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FEDERAL RESERVE BANK OF DALLAS
March 1990

•

ConOInlC

•

eVlew

Monetary Aggregates and
the Rate ofInflation
Joseph H. Haslag

Oil Prices and
Manufacturing Growth:
Their Contribution to
Houston}s Economic
Recovery
Robert W. Gilmer

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

Economic Review
Federal Reserve Bank
of Dallas
Robert H. Boykin
President and
Chief Executive Officer

William H. Wallace
First Vico President alld
Chlof Operating Officer

Harvey Rosenblum
Semor Vice President and
Oirector of Research

Gerald P. O'Driscoll, Jr.
Vice President and
Associate Director of Research

W. Michael Cox
Vice President end
Economic Advisor

Stephen P. A. Brown
ASSistant Vice President and
Senior Economist

Economists
National and International
John K. Hill
Robert T. Clair
Evan F. Koenig
Cara S. lown
Kenneth M. Emery
Joseph H. Haslag
Linda C. Hunter
Mark A. Wynne
Regional and Energy
Robert W. Gilmer
William C. Gruben
Mine K. YOcel
Keith R. Phillips
Lori L. Taylor
Fiona D. Sigalla
Editors
Rhonda Harris
Diana W. Palmer
Virginia M. Rogers
The Economic Review is published by the
Federal Reserve Bank of Dallas. 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.
Subscriptions are available free of charge.
Please send requests for single-copy and multiple-copy subscriptions, back issues, and address changes to the Public Affairs Department,
Federal Reserve Bank of Dallas, Station K, Dallas, Texas 75222, (2141651 -6289.
Articles may be reprinted on the condition
that the source IS credited and the Research Department is prOVided with a copy of the publication containing the reprinted material.

b

Contents
Pag 1

Money Aggregates and
the Rate ofInflation
Joseph H. Haslag

ome economi ts advocal focu ing les mphasis on
moneta lY aggrega l s b aus th I' lalio n hip of mo n ta lY
aggregates l th ulLimat gals f mo n lalY p Ii y is less
reliabl now than in the past. But the stabi lity of lh
relationship b lwe n m ney gr wth and inflalion is a lestable
hypothes is. J se ph H as lag inv stigates whelh I' mo n y
growth i urreml y as useful a pI' dicLO r of inflation a it
previous ly has bee n. H e l st thr e differ nl measur s f
mo ney growth: lhe mo n lalY l ase, Ml , and M2. Ha lag find
lhat th r latio n hip r main table ov r Lime.
Haslag al
find lh at bOlh th mon lary I a and M2
are usefu l in predi ting th behavior o f th infl ati n rat.
Informalion that i unique to Ml, how v r, make a
·tati ti ca lly in ignifi anl o ntributi n to predi cting infl atio n.

Pag 13

Oil Prices and
Manufacturing Growth:
Their Contribution to
Houston 's Economic
Recovery
Robert W. Gilmer

Th HUlon conomy w nt from b m to bust to
r ov IY during th 1980s. Exp tati ns o f o il pri e at 50
per barr I and hig h r in th lat '70s and ea rly '80 timulated
hundr cis of oi l-r lat d I roj clS in th are l. An o il-IXi
cle lin , how v 1', I cI lh e H ouston
onomy into a sharp
r ce i n lhat la l d from 1982 to 1986. The size of H USl n's
w rk for e shrunk I y m I' than 12 per nt wilh lh loss of
more than 200,000 job . Th lat '80s br ught r n w cI
e onomic expansi n, and Hou ton rega in d n arl y 120,000
job.
R bert W. Gi lm r xamin s th Huston
n mi
r ove lY and draw ix co nclu ions an ut lh city'
onomy
with re pect to lh busin ss ycl , th cI li ar, and th price of
oi l. H find s thaL w hil e th city's I' new d gr wth omes
primarily in th s rvi
tor, oi l and ga induslries wi ll
continu e LO play an imp rLant I' I in Houston 's futur .

..

Joseph H. Haslag
Economist
Federal Reserve Bank of Dallas

Monetary Aggregates and the Rate of Inflation
f mo n y is t have a ro l in the Feder·tJ
R serv 's p licy process, two fund amental
questi ns must b answ red. First, a a pr dictor
of infl atio n, i mon y growth still as us ful now as
in the past? eco nd , insofar a m ney remains a
us ful predict r o f infl ati o n, w hich measure of
mon y sh ulcl receive the m st 'lttenti n?
The Oep sito lY Institutio n D reg ul atio n and
Mon talY o ntro l Act f 1980 (OTDM CA) pres rib d r gul atolY c1Ylng s and permitted fin ancial
innova ti o ns. Each change potenti all y affe ted the
relati nship I twe n money growth and econ mi a tivity.1 Rec ntl y, some ec nomi lS began
t advo at that monetary aggrega t r eiv less
mphas is in th po li y pro ess b au e th yare
less r liab ly related to th e ultimate goa ls of poli y
n w than in the past. Benjamin Fri dman (1988,
440), ~ r xam pl e, claims "mo n y growth has
simply l e n ilT I vant LO any outc me that matters fo r m netalY p Ii y ."2 Friedman also id ntifies
the tability of the rel ationship betw en mo ney
gr wth and ' onomic a tivity as th c ntral is u
in the api ropriare o ndu ct of mon tary p Ii y.
The apparent instability in thi r lation hip, Friedman believ s, justifies dismissing a rol e for m n y
in th p li cy proce s.
In 1987 the Federal Op n Market ommitt
(FOMC), citing "un rtainties al o ut it und rl ying
r lati n hip to the I ehavi r f th eco nomy and
it se nsitivity LO a va ri ety of o n mic and fin ancial cir umstance " (Boa rd of Governors f th e
Fed ral Reserve ystem 1987, 21 , d ided not to
stablish a sp cific ta rg t range for Ml growth .3
This articl e fo uses o n the relatio nship
betw en money gr wth and th inflati n rat.
Pres ntly, achi ving pri c stability onc rn s policymak rs.4 Th re ar two main conclusio n in this
arti Ie pertaining to th r lation hip b tween th
1110n talY aggregates and inflati n. First, th
vi-

I

Economic Review - March 1990

d n
pr S nted here suggests Lhat mo n y gr wth
as a predi LOr o f inflation i CIS usejiJ/ now a it
was befor fin ancial d r gul atio n; thaL is, the r lationship b Lwe n m n y growth and infl aLi n is
stable ove r time.
c nd , Lil ev id nc uggest
that both th m neta lY I ase and M2 ar useful in
pr di Ling Lh behavior of Lh infl ati n raL . Ml,
how v r, makes a tati sti ally in ignifica nL
ntribution .s imilarl y, r suits from o ut-of-sa mpl ~ recaSLS show that the highesL for casting accuracy is
obs IV d wh n th p ifi ati n inclu I either

The author wishes to thank W. Michael Cox, Thomas F.
Fomby, Scott E. Hein , Evan Koenig, and Cara S. Lown for
helpful comments. Of course, any remaining errors are
solely my responsibility.
, See Tatom (1983) and Thornton (1983) for a discussion of
the potential effects of financial deregulation on the relationship between money and economic activity.
2

The apparent breakdown in the relationship between money
growth and inflation is also discussed in Kilborn (1986) and
Hill and Robinson (1988).

3

MI targets were deemphasized in 1982, relegated to a
monitored status and rebased from the previous four quarters during 1983, reestablished as a primary target in 1984,
subject to rebasing in 1985, and targeted in 1986. For a
discussion of these episodes, see Thornton ( 1983), Hafer
(1985. 1986), Nuetzel(1987), and Hafer and Haslag (1988).

, Alan Greenspan (1989) states, "That objective remains to
maximize sustainable economic growth, which in turn requires the achievement of price stability over time. "

5

In related work. Michael Darby, Angelo Mascaro, and Michael Marlow (1989) compared the predictive performance
of MIA (MI less other checkable deposits), MI , and M2.
Consistent with the findings presented here, Darby, Mascaro, and Marlow find that other measures of money are
more useful than MI in forecasting inflation.

1

the mo n tary base alo ne or the base and M2.
Overall, the vidence uggests that appropriately
mea ur d mo n y ca n continu to pl aya useful
role in th policy process a a pred icto r o f
inflatio n.

Chart 1

Monetary Base Growth and Inflation

Inflation-rate behavior: a theoretical overview
W hat is the ratio nale ro r a I' lati o nship between mo ney g rowth and inflati o n? A simpl e
fram ework or money d mand and mon y
supply-the quantity th o ly-can chara teri z
infl atio n-rate behavio r as dep n lent o n changes
in mo ney g rowth and change in no nm o n talY
factors.
The ent rpiece o f the qu anti ty th Oly is the
equatio n o r xchange. Form all y, this id nti ty is
rep resent d as

(1)

MV= Py,

w her M i a measure of th mo n y up pl y; V i
velocity, o r th numb r of tim that mo n y turns
ov l' in a given p ri od; Pith pric I vel; and y
rea l o utpu t.
In growth rates, equati n 1 may be rewritten

a
(2)

B

7

2

SOURCE : Federal Reserve Bank of St. Louis

Switching from levels to growth rates primarily reflects
technical factors that arise in the empirical analysis. Money
and prices are nonstationary time series; regressions that
use nonstationary series risk spurious correlation. To mitigate this potential problem, growth rates of money and
prices are used in the regression results that are reported
later in this article. Under the null hypothesis that the growth
rate of each series has a unit root, results from Dickey- Fuller
specification indicate that the null hypothesis is rejected.
This finding holds regardless of whether or not the specification includes a time-trend variable .
The data plotted in Chart 1 are eight-quarter moving averages of both monetary-base growth and the GNP fixedweight deflator. This particular moving-average representation was chosen because the regression analysis indicates that a change in monetary-base growth affects the
inflation rate for eight quarters; in other words, the interim
multipliers are significantly different from zero for eight
quarters following a permanent change in money growth.

