and Price Stability (1977), The Wholesale Price Index:
Review and Evaluation (Washington, D.C.: Government
Printing Office).

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Costs of Adjustment, and the Amplitude of Real Price
Changes: An Empirical Analysis,” in Development in an
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(New York: Academic Press).

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Measurement Biases in Price Indexes,” Federal Reserve
Bank of Dallas Research Paper no. 9340 (Dallas, October).

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Behavior of Industrial Prices (New York: National Bureau
of Economic Research).

The Texas Banking
Crisis and the
Payments System

As our nation’s central bank, the Federal
Reserve System plays a vital role in promoting
a smoothly functioning economy. The Federal
Reserve pursues basic macroeconomic goals of
price stability and full employment in fulfilling
its responsibilities for monetary policy, banking
supervision, and payments-system operations.
By providing payments-system services, such as
electronic transfers and check-processing, the
Federal Reserve facilitates the exchange of funds
that is necessary to complete economic transactions. This third role, to provide efficient clearing
of payments, frequently goes unnoticed. Most
individuals do not know how the checks they
deposit are collected. And if the system keeps on
working as well as it has in the recent past, they
probably never will.
Completing the payments required in economic transactions involves risks.1 Banks expose
themselves to financial risks by accepting for
deposit checks drawn on other banks, especially
when the banks clear these payments among
themselves through clearinghouses or correspondent banks.2 These risks increase during periods
of economic and financial stress.
The Federal Reserve System offers an alternative to clearing payments through clearinghouses and private wire transfer networks. Banks
that use the Fed’s payment services reduce their
risk exposure. Therefore, during periods of financial stress, the Federal Reserve provides a safer
means of completing payments, permitting economic transactions to continue without worry
about how the payments will clear.
The purpose of this article is to establish
empirically the significant effect the Texas banking crisis had on check-clearing within and outside the Federal Reserve System. Historically,
banking crises often caused or exacerbated a
decline in real economic activity, resulting in lost
jobs and income. The Federal Reserve System,
along with other government programs, limited
the damage from the Texas banking crisis. One
factor minimizing the spillover effect of the banking crisis to the nonfinancial sectors was the Fed’s
providing a safer method of clearing payments.

Robert T. Clair
Senior Economist and Policy Advisor
Research Department
Federal Reserve Bank of Dallas
Joanna O. Kolson
Assistant Vice President
Operations Analysis Department
Federal Reserve Bank of Dallas
Kenneth J. Robinson
Senior Economist and Policy Advisor
Financial Industry Studies Department
Federal Reserve Bank of Dallas

he purpose of this article

is to establish empirically the
significant effect the Texas banking
crisis had on check-clearing within
and outside the Federal Reserve System.
Historically, banking crises often
caused or exacerbated a decline in real
economic activity, resulting in lost jobs
and income. The Federal Reserve
System, along with other government
programs, limited the damage

How checks are cleared

from the Texas banking crisis.

FEDERAL RESERVE BANK OF DALLAS

A check can be cleared—that is, presented
to the bank on which it was drawn—by several
different methods in the private sector. The bank
that receives the check in deposit is called the
bank of first deposit (BOFD); the bank on which
the check is drawn is called the paying bank. The
BOFD can present the check directly to the paying bank, present the check through a clearinghouse, or engage the services of a correspondent

ECONOMIC REVIEW FIRST QUARTER 1995

Figure 1

Alternative Ways to Present a Check for Collection
Bank of first deposit

Send directly to
paying bank
Yes

Private
sector

Public
sector

Alternatives
No

Clearinghouse A
Correspondent
Bank A

Alternatives
Send directly to
paying bank
Yes

Clearinghouse B
Correspondent
Bank B

Federal Reserve
System

Paying
bank

NOTE: Both the bank of first deposit and the paying bank are members of Clearinghouse A.
Both Correspondent Bank A and the paying bank are members of Clearinghouse B.

bank to present the check to the paying bank.3
The collecting bank could physically present the check directly to the paying bank and
demand payment in what is called direct presentment (Figure 1 ). But with nearly 27,000 depository institutions in the United States, it would be
highly inefficient and costly to deliver checks to
every paying bank nationally or even regionally.
To improve efficiency, banks within a city or
region often form clearinghouses where participating banks present the checks drawn on all the
other participating banks (Clearinghouse A in
Figure 1). About 20 percent of all U.S. financial
institutions are members of clearinghouses, which
range in size from two to more than 600 members.4 Membership in a clearinghouse association
offers a financial institution a low-cost alternative
to paying an intermediary for check collection
services. Member institutions in the generally
nonprofit associations establish rules regarding
how and when they present checks and credit/
debit accounts through the exchange.

When a BOFD receives a check for deposit
drawn on a bank that is not a member of its
clearinghouse, it must use an alternate method to
present the check. Direct presentment is still an
option, but it could be costly. The BOFD often
deposits the check at a correspondent bank
(Correspondent Bank A in Figure 1). Correspondent banks, often called simply correspondents,
are usually large commercial banks that clear
substantial volumes of checks. These banks have
established extensive arrangements to clear checks,
maintain equipment to sort checks, and contract
for air and ground transportation to deliver checks
regionally or nationally. A bank using the services
of a correspondent is called a respondent bank
or a respondent. Staying within the private sector,
the correspondent can present the check directly
to the paying bank, or indirectly through a clearinghouse where both the correspondent and the
paying bank are members (Clearinghouse B in
Figure 1), or it can present the check to another
correspondent (Correspondent Bank B in Figure

1) that services the paying bank, either directly or
through a clearinghouse.
The Federal Reserve Banks offer checkclearing services similar to those correspondents
offer. Any U.S. depository institution can purchase payment-clearing services from the Federal
Reserve.5 The Fed presents the checks either
directly to the paying bank or the paying bank’s
correspondent (or third-party processor) or transports the checks to another Federal Reserve
facility for direct presentment to the paying bank
or the paying bank’s correspondent (or processor). The Fed operates a network of forty-six
Federal Reserve Banks, branches, and Regional
Check Processing Centers to clear checks. This
system supports the Federal Reserve’s task of
providing sorting and transportation of checks
drawn on any depository institution in the country. The Federal Reserve clears approximately
one-third of the total checks written and presented for collection to institutions.
In check collection, the Federal Reserve
competes most directly with correspondents. The
Federal Reserve Banks’ largest competitors, however, are also their largest customers. Correspondents often use the Federal Reserve to collect
checks drawn on paying banks that are not
members of a mutual clearinghouse or that can be
presented more economically by being passed to
the Federal Reserve for handling.

data processing, international banking, safekeeping, and credit card services.
In a correspondent relationship, the respondent typically keeps balances with the correspondent for the purpose of clearing payments. The
respondent’s primary risk in this relationship is
that the correspondent could fail, and the respondent could lose the uninsured portion of the
clearing account. Furthermore, if the respondent
has lent federal funds to the correspondent, these
uninsured funds could be lost. Even if the funds
are not lost, access to them could be disrupted
while the federal deposit insurer is closing the
correspondent.
The risk exposure of the correspondent to a
respondent’s failure is less than that of the respondent to the correspondent’s failure. Correspondents expose themselves to risk if they are
providing credit to the respondent, usually as very
short-term credit, such as federal funds sold. If the
respondent were to fail, the correspondent would
return the checks drawn on the respondent to the
bank of first deposit. Thus, the correspondent
protects itself from risk of loss, but it may incur a
significant cost in returning these checks.
Probably the most important event in making respondents aware of their risk exposures was
the collapse of Continental Illinois National Bank
in 1984. While no respondent lost funds in
Continental, the respondents became aware that
losses were possible, depending on the Federal
Deposit Insurance Corporation’s (FDIC) method
of resolving the bank failure.
Continental’s financial condition deteriorated rapidly during spring 1984. On May 17,
the FDIC, the Federal Reserve System, and the
Comptroller of the Currency announced a temporary assistance program. In June 1984, the FDIC
estimated that 2,299 commercial banks held deposits at Continental and that 179 of these banks
might fail if Continental failed. Furthermore, Continental had been active in international financial
markets, prompting concerns that its failure could
trigger an international financial crisis. The FDIC
designed an assistance program for the Continental collapse that protected all of Continental’s
respondents and correspondents from loss.
Continental’s collapse made banks much
more aware of their risk exposure in correspondent banking relationships, although preliminary
reports seriously overestimated the problem’s
severity.7 While regulators treated Continental’s
continued operation as essential to maintaining
stable financial markets, small banks were concerned that other correspondents might not be
considered “too big to fail.” Alternative FDIC
responses to bank failures, such as liquidation,

A closer look at correspondent
banking relationships
Many smaller institutions clear most or all
payments through correspondents. Correspondents typically operate on either a regional or
national basis. Regional correspondents rely on
either the Federal Reserve Banks or national
correspondents to collect checks on more remote
banks. National correspondents compete with the
Federal Reserve on a national level, presenting
checks for payment to as many as 200 other
institutions.6 A correspondent also may handle
wire transfers and provide automated clearinghouse (ACH) services for other institutions.
Correspondents provide a variety of services in addition to payment processing and
clearing. These include currency and coin services, Treasury tax and loan (TT&L) clearing,
securities safekeeping and clearing, securities
purchase, federal funds purchase and sales, cash
management, investment services, credit card
services, data processing, international banking,
trust services, and loan participations. The Federal Reserve provides only some of these services.
Service bureaus and third-party processors are
alternative service providers in payment-clearing,

FEDERAL RESERVE BANK OF DALLAS

ECONOMIC REVIEW FIRST QUARTER 1995

might cause respondents with deposits above the
insured limits to lose the uninsured portions of
their deposits.
In times of financial stress, such as occurred
in the Eleventh Federal Reserve District in the late
1980s, banks seek to lower their risk exposure.8
The Federal Reserve offers a risk-free alternative
method of collecting payments. While the Federal
Reserve requires banks to maintain an account,
there is no risk that the Fed could fail. Therefore,
the balances in these Fed accounts are safer than
if respondents deposited them at correspondents.
By risk-free, we mean there is no danger the
Federal Reserve will fail as the payment processor. The party seeking payment still may not be
paid if the bank on which the payment is drawn
refuses to honor the check because it is drawn on
insufficient funds, has an invalid endorsement, is
forged, or for a variety of other legal reasons. But
these reasons have a well-established precedent
in law, and the procedures to return the payment
are well-defined.
If respondents become concerned that their
correspondent might fail, they could present their
checks for collection through the Federal Reserve
and avoid the risk exposure associated with
clearing through the correspondents. Similarly, if
the financial condition of a broad cross-section of
respondents were to deteriorate, correspondents
could decide their risk exposure in providing
correspondent services is too large and exit the
business. Their exit would leave some respondents and their customers with limited access to
wholesale banking services.

Figure 2

Eleventh District Commercial Bank
Failures, 1982–93
Number of banks
160
140
120
100
80
60
40
20
0
’82

’83

’84

’85

’86

’87

’88

’89

’90

’91

’92

’93

but inadequate funding of the Federal Savings
and Loan Insurance Corporation (FSLIC) prevented thrift regulators from aggressively closing
insolvent thrifts through most of the 1980s.
Financial-sector difficulties in the Eleventh
District reached heights not observed since the
Great Depression. Unlike the events that occurred
during the 1930s, though, widespread financial
panic was not evident. Depositor confidence in
the latter half of the 1980s was maintained,
primarily due to the existence of federal deposit
insurance. While not without serious unintended
consequences, the federal guarantee of deposits
was successful in averting widespread financial
market instability, despite epidemic commercial
bank and thrift failures.10 However, as evidence
mounted that several large financial institutions in
the Eleventh District were facing severe problems, some large, uninsured depositors moved
their funds elsewhere. This movement of funds
presumably reflected the fear that deposits in
excess of insured limits might be lost.11
Widespread instability was also averted by
several innovative techniques for resolving financial-sector distress. New resolution techniques
implemented by the FSLIC and the FDIC were
often successful in achieving an orderly transition
in cases of thrift and commercial bank insolvencies.12 Moreover, legislation passed in 1980
extended Federal Reserve discount window privileges to all depository institutions, providing an
additional tool for averting a financial crisis.
As conditions in the Eleventh District’s
financial community began to erode, correspondent banking relationships became strained
and sometimes broken. After several small institutions failed during the early years of decline,
correspondents closely monitored respondents.

