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Methodology for Projections

of Industry Employment to 1990

J.S. Department of Labor 

3ureau of Labor Statistics 

rebruary 1980

Bulletin 2036

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United States. Bureau of Labor Statistics.

Methodology for projections of industry employment

to 1990.

(Bulletin - Bureau of Labor Statistics ; 2036)

Written by Thomas Fleming and Richard Oliver.

Bibliography: p.

Supt. of Docs, no.: L 2.3:2036

1. Employment forecasting— -United States. 2. Economic forecasting— -United States. I. Fleming, Thomas F.

II. Oliver, Richard P. III. Title. IV. Series:

United States. Bureau of Labor Statistics.

Bulletin ; 2036.

HD572U.U625 1980 33I.11’0973

Library of Congress Cataloging in Publication Data

79-607923

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Methodology for Projections

of Industry Employment to 1990

U.S. Department of Labor 

Ray Marshall, Secretary

Bureau of Labor Statistics 

Janet L. Norwood, Commissioner 

February 1980

Bulletin 2036

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Preface

This bulletin presents a description of the Bureau of 

Labor Statistics (BLS) Economic Growth model system used to develop the 1990 industry employment projections. It is intended primarily for those analysts who 

desire detailed information on the BLS projections 

methods, models, and techniques. The text covers the 

components of the Economic Growth system used to 

develop these projections and the sequence of their application. The appendixes provide the detailed equations used in the various model systems as well as a 

description of the software solution package.

The results of the 1990 projections were presented 

in three articles published in the Monthly Labor Review:

“The U.S. Economy to 1990: Two Projections for 

Growth,” December 1978, by Norman Saunders; 

“Changing Patterns of Demand: BLS Projections to 

1990,” December 1978, by Authur Andreassen; and 

“Output and Employment by Industry; Projections to 

1990,” April 1978, by Valerie Personick.

These articles covered the results and analytical 

aspects of the macroeconomic scenarios, the demand 

projections, and the industry output and employment 

estimates. Industry employment projections are primarily used within the Bureau as a basis for the occupational projections developed by the Occupational Outlook program. These are used by the Department of

Labor and a variety of other groups in planning training programs and in counseling students and workers. 

The industry projections also are used by business firms 

as a source of information in developing long-range 

capital investment programs and in anticipating changes 

in the structure of markets.

This bulletin was prepared in the Office of Economic Growth, under the supervision of Ronald E. Kutscher, Assistant Commissioner for Economic Growth. 

The report was written by Thomas Fleming and Richard Oliver. Norman Saunders contributed the methodology on the macroeconomic projections. Material on 

the techniques of projecting interindustry coefficients 

was provided by Joanne Hepburn and Tom Mooney. 

Methodologies used in projecting the major final demand sectors were provided by Arthur Andreassen, 

Robert Sylvester, Karen Horowitz, and David Frank. 

Valerie Personick developed the estimates of industry 

employment. John Tschetter provided the section on 

prospective areas of new development. Sandy Proctor 

assisted in the preparation of the manuscript.

Material in this publication is in the public domain 

and may be reproduced without permission of the Federal Government. Please credit the Bureau of Labor 

Statistics and cite Methodology for Projections of Industry Employment to 1990, Bulletin 2036.

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Contents

Page

Chapter 1. Overview of the BLS projections system .................................................................. 1

Earlier versions.................................................................................................................... 1

Current methodology ........................................................................................................ 2

Chapter 2. Aggregate economic projections .............................................................................. 5

Overview ............................................................................................................................. 5

Assumptions of the macro projections ................................................................................ 5

Supply GNP ....................................................................................................................... 7

Income flo w s....................................................................................................................... 8

Demand GNP .................................................................................................................... 9

Price/wage se c to r................................................................................................................. 10

Balancing the macro model ............................................................................................... 10

Solving the macro m o d e l..................................................................................................... 10

Chapter 3. Final demand projections......................................................................................... 11

Overview ............................................................................................................................. 11

Assumptions ....................................................................................................................... 11

Personal consumption expenditures .................................................................................... 12

Gross private domestic investment ...................................................................................... 13

Net exports ....................................................................................................................... 15

State and local government ............................................................................................... 18

Federal Government ............................................................................................ 19

Chapter 4. Intermediate demand projections ........................................................................... 21

Industry classification ......................................... 21

Industry conventions of input-output ................................................................................. 21

Valuation of transactions .................................................................................................. 22

Secondary product transfers ............................................................................................... 22

BLS input-output system .................................................................................................. 23

Projecting coefficients ........................................................................................................ 24

Chapter 5. Employment projections......................................................................................... 26

Output per hour ................................................................................................................. 26

Average weekly hours ........................................................................................................ 27

Industry employment ........................................................................................................ 27

Chapter 6. Planned changes in the projections system ............................................................... 28

Macro model ....................................................................................................................... 28

Factor demand in industry detail ...................................................................................... 28

Macro and micro relationships ............................................................................................ 29

Appendixes:

A. Macroeconomic model equations, identities, and variables.......................................... 30

B. Potential economic growth assessment system for the

United States (PEGASUS)...................................................................................... 41

C. Personal consumption model equations ..................................................................... 42

D. Investment-output ra tio s............................................................................................ 57

E. Federal Government equations ................................ 60

F. Labor demand coefficients......................................................................................... 61

G. Economic Growth sectoring plan .............................................................................. 69

H. Data sources .............................................................................................................. 72

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Chapter 1. Overview of the

BLS Projections System

The 1990 industry employment projections are the 

latest in a series that started in the mid-1960’s as the 

product of an interagency project to study the conditions and requirements for balanced economic growth 

in the United States. Since that time, projections studies have been completed for 1970, 1975, 1980, 1985, and 

1990.' While the general approach has been similar for 

each of these studies, the methodology has been continually modified to include greater industrial detail, 

more rigorous analytical techniques, and a more automatic system for processing calculations. Since that 

time, the interagency character of the projections has 

also changed. Although certain data and assumptions 

are still coordinated with other agencies, the projections have become more a BLS responsibility.