Equatio n 2 shows that inflatio n an b expl ained
by comparing the growth rat of thr e ractors:
mo ney, velocity r mo ney, and rea l gross national
produ t (G p ) .6
Th I a ic intuition b bind this r laLi onship i
th at inflatio n ris s, for instanc , wh en gr wth in
th f40 'ective mo ney suppl y o utstrips growth in
mo ney d mand. The effective m ney supply
grows ith r w h n mo n y grow o r w hen the
tran a ti ns fri ci n y (known a v loc ity) o f each
unit o f mo n y grows. Mon y d mand growth is
largely du to growth in r al income in th lo ng
run.
In additi n to th
ff cts of r al G P growth
on inflatio n, th l' no nmonetalY racto rs aff ct the
infl ati o n rat thro ugh v locity growth . C nsider
th effects on transactio ns ffi ci n y I y financial
innovati n . P o pl r duc d th ir transactio n
balan sa n w high-yield financial in trum nts
such a mo ney market depo it account (MMDAs)
and mo ney market mutual funds (MMMF ) w ere
cr ated . Fin ancial innova tio ns, ther fo r , increased th eff ti ve mo n y uppl y b ca use eacb
do ll ar was u ed mo l' effici ntl y. Tog th r
Va nd
l' fl ct the effects o f th o e no nm netary
facto rs th at influ nce th e inflation rat .
Chart 1 pl ots th growth rate o f the
moneta lY base and price from 1961 to 1988.7 A
general upwa rd trend in mo n taly-ba e growth
and th infl atio n rate exi t until about 1980. Since

y

Federal Reserve Bank of Dallas

1980, however, the moneta lY base doe not have
a discernibl e trend , while inflatio n cI arl y has
be n d c1ining. Thus, bas d on the evidence before 1980, Chart 1 ugge t that a pos itiv as ocia tion exist d between mon y growth and inflation .
Aft r 1980, the existence of this relati o nship is I ss
clear. Overa ll, the vid nc in Chart 1 indicate
that a mark d change occurred in th r lati onship
betwe n mon y growth and inflatio n after 1980.
As equation 2 states, the apparent I reakdown in the relationship b tw en mo n y growth
and infl ation must refl ect shift in v I city growth
or output growth-shift that may r ult fr m
movements in nonmo n talY factors.
To capture some of th m ovements in infl ation attributabl e to nonmo n tary factors, the
growth rate of the relative pric of nergy i inc1ud d . The notion i that o il -pri c ho ksthrough their ff cts on output grow th-are
among the principal nonmoneta lY factor that
recently have influenced th inflatio n rate. Chart 2
plots th differ nce of mon tary-ba v locity
growth and output growth ( that is, Vand the
growth rate of relative oi l pri s from 1961 to
1989. 8 A Chart 2 shows, th r are two ca e
where th growth rate of relativ
n rgy pric s
in reas d dramatically; th se in ra e correspond
to th oil-price shocks of th 1970 . In both epiod th differ nce betwe n velocity growth and
o utput growth rose sharpl y after a hort d lay.
Th is ugg sts that th growth rat of relative enrgy pric may s rv as a u ful pr d icto r of the
inflation rat .
I s the growth rate of r lativ
n rgy pric
as u ful a pr dictor o f the inflation rat now as it
was b fore 1980? In the mid-19 Os, th gr wth
rate of r lativ energy pric s decl ined sharply.
But, as Chart 2 shows, this decline in oil prices
did not pr ede a similar d c1in in th difference
b tween velOCity growth and rea l GNP gr wth.
Thus, hart 2 sugge ts that a mark d change in
the relationship between relativ oi l pri sa nd
( V- 0 curr d in the 1980 .
Relative o il prices do not account f r mov ments in velocity growth. One explanation of the
appar nt br akdown in th r lation hip between
relativ
n rgy prices and ( P-M) depi t d in
Chart 2 is that the b havior of VI' f1 ected the
ff t of finan ial innovations. 9 As not d above,
finan ial innovatio n may hav incr a d the

y)

y)

Economic Review - March 1990

Chart 2

Difference Between Velocity and
Real GNP Growth and the Growth in Relative
Energy Prices
Relative Energy
Prices (Percent)

Velocity Less
Output (Percent)

40

8

30

6
Relative Energy
Prices

20

4

10

2

o

o

-10

-2

-20

-4

-30 +:
'6~1~~
' 6"!'5~~'~6~9~~''=7'T''3.....--.-.'=77.,.....,..--.--..~81~~.-85~.....--..8--+9 -6
SOURCE : U.S. Department of Commerce

tran actio n effi ciency of mon y balanc s. Alternatively, movem ent in ve locity simply may be
due to change in the gen ral I v I of interest
rat s. To ca pture the effects of predictable
chang in velOC ity growth, th m d I includes
lagged valu of infl atio n and mo n y gr w th to
xplain curr nt inflation b havior.
The quantity theolY provides a ba ic framework to analyz inflation-rat behavior as a function f mon ta lY and nonm n tary fa tors. Th
k Y qu stio n i whether the relationship b tween
mon y and infl ation is stabl over tim -once it
ontroll d for the influence f nonmo n talY
hock , u h a hang s in il pric s, that are
unrelat d to financial innovation . If , th n

B

Hafer (1983) defines relative energy prices as the ratio of
fuels and related products and power component of the
producer price index to the business sector deflator.

• John A. Tatom (1988) offers an alternative explanation for
the behavior of inflation to the oil-price decrease. He provides evidence suggesting that oil-price shocks have asymmetric effects; that is. the marginal effect of an oil-price
shock on economic activity is larger when the relative price
of oil is rising than when it is falling.

3

Fri dman's argument that mo ney is irrelev'lnt to
po li y is not substanti ated .

Model specifications
The r latio nships betw en th infl ati o n rate
and the growth rates of the mo netary base, Ml ,
and M2 'Ire exa min ed u ing general reduced-fo rm
sp cifi atio ns that ca n b w ritten as
II,

(3)

"l

11\

'-I

, I

7C, = a u+ Lf3,7C + L 8,MI-I + L r ,J!.P
H

'-I

H

+ v, ,

ilJ

w her n repres nt the rate o f infl atio n;
denot s the growth rate of th e mo ney m asur ; l 'p is
the growth rat o f th relative price of en rgy; v
is th e ITOI' te rm ; a, {3, and 8 are the p'lrameters to
be estimated ; and 11" 112, and nj are the numb I'
of lagged va lues includ d fo r the inflatio n rate,
mo ney growth , and relative energy price gr wth ,
r spectively.
Equatio n 3 indicates that movements in the
inflatio n rate d pend o n lagged va lues o f the
growth in mo n y, infl ati o n, and relati v energy
pri c s. This spe ifica ti on is essentiall y th sa me as
o ne e lim at d by R. W . H ar r (J 983). B af r's
interests, h w v r, w er limited t assess ing the
impli ca ti o ns th at chang s in Ml growth wo ul I
have for the infl atio n rate.
Lag-length electi on is an impo rtant i sue in
estimating equati o n 3. Daniel L. Th o rnto n and
Dall as . Batten (985) provided evid nce that
po licy o n lu i ns ca n b
nsitive to the lag
struclLIre specified . To address this probl em, th
ji'l1al predictioll error (FPE) rit ri o n d velo ped by
II. A kaik (969) se lects th lag I ngth f th e
va riabl es. lo The FPE cri t ri o n suggests that eac h
speC ifica tio n include seve n lagged va lu s of the
inflatio n ["lte. With the growth rates of mo ney and
relative energy price, however, the number o f

10

Cheng Hsiao (1981) outlines a procedure tor choosing the
optimal lag length in a multivariate regression setting. Up to
twelve lagged values of the inflation ra te and money growth
were allowed to enter each specification.

/I

See Godfrey (1978) for a description of this test for serial
correlation. This test uses four lagged values of the residuals.

4

lagged va lues depends o n the mo ney measure
considered. With monetary bas and Ml , the
model includ . o nl y o n lagged va lu
f the
growth rate o f mo n y. The monetary-base model
includes seven lagg d va lu es o f the relativ enrgy pri e measure, w hereas th model w ith Ml
includ s nin e lagged va lu s. sing M2, the FPE
in lica tes th at th m od I sh uld includ e the first
and eighth lagg d va lues of mo n y and nine
lagged va lu es of the r lative n rgy price.
Th e first goa l o f this empiri ca l investigatio n
is to determin e w h th r the relati n hip between
money growth and infl ati o n is stabl e. This first
invo lves tablishing th
x i ten e of a I' lationship betw en mo ney g ro wth and infl ati o n, and
next determinin g if this relatio nship h'IS undergone ith I' a stru ctural shift or a r du ti o n in its
predi tive str ngth .
The econd goa l i to d termin w hich f
the mo ney m as ur s that pass the stability test i
th best predicto r of inflatio n. Compari ns ar
based o n w ithin- amp l perform ance and o n uto f-sa mpl fo recasting experim ents.

