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CAC DOCUMENT No. 2lU
NET ENERGY ANALYSIS; HANDBOOK FOR
COMBINING PROCESS AND INPUT-OUTPUT
ANALYSIS
By
Clark W. Bullard
Peter S. Penner
David A, Pilati
October 1976
SEP. 13J977, .
ine person charging this material is re-
sponsible for its return to the library from
which it was withdrawn on or before the
Latest Date stamped below.
Theft, mutilation, and underlining of books
are reasons for disciplinary action and may
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UNIVERSITY OF ILLINOIS LIBRARY AT URBANA-CHAMPAIGN
CAC DOCUMENT 2lU
NET ENERGY ANALYSIS:
HANDBOOK FOR COMBINING PROCESS AND INPUT-OUTPUT ANALYSIS
by
Clark W. Bullard
Peter S. Penner
David A. Pilati
October 1976
Energy Research Group
Center for Advanced Computation
University of Illinois at Urbana-Champai^n
Urbana, Illinois 6l801
This work was supported by the Energy Research and Development Administration
ABSTRACT
Methods are presented for calculating the energy required, directly and
indirectly, to produce all types of goods and services. Procedures for combining
process analysis with input-output analysis are described. This enables the
analyst to focus data acquisition effects cost-effectively, and to achieve a
specified degree of accuracy in the results. The report presents sample calcula-
tions and provides the tables and charts needed to assess total energy re-
quirements of any technology, including those for producing or conserving
energy.
ACKNOWLEDGEMENT
This work was supported by the U. S. Energy Research and Development
Administration. We wish to express our thanks to Donna Amado who was responsible
for the computer programming and to Charles R. Mandelbaum of ERDA for helpful
comments on an earlier draft of the manuscript.
Digitized by the Internet Archive
in 2012 with funding from
University of Illinois Urbana-Champaign
http://archive.org/details/netenergyanalysiOObull
Table of Contents
Page
1. INTRODUCTION 1
1.1 Definitions and Conventions 2
2. METHODOLOGY k
2.1 General k
2.2 Process Analysis h
2.3 Input-Output Analysis 10
2.k Combining Process and Input-Output 19
3. DISCUSSION 29
REFERENCES 31
APPENDIX A Tables for Computing Indirect Energy Requirements .... 33
Table A-l. Industry Classification of the 1967 Input-Output
Tables 3^
Table A-2. Price Indices 38
Table A-3. Margins on Direct Energy Sold to Final Demand .... ho
Table A-k. Margins on Goods and Services Sold to Final Demand . l+l
Table A-5. Energy Cost of Goods and Services - 106T ^3
Table A- 6 . Major Products of Common BEA Sectors 55
Table A-7. Error Tolerances {% of Mean) for 90 Energy Intensities 65
APPENDIX B Bibliography 67
List of Figures
Figure 1. Successive Stages In a Process Analysis 5
Figure 2. Production of Cars 7
Figure 3. Production of Energy & loods 8
Figure k. Hypothetical 3-Sector Process Analysis 9
Figure 5. Energy Balance for a Producing Sector 10
Figure 6. Systems Boundaries for Process and Input -Out-put Analyses . 21
List of Tables
Table 1. Specification of Production Technologies 10
Table 2. Energy Cost of a Computer 17
Table 3. Limitations of Input-Output Analysis 18
Table h. Second Approximation Energy Cost 2k
Table 5. Third Approximation Energy Cost 26
Table 6. Sample Hybrid Analysis * 25
1 . INTRODUCTION
When we consume anything, we consume energy. It takes energy to manu-
facture, deliver and sell all types of goods and services. It is possible
to add up the energy required at each step of the production process to
determine the total "energy cost" of particular goods and services.
The concept also applies to facilities that produce or conserve energy.
It takes energy to construct and operate oil wells and pipelines, and this
must be compared to the energy output. Similarly, it takes energy to manu-
facture insulation for homes and efficient capital equipment for industry;
these energy costs must be compared to the energy savings.
Consumers demand energy in two ways: directly and indirectly. Energy
is consumed directly in the form of gasoline, electricity, natural gas, or
fuel oil. It is consumed indirectly as energy used elsewhere in the economy
to produce the other goods and services purchased by consumers. Indirect
energy is by no means negligible ; the average consumer demands more energy
indirectly than directly (Herendeen and Tanaka, 1975).
To clarify the concept of energy cost, consider aluminum as an example.
A certain amount of energy is consumed directly in the ore reduction process.
But energy is also required to mine the bauxite and transport it to the
smelter. Additional energy is needed to manufacture the mining and transpor-
tation equipment, and to make the inputs to those industries. All these
energies have to be summed to determine the total energy cost of aluminum.
The purpose of this report is to provide a practical guide for calculat-
ing the energy cost of any item. Two methods are described. One is tedious
and involves adding all the energy inputs individually and is subject to
error because some inputs are inevitably neglected. The other is a simpler
one-step operation that has inaccuracies due to the level of aggregation at
which goods and services are defined. We describe both methods, and then show
how to combine them to minimize the effort required to obtain a predetermined
degree of accuracy in the result . Appendix A gives most of the data needed
for any application. Appendix B contains an extensive bibliography, organized
by subject category, covering the theory and application of both process and
input /output analysis.
The range of possible applications is quite broad. Energy analyses
have been used to determine the overall energy efficiency of systems as varied
as beverage containers (Hannon, 1973) and nuclear power plants (Rotty, et al. ,
1975). Published results of energy analyses (particularly net energy analyses)
vary for a host of reasons, due to differences in computational techniques,
system boundaries, types of fuels and energy, etc. (Bullard, 1976, Pilati, 1977)
This report is limited to treating the computational issues involved in such
analyses. The methods and results presented are consistent with a forthcoming
set of ERDA guidelines for net energy analysis (Perry, 1977).
1.1 Definitions and Conventions
The data and methodologies described in this report permit calcula-
tion of five types of energy "embodied" in a particular goods or service.
One calculation determines the coal required, directly and indirectly, to
produce a unit of aluminum. Parallel calculations yield the total crude oil
and gas, refined oil, electricity, and natural gas requirements. All these
inputs are useful for certain purposes, but they are not directly additive to
obtain a "total energy requirement." For example, due to the direct plus in-
direct nature of the calculations, there would be some double counting of
electricity and the coal used to produce electricity.
To obtain a total energy figure, we adopt the convention employed
historically by the U.S. Bureau of Mines to combine U.S. fuel and electricity
consumption. This convention views coal, crude oil and crude gas as primary
fossil energy resources, and expresses physical quantities (tons, bbl, cu. ft.)
in terms of their total enthalpy. Similarly, hydro ani nuclear electricity
are viewed as primary energy resources, whose enthalpies are evaluated in terms
of their fossil fuel equivalents using the prevailing heat rate for fossil
electric power plants. These enthalpies are then added to define a total
primary energy requirement, and double- counting is avoided.
Similarly, we define a total primary energy intensity as the energy
required directly and indirectly to produce a unit of gDods or services for
final comsumption. It is calculated by adding the (direct plus indirect)
coal intensity, crude oil and gas intensity, and the fossil fuel equivalent
of the hydro and nuclear electric intensity. It is useful to compare the
total energy intensities of goods and services for broai-based analyses of
conservation options, such as substituting fiberglass for steel in a manufactur-
ing process. In specific instances where options for fuel substitution are
limited (e.g. aluminum production), it is more useful to retain the individual
fuel intensity detail. In particular, net energy analyses often require that
the distinction between fuels be maintained, because the object of the analysis
is often a a facility (e.g. a power plant) for converting one form of energy
to another. "Viewing all Btu's as equal" obscures the economic purpose of
the facility (Bullard, 1976).
For the types of energy considered here, total enthalpy is approximately
equal to Gibbs ' free energy. The latter is viewed by many as the "ultimate"
measure of energy consumption because it is truly consumed and cannot be re-
cycled. For practical purposes in these calculations, the two are equal.
**
Energy intensity and energy cost are used interchangeably in this report.
2. METHODOLOGY
2.1 General
The energy cost of any economic activity can "be measured "by either of
two general methods: Process analysis or input-output (i-O) analysis. As
will he shown, "both theoretically require the same data and would yield the
same result if a fully disaggregated data base were available. In the real
world, each technique is most useful for a particular type of problem. Ag-
gregated, nationwide problems are well suited to 1-0 analysis because the
data base for this analysis is a 363-sector model of the entire U.S. economy.
Process analysis is more suited to specific processes, products, or manufac-
turing chains for which physical flows of goods and services are easy to
trace.
2.2 Process Analysis
Process analysis "begins by identifying one particular product as the
object of study. This target product may be either a good or a service. One
then examines the industry which makes the product and asks , "What goods and
services were required directly by this manufacturer to produce the target pro-
duct?" When the list of such inputs is obtained, it will include some fuels
(direct energy) and some non-energy goods and services from other industries.
The direct energy use is tallied while each non-energy input is further examined
to determine the energy and non-energy inputs required for its production. This
process continues, tracing back from the target product through each stage of
the production process, (fig. l). 3ach successive step in the analysis typical-
ly identifies smaller and smaller energy inputs, and all these energy inputs
are summed to obtain the total energy intensity of the target product. The
first energy input is called the direct energy requirement, the remainder is
INPUTS TO
A
o
o
INPUTS
TO
B
o
o
INPUTS TO
TARGET PRODUCT
Production of
Target Product
STAGE 3
STAGE 2
STAGE 1
FIGURE 1. SUCCESSIVE STAGES IN A PROCESS ANALYSIS
called the indirect energy requirement. It is often the case that certain
items appear as both inputs and outputs several places in the production tree,
reflecting feedback loops of economic activity.
In stage 2 and beyond, the indirect energy inputs are identified and sum-
med. Note that indirect energy inprts include the energy consumed in energy
producing industries .
In fig. 1, there are four inputs to the production of the target 'pro-
duct. Suppose input A is energy ani B, C, and D are nonenergy goods and
services. The direct energy requirement is simply input A. Indirect energy
inputs to the target product are the sum of energy inputs to all the pro-
duction processes in stages 2, 3, and beyond.
In practice, a large number of terms is never computed, and the analysis
is terminated at a point where the input is believed tc add a negligible
amount to total energy use. At the' second stage only the most significant in-
puts are considered, and of those, only a subset is further broken down into
its components. Unfortunately, diminishing contributions from each stage pro-
vide no guarantee that the truncated infinite number of terms actually sum to
a negligible quantity.
Performing a process analysis requires extensive data on the production
of the target product and similar (but usually less detailed) data on any
secondary, tertiary, and other inputs not truncated. For aggregated pro-
duction sectors, data are obtained from government statistics on economic
activity. For induvidual production process, information must often be col-
lated directly from manufacturers, trade associations, and consultants. If
all flows can be measured in physical units, there is usually no reason to
introduce dollar values in the analysis, so the resulting energy intensity is
expressed in physical terms (Btu/unit of target product).
As an example, we shall calculate the energy intensity of cars in a simple
3-sector economy.* This hypothetical economy consists cnly of energy (mea-
sured in Btu) , cars and another aggi-egate industry composed of all other goods
and services. We shall simply label this aggregate industry "goods" and
presume its output is measured in dollars due to the heterogeniety of its out-
put. Assume that census data for all three sectors in this hypothetical eco-
nomic-system identify the inputs for each industry's production precess. A
typical production facility in the car industry uses .6 car, .01 Btu energy
and $.25 worth of goods to produce one car. (in this entire example, the
numbers are chosen arbitrarily). The final stage of production is shown
in Figure 2.
01 Btu energy
Car
Production
♦ 1
car
25 $ worth of goods
Figure 2: Production of Cars
Similarly, typical energy and goods production facilities use inputs as shown
in figures 3a and 3b. Energy extracted from the earth does not appear in
fig. 3a, only purchased energy inputs are shown.
(Battelle, 1975) and (Teasley, 197*0 provide excellent examples of practical
process analyses .
,088l Btu energy
5 cars
2 $ goods
Energy
Production
(a)
Goods
Production
*► 1 Btu
energy
"► $ worth of goods
(b)
Figure 3: Production of Energy and Goods
We now have most of the data necessary to calculate the energy intensity
of cars using process analysis. The production "tree" is shown in fig. U,
where dashed lines denote inputs that are ignored, and represent the truncation
points for the analysis. Values for input flows exactly maoch figures 2 and 3
in the first production stage where the output is one unit. Outputs at all other
stages are less than one unit and their inputs are scaled accordingly. For ex-
ample, in the second stage, 0.6 cars are produced, so scaling the inputs in fig.
2 gives (.6)(.0l) Btu, (.6)(.6) cars, and (.6)(.25) $ goods.
.00005
.00? '
.0012--''
production
0l'6mm
ei.crgy
prou-ction
072.—-^
.06^
.015 .:
goods
production
.00381
.05
.02-'""
ener^/-
production
.025 — -=f goods
•Drod'j^tion
Figure h. Hypothetical 3-Sector Frocess Analysis
In fig. k, the direct energy input to car production is 0.010 Btu/car.