Earlier versions

The first version of the Economic Growth model 

system was formulated in 1963 for the 1970 projections. 

This version represented a conventional application of 

the input-output technique and was used for both the 

1970 projections and the first set of 1980 projections. 

In this version, supply GNP (gross n .ti< nal product) 

was first projected exogenously based up un independent projections of aggregate labor force, hours, and 

productivity. Several distributions of demand GNP 

were then developed through a combina;ion of trend 

analysis and assumption. In the next stage, analysts projected industry purchases for major c; te »ories of demand GNP. A model was used in only one case to assist in the projection of the bill of gocds. This was a 

consumption demand model developed by H. S. 

Houthakker and L. D. Taylor discussed in the following text. Simultaneously, the coefficients of an inputoutput table were projected. The table used was the 

Bureau of Economic Analysis’ (BEA) 1958 table of 82 

sectors. This table was updated and then projected to 

1970 and later to 1980. The projected bills of goods 

were used with the projected tables to develop estimates of gross output by industry. Employment estimates for each industry were then developed from projected employment-output ratios. These were based 

upon industry projections of hours and productivity.

A second version of the system was used for the 1975 

projections and a second set of 1980 projections. The 

principal change was the introduction of a macroeconomic model for the purpose of projecting more balanced and consistent demand levels. The macro model’s key function was to develop estimates of the distribution of demand GNP in real terms for the major demand categories. In addition, this model added other 

analytical features. Among these were the capability to 

be more explicit about fiscal policy assumptions, to examine the factors influencing the derivation of income 

projections at a macro level, and to derive projected 

revenues of the Federal and State and local government 

sectors. It also permitted the development of a time 

path for the projections and not just the projection of 

a point in the future. The macro model provided an 

aggregate production function which could be used to 

project supply GNP from both labor and capital inputs. 

However, in its early use of this model, BLS continued 

to use the procedures of the first version to project 

supply GNP. Initially, the aggregate production function overpredicted potential growth, in part because of 

its inability to account for shifts between the agricultural and nonagricultural sectors of the economy.

Another change in the second version of the system 

was the addition of a very crude capital component 

which evaluated an initial final demand vector for investment in equipment and nonresidential structures in 

total and by type. This process involved using: (1) Investment-output relationships, (2) capital flows tables, 

and (3) projected changes in industry outputs. Capital 

flows tables convert investment by purchasing industry 

into investment by type of capital good. While this provided a crude check on the amount and type of capital 

required in each industry based on its projected rate of 

growth, it was simplistic. Investment in each industry 

was then determined only by the growth in its output 

with no consideration of capital replacement 

requirements.

' ’’Revised BLS Projections to 1980 and 1985,” Monthly Labor Review, Mar., Aug., and Nov. 1978; and the following Bureau of Labor

Statistics bulletins, The Structure o f the U.S. Economy in 1980 and

1985, Bulletin 1831, (1975); The U.S. Economy in 1985, Bulletin 1809,

(1974); Projections o f the Post-Vietnam Economy, 1975, Bulletin 1733,

(1972); The U.S. Economy in 1980, Bulletin 1673, (1970); Patterns of

U.S. Economic Growth, Bulletin 1672, (1970); and Projections 1970:

Interindustry Relationships, Potential Demand, and Employment, Bulletin 1536 (1966).

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The second version of the Economic Growth System, as in the first, had a limited feedback from the 

micro or industry level to the macro level. This feedback was not directly modeled. It generally took the 

forms of balancing the industry employment estimates 

with total employment, reviewing the initial stipulation 

of investment requirements against the generated investment level, and comparing the industry structure 

of generated imports with the macro stipulation.

The input-output tables used in the second version 

were based upon the BEA’s 1963 table aggregated to 

134 sectors. This base was updated by BLS to 1970 and 

then projected to future years. The third version of the 

Economic Growth system described in this bulletin was 

based upon the BEA’s 1967 table aggregated to 162 industry sectors. This table was updated to 1973 and then 

projected to 1980, 1985, and 1990.

In the third, or current version, a major change was 

made in the production function of the macro model 

to cover only the private nonfarm economy rather than 

the total private economy to capture shifts between the 

farm and nonfarm sectors. An equation was also added 

to the model to project hours. Also, a small price-wage 

sector was introduced. Two new final demand models 

were included for the first time: One for State and local government purchases and the other covering Federal Government revenue and outlays. While not fully 

integrated in the system, these were used in a limited 

manner. In addition, a labor demand model was introduced to replace the ad hoc procedures used in the earlier versions to project industry productivity.