The empirical results
Tabl 1 displays the r suits of estimating
equ ati o n 3 fo r each of the monetary va ri' tl les
fro m th fir t qu arter o f 1959 to the first quarter o f
1989. T he Br us h-Godfrey test is used to d termin w heth r erro rs are se ri all y co rrelated . In
each cas , th Br usch-Godfrey tatistics are less
than th
riti al va lu e o f 2.37; th r fo re, th
vidence is consist nt w ith the hypoth sis that the
ITOrs are seri ally uncorrelated."
Are chang in la gg d valu es o f the infl ati o n
rat , mo ney grow th , and th gr wth rate o f relati ve energy pri es systemati ca ll y related to
changes in the urI' nt infl atio n rate? As Ta bl e 1
shows, the coe fficient o n the lagged value
f
mo netary I a e 'lnd Ml growth are Signifi ca ntl y
differ nt fr m z roo Tn th e m del w ith M2 as the
mo ney measure, the f statistic fo r a test of
w h ther the coe ffi cients on lagged va lu e o f
mo ney growth ar jOintl y qual to z 1'0 is equ al to
7.79, w hich is grea ter than its critical value of
2.2 1. Th e coe ffi ci nt on lagged va lues of th
growth rates o f the mo netary bas, Ml , and M2
are significa ntl y different fro m ze ro; therefo re, the
data suggest that changes in mo ney growth are
Federal Reserve Bank of Dallas

.

Table 1

Coefficient Estimates for the Inflation-Rate Model
with Various Money Measures, 1959-1989
n1

General Model :

n2

n3

n l = a o + Lf3ln l - 1 + LDIMI_I + L
;=1

;=1

A

YI E~_I + VI

;=1

Money Measures
Estimated
Coefficient

Monetary
Base

M2

.1947
(.45)

-.9868"
(4.33)

.7868(21 .87)

.8165"
(24.64)

.8464"
(26 .31)

.2048(14.92)

.0945(9.49)

.2002'
(7.79)

.0114(2.90)

.0182(3.96)

-.003(2.98)

- .4689
(1 .69) '

I; 0,

M1

Regression Diagnostics:
Breusch-Godfrey
(with 4 lags) F=:

S.E.E.

.31

.04

.11

.83

.82

.83

1.085

1.092

1.065

'Statistics in parentheses are F statistics. The null hypothesis is that the coefficients are joinlly
equal to zero.
" Indicates that the test is rejected at the 5-percent level.

ystemati ally related LO changes in inOaLio n .
Th
vi I n e als indica t s thaL hanges in
th e growLh rate o f relaLi v energy pri ces 'lI1d
lagged inO aLi o n are useful as pI' dicL rs of Lh
infi aLion rate. nd er th null hypoth sis LhaL the
effi ienLS n the lagged valu e o f
are jOintl y
equal L ze r , Lh e F sLaListics fr m th e Lhree spec ifi ca tions are all gr aLer Lh an the criti al value of
2.17. imilariy , under Lh null hypOlh sis Lhat th
c effi cients on lagg d inOaLio n raLes ar jOintl y
qual t z r , Lh F staListi cs fo r Lh thr e different

EP

Economic neview - March 1990

specifi ca ti o ns ar all grea t r than 21. Thus, lagg d
va lues o f the inOaLi n raL and lagg d growth
raLes f relaLiv en rgy pri s ar SYSL maLically
r lat d LO the inflatio n rat

Test for stability
Thi analysi will d
nnin wh
nifica nt shift oc urr d in the b havior
Li n rat , and , spec ifi ally, wh th I' a
change oc un'ed in the I' lation hip b

Lh r a igof the inflaignifica nt
tw en
5

mon y growth and inflation.
An important i sue in co ndu cLi ng stability
t t i th timing of th point at which the potentially significant change in stimat d parameter
OCCU lT d. W. Michael Cox and Harvey Rosenblum
(1988) find eviden e suggesting that the fo urth
quart r f 1982 is the app ropriat break point in
t sts to determine if th ave rage leve l of M2 v locity experienced a significa nt shift during the
1980s. This date correspo nds to the inrroductio n
of MMDA and up r-NOWa ounts . The break
point h re for stability tests is th ~ urth quarter of
1982.12
The first test looks for cha ng s in th coeffici nts that characteri ze the marginal effe t of each
explanatolY variable on th infl atio n rate. When
testing for significant changes in the esLimated coefficients (a lso known as a Chow test), the regressio n include a seri es of inter'lctive terms, each of
which is th product of a dummy variable and an

!2

John U. Farley, Melvin Hinich , and Timothy W. McGuire
(1975) outline a procedure for conducting stability tests
when the break point is unknown. The Farley- Hinich procedure was employed to test for structural change from
1980: 1 to 1982:4. The procedure indicates that a structural
change most likely occurred at either 1982:4 or 1980:3.
Results do not change substantially if the break point is
1980:3, rather than 1982:4.

!3

!4

David J. Stockton and Charles S. Struckmeyer (1989) also
find evidence indicating that the estimated coefficients in
an inflation-rate model are temporally stable. Ml is used as
the measure of money. Note that the Chow test results
assume that the variance is constant over the two
subsamples. Thus, the stability of the coefficients is conditional on finding the errors not heteroskedastic.
In the paper by Darby, Mascaro, and Marlow (1989), the
authors find evidence of a structural change in the relationship between Ml and inflation. The differing results may be
due to the failure of the authors to include lagged inflation
rates in their estimated equations.

15

A. Steven Holland (1984) asked if the variance of errors in

predicted inflation were related to the inflation rate. If so, the
decelerating inflation that occurred during the 1980s would
correspond to a lower variance in prediction errors. Holland
provided mixed evidence about the relationship between
the level of inflation rate and the variance of prediction
errors of the inflation.
'6

6

See Fomby, Hill, and Johnson (1984) for a description of the
test procedure of heteroskedasticity.

xplanato lY variable (including th int I' pt). The
dummy variabl has a valu of ze ro for each period before the fourth quarter f 1982, and is
given a valu of o n for each peri d thereafter.
Th null hypothes is is that the coeffic ients on the
intera tiv terms are jOintly eq ual to z 1'0 . Under
this null hypothes is, the Fstatistic are 0.97,0.91,
an I 0.91 for the models with mo netary I a e, Ml,
and M2, r spectively. Becaus the valu s are
below th 5-pe rce nt critica l va lu e of 2.1, th null
hypothe is is not reject d. Th I' for , the evidence suggests that financial d regulation did not
hav a significanr impa ct on th relationship between infhtion and its determinants.I .~
Th Chow test exam in s wh ther th I' is
vid n e of a general stru ctural change in the
inflaLion-ra t specification. Was th ere a signifi ca nt
change in the sp cific marginal ef~ ct that money
growlb has on the rate of pric inc I' ase? To test
this hypoth si ,on ca n use th co fficients on
the inL ractive t rms associated w ith lagg d
money growth after the fourth quarter of 1982.
U nder the null hypoth sis that coefficients on the
int ractiv terms are jointly eq ual to z 1'0, the
Fstatisti sa l' 0.64,0.75, and 1.1 for th e models
with m netary base, Ml, and M2, respective ly,
,compa r d to a 5-pe rcent riLi ca l va lue of 2.1.
Thus, the marginal ffect of a hange in money
growth on th inflation rate also s ms stable over
tim .14
Anoth r test for tability determines whether
there is a ignifica nt change in the accuracy of the
infl ation quations over tim . To determine
whether a signifi ca nt sh ift in the accura y of th
eq uations occurred, the fo ll owing sp cificatio n is
stim ated: IS

(4)
where V i th re idual obta in d from estimating
eq uation 3, D is a dummy variable with the value
z ro befor 1982:4 and the value ne over the
p riod 1982:4-1989:1, u is the rror term, and a
and f3 ar the estimated coeffic ients. 16
Equation 4 in licates that the accuracy of the
inflation eq uation hifted after 1982 if f3 is signifi cantly d iff r nt from zero. The t st statistics are
-1.66, -1.53, and -1.33 for the mod Is with mon tary base, Ml, and M2, respectively. In each case,
the abso lute value of the t stati tic i be low its
Federal Reserve Bank of Dallas

critica l va lu
f 1.96; th r fo re, the evidence suggests that the accura y f the infl atio n equ ati o ns
did not chang after 1982.
The r suits of th sta bility t ts indicate that
the current b havior of the inflation rate is not
significa ntly different fro m b fo r fin ancial del' gul atio n. More sp cifica ll y, th t st sugge t
tll'lt the marginal effe t o f a change in mo n y
gr wth i th ame now as b for fin anciaJ del' gulation . The evid nc , th refo re, do s not substantiate th claims o f Friedman and others that
th e relatio n hip betw n mo ney growth and inflatio n has waken d .