There are an infinite number of indirect inputs, all but three of vhich are
neglected. They sum to .006 + .100 + .036 = .lU2 Btu/car. Thus process
analysis yields a total (direct plus indirect) energy intensity of 0.152
Btu/car. The truncation error is unknown.
In this simple 3-sector example it is clear that we have sufficient
data to carry the process analysis on for an indefinite number of steps.
In a real problem, however, a process is truncated to reduce the data acqui-
sition effort. For example, in an economic system with hundreds of sectors,
a process analyst may follow only the largest branches on the tree to limit
data acquisition efforts to those sectors most important to the particular
target product .
In Table 1, the inputs shown in figs. 2 and 3 are arranged in matrix
form, normalized to one unit of output. This matrix is one way to represent
the technologies for all goods and services in our hypothetical economy. Note
9
that it shows only interindustry flows , not resource flows from Earth to
producing industries .
input + to production of -> energy cars goods
energy .0881 Btu/Btu .01 Btu/car .h Btu/$
cars .5 cars/Btu .6 cars/car .1 cars/$
goods .2 $/Btu .25 $/car 0 $/$
Table 1. Specification of Production Technologies
Entries on the diagonal show the amount of self-input required to pro-
duce 1 unit of output. For example, each Btu of energy output requires .0S8l
Btu of energy input. This representation of the data, as we shall see below,
is useful for input-output analysis.
2.3 Input-Output Analysis
Input-output analysis is a modeling technique used extensively in
economic research since its introduction in 19^1 (Leontief, 19^1). It has
been adapted to analyze energy and labor intensities (Bullard and Herendeen,
1975). The structure of the model, a large linear network, remains the same
for any variable. Initially the economy must be disaggregated into N major
sectors, each producing a unique good or service and each characterized by a
node in the network equations. Examples of these sectors might be primary
metals , retail trade or petroleum products . Figure 5 shows the energy flows
entering and leaving each sector.
N
E e. T. -
. , 1 in
1=1
' n n
Figure 5. Energy Balance for a Producing Sector
L0
Energy embodied in inputs from other sectors enters at the left and can
he expressed as e. T. , energy intensity of product i times the input of
sector i to sector n. Energy embodied in the sector's output is shown exit-
ing at the right and is expressed as the product of the energy per unit of
sector n output (e ) and its output (X ). If in fig. 5, sector n
n n
denotes the energy sector, a nonzero amount E is extracted from the earth.
The energy balance equation becomes :
N
I e. T. + E = e X (l)
. .. 1 in n n n
i=l
or, in matrix notation ve have:
e_T+E = £X. (2)
The above set of N equations can be solved for the N ummowns , e_. X is the
diagonal matrix whose elements represent the total output from each sector.
For a typical product, n, the production technology is represented by a
vector A where a typical element A. represents the amount of product i
needed directly to produce a unit of product n. The N x N matrix A_ then pro-
vides a linear representation of the technology of producing all goods and
services. From this definition of A we have:
T = A X (3)
and eq. (2) becomes:
£ = e (I-A)"1 (U)
where _e is a unit vector which identifies the energy sector row of (l_-A)
as the energy intensities.* For a multi-fuel economy, this analysis can be
repeated for each type of energy (coal, oil, etc.) and the total primary
This unit vector appears algebraically because E = X for the energy sectors;
their output defined to equal what they extract from the earth.
LI
energy intensities can "be calculated (Bullard and Herendeen, 1975).
Though 1-0 is a simple and elegant technique, it would hardly he useful
without large amounts of data. The U.S. Department of Commerce has reported
economy - wide data separated into 368 sectors of economic activity for 19o3
and 1967. From these data, the A (technological coefficients) and X (total
output) matrices are determined. Physical data for the E_ (energy) vector
are available from a variety of sources (see Bibliography) and are equal
to the output, X , of the primary energy-producing sectors. Thus, eq. (k)
can be solved for an e_ (energy intensity) vector containing 368 values for the
entire economy in the year studied.
This pure 1-0 approach implicitly assumes that the target product is
typical of a certain sector's output. (The same assumption was made for "cars"
in the process-analysis example.) Treatment of atypical products is duscussed
in section 2.3.4.
2.3.1 3-Sector Example
In the following example, input-output analysis is used to compute the
energy cost of goods in our hypothetical 3-sector economy. Both the data
base and the result should be compared to the process analysis example given in
the previous section.
The technology of producing energy, cars, and goods, is given by
the same matrix presented in Table 1.
A
For this matrix:
(I- A) =
(I-A)
-1
.0881
.5
.2
.9119
-.5
-.2
1.^72
2.041
.805
.01
.6
.25
-.01
.h
-.25
.1+32
3.265
.903
.1+
.1
0
-.h
-.1
1.0
.632
1.1U3
1.42
To obtain energy coefficients, the above must be multiplied by e_, the unit
energy vector. This vector is the energy extracted from the earth by each
sector per unit output; in this example it is (l 0 0).* Finally the product
of e_ and ( L-A) gives :
e_ = [1.1*72 Btu/Btu .1+32 Btu/car .632 Btu/$ ]
We now have the total energy required per unit output for each sector in
the hypothetical 3-sector economy. In the previous section a truncated pro-
cess analysis was used to calculate the energy cost of cars in this economy.
The previous result of .152 Btu/car is about one-third of the result obtained
from 1-0 analysis (.U32 Btu/car). We therefore find that in this example the
truncation error was not negligible.
2.3.2 A Simple I-Q Example
Now we consider a more practical application of input -output analysis. It
makes use of a 357-sector description of the U.S. economic system in 1967. It
includes detailed information on consumption of five forms of energy by each
sector, and is based on data from the U.S. Bureau of Mines and the U.S. Depart-
ment of Commerce Bureau of Economic Analysis (BEA).
In this example we shall calculate the energy cost of a typical large
computer. We assume that the price (to the ultimate consumer) was $1,000,000
in 1970. The first step is to determine which of the 368 BEA economic sectors
produces computing machines. Refer to Table A-l in Appendix A and notice that
sector 51.01 is denoted "computing and related machines." The table also lists
the SIC (Standard Industrial Classification) industries included in BEA sector
51.01. Thus for a more detailed description of 51.01, one could check either
the 1967 SIC manual or the 1967 Census of Manufactures (see Bibliography) to
insure that the correct sector is used.
*
In reality, the energy sectors are not perfectly efficient and so require
more than one Btu per Btu output because of indirect inputs. This is reflected
in the value of e for the energy sector.
13
Having identified the appropriate sector, the corresponding energy
intensity can be obtained from Table A-5 , and it is multiplied by the
quantity of computers to obtain the total energy cost. The total primary
energy intensity given in the table is hf ,116 Btu per 19^7 dollar's worth of
computers. The Department of Commerce data used to construct the 1-0 tables
in 1967 measured that sector's output in dollars because of the aggregation
within the computer industry; that is why the energy intensity is given in
those terms. This is true for all nonenergy sectors in the US input-output tables;
only the five energy sector outputs are expressed in physical units (Btu).
However, due to inflation between 19&7 anc^ 1970, there is a difference be-
tween one million 1967 dollars' worth of computers and one million 1970 dollars'
worth, even though we're talking about exactly the same machine. If we con-
vert the $1 million price tag in 1970 to 1967 prices, we can remove the effects
of inflation, and the "1967 dollars" unit of measurement becomes a surrogate
for a physical unit of measurement.* Using price indices (deflators) from
Table A-2 we calculate the quantity of computers in units of 19&7 dollars:
Value of a million
dollar (1970) cc
in 1967 dollars
nr ho7n + tin6 (1967 price index for 51.01) fin6* 1.0
^L49I?L'°mpUter = $1° 71970 price index for 51. Ol) " (l° ) LM5
(10 ) .99 = $990,000 (1967)
This figure is multiplied by the total primary energy intensity (e) for
Sector 51.01, found in Table A-5 :
•Energy cost of = $ ( g } ^ ^ 6 Btu/$196T = U6>6U Billion Btu
computer
Note that if we were to use purely physical units we could avoid the problems
of dollar cost deflation. If physical quantities are known, these can often
be energy-costed directly. The energy intensities in Table A-5 can be converted
to (Btu/physical unit) using the 19^7 implied prices of many goods and services.
For a few additional materials, energy costs/physical unit are given by Perry (19'
lU
This example demonstrates hew energy costs can be found quite simply-
using 1-0. However, anyone employing this method should have a good under-
standing of the limitations and uncertainties inherent in it.
2.3.3 Uncertainty Associated with I-Q Analysis
One source of uncertainty which has "been mentioned already is the change
in price levels over time. Due to inflation, price levels change while
physical quantities (and energy cost) may not. Price level changes can "be
approximately corrected using deflators as above, though deflators are some-
times inaccurate and may not strictly conform to BEA sector definitions.
Measuring quantities in terms of constant (1967) dollars is a surrogate for
using physical units. For some products the correspondence between physical
units and 1967 dollars is known. The average 1967 price data in Table A- 6
can be used to express many energy intensities directly in terms of Btu per
physical unit.
Another source of uncertainty is change in the structure of the economy,
the technology of producing goods and services, as represented by the matrix
A. Energy intensities are a function of A. alone, and as technological change
occurs over time, the uncertainty in z_ will increase. Recent studies have
identified the parameters in A which are most important for energy analysis
and work is now underway to update them to reflect the latest technological
advances (Bullard and Sebald, 1975).
Some of the uncertainty in e is due to sector aggregation. Ideally,
each product would be a unique output of a BEA sector, and therefore would
have a unique energy coefficient. Because millions of different goods and
services are produced by the U.S. economy, it would be infeasible to collect
2
data on N technological coefficients at that level of detail. In practice,
15
many similar products or services with a range of energy costs are grouped
in a single sector. The question one wants to ask prior to calculation is:
How much of BEA sector X is devoted to making the target product X ? To answer
this question, it is possible to go back to the original Department of Commerce
data base and examine the composition of each sector. We have done this
and list in Table A-o some common BEA sectors and their major products. To
the extent that the target product 'is typical of the sector's output, the
sector energy intensity is a relatively accurate measure of its energy cost.
This table provides a basis for estimating the certainty in an energy in-
tensity, as applied to a particular product. If the target product were a
very minor output of a large or diverse sector, there is little the user can
do to correct the error using input-output analysis. There is a way to
eliminate this problem, and it will be discussed in section 2.k.
A number of economic and accounting conventions also cause problems.
Since data are collected from firms rather than consumers, they are based
on the firm's value of the product, or producer's price. However, consumers
pay not only this price but also the wholesale and retail margins, transporta-
tion costs, insurance, etc., required to market the product. In the previous
example of the energy cost of the computer, these margins were ignored. Taking
them into account, the calculation proceeds as follows:
The total price (to the purchaser) of the computer is $1,000,000 in 1970.
Of this, the margins can be obtained from Tables A-3 and A-U , and a more
accurate energy cost can be determined as follows:
Sectors listed are those producing major inputs to construction and opera-
tion of facilities for energy production, processing, and transportation.
16
Energy Primary
allocated deflator intensity nersy
% of purchase share of total ($196T/$19T0) Btu/$1967 ° Q
Sector price (Table A-k) cost ($1970) (Table A-2) (Table A-5) (109 Btu)
65.01-
65.06 0
69.01
5
$50,000
.91
39,636
1.8
69.02
1
10,000
.8U
39,372
.3
51.01
9^
$9^0,000
.99
hi ,116
U3.8
TOTAL
$1,000,000
^5.9
Table 2. Energy Cost of a Computer.
This result compares to U6.6U x 10' Btu in the previous example where the
margins were not explicitly accounted for. The favorable comparison is
fortuitous in this example because the energy intensity of computers happens
to be approximately equal to that of trade. For a more energy-intensive com-
modity (e.g. steel), the impact of including margins explicitly could be quite
significant.
Another economic convention is that purchases of capital goods are counted
as net outputs of the economic system, rather than as inputs to production pro-
cesses. This means that ordinary 1-0 energy intensities ( Bullard and Herendeen,
197*0 do not include the energy required to build the factories or machines
used be each sector. A correction has been performed using capital require-
ments data from Fisher (1971), so the energy intensities presented in Table
This correction is described by Putnam, et al. (1975). Since capital data
were only available at the 90-seetor level of detail, it was assumed that in-
dividual processes within those categories are equally capital-intensive.
17
A-5 include the energy required to make capital equipment.
Finally, there is uncertainty in the results due to errors in collecting
and processing the basic data on the technology of producing goods and services.
These errors include those due to, more specifically, incomplete census cover-
age, reporting errors due to misunderstanding, false reports, sampling errors
inherent in surveys of firms, transcription or key punching errors, the pos-
sibility that forms are lost, classification errors, and the problems of
separating, companies from establisliments in processing returns from surveys or
census (Bullard, 1976). Considerable effort has been expended in trying to
estimate these stochastic errors, and their effect on the resulting energy in-
tensities (see Bibliography). Briefly, results indicate that the energy in-
tensities are approximately normally distributed with more than a 99 % likeli-
hood that the actual value falls within the error bounds shown in Table A-T- It
is assumed that these values, computed at the aggregated 90-sector level, can be
applied directly to the 357-sector intensities. However, these figures do not
include uncertainty due to changes in the technology of producing goods and ser-
vices since 1967. Where significant process changes have been made, the error
bounds should be increased.