Breakdown in correspondent banking
during the Texas banking crisis
Financial institutions in the Eleventh District
suffered unprecedented upheaval in the 1980s. Oil
prices weakened in 1982 and virtually collapsed
in 1986, precipitating a host of asset-quality problems at the District’s financial institutions. In
addition, severe overbuilding created a glut of
commercial real estate space. Return on average
assets of District commercial banks turned negative in 1986. Problems with business loans surfaced initially, but problem real estate loans
eventually overshadowed them. Commercial bank
failures in the Eleventh District rose sharply in the
latter half of the 1980s, as shown in Figure 2.9
Thrift institutions in the Eleventh District
suffered even more severe losses during this
period. Nearly half of all District thrifts were
insolvent at the end of 1988. At the end of 1989,
less than one-fourth of the thrifts in the District
were both profitable and solvent. The number of
thrift closures would have been extremely high,

Any negative speculation about a respondent’s
condition often caused a correspondent to stop
payment-processing or sever the relationship with
the respondent completely. The Federal Reserve
frequently became the payments processor for
these respondents.
As the decline continued and the financial
health of larger institutions deteriorated, the concerns reversed. The financial instability of many
of the District’s large correspondents caused
respondents to seek other payment-processing
arrangements. The number of changes in payment-processing arrangements increased by 57
percent in the years following the failures of the
largest District banks.13

forming loans to total loans at District commercial
banks is expected to have a positive impact on the
volume of checks processed by the Federal Reserve. That is, as nonperforming loans increase,
indicating a deteriorating banking sector, the
volume of checks processed by the Federal Reserve should rise. Second, the capital ratio of
District commercial banks is also used to gauge
the strength of the banking sector.17 Here, a
negative relationship is expected. As the capital
ratio declines, the volume of checks processed
should rise, if indeed the Federal Reserve is acting
as the “processor of last resort.” Third, the number
of bank failures in each District is included as an
explanatory variable to measure financial turmoil.
The expected sign on the bank failure variable is
positive. We obtained the bank financial ratios
from the Report of Condition and Income and the
number of bank failures from the Federal Deposit
Insurance Corporation.
The data are a pooled time series crosssection utilizing the twelve Federal Reserve Districts over the period from fourth-quarter 1982
to fourth-quarter 1993. Using cross-section data
should improve the quality of the test by increasing the variability of explanatory variables.
Furthermore, the Eleventh District was not the
only District that experienced a weak financial
sector. Including other Districts decreases the
likelihood that an increase in Federal Reserve
check-processing volume would be inappropriately attributed to financial-sector weakness.
Because pooled data are used, an error
components model was assumed in the estimation procedure. The assumption underlying this
model is that the disturbance term in the regression is composed of three independent components: one component associated with time, one
associated with the cross-section units, and the
third component is assumed to vary in both time
and spatial dimensions.
In the following model:

An empirical test
While anecdotal evidence is interesting, a
statistical test of the effect of bank conditions on
Federal Reserve check-clearing volumes is necessary to control for other factors that might have
affected Fed check-clearing operations. We therefore constructed and estimated a model of checkprocessing volumes at the twelve Federal Reserve
Districts.
In the model, Federal Reserve check-processing volumes are assumed to be related to the
level of economic activity within each Federal
Reserve District and the state of the banking
industry within each District. The following regression equation is estimated:
(1)

CHECKS = β0 + β1 ∗ ECONOMY
+ β2 ∗ FINANCIAL + E,

where CHECKS represents the total volume of
checks processed at each Federal Reserve.14
ECONOMY is an employment measure included
to control for business-cycle effects on the volume of check-clearing. FINANCIAL represents
variables used to proxy for the financial condition
of the banking industry, and E is a random error.
The number of checks processed by each Federal
Reserve District is published in the Planning and
Control System Quarterly Data, Division of Federal Reserve Bank Operations, Board of Governors of the Federal Reserve System.15
The economic activity variable, ECONOMY,
is nonagricultural employment in each Federal
Reserve District.16 This variable is estimated by
the Federal Reserve Bank of Dallas, using annual
county-level data and monthly state-level data,
with an adjustment for industrial mix by county.
The number of checks processed is expected to
be positively correlated with economic activity.
Three different measures of financial-sector
condition are tested. First, the ratio of nonper-

FEDERAL RESERVE BANK OF DALLAS

yit =

∑X

itk

βk + εit ; i = 1,… N ; t = 1,…T ,

k =1

N is the number of cross-sections, T is the length
of the time series, and p is the number of
independent variables. Under the error components model, the random errors, ⑀it , are assumed
to have the following decomposition:

where

⑀it
ui
vt
wit

= ui + vt + wit ,
∼ N(0, σ u2 ),
∼ N(0, σ t2 ), and
∼ N(0, σ it2 ).

The individual error components are assumed to

ECONOMIC REVIEW FIRST QUARTER 1995

satisfy the following conditions:
E (ui vt )
E (uiuj )
E (vt vs )
E (wit wis )

=
=
=
=

relationship between the financial condition of
banks and the volume of Federal Reserve checkclearing existed only in those Federal Reserve
Districts that could be characterized as suffering
severe banking crises. This is done by including
an interaction term, which is the cross-product of
the measure of banking difficulties with a dummy
variable for each of the Federal Reserve Districts.
The results are not affected. In models that
included nonperforming loans (1 and 2), the
employment variable remains significant, and the
only interaction terms that are significant are for
the Eighth and Tenth Districts. For models with
capital ratios (3 and 4), the employment variable
and capital variable are statistically significant,
while none of the interaction terms is significant.
This test implies that banks across the country
were sensitive to the financial condition of the
banking industry in their Districts when deciding
on a check-processing arrangement.

E (ui wit ) = E (vtwit ) = 0,
0 (i ≠ j ),
0 (t ≠ s ),
E (wit wjt ) = E (wit wjs ) = 0
(i ≠ j ; t ≠ s).

Generalized least squares estimation produces consistent parameter estimates.18 Because
the estimates of the first-order autocorrelation
coefficients are very close to 1, first differences of
all the variables (in logs) are used in the estimation
(with the exception of the bank failure variable).19
Several different tests are conducted for
determining the appropriate pooling method.
The tests show that the error components approach is statistically superior to the hypothesis
that no differences existed across Federal Reserve
Districts, and it is superior to the hypothesis that
the inter-District differences are fixed effects.
The results of estimating equation 1 appear
in Table 1. Four models are tested, all of which
show that Federal Reserve check-processing volumes are positively correlated with the level of
economic activity. Models 3 and 4 utilize the
capital ratio as the indicator of bank financial
condition; it is significant, with the expected sign
in both cases. Models 1 and 2 use nonperforming
loans as the indicator of bank condition; it is
insignificant in explaining Federal Reserve checkprocessing volumes. Similarly, bank failures, which
are included in models 1 and 3, are insignificant
as an explanatory variable.
These results support the hypothesis that
banks increase their use of Federal Reserve checkclearing services when banking conditions deteriorate. Banks appear to be most concerned
about bank capitalization.20 This implies that
banks have foresight and act in anticipation of
potential bank failures. The insignificance of the
bank failure variable suggests that respondent
and correspondent banks respond before the
banks actually fail. This evidence is consistent
with Federal Reserve attempts to maintain a
smoothly functioning payments system in the face
of unprecedented financial-sector distress.
The insignificance of nonperforming loan
ratios in models 1 and 2 suggests that banks are
more focused on the immediate indicator of
failure, bank capitalization, rather than on an
indicator of potential future reductions in capital.
Nonperforming loans may be an indicator of
future declines in capital, but a well-capitalized
bank could sustain higher than average nonperforming loans and remain solvent.
A final test is conducted to determine if the

The impact of the Texas banking crisis
on Federal Reserve payment services
The financial industry problems not only
caused an increase in checks processed by the
Fed’s Eleventh District operations, as shown above,
but also increased the amount of handling these
checks required. Eleventh District check-processing volume increased by 9.8 percent from 1987 to
1989, while the other Federal Reserve Districts
averaged only a 2.8-percent increase. The aboveaverage increase in the Eleventh District was
largely attributed to increased check volume from
banks with total deposits between $30 million and
$500 million. Check volume from these banks
cleared through the Fed increased by more than
50 percent between 1987 and 1989 and accounted
for 64 percent of the total increase in all checks
processed by the Eleventh District Fed.
These small to mid-size institutions were
most often respondents that previously cleared
payments through correspondents. Often, these
institutions viewed their processing with the Federal Reserve as only a temporary arrangement.
Because the Fed does not supply all correspondent services, these banks intended to resume
payment-processing with a new correspondent.
The increase in Eleventh District processed check
volume was particularly significant because of the
associated check-handling requirements. The Fed’s
new customers sent most of the additional volume with limited presorting done to the checks.
This meant more sorting and handling of the
checks by the Reserve Banks.
Various check-processing support areas also
faced increased demands and pressures. Frequently, banks requested check collection ser-

Table 1

Determinants of Federal Reserve Check-Processing Volume
Dependent variable: CHECKS
Independent variables

Model
1

INTERCEPT

.0044
(.004)

.0046
(.005)

.0047
(.004)

.0051
(.004)

EMPLOYMENT

.4792*
(.206)

.4697*
(.206)

.5758**
(.1954)

.5650**
(.1953)

NONPERFORMING

–.006
(.012)

–.007
(.012)
–.1655**
(.0340)

–.1638**
(.0340)

CAPITAL
FAIL

0
(0)

Summary Statistic
SSE

.2035

.1981

.1982

* = Significant at the 5-percent level.
** = Significant at the 1-percent level.

than 30 percent of total Eleventh District commercial banking assets in 1988 to 97 percent in thirdquarter 1994.21 By the end of third-quarter 1994,
only 9 percent of the Eleventh District’s commercial banks could be characterized as unhealthy,
and these were smaller than average banks holding only 3 percent of total commercial banking
assets in the District.
The improvement in the health of the Eleventh District commercial banking industry has
resulted in increased correspondent banking activity in payment-processing and other services.
With consolidated operations and improved efficiencies, the correspondents have improved their
competitive position and have seen opportunities
to generate fee income. In addition, the risk of
providing correspondent services has declined as
banking conditions have improved.
As banks have established new correspondent relationships, Federal Reserve service trends
again have changed. From 1990 to 1993, the
Eleventh District saw a 1.3-percent increase in
checks submitted for processing and collection,
versus a 12-percent increase from 1985 to 1989. As
correspondents attempt to avoid costs and optimize use of existing check-processing capability,
the Eleventh District has received more checks
that require little or no machine sorting.
The other significant change resulted from
statewide branching of the large holding compa-

vices from the Fed on short notice. The Fed often
had to handle these checks on an exception basis
until databases could be updated, forms could be
delivered, and notifications completed. The new
management of failed banks that had been acquired often requested changes in delivery of
processed checks and associated accounting information. If the FDIC liquidated a failed paying
bank, the Fed had to intercept and return these
checks to the BOFD. The additive effect of
ownership changes, correspondent changes, liquidations, and branching meant three to four
changes daily in sorting procedures for Dallas
Office check operations. The updating required
to the District’s Customer Information System
(CIS) database increased significantly from 1986
to 1990. By 1988, updates to the CIS required
about four hours of clerical time daily at the
Federal Reserve Dallas Office, and half of the
requested changes required same-day handling.