Table 2

Coefficient Estimates for the InflatlonRate Model Comparing Monetary Base
and the Broader Monetary Aggregates,
1959-1989
n1

General Model :

n2

fCt =a o + L.8;fCt_1+ L 0;Bt-I
;=1

;=1

n2

n3

1=1

;=1

L 111Mt_l +L Y;EP,_;+Vt

+

Money Measures

Within-sample comparisons of the
monetary variables

Estimated
Coefficient

Now that eac h m n y measure pass d th e
stabiJity test, w hi ch mo ney m a ul' is th be t
predi to r o f th e inflation rate? Comparing th
mo n y m asur s hea d-to-h ad in a I' gres io n
answers this questi o n.
F rmaliy , the
mpari son is condu t d by
stimating the foll owing regres io n mode l:
"I

(5)

fc ,

=

"2

"3

a o + L.81fC '_1+ L 0 113,_1+ L
1= 1

II,

1= 1

't'l

EPt-I

L Tit M'_I + V, ,

M2

aD

-.3283
(.76)

- 1.110'
(5.86)

Ef3i

.7764'
(22.51)

.7342'
(15.16)

LO,

.1611'
(4.53)

.1695'
(7.78)

E TJ ,

.0291
(.45)

.1288'
(4.69)

Er,

.0186'
(2.81)

.0207*
(3.17)

1=1

+

M1

1= 1

wh re 13 denot s monetalY ba e growth and Mi
the growth rat
f M1 I' M2. Th pecifica tio n in clud s on lagged va lu e of bas growth. On
lagged va lu is inclu I d wh r M1 is th e mon y
m asure conjoined with the mo n talY base,
whereas the first and ighth lagg d valu s of M2
growth are includ ed in th e pe ifi ca ti o n. 17
What d th results fro m stimating quati n
5 suggest? Suppose that th e coe ffi cients fo r lagged
values of both mon ey measures ar Signifi ca ntly
diffi rent from zero. In thi s ca ,both mo ney
m as ur s are important w hen predi cting infl ati n.
Cons id r a s cond scenario where th coe ffic ient for lagged va lu es of o ne mo ney m asur
ar statisti ally Significant, but th co ffi cients for
th
th I' mon ey m asur are not. 18 The ev i I n e
th n suggest that th info rmati o n fro m o ne
mo ney meas ure i imp rtant in pI' di ting infl atio n wh il e th e other m as ure is not. Thus, th e
mo ney measur that is systematica ll y I' lated to
Economic Review - March 1990

• Indicates that the test is rejected at the 5-percent level.

infl ati n in this encompassing model is superio r to
th oth r meas ur in predi cting infl ation .
Tabl 2 prese nts th results from quation 5
estimat d se parately w ith M1 and the monetary
base and th n w ith M2 and th e m n talY base.

" Note that the encompassing model conjoins the model
specification with the monetary base to the specification
with MI or M2.
.. There is actually a third scenario. The coefficients on both
money measures are not statistically significant. In light of
the empirical findings reported above - when money
measures are specified individually- multicollinearity is
the most likely cause of this occurrence. With multicollinearity we would simply be unable to draw inferences about
which money measure is a better predictor of inflation.

7

The oeffi cient o n lagged va lu s o f mo n tarybas growth are ignifica ntly differ nl from zero
in bOlh models. Tn th M l - m neta ry base combinati n , th e 0 ffi ient on lh lagged va lu o f Ml
gr Mil is not Significa ntly differ nt from zero .
Th refo re, the evidence i consistent w ith th e
hypothesis that th e moneta ry ba e i sup ri o r to
M l as a p red icto r of infl atio n.
U nd r the null hypoth sis lhat th
0 ffi cie ms o n lagg d va lu s o f M2 gr w th are qual to
z r , lh F ta tistic is 4.69, w hich is greater than
th 5-p I' ent cri tica l va lu of 2.04. The c fficient
o n the lagg d va lue o f th mo n lary bas is also
sta tisli ca ll y signi fica nt. Thu , the ev id nce uggesls lh at both ba money an I M 2 contribute
u eful info rmatio n w hen predi ting inflatio n.
Tn sho rt, info rmati on in th mon tary base is
imp rlant w b n predicting infl atio n. Info rm alio n
uniq ue lO M l , how v r, is not systemali ally related l in fl atio n , but the vid nc ugg sts that
in fo rm ati o n uniqu e to M2 is us ful w h n predi cting infl atio n.

Out-of-sample forecasting performance
Out-of-sa mpl fo recasling ca n indi cat how
w II th specificatio ns x pl ain inflatio n-rat b of
hav ior. Four p cifi atio ns ar exa min Ii thr
th s incl ude th thl' e mo n y mea ure alo ne.
Ba d o n the w ithin-sa mpl e compari sons, a comb inati n f ba mo n y and M2 is co nsid r d as

,. The forecasts are generated with actual lagged values of
the monetary variables. Thus, the forecasts are conditional
on the actual history of monetary behavior.
20

21

22

8

This period does not entirely exclude supply shocks. The
forecasting period includes the summer drought of 1988.
An alternative method to evaluate forecasts is the mean
error criterion. A biased forecast may be less preferred than
an unbiased forecast. The mean forecast errors were calculated, and in each case the evidence suggests that forecasts are unbiased.
Suppose that the forecas ts are unbiased, then the expected values of the random variables P and 0 may be
written as: E[(e, + e,)(e,-e, )] . This expected value equals
(cr,2_cr ?). Thus , the difference between the mean squared
error is equal to the covariance between P and O. The
correlation coefficient is simply the covariance divided by

the fourth specifica tio n. Tn lhis articl e, th fo recasting x perim ent us s a rolling regressio n l
generale one-step-a h ad fo r caSls ove r lhree di fferent ho ri zons. T h term rollil1g regressiol1 re~ rs
to forecasls generated by a model th al i re stimal d each quarter lO in lude additi o nal rea li zaLio ns f th data. 19
B ca use fo r cast r ult may di ffer by the
sa mpl e peri od chos n, lhr alt m ati ve fo recast
p ri ods we re u I. The span 1981:3-19 9: 1 enmpas e the peri od since the lasl busin ss cycle
p ak and ther fore cove rs an mire busin S5
cycl e. Th
pan 1982:4-1989: 1 r p r se nts the peri od sin e th last I u in s cycle lr ugh and thu s
cov rs the currenl expansio n. The span 19 6:21989: 1 cove rs the peri od since the dramatic o il pri c de lin e. To th extent thal inflati n-I"l te
b havio r during th o il -pri ce sho k did not repr nt mo n ta ry influ nc , this x perim el1l all mpts l focus o n a p ri od Wilh ut eXlrao rd inary
factors. 2o
Th fo r ca ting ca pabilities of ac h m del
are va lual d by minimi zing th e rool-mea n-sq uare
rTo r (RM E). 21 The implicit a umpli n is that
COSlS rise al an in creas ing rate w ilh fo recasl erro rs.
Tabl 3 presents th results o f th o n -sl epah ad f I' cast fo r the thr e for ast peri ods.
Am o ng the models w ith the mo n y mea ures
includ d al n , th RM E is alway mall est w hen
th m n w ry bas is the mo n y measure. Indeed,
thi RM E is small st amo ng all four sp ifica ti o ns
over th 1981:3-1989:1 fo recasling ho ri zo n. Ta bl e
3 also shows that the RM E fo r lh mode l o mbining bas mo n y and M2 is even lowe r lh'lI1 th
mod I Wilh base mo n y alo n fo r the fo r casling
ho ri zons f 1982:4-1989:1 and 1986:2-1989:1.
Th questi on lhat naturall y fo ll ows is
w h ther lh differ nces in the RM Es are statisti ca ll y signif'i ant. C. W . ] . Granger and Paul
ewb Id (987) o utlin a pr edur to tesl fo r
dif~ renc s in th RM E. The proc c1ur defin es Pt
a th Lllll of two f re a t err r in peri od I,
w h I' as Qt is the differ nc bel w n the fo r cast
erro rs in peri od I. If th simple correlatio n oeffi i l1l b tween Pt and Qt i ignifica ml y different
fr 111 Z 1'0, th n th difference betwee n l wO HM E
timates is also stati slicall y signifi ant. 22 Appl ying
III Granger-N w bo ld proced ure lO lh four
inflati n-rale models ind icat s lhat no n of lhe
RM Es is slatistica ll y diff r nt fro m lh others.
Federal Reserve Bank of Dallas

Table 3

Results from the One-Step-Ahead
Forecasting Experiment
RMSE

Forecast Period
(Starting Date)

BaseM2

Monetary
Base

M1

M2

1981 :3

1.185

1.378

1.571

1.33

1982:4

1.384

1.428

1.51

1.334

1986:2

1.948

2.417

2.092

1.80

Th m del with th low t RM E depend
o n the ~ I' asting hori zon. O v rth lo ng st ho ri zon , the model w ith th mo netary ba e alone
actuall y ha the low t RM E; but the model that
combin es I a money and M 2 ha a lower RM E
over the two short I' fo r casting h ri zon . The fact
Lhat the RM Es are 11 t ignifica ntly differ nt, howver , sugg sts that the deLeri oratio n in fo recasting
a cura y i not large if the broader aggr gate i
used al ne, in tead f th I as ,as th predictor
of infl ati o n.

Summary
Th aim of th e analysis is to d termin
w heth I' a significa nt d L ri o ratio n occurred in the
rel ati o nship b tween mo ney growth and infl ation
and to det rmine w hi h mo ney m asur has the
trong st I' latio nship to inflatio n. Th mo netary
l ase, Ml , and M2 are th mo ney m asur s considered .
A simple th o retica l framework characteri z
inflatio n-rate behavior as a fun ctio n of changes in
mo netalY and nonmo n Lary facto rs. Th
vidence
suggest Lhat ach infl atio n-rate model is stable.
Moreov 1', the evidenc indi cat that th
stimated marginal ffect f a chang in mon y
grow th n inflatio n has not chang d ignifi antl y
over tim . Thi latter findin g directly contradicts
claims that d uring th 1980 a br akdown 0 Economic Review -

March 1990

curred in the relatio nship between mo n y growth
and infl ati o n.
Th mod I were compared to d termin e
w heth r o n mo ney m a ul' is b tt r than the
others at x plaining va ri ati o n in th infl ation rat
Th e resul ts suggest that informatio n from th
mon talY I a and M 2 is impo rtant w h n predi ting inflatio n, w hil info rmatio n uniqu to Ml i
less impo rta nt. Out o f ampl e, th e vid nce show
that a model w ith the mo netalY bas ha th lowest forecast H O I'S in each f th e thr e horizons
on ider d . The differenc s in the foreca ting
accuracy, how v r, are n t tatistica ll y ignifica nt.
Thu , the evid nc favor ither the mon tary
ba e alo n
r the mon talY ba and M 2 together
as predictors of the inflatio n rate.
Th I' ul ts presented in this articl sugg t
that mo n y r mains u eful as a predicto r of inflati o n. Furtherm o re, the vidence indica tes that
either the mo netalY ba o r a combinati o n of bas
money and M2 should rec ive the most attention
w h n pr di ting inflatio n.

the square root of the product 0 ; and 0 0 2. So, if the
correlation coefficient is significantly different from zero,
then the difference between the RMSEs is significantly
greater than zero.