Current methodology

BLS industry employment projections currently are 

produced using a variety of models and analytical methods. There are five major steps in projecting industry 

employment levels: 1) A macro model projection of the 

aggregate economy; 2) a disaggregation of GNP to detailed demand categories; 3) a distribution of each demand category to producing industries; 4) projection 

of an input-output table and its use in solving for industry outputs; and 5) a projection of productivity, 

hours, and employment at the industry level of detail.

Some portions of each step are independent of the 

other steps, but, in general, each step is also dependent 

to some degree upon the step prior to it. The current 

approach allows for only limited conceptual or computerized feedbacks from a later step to an earlier one. 

However, results at certain stages are compared analytically with earlier controls, and adjustments are made. 

Linkage of the various steps is accomplished with a 

software package known as the Potential Economic 

Growth Assessment System for the United States 

(PEGASUS). This software system is described in appendix B in terms of its impact on these projections. 

More detailed system descriptions and users’ guides are 

available upon request.

Industry projections start with a set of assumptions, 

or a scenario, describing the expected conditions of 

growth. Various policy targets and other assumptions 

are formulated and fed into a macroeconometric model, along with base period data. This model uses these 

assumptions to develop consistent projections of supply 

or potential GNP growth and the resulting income 

flows. Income flows are next used by the model in projecting demand GNP by major components. Supply and 

demand GNP are balanced, providing control totals for 

the purchases of various final demand sectors which 

are consistent with all conditions and assumptions. The 

industry employment projections usually assume that 

government goals for reduced unemployment, control 

of inflation, and a more favorable trade balance will 

generally be achieved or approximated. Policy variables and exogenous demand levels are adjusted to permit the economy to achieve potential levels of output 

consistent with these goals.

Control totals for each of the categories of demand 

GNP developed in the macro model are then used with 

various techniques and submodels to distribute sector 

demand to functional categories of demand or product 

groups. For example, personal consumption expenditures for nondurable goods are distributed to various 

product groups, such as food purchased for use at home, 

while investment in producers’ durable equipment is 

distributed by purchasing industry.

The next step is to distribute the functional or product level demand in each sector to specific purchases 

of goods and services produced by 162 different industries using projected factors or bridge tables. This industry classification is consistent with the interindustry 

models used to project intermediate demand. The coefficients of the input-output models are projected separately based upon such things as expected changes in 

technology, shifts in inputs, and changes in the mix of 

products. They provide the framework for estimating 

the purchases each industry must make to support its 

projected sales. The projected interindustry tables, or 

matrices, provide estimates of the projected output 

needed from each industry for all final and intermediate demand requirements. At this stage, each industry’s 

output level is evaluated for projected changes in total 

output and the share going to final and intermediate 

sales. Where annual rates of change in output or the 

distribution of intermediate and final demand vary significantly from past experience, the analytical reasons 

are reexamined. As a result, changes may be made in 

final demand purchases or coefficients.

The projections sequence then proceeds to estimating industry employment requirements. A labor demand model is used to project productivity changes in 

each industry. Industry output requirements are then 

converted to industry employment requirements. Finally, the industry employment changes are compared to 

historical change. If the growth in employment appears

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reasonable, it is aggregated and compared with levels 2. Industry purchases

used at the macro stage. At all steps in this process, the 

disaggregated estimates are made consistent with their 

macro counterparts.

An outline of the various analytical stages of the projections methodology is given below. Chart 1 shows 

the computational blocks of the system.

A. Macroeconomic projections

1. Policy inputs

2. Potential GNP

3. Income flows

4. Demand sectors

Final demand purchases

1. Functional levels

C. Interindustry tables

1. Base period tables

2. Coefficient projections

3. Projected tables

D. Projected industry outputs

1. Calculation of gross outputs

2. Evaluation and feedback

E. Projected industry employment

1. Productivity changes

2. Labor demand

3. Evaluation and feedback

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Chart 1. Economic Growth System

Industry Activity Model

Personal

consumption

expenditures

submodel

BLS Labor Demand Model

Industry

productivity

Industry

hours

Industry

employment1

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Chapter 2. Aggregate

Economic Projections

Overview

The macroeconomic model provides estimates of 

growth in the major sectors of the economy that are 

consistent with all assumptions and conditions of a particular projection scenario. The purpose of the aggregate projections is to provide consistent and integrated 

control totals for the projected industry purchases that 

are developed later in the system. Projections for the 

overall economy are prepared using a modified version 

of a fiscal-policy model first designed and estimated by 

Lester Thurow in 1969.

The BLS macro model is a relatively small-scale 

model (approximately 50 equations) whose purpose is 

to capture the impacts of those factors which affect demand and supply over the medium to long term.2 The 

model is structured around a framework in which output produced is balanced with output demanded via income flows. To bring about this balance between supply and demand GNP, the model is structured to respond to fiscal policy changes, which affect the level 

and distribution of spendable income in the personal 

and corporate sectors. The following discussion of the 

model covers its three main areas or blocks: Supply, 

income, and demand. Although these blocks are treated 

as separate entities, they are not independent, due to 

simultaneous solutions in the structure of the model. A 

fourth block, price/wage determination, is discussed 

briefly as well. Major exogenous variables are pointed 

out as necessary. All of the behavioral equations and 

major model identities referred to in the text are detailed in appendix A.

