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Economic Review
Federal Reserve Bank of Dallas
March 1986
1
Exchange Rates and World Oil Prices
Stephen P. A. Brown and Keith R. Phillips
Appreciation of the U.S. dollar contributed to
downward pressure on the dollar price of oil during
the first half of the 1980s. An econometric and
simulation analysis suggests that had the dollar
maintained its real 1980 value through fourth quarter
1984, the real dollar price of oil would have been
more than 25 percent higher. The increase in the
value of the dollar increased the foreign price of
oil, contributing to decreased foreign demand and
increased foreign supply. These changes in foreign
demand and supply added to downward pressure on
the dollar price of oil during the first half of the
1980s.
11
The Labor-Intensive Nature
of Manufacturing High-Technology
Capital Goods
Robert T. Clair
State government programs designed to increase
employment will have greater success by encouraging
high-technology equipment manufacturing rather
than the manufacture of other types of producers'
durable equipment. Because of the labor-intensive
nature of manufacturing high-technology equipment,
an expansion in this industry will produce a greater
increase in employment than would an equal
expansion in other capital goods industries. The
average high-technology job, however, requires little
skill and pays a relatively low wage. As a result,
income gains will be less than employment gains.
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
March 1986
President
Robert H. Boykin
First Vice President
William H. Wallace
Senior Vice President and Director of Research
Harvey Rosenblum
Vice President and Associate Director of Research
James E. Pearce
Assistant Vice President and Senior Economist
leroy O. laney
Eugenie D. Short
Economists
National/International
W . Michael Cox
Gerald P. O'Driscoll, Jr.
Robert T. Clair
John K. Hill
Richard C. K. Burdekin
Steven L Green
Regional/Energy
Stephen P. A. Brown
William C. Gruben
Ronald H. Schmidt
Hilary H Smith
Roger H. Dunstan
William T. long III
Editorial
Virginia M . Rogers
Elizabeth R. Turpin
Graphics and Typesetting
Publications Department
The Economic Review is published by the Federal
Reserve Bank of Dallas and will be issued six times
in 1986 (January, March, May, July, September, and
November), The views expressed are those of the
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the reprinted material.
Exchange Rates and World Oil Prices
Stephen P. A. Brown
Keith R. Phillips
Senior Economist
Economic Analyst
Federal Reserve Bank of Dallas
Federal Reserve Bank of Dallas
Introduction
statistically significant response to changes in the
foreign value of the dollar. Furthermore, the simulation suggested that the sharp appreciation of the
dollar between 1980 and 1984 had a considerable
impact on the dollar price of oil. Had the dollar
maintained its 1980 value and not appreciated
against foreign currencies, the real dollar price of
oil might have been more than 25 percent higher in
fourth quarter 1984.
From fourth quarter 1980 through the end of 1984,
the value of the U.S. dollar rose dramatically while
real dollar prices of oil fell nearly as sharply (see
Chart 1). Because world oil prices are denominated
in dollars, appreciation of the dollar during this
period likely contributed to the decline in world oil
prices. The appreciation of the dollar increased the
foreign price of oil, which decreased foreign demand and increased foreign supply, thus putting
downward pressure on the dollar price of oil.'
An econometric model was used to estimate the
relationship between movements in the foreign
value of the dollar and those in the official dollar
price of Mideastern light crude oil. This estimated
relationship was used in a simulation analysis to
calculate the impact of recent exchange rate
movements on the price of oil. I n the analysis, the
value of the dollar was held constant at its 1980
level through 1984. This simulated price of oil was
then compared to the actual price of oil during the
period.
Regression results showed that the official dollar
price of Mideastern light crude has a strong and
Economic Review I March 1986
Exchange rate movements
and the world oil market
The historical record. During the 1981-84 period,
the value of the U.S. dollar generally rose against
other currencies. As is shown in Chart 2, appreciation of the dollar had a dramatic impact on the real
prices for oil that other countries faced. I n fact, for
consumers in West Germany, France, the United
Kingdom, and Italy, exchange rate movements more
than offset declines in the dollar price of oil, causing the price paid for oil to be greater in the fourth
quarter of 1984 than in the same period for 1980.
For the six non-Communist countries other than the
United States that consume the most oil-Canada,
Chart 1
The Value of the Dollar and the Price of Oil
(1980 = 100)
160
140
120
100
.,., ...... _._._.-
80
--------
REAL DOllAR PRICE OF OIP
60
40
20
o
1981
1980
1984
1983
1982
1. Weighted by oil consumption in big seven countries. excluding the United States.
2. Official price for Mideastern light crude oil, adjusted for inflation.
SOURCES OF PRIMARY DATA: International Monetary Fund.
U.S. Department of Energy.
Petroleum Intelligence Weekly.
Chart 2
Real Foreign Oil Prices
(1980 = 100)
200
175 -
/
150 t/~
125
/{/
/
----
100
75
\
~;.".
--------/
,,------
\
't::..,••:::::"....... ;
/----;::=-_--~
...., '"',
.. / / .•• ~ •••••• -.:L!•••• :..........-:.-:----... -...
I~"~"'-'
...... WEST GERMANY
~=--:.~
,,_,-,-,-7
" ,.........
/./
'/
,.,,"'---,,---/
---- \
,/•~~~
•/ . ;
r
/'.
/_---
_-----
_.........
r-~_---
/'
FRANCE
UNITED
KINGDOM
"
---- / ,- -ITALY
\ " ....:':i...---""- - - - --\\
". \. . . . . ________. . __________---------
JAPAN
.................. ······CANADA
UNITED STATES
r-I
50
1980
I
1981
I
I
1982
1983
I
1984
NOTE: Each entry is the official price of Mideastern light crude oil, converted to
each country's currency and then deflated with that country's implicit
price deflator for the appropriate period.
SOURCES OF PRIMARY DATA: International Monetary Fund.
Petroleum Intelligence Weekly.
2
Federal Reserve Bank of Dallas
Figure 1
Effect of an Appreciating Dollar
on the World Oil Market
DOLLAR
PRICE
DOLLAR
PRICE
DOLLAR
PRICE
U.S.
SUPPLY
AND
DEMAND
FOREIGN
SUPPLY
AND
DEMAND
D
o
SSL/DAY
WORLD
SUPPLY
AND
DEMAND
DF,
DF,
dl, dl, / \
sl, sl,
SSL/DAY
DW,
o
SSL/DAY
Q,Q,
FOREIGN
PRICE
PI,
PI,
FOREIGN
SUPPLY
AND
DEMAND
o
France, Italy, Japan, the United Kingdom, and West
Germany-the average real price of oil in local currency rose 16 percent (from fourth quarter 1980 to
fourth quarter 1984) while the real price of oil in
U.S. dollars fell 25 percent.