Outlook for the future
The Eleventh District banking industry has
recovered from its financial difficulties; therefore,
the pressure on the payments system has been
reduced. The improvement in performance,
coupled with the resolution of failed commercial
banks, has resulted in a substantial improvement
in the health of District commercial banks. Assets
held by healthy commercial banks rose from less

FEDERAL RESERVE BANK OF DALLAS

ECONOMIC REVIEW FIRST QUARTER 1995

nies. As bank holding companies consolidated
their affiliated banks into branches, they changed
their check routing numbers to that of the lead
bank in the holding company. This change created a substantial shift in workload at the Dallas
Fed, with additional checks deposited early in the
day for processing. The workload shift required
changes in personnel, work schedules, and assigned duties.

Reserve System’s ability to clear payments and
minimize spillover from the banking crisis to the
payments system.

Notes
1

Before the creation of the Fed, the risk involved in
accepting a check as payment was more explicit.
Parties accepting checks often discounted the face
value to reflect the cost and risk of clearing. One
reason for creating the Fed was to establish on-par
clearing of checks. On-par clearing requires that a
check not be discounted — that is, that it be accepted
for its full face value.

The term bank is used in this article to refer to any
depository institution, including commercial banks,
savings and loan associations, mutual savings
banks, and credit unions. Where necessary to make
a distinction, the term commercial bank is used to
refer to institutions chartered by the Office of the
Comptroller of the Currency or state banking agencies and typically insured by the Bank Insurance
Fund managed by the Federal Deposit Insurance
Corporation (FDIC).
If a check drawn on one bank is deposited by another
customer of the same bank, then there is no collection
process. The bank simply debits the account of the
party that wrote the check and credits the account of
the party that deposited the check.
U.S. General Accounting Office (1989, 37).
The Depository Institution Deregulation and Monetary
Control Act of 1980 mandates that Federal Reserve
services be available to all U.S. depository institutions
and that the Fed charge an appropriate price for these
services. Fed pricing is set as a markup over costs,
with an adjustment factor for the profits the private
sector would require and the taxes the private sector
must pay.
U.S. General Accounting Office (1989, 12).
For a detailed analysis of the number of likely commercial bank failures that might have resulted from the
Continental failure, see the staff report entitled “Continental Illinois National Bank Failure and Its Potential
Impact on Correspondent Banks” in U.S. House of
Representatives (1984).
The Eleventh Federal Reserve District includes Texas,
northern Louisiana, and southern New Mexico.
For more on the performance of Eleventh District
financial institutions in the past decade, see Robinson
(1990).
For more on the problems associated with federal
deposit insurance, see Kane (1989, 1985). Subsidized deposit insurance with uniform premiums
encouraged bankers to take greater risks and
discouraged depositors from carefully monitoring
banks’ risks.
For example, as FirstRepublic Bank’s troubles became
increasingly apparent, depositors began shifting their

The Federal Reserve provides
a needed safety valve
The Federal Reserve System provides a riskfree method of clearing payments. The account
balances held at the Federal Reserve that are
necessary to clear payments are not exposed to
risk even during periods of financial crisis. Some
have called the Federal Reserve the “processor of
last resort.” A more accurate description would be
that in a financial crisis, there is a “flight to quality.” Our empirical test demonstrates that Federal
Reserve check-processing volumes rose when
banking conditions deteriorated.22 The Fed represents the safest method of clearing payments.
If the Federal Reserve could not provide this
risk-free payment-clearing service, then turmoil
in the financial markets could have negative
effects on the economy. Difficulty in determining
how the payment for a transaction would clear
might hamper the sales of goods and services.
Such problems would place an additional cost on
businesses and could slow an already weak
economy. At a minimum, without the Federal
Reserve’s payment operations as a backstop,
businesses and banks would have to invest in
reducing payments-system risk. Banks might need
to maintain multiple correspondent relationships,
and businesses might alter their policies for accepting payment, such as requiring payments to
clear before delivery of goods.
For the Federal Reserve to maintain the
ability to respond to a financial crisis, it must
maintain an ongoing payment-clearing operation
that can be expanded as necessary. Such operations are complex and cannot be established
overnight. A financial crisis can develop faster
than the Fed could establish a payment-clearing
operation from scratch.
The banking crisis in the Eleventh District is
an example of the Federal Reserve’s response to
the temporary needs of financial institutions during a crisis. Now that the Eleventh District’s
economy and its banking industry have recovered, the Fed’s role in clearing payments has
diminished. Perhaps the one positive result of the
regional economic downturn and the banking
crisis that followed was the test of the Federal

4
5

6
7

17
18
19

funds to safer institutions. From December 1987 to
mid-February 1988, FirstRepublic lost a total of $1.14
billion in average deposits (Apcar 1988).
For a discussion of these new techniques and their
related problems, see Cole (1990) and Kane (1989).
Each change in processing arrangement required an
update to the Eleventh District’s Customer Information
System (CIS). Numerous updates to the CIS reflected
the shift of clearing arrangements and the commercial
bank merger activity driven largely by commercial
bank failures. In the two years before 1988, the
average annual number of changes in correspondent
banking relationships was 237.5 in the Dallas Office of
the Eleventh District. The failures of major Eleventh
District commercial banks began in 1988. In the
following three years, the average number of changes
in correspondent bank relationships rose to an estimated 373 in the Dallas Office. By comparison, in
1993, there were only 184 changes in the Dallas
Office’s correspondent banking relationships.

References
Apcar, Leonard (1988), “Lender in Crisis: Big Texas
Bank’s Plan to Ride Out Troubles Could Be Faltering,”
Wall Street Journal, February 2.
Clair, Robert T., Joanna Kolson, and Kenneth Robinson
(1994), “Risky Business: Clearing Checks During Banking
Crises,” Federal Reserve Bank of Dallas Southwest
Economy, Issue 4, 5 – 8.
Cole, Rebel (1990), “Thrift Resolution Activity: Historical
Overview and Implications,” Federal Reserve Bank of
Dallas Financial Industry Studies, May, 1–12.

While the optimal dependent variable would probably
be market share, such data do not exist.
One variable that would have improved the model is,
of course, the price of Federal Reserve check-clearing
services relative to private-sector prices. Unfortunately,
such pricing data do not exist. Anecdotal evidence
indicates that the Fed was receiving the costlier
checks to clear, which would drive up the Fed’s prices
relative to the private sector. This relative price effect
would be in the opposite direction of the empirically
significant effect that banks seek safer clearing
arrangements in chaotic times.
Retail sales may be a better measure of economic
activity that would correspond to the need to clear
checks. Unfortunately, it is not possible to construct a
retail sales variable by Federal Reserve District. A test
of this model based solely on Texas retail sales data
and Eleventh Federal Reserve District check-clearing
was not materially different in results. Furthermore, the
Pearson correlation coefficient between retail sales in
Texas and employment in Texas was 0.97.
The capital ratio is the Tier I equity-to-asset ratio.
See Fuller and Battese (1974).
While there may be some concern that the model is
picking up a secular trend of declining capital ratios
and increasing Federal Reserve check-clearing
volumes, the fact that the model is estimated in first
differences and that there is no evidence of residual
autocorrelation alleviates such concerns.
Current capital ratios are released on a lagged basis,
especially for small banks. Tests with lagged values of
capital ratios were insignificant. This result suggests
that banks have knowledge of the financial condition
of their correspondents and respondents, and the
current capital ratio is a reasonable proxy for this
knowledge.
A simple definition of a healthy commercial bank is one

FEDERAL RESERVE BANK OF DALLAS

with a capital ratio at least a half of a percent above
regulatory minimums, troubled assets less than 3
percent of total assets, and profits.
The Eleventh Federal Reserve District is not the only
example. See Clair, Kolson, and Robinson (1994) for
details of the effects of the Rhode Island crisis and the
failure of the Bank of New England on Federal Reserve
check-clearing.

Fuller, W. A., and G. E. Battese (1974), “Estimation of
Linear Models with Crossed-Error Structure,” Journal of
Econometrics 2 (May): 67–78.
Humphrey, David Burras (1984), “The U.S. Payments
System: Costs, Pricing, Competition, and Risk,” Monograph Series in Finance and Economics, Issue 1/2.
Kane, Edward (1989), The S&L Insurance Mess: How Did
It Happen? (Washington, D.C.: The Urban Institute).
——— (1985), The Gathering Crisis in Federal Deposit
Insurance (Cambridge, Mass.: MIT Press).
Knudson, Scott E., Jack K. Walton II, and Florence M.
Young (1994), “Business-to-Business Payments and the
Role of Financial Electronic Data Interchange,” Federal
Reserve Bulletin, April, 269 – 81.
Robinson, Kenneth J. (1990), “The Performance of
Eleventh District Financial Institutions in the 1980s: A
Broader Perspective,” Federal Reserve Bank of Dallas
Financial Industry Studies, May, 13 –24.
U.S. General Accounting Office (1989), Check Collection:
Competitive Fairness Is an Elusive Goal, May.
U.S. House of Representatives (1984), “Inquiry into Continental Illinois Corp. and Continental Illinois National
Bank,” hearings before the Subcommittee on Financial
Institutions Supervision, Regulation and Insurance of the
Committee on Banking, Finance and Urban Affairs,
September 18, 19, and October 4, Serial No. 98 –111
(Washington, D.C.: Government Printing Office).

ECONOMIC REVIEW FIRST QUARTER 1995

The Role of
Merchandise Exports
To Mexico in the
Pattern of Texas
Employment

Under the North American Free Trade Agreement (NAFTA), Mexico has reduced its average
tariff on U.S. goods to approximately 11 percent
and will reduce it to nothing by 2010.1 However,
these cuts represent only the latest in a series of
tariff reductions by the Mexican government. In
the latter half of the 1980s, the Mexican government instituted four major tariff reforms that
produced two major reductions in tariff rates
(Lustig 1992).
Texas has been a major beneficiary of
Mexico’s trade liberalization. Adjusted for inflation, Texas’ merchandise exports to Mexico have
nearly tripled since the first quarter of 1987.2
While Mexico’s liberalization only partially explains the boom in merchandise exports, it clearly
has made Texas products more competitive in
Mexico than they would otherwise have been,
thereby fueling the expansion.
In this article, we use an input–output
model of the Texas economy to evaluate the
employment consequences of the recent expansion in Texas’ merchandise exports to Mexico.
Because the input–output model describes the
interrelationships among industries, it allows us
to identify not only the employment gains by
industries that export directly but also the employment gains by industries, like transportation
services, that interact with the direct exporters.
We find that merchandise export growth can
explain only a small fraction of Texas’ overall
employment growth since 1987 but can explain
much of the employment growth in specific
industries. In particular, we find that all of the
recent growth in high-technology manufacturing
may be explained by increasing merchandise
exports to Mexico.

Kelly A. George
Assistant Economist
Federal Reserve Bank of Dallas
Lori L. Taylor
Senior Economist and Policy Advisor
Federal Reserve Bank of Dallas

exas has been a major beneficiary
of Mexico’s trade liberalization.

