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BusinessFrontier
FEDERAL RESERVE BANK OF DALLAS

Composite Index:
A New Measure
of El Paso’s
Economy
The El Paso index
of coincident
economic activity
is a valuable
new tool for
understanding
local economic
performance.
The index
systematically
integrates the latest
movements in four
broad regional
economic indicators —
employment,
unemployment rate,
wages and retail sales.

EL PASO BRANCH

ISSUE 1 • 2003

H

ow’s the economy doing?
This is a common question, although it is not always clear which economic measure provides the best
answer. Should we look at the unemployment rate or at
employment growth? Perhaps a broader measure such
as gross domestic product or personal income may be
a better indicator, even if it is less timely. Further, different measures often send conflicting signals about current economic conditions. No matter what your level of
expertise, following movements of the local economy
is a difficult and sometimes frustrating experience.
One way to solve this dilemma is to design a composite index that aggregates the movements of several key
economic indicators and thus represents a single summary statistic that tracks the current state of the economy.
The composite index allows researchers to identify when
the economy is in an expansionary or recessionary
phase of the business cycle.
This article introduces a coincident index of the El
Paso economy based on new methods to combine and
weight key economic indicators. The El Paso indicators
used in the index are nonagricultural employment, the
unemployment rate, inflation-adjusted wages and inflation-adjusted retail sales. The statistical technique we use
chooses the weights on each indicator based on its comovement with the other indicators and combines that
information into an index that best reflects overall economic conditions.

COINCIDENT INDEXES
In 1930, the National Bureau of Economic Research
(NBER) pioneered business cycle research, sponsoring
a team led by Wesley C. Mitchell and Arthur F. Burns.
They studied 487 economic variables to see if turning
points in the variables persistently led, coincided with or
lagged turning points in the U.S. business cycle. In later
research, conducted in the 1950s and 1960s, NBER

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

Chart 1

Coincident Index of Economic Indicators
for El Paso, 1979–2003
Index, July 1992 = 100
130
120
110
100
90
80
70
60
July July July July July July July July July July July July July
’79 ’81 ’83 ’85 ’87 ’89 ’91 ’93 ’95 ’97 ’99 ’01 ’03
SOURCE: Authors’ calculations.

researchers combined the best series into composite indexes of leading, coincident and lagging
economic indicators. In the early 1960s, the U.S.
Department of Commerce took over the production of the composite indexes, and since 1995 the
Conference Board, a business membership and research organization, has regularly published leading and coincident indexes for the U.S. economy.
In the late 1980s, NBER economists James
Stock and Mark Watson developed new composite
indexes of coincident and leading indexes for the
nation.1 The main contribution of their research
was the use of a statistical technique called the Kalman filter, which estimated the optimal weights on
the component indicators. The traditional composite index methodology did not attempt to estimate
optimal weights but simply applied equal weights
once the volatility in each series was standardized.
In contrast, Stock and Watson advance the notion
of the business cycle by statistically estimating the
weights on the component series that best identifies a single underlying factor that is time dependent and that best represents the co-movement in
the components. Thus, the index provides a better
definition of the underlying state of the economy.
Mathematically sophisticated, the general approach will be familiar to many social scientists as a
variant of principal components or factor analysis—statistical techniques designed to extract a
measure of some underlying, unobservable characteristic from a number of closely related variables.
For example, if we give a battery of tests to 100
people to measure various aspects of their mental
agility and cognitive powers, the intercorrelation
among these test scores may suggest a single,
weighted average of these scores that may reveal
an underlying or latent commonality called intelligence.

The principle used to build an index of coincident economic activity is similar, except the unobservable variable is the current state of the economy, and we substitute for the administered tests
the intercorrelation of various economic indicators
measured through time. Just as for intelligence, the
intercorrelation of economic indicators suggests the
weighting of the indicators that best represents the
state of the economy. Indicators will have behavior that reflects their contribution to the business
cycle as well as behavior that is idiosyncratic and
unrelated. Further, because the procedure is dynamic, estimates can be extracted of the underlying
statistical process, telling us about the stability of
the local economy in the face of external shocks.