The four computational blocks of the model are outlined below. It is important to note that all blocks are 

solved simultaneously.

A. Supply-side GNP

1. Aggregate labor force, employment, and average 

hours

2. Total hours

3. Aggregate capital stocks

4. Gross product originating

5.. Output per hour

B. Income

1. Corporate sector

a. Profits

b. Capital consumption allowances

c. Corporate profits taxes

d. Corporate dividends

2. Personal income

a. Indirect business taxes

b. Transfers to persons

c. Social insurance contributions

d. Personal taxes

e. Personal savings

C. Demand-side GNP

1. Personal consumption expenditures

2. Gross private domestic investment

a. Producers’ durable equipment

b. Nonresidential structures

c. Residential structures

d. Change in business inventories

3. Net foreign trade

a. Exports

b. Imports

4. Government

a. Federal

b. State and local

i) education

ii) other

D. Price/wage

1. Private GNP implicit price deflator

2. Private compensation per hour

Assumptions of the macro projections

There are 51 variables in the BLS macroeconomic 

model that are exogenous, or that must be estimated 

externally in various ways for the projected periods. 

From a solution point of view, all exogenous variables 

are assumptions. From a structural approach, however, 

the exogenous variables may be grouped in three ways. 

First are those items projected with sophisticated techniques outside the Office of Economic Growth, such 

as the population or labor force estimates. Second are 

those items which represent either policy instruments

2 Lester C. Thurow, “A Fiscal Policy Model of the United,”—

iSurvey o f Current Business, June 1969, pp. 4S-64.

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or policy goals. The policy instruments, such as Federal tax rates or Federal employment levels, represent 

the Federal Government’s position at any particular 

point in time. The policy goals, such as the unemployment rate or the Federal deficit, are the result of such 

measures. Finally, there are those exogenous variables 

which are assumptions in the narrowest sense; i.e., they 

represent a judgment as to the probable course of a 

particular item. An example of this category would be 

the inflation rate.

When all of these variables are projected and considered as a whole, they present a picture of the economic conditions assumed for a particular set of projections. All of the projection results are heavily influenced by the initial assumptions required to operate the 

macro model. These follow from the nature of the scenario or the conditions being examined for their effects 

on employment. Four categories of explicit assumptions 

are developed for each scenario: Demographic, fiscal 

policy, price, and productivity and employment assumptions. In addition, certain general goals or guidelines 

affect the projections process. For example, the effects 

of rising energy prices and potential energy shortages 

were considered and were assumed, or expected, not 

to be sufficient to affect aggregate economic growth. 

Foreign trade was assumed to achieve a rough balance 

over time. And, in balancing supply and demand GNP, 

there was an attempt to maintain Federal outlays as a 

percent of GNP at below current rates and approximately to balance budget receipts and expenditures to 

the extent the scenarios permitted.

Demographic. Demographic assumptions include the 

projected size of the population and its component 

groups, such as urban and rural, number of households, 

and changes in the size of the school-age population. 

The primary determinants of the demographic assumptions are the current and expected level and age distribution of the population. Three projected population 

series were available, differing primarily in the assumed 

fertility rate.3 The series II projections were accepted 

for the base projections. Projections of the number of 

households and the number of students were also available from the Bureau of the Census.4 It was assumed 

that recent trends in urban population growth would 

continue throughout the projected period.

Fiscal policy. These include a variety of assumptions 

about personal and business taxes, Federal purchases of 

goods and services, Federal transfer payments, grantsin-aid, and subsidies. Federal personal income taxes 

were assumed to be cut in 1979, consistent with the 

Revenue Act of 1978. Further tax cuts were assumed 

for the 1980’s of sufficient magnitude to offset the impact of inflation on the personal tax rate. The tax rate 

on corporate profits was assumed to drop moderately, 

leveling off at 45 percent after 1980. Extimates of contributions for social security programs were based upon 

the expected taxable wage base and the combined employer/employee tax rate. Federal purchases of goods 

and services, excluding compensation, were assumed to 

grow slowly in real terms, increasing at an average of 

slightly less than 2 percent per year. Federal transfer 

payments consist of: (1) Unemployment insurance benefits; (2) social security benefits; (3) Federal civilian employee retirement; (4) railroad retirement; (5) veterans’ 

benefits; (6) hospital and supplementary medical insurance; (7) supplementary security income; and (8) all 

other Federal transfer payments. Projections of each 

category are generally based upon expected inflation, 

changes in the size of client populations, and expected 

real changes in benefits. For this projection series, all 

categories were assumed to maintain the same level of 

real benefits through 1983; after 1983, modest annual 

increases in real benefits were assumed for each. Grantsin-aid to States and localities and subsidies to Federal 

Government enterprises were assumed to continue unchanged in real terms.

Price. While price assumptions do not directly affect 

the determination of real GNP, they do affect the pro-' 

jections in several important ways. First, wage rates 

and interest rates are influenced to a great extent by 

price changes. These in turn affect consumption expenditures and residential investment. Second, price 

changes affect the Federal budget. They enter implicitly into the determination of various expenditure levels, while, on the revenues side, they affect personal 

income taxes because of the progressive tax structure. 

The movement of prices in the future, of course, can 

not be adequately projected. Price assumptions used in 

the projections are judgments that may contain substantial error. For these projections, the inflation rate was 

assumed to be lower than the average rate since 1973, 

but above the average for the 20 years preceding 1968.