Table 3
Limit at ions of Imout-Output Analysis
Problem
Treatment
Use Tables A-2 and A-6
1. Price level changes
2. Technology changes (since base year) Updated energy intense
not yet available
3. Aggregation: Typical and atypical products Vse Table A-6 ^
U. Producer's vs. purchaser's prices
5. Including energy cost of capital
6. Uncertainty in base year data
7. Physical flows assumed proportional to dollar values Use a more disaggregate.
model
8. Errors due to secondary products and linearity as- None
sumptions
13
Use Table A-5
Use Table A- 7
Table 3 summarizes the error treatment in energy input-output analysis
and points to two errors that are urire solvable using this technique.
The last two items in Table 3 result from the fact that the U.S. input-
output tables are aggregated to such a level that it is not possible to ex-
press each sector's output in terms of a single physical unit, and the data
are collected on establishments not directly on processes. Methods for
eliminating these problems are discussed by Bullard and Herendeen (1975).
2.k Combining Process and Input -Our, -put Analyses
As shown above, the energy cost of any good and service can be deter-
mined by either process analysis or input-output analysis. In theory, both
methods require identical input data and provide identical results.
For most applications, however, the complete set of input-output data
(the N x N matrix A) are not available at the necessary level of detail. It
exists only at a more aggregated level of about 368 sectors for the United
States economic system, and is much smaller for most other nations.
Because of this lack of data, input-output results give only the average
energy intensity of a sector's output. Accuracy is limited by the level of
aggregation: the energy intensity of aluminum castings would apply to both
pressure cookers and aluminum tools because both are included in sector 38.11.
Process analysis does provide a framework for determining the energy intensity
of atypical products within a sector. The chain of inputs can be traced back
to the point where all inputs are sufficiently "typical" or until the inputs
are so small that the aggregation error is tolerable.
The errors associated with truncating a process analysis can be minimized
using the results of input-output analysis. The truncation error is replaced
by a smaller aggregation error associated with energy-costing the higher indirect
order inputs. The combination of these techniques is called "hybrid analysis" and
19
the procedures are described below.
Theoretically, each step in a process analysis may "be viewed as an ex-
pansion of the system boundary (arcund the item being analyzed) into the
economic system, tabulating direct energy inputs at each step (see fig. k) .
The results of input-output analysis may be used to estimate the energy em-
bodied in flows crossing the system boundary at any level, by associating each
good or service with one of the 368 sectors of the 1-0 model. These 1-0 results
are indifferent to the location of the system boundary. Regardless of the
number of process analysis steps taken s the boundary looks the same from the
1-0 side. Thus in theory, it does not matter at which stage of the process
analysis you correct for the truncation error. In practice, by carefully
choosing the number of stages, hybrid analysis can reduce the error in both
techniques and produce the most accurate result possible. The truncation er-
ror is eliminated from the process analysis and the aggregation error is mini-
mized in the 1-0 analysis.
2.^.1 Procedure
To perform a hybrid analysis, begin by doing the first one or two steps
in a process analysis. Select the target product and carefully determine the
energy and materials required for its production. Some of the input materials
may be typical products of 1-0 sectors; 1-0 can be used to determine their tots
energy costs with only a single additional calculation. Thus the only input
materials requiring further process analysis are atypical products not easily
classified in an 1-0 sector. The technology for producing these items must be
*
Obviously, if the target product is "typical" of an 1-0 sector's output, no
hybrid analysis is needed.
20
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21
examined to identify their inputs which must in turn be energy-costed with
either 1-0 or further process analysis, depending on whether they are typical
or not. Hybrid analysis is best suited for large atypical problems such as
determining the energy cost of a power plant, since there is no 1-0 sector
corresponding to power plant construction.
2.U.2 Example
We will now calculate the energy cost of a large prototype coal-fired
power plant (Pilati and Richard, 1975). Assume that information on this
plant is available from either a line-item plant budget or an expert consult-
ant on the project. Our objective is to calculate this energy cost in the
easiest manner within an uncertainty of ±10$. A sequence of approximations
will be used, starting with the simplest assumptions. The sequence can be
terminated as soon as the error tolerance is less than 10$.
As a first approximation, we could multiply the dollar cost of the power
plant ($88 million at 1970 prices, ±15%) by the average intensity for all
goods and services in 1970 (68,690 Btu/$) . This coefficient is simply the
ratio of total U.S. energy use to gross national produce in 1970. When used
to approximate the energy intensity of a particular item such as a power plant,
this coefficient has an extremely large uncertainty (say a factor of two:
+100$, -50$). The total energy cost and error terms are given by the formula:
(a ± Aa)(e ± Ae) = ae ± aAe ± eAa ± AeAa
This is the cost of all purchased inputs to power plant construction —
materials, services, etc. Wages and taxes are excluded to be compatible
with the system boundary of the 1-0 model which corresponds to GNP (See
Bullard, (1976)). Using this convention, energy to produce items bought with
wages are charged to the wage earner, not the employer.
If the energy/GNP ratio for the appropriate year were not known, construction
costs could be deflated to the year for which it is known . A construction cost
index is given in Table A-2.
where a is the budget figure and e the energy intensity, and Aa and Ae
represent the uncertainties. Values for Aa and Ae are obtained by simply
multiplying a and e by their respective percentage errors. This first
12
approximation yields an energy cost of 6.0U x 10 Btu, while the first-order
errors are clearly far outside the desired tolerance interval:
+ (eAa) + (aAe) = +6.9 x 1012Btu (+llW
- (eAa) - (aAe) = 3.9 x 1012Btu (-655?)
For some applications, however, errors such as these may be acceptable, and
the analysis could terminate here.
The second approximation begins by identifying the major single expenses
in the budget. Assume that an expert consultant provided a list of such pur-
chases shown in column I of Table k. Care must be taken to identify each
expense with its appropriate BEA sector, as defined in the S.I.C. Manual
(U.S. Department of Commerce (197*0).
The energy cost calculation for these purchases , including removal of
transportation and trade margins and price deflation, is shown in columns II
thru VII of Table U. Energy used directly (on-site for construction) should be
included in every energy cost calculation, because it may be significant even
if it is not a large dollar expense . The energy embodied in the remaining
(miscellaneous) inputs to the plant is estimated using the energy/GNP ratio as
an average energy intensity as was done in the first approximation.
Column VIII contains the error due to budget uncertainty (eAa), which is
assumed in this example to be 15% for all items. Column IX reflects the un-
certainty in the energy intensity (aAe). The magnitude of the uncertainty in
For convenience, a 90-sector level of aggregation is used in this example.
Generally, more accuracy (less aggregation error) can be achieved with the
368-sector level of detail. Tables in the Appendix are 368-order, so the
numbers in the example will differ slightly from the figures in those tables.
23
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e is based on Table A-7.* An examination of Table A-6 can indicate whether
an input is typical of a particular sector's output. Assume that, based on
careful classification and data from the consultant, all inputs except cons-ruc-
tion machinery (1*5.00), are believed to be typical sector outputs. Typical
inputs can use the figure from Table A-7 for their As terms. To account for
the atypical construction machinery, an additional 20^ is added to the con-
struction machinery uncertainty from Table A-7.
The result of calculating the second approximation is a total energy
1 ? an
cost of 6.78 x 10 Btu with error bounds of +53$, -30/S. This is an improve-
ment but it still does not fall within our desired ±10$ limits.
In the next approximation fewer inputs are classified as miscellaneous
in order to further reduce the error. Assume that we instructed the consult-
ant to write down every significant budgeted expense classified in BEA sectors
36.00, 38.00, 1*0.00, 1*2.00, 1*3.00, 1*5.00, 1*6.00, 1+9.00, 53.00, 62.00, and 75.00.
These sectors were chosen because they contain most of the materials commonly
used for power plant construction; the amounts appear in column I of Table 5.
As in Table 1*, computing the energy cost of these purchases is straightforward
and the remaining expenses are costed with the average energy/GNP ratio as
before. The error analysis proceeds as in the previous step, and this time the
12
error is +15, -13$ for an energy cost of 7.19 x 10 Btu. This still does net
meet our accuracy requirements so the analysis must proceed another step.
From Table 5 it appears that two of the largest errors are due to budget
uncertainties for sectors 1*3.00 and 1+0.00. Assume that we have no way of
*These uncertainties apply to the energy intensity of goods in 1967. If we assume
the power plant will be built in 1980, the total energy cost will be higher or lower,
defending on trends in energy-related technological change throughout the US economy
during the 1967-80 period. This correction may be applied after the final result is
obtained, and may be approximated by anticipated changes in the aggregate energy/
GNP ratio.
**
Note that for each input, the first order budget and energy coefficient er-
rors are tabulated. We assume errors on each input item are independent,
and therefore the total error in any approximation is the square root of the
sum of the squares of each input error.
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improving the 15% accuracy of the expenses in sector 1+3.00, hut note that the
"budget figure in sector Uo.00 has an unusually large (±30$) error. Assume that,
with a small effort, the consultant could improve the error term on structural
steel expenses to ±15%- This reduces the eAa error in that sector and reduces
the error hound for the entire power plant to +8, -1%. This is within our er-
ror specification and the analysis can now he terminated.
To give an idea of how much effort was saved hy these approximations , a
complete computation from a line-item "budget for the plant is shown in Tahle
6. Column I lists all inputs deflated to 19^7 dollars with margins already
computed and assigned to the appropriate margin sectors. This is 'why, for
example, sector 65.01 (rail transport) shows an expense of $883,15^ even though
the plant hudget may not actually show any money allocated to direct purchases o:
rail transport- This complete 1-0 analysis eliminated the large errors due to
use of the average energy/GNP ratio as an energy intensity. It can he seen
that accuracy has been slightly improved hy this method; total energy cost is
7.36 x 1012Btu ±1%.
If a greater degree of accuracy were desired, it would not have heen nec-
essary to perform the arduous task of itemizing all inputs, especially the
smallest ones. The effort might have been "better spent reducing the budget
uncertainty on some of the inputs contributing the largest errors. For example,
reviewing design details to reduce the budget uncertainty on inputs from sectors
U0.00 and 1+3.00 to ±5$ could have improved the estimate in Tahle 5 to +5%, -3%.
If, in this example, there were significant inputs not typical of their
sector, similar reductions in the Ae errors may have been achieved by perform-
ing a one-or two-step process analysis on several of trem.
In closing, we return to the question of the unqusntified uncertainty due
to the fact that the technologies for producing goods end services changed
27
Table 6
Sample Hybrid Analysis
I
II
III
IV
V
energy
budget
intensity
BEA
Expenses
energy
intensity
energy
(10 Btu)
uncertainty
(10 BtuHeAa)
uncertainty
(aAe).(l0 Btu)
Sector
($1967)
(Btu/$)
3101
5.77 X loi1 3TU
7.2U X 10° BTO
1.2194
7C3609
105541
21108
6801
4.0643
29
4
1
6802
9,68 X 10° R1U
1. 1157
1080
162
43
200
65C4
77672
505
76
66
400
5155
42482
219
33
22
900
16100
117771
1896
284
265
120C
1880
60140
113
17
9
1600
1736
112644
196
29
6
1700
6730
109024
734
110
29
1800
186
61440
11
2
1
1900
100
81326
8
1
0
2000
766938
73312
56226
8434
3374
2200
613
596 29
37
5
1
2300
34239
67760
2320
348
70
240C
24H4
1689^14
4075
611
122
2600
242
57880
14
2
0
2700
34507
26 3170
9081
136 2
363
300*
6 38 23
125326
10505
1576
420
3102
11974
576357
6901
1035
897
3103
24445
492584
12041
1806
1686
3200
1571C9.