Adjusted for inflation, Texas’ merchandise
exports to Mexico have nearly tripled
since the first quarter of 1987. While
Mexico’s liberalization only partially
explains the boom in merchandise
exports, it clearly has made Texas

The link between trade and employment
Nationally, import and export changes
have few lasting effects on the level of employment. Over time, workers displaced by increased import competition find jobs in other
industries. Similarly, workers hired by growing
export firms generally surrender existing jobs.
While the composition of employment can
change dramatically, the level remains essentially unchanged.3
Regionally, however, the situation is very
different. As employment patterns shift in response to trade, workers can move geographically, as well as occupationally. After all, the
cultural and legal barriers that make it difficult
to move across national borders in response to
labor market conditions seldom inhibit movement across state lines. Thus, when an increase
in exports attracts workers to the petrochemi-

products more competitive in Mexico
than they would otherwise have been,
thereby fueling the expansion.

cal industry, it also attracts them to states like
Texas that are home to petrochemical firms.
Furthermore, because proximity to Mexico can
reduce transportation costs, increases in exports to Mexico also encourage firms in those
export-oriented industries to locate in Texas
rather than in other states.
Measuring the total influence on Texas
employment of the state’s increasing trade with
Mexico requires information on the full range of
trade between the two jurisdictions. Thus, we
would need data not only on Texas merchandise
exports and imports but also on imports and
exports of services like tourism and health care.
After all, Texas imports services from Mexico
whenever Texans vacation in Cancun and exports
services to Mexico whenever Mexicans vacation
in San Antonio.
Unfortunately, data on Texas’ trade in
services and merchandise imports from Mexico
are not available.4 Therefore, we focus our
analysis on the role that Texas’ merchandise
exports to Mexico play in the state’s economy.5
Given this narrow focus, our analysis reveals
only part of the influence that increasing trade
with Mexico has had on the Texas economy.
However, because merchandise exports to Mexico
represent nearly 5 percent of Texas gross state
product (GSP), our analysis describes an important part of the total trade picture.6

other Texas industries. For example, the 1986
input– output table of the Texas economy indicates that 97 percent of the output of the Texas
aircraft industry was consumed locally or exported, 2 percent was used in the production of
other aircraft or space vehicles in Texas, and 1
percent was used as an input by firms providing transportation services in Texas. Firms in
other states and other countries are consumers
from Texas’ perspective, so their purchases are
included as part of consumption.
Because the inputs of one industry come
from the outputs of another, input– output
tables also enable users to trace the ways in
which each industry uses the products of every
other industry. For example, the input– output
table described above indicates that to produce
$1,000 worth of output, the Texas aircraft and
parts industry uses $13 worth of Texas electronics, $4 worth of metals fabricated in Texas,
and $36 worth of business services provided by
Texas firms.
Simultaneously solving the system of 158
equations (representing 157 industries and the
household sector) yields the amount of output
from each industry that is needed to satisfy
consumers’ final demands and Texas industry’s
intermediate-goods demand. By changing final
demand, solving the system of equations again,
and comparing the industry output across the two
cases, one finds the change in each industry’s
output that would be necessary to satisfy the
observed quarterly change in export demand.
This change in output reflects not only direct
changes in demand but also changes in demand
for intermediate goods and changes in household
demand induced by changes in worker income.

Input–output analysis
We use an input–output model of the
Texas economy to trace the changes in the
composition and level of employment that can
be attributed to the actual, quarterly changes in
merchandise exports since first-quarter 1987.
Input– output analysis is an analytic framework
that describes the interrelationships between
industries and households as a system of simultaneous equations.7 Each equation represents a
sector of the economy. The sectors generally
correspond with industries, but some models
also include the household sector to reflect the
influences that employment changes can have
on household demand. Our model of the Texas
economy, which we obtained from the Economic Analysis Center of the Texas Comptroller of Public Accounts, incorporates a household
sector.
The equation for any given industry describes the total value of that industry’s output
as the sum of the value of that industry’s output
that is sold to consumers, the value of that
industry’s output that is used in the industry’s
own production process, and the value of that
industry’s output that is sold as an input to

FEDERAL RESERVE BANK OF DALLAS

Figure 1

Texas Exports to Mexico, 1987:1– 94:4
Millions of 1987 dollars
5,000

4,000

3,000

2,000

1,000

0
1987

1988

1989

1990

1991

1992

1993

SOURCE: Massachusetts Institute for Social and Economic
Research.

ECONOMIC REVIEW FIRST QUARTER 1995

1994

out changing relative prices for goods or factors. Thus, if the model predicts that a given
change in final demand would increase output
in the electronics industry by 10 percent, then
employment in the electronics industry should
also increase by 10 percent.
We use data on average industry employment in the model’s year (1986) to predict the
changes in industry employment attributable to
the quarterly changes in merchandise exports.8
For each industry, the sum of the quarterly
changes in employment indicates the total change
in employment between first-quarter 1987 and
fourth-quarter 1994.

Figure 2

Average Share of Texas Exports
To Mexico by Sector, 1987–94
Percent
100
90
80
70
60
50
40
30
20
10

Changes in Texas’ merchandise
export trade with Mexico

0
1987

1988

1989

1990

Agriculture
Mining

1991

1992

1993

Nondurable goods
Durable goods

1994

In 1987, Texas exported $25 billion worth
of merchandise to foreign countries.9 Twentysix percent, or $6.5 billion, of Texas merchandise exports went south to Mexico. By 1994,
Texas merchandise exports to Mexico had
grown to more than $18.5 billion per year (in
1987 constant dollars). Real Texas merchandise exports to Mexico have grown more than
10 percent a year for six of the past seven years
(Figure 1 ).
Despite such rapid growth, the general mix
of the goods exported to Mexico from Texas has
not changed dramatically since 1987 (Figure 2 ).
Durable goods consistently account for approximately 70 percent of Texas’ merchandise exports.10 Nondurable goods account for more than

Other

SOURCE: Massachusetts Institute for Social and Economic
Research.

In this modeling framework, industry employment should change at the same rate as
industry output. Input–output analysis assumes
constant returns to scale and a fixed relationship between factor inputs. For example, if
manufacturing $1 worth of apparel requires 50
cents worth of textiles, then manufacturing $2
worth of apparel would require $1 worth of
textiles. It also implicitly assumes that labor
and capital supplies are perfectly elastic, so
that all industries could increase output with-

Figure 3

Percentage Change in Real Texas Merchandise Exports to Mexico after NAFTA
Printing and publishing
Stone, clay, and glass
Rubber and miscellaneous products
Fabricated metals
Apparel and other textile products
Chemicals and allied products
Paper and allied products
Industrial machinery and computer equipment
Transportation equipment
Food and kindred products and tobacco
Total
Primary metals
Electronics and other electrical equipment
Miscellaneous manufacturing
Instruments and related products
Petroleum and coal products
Agriculture
Leather and leather products
Furniture and fixtures
Lumber and wood products
Mining
–40

–30

–20

–10

Percent

SOURCE: Massachusetts Institute for Social and Economic Research.

Figure 4

Percentage of Industry Trade and the Timing of Zero Tariffs
Minerals
Petroleum and natural gas
Instruments and precision manufacturing
Leather and leather products
Wood and wood products
Agriculture
Chemicals
Industrial machinery
Electrical machinery
Textiles and apparel products
Other products
Base metals
Stone, clay, and glass
Transportation equipment
Furniture and fixtures
Total trade
0

100

Percent
Duty-free before NAFTA

Duty-free immediately with NAFTA

Staged reductions*

* Includes tariffs that will be reduced in equal annual increments over five to fifteen years. Some staged reductions began January 1, 1994,
while others will not be implemented until future years.
SOURCE: United States International Trade Commission (1993).

produce stone, clay, and glass, and rubber and
miscellaneous products.
Solid growth in merchandise exports to
Mexico following the implementation of NAFTA
is particularly striking when one considers the
other factors acting to suppress demand. The
peso was weaker in 1994 than it had been in 1993,
making Texas exports more expensive. Mexico’s
gross domestic product growth rate was barely
positive in 1993 and early 1994 and much weaker
than in 1991 and 1992. And finally, political instability in Mexico slowed foreign investment and
expansion plans.
Figure 4 details the changes in tariffs with
the implementation of NAF TA. For example,
the figure indicates that 15 percent of agricultural exports to Mexico were duty-free before
January 1, 1994, an additional 37 percent of
agricultural exports became duty-free on January 1, 1994, and the tariffs will be reduced in
stages for the remaining 48 percent of agricultural exports (U.S. International Trade Commission 1993).
Surprisingly, there is little apparent correlation between the industries that experienced a
major boost in exports during 1994 and the
industries that experienced a major reduction in
tariffs.12 For example, on January 1, 1994, tariffs
dropped to zero for more than 70 percent of
instruments exports, yet exports by the instru-

20 percent of total merchandise exports. Agricultural goods, mining, and other exports (scrap and
waste, secondhand merchandise, and special classification goods 11) make up the remaining 10
percent of merchandise exports.
At a less aggregate level, however, the pattern of merchandise exports shows more variation. The electronics and other electrical equipment
category remains Texas’ primary merchandise
export to Mexico, but the industry’s share of total
Texas merchandise exports declined from almost
one-third in 1987 to almost one-quarter of merchandise exports in 1994. Merchandise export
shares have also declined substantially for petroleum and coal products, paper and allied products, chemicals and allied products, and industrial
machinery and computer equipment. On the
other hand, export shares have more than doubled
since 1987 for printing and publishing, transportation equipment, and instruments and related
products.

The pattern of exports after NAFTA
Figure 3 details the changes in Texas’ merchandise exports since the implementation of
NAFTA. Real merchandise exports to Mexico
from Texas increased 14 percent between 1993
and 1994. Printing and publishing exports grew
63 percent during that period. Other industries
that experienced dramatic growth in exports

FEDERAL RESERVE BANK OF DALLAS

ECONOMIC REVIEW FIRST QUARTER 1995

ments industry grew only 4 percent in 1994.
There are a number of possible explanations for this lack of correlation. Price elasticities
differ from industry to industry, making some
industries more responsive to tariff changes than
others. Mexico may have introduced nontariff
barriers (like additional inspections or paperwork
requirements) that offset the tariff reductions in
some industries. Finally, the tariffs are classified
according to commodities, while the exports are
classified according to industries. At the two-digit
level of aggregation, the two series do not correspond exactly, and that lack of correspondence
could blur the connection between tariff cuts and
export growth.

employment growth can be attributed to corresponding multiplier effects.
While merchandise export growth cannot
explain much of total employment growth, it has
had a considerable influence on the composition
of the Texas economy. As Figure 5 indicates,
increasing merchandise exports to Mexico encouraged workers to shift toward industries that
manufacture durable goods like electronics and
other electrical equipment and transportation
equipment.14 The electronics and other electrical
equipment industry gains the most employment
share because exports to Mexico represent a
disproportionately large percentage of that
industry’s production. Especially rapid export
growth produced gains in employment share for
the transportation equipment industry.
When some industries gain employment
share, others must necessarily lose it. Not
surprisingly, our analysis indicates that increases in merchandise exports cause employment to shift away from industries that do not
produce merchandise exports. Multiplier effects determine the extent of the losses for
these industries. Industries that are closely
linked to merchandise exporters — such as the
transportation-services industry— lose less
employment share than industries that are not
closely linked.
In Figure 6, we compare the actual employment composition in 1994 with the em-

The employment consequences of
increasing merchandise exports to Mexico
Although Texas’ merchandise exports to
Mexico have nearly tripled since 1987, they still
represent less than 5 percent of GSP. Therefore,
it would be surprising if merchandise export
growth could explain a large percentage of Texas
employment growth. Our analysis indicates that
6.1 percent of Texas employment growth between first-quarter 1987 and fourth-quarter 1994
can be attributed to increasing merchandise exports to Mexico.13 On average, 3 percent of Texas
employment growth can be attributed to the
direct effects of increases in merchandise exports
to Mexico, while another 3.1 percent of Texas
Figure 5

Changes in Employment Composition Due to Changes in Real Texas Merchandise
Exports to Mexico, 1987– 94
Electronics and other electrical equipment
Transportation equipment
Fabricated metals
Apparel and other textile products
Rubber and miscellaneous products
Industrial machinery and computer equipment
Primary metals
Instruments and related products
Furniture and fixtures
Paper and allied products
Leather and leather products
Food and kindred products and tobacco
Printing and publishing
Miscellaneous manufacturing
Stone, clay, and glass
Lumber and wood products
Chemicals and allied products
Electric, gas, and sanitary services
Communications
Petroleum and coal products
Transportation services
FIRE*
Mining
Construction
Wholesale/retail trade
Services
Government
–.25

–.2

–.15

–.1

–.05

.05

.10

.15

Percent
* Finance, insurance, and real estate.
SOURCES OF PRIMARY DATA: Massachusetts Institute for Social and Economic Research; U.S. Department of Labor, Bureau of Labor
Statistics.