AN INDEX FOR EL PASO
The Stock–Watson methodology has been widely applied at the state and substate levels.2 These
indexes were constructed using different components based on data availability and reliability. For
El Paso, the broadest, most reliable measures of the
economy are nonfarm employment, unemployment
rate, real wages and real retail sales. Employment
and the unemployment rate are reported monthly
with a lag of about one month, while the wage and
sales variables are reported quarterly with a lag of
approximately three quarters.
Chart 1 shows the computed index of coincident
economic activity for El Paso. The Stock and Watson methodology that we use creates an index that
defines business cycle swings in the economy but
not the long-term trend in economic growth. To estimate the trend rate of growth, we simply set the
trend in the index to equal the historical growth in
personal income. The movements in all economic
indicators but unemployment coincide with the
estimated coincident index. The unemployment rate,
however, lags the economy by one month.
The model’s optimal weighting process results
in employment and the unemployment rate getting
the greatest weight. Changes in employment represent 54.5 percent of the movement in the index,
while changes in the unemployment rate get a
weight of 32.5 percent. Given the reliability of the
employment series and the timeliness of both employment and the unemployment rate, these weights
are perceived as a positive for the model and
should reduce the impact of revisions caused by
the later incorporation of the quarterly data values
for retail sales and wages.

INTERPRETING RESULTS
At the national level, the Stock and Watson coincident index has had turning points that match
almost exactly with the official turning points of
the U.S. business cycle as determined indepen-

Chart 2

El Paso Economy Reflects U.S. Industrial
Production Double-Dip
Index, July 1979 = 100
210
190
170

El Paso economy

150
130
110

U.S. industrial
production–manufacturing

90
70
July July July July July July July July July July July July July
’79 ’81 ’83 ’85 ’87 ’89 ’91 ’93 ’95 ’97 ’99 ’01 ’03
SOURCES: Federal Reserve Board; authors’ calculations.

dently by the NBER Business Cycle Dating Committee.3 If the same relationship holds between
turning points in the El Paso Coincident Index and
the true turning points in the El Paso economy, then
the index can be used to define local recessions and
expansions.
According to broad movements in the coincident index, El Paso has experienced at least five
recessionary periods in the last 24 years. While the
economy turned down in October 2002, the data
are still subject to revision, so we hesitate to define this period as a recession until the data are
revised in early 2004. Historically, El Paso has followed the nation’s downturns: the oil recessions
of the 1980s, the long period of stagnation in the
early 1990s, and the current recessions and slow
recovery, under way since early 2001. It is also true
that the Sun City has experienced some business
cycle events of its own.
Regional business cycles are often caused by
their national counterparts, but for an international
economy like El Paso’s, a number of factors can
influence local expansion or decline. For example,
in the 1980s, recession in the Texas economy combined with financial and economic crises in Mexico
to adversely affect El Paso, as did another Mexican
peso crisis in 1995. The loss in value of the peso
relative to the dollar during these crises kept Mexican shoppers at home. This is important in El Paso,
where in 2000 Mexican shoppers accounted for
$500 million, or 7.6 percent of local retail sales.4
The most recent downturn in El Paso is largely
a product of the national economic downturn that
began in March 2001. The combination of national
recession and a strong dollar took a serious toll on
the U.S. industrial sector, and manufacturing was
by far the most seriously damaged of all sectors during the current downturn. Damage to the ma-

quiladora sector across northern Mexico followed
quickly on the heels of the U.S. industrial recession.
El Paso is the second largest U.S. land port, handling about 20 percent of total U.S.–Mexico land
trade—some $39 billion in 2002. Cross-border
traffic has been hurt by the maquiladora downturn,
as well as by both countries being in recession,
and damage to the El Paso economy has come
primarily through the maquiladora downturn.
The U.S. recession began in March 2001 and
ended in November of the same year. U.S. industrial production, however, entered a second stage
of decline in 2002, severe enough to pull the national economy down again, not into recession
but into a prolonged period of slow growth. The
double-dip pattern of the El Paso economy, however, bears a striking resemblance to the twice-negative pattern set by the industrial sector (Chart 2 ).
So far, there is no indication of recovery in the El
Paso Coincident Index, although recent stabilization in both the U.S. industrial sector and Mexican
maquiladora employment offer hope for recovery
in the near future.
The maquiladora industry is of special importance to the El Paso economy. Over the last
decade a rising number of rubber and plastics,
electronic and electrical equipment, and primary
metals companies have opened operations in El
Paso to serve as suppliers for the maquiladora
industry. Manufacturing activity south of the border has also positively influenced employment in
transportation, business and legal services.5 One
estimate is that a 10 percent increase in maquiladora output in a Mexican border city increases employment on the U.S. side of the border by 3 to 4 percent.6 Unfortunately, the formula
works equally well in reverse during periods of
maquiladora decline (Chart 3 ).