9

Appendix
p. Versus a General M2 Model
Jeffrey J. Hallman , Richard D. Porter,
and David H. Small (1989) recently proposed
an alternative indicator of inflation-rate behaviorthat measures the long-run equilibrium
price level consistent with the level of M2
balances . This measure , called P*, is derived
from the equation of exchange under the assumption that M2 velocity has a constant
trend value. Hallman , Porter, and Small then
specify a simple inflation-rate regression with
five lagged values of the inflation rate and one
lagged value of the price gap, which is the
difference between P* and the actual price
level. Formally, the inflation-rate specification in Hallman, Porter, and Small is given by
5

(A 1)

lCt = a o + Lf3;lCH + A.(P

*(-1 -

P'-1)+ Il t,

;=1

where P denotes the values of the fixedweight GNP deflator, and A. is the estimated
coefficient of a change in the price gap. In
constrast, the M2 growth specification introduced in this article is
7

(A2)

lCt = a o + Lf3,lCt-; +OlM2 (-1 +02M2 t_s
'=1
9

+

L y,Ep,_,+ V" ~
A

'=1

The question arises concerning which specification is better at explaining inflation-rate

The calculation ofthe price-gap term resulted in equation A 1 not being a nested
version of equation A2. Consequently, comparing the alternative specification involves
nonnested test procedures . Russell Davidson
and James G. MacKinnon (1981) outline a J
test procedure designed to make comparisons of competing models. To implement the
procedure, initially allow the price-gap speci fication to be the null hypothesis (that is, the
P* variable is presumed to be the correct way
to capture the influence of a monetary variable on inflation) , and take the M2 growth
specification as the alternative. The price-gap
specification includes the fitted values from
the M2 growth model as a separate explanatory variable.
The J test statistic is the tstatistic on the
coefficient on the fitted value from the M2
growth equation . As Table A shows , the J test
equals 7.6 when the price-gap model is the
null hypothesis. Switch the null hypothesis so
that the specification with M2 growth is the
true model. Under this null hypothesis, the t
statistic on the fitted value from the price-gap
model is 1.8. The critical value at the 5percent level is 1.96. The evidence suggests
that the model with M2 growth used here is
significantly better at explaining inflation-rate
behavior than the specification with the price
gap developed by Hallman, Porter, and Small.

movements.

Table A

Results of Nonnested Specification Tests
Comparing the Models with M2 Growth and p.
Null Hypothesis

J test statistic

10

M2 Growth

p.

1.8

7.6

Federal Reserve Bank of Dallas

References

1

I

Aka ike, H. (969), "Fitting Autoregressive Models
for Prediction, " Annalsfol' the In titute of
tatistics and Mathematics, 243-47.

Green pan, Alan (989), "Statements to Congress,"
reprint d in the Federal Reserve Bulletin 75
(Septembe r): 614-24.

Bel ley, D. A., E. Kuh, and R. E. Wei h (980),
Regression Diagnostics: Ident(fying In:!luential
Data and ou rce of Collinearity (New York:
John Wiley & Sons).

Haf r, 11.. W. (983), "Inflation: ASing Its Recent
Behavior and Future Prospects," F deral Rerv Bank of t. Loui Review (August): 36-4l.

Board of Governo rs of the Federal Reserve Syst m (987), "MonetalY Policy Report to the
Congr ," Federal Reseme Bulletin 73 (April):
239-54.
Cox, W. Mi hael, and Harvey Ro enblum (988),
"Money and Infl ati n in a Deregulated Environm nt: An Overvi w ," Fed ralR serve
Bank of Dalla Economic Review (May): 1-19.
Dar! y, lI;1 ichael 11.., Ang 10 11.. Mascaro, and
Micha I L. Marlow (989), "Th Empirica l Reli abi lity of Mon tary Aggregates as Indicators:
1983-87," Economic Inquiry ( eptember):
555-85.
Davidson, Russell, and Jame G. MacKinnon
(981), " evera l Tests fo r Mode l pecification
in the Presence of Alternative Hypothesis,"
Econometrica 49 (May): 781-93.
Farl ey, John u., Melvin Hinich, and Timothy W.
McGuire (975), "om Comparisons of T sts
for a hift in the Slopes of a Multivariate Linear Time Serie Model," j ou1"/1,al of Econometrics (August): 297-318.

,
l

Fomby, Thomas B., R. Carter Hill, and Stanl ey 11..
John on (984), Advanced Econometric Methods (New York: Sp ringer-V r1ag).
Friedma n, Benjamin M. (988), "Monetary Policy
with ut Quantity Variables," American Economic Review 78 (May): 440-45.
Godfrey, L. G. (978), "Testing for Higher Order
S rial Correlati n in Regression Equations
w h n the Regr ssor include Lagged Depend nt Variables," Econometrica 46 (November):
1303-10.
Granger, C. W. J., and Paul N wbold (987), F01'ecasting Economic Time Series (Orlando:
Academic Pr s , Inc.).
Economic Review -

March 1990

_ _ (985), "The FOMC in 1983-84: etting
Policy in an Un erta in World, " Fed ral Reserve Bank of St. Louis Review (April): 15-37.
_ _ (986), "The FOMC in 1985: Reacting to
Declining M1 VelOCity," F deral Reserve Bank
of t. Louis Review (F bruaIY): 5-2l.
_ _ , and Joseph H. Haslag (988), "The FOMC
in 1987: The Effects of a Falling Dollar and
th tock Market Collapse," Fed ral Re erv
Bank of t. Louis Review (March/ April): 3-16.
Hallman, Jeffrey J., Richard D. Porter, and David
H. mall (989), "M2 per unit of Potential
GNP as an Anchor for the Price L vel," taff
Stud ies n . 157 (Wa hington, D.C.: Board of
Gov rnors of the Federal Reserve Sy tem).
Hill, John K., and K nneth J. Robinson (988),
"Money, Wage, and Factor carcity as Pr dictor of Inflation," Fed ral Reselve Bank of
Dallas Economic Review (May): 21-29.
Holland, A. Steven (984), "Does Higher Inflation
Lead to Mor Unc rtain Inflation?" Federal
Re elve Bank of t. Loui Review (February):
15-26.
Hsiao, Ch ng (981), "Autoregressiv Modeling
and Money-Income Causality D tection,"
j ournal ofMonetalY Economics (January):
85-106.
Kilborn, P ter T. (986), "Moneta rism Falls From
Grace, " New Y01'k Times, 3 July.
Nuetzel, Philip A. (987), "The FOMC in 1986:
FI xible Policy for Uncertain Time ," Federal
Reserve Bank of t. Loui Review (FebruaIY):
15-29.
tockton, David J., and Charles . Struckmeyer
(989), "Tests of the Specificatio n and Predictive Accuracy of Nonnested Models of
11

Inflation, " Review oj Economic and talistics
(May): 275-83.
Ta lom,] hl1 A. (1983), "Wa th 1982 V I city
Decline nusual?" Fed ral Res rve Bank of Sr.
Loui Review (Augu t/ ept mb r) 5-15.

_ _ 1988), "Are the Macro conomic Eff ts of
Oil -Pric
hock Symm tric?" Carnegie-Rocbester erie' 011 Public Policy ( pring): 325-68.
Thornto n, Dani I L. (1983), "Th FOMC in 1982:
De-emphasizing Ml, " Federal Reserv Bank
of r. LOlli Review Oun /]uly): 26-35.

___ (1983), "Why Does V locity MattetT'
F d ral R serve Bank of r. Louis Review
(Dec mber): 5-13.
___ , and Dallas . Batt n (1985), "Lag-L ngth
I tion and Test of Grang r Ca usa li ty Between Money and Incom ," Journal q( Money,
Credit, and Banking (May): 164-78.

