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HoustonBusiness
A Perspective on the Houston Economy
FEDERAL RESERVE BANK OF DALLAS

•

HOUSTON BRANCH

•

A New Index of Coincident
Economic Activity for Houston

This article
introduces a new
tool to monitor the
Houston economy. It
is a coincident index
of local economic
activity based on new
methods to combine
and weight key
economic indicators.

N

o matter what your level
of expertise, following the movements of the local economy can
be a difficult and sometimes
frustrating experience. Numerous data series are reported, and
they often provide conflicting
signals of the economy’s direction. Data are reported by different frequencies — monthly,
quarterly, annually. And they
are often revised, changing our
picture of where we have been,
as well as where we are or
where we are headed. Some
data lag changes in general
economic activity, while other
data lead and some are contemporaneous, or coincident.
One way to cut through the
noise and discern the economy’s
current status is to build an
index of coincident economic
activity. At the national level,
gross domestic product (GDP)
is reported months after events
are over. At the metro or substate level, we don’t get a report
on such broad aggregates, ex-

APRIL 2003

cept for an annual report on
personal income. To build a
guide to the current state of the
economy, key data series or
indicators are selected and
combined into an index as a
weighted average.
This article introduces a new
tool to monitor the Houston
economy. It is a coincident index
of local economic activity based
on new methods to combine
and weight key economic indicators. The Houston indicators
are establishment employment,
unemployment rate, real wages
and real retail sales. The index
extracts from each series the
information relevant to the current state of the Houston economy and combines that information into an index that reflects
overall economic conditions.
Coincident Indexes
In 1937, Wesley C. Mitchell
and Arthur F. Burns of the
National Bureau of Economic
Research (NBER) developed a
list of 487 indicators that led,
lagged or were coincident with
the business cycle. The project
embraced the concept that there
is a business cycle, or reference
cycle, that cannot be observed
directly but can be measured

Figure 1
Coincident Index of Economic Indicators for Houston, 1981–2003

by the consistent movement of
many economic variables as
the phases of growth change.
In the 1950s and 1960s, NBER
researchers extended the concept by constructing indexes
from these indicators, weighting and adding together variables that consistently led,
lagged or kept pace with the
business cycle. The Index of
Leading Indicators became the
most widely followed of the
indexes, probably because of
its ability to forecast change in
the business cycle from growth
to contraction and vice versa.
But for many years, the Conference Board (and before that
the Bureau of Economic Analysis) has regularly published
leading, lagging and coincident
indexes. The coincident index
has developed a good track
record of having its peak value
fall within three months of the
official business peaks selected
by NBER’s Business Cycle Dating
Committee. Its ability to match
the committee’s troughs is even
better. The coincident indicators
point to a likely trough in the
2001 recession in November
2001 and expansion through
much of 2002, although the
index has been flat over the
past six months. Similar indexes
have been built for states,
regions and metro areas.
In recent years a new approach, suggested by the academics Stock and Watson,1 has
evolved for the construction
and interpretation of leading
and coincident indexes. 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

Index, July 1992 = 100
170

150

130

110

90

70

50
July July July July July July July July July July July July July July July July July July July July July July
’81 ’82 ’83 ’84 ’85 ’86 ’87 ’88 ’89 ’90 ’91 ’92 ’93 ’94 ’95 ’96 ’97 ’98 ’99 ’00 ’01 ’02

to measure various aspects of
their mental agility and cognitive powers, the intercorrelation
among these tests may suggest
a single, weighted average of
these tests 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 Houston
The Stock–Watson methodology has been widely applied
at the state and substate levels.2
Four seasonally adjusted variables were selected to build a
coincident index for Houston:

establishment employment, unemployment rate, real wages
and real retail sales. The two employment variables 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. The different frequencies cause no
significant problem for history,
but, as discussed below, they
affect interpretation of the most
recent economic observations.
Figure 1 shows the computed
index of coincident economic
activity for Houston. The curve
has been retrended and scaled
to historical growth in metroarea regional personal income,
which is the broadest available
measure of substate economic
activity and is reported with a
delay of two years. The most
recent movements of the selected
indicators are all found to coincide except for the unemployment rate, which moves one
month later. Higher lagged values of all variables demonstrate
significant idiosyncratic noise
unrelated to current economic
conditions.
Cumulative weighted multipliers suggest the following
weighting scheme for the variables: employment, 0.468; real
wages, 0.341; unemployment
rate, 0.110; and real retail sales,