Figure 6

Ratio of Employment Share to Predicted Employment Share Absent Growth
In Merchandise Exports to Mexico, 1994
Transportation equipment
Furniture and fixtures
Electronics and other electrical equipment
Primary metals
Leather and leather products
Rubber and miscellaneous products
Apparel and other textile products
Instruments and related products
Fabricated metals
Paper and allied products
Industrial machinery and computer equipment
Stone, clay, and glass
Miscellaneous manufacturing
Printing and publishing
Food and kindred products and tobacco
Lumber and wood products
Electric, gas, and sanitary services
Chemicals and allied products
FIRE*
Communications
Wholesale/retail trade
Transportation services
Services
Petroleum and coal products
Mining
Construction
Government
96

100

102

104

106

108

110

Percent
* Finance, insurance, and real estate.
SOURCES OF PRIMARY DATA: Massachusetts Institute for Social and Economic Research; U.S. Department of Labor, Bureau of Labor
Statistics.

industry, spending on research and development
must be more than 50 percent above the U.S.
average (Bureau of the Census 1993). We estimate
that increasing merchandise exports to Mexico
can explain all of Texas’ employment growth in
high-tech manufacturing since 1987.16 However,
the relationship need not be causal because our
analysis does not discriminate between increases
in Texas merchandise exports that reflect increasing Mexican demand and increases in Texas
merchandise exports that reflect export firms’
relocating to Texas from other states.
While the input– output analysis reveals
those industries that have been highly influenced by increasing merchandise exports to
Mexico, it also reveals those industries that
have been essentially unaffected. For example,
the analysis indicates that increasing merchandise exports to Mexico have had little influence
on the employment shares for energy-related
manufacturing (chemicals and petroleum and
coal products). This potentially surprising result reflects the fact that while these industries
represent 10 percent of Texas merchandise
exports to Mexico, exports to Mexico represent
less than 1 percent of gross output for these
industries.17

ployment composition we predict would have
occurred if merchandise exports to Mexico had
not changed.15 This analysis allows us to isolate
those industries in which increasing merchandise exports to Mexico have had a significant
influence on employment shares. We find that
four industries — transportation equipment,
furniture and fixtures, electronics and other
electrical equipment , and primary metals —
would have had much smaller shares of Texas
employment had merchandise exports to
Mexico remained unchanged. We estimate that
since 1987, all the gains in employment in the
electronics and other electrical equipment and
furniture and fixtures industries, and more than
half of the gains in the primary metals industry,
can be attributed to increasing merchandise
exports to Mexico. Furthermore, we calculate
that employment in transportation manufacturing would have fallen much more rapidly over
the past few years if increases in merchandise
exports to Mexico had not partially offset
declines in defense spending by the U.S. government.
A common denominator among three of the
four industries that have gained considerable
employment share through increasing merchandise exports is that major components of these
industries are classified as high-technology manufacturers by the Bureau of the Census. To be
classified as a high-technology manufacturing

FEDERAL RESERVE BANK OF DALLAS

Sensitivity analysis
The preceding analysis uses data on the
“origin of movement to port” to evaluate Texas’

ECONOMIC REVIEW FIRST QUARTER 1995

merchandise exports to Mexico. Recently, the
Commerce Department has also released data
using “state of ZIP code of exporter” to allocate
merchandise exports among the states. Because the ZIP-codes series begins in the first
quarter of 1993, it was not appropriate for our
longer term analysis. However, we wondered
if an analysis of the employment effects of
merchandise export growth after NAF TA would
be sensitive to the export series used.
To make the two series comparable for
sensitivity analysis, we restrict our evaluation
to year-over-year changes in real merchandise
exports that have not been seasonally adjusted.18 For each industry and each series,
predicted employment after NAF TA is the sum
of actual employment in the fourth quarter of
1993 and the predicted change in employment
for 1994.19
Figure 7 indicates the difference in employment share between the fourth quarter of
1993 and the predicted employment after
NAF TA for each merchandise export series.
While the correspondence is not exact, the two
merchandise export series generate estimates
of employment impact that are qualitatively
similar. In either case, the primary beneficiaries of recent increases in merchandise exports
to Mexico produce electronics and other electrical equipment, fabricated metals, and apparel

and other textile products. The analysis predicts modest growth in employment share for
these industries as a result of export growth
after NAF TA. Similarly, regardless of the measure of merchandise exports, the analysis predicts
a decline in employment share for government,
transportation equipment manufacturing, and
narrowly defined services such as business services and health care. Thus, our results appear
qualitatively insensitive to changes in the definition of merchandise exports.

Conclusion
Our analysis of the employment consequences of increasing merchandise exports to
Mexico is more suggestive than definitive for a
number of reasons. An input–output model is
particularly well-suited to identifying multiplier
effects that are not readily apparent, but it cannot
incorporate changes in production technology.
Therefore, the model will underestimate the employment consequences of export growth for any
industry that has become more labor-intensive
over time (and vice versa) and will not capture
any changes in the interrelationships among industries. Furthermore, data limitations prevent us
from describing the employment changes that
growth in merchandise imports or bilateral services trade could induce. Because trade is an
exchange, it is possible that the compositional

Figure 7

Change in Industry Composition after NAFTA:
Two Measures of the Effects of Export Growth
Electronics and other electrical equipment
Fabricated metals
Apparel and other textile products
Rubber and miscellaneous products
Industrial machinery and computer equipment
Primary metals
Paper and allied products
Stone, clay, and glass
Chemicals and allied products
Food and kindred products and tobacco
Instruments and related products
Printing and publishing
Electric, gas, and sanitary services
FIRE*
Communications
Miscellaneous manufacturing
Petroleum and coal products
Transportation services
Leather and leather products
Lumber and wood products
Mining
Construction
Wholesale/retail trade
Furniture and fixtures
Services
Transportation equipment
Government

Origin of port
ZIP code of exporter

–2

–1.5

–1

–.5

1.5

Percent

* Finance, insurance, and real estate.
SOURCES OF PRIMARY DATA: Massachusetts Institute for Social and Economic Research; U.S. Department of Labor, Bureau of Labor
Statistics.

effects of merchandise exports are fully offset by
merchandise imports or by the pattern of trade in
services.
Our analysis suggests that growth in Texas’
merchandise exports to Mexico can account for
only a small fraction of the employment growth in
Texas since 1987. However, we find that the
growth of merchandise exports to Mexico has had
a considerable influence on the composition of
the Texas economy. In particular, growth in
merchandise exports can explain all of the recent
growth in high-tech manufacturing.

Notes

Our thanks to Stephen P. A. Brown, David Gould, Keith
Phillips, and Fiona Sigalla for their helpful comments
and suggestions and to Carla Miller for her assistance
with the export data.
Data on Mexican tariff rates were provided by Mexico’s
Department of Commerce and Industrial Development
(SECOFI).
Data on merchandise exports to Mexico from Texas
are not available for prior years.
Changes in trade flows can change real wages, but
recent research by Kydland (1995) indicates that
changes in real hourly compensation have little longterm influence on hours worked per household.
We considered using data on U.S. trade in services
with Mexico and U.S. merchandise imports from
Mexico as proxies for the corresponding Texas data
but rejected that approach because we would not
expect Texas’ trade to be proportionately similar to
U.S. trade. Given its close proximity to Mexico, Texas
is likely to be a disproportionately large trading partner
in services. Texas is also likely to consume a disproportionately large share of Mexican goods that are
expensive to ship. Consumption of imports from
Mexico may also be unusually heavy because Texas’
large population of Mexican –Americans is more
familiar with Mexican products. (For a discussion of the
effects that immigrants can have on imports, see
Gould 1994.)
This analysis does not incorporate any effects that
increasing exports to Mexico from other U.S. states
may have on Texas.
We have extrapolated GSP using data on national
productivity trends and Texas employment after 1991.
For a more detailed discussion of input – output
analysis, see Miller and Blair (1985) and the Texas
Comptroller of Public Accounts (1989).
For each industry, the input – output table indicates the
percentage change in output and employment (φit ) that
would be required to satisfy the observed change in
merchandise exports for period t. Therefore, the
change in industry employment in each period that is
attributable to changes in merchandise exports would
be Li•φit , where Li is the average employment in

FEDERAL RESERVE BANK OF DALLAS

industry i for 1986.
The merchandise export data were provided by the
Massachusetts Institute for Social and Economic
Research (MISER). The data are based on “origin of
movement to port” state-level export codes derived
from standard industrial classifications. We use the
fixed-weight GDP deflator to adjust the nominal export
data for changes in the U.S. price level and use the
SAS Institute’s X-11 procedure to seasonally adjust the
real export data.
Mexico’s maquiladora program undoubtedly contributes to the heavy emphasis on durables in the merchandise export mix.
Special classification goods include military equipment, miscellaneous equipment, antiques, donations
and charity, and magnetic tape recordings.
The Pearson correlation between the percentage of
merchandise exports to Mexico becoming duty-free
on January 1, 1994, and the percentage growth in
merchandise exports between 1993 and 1994 is only
0.3040.
While increasing merchandise exports to Mexico can
explain only a fraction of total employment growth
since 1987, they could explain much of the differential
in growth between Texas and the United States.
Employment has been growing faster in Texas than in
the United States since 1988 (Sigalla 1995).
Figure 5 indicates the difference in employment share
between first-quarter 1987 and the predicted employment for each industry in fourth-quarter 1994. The
predicted employment for each industry is the sum of
actual employment in first-quarter 1987 and the total
change in employment attributable to increasing
merchandise exports to Mexico between first-quarter
1987 and fourth-quarter 1994.
We estimate employment shares in the absence of
merchandise export growth by subtracting the total
predicted change in employment due to merchandise
export growth from the observed level of employment
in 1994.
In Texas, employment in high-tech manufacturing
industries represents 100 percent of the chemicals
industry, 93 percent of the petroleum refining and coal
products industry, 92 percent of the instruments and
related products industry, 88 percent of the transportation equipment industry, 86 percent of the electronics
and other electrical equipment industry, 28 percent of
the industrial machinery industry, and 19 percent of
the primary metals industry (Bureau of the Census
1993 and Bureau of Labor Statistics 1993). Our analysis
indicates that increasing merchandise exports to
Mexico should have generated 17,900 high-tech
manufacturing jobs between first-quarter 1987 and
fourth-quarter 1994. Texas actually added 13,500
high-tech manufacturing jobs during that period.
However, the actual job gains would have been much
greater if defense contractors in the transportation

ECONOMIC REVIEW FIRST QUARTER 1995

equipment industry had not laid off thousands of
workers over the period in question.
We determine export’s share of gross output for each
industry by comparing the value of exports to Mexico
in 1987 with estimates of gross output for 1986 from
the input – output table. Assuming that output grew
between 1986 and 1987, our estimates represent an
upper bound on export’s share of gross output.

Gould, David M. (1994), “Immigrant Links to the Home
Country: Empirical Implications for U.S. Bilateral Trade
Flows,” Review of Economics and Statistics 76 (May):
302– 42.
Kydland, Finn (1995), “Business Cycles and Aggregate
Labor Market Fluctuations,” Frontiers of Business Cycle
Research, ed. T. F. Cooley (Princeton, N.J.: Princeton

The full analysis uses seasonally adjusted data, but the
ZIP-codes series is too short to seasonally adjust. We
use seasonally unadjusted data for both series in the
sensitivity analysis to avoid introducing an additional
reason for differences between the two series. As
before, we adjust both series for inflation, using the
U.S. fixed-weight GDP deflator.
The predicted changes in employment for 1994 represent the changes in employment that the input – output
table indicates would be necessary to support the
total change in industry exports between 1993 and
1994.

University Press).
Lustig, Nora (1992), Mexico: The Remaking of an
Economy (Washington, D.C.: Brookings Institution).
Miller, Ronald E., and Peter D. Blair (1985), Input – Output
Analysis: Foundations and Extensions (Englewood Cliffs,
N.J.: Prentice Hall).
Sigalla, Fiona (1995), “Another Strong Year for the Eleventh District,” Federal Reserve Bank of Dallas Economic
Review, First Quarter, also in this issue.

References

Texas Comptroller of Public Accounts (1989), “The Texas
Input – Output Model, 1986 Update: Technical Documentation” (Austin, Texas, mimeo).