Productivity and employment. Private nonfarm productivity was assumed to grow slowly during the projected period; above the average for 1968-77, but below 

that for 1955-68. Very little growth in productivity was 

assumed through 1980. Thereafter, a slow recovery to 

rates of growth typical of the 1960’s was assumed. This 

increase was predicated upon the reversal of some previously depressing factors. Members of the post-World 

War II baby boom will be more experienced as workers during the 1980’s. Also, recent rapid growth in the

3 Current Population Reports, Series P-25, No. 704 (Bureau of the

Census, July 1977 and 1978).

4 Projections of the number of households are from Current Population Reports, Series P-25, No. 607 (Bureau of the Census, July 1977

and 1978). School enrollment participation rates by age group are

drawn from Current Population Reports, Series P-20, No. 278 (Bureau

of the Census, July 1977 and 1978).

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levels of investment in environmental and energy conservation equipment is expected to slow down by 1985, 

allowing a greater proportion of investment funds to 

be spent on more productive plant and equipment.

Aggregate labor force projections were obtained 

from studies made by the BLS Office of Current Employment Analysis.5 Their moderate labor force projection was adopted for the base case, while the higher 

labor force estimate was used for the high employment 

alternative case. From these levels, assumptions were 

then made as to the expected size of the agricultural 

labor force, the Armed Forces and the Federal civilian 

labor force, leaving a residual of private nonfarm labor 

to be employed. The unemployment rate, treated as a 

policy objective in the projections, had a major impact 

on the results. Unemployment rates were selected to 

show a realistic recovery path from the 1975 recession 

to 1980. After recovery, unemployment was assumed 

to achieve a stable long-run rate close to full-employment goals.

The major variables for which explicit assumptions 

were required in the projected years are:

U.S. population 

Urban population 

School enrollment 

Number of households 

Civilian labor force

Unemployment rate 

Military employment 

Federal civilian employment 

Agricultural employment 

Private GNP deflator

Farm equipment purchases 

Farm structures purchases 

Equipment discards 

Structures discards 

Residential structures discards

Statistical discrepancy 

Unemployment insurance contribution rate 

Combined Social Security contribution rate 

OASDI coverag ratio 

3-month government bill rate

3- to 5-year government bond rate 

Federal gasoline tax 

Motor fuel usage 

Federal corporate profits tax rate 

Exports of goods and services

Federal purchases less compensation

Federal transfer payments

Federal grants to State and local governments

Federal subsidies to enterprises 

State and local corporate profits taxes

Transfer payments 

Interest payments 

Subsidies to enterprises

Supply GNP

The first stage in the model sequence is to determine 

what the economy can produce. This occurs in the supply block, which is divided between the private and 

public sectors. These two sectors are defined on a gross 

product originating basis. That is, all income generated 

in the private sector is allocated to that sector regardless of which sector consumes the products. Under this 

definition, the public sector includes only compensation 

paid to Federal, State, and local general government 

employees. All other income is assumed by national income accounting conventions to originate in the private sector. Private production is further distributed 

between farm and nonfarm activities.

The first step in determining private production is to 

arrive at an estimate of the labor input to the process. 

In the original version of the Thurow model, there were 

several behavioral equations specified to determine labor force participation rates for males and females. The 

current version takes the labor force as exogenous. Projections of the labor force by the Office of Current 

Employment Analysis are now included in lieu of the 

original participation rate equations.6 Labor force projections start with population projections made by the 

Bureau of the Census.7 The principal area of uncertainty 

in these projections is the estimate of the labor force 

participation rate for women. The unemployment rate 

of the civilian labor force is set exogenously as a target 

variable. Thus, civilian employment as a count of persons is determined by multiplying the civilian labor 

force by the unemployment rate (equation 1, appendix 

A).

Employment data at the industry level of detail are 

available from the monthly BLS survey of business establishments. This survey is a count of jobs, whereas 

the household survey, which forms the basis for the 

historical time series on the labor force and unemployment rate, is a count of persons. In order to maintain 

consistency between aggregate and industry results, 

equation 2 (appendix A), is used to relate establishment 

based civilian employment to civilian employment on 

a persons basis and the unemployment rate. A major

5The projections of the U.S. labor force are fully detailed in the

article by Howard N. Fullerton and Paul O. Flaim, “Labor Force

Projections to 1990: Three Possible Paths,” Monthly Labor Review,

Dec. 1978, pp. 25-35.

6 Ibid.

7 Current Population Reports, P-25, No. 704.

8 This BLS survey is described in monthly issues of Employment

and Earnings (Bureau of Labor Statistics).

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difference between the two series arises from individuals who hold more than one job, who would be counted 

only once in the household survey but more than once 

in the establishment survey. Other differences between 

the two series have been examined in detail elsewhere.9 

The absolute difference between the two series, termed 

the conversion factor, tends to increase in recovery periods, as the number of persons holding two or more 

jobs increases, and to decline in recessionary periods, 

as the number of these workers declines. The unemployment rate is entered into the equation as an attempt 

to capture this tendency.