12

Federal Reserve Bank o f Dallas

Robert W. Gilmer
Senior Economist
Federal Reserve Bank of Dallas
Houston Branch

Oil Prices and Manufacturing Growth:
Their Contribution to Houston's Economic Recovery
o usto n is the self-pro laim d iI apital o f
the natio n, and ind ed th ere are ve ly str ng
argum nts fo r th a CLIr'I CY f this titl e. H o usto n i
a c nt I' for virtu all y every plYIS of th e il and
gas busin ss, much of it o perating o n a glo bal
s ale. H o usto n mploys 66,000 worker in th
mining s cto r, almost all in iI and gas explo rati n and d velo pment. ea rl y o ne-third o f the
metropo litan area 's manufacturing jobs ar dire Li y
in o il fi eld machinery, pet I' chemi ca ls, o r o il refin ing. H u to n is ho me to m st f th worl I' large
o il compani s o r th ir op erating divisio ns, with
Exx n
A , T nn e 0, P nn zoil , and Mit hell
En rgy amo ng th
il firms h adqu arter d in
Husto n. Majo r publicl y- w ned , H o usto n-I as d
pipeline ompani es includ e th
oa w i o rpo rati n, Enr n, Panhandle E'lstern , and Trans o. The
T xas ulf Coast regio n, w ith H o usto n at its
ntel', ontains o ne-fo urth of the nali on's refinin g capacity and half o f it ba ic petro hemica l ca pacity.
M.W. K 1I0gg, Flu o r Daniel, and Brown and H ot
are amo ng th giant constructi n and ngin rin g
firms lh at. draw o n th e I' g io n's d ep te hnical
experti e.
Husto n has shar d g d Limes and I ad
w ith the o il industry. M ost f the 1980s were a
time o f relren hmenL fo r I th ity and industly. In
1982, H o u l n found itself ho me t hundr d
f
il-relat d I roject I a ed n x pectati o ns of o il
pric at 50 per barrel o r mo re. Wh n it beca me
clea r lhat the e pri es we re ho peless ly unrea listic,
H ousto n' o il boom f th e 1970s turned into an
o il bust, and th ci ty slid into 'I sharp reces io n
fro m 1982 lO 1986. Betw en Janu ary 1982 an I
January 1987, th CilY lost mo l' th an 100,000
wage and alalY jobs in energy industries. The city

H

Economic Review -

March 1990

lost sli ghtl y mo l' th an 200,000 j bs in all e to rs,
whi h I' pI' S nts 12. p I' enl of the pre-bust
work fo rce .
13 g inning in arl y 1987, H o ust n's con mic fortunes rebound d w ith robust and st ady
econo mi c x pansio n. By
lo l er 1989, n arl y
120,000 jol s had b en added back to H ouston's
LOlaI wag and ablY empl ymenL. As Chart 1
indi ates, most of H o usto n's n w job ar in th
servi e secto r, and in many way this fa l refl e ts
a hea lthy div rsifi ca ti n of the H o ust n economic

Chart 1

New Jobs Added in Houston Recovery
(Thousands)

70
60
50
40
30
20
10
0

M ining

Private
Services

SOURCE: Texas Employment Commission
NOTE : Abbreviations are as follows :
Const =Construction
Mfg = Manufacturing
Trade = Wholesale and retail trade
Gov't = Government
Private Services = Private Service-Producing Industries

13

Chart 2

New Jobs Added in Private Service-Producing
Industries
January 1987-0ctober 1989
(Thousands)

50

40
30

20

10
O~-------'

____

r--

- 10~~~~~~~~~~~

TCPU

FIRE

PERS

__~~----~
BUSS

PROF

SOURCE: Texas Employment Commission
NOTE : Abbreviations are as follows:
TCPU = Transportation. Communications. and Public Utilities
FIRE = Finance. Insurance. and Real Estate
PERS = Personal Services
BUSS = Business Services
PROF = Professional Services
Personal Services include Standard Industrial Classification
(SIC) Codes 70-79. excluding SIC 73. Business Services.
Professional Services include SIC 80-89.

base away fro m o il. Chait 2 show furth er d ta il
about s rvi e ; th bar mark d PROF (pro~ s inal
service) o n i t o f job in medica l, I ga l, educatio nal, and other groupings. Abo ut half of this
prof ssional incr a i in m di ca l rvices
(14,500 job ) and
n tructi n-e ng in rin g 1'vice (4,000 j b ) .
Th
ntributio n o f o il and ga t thi I' covelY ha b en light 0 far. Chart 1 hows thal mining co ntributed o nl y 4,400 new jobs, and o nl y
6,700 n w jobs we re add d in machineri , I' fin ing, and chemica l (om
3.5 percent of the total

, For the purposes of this article. the definition of the economic base is deliberately limited. Several service -sector
industries could and should be added if, for example. this
article were intended as an economic base study. See
Leistritz and Murdock (1981). Our purpose here is to cast
Houston as a one-industry town. and to explicitly see how
this one industry performed in Houston in the recent past.

14

new m anufacturing jo bs) .
Th purpos of this articl e i to ass ss th
role o f o il and gas in H o usto n's futllr in light o f
ilS recent lackluster perfo rmance. Altho ugh di v 1'sifi ca ti o n is a pos iti v facto r fo r H ou tn's conomy and I ng-t I'm futur , o il and gas w ill remain
dominant for yea rs to com . Why ha it rec nt
ontributio n been 0 wea k? H as it hi to ri ca l I' lati nship to th H o uston cono my b en altered by
th five y aI'S of re essio n?
A a m th d logica l and o rgani zati o nal cI vice, w
timat d la ti citi o f o il-relat d mpi ym nt in a numl I' of industry s cto t' in I til
Housto n and Texas and computed th elasticiti es
w ith I' p ct to o il pri es, th
.5. busin
cycl,
and the doll ar. Th ese qu atio n are d scrib d in
f these tim ates
the next sectio n. On the ba i
we draw six o ncl usions about H o uston 'S econom y (Tabl e 1) . The
o n lu i n do not (a n I
ca nnot) a Id up to a fo recast of H o usto n' e 0nomic future, but th y provid in ight into how
H o usto n will rea t to outsid fo r s from the busin s ycl ,CUlT ncy market , and th wo rld o il
market.

Def"initions and Methodology
Manufacturing and mining make up
Ho usto n'S cono mic ba fo r purpos o f this
articl e.' W e furth er divid manufacturing into durabl e good and nondurable goods, and defin e a
s parat gr up f o il -relat d manufacturing industries as refining, ch mi ca ls, an I no n I lrica l mahinelY . Tabl e 2 ummari z s the distribution o f
this empl oyment in b th H o usto n and T xas.
Our m thodo logy i b ITowed dir ctly fro l11
W .H . Branson and James P. Love (1987). B'IS d
on th ir wo rk , one red u d-fo rm equatio n is appli d to to tal mining and manufacturing and to
vari o us di saggr ga ted secto rs. Th d p nd nt
va ri able is th natural loga rithm of mpl oym nt.
Th ri ght-hand independent va ri ables are: a co nsta nt, th e .. un mploym nt rate to aptur ycli cal change, a trend term to ca ptur s ul ar
hang s in demand , the rea l price o f o il , and the
rea l exchange value o f the do ll ar. The unempl yment rat ( urI' nt and fo ur lag ), the I rice o f o il
( urr nt and four lag ), and the va lu o f th do ll ar
CUlT nt and six lag) are all transform ed to logarithm s.
Federal Reserve Bank of Dallas

Table 1

Six Conclusions
1. Houston's economic base is no less sensitive than the rest of Texas to the national
business cycle , other things being equal.
2. Houston's economic base is more sensitive than the Texas economic base to
changes in the price of oil. The difference is the large share of oil-related manufacturing in Houston.
3. The response of mining (upstream oil) jobs in Houston to changes in the price of oil
is now 40-percent smaller than before the Houston recovery began in 1987. The
response of Houston manufacturing remains unchanged .
4. Houston's economic base is much more sensitive than the state's economic base
to the international value of the dollar.
5. Thus far, Houston's recovery has been led by a more robust U.S. economy and
stronger world-commodity prices. However, the decline in the dollar since 1987
exerted roughly equal influence on the Houston economy. Oil-price changes
slowed Houston 's recovery.
6. Oil maintains a significant presence in Houston. Although Houston's oil-related
economic base is now less responsive to oil-price increases, more stable and
higher oil prices still promise big employment gains for the Houston area.

Table 2

Distribution of Mining and Manufacturing
In Houston and Texas, 1988

Base
Mining
Manufacturing
Durables
Nondurables
Petroleum-Related
Chemicals
Petroleum Refining
Nonelectrical Machinery

Economic Review -

Ma rch 1990

Houston
(Percent)

Texas
(Percent)

100.0
30 .0
70.0
37.3
32.7
40.9
15.4
5.6
19.9

100.0
16.2
83.8
48.5
35.4
22 .3
8.0
3.1
11.0

,

15

Table 3

Regression Coefficients for Branson-Love Equations,
Estimated for the Houston and Texas Economic Bases

Base

Mining

Manufacturing

Durables

Nondurables

Trend
Houston
Texas

.0033
.0038

.0119"
.0046

.0025"
.0031

.0044"
.0048

.0032
.0008

Unemployment Rate
Houston
Texas

-. 324
-.297

-. 130
-. 241

- .448
-.316

-.749
- .475

-.057*"
-.114

.424
.292

.570
.580

.404
.224

.629
.316

.128
.115

-1.109
-.481

-1.111
-. 337

- 1.270
-.418

- 1.791
-.620

-.561
-.220

Oil Price
Houston
Texas

Dollar
Houston
Texas

Dummy
Houston
Texas

.164"
.180

.394"
.558

.109"
.080"

.115"
.154"

.097'·
-.120"

-. 121'·
-.070

- .149'·
-.121·

-.087*'
.001"

Delta
Houston
Texas

-.132"
-.114

-.242
-.267*

NOTE: The lack of an asterisk indicates that a coefficient is significantly different from zero at 95-percent confidence level. A
(0) indicates that the coefficient is significantly different from zero at a 90-percent confidence level. A ('0) indicates
that the coefficient is not significantly different from zero at a 90-percent confidence level.