Higher foreign oil prices were one factor contributing to reduced world oil demand. In major
non-Communist industrialized countries other than
the United States, 1984 oil consumption was 7 percent lower than it was in 1980.' Previous research indicates that a number of factors contributed to
changes in world oil consumption during the first
half of the 1980s. These factors include a lagged oilconservation response to the sharp oil price increase
in 1979, fluctuations in worldwide aggregate
economic activity, changes in government regulations, and changes in the value of the U.S. dollar. In
Economic Review I March 1986
DF
SSLIDAY
addition, rising oil production in non-OPEC countries contributed to downward pressures on the
price of oiL'
The theory. As illustrated-in Figure 1, appreciation
of the dollar affects the world oil market by increasing world oil supply but reducing demand -leading
to a reduced dollar price of oil. But the reduction in
the dollar price is not sufficient to prevent an increase in the foreign price of oil.
Appreciation of the dollar changes the relationship between the foreign-currency-denominated
foreign supply of oil and the U.S.-dollardenominated foreign supply of oil. Foreign producers are willing to accept a lower dollar price at
every level of production. The supply increase is
shown as the shift from SF1 to SF2 .
Appreciation of the dollar also changes the rela3
tionship between the foreign-currency-denominated
foreign demand for oil and the U.S.-dollardenominated foreign demand for oil. Foreign consumers choose a lower level of consumption at
every dollar price. The decrease in U.S.-dollardenominated foreign demand is shown as the shift
from OF1 to OF 2 .
Together, the increase in foreign supply, which increases total world supply, and the decrease in
foreign demand, which reduces total world oil demand, establish a lower dollar price. In Figure 1,
these changes are shown as an increase from SW1 to
SW 2 , a decrease from OW 1 to OW 2 , and a reduction
from P1 to P2 .
As indicated previously, the reduction in the
dollar price of oil cannot be sufficient to prevent a
net increase in the foreign price of oil. The decrease
in the dollar price of oil leads to decreased U.S. oil
production (from s1 to s2) and increased U.S. oil consumption (from d1 to d 2 ). To balance these changes,
foreign oil production must be increased (from sf1
to sf 2 ) and/or foreign consumption reduced (from df1
to df 2 ). This increase in foreign production and/or
reduction in foreign oil consumption can be accomplished only if the foreign currency price of oil
is higher after the dollar appreciates and the dollar
price of oil falls. In Figure 1, this price increase is
shown as a movement from Pf 1 to Pf 2 4
If, as is shown in Figure 1, the increase in foreign
supply is smaller than the decrease in foreign demand, the equilibrium quantity of oil will be reduced. If, however, foreign supply increases more
than foreign demand decreases, the equilibrium
quantity of oil will be increased. Thus, as a result of
appreciation of the dollar, the total quantity of oil
produced and consumed worldwide may increase,
decrease, or remain the same.
Estimating the relationship
between exchange rate movements
and the price of oil
An equation based on supply and demand conditions in the world oil market was developed for
estimating the relationship between the inflationadjusted foreign value of the dollar and the
inflation-adjusted official pr,ice of Mideastern light
crude oil. Econometric analysis with this equation
showed that the official dollar price of Mideastern
light crude oil has a strong and statistically signifi4
cant response to changes in the foreign value of the
dollar. The long-run elasticity of the official price of
Mideastern light crude oil with respect to the value
of the dollar was estimated at -0.74.
The estimating equation. The estimating equation
was developed from underlying supply and demand
conditions. The quantity of world oil consumption is
a function of its price, the value of the dollar, and
worldwide aggregate economic activity. The quantity of oil supplied is a function of its price and the
value of the dollar. These demand and supply relationships are expressed in general terms as follows:
(1 )
Q = O(P, X, Y)
(2)
Q = S(P, X)
where
Q
the quantity of oil demanded and supplied.
P
the price of oil.
X
the foreign currency value of the dollar.
Y = worldwide aggregate economic activity.
In addition to exchange rates, other exogenous
factors-such as military conflict, property rights,
market structure, technology, and perceptions of
user costs-can have a major role in determining
the su pply of oi I. Because these factors are d ifficu It
to quantify, they have been omitted from the present analysis. To the extent that any systematic
changes in these factors occurred during the sample
period, the estimates in the regression analysis may
reflect some bias and inconsistency.
Although it is generally indicative of the market
price of oil, the official price of Mideastern light
crude oil does not adjust to clear the market in any
short period of time such as a quarter. Empirical
evidence suggests that although the price is set administratively, it generally reflects recent market
conditions.' This dependence can be captured by including lagged values of the dependent and independent variables in the estimating equation.
With these lags included, the estimating equation is
consistent with the reduced form of either a laggedadjustment model or an adaptive-expectations
model. The estimating equation is as follows:
Federal Reserve Bank of Dallas
m
1'.1.
n
where
+ l:)i In(Pt -;) + l:>i In(X t - i)
i=1
n
n
+ LOiln(Yt -;) + LAiln(Qt-i) +et
i=O
the estimated long-run elasticity of price
with respect to variable j.
i=O
II
z·I
i=1
a summation variable having a value of zero
or one; it has a zero value if a coefficient
was estimated for the natural log of the
coincident value of variable j.
where
Pt - i
the official price of Mideastern light
crude oil at time t - i.
the value of the dollar at time t - i.
the estimated coefficient for the natural log
of the ith lag of variable j.
II
[3i
the estimated coefficient for the natural log
of the ith P.
worldwide aggregate economic activity at
time t-i.
Qt-i
the equilibrium quantity of oil at time
t-i.
et
a random error that has a zero mean and
is normally distributed.
This estimating equation expresses the real ofhcial price of Mideastern light crude oil during any
period in time as a function of its own history, coincident and prior values of the dollar, coincident and
prior general economic activity, and prior
equilibrium quantities. Using natural logs of the
variables allows the estimated coefficients to be interpreted as elasticities.
The expected degree of multicollinearity between
coincident and lagged values of the independent
variables makes it difficult to place prior expectations on the signs of individual variables. Nevertheless, estimated long-run elasticities of price with
respect to the exogenous variables can be computed by combining the appropriate estimated coefficients. For the model to be acceptable, the
estimates of these long-run elasticities should be
consistent with the first-order conditions in the supply and demand equations.
For the demand equation, the first-order conditions for price are 8Pd /8X < 0, 8Pd /8Y > 0,
8Pd/8Q < O. For the supply equation, the first-order
conditions for price are 8Ps/8X < 0, 8Ps /8Q > o.
