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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, .
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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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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 |
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|
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.
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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
Ml