In additi on, we add d paramet rs to test fo r
the exi tence of stru ctural change in the relati nship betwe n oil prices and base empl oyment
after 1987 as Ho uston's recove ry got und rway. A
dumm y variabl e assuming the v'due o ne in 1987 :1
and after was in Iud d, as we ll as a term to test
fo r a shift in the o il-price elasti city after 1987: l.
Empl oyment data are the no nagri ultural
wage and sa lG
IlY fi gures provid ed by th Texas
Empl oym nt ommissio n; the rea l pri ce o f o il is
the refin er-acqui siti o n cost o f crud (bas d o n the
ove rall pri c lev I preva iling in 1982) denated by
the co nsumer price ind x; th e I' al va lu e f the
d li ar is th index computed by the R s ar h
D epartment o f the F deral R serv Bank o f D all as
(Cox 1987). Data cover 1975: 1 to 1989:2. W e ap16

pl y o rdin ary I ast square w ith an adjustm III fo r
first-o rd r autoco rrelati o n. Elasti iti s o f employment w ith respect to the unemployment rate, oil
pri ces, and the do ll ar are co mput d a the. LlI1l of
currelll and lagged co ffi cients. H ypothesis t t
I' quire that the equatio ns be I' estimat d under
th e restri cti o n that the LlIll o f the current and
lagged valu es is zero fo r a ingle lasti ciry, and an
F test is co ndu cted to test th e I' strictio n.
Tabl es 3 and 4 summari ze th results. Th
tabl es pres nt regr ssio n coe ffi cients fo r th tr n I
t I'm , th un mpl oyment rate, o il pri ces, and th
do llar. Th e tabl es al show the variabl used to
test fo r stru ctural chang in th impact of o il
pri ces aft I' 1987. A n asteri k markin g a 0 ffi ci nt
d no tes a 90-perce nt to 95-p rc nt probability
Federal Reserve Bank of Dallas

Table 4

Regression Coefficients for Branson-Love Equations,
Estimated for Houston and Texas Petroleum-Related Industry

Petroleum
Trend
Houston
Texas
Unemployment Rate
Houston
Texas
Oil Price
Houston
Texas
Dollar
Houston
Texas
Dummy
Houston
Texas
Delta
Houston
Texas

.0056"
.0005*'

Machinery

-.0 101 "
.0003

Chemicals

Refining

.0038"
.0010'

-.0019*'
- .0051

-.487
-. 313

-.773
- .624

- .159
-. 151

.506
.341

.760
.584

.1 17
.102

- 1.471
-.784

-1.287
-1 .072

- .724
-.309

.189*'
.148*'
-.17 1**
- .1 13*'

.174**'
.138*'
.131
.172
- .746
- .307"

-.468"
.219**

-.334**
-. 068**

.263**
.197**

.214***
- .155

- .01 8**
.017"

-.241**
- .123"

NOTE : The lack of an asterisk indicates thai a coeffici ent is significantly different from zero at a 95indicates that the coe fficient is different from zero at the 90percent confidence level. A
percent confidence level ; ("") indicates that the coefficient is not significantly different from zero
at a gO-percent level , and ("') indicates that the coefficient is significant and carries the wrong
sign .

n

that th c effi ci nt dif~ rs rrom zero; two asteri sks
incli ate th at there is a less than 90-percem chane
it clirrers from zero; no asteri sk indi ca tes a probability above 95 perc nt that th c erricient i
dirrer nl rro m zero.
T he economi c interpretatio n o r the coeffici nts is straightfolwa rd . Th lrend t rm is the
qUGl rLerl y growth rate of empl oym nt in thaL
seclo r, ho lding fixed the ther rfects o f the ri ghthan I va ri 'd les. The coefri cicnts o r the ther variabl are th elasticity or mpl oyment w ith
res pe l l each ind pend nt variabl e. Thi s repr se nlS th p rc ntag change in mpl oyment
ca used by a I-perc nt change in th unempl oyment rates, o il pri s, I' th e do ll ar.
Estim ates wer mad ro r the H ousto n m troEconomic Review -

March 1990

po li wn area and for lh state o f T xas .2 Tab l 3
shows the resulls ro r the br adest industry lefini ti o ns-t tal ba se, minin g, manufacturing,
dural les, and nondurabl es. Tabl 4 u es th e am
format, but shows mo re d tail of the petro leum-

2

Branson and Love also provide estimates for the state of
Texas. Their coefficients are estimated for 1970- 87; the
coefficients measure real energy prices using the ratio of
the energy consumer price index (CP!) to overall CPI, and
measure the real value of the dollar using the International
Monetary Fund (/MF) index of relative unit labor costs. Their
estimated elasticities are: - 0.24 for the unemployment rate.

0.43 for real energy prices. and - 0.34 for the dollar. All
estimates are highly significant. For comparison, our estimates are, respectively. - 0.30, 0.30, and 0.48.

17

based industries.
Six Conclusions

Table 1 pre ents six conclusio ns that might
be drawn from this econom tric x r i . W will
discuss ach of these concl u ions and add whatever qua lifications are nec ssa ry.

Houston 's economic base is no less sensitive than
the rest of Texa to the national business cycle,
other things being equal.
Both Hou ton and T xa hav nearly idential elasticities of base employm nt with resp t to
the U.. unemployment rate , -0.32 for Houston
and -0.30 for Texas. This i surprising to th extent that Houston econom ic myth logy typica lly
holds that the city i immune to the U. . busin ss
cycle, and Houston mi sed u.s. rece ions everal
tim in its hi tory.
A b tter analogy than immunity, how v 1', i
that an antidote to U.S. bu iness condition i
om tim ava ilable to Houston in th form of
rising oil and gas prices. W will s the effe ts of
oil pric s more lea rly below, but there is no
question that g od times in th oi l industry an
carry Hou ton right through U. . re e ion. By
the am log ic, Houston missed mu h of the current U. . xpansion from 1982 to 1986 as oil
pric D II. Holding oil price and the xchange
rate as n utral factors, how vel', Hou ton and the
re t of Texas can expect similar stimulus from
national bu in
condition.

Houston 's economic base is mOl-e sensitive than the
Texas economic base to changes in the p'-ice of oil.
The difference is in the large sbare of oil-I-elated
mam~racturing in Houston.
Th re pon e of Hou ton and Texa mrnrng
to changes in oi l prices are Virtually id ntical, with
an elasticity nea r 0.6. However, Houston's manufacturing sector carries an la ticity f 0.4, and
that of Texa i only 0.2. Within the manufacturing s tor, we s simil ar e la ticities for o il-related
indu try in both Houston and Texa . The machinry indu try i much more sensitive than l' fining
or chemicals, and Houston 's shar of the vo lati le
machin rie group is much larger than that of
18

Texa . Ab ut half of the machin ry is o il-service
products haded dir ctly for o il and gas xp lo ration and d velopment, and thes industries ar
ensiti ve to oil pric j chem icals and r fining ,
howev r, I' spond more to co n umpti o n than to
sho rt-run price changes.

The response of mining (up tream oil) jobs in
Houston to cbanges in the pI-ice of oil is now 40percent smaller tban before the Houston recovery
began in 1987. The response of Houston manufactwing remains unchanged.
The dummy and coefficient shi ft (delta)
variabl s ud to te t for chang in th oil-pric
elasticity since 1987 how no indicati n of large
o r ignificant change in Houston or T xas
manufacturing. Thi is true for individual petroI um-r lat d sector as well a for th enti re
manufacturing sector.
In the mining ector, however, the oil-price
la ticity shrunk more than 40 perc nt in both
Houston and Texa . A reduc d elasticity is ertainly cons i tent with the con mics of xploration and d velopment of o il and gas fi I Is si nc
1987. Aft r o il price began to fall in 1982, oil and
gas exp lo ration companies that gea red up for o il
at $50 p I' barrel found their employm nt levels
and c t tructure greatly out f lin j th layoffs,
re tructuring, and reorganization of exploration
and dev lopment divisions in Hou ton-based oil
compa ni s ontinu d through 1987, and indeed
continu today.
On major qualification to th
results
stems fr m the re e nt shift in exploration away
from oil and toward natural gas. By mid-1989 a
cou nt of il and gas rigs in op ratio n indicated
that mol' d m stic exploration wa g are I to gas
than o il. Continu ed natural ga urplu sand
depressed natural gas prices-depr
d even
mor than o il--could explain this reduc d elasticity a w have measured it. By including only an
o il-pric variable, we could ov I' tat the ext nt of
indu try r structuring, and w wou ld xp ct to
see a r turn to tronger m a ured elasticiti if, as
is frequ ntly for a t, natural gas returns to selling
at a pI' mium to th price of oi l.

Houston 's economic base is much more ensitive
than the tate 's economic base to the international
Federal Reserve Bank of Dallas

value oj the dollar.
The lasti ity of base mployment in Texas
with res pe t to the va lu e o f the do llar o n int rn ational markets is - 0. 8; lh
h sLi city for H o uston
i mo re than lw ice thi va lu e al - 1.1 1.3 The patt rn ho lds in mining and manuracLUring, b tween
dural I s and nondurabl es, and ro r pelr I umr laled industly.
H ou LOn ' stro ng inlern atio nal ri enta tio n is
indi pUlabl . Bas d n f reign l nnag , the Po rt
o f Hut n is the busie t po rl in the U nit d Stat ,
and mu ch or th impo rted l nnag is fo reign o il
fo r th I' fin ri sa nd petrochemi ,t! plant thal
lin Lh Hut n hip hann I. Agri ulLural pr du LS, hemica ls, and fu I o il ar Hulo n' to p
thre x p ItS.
H owever, as a world p Lro l um c nter,
H o u Lo n's int rn atio nal o nn e Li n x L nd bey nd lh po rL and ship channel. In H ousto n in
1989, ther we re 574 foreign rinn s h adquartered
in rifty-on nations. The city ranks third amo ng
U. . iti es in the number o f f I' ign trade ffi s,
fifth in fo reign consulaLes, and SiXLh in intern ational air pa ng r . TL i an inl rn ati nal
financi al
nter for th
outh and Southwest with
fifty-Lhr e ror ign banks (Gr aL r H o u ton Partnerhip 19 9).
Thi slrong dep nd enc
n th do llar al so
provide o n mo r I' a on fo r H o uston ' tough
tim b tw n 1982 and 19 6. This wa the am
period that th doll ar soa r d n int rnationalmarkets, appr ci ating I y 38 p [ cent according to th
ind x u d in thi articl . Thi appr ciati n certainl y add d co n id ral Ie mom ntum to the
downturn air ady prec il iLal d I y th e d cline in
oil pri s.(A tu ally, th do llar peak d in arly
1985, but its high relativ valu in 1985 and 1986,
combin d WiLh adjustm nt lags, prolo ng I the
impact r th overvalu d do llar n Huston .)