1C0306
15759
2364
473
3500
27726
130543
3619
543
181
360 0
1342855
.177176
237922
35688
7133
370 C
549914
233593
128456
19268
3 854
3800
1316802
158599
2C8856
31323
6 266
aooo
28279568
10c593
2985851
447879
89576
4100
4108
98244
404
61
12
4200
188C925
95036
178755
26313
7150
4300
15018830
81113
1218227
182734
36547
4500
3042544
82534
251114
60267
7533
U600
1224037
69959
85633
12345
2569
4900
2961657
72460
214602
32190
4292
5000
3299
60872
201
30
8
5200
642963
75211
48358
7254
1934
5300
3648279
65406
238618
35793
7159
5400
12697
79750
1013
152
30
5500
117535
70393
8274
124 1
248
5600
5386
41520
224
34
7
5800
3894
73531
286
43
11
5900
23
78052
2
0
0
6200
1248479
54c45
68099
10215
2724
6U00
11115
63973
711
107
14
6501
883154
98184
86712
13007
4336
6503
704982
54654
38530
5779
2 697
650U
15083
256200
3864
580
309
6505
67575
205114
13861
2079
1386
6506
96
1429^0
14
2
2
6600
28105
54723
1528
231
215
6803
1215
1186 1 9
144
22
14
6900
6087317
45825
278949
41842
27895
7000
40731
28037
1142
171
80
7100
47448
17596
835
125
50
7 300
3710C8
37056
13748
2062
825
7 50 0
2785132
74526
207564
31135
22832
7700
6367
54757
349
52
42
7800
241U •
40514
98
15
11
79C0
2000
111926
224
34
31
8100
44362
105911
4698
7C5
658
8200
239U
82546
198
30
20
TOTAL
$73,608,500
7357052
518,8
56 (±7*)
# Budget uncertainty ±13% on all items.
* All inputs assumed typical except U'5.00 (±2U#)
between 1967 (the model "base year) and the time construction of the power plant in
1980. This will have the effect of increasing As for all goods and. services .
Rather than speculating on each production technology individually, it may be
easiest to lump the uncertainty in a single factor that attempts to average
these effects for all goods and services. The energy/GIIP ratio may be used for
this purpose since it is essentially a weighted average of the energy intensities
of all production technologies. The ratio has been relatively stable, changing
by no more than ±5% for about 20 years , so its impact has been negligible in
the past. Anticipating a downward trend in response to post-embargo energy
prices, one might wish to adjust the As values accordingly. For our purposes
we have neglected this effect; for longer range application, it must be con-
sidered explicitly.
3.0 DISCUSSION
The preceeding example outlined the basic steps that must be taken to
calculate the energy cost of any item. In the trivial case where the item is
a typical output of a sector of the economy, its energy cost can be read di-
rectly from Table A-5. The example considered an atypical item, an electric
power plant, and showed how to perform a one- stage process analysis to obtain
a ±10% estimate of its energy intensity.
The foregoing example was structured to highlight the payoffs obtained
by focusing attention on a few primary inputs — the most significant element
in the first stage of the process analysis. It was seen t iat it is not always
necessary to obtain a detailed breakdown of exact quantities of all input mater-
ials in order to obtain a reasonable accurate final result. This technique yields
considerable cost savings over conventions! analyses (e.g. Just, 1975) that
?9
rely on a compilation of accurate and detailed lists of input materials and
services.
In the interest of simplicity, the example did not include any two-stage
process analyses, because the method is identical to that shown for the
first-order step. In practice, the presence of large atypical inputs (e.g.
the pressure vessel for a nuclear plant) may result in some of the largest
uncertainties "being associated with the Ae terms; it may prove more fruitful
to perform crude process analyses on these inputs than to seek more accurate
data on input quantities.
The methods developed here can be applied to calculating the energy cost
of any good or service within a specified degree of accuracy. This report was
written to support energy analyses of energy supply and conservation systems
in particular, but applications are not restricted to that area. Detailed
guidelines for using this method for net energy analysis are presented by
Perry (1977).
30
References
Batt ell e/ Columbus Labs, "Energy Use Patterns in Metallurgical and Nonmetallic
Mineral Processing," U.S. Bureau of Mines, 1975.
Bullard, Clark, "Energy Costs, Benefits, and Net Energy," Energy Systems and
Policy, Vol. 1, No. U, pp. 367-381, 1976.
Bullard, Clark and Robert A. Herendeen, "Energy Impact of Consumption Decisions,"
Proceedings of the IEEE, Vol. 63, No. 3, pp. U8U-1+93, March 1975, CAC Document
135, Center for Advanced Computation, University of Illinois, Urbana, 6l801,
October 19lk.
Bullard, Clark and Anthony V. Sebald, "Effects of Parametric Uncertainty and
Technological Change," CAC Document 156, Center for Advanced Computation,
University of Illinois, Urbana, 6l801, March 1975. Also in Review of Economics
and Statistics (forthcoming) .
Fisher, W. H. and C. H. Chilton, An Ex Ante Capital Matrix for the United
States, 1970-75, Battelle Memorial Institute, 1971.
Hannon, Bruce, "System Energy and Recycling: A Study of the Beverage Industry,"
CAC Document 23, Center for Advanced Computation, University of Illinois, Urbana,
61801, March 1973.
Herendeen, Robert and Clark Bullard, "Energy Cost of Goods and Services, 1963
and 1967," CAC Document lUo,. Center for Advanced Computation, University of
Illinois, Urbana, 6l801 , November 197^; Energy Policy, December 1975.
Herendeen, Robert and Jerry Tanaka, "Energy Cost of Living," CAC Document 171,
Center for Advanced Commutation, University of Illinois, Urbana, 6l801, April
1975.
Leontief, Wassily, The Structure of American Economy, 1919-1939, Oxford
University Press, 1941.
Perry, A. M. , "Guidelines for Net Energy Analysis," Oak Ridge Associated Univer-
sities, Institute for Energy Analysis, Oak Ridge, TN , 1977.
Pilati, David A., "Energy Analysis of Electricity Supply and Energy Conserva-
tion Options," Energy, Vol. 2, No. 1, pi3. 1-7. 1977.
Pilati, David A. and Ralph Richard, "Total Energy Requirements for Nine Elec-
tricity - Generating Systems, " CAC Document 165 , Center for Advanced Computa-
tion, Universitv of Illinois, Urbana, 6l801, August 1975. Also in Energy
Vol. 2 No. 1, pp. 1-7, 1977.
Putnam, Dan, Ralph Richard, and Clark Bullard, "Energy Labor and Capital Updates
to the Energy Employment Model," CAC Technical Memo. 36, Center for Advanced
Computation, University of Illinois, Urbana, 6l801, January 1975.
31
Rotty, R. M. et al. , "Net Energy From Nuclear Power," Report No. IEA-75-3,
Institute for Energy Analysis, Oak Ridge, TN, 1975-
Teasley, Larry, N. , "Energy Implication of Polymer Production and Use," Wash-
ington University, St. Louis, 197^.
U.S. Department of Commerce, Standard Industrial Classification Manual, 1971,
Washington: Government Printing Office, 197**.
32
APPENDIX A
Tables for Computing Indirect
Energy Requirements
33
Table A-l
Industry Classification of the 1967 Input-Output Tables
The titles in bold face represent the proupinps of industries
used for the summary version of the 1967 tables and
were also used in the 1958 and 1963 input-output
tables prepared by the Bureau of Economic Analysis.
Industry number and title
Related Census-
SIC codes (19<i7
edition)
AGRICULTURE, FORESTRY. AND FISHERIES!
1.01
1.02
1.03
2.01
2.02
2.03
2.04
2.05
2.06
2.07
3.00
4.00
1 Livestock and livestock products
Dairy farm products
Poultry and eggs
Meat animals and miscellaneous
livestock products.
2 Other agricultural products
Cotton
Food feed grains and grass seeds
Tobacco
Fruits and tree nuts
Vegetables, sugar, and miscellaneous
crops.
Oil bearing crops
Forest, greenhouse, and nursery
products.
3 Forestry and fishery products
Forestry and fishery products
4 Agricultural, forestry, and fishery
services
Agricultural, forestry, and fishery
services.
MINING
3.00
6.01
6.02
7.00
8.00
9.00
10.00
5 Iron and ferroalloy ores mining
Iron and ferroalloy ores, mining
6 Nonferrous metal ores mining
Copper ore mining
Nonferrous metal ores mining, ex-
cept copper.
7 Coal mining
Coal mining
0132, pt. 014.
0133,0134, pt.
014.
013.">, 0136, 013"),
pt. 014, 0193,
pt. 0729.
0112, pt. 014.
0113, pt. 0119,
pt. 014.
pt. 0114, pt. 014.
0122, pt. 014.
0123, pt. 0119,
pt. 014.
pt. 0113, pt.
0119, pt. 014.
0192, pt. 014.
074.081.082,084,
086,091.
071,0723.073.
pt. 0729, 085,
098.
8 Crude petroleum and natural gas
Crude petroleum and natural ga.>.
9 Stone and clay mining and quarrying
Mono and clay mining and
quarrying.
10 Chemicals and fertilizer mineral mining!
Chemical and fertilizer mineral I
mining.
CONSTRUCTION
11.01
II New construction
New construction, residential build-
ings (nonfarm).
11.02
11.03
11.04
1 1. 0.*>
12.01
pt. 13, pt. 16,
pt. it, pt.
6361.
pt. 13, pt. 17.
pt. 15, pt. 10,
pt, 17.
pt. Id, pt. 17.
pt. 15, pt. 16, pt.
17, pt. 13S.
12 Maintenance and repair construction
Maintenance ami repair construe- pt. 13, pt. 17.
tion, residential buildings (nun- |
farm). I
New construction, nonrc-.deutial
building-.
New con.-truction, public utilities..
New construct ion, highways. . . .
New construction, all other.
1011. 106.
102.
103, 104, 105,
108, 109.
11. 12.
1311, 1321.
141, 142. 144, 145,
148, 149.
147.
Industry number and title
Related Ccnsus-
SIC codes (1967
edition)
15 01
15 02
I 1601
I
1 16
02
16.
0.3
16
04
17.
01
17
02
17
OS
17
04
17
05
1 I?
06
17.
07
i! 17.
OS
1 17
0<>
i 17
10
18.
01
18
02
IN
03
il IS.
04
12. 02 Maintenance and repair construc-
tion, all other.
MANUFACTURING
13 Ordnance and accessories
13.01 Complete guided missiles
13. 02 Ammunition, except for small arms,
n.e.c.
13. 03 Tanks and tank components.
13. 04 Sighting and fire control equipment..
13. 05 Small arms
13 00 Small arms ammunition
13. 07 Other ordnance arid accessories
14 Food and kindred products
14. 01 .Meat products
14.02 Creamery hutter
14 03 Cheese, natural and processed j
14. 04 Condensed and evaporated milk i
14. 05 Ice cream and frozen desserts j
14 00 Fluid milk
14 07 Canned and cured sea foods |
14. OS Canned specialties |
14 09 Canned fruits and vegetables
14. 10 Dehydrated food products
14. U Pickles, sautes, and salad dressings..
14. 12 Fresh or frozen packaged fish
14. 13 Frozen fruits and vegetables
14. 14 Flour and cereal preparations
14 15 Prepared feeds for animal- and fowls.
14. 16 Rice milling
14.17 Wet corn milling
14 18 Bakery products
14 19 Sugar
14 20 Confectionery an'l related products. .i
14. 21 Alcoholic bcvcrac.es .' i
14.22 Bottled and canned --oft drinks i
14. 23 Flavoring extracts and sirups, n.c.c.i
14.24 Cottonseed oil mill.-,
14. 25 Soybean oil mills
14. 26 Vegetable oil mills, n.e.c
14 27 Animal and marine fat> and oils
14. 28 Roasted coffee |
14. 29 Shortening and cooking oils j
14. 30 Manufactured ic<
14. 31 Macaroni and spaghetti j
14. 32 Food preparations, n.e.c j
15 Tobacco manufactures
Cigarettes, cigar* , etc. j
Tobacco stemming and redrying.. . .]
16 Broad and narrow fabrics, yarn and!
thread mills
Broadwoven fabr.c mills and fabric j
finishing plants.
Narrow fabric mills |
Yarn mills and finishing of textiles, j
n.e.c. j
Thread mills
17 Miscellaneous textile goods and floor j
coverings j
Floor covering*- ;
Felt goods, n.e.c !
Lace good* i
Padding- and uphuHtery fillings.
Processed teitilr waste ;
Coated fabrics, n>>t rubberized
Tire cord and fabric
Scouring and combing plants
Cordage and twn e : .
Textile good-, n.e.c
18 Apparel
Hosiery
Knit apparel nulU
Knit fabric mills
Apparel made from purchased
materials.
19 Miscellaneous fabricated textile
products.
19 01 Curtains and draperies
pt. 15, pt. 16.
pt. 17, pt. 138.
1923.
1929.
1931.
1941.
1951.
1961.
1911, 1999.
201.
2021.
2022.
2023.
2024.
2026.
2031.
2032.
2033.
2034.
2035.
2030.
2037.
2041.2043,2045.
2042.
2044.
2046.
205.
206.
207.
2082-5.
20S6.
20S7.
2091.
2092.
2093.
2094.
2095.
2096.
2097.
2098.
2099.
2111.2121.2131.
2141.
2211.2221. 2231.
2261, 2262.
224 1 .
2209,2281-3.
2284.
227.
2291.
2292
2203.
2294.
2295.
2296.
2297.
229S.
2299.
2251. 2252.
2253, 2254. 2259.
2256.
23 (cxd.
239), 39996.
2391.
3U
Table A-l (continued)
Industry Classification of the 1967 Input-Output Tables — Continued
19.02
19.03
20.01
20.02
20.03
20.04
20.05
20.06
20.07
20.08
20.09
21.00
22.
01
22.
02
22.
03
22.
04
23.
01
23.
02
23.
03
23.
04
23.
0.5
23.
00
23.07
24
01
24
02
24
03
24
04
24.
05
24.
06
Industry number and title
Related Ccnsus-
SIC codes (1967
edition)
Housefurnishings, n.e.c
Fabricated textile products, n.e.c.