The long-run elasticity of price with respect to an
independent variable is estimated as follows:
Economic Review I March 1986
The long-run elasticity of the dollar price of oil
with respect to the value of the dollar should be
negative. An increase in the value of the dollar
decreases both the demand price and supply price
of oil (8Pd /8X < 0 and 8Ps /8X < 0).
In addition to being negative to conform to
theory, the long-run elasticity of the dollar price of
oil with respect to value of the dollar must be
greater than -1.0. The estimated long-ru n elasticity
of the foreign price of oil with respect to the value
of the dollar equals 1 + ~x' If Ax is less than -1.0,
the estimate will indicate an inverse relationship
between the foreign price of oil and the value of
the dollar, which is contrary to theory.
The long-run elasticity of the price of oil with
respect to worldwide aggregate economic activity
should be positive. An increase in aggregate
economic activity will increase the demand price
for oil (8 Pdf 8 Y > 0), and aggregate economic activity will have no effect on the supply price of oil.
Theory places no prior expectations on the longrun elasticity of the price of oil with respect to
quantity. An increase in the quantity decreases the
demand price for oil (8Pd /8Q < 0). On the other
hand, an increase in quantity increases the supply
price of oil (8Ps/8Q > 0).
In a lagged-adjustment model, however, positive
coefficients for the quantity variables would be consistent with demand adjusting more slowly to
changes in prices than does supply. Similarly,
negative coefficients would be consistent with supply adjusting more slowly to changes in price than
does demand.
Estimation. Equation 3 was used for an
econometric analysis of the relationship between
the real value of the dollar and the real official
5
dollar price of Mideastern light crude oil. This
analysis revealed that the relationship is statistically
significant and placed the long-run elasticity of the
dollar price of oil with respect to the value of the
dollar at - 0.74.
For the econometric analysis, data for the big
seven countries were used to represent the influences of .exchange rate movements and aggregate
economic activity on world oil prices. Of the freeworld countries, these seven-which have the
largest national products and consume the most
oil-represent nearly 75 percent of free-world oil
consumption.
Appropriate lag lengths for the variables were
selected in a two-step statistical procedure. After
the appropriate autoregressive structure for the
dependent variable was found, it was used in determining the appropriate lag length for the independent variables. Under this procedure, lags for all
variables were set at two quarters.
The autoregressive structure of the dependent
variable was determined by regressing the dependent variable on various lags of itself. The appropriate structure yields the highest F value for the
hypothesis that regression coefficients other than
the intercept are zero. On this basis, the structure of
the dependent variable was found to be two lags.
After the lag structure of the dependent variable
was set, that for the independent variables was
selected. Selection of the lags for the independent
variables was based on overall goodness of fit, adjusted for degrees of freedom.
I n a series of regressions, various lags of the three
independent variables were included as regressors
along with the coincident series for the value of the
dollar, the coincident series for aggregate economic
activity, and the two lags of the dependent variable.
For anyone regression, the same number of lags
was used for each independent variable. The appropriate lag length for the independent variables
was chosen by increasing the lag length until the adjusted R2 peaked. A search was not conducted to
determine whether the peak was local or global
because the sample size limited the degrees of
freedom for regressions with many lags. On this
basis, two lags were selected for the independent
variables 6
Estimation was conducted with quarterly data for
the interval from fourth quarter 1973 through fourth
quarter 1984. The beginning date was selected to
6
avoid inclusion of any data prior to second quarter
1973 because it was the first quarter in which exchange rates were no longer fixed. The availability
of data determined the end date.
Equation 3 was estimated as follows: 7
In(P t ) = 1.11
+
(6.56)
+
0.91 In(P t - 1 ) - 0.26 In(P t - 2 )
(- 2.50)
(7.12)
0.87 Xt - 0.32 In(X t _ 1) - 0.81 In(X t _ 2)
(2.03)
(- 0.53)
(-1.86)
-
+
-
0.95 In(Qt-1)
3.98 In(Yt)
(- 2.69)
(-2.14)
R2
=
.96, R2
=
5.49 In(Yt - 1) - 0.82 In(Yt - 2)
(2.05)
( - 0.45)
+
0.90 In(Qt-2)
(2.08)
.95, Durbin's h
-1.01
Overall F11 ,34 = 80.24
where
Pt - i
the real official price of Mideastern light
crude oil in quarter t-i.
Xt -
i
an index of the real oil-consumptionweighted value of the dollar in foreign
currency during quarter t - i and is
calculated with real exchange rates from
the big seven countries excluding the
United States.
Yt -
i
Qt-i
an oil-consumption-weighted index of real
aggregate economic activity in the big
seven countries during quarter t - i.
world oil production during quarter t - i.B
Overall test statistics indicate that the model provides an acceptable explanation of real official
prices for Mideastern light crude oil. The overall F
statistic indicates that the model explains the dollar
price of oi I at greater than the 99-percent confidence level. And the model satisfies requirements
for dynamic stability of the endogenous variable,
and the Durbin's h statistic indicates the absence of
autocorrelation. 9
The expected degree of multicollinearity between
the independent variables and their lagged values
makes it difficult to interpret the signs or
Federal Reserve Bank of Dallas
significance of individual coefficients. Nevertheless,
tests for the joint significance of groups of variables
are possible. Furthermore, by combining coefficients, long-run elasticities of the dollar price of oil
with respect to the exogenous variables can be
derived. These elasticities are more indicative of the
impact of movements in the exogenous variables on
the dollar price of oil than are individual
coefficients.
The F statistic shown in Table 1 indicates that
jointly the coefficients on natural logs of current
value of the dollar and its lags are significant at the
99-percent level. At -0.74, the estimated long-run
elasticity of the dollar price of oil with respect to
the value of the dollar is consistent with theory,
which predicted that the elasticity would be
negative but greater than -1.
The F statistic shown in Table 1 indicates that
jointly the coefficients on natural logs of current aggregate economic activity and its lags are significant
at greater than the 99-percent level. At 1.99, the
long-run elasticity of the dollar price of oil with
respect to aggregate economic activity is positive
and consistent with theory.
The F statistic shown in Table 1 also indicates
that jointly the coefficients on natural logs of the
lags of the quantity variable are significant at the
93-percent level. Nevertheless, the estimated longrun elasticity of price with respect to quantity is not
significantly different from zero. The lack of
significance of this long-run elasticity suggests that
whatever impact lagged quantity has in the short
run, these effects cancel each other when they
reach the equilibrium price in the long run.