ThusJar, H01lston 's recovelY bas been led by a
more rob1lst U. . eC0110my and stronger worldcommodity prices. However, tbe decline in the
dollal· since .7987 exerted m ughly equal influen ce
on the Houston economy. Oil-price changes slowed
Houston 's recovelY.
hart 3 sho ws th d li ar's path , Lh U.S.
unemployment rate, and th r al pric of oil from
Economic Review -

March 1990

Chart 3

The Dollar, U.S. Unemployment, and Oil Prices:
Their Path from 1987 to 1989
120

110

100
Do ll ar
90

80
Unemployment
Rate
70

60~----------~----------~----------~

1987

1988

1989

INDEX = 100 for all variables in the first quarter of 1987
SOURCES: United States Energy Information Administration
Federal Reserve Bank of Dallas
United States Bureau of Labor Statistics

1987 LO mid -1989, with ach vari abl set at a
valu
r 100 as H o uston 's econ mi r e v ry
b ga n in 1987. The actual valu e r th do ll ar index m v d fro m nea r 100 in 1987 to n ar 90 in
ea rly and mid-1988; by 1989: 2 iL had appr ciated
to 95.2. Th
.. unemployment raL dropped
teadil y from 6.6 perc ill L 5.3 per ent. R al o il
I ri ces w re n ar $15 p I' barr I aL Lh beginning
and nd of th p ri od, bUL f II as Iowa $10.50 in
lat 1988.
On w ay to quantify the impo rLanc o f these
vari abl is t perform Lil f llowing ount rfactu al xp rim ent. What if, instead f following the
palh hown in Chart 3, th e . . un mploym nt
raLe had rem ain d at 6.6 p rc nt while th oth I'
vari able follow d their a tual
ur e? Tabl 5

3

For comparison, Branson and Love ( 1987) obtained an
elasticity of - 0.34 for Texas, using the IMF index of relative
labor costs as the value of the dollar on international
markets. Their largest coefficients across all tifty states
were: North Dakota (- 0. 73), Nevada (- 0.55), Alaska (- 0.54),
and Wyoming (-0.54).

19

Table 5

Hypothetical Forecasts of Employment in 1989:2
if Each Variable is Held at 1987:2 Levels

Actual
Houston
Texas
Unemployment Rate
Houston
Texas
Oil Price
Houston
Texas
Dollar
Houston
Texas

Base

Mining

Manufacturing

Durables

224.2
1147.8

66 .1
177.2

158.1
970.6

85.5
558.5

72.2
412.4

210 .7
1081.9

64.4
169.1

145.5
911 .1

74.2
510.8

71 .6
401 .8

242.9
1205.5

75 .0
199.9

168.3
1005.3

92.9
587.3

75 .0
419.8

206.1
1107.2

61.4
173.3

143.8
936.0

75.7
534.2

69 .2
404.1

pre nts forecas ts of th ese hYI Olheti al levels of
em ploymenl. imilarl y, the other va ri abl s were
each held in LUrn at 1987: J lev Is, 'Ind the hypothetica l experi ment repea ted . The to p of the tab le
shows aCLUal va lu es of the va ri ables in 1989:2.
T he most signiri ca nt effect o f th ese three
variabl s comes fro m o il prices. H o uSLO n's mining
and manufacturing would have had an th r
18,700 j bs if il pri ces had simpl y sLayed at th eir
1987 level instead of plunging by 30 percent and
then reLUrning to the initial leve l. I Th e employment ga in fr m this x perim enr (or th al pare11l
loss s fro m the a tu al o il-pri e decl ine) w re split
45-55 betwe n mining and manu fa LUring.
The do ll ar has th second most Signifi ca nt
effect, and if the dollar had not been allowed to
d prec iate as it d id aga inst other CUlT ncies,
H o uston would hav had 18,100 fewer jobs in
1989. Most o f th e hypoth ti ca l losses (75.2 perent) w ukl have been in manufa turing.
H o lding the unempl oyment rat at 6.6 p 1'c nt woul d have ost H o usto n 13,500 j bs, w ith
88. 1 pe r ent of the job los s conce ntrated in
manu fac tu ri ng.

• These estimates use the reduced post- 1gB? oil-price elasticity.

20

Nondurables

Oil ma inta in a sig llificant p resence in Houston .
Altbougb HOllston 's oil-related economic base is
/l OW less responsive to oil-price increa es, more
stable a nd bigIJer oil p rices still p rom ise big em p loyment gains/ or tIJe Hall ton a rea.
Suppose the refin er-a quisitio n price o f
rud e oil rose in current d li ars to $22.50 per ba rrel in 1989:3 and remained at that leve l through
1990:2. uppos that d uring this peri od the d li ar
rema ined at its 1987 index va lu e o f 95 and the unem pl oyme nt rat stayed at the full employment
5.5 percent of 1989:2. Th result would b 19,800
new jobs in H o usto n and 55,400 new jo bs in
T xas. H ust n's n w jobs would b o ri ented
aim st 2-to-1 in favor o f the mining sector, w hile
Texas jo bs woul d split ev nl y betwee n mining
and manu fa turing. H o u ton woul d ca ptu re 35.7
perce nt o f th sta tew id e job ga ins in the LOta l
base, I' presenting 9.3 p rce nt o f th e ga ins in
mining, but o nl y 27.7 p rc nt of the ga ins in
man u factu ri ng.
Th ese e timates assume that both H ousto n
and T xas now add il-r lat d jobs at a rat 40p r ent bel w the pre-1987 lasti ity. The
incr a e t $22.50 p I' barr I in th refin era q uisitio n pri ce of o il is a 30-perc nt increase
over $17.50 per barrel, the price in mid-1989.
u h an increase remains poss ibl and pl aUSibl e
(p rh aps four qu art rs o f o il -pri ce stability is the
Federal Reserve Bank of Dallas

less pl ausibl part f the s nari o). Tf achi v d ,
ould still bring big employment
thi in I' a
gains to the Housto n area. It d
not I' turn
Hut n to the day o f the o il b om . Prices at
$22.50 per barr I would I' turn mining empl oyment to on ly 69 p rcent of th 1982 p ak I vels;
manufacturing would return LO 94.7 p rc nt o f it
19 1 pea k mployment.

Implications for Houston's Future
The H o usto n econo my share w ith the re t
of T xa it sen itivity to bu iness-cycl e o nditi ons. At the sa me tim e, w find it i al 0 far mo re
en itive to volatile w o rl I o il mark t and the
valu of th doll ar on w o rl d mark t . In th e past,
this combinati on led Housto n through remarkable
highs and lows in conomi c p rformance. The

imm di aL futur looks more s daLe. Ass uming
Lh do llar remains tabl e rd e lines lightl y, and
Lh at OPE I' mains unabl to I' 'IS en ontro l of
world o il pri
,gr Wlh in H o u LOn and the
nited States w ill b imilar during 1990. Over the
lo ng I' run , il pri c s may o nce more begin LO ri se
in rea l terms, as many analysLs expe L. s Tr so,
H o usLo n w ill benefit grea tl y. O il surely w ill move
H USL n ' gr Wlh rat ahea d o f th
veraII
p a e. Add to this H ousto n's positio n in medi ca l
s rvic s, its potential edge in mergi ng nvir nm ntal rvi e , and its d pLh in t hni al kill
deri ved from A A and Lh large engin rin g
firm , and th city ee ms po is d t move fo rwa rd
in way that may slow ly diminish its image as a
o n -indu stry town .6 il and gas, how ey 1', w ill
r main aL th e e no mi c h arL o f H ouston fo r
many yea r t
om .

• See Brown and Phillips (1989).
• For a careful look at oil in Texas, recent diversification from
oil, and its effect on the state 's performance, see Fomby
and Hirschberg (1989).

Economic Review-March 1990

21

References
Bran on, W.H. , a nd l a me P. L v (1987) , "The
Real E change Rate and Employme nt in .S.
Manufacturing: tate and R giona l Results ,"
W rking Pap r No. 2435 (Camb ri dg , Mass.:
Nati na l Bur au of Econom ic R s a r 11) .

Fomby, Tho ma B. , and]o ep h G . HiI' chb rg
(1989), "Texas in Transitio n: 0 pend neon
O il and th
ational Econo my, " Fed ral
R serve Bank of Da ll as Economic Review
(Ja nu a ry): 11-27.

Br wn , t phen P.A. , a nd Keith R. Phillips (1989),
"O il Demand a nd Pric s in th 1990 ," Federal
Reserv Bank of Dalla Economic Review
(January): 1-8.

Greater Houston Partnership (1989), Houston
Facts (Hou t n: Greater Hut n ha mbe r of
omme rc ), 1- 12.

Cox, W . Mi hael (1987) , "A Compreh nsive ew
Real 0 lia r Exchange Rate Ind ex," Federa l
R serve Ba nk of Dallas Economic Review
(March): 1-14.

22

Leistritz, F. Larry , a nd Steve n H. Murdock (981),

Tbe ocioeconomic Impact 0/ Resou rce Developmel/t: Metbods/or Assessment (Bould r,
Colo.: We tvi w Pres ).

Federal Reserve Bank of Dallas