20 Lumber and wood products, except
containers
Logging camps and logging contrac-
tors.
Sawmills and planing mills, general.
Hardwood dimensions and flooring.
Special product sawmills, n.e.c
Millwork
Veneer and plywood
Prefabricated wood structures
Wood preserving
Wood products, n.e.c
21 Wooden containers
Wooden containers.
22 Household furniture
Wood household furniture
Upholstered household furniture...
Metal household furniture
Mattresses and bedsprings
2392.
2393-9.
2411.
2421.
2426.
2429.
2431.
2432.
2433.
2491.
2499.
23 Other furniture and fixtures
Wood office furniture
Metal office furniture
Public building furniture
Wood partitions and fixtures.
Metal partitions and fixtures.
Venetian blinds and shades. .
Furniture and fixtures, n.e.c.
24.07
25.00
26.01
26.02
26.03
26.04
26.05
26.06
26.07
26.08
27.01
'27. 02
27.03
27.04
28.01
28.02
28. 03
28.04
29.01
29.02
29.03
30 00
24 Paper and allied products except con-
tainers and boxes
Pulp mills
Paper mills, except building paper.
Paperboard mills
Envelopes
Sanitary paper products
Wallpaper and building paper and
board mills.
Converted paper, products, n.e.c,
except containers and boxes.
25 Paperboard containers and boxes
Paperboard containers and boxes..
244.
2511,2519.
2512.
2514.
2515.
2521.
2522.
2.531.
2541.
2542.
2591.
2599.
2611.
2621.
2631.
2642.
2647.
2644, 2661.
2641,2643,264 5,
2646, 2649.
265.
26 Printing and publishing
Newspapers 2711.
Periodicals 2721.
Book printing and publishing 273.
Miscellaneous publishing 274 1 .
Commercial printing i 2751, 2752.
Manifold business forms, blank-i 2761, 2782.
books, and binders.
Greeting card publishing 2771.
Miscellaneous printing services 27.53, 2789, 279.
27 Chemicals and selected chemical prod-!
ucts
Industrial inorganic and organic
chemicals,
Fertilizers
Agricultural chemicals, n.e.c
Miscellaneous chemical products
28 Plastics and synthetic materials
Plastics materials and resins
Synthetic rubber
Cellulosic man-made fibers
Organic fibers, noncellulosic
29 Drugs, cleaning and toilet preparations
Drugs
Cleaning preparations
Toilet preparations
30 Paints and allied products
Paints and allied products.
281 (excl. 2819.5.)
2871,2872.
2879.
2861, 289.
2821.
2822.
2823.
2824.
283.
284 (excl. 2844.
2844.
2851.
31.01
31. 02
31.03
32.01
32. 02
32. 03
32.04
33.00
34.01
34. 02
34.03
35.01
35.02
36.01
36. 02
36.03
36.04
36.05
36.06
36.07
36. 08
36.09
36. 10
36. 11
36. 12
36. 13
36.
3-V
3o.
36.
36. 18
36. 19
36.20
36. 21
36.22
37.01
37.02
37. 03
37.04
38.01
3S. 02
38.03
38. 04
3.8. 0.5
3S. 06
38. 07
38. 08
38. 09
38. 10
38. 11
38. 12
3K. 13
38. 14
39.01
30.02
40.01
40.02
Industry number and title
Related Ceosus-
SIC codes (1967
edition)
31 Petroleum refining and related indus-
tries
Petroleum refining and related
products.
Paving mixtures and blocks .
Asphalt felts and coatings...
32 Rubber and miscellaneous plastics
products
Tires and inner tubes
Rubber footwear
Reclaimed rubb'-r and miscellaneous
rubber products, n.e.c.
Miscellaneous plastics products
33 Leather tanning and industrial leather
products
Leather tanning and industrial
leather products.
34 Footwear and other leather products
Footwear cut stock
Footwear except rubber
Other leather products
35 Glass and glass products
Glass and glass products except con-
tainers.
Glass containers
36 Stone and clay products
Cement, hydraulic
Brick and structural clay tile
Ceramic wall and floor tile
Clay refractories
Structural clay products, n.e.c
Vitreous plumbing fixtures
Food utensils pottery
Porcelain electrical supplies
Pottery products n.e.c
Concrete block and brick
Concrete products, n.e.c
Ready-mixed concrete
Lime
Gypsum producs
Cut stone and stone products
Abrasive products
Asbestos products.
Gaskets and insulatious
Minerals, ground or treated
Mineral wool
Nonclay ref ractories
Nonmetallie mineral products, n.e.c.
37 Primary iron and steel manufacturing
Blast furnaces and ba-sic steel prod-
ucts.
Iron and steel foundries
Iron and steel fc rgings
Primary metal products, n.e.c
38 Primary nonferrous metals manufac-
turing
Primary copper
Primary lead
Primary zinc
Primary aluminum
Primary nonferrous metals, n.e.c
Secondary nonferrous metals
Copper rolling and drawing
Aluminum rolling and drawing
Nonferrous rolling and drawing,
n.e.c.
Nonferrous wire drawing and insu-
lating.
Aluminum castings
Bra>s, bronze, and copper castings..
Nonferrous castings, n.e.c
Nonferrous forgings
39 Metal containers
Metal cans
Metal barrels, drums, and pails.
40 Heating, plumbing, and fabricated
structural metal products
Metal sanitary ware
Plumbing fitting} and brass goods...
2911,299.
2951.
2952.
3011.
3021.
3031,3069.
3079.
3111,3121.
3131.
314.
3151,3161,317.
3199.
3211,3229,3231.
3221.
3241.
3251.
3253.
32.55.
3259.
3261.
3262. 3263.
3264.
3269.
3271.
3272.
3273.
3274.
3275.
3281.
3291.
3292.
3293.
3295.
3296.
3297.
3299.
331.
332.
3391.
3399.
3331.
3332.
3333.
3334.28195.
3339.
3341.
33.51.
3352.
3356.
3357.
3361.
3362.
3369.
3392.
3411.
3491.
3431.
3432.
35
Table A-l (continued)
Industry Classification of the 1967 Input-Output Tables — Continued
Industry number and title
40. 03 Heating equipment, except electric.
40. 04 Fabricated structural steel
40.05 Metal doors sash and trim
40. 06 Fabricated plate work (boiler shops) .
40.07 Sheet metal work
40. 08 Architectural metal work
40. 09 Miscellaneous metal work
41 Screw machine products, bolts, nuts,
etc. and metal stampings
41. 01 Screw machine products and bolts,
nuts, rivets, and washers.
41. 02 Metal stampings
42 Other fabricated metal products
4Z01 Cutlery
42. 02 Hand and edge tools including saws'.
42. 03 Hardware, n.e.c. -•
42. 04 Coating, engraving, and allied serv-
ices.
42. 05 Miscellaneous fabricated wire prod-
ucts.
42. 06 Safes and vaults :
42. 07 Steel springs
4Z 08 Pipe, valves, and pipe fittings
4Z 09 Collapsible tubes
4Z 10 Metal foil and leaf
4Z 11 Fabricated metal products, n.e.c
43 Engines and turbines
43. 01 Steam engines and turbines
43. 02 Internal combustion engines, n.e.c.
44 Farm machiney
44. 00 Farm machinery
45 Construction, mining, oil field ma-
chinery equipment
45. 01 Construction machinery
45. 02 Mining machinery -.
45. 03 Oil field machinery
46 Materials handling machinery and
equipment
46. 01 Elevators and moving stairways
46- 02 Conveyors and conveying equip-
ment.
46. 03 Hoists, cranes, and monorails
46. 04 Industrial trucks and tractors
47 Metalworking machinery and equip-
ment
47. 01 Machine tools, metal cutting types.
47. 02 Machine tools, metal forming types
47. 03 Special dies and tools and machine
tool accessories.
47. 04 Metalworking machinery, n.e.c
48 Special industry machinery and equip-
ment
48.01 Food products machinery
48. 02 Textile machinery
48. 03 Woodworking machinery
48. 04 Paper industries machinery
48. 05 Printing trades machinery
48. 06 Special industry machinery, n.e.c
49 General industrial machinery and
equipment
49. 01 Pumps and compressors
49. 02 Bail and roller bearings
49. C3 Blowers and fans
49. 04 Industrial patterns
49. 05 Power transmission couipment
49. 06 Industrial furnaces and ovens
49. 07 General industrial machinery, n.e.c
50 Machine shop products
50. 00 Machine shop products
51 Office, computing, and accounting ma-
chines
51. 01 Computing and related machines. .
Related Census -
SIC codes (1967
edition)
3433.
3441.
3442.
3443.
3444.
3446.
3449.
345.
3461.
3421.
3423, 3425.
3429.
3471, 3479.
3481.
3492.
3493.
3494, 3498.
3496.
3497.
3499.
3511.
3519.
3522.
3531.
3532.
3533.
3534.
3535.
3536.
3537.
3541.
3542.
3544^ 3545.
3548.
3551.
3552.
3553.
3554.
3555.
3559.
3561.
3562.
3564.
3565.
3566.
3.->67.
3569.
359.
3573, 3574.
51. 02
51.03
51. 04
52.01
52.02
52.03
52.04
52.05
53.01
53.02
53.03
53.04
53. 05
53. 06
53.07
53.08
54. 01
54. 02
54. 03
54.04
54.05
54. 06
54.07
55. 01
55 02
55. 03
56 01
56.02
56. 03
56.04
57.01
57 02
57.03
01
02
03
01
05
59.01
59 02
59. 03
60 01
60 02
60 03
60 04
61.01
61 02
61 03
61 04
61.05
61 06
61 07
62 01
Industry number and title
Related Census-
SIC codes (1967
edition)
Typewriters
Scales and balances..
Office machines, n.e.c.
52 Service industry machines
Automatic merchandising machines. 3581.
Commercial laundry equipment 3582.
Refrigeration machinery 3585.
Measuring and dispensing pumps i 3586
Service industry machines, n.e.c 3589
3572.
3576.
3579.
53 Electric transmission and distribution
equipment and electrical industrial
apparatus
Electric measuring instruments
Transformers
Switchgear and switchboard appa-
ratus.
Motors and generators
Industrial controls
Welding apparatus
Carbon and graphite products
Electrical industrial apparatus, n^e.c.
3611.
3612.
3613.
3621.
3622.
3623.
3624.
3629.
54 Household appliances
Household cooking equipment 3631.
Household refrigerators and freezers.! 3632.
Household laundry equipment i 3633.
Electric housewares and fans.
Household vacuum cleaners.
Sewing machines
Household appliances, n.e.c.
55 Electric lighting and wiring equipment
Electric lamps . ....
Lighting fixtures
Wiring devices
56 Radio, television and communication
equipment
Radio and television receiving sets..
. Phonograph records
Telephone and telegraph apparatus.
Radio and television communication
equipment.
57 Electronic components and accessories
Electron tubes
Semiconductors
Electronic components, n.e.c.
58 Miscellaneous electrical machinery,
equipment and supplies
Storage batteries
Primary batteries, wet and dry
X-ray apparatus and tubes
Engine electrical equipment
Electrical equipment, n.e.c
59 Motor vehicles and equipment
Truck and bus bi .dies
Truck trailers
Motor vehicles and parts
60 Aircraft and parts
Aircraft
Aircraft engines and parts. . .
Aircraft propellers and parts.
Aircraft equipment, n.e.c. . -
61 Other transportation equipment
Shipbuilding and repairing
Boatbuilding and repairing
Locomotives and parts
Railroad and street cars
Motorcycles, bicycles and parts
Trailer coaches
Transportation equipment, n.e.c...
62 Professional, s, ientific and controlling
instruments, and supplies
Engineering .rid scientific instru-
ments.
3634.
3635.
3636.
3639.
3641.
3642.
3643, 3644.
3651.
3652.
3661.
3662.
3671, 3672, 3673.
3674.
3679.
3691.
3692.
3693.
3694.
3699.
3713.
3715.
3711, 3714.
3721.
3722
37295.
3729 (excl. 37295).
3731.
3732.
3741.
3742.
3751.
3791.
3799.
3811
36
Table A-l (continued)
Industry Classification of the 1967 Input-Output Tables-Continued
Industry number and title
Related Census -
SIC codes (1%7
edition)
62.02
62.03
62.04
62.05
62.06
62.07
63.01
63.02
63.03
•Mechanical measuring devices
Automatic temperature controls..
Surgical and medical instruments.
Surgical appliances and supplies..
Dental equipment and supplies...
Watches, clocks and parts
64.01
64.02
64.03
64.04
6405
64.06
64.07
64.08
64.09
64. 10
64. 11
64. 12
63 Optical, ophthalmic and photographic
equipment and supplies
Optical instruments and lenses
Opththalmic goods
Photographic equipment and sup-
plies.
64 Miscellaneous manufacturing
Jewelry, including costume, and
silverware.
Musical instruments and parts
Games, toys, etc
Sporting and athletic goods, n.e.c."'
Pens, pencils, etc
Artificial flowers
Buttons, needles, pins and fasteners.