The impact of recent exchange rate movements
on the price of oil
To estimate the impact of exchange rate movements
from 1981 through 1984, a simulated price series
was computed. This series represents the price of oil
Table 1
SUMMARY STATISTICS
I ndependent variables
Value
of the
dollar (X)
Aggregate
economic
activity (Y)
Quantity (Q)
4.23
4.64
2.86
Degrees of freedom
for F test
(F 3 ,34)
(F 3 ,34)
(F 2 ,34)
Estimated longrun elasticity
of price with
respect to
indicated variable
-0.74
1.99
-0.15
Standard error
of estimated
long-run elasticity
0.60
0.54
1.19
89*
>99*
<12**
F statistic for
joint significance
of coefficients
Significance of
estimated long-run
elasticity (in percent) .
* Significance level for a one-tail test.
* * Significance level for a two-tail test.
Economic Review I March 1986
7
Chart 3
Actual and Simulated Real Dollar Oil Price
1980 DOLLARS
35 .-----------------------------------------~
/
30
./
,
......
.-._ ........ -.,,
\
'
'-'
\
\,
\
SIMULATED
--- .. -----------
25
20 ~------~--------~--------~--------~------~
1984
1980
1981
1982
1983
1. Entry is the official price of Mideastern light crude oil, deflated to 1980 dollars.
SOURCES OF PRIMARY DATA: International Monetary Fund.
Petroleum Intelligence Weekly.
Authors' estimates.
under the assumption that the value of the dollar remained at its 1980 level through the end of 1984. A
comparison of this simulated price series with actual oil prices during the period 1981-84 indicates
that the appreciation of the dollar had a substantial
impact on the dollar price of oil.
To establish the price of oil that would have
prevailed in the absence of the dollar's appreciation
from its 1980 level, the actual price was multiplied
by a simulation multiplier derived from the
estimating equation and calculated as follows:
where
the value of the multiplier for quarter
t- i, for which values prior to first the
quarter of 1981 are set at one.
A
(3j
8
the estimated coefficient for the ith lag
of the dependent variable.
Xt -
j
X80
A
Cj
1 for quarters prior to first quarter 1981
and the actual value of the dollar for
quarters following fourth quarter 1980.
the 1980 value of the dollar.
a transformation of the estimated coefficient for the log of the ith lag of the
value of the dollar.
For the simulation, the estimated coefficients were
transformed to smooth the impact of changes in the
value of the dollar on the price of oil. This transformation preserved the long-run elasticity of the
dollar price of oil with respect to the value of the
dollar.'°
The result of the simulation is shown in Chart 3.
According to the simulation, the actual dollar price
of oil was more than 20 percent lower in the fourth
quarter of 1984 than it would have been had the
dollar not appreciated during the 1980s.
The simulation also has implications for the
foreign price of oil. As shown in Chart 4, appreciation of the dollar resulted in a sizable net increase
Federal Reserve Bank of Dallas
Chart 4
Actual and Simulated Real Foreign Oil Price
(1980=100)
140
r-----------------------------------------------,
130
ACTUAL'
120
110
/
."
,
.___a-- ........ --"""' ..
"
".
100
- .. _-----------_.
SIMULATED
90
80
70
60
1980
1981
1982
1983
1984
1. Entry is an index of the official price of Mideastern light crude oil that has been
deflated to 1980 U.S. dollars and multiplied by an oil-consumption-weighted index
of the real foreign value of the U.S. dollar.
SOURCES OF PRIMARY DATA: International Monetary Fund.
U.S. Department of Energy.
Petroleum Intelligence Weekly.
Authors' estimates.
in the foreign price of oil. According to the simulation, the foreign price of oil was more than 20 percent higher in the fourth quarter of 1984 than it
would have been had the dollar held its 1980 value.
The direct impact of a more than 50-percent appreciation of the dollar was partially offset by the
resulting decline in the dollar price of oil.
Outlook
Appreciation of the dollar contributed to downward
pressure on the dollar price of oil from 1981
through 1984 because it increased the price of oil
faced by producers and consumers in countries outside the United States. Appreciation of the dollar increased the supply but reduced the demand for oil
in these countries. And these changes in supply and
demand contributed to downward pressure on the
dollar price of oil.
Furthermore, the high value of the dollar likely
contributed to oil price declines throughout 1985.
Economic Review I March 1986
Although the real value of the dollar reached a high
in the first quarter of 1985, the official price of
Mideastern light crude oil adjusts to changes in
market conditions with a lag. Thus, some of the
decline in oil prices occurring after this peak can be
attributed to earlier increases in the value of the
dollar.
A number of factors other than exchange rate
movements also were important in reducing the
dollar price of oil in the first half of the 1980s. And
they may still be contributing downward pressure.
Nevertheless, the depreciation of the dollar
occurring in 1985 should eventually alleviate some
of this pressure. To the extent that the dollar
depreciates further, it would moderate any future
downward pressure on the price of oil.
9
1. Stephen Brown and Keith Phillips have shown that an
increased value of the dollar contributed to the decline in
world oil consumption between 1980 and 1983. See Stephen P.
A. Brown and Keith R. Phillips, "The Effects of Oil Prices and
Exchange Rates on World Oil Consumption," Economic
Review, Federal Reserve Bank of Dallas, July 1984, 13-21.
2. The major non-Communist industrialized countries are taken to
mean France plus the 21 signatory nations of the International
Energy Agency (lEA), which include Australia, Austria, Belgium,
Canada, Denmark, West Germany, Greece, Ireland, Italy,
Japan, Luxembourg, the Netherlands, New Zealand, Norway,
Portugal, Spain, Sweden, Switzerland, Turkey, the United
Kingdom, and the United States.
3. See Brown and Phillips, "The Effects of Oil Prices and Exchange Rates on World Oil Consumption."
4. A secondary effect of appreciation of the dollar is to reduce
U.S. demand for oil and to increase foreign demand for oil.
Appreciation of the dollar makes foreign goods cheaper in the
United States and U.S. goods more expensive in foreign countries, shifting industrial production out of the United States
and into foreign countries. Because those U.S. industries
adversely affected by increased foreign competition are
generally more energy-intensive than their foreign counterparts,
world industrial demand for oil will fall. If this reduction in the
world industrial demand for oil were the only effect of a
higher-valued dollar, it would be possible for appreciation of
the dollar to result in a lower foreign-currency price of oil. To
the extent that such an effect occurs, however, it would be
overshadowed by the primary shifts in demand and supply
described above.
5. See Philip K. Verleger, Jr., "The Determinants of Official OPEC
Crude Prices," The Review of Economics and Statistics 64 (May
1982): 177-83.