State and local government employment per capita 

in education and noneducation (equations 3 and 4) are 

related behaviorally to real purchases of goods and 

services per capita, and to trends in urban population 

growth as a proportion of the total population. Purchases per capita represent the average demand for 

State-provided services. This demand is moderated 

somewhat as the urban population expands due to the 

more efficient delivery of services in urban areas. Federal civilian employment and private farm employment 

are exogenous. Deducting these items from civilian jobs 

yields an estimate of private nonfarm employment in 

equation 5.

Equations 6 and 7 estimate average annual hours 

worked in the farm and nonfarm sectors. In both cases, 

the equations are basically time trends to explain the 

long-term secular movement of these series, with the 

unemployment rate entered to account for variations 

around the trend. In the nonfarm equation, the female 

labor force participation rate has been entered as a proxy 

for recent increases in part-time workers. Traditionally, women entering the labor market have been more 

likely to accept part-time work. The continuation of 

this trend is, however, subject to some question, and 

the female participation rates must be carefully evaluated in the projection period. Multiplying average annual hours by employment in equations 8 and 9 yields 

estimates of total hours worked in the farm and nonfarm sectors. Total hours worked in the two sectors 

are transformed to indexes in equations 10 and 11, and, 

as such, form the labor inputs to the macro model production relationships.

Capital stock series for farm and nonfarm equipment 

and structures are derived by identities 12-15. Stock series are maintained as well for residential structures and 

business inventories (equations 16 and 17). However, 

these two stock series do not enter the production relationships. Stocks are updated by adding current investment to last year’s capital stock and subtracting discards. Five discard series are maintained, all exogenous 

to the model. The resulting fixed business capital series 

are then indexed (equations 18 and 19), and these indexes form the capital input to the macro model production relationships.

The final step in calculating private supply GNP is 

to translate hours worked and capital stocks into a resulting flow of goods and services via a production relationship. Two production functions are currently in 

use in the macro model, one for the farm sector (equation 20) and the other for the private nonfarm sector 

(equation 21). In both cases, the functions allow for capacity utilization (as indicated by the unemployment 

rate), the impact of available labor and capital, and disembodied technical progress in the form of a time trend. 

The capacity utilization term is nonlinear, that is, as 

employment increases relative to the available labor 

force, output per hour also increases, but at a diminishing rate. In the original formulation of these relationships, a measure of embodied technical progress for 

both capital and labor was introduced. Since that time, 

however, it has been found that the equations estimated 

without these terms enjoy a slight statistical superiority.

The final step in estimating supply GNP is to arrive 

at values for gross government product. As was noted 

earlier, the supply concept of government covers, by 

convention, only compensation of employees. Four 

equations are estimated to arrive at compensation for 

Federal military, Federal civilian, State and local education, and State and local noneducation employees 

(equations 22-25). In all four cases, the equations contain terms for the absolute level of employment as well 

as adjustment factors to account for shifts in the pay 

structure over time.

The four government compensation estimates are 

combined with the two private components of GNP to 

arrive at the supply-side estimate of total real GNP 

(equations 26 and 27).

Income flows

Unlike the supply side of the model, the income flows 

are determined in current prices. The income block is 

divided between corporate and personal incomes. The 

corporate sector centers around six equations and two 

identities. First, the gross flow of corporate funds (equation 28), defined as book corporate profits and capital 

consumption allowances, is estimated as a function of 

nominal private GNP, capacity utilization, and the relative movements of output, prices, and labor costs. Corporate capital consumption allowances, with (equation 

29) and without (equation 30) the capital consumption 

adjustment, are related to the fixed stock of business 

capital. Third, Federal corporate profits taxes are determined in equation 31 as a function of corporate profits and the Federal corporate profits tax rate. State and 

local corporate profits taxes are exogenous.

Corporate dividend payments are derived (equatior 

32) as a function of lagged dividend payments, reflecting the importance of precedent on this item, and tc

9 Gloria P. Green, “Comparing Employment Estimates from House

hold and Payroll Surveys,” Monthly Labor Review, Dec. 1969.

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corporate internal funds net of fixed investment expenditures. Inventory valuation adjustments are related in 

equation 33 to price change, changes in real business 

inventories, and to last year’s stock of inventories. A 

dummy variable has been added to reflect the effects 

of the oil price increases not adequately covered in the 

private GNP deflator. Identities 34 and 35 are then 

specified for corporate internal funds and for undistributed corporate profits.

The key to personal income is an identity which expresses personal income as a series of deductions from 

and additions to GNP as depicted below:

Gross national product

Less: Corporate and noncorporate capital

consumption allowances 

Equals: Net national product

Less: Indirect business taxes

Business transfer payments 

Statistical discrepancy

Plus: Subsidies less current surplus of government

enterprises

Equals: National income

Less: Book corporate profits

Social insurance contributions 

Plus: Transfer payments

Net interest 

Consumer interest 

Dividends

Business transfer payments 

Equals: Personal income

Noncorporate capital consumption allowances (equation 36) depend upon the housing stock as the principal explanatory variable. The housing stock multiplied 

by a time trend is used as an additional explanatory 

variable. Determined in real terms, noncorporate consumption allowances are then converted to current dollars with the capital consumption deflator in equation 

37. Federal indirect business taxes (equation 38) are related to private nominal GNP, the Federal tax rate on 

gasoline, projected motor fuel usage, and a dummy variable for the Korean War period. State indirect business 

taxes (equation 39) are related to major State-funded 

expenditures, that is, purchases of goods and services 

and transfer payments less grants-in-aid from the Federal Government. Business transfer payments, the statistical discrepancy, and subsidies to Federal and State 

government enterprises are exogenous.