Table 1
Dating the Business Cycle in Houston

0.081. The model’s dynamic
properties are based on the
assumption that the business
cycle is driven by random shocks
to the local economy, and the
Houston economy shows great
persistence or stability as the
shocks slowly die out. Over the
first quarter after a shock occurs
(such as a large bankruptcy or an
oil price change), only 30 percent of the shock is absorbed by
the local economy. The smoothness of the curve in Figure 1 is
a product of this persistence.
Interpreting Results
The curve broadly reflects
economic history as we understand it: the double-dip oil recessions of the 1980s, the long
period of stagnation in the early
1990s and the current slowdown,
which has been under way since
early 2001. Table 1 shows the
dates of Houston’s business cycle
peaks and troughs indicated by
the new index. The 1980s saw
two distinct and well-defined
cycles. The March 1982 peak
occurred as OPEC failed in an
attempted oil price increase and
the rig count began to collapse.
The 1984 peak and the following recession were exacerbated
by the collapse of both Texas
real estate and banking.
In the 1990s and early 2000s,
the story is one of two prolonged pauses in economic
growth, with the second perhaps
being a mild recession.3 The first
pause began in December 1990
in anticipation of a peak in oil
prices following the first Gulf
War. It was prolonged by weak
natural gas prices and poor oil
field conditions. Expansion
resumed in February 1992 after
about 14 months of no significant expansion or contraction
in the local economy.
The current slowdown began
with a pause (or perhaps a peak)
in April 2001, and after 22
months there is no clear sign of

resumed progress. If April 2001
is a peak, indicating that Houston has entered its first recession since the 1980s, the following recession has been very
mild. At no time has the index
declined by more than 0.8 percent from the peak. However,
unlike the pause of the early
1990s — when the index waffled back and forth, first above
and then below the previous
peak— the current index has
been below the April 2001
value since the pause began.
The index reported here contains revised North American
Industry Classification System
(NAICS) employment and wage
data back to 1996, as well as
the rebenchmarked establishment employment data for
Houston made available each
spring. Our mix of monthly
and quarterly data, with the
quarterly data available only
with a lag of several quarters,
does not affect the computations significantly and certainly
does not change our interpretation of history. The most recent
data are affected, however. For
example, our index’s current
estimates contain employment
and unemployment data through
February of this year but retail
sales data only through the third
quarter of 2002 and wage data
only through the first quarter of
2002. We operate on less and
less information as the estimate
becomes more current.
The most widely followed
series on the Houston economy
is the establishment employment
data, released each month along
with the unemployment rate.
This is all the information available in the computed index
since the third quarter of 2002,
and based on the weighting
scheme, the index contains only
about 55 percent of the information we will eventually integrate into it. In the second and
third quarters of 2002, we still

March 1982

Peak

August 1983

Trough

November 1984

Peak

January 1987

Trough

December 1990

Pause Begins

February 1992

Growth Resumes

April 2001

Peak? Pause?

have only 63 percent of the
information ultimately available
and must go back to the first
quarter of 2002 to arrive at a
full index. So as you look at
the flat line stretching out since
early 2002, it is essential to
remember that the picture can
still be modified by additional
information and revision.
Whatever the shortcomings
in the data, the Houston index
of coincident economic activity
is a valuable tool to summarize
what we know about the state
of the local economy. It systematically integrates the latest data
available, allows the entry of
additional data as they become
available and weights the data
according to their ability to help
us interpret current conditions.
— Jesús Cañas
Robert W. Gilmer
Keith Phillips
Cañas is an economic analyst at
the El Paso Branch of the Federal
Reserve Bank of Dallas. Phillips is
a senior economist at the Bank’s
San Antonio Branch.