6. In a model with lagged dependent variables, ordinary least
squares has poor small-sample properties, resulting in biased
estimates.
Selecting lag length to maximize the adjusted R2 will result
in choices that are quite similar to that made with Akaike's
criterion for selecting lag lengths. Under Akaike's criterion, laglength selection is based on a statistic known as the final
prediction error. Both Akaike's criterion and the method
employed here select the lags that best predict the dependent
variable while rewarding parsimony in the number of lags
chosen. The adjusted R2 for selecting lags is preferred because
it is more closely related to the F test for overall significance
of the regression than is the final prediction error used in the
Akaike procedure. For a description of the final prediction
error and its use for selecting appropriate lag lengths, see H.
Akaike, "Fitting Autoregressive Models for Prediction," Annals
of the Institute of Statistical Mathematics 21 (1969): 243-47, as
cited and discussed by David A. Bessler and James K. Binkley
in "Autoregressive Filtering of Some Economic Data Using
PRESS and FPE," Procee'dings, Business and Economics
Statistics Section, American Statistical Association, 1980,
261-65.
8. The index of the oil-consumption-weighted value of the dollar
was calculated as follows: Xt = ~ WjXj t' where Wj is the weight
given country j's currency; X.J,t is an index of the real value of
the dollar as measured in country j's currency at time t; and
summation is over j for the big seven countries except the
United States. The weight given each country is calculated on
the basis of its share of oil consumption for these six countries
during the period from 1973 through 1984.
The index of aggregate economic activity is calculated as
follows: Yt = ~ Yj Yj,t' where Yj is the weight given country j's
aggregate economic activity; Yj,t is an index of real aggregate
economic activity in country j during period i-measured by
that country's gross national product or gross domestic product; and summation is over j for the big seven countries. The
weight given each country is calculated on the basis of its
share of big seven oil consumption during the period 1973
through 1984.
Nominal oil price data were obtained from the Petroleum Intelligence Weekly and deflated with the U.S. implicit price
deflator, which was obtained from the International Monetary
Fund (IMF). Indexes of the real value of the dollar measured in
each currency and indexes of aggregate economic activity in
each country were calculated with IMF data. World oil production data were obtained from various issues of the Oil and Gas
Journal, July 1973 through April 1985.
9. Given that the coefficient estimates satisfy stationarity conditions, the estimated model will have a stable equilibrium for
each setting of the exogenous variables. Had the coefficient
estimates not satisfied these conditions, the model would be
dynamically unstable, and a change in an exogenous variable
would result in the endogenous variable never reaching a
steady state again.
Stationarity is indicated if the following conditions hold:
<1
<1
< b2 < 1
b2
+
b1
b2
-
b1
-1
where b 1 and b 2 are the coefficients of first and second lags of
the dependent variable. Statistical tests based on these conditions indicated rejection of nonstationarity at greater than the
95-percent confidence level. For derivation of these stationarity
conditions, see George E. P. Box and Gwilym M. Jenkins, Time
Series Analysis: Forecasting and Control (San Francisco:
Holden-Day, Inc., 1970), 58-59.
10. Simulated prices calculated with these transformed coefficients are different than those calculated with the estimated
coefficients, but values calculated with the two methods approach each other asymptotically.
7. Figures shown in parentheses are t statistics.
10
Federal Reserve Bank of Dallas
The Labor-Intensive Nature
of Manufacturing High-Technology
Capital Goods
Robert T. Clair
Economist
Federal Reserve Bank of Dallas
With unemployment in the economy a costly problem, state governments may be seeking a solution
by encouraging the expansion of high-technology
equipment manufacturing. One approach to reducing unemployment is to encourage the development
of firms utilizing production processes that are
labor-intensive. A substantial number of state programs have been designed to attract all types of
high-technology firms to their locale or to encourage the expansion of high-technology firms
already in the state.
This article analyzes the production process for
manufacturing high-technology equipment in an
effort to determine whether the production
characteristics of that industry are consistent with
state objectives to encourage the expansion of
labor-intensive industries. The research here uses the
U.S. Department of Commerce definition of hightechnology equipment, which consists of office,
computing, and accounting equipment; communications equipment; and instruments.' The results of
the analysis show that an expansion in high·technology equipment manufacturing will create
more jobs than expansion in manufacturing of other
Economic Review I March 1986
types of producers' durable goods. Hence, state
government programs designed to attract or encourage the expansion of firms that manufacture
high-technology equipment are consistent with the
goal of reducing unemployment. Additional analysis
shows that high-technology manufacturing utilizes
low-skilled workers and that the average wage in
this industry is relatively low. As a result, income
gains may not appear as substantial as employment
gains.
Growth of high-technology industries attracts
interest of state and local governments
The growth of output and employment in the hightechnology equipment industry has been extremely
rapid in recent years. Private purchases of hightechnology equipment rose at an annual rate of 15.8
percent from 1977 to 1984, double the rate of
growth for all other producers' durable equipment.
The private purchases of high-technology equipment
and all other capital equipment for 1972 through
1984 are plotted in Chart 1. Because of the rapid
growth of purchases of high-technology equipment,
its share of the total producers' durable goods
11
Chart 1
Purchases of Producers' Durable Equipment
(1972 =100)
600
500
- - HIGH-TECHNOLOGY EQUIPMENT
---- ALL OTHER EQUIPMENT
400
/'
300
.................
.......
.. .......
-.
/'
~/ ..
200
100
'72
'73
'74
'75
'76
'77
'78
'79
'80
'81
'82
'83
'84
SOURCE OF PRIMARY DATA: U.S. Department of Commerce, Bureau of Economic Analysis.
market rose from 21.4 percent in 1972 to 32.6 percent in 1984.
The rapid growth of the output of hightechnology equipment generated tremendous
employment gains. Indexes of high-technology and
total nonagricultural employment are plotted in
Chart 2. From 1977 through 1983, high-technology
employment in the United States increased more
than 30 percent, compared with a 9-percent increase
in total nonagricultural employment. Although hightechnology employment is only a small share of the
nation's work force, representing less than 3 percent
of total employment, it accounted for 7 percent of
the new jobs created over that six-year period.
The rapid growth of high-technology output and
employment has sparked the interest of state and
local governments. Numerous programs have been
undertaken by state governments to encourage all
types of high-technology firms to expand their
operations within the states and to encourage other
high-technology firms to locate within the states'
borders.2
These state programs use various methods of
attracting or cultivating high-technology industries.