Bureau of Labor Statistics (1993), Employment and
Wages, Annual Averages, 1991, Bulletin 2419 (Washington, D.C.: Government Printing Office).

U.S. International Trade Commission (1993), Potential
Impact on the U.S. Economy and Selected Industries of
the North American Free-Trade Agreement, Publication
2596 (Washington, D.C.: Government Printing Office).

Bureau of the Census (1993), Statistical Abstract of the
United States: 1993, 113th ed. (Washington, D.C.:
Government Printing Office).

Another Strong
Year for the
Eleventh District

The Eleventh District economy marked its
eighth year of economic expansion in 1994
with broad-based employment growth in all
three Eleventh District states —Louisiana, New
Mexico, and Texas.1 Robust U.S. and global
economies stimulated demand for District manufacturing and services. The District’s favorable
business climate encouraged growth by attracting firms to relocate or expand in the Southwest, and the North American Free Trade
Agreement, or NAFTA, bolstered the District’s
trade with Mexico.
All sectors of the District economy except
energy and defense-related industries experienced robust growth in 1994. The construction
boom that began in 1993 continued into 1994.
Manufacturing and service industries posted strong
gains. The region prospered despite continued
declines in the once-dominant energy industry.
Defense reductions again lowered employment
for specific manufacturing and federal government positions, although declines were smaller
than in previous years. The sector-by-sector
portion of this article elaborates on the 1994
performance of specific industries.
Although 1994 was a year of robust growth,
the Eleventh District economy shows signs of
slowing in 1995. In the past year, several District
industries reported that shortages of inputs and
workers were pushing up costs and limiting
growth. As the expanding U.S. economy neared
full capacity, interest rates rose,2 which began to
slow District growth. At the end of 1994, the
sudden drop in the value of the Mexican peso
caused a sharp reduction in demand for retailing
and other services along the border. The peso’s
decreased value will reduce District exports in
1995 and add a heavy dose of uncertainty to the
region’s economic outlook.

Fiona D. Sigalla
Associate Economist
Federal Reserve Bank of Dallas

he nation’s economy grew very

strongly in 1994, but the Eleventh
District economy grew even faster,
in part by attracting some of the
country’s most rapidly expanding
industries. Eleventh District
employment has grown more
strongly than the rest of the country
for six consecutive years.

A magnet for fast-growing industries
The nation’s economy grew very strongly in
1994, but the Eleventh District economy grew
even faster, in part by attracting some of the
country’s most rapidly expanding industries. Eleventh District employment has grown more strongly
than the rest of the country for six consecutive
years.3 In 1994, employment in the three-state
District grew 4 percent, faster than the nation’s job
growth of 3.1 percent. The District’s employment
growth in 1994 exceeded its 1993 rate of 3.3
percent and its 3-percent average over the past
twenty-six years. As discussed in the box entitled
“All Three Eleventh District States Grew Faster
than the Nation,” Louisiana, New Mexico, and
Texas all contributed to the Eleventh District’s
strong performance in 1994.

FEDERAL RESERVE BANK OF DALLAS

ECONOMIC REVIEW FIRST QUARTER 1995

Many factors are attracting firms to the
Eleventh District—particularly Texas and New
Mexico —but a low-cost business climate is the
reason companies relocating to the area cite most
often.4 The District has relatively low wages,
regulation, and tax burden.5 With the area’s low
prices and construction costs, many firms find
building a new factory in the Southwest cheaper
than refitting an existing building elsewhere in the
country. Texas and New Mexico, with research
facilities and computer-literate graduates from
local universities, have been particularly successful in attracting California firms.6 The District’s
central location reduces the costs of shipping,
travel, and communications for companies that
operate on both coasts and in Canada and Mexico.
In recent years, the District’s large population of
bilingual residents has been an asset for companies doing business with Latin America.
Low land prices, taxes, and construction
expenses also make the Southwest’s cost of living
desirable to workers, who can buy more goods and
services with a given wage than their counterparts
in most other areas of the country. In 1993, for
example, Austin was the site of more California
business relocations and expansions than any
other U.S. city.7 Companies moving to Austin
were able to pay their workers lower nominal
wages, and yet, because of lower costs of living,
the workers enjoyed higher living standards.8
The appeal of the region’s business and
living costs has helped keep population growth
robust. A high birth rate and migration into New
Mexico and Texas kept the states among the
fastest growing in the country in 1994. Eleventh
District states added 1,625,000 residents between
July 1, 1993, and July 1, 1994, for a total population of more than 24 million.

Figure 1

Louisiana Merchandise Exports to Mexico
Millions of dollars
800
700
600
500
400
300
200
100
0
1991

1992

1993

1994

SOURCE OF PRIMARY DATA: Massachusetts Institute for Social
and Economic Research.

Figure 2

New Mexico Merchandise Exports to Mexico
Millions of dollars
120

100

0
1991

1992

1993

1994

SOURCE OF PRIMARY DATA: Massachusetts Institute for Social
and Economic Research.

Growing trade with Mexico

Figure 3

Trade with Mexico has been an increasing
stimulus for the Southwest economy since 1986,
when Mexico joined the General Agreement on
Tariffs and Trade (GATT) and began liberalizing
its economy.9 In recent years, Mexican demand
for Southwestern retailing, manufacturing, and
tourism has helped these industries become among
the fastest growing in the United States. In 1992,
Wal-Mart opened its largest U.S. store in Laredo,
replacing a smaller store that was already the
chain’s nationwide sales leader. Across the highway is the second largest Target store in the
United States.
A strong and growing network of shipping
and transportation infrastructure makes the District an important distribution hub. Nearly 75 percent of goods traded between the United States

Texas Merchandise Exports to Mexico
Millions of dollars
25,000

20,000

15,000

10,000

5,000

0
1991

1992

1993

1994

SOURCE OF PRIMARY DATA: Massachusetts Institute for Social
and Economic Research.

Table 1

Louisiana’s Top Ten Merchandise Export Industries to Mexico
(1994 Year-to-Date)

and Mexico travel on Texas highways. Most of
those goods flow through Laredo, the largest inland port on the U.S.–Mexican border. Houston has
the largest water port serving Mexico. Ports in Galveston and New Orleans also ship large quantities
of Mexican goods, and a new port in Shreveport–
Bossier City has opened to help funnel goods
between the Midwest and Mexico. In 1994, NAFTA
provided a catalyst to U.S.–Mexican trade by
reducing the risk and lowering the cost of participation in Mexico’s economy. On January 1, 1994,
48.9 percent of U.S. exports entered Mexico dutyfree, compared with 17.9 percent in 1993.
NAFTA’s implementation was a starting gun
for further development of District transportation
services, warehousing, and infrastructure. Transportation services employment in the District
states grew 6.6 percent in 1994. While Louisiana
and New Mexico posted strong increases, the
strongest growth was in Texas, where air, trucking, and railroad companies raced to expand their
cargo facilities. Texas employment in railroad,
trucking, warehousing, and transportation services increased 9.9 percent in 1994.
In addition to transportation services, other
industries in the service sector profited by helping
companies comprehend changing regulations and
unfamiliar laws and tax codes. Accounting, communications, consulting, and legal firms set up
new offices to help companies learn how to trade.
Legal firms facilitated an increase in joint ventures, mergers, and acquisitions, as firms joined
forces to overcome informational and cultural
obstacles and speed entry into a new market. A
large Hispanic population and already strong ties
to Mexico helped make the region’s workers
valuable to budding international companies.
The strong growth of U.S.–Mexican trade
since NAFTA’s implementation is particularly startling, given the relative weakness of the Mexican
economy. Mexico was in recession when NAFTA
became law on January 1, 1994. Although observers expected the Mexican economy to accelerate
in 1994, political uncertainty slowed growth and
led many investors to move cautiously.
Still, trade and investment in Mexico picked
up strongly in 1994. All three states in the Eleventh
District profited from rising exports to Mexico. As
shown in Figure 1, in 1994 Louisiana merchandise
exports to Mexico increased 50.3 percent over
1993.10 As Table 1 shows, agricultural products,
chemicals, and petroleum products are among
Louisiana’s top export industries. New Mexico’s
merchandise exports to Mexico rose 32.9 percent
in 1994, as shown in Figure 2. Table 2 lists New
Mexico’s top export industries in 1994, which
were computer equipment, oil and gas, electron-

FEDERAL RESERVE BANK OF DALLAS

Agricultural production—crops
Chemicals and allied products
Petroleum and coal products
Food and food products
Industrial machinery,
computer equipment
Paper and allied products
Transportation equipment
Lumber and wood products
Stone, clay, and glass products
Electronics, electric equipment,
excluding computers

Millions of dollars

Change from 1993
(Percent)

$408.7
109.5
70.3
48.9

160
4
10
–32

30.9
19.9
14.9
6.7
5.9

–1
15
365
99
3

5.8

–38

Table 2

New Mexico’s Top Ten Merchandise Export Industries to Mexico
(1994 Year-to-Date)
Millions of dollars
Industrial machinery,
computer equipment
Oil and gas extraction
Electronics, electric equipment,
excluding computers
Chemicals and allied products
Apparel and other textile products
Agricultural production—crops
Food and food products
Lumber and wood products
Instruments and related products
Rubber and miscellaneous
plastic products

$28.7
21.1

111
81

14.7
12.9
6.9
5.3
4.1
2.7
.9

– 48
37
92432
72
43
5
168

–1

ics, and chemicals. Texas has been the most
successful U.S. state in capitalizing on the expanding Mexican market. In 1994, 47 percent of
all goods exported to Mexico from the United
States were made in Texas.11 Figure 3 highlights
the steady growth in Texas merchandise exports
to Mexico, which increased 17 percent in 1994.
Texas’ top ten export industries to Mexico, listed
in Table 3, include electronics, transportation
equipment, computers, and metals. Texas exports
to Mexico represent a significant share of the
state’s economy. In 1993, for example, Texas’
$20.4 billion in merchandise exports to Mexico
constituted about 20 percent of the state’s total
manufacturing sales. Exports to Mexico, while
growing in all three District states, constitute a
larger percentage of the Texas economy than
New Mexico’s or Louisiana’s. Texas’ exports of
goods and services to Mexico, as listed in Table 4,
represent approximately 6 percent of gross
state product.12
NAFTA’s passage generated great enthusi-

ECONOMIC REVIEW FIRST QUARTER 1995

Change from 1993
(Percent)

Table 3

Texas’ Top Ten Merchandise Export Industries to Mexico
(1994 Year-to-Date)
Millions of dollars
Electronics, electric equipment,
excluding computers
Transportation equipment
Industrial machinery,
computer equipment
Fabricated metals
Chemicals and allied products
Instruments and related products
Rubber and miscellaneous
plastic products
Food and food products
Primary metals
Apparel and other textile products

and the peso’s devaluation. After increasing by an
estimated 4 percent in 1994, employment in
Eleventh District states is likely to grow about 2.5
percent in 1995.
A slower national economy and higher
interest rates than in 1994 will likely curb the
District’s economic expansion in 1995. After nearly
four years of U.S. economic expansion, interest
rates rose in 1994. Higher interest rates began to
slow the District’s construction industry in 1994,
curbing the region’s homebuilding boom.
Although growth will probably slow, many
positive factors driving the District economy
will continue in 1995 and should help the
region grow faster than the national average.
The Southwest’s relatively low cost of living
and doing business will continue to attract
firms. The cost of trucking goods within each
state will be cheaper in 1995, thanks to the
federally mandated deregulation of intrastate
trucking that went into effect on January 1. This
legislation is expected to have a large impact in
Texas, which had one of the most regulated
trucking markets in the nation.
Mexico’s economy is an important wildcard
in the Eleventh District’s economic forecast. At a
minimum, Mexicans are likely to purchase fewer
Eleventh District goods and services in 1995
because the peso devaluation makes U.S. goods
more expensive than they were in 1994. A positive result of the peso devaluation will be that
Eleventh District firms and consumers can purchase goods and services from Mexico more
cheaply.