Brooms and brushes ■
Hard surface floor covering
Morticians goods
Signs and advertising displays
Miscellaneous manufactures, n.e.c...
TRANSPORTATION. COMMUNICATION.
ELECTRIC. GAS, AND SANITARY SERVICES
65 Transportation and warehousing
65. 01 Railroads And related services
65.02 Local, suburban and interurban
highway passenger transporta-
tion.
65. 03 Motor freight transportation and
warehousing.
65. 04 Water transportation
65. 05 Air transportation * ~ "
65. 06 Pipe line transportation
65. 07 Transportation services
66 Communications, except radio and
television broadcasting
66. 00 Communications, except radio and
television.
67 Radio and television broadcasting
67. 00 Radio and television broadcasting..
68 Electric, gas. water and sanitary
services
68. 01 Electric utilities
68. 02 Gas utilities
68. 03 Water and sanitary services.. * ...
WHOLESALE AND RETAIL TRADE
69.01
Retail trade.
69 Wholesale and retail trade
Wholesale trade
69.02
FINANCE. INSURANCE AND REAL ESTATE
»„ - 70 Finance and insurance
70.01 Banking
70. 02 Credit agencies
In £? Security and commodity brokers"
7U. 04 Insurance curriers... ...
70. 05 Insurance agents and brokers .". * '.
71 Real estate and rental
!!- 9i Owner-occupied dwellings..
71.02 Real estate
3821.
3822.
3841.
3842.
3843.
387.
3831.
3851.
3861.
391, 3961.
3931.
3941, 3942, 3943.
3949.
395.
3962.
3963, 3964.
3991.
3996.
3994.
3993.
3999 (excl. 39990).
40, 474.
41.
42, 473.
44.
45.
46.
47, (excl. 473,
474.).
48, (excl. 483).
483.
491, pt. 493.
492, pt. 493.
494, 495, 496,
497, pt. 493.
50 (excl. manu-
facturers' sales
offices).
52, 53, 54, 55, 56,
57, 58, 59,
7396, pt. 8099.
60.
61, 67.
62.
63.
64.
65 (excl. pt.
6561), 66.
Industry number and title
Related Census-
SIC codes (1967
edition)
SERVICES
72.01
72.02
72.03
73.01
73.02
73.03
72 Hotels and lodging places, personal
and repair services, except automobile
repair
Hotels and lodging places...
Personal and repair services except
auto repair and barber and beauty-
shops.
Barber and beauty shops..
73 Business services
Miscellaneous business services
75.00
76 01
76.02
77.01
77 02
77.03
77.04
77.05
Advertising
Miscellaneous professional services .
74 Research and development
Eliminated as a separate industry in
the 1963 study. Research and devel-
opment performed for sale is dis-
tributed to the purchaser bv each
of the industries performing the
research and development.
75 Automobile repair and services
Automobile repair and services
76 Amusements
Motion pictures
Amusement and services
77 Medical, educational services, and
nonprofit organizations
Doctors and dentists
70.
72 (excl. 723. 724)
76 (excl. 7692,
7694, and
pt. 7699).
723, 724.
73 (excl. 731,
7396), 7692,
7694, pt. 7699.
731.
81. 89 (excl.
8921).
Hospitals
Other medical and health services.
Educational services
Nonprofit organizations.
GOVERNMENT ENTERPRISES
78 Federal Government enterprises
Post Office
Federal electric utilities
Commodity Credit Corporation
Other Federal Government en-
terprises.
79 State and local government enterprises
Local government passenger transit.
State and local electric utilities
Other state and local government
enterprises.
RTS
78
01
78
02
78.
03
78.
04
79
01
79
02
79
03
75.
78.
79.
801, 802, 803,
804.
8061.
0722, 807, 809.
(excl. pt. 8099)
82.
84, 86, 8921.
IMPO
80.01
80. 02
80 Gross imports of goods and services
Directly allocated imports.
Transferred imports
DUMMY INDUSTRIES
81
81. 00
8'J. 00
82
83
83. 00
SPECIAL
84
84.00
85
8"). 00
86
8fi. 00
Business travel, entertainment and gifts
Business travel, entertainment and
gifts.
Office supplies
Office supplies
Scrap, used and secondhand goods
Scrap, used and secondhand goods.
INDUSTRIES
Government industry
Government industry
Rest of the world industry
Rest of the world industry.
Household industry
Household industry
Source. U.S. Departments Commerce. Bureau at Economic Analyst*.
37
Table A-
-2
PRICE INDICES
(1967 = 1
00)
BEA Sectors
1970
1971
1972
1973
1971*
(1.01). ..(1.03) (2.01)
(2.03). ..(2.07)
1.111+
1.127
1.337
2.031
2.059
(3.00)(l+.00)
1.206
1.280
1.371+
1.1*67
1.670
(5.00)(6.01)(6.02)
1.685
1.1*31+
1.532
2.388
2.31*7
(7.00)
1.1+21
1.1*60
1.590
1.81*6
2.579
(8.00)
1.017
1.007
1.101+
1.192
1.685
(9.00> (10 ..00)
0.991+
1.169
1.212
1.350
1.729
(11. 01). ..(11. 05)
(12.01)(12.02)
1.31+9
1.1+73
1.603
1.779
1.931+
(13.01). ..(13.07)
1.132
1.175
1.209
1.252
1.391+
(ii*.oi). ..(lU. 32)
1.123
1.150
1.209
1.1*1*9
1.619
(15.01)(15.02)
1.130
1.157
1.191
1.238
1.368
(16.01)... (16. Ok)
1.0U0
1.01+2
1.10U
1.237
1.393
(17.01). ..(17-10)
1.015
1.017
1.055
1.151
1.299
(18.01).. ..-(18. Ok)
1.122
1.11+3
1.161
1.208
1.307
(19.01)(19.02)(19.03)
1.027
1.023
1.098
i.ii+3
1.302
(20. 01),.. (20. 09)
1.11+2
1.292
1.1*68
1.819
1.877
(21.00)
1.11k
1.212
1.300
1.575
1.71*1
(22.01). ..(22. Ok)
1.116
1.11+8
1.171
1.227
1.358
(23.01). ..(23.07)
1.138
1.161+
1.196
1.305
1.51*2
{2k. 01). ..(2^.07)
1.078
1.087
1.115
1.188
1.1*86
(25.00)
1.079
1.113
1.156
1.21*6 -
1.1*66
(26.01). ..(26.08)
1.162
1.212
1.21+5
1.296
1.376
(27-01)... (27. Ok)
0.992
1.013
1.025
1.075
1.1*71
(28.01)... (28. Ok)
O.969
0.962
0.963
0.983
1.210
(29.01)(29.02)(29.03)
1.037
1.06U
1.066
1.080
1.173
(30.00)
1.113
1.11*8
1.175
1.222
1.570
(31.01)(31.02)(31.03)
1.003
1.059
1.080
1.1*06
2.125
(32. 01)... (32. Ok)
1.059
1.081
1.101+
1.152
1.393
(33.00)
1.089
1.117
1.1*07
1.591
1.512
(3**. 01) (31*. 02) (3**. 03)
1.110
l.ll+O
1.221
1.299
1.390
(35.01)(35.02)
1.209
1.279
1.316
1.359
1.1*90
(36. 01)... (36. 22)
1.128
1.210
1.255
1.301*
1.1*91
(37.01)... (37. Oil)
l.ll+O
1.225
1.292
1.337
1.695
(38.01)... ( 38. Ik)
1.223
1.158
1.161
1,270
1.683
(39.01) (39.02)
1.125
1.218
1.290
1.350
1.652
(1*0.01).. .(1+0.09)
1.117
1.175
1.211+
1.261
1.586
(1+1.01) (1*1.02)
1.175
1.216
1.2^7
1.31+7
1.630
(1+2.01)... (1+2.11)
1.129
1,181*
1.226
1.261+
1.1*81*
(1+3.01) (1+3.02)
1.11+8
1.200
1.239
1.271
1.1*31
(1*1*. 00)
1.125
1.166
1.211
1.21*5
1.1*10
(U5.0l)(l+5.02)(l+5.03)
1.161+
1.221
1.267
1.318
1.550
(1+6.01)... (1+6. 01+)
1.11+7
1.195
1.226
1.261+
1.1*28
(l+7.0l)...(l+7.0l+)
1.125
1.157
1.177
1.21*5
1.1*39
(1+8.01). ..(1+8. 06)
1.158
1.206
1.236
1.303
1.516
(1+9. 01)... (1+9. 07)
1.139
1.185
1.215
1.260
1.1*71*
(50.01). ..(50.05)
1.217
1.296
1.337
1.1*00
1.611
(51.01)... (51.01+)
1.015
1.030
1.038
1.01*7
1.067
(52.01). ..(52.05)
1.071
l.llU
1.12k
1.132
1.232
(53.01). ..(53.08)
1.085
l.llU
1.120
1.11+7
1.329
38
Table A-2 (continued)
PRICE INDICES (continued)
(1967 = 1.00)
1912 1971 1972 1973 197h
(5U.01) ...(5U. 07) 1.057 1.071 1.075 1081. 1 n
55-01 (55.02X55.03) 1.106 1.163 1.182 I 213 J'S,
56.01)... (56. 0U) 1.06!. 1.106 1 120 1 170 Tnftn
"•°J)(57 -02)(57.03) 0.983 0.989 Jj^ oloo !o6
S:feS U i:o93 iail ill,1 ilil iii°
&£::: : • if5i i-238 j-» ^
(61.. 01)... (61*. 12) 1.08)t
121 1.155 1.200 1.355
(fis'ool l'1J? ~359 l-389 l-1*22
6s"o? 1-166 1'356 1"555 i-SSS 2.101
^5.03; 1.10P 1 1«0 T AA? , ,r-r. -
<(k no ■ ' ,5 —"y L-ia? l-u22 I.517
(65-°2) i-1* 1-356 1.555 1.983 2.101
1.182 1.203 I.155 1.272
0.930 0.972 0.961 1.051
(65 OU) Af, 1-182 1-203 ^^ 1-272
fs'05 °-967 °'930 °-972 0.961 1.051
fis"o1 1-15" 1-203 X-266 1-381* 1.W.3
^•07 1.083 1.173 1.109 1.228 1.275
67 TO I"020 1-°62 la°T X-136 1-lft
:i-(68-03) ™ -- -" -S i:%
So'oo i,°95 la2° i'163 1-278 1502
7o'oi (70 «1 1'197 X-268 l'280 X-327 1-^7
70'ni " l'33b 1'297 i-S*11 1-Wli I.6U7
S'Ss ^-135 X'318 X-381 1'355 i-1*20
n 01 (71 02) }'U* X-221 X-306 i-28? 1-381
71.01 (71.02) !.12L. la6o 1-201 g
• L2 „„ 1-138 1.228 1.200 1.271 1.1.13
73' 01 7, '02 1'152 1>1T8 ^^ X-275 1-358
?HJ ( ,"139 X-192 X'221 1-339 1.371.
7,'oo '-1!7 ^^ 1'353 i-^O 1-552
76"m 1'lf? X-238 I-28? 1-307 l.klk
7fino ^ la65 1-21Z l-239 1.381
77'm (77 0PW77 ml la8:! 1,m 1-282 i-336 l-*05
77.01 (77.02X77.03) 1.229 1.286 1.31.1 1.395 1.520
77 ' X-2i5 1-277 1.397 1.529 I.698
(ll'oV) (78 om ^f6 i-307 l-3^ 1-367 1.U51.
79'm ' ' 7q'o, X'^3 Ukl9 :-623 1'377 1.800
(8l.O0)(82.00)(83.0O) i:^3 J,*T 1319 138 l^oi
Construction Cost Index 1.277 1.1*69 1.597 I.769 1.955
Source: Phillip Ritz, US Dept. of Comrrerce, Bureau of Economic Analysis and Several
Issues of Engineering Nevs Record
39
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Table A-6
Major Products of Common BEA Sectors
BEA
Sector Source
**
9.00
11.02
A
11.03
B
B
11.05
12.02
B
B
27.01
27.014
*
Major Products
##*
li+22 Crushed and Broken Limestone
1U29 Crushed and Broken Stone, n.c.c,
lU^2 Construction sand and Gravel
New Construction
New Construction
New Construction
New Construction
New Construction
New Construction
Industrial Buildings
Office Buildings
Stores, Restaurants
Education Buildings
Hospital Buildings
Other Non-farm
New Construction Telephone, Telegraph
New Construction Electric Utilities
New Construction Gas Utilities
New Construction Water Supply
New Construction Sewers
New Construction Farm Residential
New Construction Earm Service
New Construction Oil/Gas Wells
New Construction Military-
New Construction Conservation & Development
New Construction Other Non-building
Maintenance Construction Other Non-farm
Maintenance Construction Railroads
Maintenance Construction Water Supply
Maintenance Construction Military-
Maintenance Construction Highways
28151 Cyclic Intermediates
28182 Miscellaneous Acyclic Chemicals and
Chemical Products
28191 Synthetic Ammonia, Nitric Acid and
Ammonia Compounds
28199 Other Inorganic Chemicals n.e.c.
28911 Glues, Adhesives, and Sizes
28921 Explosives (except government owned
and contractor-operated plants)
28$
Q%
21%
2k%
lk%
105
2k%
1%
\2%
1%
h2%
lk%
12%
10$
Q%
2Q%
29%
13,o
k2%
6%
6%
%
11%
1%
30%
6%
1%
12%
7 of
1967
Implied
Price
56.10 $/short toi
IOI4.OO $/short toi
.20 $/lb.