Direct financial aid programs provide equity capital,
research grants, lines of credit, and discounts on
12
utility charges. Research assistance programs
increase basic research at public institutions or
reduce the cost of research and development to
private firms.3 A common type of research
assistance program aids in the development of
commercial appl ications based on basic research
breakthroughs at universities and government
research laboratories. I n addition, some states are
investing in infrastructure that will encourage and
attract industries, and some of this investment is
specifically designed to encourage the expansion of
high-technology firms.' Finally, state educational
programs assist in the development of a hightechnology work force at all levels, from graduate
degrees for professional engineers to vocational
training for production workers.
State governments seek to reduce unemployment
by encouraging high-technology firms
One reason state governments implement these
programs is to increase the economic well-being of
their citizens by providing employment opportunities. More specifically, reducing unemployment
within the state is probably one of the goals of state
governments. Unemployment carries a high cost in
terms of output lost through the wasting of reFederal Reserve Bank of Dallas
Chart 2
High-Technology and Nonagricultural Employment
(1972 = 100)
160
150
HIGH-TECHNOLOGY
140
TOTAL NONAGRICULTURAL
130
--------- . -.. _-
120
110
100
90
'72
'73
'74
'75
'76
'77
'78
'79
'80
'81
'82
'83
SOURCE OF PRIMARY DATA: U.S. Bureau of Labor Statistics.
sources. For a state government budget, unemployment resu Its in the loss of tax receipts and an
increase in state government expenditures, such as
unemployment compensation and income transfer
payments.
Three main issues need to be addressed in determining the feasibility and effectiveness of these
types of state programs. First, will the state programs have an effect on the location and expansion
decisions of a high-technology manufacturing firm?5
Second, will the expected social benefits of such a
program exceed the program's expected cost?6
Third, will the expansion of operations of hightechnology equipment manufacturers create jobs
and, if so, what are the characteristics of these jobs?
The third issue is the focus of this article.
The remainder of the article addresses the third
issue by presenting empirical evidence that an expansion in the production of high-technology equipment will provide jobs and that the industry is
relatively superior to other major types of capital
equipment industries in this regard. The evidence
was obtained by estimating and comparing the production processes for high-technology, heavy industrial, transportation, and "other" equipment industries. 7 By examining these production processes,
Economic Review I March 1986
it is possible to describe the type of employment
that will most likely result from a program designed
to encourage high-technology equipment producers.
A production process that substantially reduces
unemployment will be labor-intensive. Beyond this
characteristic, the production functions are also examined for evidence of likely future wage increases
and job stability.
The production function
The primary purpose of the empirical work is to obtain estimates of the production functions of four
major types of producers' durable equipment.
Foremost, these estimations of production functions
will provide measures of labor share in the production process. Labor share data are necessary in
determining the amount of job creation that can be
expected from an expansion of various industries. In
addition, the estimated production functions will
provide measures of productivity and trends in longru n average costs that are needed to forecast likely
future wage increases. The estimations will also produce a measure of the substitutability of capital
and labor. This last characteristic is important in
determining job stability.
A production function is simply a mathematical
13
representation of the maximum quantity of output
that can be produced from a given amount of inputs. To obtain these estimates, constant elasticity
of substitution (CES) production functions were
estimated. The CES production function assumes
that the ability to substitute capital for labor remains constant-whatever the mix of capital and
labor. To simplify the analysis, separabil ity of
material inputs was assumed.
The CES production function was specified as
(1)
X =
e e~t [(1
-
d) K-P
+
dL -P]-I1/ P
Greek letters denote parameters that are to be
estimated. Italic letters represent variables except
for e, which is the base for natural logarithms. Output is denoted by X, capital by K, and labor by L.
The variable t is a time trend. An interpretation of
the relevant parameters is presented below.
I n the previous section, it was hypothesized that
state governments want to encourage laborintensive production processes in order to create
jobs and to reduce unemployment. Labor share, the
measure of labor intensity, is the parameter d. The
higher the value of labor share, the more laborintensive is the production process. If labor share
were to equal 1, then labor would be the only input
in the production process-that is, production
would be completely labor-intensive. In contrast, if
labor share were equal to zero, then labor wou Id
not be an input in the production process.
The production functions were also analyzed for
evidence of likely future wage increases. Future
wage increases are important to state governments
because they will correspond to increases in future
tax receipts. Wage increases must typically be supported by additional productivity. One source of
additional productivity is an increase in the quality
of inputs. For example, as labor becomes more experienced, it becomes more productive. This type of
productivity is measured by the rate of technical
change, ~. The rate of technical change is the
percentage increase in output that can be expected
each year without increasing any of the inputs. A
high value of ~ suggests a high rate of future wage
increases.
Productivity gains can also result from expanding
operations to take advantage of possible economies
of scale. I n some industries, increasing the scale of
operations permits average unit cost to fall. This implies that labor becomes more productive as the
14
average output per worker increases. The potential
to exploit economies of scale is measured by the
returns-to-scale parameter, /1. If the production function exhibits increasing returns to scale, a value of /1
greater than 1, then productivity gains can be
achieved by increasing the scale of operations. Such
gains can support higher future wages.
Finally, the production function was examined for
evidence of job stability. Although job stability is
not needed to reduce unemployment, it is assumed
that job stability is probably a secondary goal of
state government. Of course, one of the primary
factors determining job stability will be the stability
of demand for the output, but an analysis of the
demand for each type of producers' durable equipment is outside the realm of this article.
The parameter P from the estimated production
functions does provide a measure of how stable
employment is, given changes in the relative costs
of inputs: more specifically, how sensitive is the mix
of capital and labor to changes in wages relative to
the cost of capital. The elasticity of substitution between capital and labor measures this sensitivity.
The elasticity of substitution, 0, in the CES production fu nction is
(2)
o = 1/(1
+ pl.
A lower value for 0 implies a less sensitive reaction
in the input mix. For example, if wage3 should rise
relative to the cost of capital, then firms will substitute capital for labor. The lower the value of 0,
the less substitution of inputs will occur. Consequently, a lower value of 0 indicates greater job
stability.
Estimation technique and empirical results
The CES production function was estimated using a
two-step procedure. In the first step, the equilibrium
condition in the factors markets is used to estimate
the labor share and elasticity of substitution. These
estimates are then used in the second step, in which
the remaining parameters in the production function
are estimated. The details of this procedure are provided in the Appendix. The estimations used data
for 1968 to 1976.