Notes
1

2

3

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.
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.
Robert W. Gilmer and Iram Siddik
(2003), “The Houston Business Cycle
Since the Oil Bust,” Federal Reserve
Bank of Dallas Houston Business,
January.

Houston

T

he end of winter brought
lots of action in Houston’s
energy sector — war in the Persian Gulf, depleted inventories,
and soaring oil and natural gas
prices. The result has been a
mix of good and bad news for
different energy sectors, but the
outlook for domestic drilling has
definitely improved. Perhaps a
rapid expansion of domestic
drilling can finally lead Houston’s economy upward after 22
months of no growth.
Retail Sales and Autos
Retailers are still not seeing
large purchases, with buying
confined to necessities. Department, sporting goods and clothing stores all continue to run
behind plan, with any good
news coming out of discount
chains. War seemed to have little
effect on consumer purchases.
Auto sales picked up sharply
in February, averaging 12.3 percent higher than the same month
last year. However, combined
with a weak January, sales were
up only 1.2 percent for the first
two months of the year. Through
March, the combined 1.2 percent increase seemed a better
indicator of the market’s current direction.
Oil and Natural Gas Prices
Spot prices for West Texas
Intermediate stayed above $35
per barrel from mid-February
until the outbreak of war in
Iraq. The situation had lots of
moving parts—the hangover
from the Venezuelan general
strike, civil unrest in Nigeria
and OPEC’s overproduction in
advance of war. Prices quickly
moved under $30 with signs of
a quick resolution to the war,

BeigeBook

April 2003

the arrival of an armada of
tankers from Saudi Arabia and
clear indications that crude
inventories are being rebuilt.
Cold weather played havoc
with natural gas prices, briefly
pushing them as high as $16
per thousand cubic feet (Mcf)
and pulling inventories to levels
50 percent below the five-year
average. Natural gas prices
have now settled into a range of
$4 – $5, and lower inventories
seem to have finally convinced
oil and gas producers that
higher prices are here to stay.
Oil and Gas Services and Machinery
Over the past quarter, the
domestic rig count has broken
out of the 850 range it had held
for nearly a year and has now
added over 100 rigs. Oil service
respondents seemed convinced
that the upward trend would
last a while longer, with as many
as 1,200 rigs working before
year-end. Drilling so far has
been directed to natural gas, and
projects are relatively inexpensive— shallow and onshore.
But calls from customers are
now indicating riskier and
more expensive projects ahead.
International work, largely
directed to oil, has not picked
up; the downside risks for oil
markets are seen as much
greater than for natural gas.
Refining
Refiners have run at high
levels of capacity utilization.
Reluctant to lose their excellent

margins, they postponed or
minimized the normal spring
maintenance. Margins spiked
to high levels in February and
fell back slowly in March.
Gasoline prices have come
down but are expected to
remain high through the summer as low inventories slowly
rebuild. Gasoline demand was
strong throughout the winter.
Petrochemicals
High energy prices hit the
chemical industry hard. A number of plants briefly shut down
in the face of high natural gas
prices, and all struggled to pass
through the higher energy costs.
As energy prices rose, price
increases occurred up and down
the product chain for plastics.
As natural gas prices fell back
to $5 per Mcf in early April, a
number of plants came back
on-line.
Housing
Sales of both new and existing homes eased early in the
year, with sales flat to down
slightly compared with the previous year. War jitters, combined with concerns about the
economy, left respondents unsure of the housing market’s
near-term direction. The apartment market continues to deteriorate, as low interest rates
make home ownership more
attractive. Flat rents, falling
occupancy and barely positive
absorption all indicate the
apartment market’s struggles.

For more information or copies of this publication, contact Bill Gilmer at
(713) 652-1546 or bill.gilmer@dal.frb.org, or write Bill Gilmer, Houston Branch,
Federal Reserve Bank of Dallas, P.O. Box 2578, Houston, TX 77252. This publication is
also available on the Internet at www.dallasfed.org.
The views expressed are those of the authors and do not necessarily reflect the positions
of the Federal Reserve Bank of Dallas or the Federal Reserve System.