Change from 1993
(Percent)

$5,799.2
3,757.4

13
20

2,397.6
1,514.2
1,430.5
1,125.1

23
28
25
7

1,067.5
1,009.5
1,031.8
727.1

47
16
17
23

Table 4

1994 Exports to Mexico as a Percentage of Gross State Product
Merchandise
exports
New Mexico
Louisiana
Texas

.3%

Service
exports

Total
exports

Miniscule

.3%

.7%

.1%

.8%

5.0%

1.0%

6.0%

asm for new trade with Mexico and may have
stimulated investment in anticipation of rising
trade. Many service-sector companies—such as
law, consulting, and transportation firms—reported opening or expanding offices designed to
attract Mexico-related business. Several cities expanded infrastructure investment to accommodate expected increases in trade with Mexico.
The recent peso devaluation may have
taken some of the momentum away from NAFTA
and delayed some investment directed at selling
to that market. The peso’s sudden devaluation
reversed a long-held managed exchange rate
policy. The policy change was costly to many
investors and has increased uncertainty for companies doing business south of the border. Over
the long term, however, Mexico remains a burgeoning market for goods and services, and the
District is well-positioned as a base for firms that
want to export to that market.

A sector-by-sector overview:
A broad-based expansion
The District’s expansion in 1994 was broadbased, with the exception of energy and defenserelated industries. Rapidly expanding service and
manufacturing industries helped feed a booming
construction sector. As shown in Figure 4, construction had the fastest employment growth.
Private service-producing industries, which include transportation, trade, business services,
finance, insurance, and real estate, posted the
second fastest job gains. The District’s manufacturing sector also had relatively strong employment growth, given the sector’s weak employment
growth nationwide over the past few years. The
mining sector continued to decline in 1994. Government employment growth accelerated to 3.5
percent in 1994, but was outpaced by the 4.1percent rate of the private-sector expansion.
While construction had the fastest employment growth, that sector’s employment is relatively small and added only 0.4 percentage points

Slower growth in 1995
Eleventh District economic expansion is
likely to slow slightly in 1995, although growth
should remain faster than the national average. A
favorable business climate, trucking deregulation, and long-term prospects for growing trade
with Mexico will not fully offset the effects of a
slowing national economy, higher interest rates,

strong. Apartment construction more than doubled
during the year. Single-family home building
slowed but remained relatively strong after surging in 1992 and 1993.

Figure 4

1994 Eleventh District Employment Growth
Percent
8

Manufacturing gains speed

Eleventh District manufacturers were
busy in 1994. Booming construction, a strong
national economy, and expanding exports
spurred heavy demand for District durable
goods. Several manufacturing industries reported that they could not expand fast enough
to meet demand, and their prices increased.
In April, heavy overtime pushed Eleventh District average weekly hours worked in manufacturing to a record 43.8, among the highest in
the nation. District manufacturing employment
increased 2.3 percent in 1994. While the growth
rate appears relatively slow compared with
other sectors of the economy, manufacturing
employment has been growing faster in District
states than in the nation for eight years.
Manufacturing in District states was boosted
by strong growth in construction supplies, automotive, and high-technology products. Production was strongest for construction-related
industries, such as brick, cement, fabricated metal,
steel, lumber, furniture, electrical products, and
glass. Despite continued defense industry reductions and layoffs in 1994, District production of
electronics, computers, and instruments remained
very strong. The Southwest is a growing heartland
for high-tech producers, such as computers, semiconductors, and telecommunications industries.
Worldwide demand for these products has spurred

–2

–4
Construction Private service- Government
producing

Manufacturing

Mining

SOURCES OF PRIMARY DATA: U.S. Bureau of Labor Statistics;
Federal Reserve Bank of Dallas.

to the District’s employment increase in 1994. As
shown in Figure 5, the service sector added the
bulk of new jobs in the Eleventh District in 1994,
contributing 2.7 percentage points to employment growth.

Construction booms
Construction employment surged 7.8 percent in 1994, posting its strongest growth since
1978. Booming nonresidential and apartment
construction more than offset slower growth in
homebuilding. Labor and materials shortages in
some areas suggested that capacity constraints
limited District construction growth.
Three huge, billion-dollar semiconductor
factories led the upswing in nonresidential construction. A new Intel factory was under construction in Rio Rancho, New Mexico, and Motorola
and Advanced Micro Devices built factories in
Austin. Construction of petroleum refining facilities also was brisk in 1994, driven by heavy
demand and regulations. Some construction was
necessary to bring refineries into compliance with
new regulations under the Clean Air Act, parts of
which took effect at the end of 1994. The demise
of the proposed Btu13 tax reduced uncertainty and
stimulated building at several refineries along the
Gulf Coast.
Retail and restaurant construction also picked
up in 1994. Demand was heavy for retail space
large enough to house warehouses, known as
“supercenters,” as was demand for restaurant
space. Growth of gambling-related tourism in
Louisiana boosted construction of hotels, restaurants, and casinos there.
Although rising interest rates slowed growth
in 1994, District residential construction remained

FEDERAL RESERVE BANK OF DALLAS

Figure 5

1994 Employment Growth by Sector
As a Percentage of Total Employment
Percent
4.5
4
3.5
3
2.5
2
1.5
1
.5
0
–.5
Total

Private service- Government
producing

Construction Manufacturing

Mining

SOURCES OF PRIMARY DATA: U.S. Bureau of Labor Statistics;
Federal Reserve Bank of Dallas.

ECONOMIC REVIEW FIRST QUARTER 1995

All Three Eleventh District States Grew Faster than the Nation
Louisiana, Texas, and New Mexico each contributed to
the Eleventh District’s strong performance in 1994. Employment in all three District states grew faster than the national
average of 3.1 percent. As shown in Figure A, employment
growth was strongest in Louisiana and New Mexico. Rapid
growth of Louisiana’s casino industry led to a 5.6-percent
employment increase in 1994, after a 3-percent rise in 1993.
In New Mexico, rising exports and strong growth of high-tech
industries helped boost job growth 5.3 percent in the past
year. Both Louisiana and New Mexico posted the strongest job
growth since 1978. The Texas economy also grew strongly in
1994, with employment increasing 3.5 percent. Expanding
exports boosted employment growth in manufacturing and
services in the state.
While employment growth was strong in all three District states, population growth has been more uneven. Population growth in Texas and New Mexico has been much stronger
than in Louisiana. Between April 1, 1990, and July 1, 1994,
population increased 9.1 percent in New Mexico, 8.2 percent
in Texas, and 2.2 percent in Louisiana. All three states had a
very high birth rate, but Texas and New Mexico had a large
influx of people moving into the state. More people moved out
of Louisiana than moved into the state, however.

Figure A

Total Nonfarm Employment
Index, January 1993 = 100
112
New Mexico
Louisiana
Texas
United States

110
108
106
104
102
100
98

1993

1994

Twenty-five percent of New Mexico workers are employed
by the government, mostly at federal research and defense
labs in Los Alamos and Sandia. So far, New Mexico has
escaped major defense cuts because the state’s defense
industries focus more on research and development than
on procurement.

Louisiana hits a jackpot
Despite its population decline, the Louisiana economy
roared in 1994, with the fastest employment growth in more
than fifteen years. Louisiana’s economic growth had been
sluggish since the oil bust in 1986, but in 1994 its employment accelerated to one of the fastest growth rates in the
nation. Much of the state’s rapid growth can be attributed to
Louisiana’s gamble on the casino industry. Renewed strength
in energy-related manufacturing and services also boosted the
state’s economy.
Development of the casino industry has spurred growth
in the state’s construction, manufacturing, and service sectors.
In 1994, 26.5 million tourists visited Louisiana,1 bolstering
demand for hotels and restaurants. Building of hotels, restaurants, and casinos led to a 7.9-percent jump in construction
employment in 1994, while construction of riverboats was a
catalyst for growth in the state’s manufacturing sector.
Louisiana’s energy industry also had a very good year,
as the state benefited from particularly strong demand for
petrochemicals and drilling activity in the Gulf of Mexico.
Louisiana provides most of the service activity for rigs in the
Gulf — a very lucrative industry in the past year.

New Mexico: The District’s perennial leader
The New Mexico economy continued its solid expansion in 1994. For several years, rapidly growing high-tech
industries have given New Mexico one of the nation’s fastest
rates of employment growth. New Mexico’s economy also has
benefited from a large growing government sector, including a
defense industry that is relatively stable compared with other
states.
New Mexico’s growing nexus of telecommunication and
computer industries has spurred rapid growth in the construction, manufacturing, and service sectors. Much of the state’s
growth has been in Albuquerque and Rio Rancho, in the semiconductor and electronic equipment industries.
New Mexico’s large public sector accelerated in 1994,
despite slight reductions in federal government employment.

Mighty Texas continues its solid expansion
Texas is by far the District’s largest state. With 18.4
million residents, Texas surpassed New York in 1994 to
become the nation’s second most populous state.2 The Texas
economy grew strongly in 1994, thanks to continued expansion of high-tech industries and healthy export growth.
The growth in high-tech industries is reflected in the
state’s manufacturing and construction sectors. Austin—home
of two of the largest microchip manufacturers in the world,
Motorola, Inc. and Advanced Micro Devices—is also home to
the world’s leading producer of wafer fabrications systems,
Applied Materials.3 Expansion of these and other computerrelated manufacturers has continued to attract other high-tech
firms and suppliers. Construction of manufacturing and
research facilities and homes in Austin absorbed the area’s
labor force and stimulated demand for the state’s construction
materials. Healthy expansion of high-technology industries is
not limited to Austin. The Houston economy is benefiting from
the strong growth of Compaq, which has become second only
to IBM as the largest computer producer. Vibrant growth of
telecommunications manufacturers in Richardson (near
Dallas) also has stimulated the state’s economy.
Last year, Texas’ service sector continued its solid
expansion despite slower growth in tourism and health care.
Restructuring at hospitals and other health service organizations hit Texas’ economy relatively harder than other District
states because of the industry’s size in the state. Texas has a
large health research and biotechnology industry and exports
many health services to international visitors. A decline in
Texas’ tourism industry also slowed service growth. The
state’s tourism industry received heavy competition from
Louisiana’s thriving casino industry in 1994, reducing demand
for hotels and tourist attractions.
1
2
3

Louisiana Department of Culture, Recreation, and Tourism.
California is the most populous state.
Sharp (1993).

expansion of research facilities and construction
of huge factories in Texas and New Mexico. Many
California firms have relocated to the Eleventh
District to be close to these large manufacturers
and research facilities.
Strong worldwide demand for District refining, petrochemicals, and oil field equipment and
services held energy-related manufacturing
steady despite weaknesses in oil and gas extraction. As major refining centers, Texas and Louisiana are the only U.S. states that export large
quantities of energy products to other parts of
the country—particularly the East Coast. Demand
for these products was heavy all year, and capacity utilization at regional refineries was high.
However, changing regulations concerning the
introduction of reformulated gasolines under
the Clean Air Act kept profits volatile and generally weak. Petrochemical production was
extremely strong and highly profitable in 1994.
The recovery of the international economy and
strong national growth improved the market
for Gulf Coast petrochemicals, which led to
high capacity utilization, low inventories, and
six rounds of price increases for basic chemicals
such as ethylene and propylene.

record levels and increased employment at hotels,
bars, restaurants, and other tourist attractions.
Not all District service industries are expanding rapidly, however. Employment in health
services continued to decelerate in 1994, growing
just 4.1 percent after increases of 4.5 percent in
1993, 4.7 in 1992, and an average 6.3 percent per
year between 1987 and 1991. Competition from
health maintenance organizations (HMOs) and
proposals for national health insurance have
encouraged health service companies across the
nation to restructure. Several hospitals in District
states reported job losses after cost-cutting led to
more outpatient care.
Continued consolidations and restructuring reduced employment slightly at financial
services firms in District states. Banks in Louisiana, New Mexico, and Texas are in good
financial shape, however, and loan growth was
strong in 1994.14

The energy industry continues to decline15
The energy industry declined in 1994,
continuing a trend that started in 1982. Dwindling reserves led major companies to turn
away from oil exploration in the District— and
the United States —which shrank the region’s
energy sector. In 1994, District oil and gas
employment fell 3 percent. Although the sector’s
employment rose in Louisiana and only declined
slightly in New Mexico, Texas lost energyrelated jobs, possibly because the state is headquarters for several major oil and gas companies
that have been restructuring and downsizing.
Although the District economy still is tied to
swings in oil and gas prices, the effects of those
swings have diminished in recent years.16
Low oil and natural gas prices contributed
to weakness in the energy sector in 1994. Real
oil prices at the start of 1994 were at pre-Araboil-embargo levels of 1973. Oil prices strengthened during 1994, as the global recovery and
strong national expansion continued. A declining dollar also contributed to upward pressure
on oil prices. Still, West Texas Intermediate
crude oil averaged just over $17 per barrel in
1994, relatively low compared with prices over
the past several years.
In contrast, natural gas prices were very
strong at the start of 1994, after one of the coldest
winters of the twentieth century. Prices weakened
during the year, however, falling to $1.47 per
million Btu in November, the lowest November
price since 1986. Large supplies, weak demand,
and competition with low oil-product prices
helped keep natural gas prices relatively low
during the year.