Federal interest payments are determined in equation 

40 as a function of the 3- to 5-year government bond 

rate, times a proxy for the Federal debt. The proxy is 

constructed from the 1954 value of public issues of marketable bills, bonds, and notes, incremented by the value of the Federal deficit (+ ) or surplus (-) in each succeeding year. State and local interest payments are 

exogenous.

Social insurance contributions are determined by four 

equations and one identity. The major determining variable in three of the equations is compensation adjusted 

for employer contributions for social insurance. Therefore, equation 41 relates the employer share of social 

insurance contributions to total contributions. Following this determination are three equations (equations 

42-44) for the following types of contributions: 1) Unemployment insurance funds, 2) social security funds, 

and 3) all State and local government social insurance 

funds. The unemployment fund contributions are determined as a function of adjusted compensation and 

the exogenous average employer contribution rate for 

this category of social insurance. Social security contributions are related to the adjusted level of compensation, the wage base, social security coverage, and the 

combined employer/employee tax rate. The tax rate 

and coverage ratio are exogenous as is the wage base 

in the historical period. In the projection period, however, attempts have been made to relate the wage base 

to changes in nominal average compensation, lagged 

two periods. State insurance funds are related to adjusted compensation of State employees only. All other contributions to Federal programs, such as Federal 

civilian employee retirement funds, are exogenous. An 

identity is introduced at this point summing the four 

types of contributions to arrive at the total level of social insurance contributions (equation 45).

Interest paid by consumers is determined in equation 

46 by the level of personal income and the yield on 

3-month government bills. Combining all of these items 

in equation 47 yields the estimate for personal income.

Median family income (equation 48) is a function of 

the employment rate, GNP per worker, and the share 

of GNP going to personal income. Federal personal 

taxes depend upon the level of personal income in equation 49. Progressivity is built into the equation by including the average tax rate on median family income. 

State and local personal taxes (equation 50) are a function of personal income, lagged taxes, and a time trend. 

Deducting personal taxes from personal income (equation 51) yields an estimate of disposable personal income. Personal savings are related to the level of disposable income, medium-term interest rates, and the inflation rate in equation 52. Aggregate personal consumption expenditures are determined by identity in 

equation 53.

Demand GNP

There are currently three equations (equations 54-56) 

in the model for personal consumption expenditures. 

The durable goods equation depends upon total personal consumption as an income proxy as well as the 

unemployment rate, last year’s residential investment, 

the change in real disposable income, and a proxy for 

consumer debt burden. Nondurable goods purchases 

are related to total consumption, the debt burden, and

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the unemployment rate. Consumption of services is a 

function of total consumption, the unemployment rate, 

and the stock of residential structures.

There are four equations for investment (equations 

57-60). Nonfarm equipment purchases depend upon private nonfarm GNP, the internal flow of funds available for investment, the existing stock of equipment, and 

the interaction between capacity utilization and profitability as measured by the previous year’s ratio of internal funds to the capital stock. Nonfarm structures 

purchases are related to private nonfarm GNP and last 

year’s investment in structures. Farm purchases of 

equipment and structures are exogenous.

The equation for changes in the stock of business inventories is not formulated to capture short-run fluctuations in inventories. Rather, it represents an attempt 

to estimate desired inventory changes by means of a 

stock-adjustment process, modified to allow for a time 

trend and a nonlinear capacity utilization variable.

Investment in residential structures depends upon the 

number of households, medium-term interest rates, and 

real disposable income per household. This latter variable is included to take account of increasing family 

incomes which are not necessarily reflected on a per 

capita basis.

Imports of goods and services are determined in equation 61 by real incomes, relative prices, lagged imports, 

and a capacity-pressure variable based upon the spread 

between potential and actual GNP. This particular variable has an accelerator impact on imports. That is, as 

the actual/potential GNP ratio moves away from its 

long-run average, the impact on imports increases at an 

increasing rate.

Purchases of goods and services by the Federal Government are determined by identity given in equation

62. Compensation, determined in the supply block, is 

added to exogenous goods purchases to arrive at this 

figure. State and local purchases are determined by 

equations for the education (equation 63) and noneducation (equation 64) sectors. Noneducation purchases 

are related to private GNP, Federal grants-in-aid for 

noneducational uses, and the unemployment rate. Education purchases are determined as a function of private GNP, Federal education grants, and school 

enrollments.

Price/wage sector

As was previously noted, the supply and demand 

blocks of the BLS macro model are determined in constant prices, whereas the income side is expressed in 

current prices. In the original formulation of the model, the movement between real and nominal prices was 

accomplished with a set of exogenously specified deflators. The price/wage sector has been added to insure 

internal consistency between price and wage determination and to determine the rate of inflation within the

model.10

There are two major equations and four identities in 

this sector of Jhe model. The price equation (equation 

65) determines the implicit deflator for private GNP as 

a markup on unit labor costs and crude materials prices. 

The unemployment rate is also included. The percent 

change in private compensation per hour (equation 66) 

is, in turn, a function of private productivity, prices, 

and the unemloyment rate. Equations 67-70 are identities for private compensation per hour, private compensation, unit labor costs, and the spread between price 

change and w'age change. Equations 71-79 are derivations of other deflators as a function of the private GNP 

deflator. Finally, equation 80 is an identity for the total 

GNP deflator as a weighted sum of the various demand 

component deflators.