The empirical results support the proposition that,
other things equal, an expansion in high-technology
equipment manufacturing will create more jobs
than expansion in the manufacture of other
categories of capital equipment. The results of the
Federal Reserve Bank of Dallas
Table 1
PRODUCTION FUNCTION PARAMETERS FOR FOUR
MAJOR TYPES OF CAPITAL GOODS, 1968-76 PERIOD
Type of
capital goods
Estimated from
equilibrium condition
Elasticity
of sublabor
stitution
share
d
a
Estimated from
production function
Rate of
technical
Returns
Efficiency
change
to scale
IJ
~
fl
High-technology
.325*
1.166*
1.098*
.028*
.107*
Heavy industrial
.281 *
1.251 *
.978*
.019*
.250*
Transportation.
.069*
2.420*
1.082*
.033*
.173*
Other
.112*
1.642*
.998*
-.030*
.829
* Significant at the .05 level.
estimations are presented in Table 1.8 The differences between high-technology parameters and
the parameters of the other industries are presented
in Table 2. The statistical significance of these differences is also presented in Table 2.9 Estimates of
d, the measure of labor intensity, indicate that the
production of high-technology equipment is
significantly more labor-intensive than transportation or "other" equipment production. Hightechnology equipment production has a labor share
of 0.325, whicb is higher than for any other category
of equipment production. Being more laborintensive suggests that expansion of high-technology
equipment manufacturing will create more jobs
than similar expansions in the manufacture of other
types of capital equipment.
Wages of high-technology workers are likely to
increase at a more rapid rate than are wages of
heavy-industrial workers or workers in the "other"
category.'0 In the long run, wage increases are
based on gains in productivity, and the rate of gain
in the productivity of workers is measured by the
rate of technical change. For high-technology equipment production the rate of technical change was
2.8 percent annually, significantly higher than the
rates for heavy industrial and "other" equipment
production. The high-technology rate of technical
change, however, was significantly below the
transportation rate of technical change.
High-technology equipment manufacturing has a
Table 2
DIFFERENCES IN PRODUCTION FUNCTION
PARAMETERS FOR HIGH-TECHNOLOGY
AND OTHER TYPES OF CAPITAL GOODS
labor
share
Elasticity
of substitution
Returns
to scale
Rate of
technical
change
Efficiency
d
a
fl
~
IJ
High-technology parameters less the respective parameters
Type of
capital goods
Heavy industrial
.044
-.085
-.121 *
.009*
-.143*
Transportation
.256*
-1.254*
-017*
-.005*
-.066*
Other.
.213*
-.476*
-.101 *
.057*
-.772*
* Significant at the .05 level.
Economic Review I March 1986
15
greater potential for productivity gains resulting
from expanding operations to take advantage of
economies of scale. The ability to exploit increasing
returns to scale requires the returns-to-scale
parameter, j.t, to be greater than 1. I n the case of
high-technology equipment manufacturing, the
returns-to-scale parameter, at 1.098, is significantly
greater than 1 and significantly higher than for the
other three categories of equipment.
It is clear that high~technology workers appear
likely to have larger wage increases than either
heavy-industrial workers or "other" workers, but it
is ambiguous whether wages of high-technology
workers will increase more than wages of transportation workers. Compared with heavy-industrial and
"other" workers, high-technology workers are in production processes in which labor has both a higher
rate of technical change and a greater potential for
the advantages of economies of scale. Compared
with transportation workers, high-technology
workers also have a greater possibility of productivity gains attributable to economies of scale. The
transportation workers, however, have a higher rate
of technical change. The ambiguity occurs in
whether the rate of technical change or the potential for economies of scale will be the dominant
factor in determination of productivity gains and
wage increases in the future.
When the goal of long-run job stability is taken
into account, high-technology workers are less likely
to be replaced by capital. As stated before, this is
only one factor promoting job stability, but a lower
value for the elasticity of substitution does indicate
the relative difficulty in substituting capital for
labor in the long run. High-technology equipment
production has an elasticity of substitution between
capital and labor of 1.166- the lowest among the
four categories of capital goods and significantly
lower than the elasticity of substitution for transportation or "other" equipment. Consequently, in the
long run, changes in the relative costs of capital and
labor will have less effect on employment for hightechnology equipment production than for production of transportation or "other" equipment."
High-technology manufacturing reduces
structural unemployment of low-skilled workers
The employment gains that would result from an expansion in high-technology equipment manufacturing are likely to be concentrated among low-skilled
16
workers. It is clear from the estimation of the production function that high-technology equipment
production is labor-intensive. While there is a correlation between labor-intensive production processes and processes utilizing low-skilled workers,
further evidence is needed to show that the hightechnology work force is low-skilled.
The best evidence that the work force of hightechnology equipment producers is low-skilled is its
low relative wage. Low-skilled workers are less productive and, consequently, receive a lower wage.
The average wage in high technology is substantially
below that in heavy industrial or in transportation.
Chart 3 shows the average annual wage in each of
the four categories of producers' durable equipment
production. In 1976 the average wage of workers in
high-technology equipment production was roughly
two-fifths that of heavy-industrial workers and onehalf that of transportation workers. It was marginally above the average wage of "other" workers.
Given this wage structure, it is apparent that hightechnology equipment production is a low-skilled,
labor-intensive process.
Creating jobs for low-skilled workers is very important because unemployment of these workers is
much higher than average. A direct measure of the
unemployment rate for low-skilled workers is not
available, but a close proxy may be the unemployment rate for teenagers. Workers 16 to 19 years of
age typically have little job experience and, consequently, have not obtained on-the-job training that
might provide job skills. Furthermore, at their young
age, it is unlikely that these workers have received
advanced formal education, such as in college. The
unemployment rate for individuals 16 to 19 years
old is, on average, more than three times the
unemployment rate for individuals 20 and older.
High-technology manufacturing faces
substantial foreign competition
One reason for the high unemployment of lowskilled workers in the United States is the competition these workers face from foreign low-skilled
workers. In nonindustrialized economies, there is
usually a large work force of low-skilled labor. This
plentiful supply of workers depresses the wages of
foreign low-skilled labor. As a result, businesses
deciding to locate low-skilled, labor-intensive production processes must evaluate whether savings
from the lower labor cost of operating in many
Federal Reserve Bank of Dallas
Chart 3
Average Wages in Equipment Manufacturing
THOUSANDS OF DOLLARS
25
.......... HEAVY INDUSTRIAL
20
................
./...../ ............ /
-._.- TRANSPORTATION
- - HIGH-TECHNOLOGY
----- OTHER
15
...................
10
5
,_.-.-.1
,,'
................................/ ..._...........-.........................
---=-"'"-,--------------------i'
::--::--:;.:--:.:::-----:----.-. _. _. _. -. -. -._'
-~-.----------
o
'58
'60
'62
SOURCE OF PRIMARY DATA:
'64
u.s.