Chart 3

El Paso Economy Follows Maquiladora Industry
El Paso Coincident Index
July 1992 = 100

Thousands of workers
(seasonally adjusted)

140

300

130

250

120
110
100
90

El Paso economy

200
150

Ciudad Juárez
maquiladora employment

100

80
50

70
60

0
Jan. Jan. Jan. Jan. Jan. Jan. Jan. Jan. Jan. Jan. Jan. Jan.
’81 ’83 ’85 ’87 ’89 ’91 ’93 ’95 ’97 ’99 ’01 ’03

SOURCES: Instituto Nacional de Estadística, Geografía e Informática;
authors’ calculations.

SUMMARY

NOTES

The El Paso index of coincident economic
activity is a valuable new tool for understanding
local economic performance. The index systematically integrates the latest movements in four broad
regional economic indicators—employment, unemployment rate, wages and retail sales. Though
the basic data are still subject to revision, currently
the index suggests that after a recession in 2001
the El Paso economy began a recovery that, like
the U.S. industrial sector, may have stalled in late
2002. After weakness in the first half of 2003, the
El Paso economy is likely to improve in the second half if and when the U.S. industrial sector
picks up.
— Jesus Cañas
Robert W. Gilmer
Keith Phillips

The authors would like to thank Robert Crawley of the Texas
Workforce Commission for providing wage data for our coincident index, thus making it possible.
1
James H. Stock and Mark W. Watson (1989), “New Indexes of
Coincident and Leading Economic Indicators,” in NBER
Macroeconomics Annual, ed. Olivier J. Blanchard and Stanley Fischer (Cambridge, Mass.: MIT Press), pp. 351–95.
2
Alan Clayton-Matthews and James H. Stock (1998/1999), “An
Application of the Stock/Watson Index Methodology to the
Massachusetts Economy,” Journal of Economic and Social
Measurement, Vol. 25, Issue 3/4, pp. 183–233.
3
The NBER Business Cycle Dating Committee determines the
official dates for the beginning and end of national recessions. The peaks and troughs of the Conference Board’s
coincident index correspond exactly to the official recession
dates since 1973. The peaks and troughs of Stock and Watson’s index correspond to the official dates except for one
month’s difference at the trough in 1982.
4
Keith Phillips and Carlos Manzanares (2001), “Transportation
Infrastructure and the Border Economy,” in The Border Economy, Federal Reserve Bank of Dallas (June). Data updates by
Roberto Coronado.
5
Jesus Cañas (2002), “A Decade of Change: El Paso’s Economic
Transition of the 1990s,” Federal Reserve Bank of Dallas
Business Frontier, Issue 1.
6
Gordon H. Hanson (2001), “U.S.–Mexico Integration and
Regional Economies: Evidence from Border-City Pairs,” Journal of Urban Economics 50 (September), pp. 259–87.

All authors are with the Federal Reserve Bank of Dallas:
Cañas is an economic analyst (El Paso Branch), Gilmer
a senior economist and vice president (El Paso Branch)
and Phillips a senior economist (San Antonio Branch).

Maquiladora Downturn
Structural Change or Cyclical Factors?
A conference sponsored by the
El Paso and San Antonio Branches
Federal Reserve Bank of Dallas

E l

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BusinessFrontier
Business Frontier is published by the El Paso Branch of the
Federal Reserve Bank of Dallas. The views expressed are those
of the author and do not necessarily reflect the positions of the
Federal Reserve Bank of Dallas or the Federal Reserve System.

Mexico’s maquiladora industry saw its
biggest decline ever over the past two
years. Are structural changes or cyclical
factors the cause of this weakness? This
conference will examine the long-term
outlook for this important industry.

November 21, 2003
Sheraton Hotel
South Padre Island, Texas
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