Includes sectors providing more than 1% of the capital costs or more than 5% of the
non-energy operating costs for any of the six energy facilities in Just, et al
New Energy Technology Coefficients and Dynamic Energy Models.
See Code at end of table.
t
A major product is one accounting for >_ 5% of the control total for the se-tor
considered unless noted. See code for explanation of control total.
n.e.c. = not elsewhere classified
n.s.k. = not specified by kind
*#
***
55
BEA
Sector Source
36.01
36.10
36.12
36.17
36.19
36.20
36.21
Table A-6 (continued)
Major Products
1967
Implied
Price
2893- Printing Ink 9%
2895- Carbon Black 5%
28993 Essential Oils, Fireworks, and
Pyrotechnics and Chemicals and Chemical
Preparation 3H/o
32^10 11 Portland Cement
9h%
32710 13 Lightweight Aggregate Structural
Block 5 3%
32710 16 Heavyweight Aggregate Structural
Block 23$
32710 00,02 Concrete Block and Brick n.s.k. 18%
.5k 3/lb,
.07 S/lb.
.28 $/ib.
^ */3768i£
.20 $ /Block
32730 11 Ready-mix Concrete
100/1
32922 Asbestos Friction Materials 26%
32926 Vinyl Asbestos Floor Tile 27%
32927 Asbestos Textile and other Asbestos and
Non-asbestos Cement Products . 38/»
32950 11 Lightweight Aggregate 9%
32950 20 Dead-burned Magnesia or Magnesite 10%
32950 31 Crushed Slag 1*$
28%
32961 — Mineral Wool for Structural Insula-
tion
32961 27 3.0 to k.k inches thick Building
Batts , Blankets and Rolls ;
32961 33 2.0 to 2.9 inches thick Blankets
(flexible including Fabricated pieces,
rolls , and batts :
32962 31 Plain
32962 36 Faced and Metal Meshed
32962 51 Blocks and Boards
32962 6l Pipe Insulation
32962 71 Acoustical Pads and Boards
32962 98 Other Mineral Fibers for Industrial
Equipment , and Appliance Insulation
such as loose fiber (shipped as such)
granulated fiber felts, insulating and
finishing cements, etc.
lU.UO 3/cu.yd.
1.07 $/sq.yd.
1.78 S/short
ccf
32970 15 Magnesite and Magnesite-chrome Brick
and Shapes 30 /»
32970 21 Chrome and Chrome-magnesite Brick
and Shapes °'»
9%
.OH
$/sq.ft
5%
s,
.OH
$/sq.ft
18%
1%
n%
.05
$/bd.ft
8%
.31
S/ln.ft
8%
.22
$/sq. ft
96 $/9" eqi'
85 $/9" eajv
56
BEA
Sector
Source
Table A-6 (continued)
Major Products
1967
Implied
Price
32970 35 Carbon refractories; brick, blocks
and shapes , excluding those contain-
ing natural graphite lk%
32970 65 Basic plastic refractories and ram-
ming mixes, wet and dry types 6$
32970 92 Nonclay gumming mixes 7$
1.62 3/9" equiv.
113 $/short ton
86.30 3/short ton
37.01
c
33121 pt. Coke Oven and Blast Furnace Products,
except Ferroalloys 5$
33122 Steel Ingot and Semi-finished Shapes 11$
33123 Tin Mill Products , Hot-rolled Sheet &
Strip 20$
33121+ Hot-rolled Bars and Barshapes ; Plates 19$
38.10
c
33571
Aluminum and Aluminum-base Alloy Wire
^ and Cable 7$
33572 Copper and Copper-base Alloy wire,
including Strand and Cable, Bare and
Tinned for Dectrical Transmission 10$
Ilk $/short ton
1070 $/short ton
1+0.01+
c
3I+U1O Fabricated Structural Metal n.s.k. 9$
3I+I+H Fabricated Structural Metal for
Buildings 1+8$
31+^12 Fabricated Structural Metal for Bridgesll$
31+1+13 Other Fabricated Structural Metal 19$
337 $/short ton
363 $/short ton
1+38 $/short ton
1+0.06
c
31+1+31 Heat Exchangers and Steam Condensers 13$
31+1+32 Fabricated Steel Plate, including Stack
and Weldments 20$
31+1+33 Steel Power Boilers, Parts and At-
tachments (over 15 p.s.i. steam working
pressure) 20$
31+1+37 Metal Tanks, Complete at Factory
(standard line, non-pressure) 7$
31+1+38 Metal Tanks and Vessels, Custom
Fabricated at the Factory 18$
31+1+39 Metal Tanks and Vessels, Custom Fabric-
ated and Field Erected 7$
1+5800 $/unit
231 $/unit
273 $/unit
1+1.01
c
31+51- Screw Machine Products 36$
31+521 Bolts, Nuts, and Other Standard
Industrial Fasteners 36$
31+533 Special Industrial Fasteners 13$
31+523 Headed Products Other than Industrial
Fasteners 6$
57
Table A-6 (continued)
1967
BEA
Sector Source
1+1.02
1+2.08
1+3.01
1+3.02
1+5.01
1+5.02
Major Products
3l+6l2 Job Stampings, except Automotive
3l+6l3 Job Stamping, Automotive
3I+618 Other Stamped and Pressed Metal End
Products
19%
58:
Rot
6%
3I+9I+I Automatic Regulating and Control Values
3I+9I+2 Valves for Power Transfer (pneumatic an
hydraulic)
3I+9I+3 Other Metal Valves for Piping Systems
and Equipment (except plumbing and
heating valves)
3I+9I+5 Metal Fittings, Flages, and Union for
Piping Systems
3I+98O 13 Iron and Steel Fabricated Pipe and
Pipe Fittings
9%
7%
07*
d. 1 /0
15%
12%
35111,2 Steam, Gas and Hydraulic Turbine and
Turbine Generator Set Units and Parts 80%
35191 Gasoline Engines under 11 h.p. except
Aircraft, Auto, Truck, Bus and Tank 10%
35192 Gasoline Engines 11 h.p. and Over,
except Aircraft, Automobile, Truck, Bus
and Tank
35193 Diesel Engines (except for trucks and
Buses)
35195,7 Outboard Motors and Tank and Con-
verted Internal Combustion Engines
35199 Parts and Accessories for Internal
Combustion Engines
6%
33%
11%
33%
35313 Parts and Attachments for Tracklaying-
type Tractors, Contractors, Contractors
Off -highway Wheel Tractors, and Tractor
Shovel Leaders
35311+ Power Cranes, Draglines, Shovels, and
Parts
35317 Tractor Shovel Loaders, Exceluding Part
and Attachments
35318 Scrapers, Graders, Rollers, and Off-
highway Trucks, Trailers and Wagons
35319 Other Construction Machinery and Equip-
ment, including Parts
13%
15%
s
16%
10%
12%
35321 Underground Mining and Mineral Bene-
fication Machinery and Equipment
35322 Crushing, Pulverizing, and Screening
Machinery
19%
15%
Implied
Price
308 $/unit
216 $/short 1
50 $/unit
2690 $/unit
Table A-6 (continued)
BEA
1967
Imoliei
Sector
Source
Major Products
Price
35323 All Other Mining Machinery and Equip-
ment
3532U Parts and Attachments for Mining
Machinery and Equipment
35320 Mining Machinery n.s.k.
1Q%
1%
1+5.03
C
35331 Rotary Oil and Gas Field Drilling
Machinery and Equipment
35332 Other Oil and Gas Field Drilling
Machinery and Equipment
35333 Oil and Gas Field Production Machinery
and Equipment (except pumps)
3533^ Other Oil and Gas Field Machinery and
Tools (except pumps) including Water
Well
35330 Oil Field Machinery n.s.k.
31%
1%
39%
10%
1%
H6.02
C
35351 Conveyors and Conveying Equipment
(except hoists and farm elevators)
35352 Parts, Attachments, and Accessories
for Conveyors and Conveying Systems
35350 Conveyors and Conveying Equipment n.s.,
13%
1Q%
k.9%
U6.03
C
35361 Hoists
35362 Overhead Traveling Cranes and Monorail
Systems
35360 Hoists, Cranes and Monorails n.s.k.
3&%
1%
lk million$/uni
U8.06
C
35591 Chemical Manufacturing Industries
Machinery and Equipment and Parts
35592 Foundry Machinery, and Equipment,
excluding patterns and molds
35593 Plastics-working Machinery and Equip-
ment excluding patterns and molds
3559^ Rubber-working Machinery and Equipment
excluding the molds
11%
9%
15%
I/O
201*00 $/unit
35595 Other Special Industry Machinery and
Equipment
35590 Special Industry Machinery n.s.k.
M%
6%
U9.OI
C
35611 Industrial Pumps, except Hydraulic
Fluid Power Pumps
35612 Hydraulic Fluid Power Pumps and Motors
and Vacuum Pumps
35613 Domestic Water Systems and Pumps, In-
cluding Pump Jackets and Cylinders
26%
Q%
91000 $/unit
59
Table A-6 (continued)
BEA
Sector Source
^9-03
U9.05
i+9.06
^9- 07
51.01
52.05
53.02
Major Products
1967
Implied
Price
3561^ Air and Gas Compressors, except
Refrigerator Compressor
35615 Pumps and Compressors n.e.c. except
Refrigerator Compressor
35616 Parts and Attachments for Pumps and
Compressors, n.s.k.
29?*
12%
22%
356U1 Industrial Fans and Blowers
356U2 Dust Collection, Air Purification
Equipment and Air Washers
59%
31%
35661 Plain Bearing 9%
35662 Speed Changers , Industrial High Speed
Drivers , and Gears 39/*
35663 Other Mechanical Power Transmission
Equipment ^7/*
851000 $/unit
35671 Electric Industrial Furnaces and Ovens,
Metal Processing 22%
35672 Fuel-fired Industrial Furnaces and
Ovens, Metal Processing 37%
35673 High Frequency Induction and Dielectric
Heating Equipment and Parts, Attachments
and Components
36%
No Subclassifications
35731 Electronic Computing Equipment, except
Parts and Attachments 67/«
35733 Parts and Attachments for Electronic
Computing Equipment
3571+1 Calculating and Accounting Machines,
including cash registers, except parts
and attachments
19 &
10%
35891 Commercial Cooking and Food Warming
Equipment 29/*
35892 Service Industry Machinery and Parts 57%
35890 Service Industry Machines n.e.c, n.s.k 9%
36121 Natural-draft Type Transformers
(specialty transformers)
36122 Power and Distribution Transformers,
except Parts
36123 Power Regulators, Boosters, Reactors,
Other Transformers, and Transformer
Parts .
18%
70%
11%
22 $/unit
3.06 $/unit
Ul+7 $/unit
60
Table A- 6 (continued)
BEA
Sector Source
Major Products
1967
Implied
Pr-1* ce
53.03
c
36131 Switchgear, except Ducts and Relays 29$
36132 Power Circuit Breakers, All Voltage 13$
36133 Low Voltage Panelboards and Distribution
Boards and Other Switching the Inter-
rupting Devices, 750 Volts and Under 2k%
36135 Molded Circuit Breakers , 750 Volts and
Under 11$
36137 Relays, Control Circuit 12$
53,01+
c
36211 Fractional Horsepower Motors 36$
36212 Integral Horsepower Motors and
Generators (except for land xpo equip-
ment 25$
36213 Land xpo Motors , Generators , and
Control Equipment and Parts 6$
3621^ Prime Mover Generator Sets , except
Steam or Hydraulic Turbine 10$
36215 Motor-Generator Sets and Other
Rotating Equipment 15$
36216 Parts and Supplies for Motors , Generator
Generators, Motor Generator Sets except
for Land Transportation Equipment 7$
6600 $/unit
209 $/unit
1590 $/unit
3280 $/ur.it
53.05
No Subclassifications 100$
53.06
c
36231 Arc Welding Machines Components , and Ac-
cessories , except Electrodes 32$
36232 Arc Welding Electrodes, Metal 38$
36233 Resistance Welders, Components, Ac-
cessories and Electrodes 20$
36230 Welding Apparatus n.s.k. 9$
338 $/unit
.22 $/Ib.
55.03
c
36U30 Current Cariying Wiring Devices, In-
cluding Lightning Rods 59$
36HUl Pole Line and Transmission Hardware 10$
36UU2 Electrical Conduit and Conduit Fitting 23$
36UU3 Other Non Current Carrying Wiring Devices
and Supplies 7$
.20 $/lt.