'68
'70
'72
'74
'76
Bureau of the Census.
foreign countries will offset the higher shipping
costs and any tariffs. In general, low-skilled, laborintensive industries in the United States are at a
disadvantage when competing with Third World
producers. Consequently, fewer low-skilled jobs are
created in the United States, and unemployment of
low-skilled U.S. workers is higher.
Because high-technology equipment production is
labor-intensive and utilizes low-skilled labor, it will
be subjected to substantial foreign competition.
There is already evidence of a shift of hightechnology equipment manufacturing to foreign
producers. The semiconductor industry began
assembling chips in the Far East in the early 1970s.
As quality controls of foreign producers improved, more complex components were "outsourced" - that is, produced overseas. Early in
1984, Atari completed transferring all its manufacturing operations to Taiwan. In late 1984, Motorola
located three plants in Mexico, and Digital Equipment and IBM applied for permission to locate
computer production facil ities there. 12
State governments face a real dilemma. Programs
designed to attract or encourage the expansion of
high-technology firms, with the goal of employing a
sizable number of structurally unemployed workers,
Economic Review I March 1986
'66
may produce fewer jobs in the long run as a result
of foreign competition. On the other hand, encouraging the high-technology areas in which the
United States could maintain a comparative advantage-such as research, software programming, and
sophisticated manufacturing-will affect few of the
structurally unemployed workers. The primary point
of this dilemma is that there are no easy solutions
to the problem of structural unemployment. For a
governmental program to be successful in the long
run, it will probably need to promote the retraining
of the structurally unemployed workers and, at the
same time, attract firms that can utilize their newly
acquired skills. 13
Conclusion
This article examines the implications for employment arising from state government programs
designed to attract and encourage the expansion of
high-technology firms. One method of reducing
unemployment is to encourage the expansion of
labor-intensive industries. The results of the research
here show that state programs designed to attract or
encourage the expansion of firms that manufacture
high-technology equipment are consistent with the
goal of reducing unemployment.
17
The production process of manufacturing hightechnology equipment was estimated. From the
results of this estimation, it is clear that hightechnology manufacturing is relatively laborintensive. I n addition, an analysis of wages suggests
that the high-technology workers are, on average,
low-skilled workers. Consequently, the expansion of
high technology will have a large impact on reducing structural unemployment of low-skilled workers.
The results of the estimation also indicate that hightechnology workers will have rising real wages over
time as a result of productivity gains. Moreover,
there is some evidence that long-run job stability is
greater in high-technology manufacturing than in
the manufacture of other types of producers'
durable equipment.
1. The term "high technology" has been applied to a multitude
of industries, so much so that it may now be somewhat ambiguous. For the sake of clarity, the Commerce Department
will soon call this category information-related durable
equipment.
2. It is not possible to determine to what extent these programs
are designed to attract or encourage the expansion of hightechnology firms other than producers of high-technology
equipment.
3. "Basic research" is defined as investigation to gain knowledge
for its own sake.
4. Alton K. Marsh, "High Technology/Southwest U.S.: New Mexico to Build On-line Data Link," Aviation Week & Space
Technology, 27 August 1984, 55-57.
5. There is evidence that state governments can affect decisions
by high-technology firms to expand operations. A survey of 240
high-technology manufacturing firms in the Tenth Federal
Reserve District showed that state government programs can
have significant impact on the decision of high-technology
manufacturing firms to expand operations within a state but
state government programs are unlikely to exert a major influence in attracting new high-technology firms. The survey
reveals that financial incentives provided by the state government, such as low-interest loans and reduced taxes, would be
considered significant factors in expansion plans by 68 percent
of the survey firms. The definition of high-technology manufacturing used in that survey is somewhat broader than the
Commerce Department definition used in this article. See
Tim R. Smith and Marla Borowski, "High-Technology Development in the Tenth District," Economic Review, Federal Reserve
Bank of Kansas City, November 1985,9-24.
6. Whether the social benefits exceed the costs is an unresolved
question. The existence of state government programs to encourage the development of high-technology firms is evident.
In 1985, 33 states had programs to promote high-technology in-
18
dustries. See Miriam Rozen, "State Programs Lure High Tech
Companies," Dun's Business Month, March 1985, 93. The existence of such programs makes important the issue of whether
the job characteristics of high-technology manufacturing are
consistent with reducing unemployment.
7. The producers' durable equipment industries have been
categorized by the Commerce Department, by type of output,
as high-technology, heavy industrial, transportation, or other.
The category "other" refers to all capital equipment that does
not fit in the first three categories. High-technology equipment
includes office, computing, and accounting equipment; communications equipment; instruments; and electronic components. The high-technology category also includes part of
the software industry-that software produced and sold by
computer manufacturers but not that written and sold by
independent software houses.
The category of heavy industrial equipment consists of a
variety of goods, including engines, turbines, metalworking
machines, and electrical transmission equipment, such as
transformers and switchgears. Also included in this category
are such general industrial machinery as pumps, fans, bearings,
nonautomotive transmissions, and furnaces. Finally, heavy
industrial equipment includes special machinery for such industries as food processing, textiles, woodworking, paper, and
printing.
The remaining two categories of producers' durable equipment are transportation and" other." All modes of transportation are included in the transportation equipment category
except defense and space equipment and recreational motor
vehicles, such as motorcycles and motor homes. The producers' durable equipment industries that are not classified
above are grouped together as other equipment. This group includes construction equipment, mining and oil field machinery,
and agricultural machinery.
An alternative categorization of high-technology equipment
and" all other" capital equ ipment was considered and rejected
following empirical tests that showed the aggregation of heavy
industrial, transportation, and other capital equipment was not
justifiable.
8. The data used for the estimations were published in the Annual Survey of Manufactures and the Census of Manufactures.
Output (X) was total value added, and labor (L) was total
employment. The capital stock data were constructed using
the Census data on book values of fixed assets as benchmarks
and using the perpetual inventory method to generate capital
stock figures for the years between censuses. Wages were
calculated as total salaries and wages divided by total employment. The rate of return on capital was calculated as the difference of total value added less total salaries and wages
divided by the capital stock. For a description of this method
of generating the capital stock and the return on capital, see
Robert F. Engle, "A Disequilibrium Model of Regional Investment," Journal of Regional Science 14 (December 1974):
367-76.
9. Two statistical tests of the differences in the parameters were
conducted. First, the hypothesis that one of the other three
production functions was identical to the high-technology
production function was tested using a Chow test. The results
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