The service sector accelerates
Strong growth in communications, transportation, retail and wholesale trade, and business services, along with growing trade with
Mexico, stimulated the District service sector in
1994. After several years of restructuring and
downsizing, most industries resumed hiring in
1993, spurring broad-based expansion of the
service sector in 1994. After a 3.7-percent increase
in 1993, private service-sector employment growth
accelerated to 4.4 percent in 1994.
The sector’s strongest job growth was at
business service firms that had heavy demand for
temporary, or just-in-time, employees. Employment also grew strongly at District transportation
firms, as NAFTA encouraged firms to expand their
air cargo, trucking, and warehouse facilities. District cargo firms reported increased shipments for
all modes of transportation, including intermodal
shipping, which is a combination of carriers, such
as trucking and air. Growing U.S.–Latin American
trade also helped boost expansion of the District’s
telemarketing industry because of the region’s
large bilingual population and location in the
Central time zone.
Other fast-growing District services include
wholesale and retail trade employment, particularly in building materials, automotive, and eating
and drinking establishments. Recent expansion of
gambling facilities in Louisiana boosted tourism to

FEDERAL RESERVE BANK OF DALLAS

ECONOMIC REVIEW FIRST QUARTER 1995

Conclusion

Despite comparatively weak energy prices,
drilling activity in District states increased 7.3
percent in 1994. One reason drilling remained
strong may have been new technologies that
lowered drilling costs and made drilling more
attractive at lower prices. Producers can use new
seismic exploration technologies to look for oil
and natural gas in previously unexplored salt
structures. This new capability greatly reduces the
cost of drilling in these areas and has spurred a
tremendous amount of drilling activity in the Gulf
of Mexico, the site of many of the region’s most
productive wells.

Economic growth in Eleventh District states,
once dependent on a prominent energy industry,
today is driven by a relatively low cost of living
and growing trade with Mexico. In 1994, NAFTA
and a robust national economy also helped the
three District states attract new business and gain
employment faster than the national average.
After a strong year in 1994, economic growth
in Louisiana, New Mexico, and Texas is likely to
slow in 1995. The national economic slowdown
and higher interest rates than in 1994 are expected
to inhibit employment growth in District states.
The diminished value of the peso and continued
political uncertainty in Mexico also are likely to
restrain the region’s economic growth in 1995.
Despite these negative factors, however, the
Eleventh District will probably remain one of the
fastest growing areas in the country.

Government employment
growth accelerates
While the District’s government sector has
grown more slowly than the rest of the economy
for the past three years, employment growth in
the sector has been accelerating despite continued reductions at the federal level. In 1994,
government employment in District states increased 3.5 percent, after rising 2.4 percent in
1993.
State and local government employment
rose in all three District states in 1994. The
strongest growth occurred in Texas, where courtordered improvements in prisons and mental
health facilities contributed to a 4.7-percent rise in
state government employment.
Federal government employment in Eleventh District states held steady in 1994, after
declining in 1993 and 1992. Defense reductions in
New Mexico and Texas cut the federal government’s employment of civilians in those states,
although such employment increased 2.2 percent
in Louisiana.

Notes

Agricultural surprises
For Southwest agriculture, 1994 was a year
of surprises: unexpectedly good crop and livestock production after very dry conditions in
some areas early in the year, a steep and sudden
drop in beef prices in the spring, and at year’s end,
a good harvest—particularly from irrigated fields—
and the highest harvest-time prices for cotton in
fifteen years.17 With low prices for livestock
products, 1994 farm income is expected to be
lower than in 1993.
The increasingly global marketplace is boosting demand for District agricultural products. This
year, producers benefited as strong worldwide
demand pushed up cotton prices after crop losses
in Pakistan and India. NAFTA stimulated demand
for many District products, including livestock,
animal products, sugar cane, soybeans, grains,
and feeds.

Research by Keith Phillips and editing by Rhonda
Harris have contributed greatly to this article. The article
also benefited from analysis and comments by Steve
Brown, Bill Gilmer, Evan Koenig, Lori Taylor, Lucinda
Vargas, and Mine Yücel. Whitney Andrew and Michelle
Thomas provided excellent research assistance.
The Eleventh District includes northern Louisiana,
southern New Mexico, and Texas. This analysis,
however, is based on data for the entire states of
Louisiana, New Mexico, and Texas.
Nationwide capacity constraints, coupled with economic expansion in excess of the natural rate of
growth, prompted the Federal Reserve to raise interest
rates six times in 1994. Over the business cycle,
market forces also push up interest rates.
This record is based on the growth rate of jobs from
December to December each year. Based on the percentage change in the twelve-month annual average,
District employment has grown more strongly than the
nation for five consecutive years.
For further discussion of the Southwest business
climate, see Brown and Anderson (1988).
For the past two decades, Louisiana, New Mexico, and
Texas per capita state and local tax burdens have
been below the national average, according to the
Advisory Commission on Intergovernmental Relations.
The University of Texas at Austin has one of the largest
installed bases of MacIntosh computers in the world,
making graduates strong candidates for high-tech jobs.
In the past two decades, about two-thirds of Austin’s
manufacturing relocations have come from metropolitan San Jose, California.
At the end of 1993, the average cost of a home in
Santa Clara County, California—the heart of Silicon
Valley—was $252,264. The average cost of a house in
Austin was $114,800.

The George –Taylor article, also in this issue, concentrates on the average effects Texas exports to
Mexico have had on Texas employment between
1987 and 1994. The authors conclude that the
dramatic growth in merchandise exports between
1987 and 1994 accounts for only a small fraction of
the employment growth in Texas. As they indicate,
their analysis describes only part of the total trade
picture. In particular, they were unable to measure
the effects of increasing trade in services, merchandise imports from Mexico, and any spillovers from
increasing exports to Mexico from U.S. states other
than Texas. In this article, I use data on U.S. and
Texas trade flows and anecdotal information to
discuss the broader trade picture.

16
17

References
Anderson, Carl G. (1995), “Will World Cotton Supply
Recover this Year?” Cotton Market Comments, Texas
Agricultural Extension Service, Texas A&M University
System, February 20.
——— (1994), “The Market Was Right!” Cotton Market
Comments, Texas Agricultural Extension Service, Texas
A&M University System, December 14.

Adjustments to the data from the U.S. Census Bureau,
Foreign Trade Division, were performed by the Massachusetts Institute for Social and Economic Research
(MISER). Exports are measured by state of origin;
products are measured from the state where they
begin the journey to point of export. This measure may
attribute goods to the state where they are warehoused prior to beginning the journey to point of
export. In the case of Southwest exports to Mexico,
this measure is likely to overstate exports.
An alternative measure available from MISER calculates state exports to Mexico from the ZIP code of
origin. The ZIP code measure may attribute an export
from the ZIP code of the state where the manufacturer
is headquartered, rather than the ZIP code of the
manufacturing facility. In the case of the Southwest,
this measure is likely to understate exports. Based on
the ZIP code of origin measure, Louisiana exports to
Mexico increased 106.2 percent, New Mexico exports
to Mexico declined 10.4 percent, and Texas exports to
Mexico increased 10.9 percent in 1994.
This statement is based on data from the U.S. Census
Bureau, Foreign Trade Division, adjusted by MISER.
Gross state product data are Federal Reserve Bank of
Dallas estimates for 1994. Merchandise exports are
from MISER. Services are assumed to equal 20 percent of merchandise exports, which is the average
percentage of U.S. service exports to Mexico, based
on estimates from the U.S. Department of Commerce,
Economics and Statistics Administration, Bureau of
Economic Analysis. (Total U.S. service exports to the
world average 40 percent of merchandise exports.)
While service exports are likely to vary by state, Eleventh District states are closer to Mexico and would be
expected to export more services than other states.
Consequently, estimates for services are likely to
understate actual service-sector exports.
Btu, or British thermal unit, is the quantity of energy
required to raise the temperature of one pound of
water one degree Fahrenheit at or near 39.2 degrees
Fahrenheit.
Clair (1995).

FEDERAL RESERVE BANK OF DALLAS

Research by Steve Brown, Bill Gilmer, and Mine Yücel
contributed to this section.
Brown and Yücel (forthcoming).
Anderson (1995).

Barkema, Alan D. (1994), “The New Mexico Economy: Leading the League” (Paper presented at the Federal Reserve
Bank of Kansas City’s New Mexico Economic Forum, September 29, Albuquerque, New Mexico, September 29.)
Brown, Stephen P. A., and Mine K. Yücel (forthcoming),
“Energy Prices and State Economic Performance,”
Federal Reserve Bank of Dallas Economic Review.
———, and Lea Anderson (1988), “The Future of the
Southwest Economy,” Federal Reserve Bank of Dallas
Southwest Economy, November.
Clair, Robert T. (1995), “Is the Southwest Lending Boom
Too Much of a Good Thing?” Federal Reserve Bank of
Dallas Southwest Economy, Issue 1.
Davis, Ernest E., and Shari L. Popp (1994), “1994: Beef
Cattle’s Record Price Crash!” Texas Livestock Market
Comments, Texas Agricultural Extension Service, Texas
A&M University System, December 13.
George, Kelly, and Lori L. Taylor (1995), “The Role of
Merchandise Exports to Mexico in the Pattern of Texas
Employment,” Federal Reserve Bank of Dallas Economic
Review, First Quarter, 22–30.
Gilmer, Robert W. (1994), “Houston’s Economy Continues
to Improve,” Federal Reserve Bank of Dallas, Houston
Branch Houston Business, September.
McDonald, Brian (1994), “Economic Outlook: Good and
Getting Better,” New Mexico Business Journal, December.
Phillips, Keith R. (1994), “Southwest Expansion to Continue in 1995,” Federal Reserve Bank of Dallas Southwest
Economy, Issue 5.
Sharp, John (1994), “Telecom Corridor,” Fiscal Notes
(Austin: Office of Texas Comptroller of Public Accounts,
December).

ECONOMIC REVIEW FIRST QUARTER 1995

——— (1993), Texas Regional Outlook (Austin: Office of
Texas Comptroller of Public Accounts, October).

of Dallas Business Frontier, El Paso Branch, November/
December.

U. S. Department of Commerce, Bureau of the Census,
Economics and Statistics Administration (1994), “Texas
Now Second Largest State,” Press release CB94-204
(Washington, D.C., December 28).

——— (1994b), “The Changing Dynamics of the
Maquiladora Industry, Part 1” Federal Reserve Bank of
Dallas, El Paso Branch Business Frontier, September/
October.

Vargas, Lucinda (1994a), “The Changing Dynamics of
the Maquiladora Industry, Part 2” Federal Reserve Bank

Full text of Review (Federal Reserve Bank of Dallas) : First Quarter 1995

FRASER