62.02
c
38211 Aircraft Engine Instruments Except
Flight 9$
38212 Integrating Meters, Nonelectric Type lh%
38213 Industrial Process Instruments 55$
3821U Motor Vehicle Instruments except
Electric 5$
38216 Other Mechanical Measuring and Control-
ling Instruments lU$
55 $/unit
1600 $/unit
ol
BEA
Sector Source
Table A- 6 (continued)
Major Products
1967
65.01
H
Railway Express 3%
Electric Railways .2%
Pullman Companies .3%
Class I Passenger Service 5%
Other Class I Non- Freight Service (Baggage,
Main, Switching, Express, etc, 5%
Incidental Operating Revenue 2%
(Dining, Hotel, Rents, Power, Storage, Misc)
Freight Service 83%
68.03
No Subclassification 100$
69.01
D
Motor Vehicles , Automotive Equipment 7%
Groceries and Related Products 20/5
Farm Products, Raw Materials 8%
Electrical Goods 7%
Machinery, Equipment, Supplies 12%
Metals, Minerals (except petroleum products,
scrap) 6%
Beer, Wine Distilled Alchoholic Beverages 5%
Lumber, Construction Materials 5%
69.02
E
Groceries and Other Foods 20%
Meals and Snacks 6%
Cosmetics , Drugs , Cleaners h%
Men's, Boy's Clothing Excluding Footware 3%
Women's, Girl's Clothing Excluding Footware 6%
Major Appliances, Radio, TV, Musical Instru-
ment 3%
Furniture, Sleep Equipment, Floor Coverings 3%
Lumber, Building Material k%
Automobiles and Trucks lk%
Auto Fuels and Lubricants 6%
;
Auto Tires, Batteries, and Accessories 3%
All Other Merchandise k%
1
Nonmerchandise Receipts k%
70. 0U
No Subclassification 100/5
71. 02
No Subclassification 100%
73.01
G
73^+- Services to Dwellings and Other Buildings
(window cleaning, pest control, etc.) 10%
7391 Commercial R&D Laboratories 8%
7392 Business and Consulting Services 21%
739^- Leasing, Rental of Heavy Construction
and all other equipment 10%
7399 Other Business Services n.e.c. lk%
62
Table A- 6 (continued)
BEA
1967
ImDlied
Sector
Source
Major Products
Prices
73.02
G
7311 Advertising Agencies
93$
73.03
No Subclassification
100$
75-00
G
751 Car, Truck Rental Leasing, Without
Drivers
752 Automobile Parking
7531 Top and Body Repair Shops
753^ Tire Retreading and Repair Shops
29%
Ho
12%
6%
7539 Automobile Repair Shops, n.e.c.
75^ Automobile Services , except repair
10%
5%
f3
Table A- 6 (continued)
CODE
A Census of Mineral Industries , reports for SIC sectors comprising 3EA
sector. Table 5 or 6 depending on aggregation level. Control table
is
B Internal C.A.C. documentation. Control total is gross domestic
output .
C Census of Manufacturers, reports for SIC sectors comprising BEA
sector, Table 5B or 6A depending on aggregation. Control total is
value of shipments.
D Census of Business, Vol. 3 Table D: Sales of Merchant Wholesalers,
by kind of business.
E Census of Business, Vol. 1, Table 1: Sales of specified Merchandise
Lines. NOTE: Major products here are defined as any line representing
j^ 3% of total sales.
G Census of Business, Vol. 5, part 1. Table 2: Receipt of All Establishments
is control total.
F Total Insurance Written in 196? is control total from Best's Insurance
Reports - Life /Health 1975 p. vii and "Best's Insurance News," Property-
Liability Edition, Vol. 69, No. 6, p. 38. Percentage breakdowns are
made directly for property-liability from the latter reference and are
based on "sales" for life from "Best's Insurance News," Life Ed.,
Vol. 68, No. 2, p. 2.
H Based on 1966 statistics from the Interstate Commerce Commission. Control
total is total operating revenue for the entire railroad system ($11, 163,
1+22, 895 from Table 109, Transport Statistics 1966. ) Major Products
listed is a subjective list of identifiable classes of real service from
various tables in Transport Statistics, 1966, Part 1.
6U
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66
Appendix B
BIBLIOGRAPHY
Theory of Input-Output Analysis
Leontief , Wassily, The Structure of American Economy , 1919-1939 , Oxford
University Press, 19^+L
, Studies in the Structure of the American Economy, 1953.
, Input-Output Economics , Oxford University Press, 1966.
9 "Environmental Repercussions and the -Economic Structure: An Input-
Output Approach." Review of Economics and Statistics, 52:3:262-71, 1970.
"Input-Output Analysis," a collection of articles from Scientific American, 1970
Miernyk, W. H. , The Elements of Input-Output Economics, Random House, 1965.
Input-Output Data Sources and Refersnce Works
1967 Census of Mineral Industries, U.S. Department of Commerce, Bureau of the
Census, 1970.
, 1967 Census of Manufacturers.
-, 1967 Census of Construction Industries
-, 1967 Census of Agriculture
-, 1967 Census of Transportation
-, 1967 Census of Business
-, 1967 Census of Foreign Trade
Edison Electric Institution, New York, NY, Statistical Yearbook of the
Electric Utility Industry, (annual).
"Fuel and Electric Energy Consumed in Manufacturing Industries, 1962," U.S.
Bureau of Census, report NC63(l)-7-
American Petroleum Institute, Petroleum Facts and Figures, New York
"Consumption of Refined Petroleum Products in 1963 Input-Output Industries,"
JACKFAU-71-73(1) , October, 1971. Jack Faucett Association, Silver Springs, MD.
This report is only disaggregated to 80 sectors, but 360 sector worksheets are
available from Jack Faucett Associates.
Office of Statistical Standards, Bureau of the Budget, Standard Industrial
Classification Manual, U.S. Government Printing Office, 1967.
Definitions and Conventions of the 1967 Input-Output Study, Bureau of Economic
Analysis, 197*+ •
67
Simpson, David and David Smith, "Direct Energy Use in the U.S. Economy, 196?,"
CAC Technical Memo. 39, Center for Advanced Computation, University of Illinois,
Urbana, 6l801, January 1975*
Bullard, C. W. , "Sector Outputs and Intralndustry Transactions: Definition of
System Boundaries," CAC Technical Memo. UO, Center for Advanced Computation,
University of Illinois, Urbana, 6l801, November 197*+.
Input -Output Models
U.S. Department of Commerce, Bureau of Economic Analysis, Input-Output Struc-
ture of the U.S. Economy: 1967 s Vol. 1-3, (also available on magnetic tape from
BEA) (197*0. Available from U.S. Government Printing Office. BEA has several
amplifying articles: "Input-Output Structure of the U.S. Economy: 1963,"
Survey of Current Business , November 1969; "Personal Consumption Expenditures
in the 1963 Input-Output Study," SCB. January, 1971; "Interindustry Trans-
actions in New Structures and Equipment, 1963, 5CB, August 1971. "Definitions
and Conventions of the 1967 Input-Output Study," April 1972 (available on re-
quest from BEA)
W. Leontief, "Environmental Repercussions and the Economic Structure: An In-
put-Output Approach," Review of Economics and Statistics 3 52, No. 3, 363-71
(1970).
Herendeen, R. A., "An Energy Input-Output Matrix for the United States, 1963:
User's Guide," CAC Document No. 69, Center for Advanced Computation,
University of Illinois, Urbana, 6l801, March 1973.
Bullard, C. W. and Robert Herendeen, "Energy Cost of Consumer Goods 1963/67,"
CAC Document No. lUo , Center for Advanced Computation, University of Illinois,
Urbana, 618OI, November 197*+. Energy Policy , 3:H, December 1975-
Folk, Hugh and Bruce Hannon, "An Energy, Pollution and Employment Policy Model,"
CAC Document No. 68, Center for Advanced Computation, University of Illinois,
Urbana, 618OI, February 1973. Energy: Demand, Conservation and Institutional
Problems, MACKRAKIS, M.S., editor, M.I.T. Press 197*+, Chapter 13.
Bullard, C.W. , "An Input-Output Model for Energy Demand Analysis, CAC Document
No. lU6, Center for Advanced Computation, University of Illinois, Urbana, 6l301,
December 197*+.
Bullard, C. W. and Robert Herendeen, "Energy Impact of Consumption Decisions."
Proc. IEEE 63:3: U8U-i+93, revised March 1973.
Input-Output Models: Error Analysis
Problems of Input-Output Tables and Analyses. Studies in methods series F,
No. Ik. United Nations, New York.
Kirkpatrick, Ken, "Independent Verification of Input-Output Results, CAC
Technical Memo. 26, Center for Advanced Computation, University of Illinois,
Urbana, 618OI, August 197*+.
68
^'^f ^ Anthony Sebald, "Effects of Parametric Uncertainty and Te~h
nological Change In Input-Output Models," CAC Document 156, Center tor Mva^ced
Computation, University of Illinois, Urbana, 6l801, March 1975. Advanced
o?1^^' J1^ !* and Annh°ny V' Sebald> "A Model for Analyzing Energy Impact
£^^^^>:, r^ir of the l9T5 *- * w- ~-
P^rd' C\W; and David A- Pllati> "Reducing Uncertainty in Energy Analysis "
"blnt^^ ** "™d °— ^iversity^f ZlSois ,
Bullard, C. W. , Donna L. Amado, Dan L. Putnam, Anthony V. Sebald "stochastic
Center for Advanced Computation, University of Illinois, Urbana, 61801, September
£_£. r™L' "Errf „Tolerances °n En^sy Model Results ," CAC Technical Memo 75
Center for Advanced Computation, University of Illinois, Urbana, 61801, June 1976.
196?"*^ *_"•' "f«eCt °LInClUding CaP"al Flows o" Energy Ceofficients ,
1963, CAC Technical Memo. 32, Center for Advanced Computation, University of
Illinois, Urbana, 61801, August 197ft. ' ' G1
Putnam, Dan, Ralph Richard, and Clark Bullard, "Energy Labor and Canital [M.t-
the Energy Employment Model," CAC Technical Memo. 36 Center for Advanced ^ + _°
University of Illinois, Urbana, 618OI, January 1975. Advanced Computation,
oc"^sj WV-75, Battelle Memorial Institute, 1971.
Empirical Tests of Input-Output Forecasts: Review and Critique, Bureau of
Economic Analysis, 197*+. H *
f±T^k R°Se^ "Anal^S °f ChanSes in U'S- Input-Output Final Demand Coef-
licients, Bureau of Economic Analysis, 1973.
Applications of 1-0 Analysis and Process Analysis
^heestatP;^ \ f ^ "APPlica^ons °? Imput/Output Analysis." Also Carter,
The State of the Arts in Projecting Input-Output Structures," Institute of
Management Sciences, 1967. x
of Mr' ^i°ny/»d+ROt!r? Herendee"> "The D°H*r, Energy and Employment Impacts
nf i VBalL d Autonotlle Passenger Transportation," CAC Document No. 06
MTUer ™_ fvance* Computation, University of Illinois, Urbana, 61801, Se.tember
in! rJ /3l C°nsemat™» *"P«». (Robert H. Williams, ed. , Ballinger 4lT-h-
ing Company, Cambridge, MA, 1975, Chapter 3.) --udj.i_.i-
Certafn6^ R' A" TtA- Vm Setald' "The D°llar'' Ener^ and Employment Impacts of
Sfv i TnvP™S' CAC D?Crent No- 97- Center for Advanced Commutation
University of Illinois, Urbana, 61801, April 197,. "
69
"Energy Use Patterns in Metallurgical and Nonmetallic Mineral Processing," Report
to U.S. Bureau of Mines, Battelle/Columbus Laboratories, 1975.
Teasley, Larry I. , "Energy Implications of Polymer Production and Us-.," Washing-
ton University, St. Louis, 197^.
Pilati, David A. and Ralph Richard, "Total Energy Requirements for Nine Elec-
tricity-Generating Systems," CAC Document No. 165, Center for Advanced Computa-
tion, University of Illinois, Urbana, 618OI, August 1975. Energy, Vol. 2 No. 1,
pp. 1-7, 1977.
Rotty, R. M. , A. M. Perry, D. B. Reister, "Net Energy From Nuclear Power," Report
No. IEA-75-3, Institute for Energy Analysis, Oak Ridge, TN, 1975-
Hannon, Bruce, "System Energy and Recycling: A Study of the Beverage Industry,"
CAC Document No. 23, Center for Advanced Computation, University of Illinois,
Urbana, 618OI, March 1973.
Bullard, Clark, "Energy Costs, Benefits, and Het Energy," Energy Systems and Policy,
Vol. 1 No. k, p. 376-381, 1976.
Herendeen, Robert and Jerry Tanaka, "Energy Cost of Living," CAC Document No. 171,
Center for Advanced Computation, University of Illinois, Urbana, 618OI, April 1975-
Perry, A. M. , "The Energy Cost of Energy-Guidelines for Net Energy Analysis,"
Associated Universities Institute for Energy Analysis, Oak Ridge, TN, 1976.
70
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