Balancing the macro model

Summation of the derived real components of demand in equation 81 yields the demand-side estimate of 

GNP. The demand- and supply-side estimates of GNP 

may not agree, and the magnitude of such an imbalance 

is represented by equation 82. A positive sign for the 

gap represents a situation of excess supply, while a 

negative sign indicates excess demand. Although the 

sum of disposable sector incomes necessarily equals the 

supply-side estimate of the GNP, demand for GNP will 

fall short of or exceed the supply of GNP unless the 

total purchases of the various sectors happen to equal 

their combined incomes.

The gap between supply and demand GNP depends 

in part on the government policies incorporated in the 

model. If there is a gap, this implies that the target rate 

of unemployment cannot be achieved with the existing 

fiscal assumptions. Thus, the various policy instruments 

in the model are modified to effect a balance between 

supply and demand. Many combinations of policies are 

possible, and a final choice is made on the basis of many 

considerations that are outside the model.

Solving the macro model

The solution of the model is somewhat different from 

the foregoing discussion of behavioral relationships and 

identities. In order to facilitate solution, equations are 

arranged by block, where equations within a block are 

simultaneous. Initial estimates of the key block results 

are provided and iterative solution techniques are applied to refine the initial solution until the model arrives 

at a consistent solution.

10 Richard C. Barth, “The Development of Wage and Price Relation-collect ships for a Long-Term Econometric Model,” Survey o f

Current Business, Aug. 1972, pp. 15-20.

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Chapter 3. Final Demand

Projections

Gross national product (GNP) is the final output of 

the economy measured from the demand side, or the 

output of the economy distributed among its final users. 

Final users are broadly categorized as persons, businesses, governments, and foreign. Final demand consists of the purchases made by these groups, or the purchases of the demand sectors of GNP. Final demand 

projections involve estimating the future purchases of 

each demand sector, by industry of origin. For the 1990 

projections, the economy was disaggregated into 162 

different industries. These industries define the bills of 

goods, or lists of purchases, prepared for each final demand sector. The output of the macro model provided 

control totals for each final demand sector. The first 

step in projecting distributions of purchases for each 

sector was to develop data series for the purchases each 

made in past years. The years studied were primarily 

years for which the Department of Commerce published input-output studies (1958, 1963, and 1967)" and 

1973, which became the base year of the projections. 

In addition, many data series were available through 

1976, providing recent trends. These historical data 

were used with a variety of techniques and submodels 

to project purchases.

Overview

Final demand projections, or the estimation of purchases within the control totals provided by the macro 

model, in most cases started with the functional levels 

or broader groups of products purchased by each demand sector. These levels were then distributed to each 

of the 162 different industries. Industry purchases were 

then converted from purchasers’ values to producers’ 

values by separating out distribution costs. All purchases 

were then converted to a constant price level.

In the case of personal consumption, expenditures 

were first distributed to 82 major product categories 

using a consumption demand model. For each of these 

82 products, a distribution pattern was used to allocate 

each total to its appropriate producing industries.

In the business or investment sector, four major subsectors were defined: Nonresidential construction, producers’ durable equipment, residential construction, and 

change in business inventories. Investment was treated 

as a function of the level of sales in each industry or 

the ratio of investment to output in each industry. Residential construction was estimated in the macro model. In the case of foreign trade, projections were based 

largely upon historical data. Import and export projections relied heavily on least-squares time trends or 

growth rate extensions with modifications. Special studies were also made of expected import penetration ratios 

and expected demand for exports of selected products.

The Federal Government sector was initially divided into six subsectors while State and local government 

purchases were distributed into 20. The Federal sector 

was split into two defense subsectors and four nondefense subsectors with each of the six bills of goods 

dependent on historical input-output data and other 

government data on industry purchases. The State and 

local government sector was disaggregated to 20 major functions, such as primary education, higher education, health, hospitals, and general government, with 

each of the 20 bills of goods based upon past distributions of purchases and other conditions.

Assumptions

Various assumptions underlie projections of the detailed purchases of the final demand sectors. In general, these assumptions follow the conditions of the scenarios being examined; major changes expected in the 

magnitude and nature of the activities of each demand 

sector; and in some cases, changes in the demand, price, 

and availability of particular products. While assumptions were developed primarily for functional levels of 

demand sectors, such as education or space, they were 

also used for important industry sectors, as in the case 

of energy costs and availability. Prior to making the 

detailed projections of purchases, assumptions for each 

scenario were jointly developed by members of the final demand group.

Major functional areas were considered first. For example, the recent history of health care was examined 

for trends, and various current proposals for change 

were considered. Since the classification of health purchases is different for private and public buyers, the 

extent of increased government participation through 

1990 had to be examined. Since information at the time 

was limited, it was assumed that government participation would increase slightly, but that no comprehensive

11 The Input-Output Structure o f the United States 1958, 1963, and

1967 (U.S. Department of Commerce, Bureau of Economic Analysis).

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national program would be adopted by 1990. Further, 

the extent to which medical purchases would continue 

to be influenced by new technologies had to be considered. Educational purchases, as a total, were assumed 

to vary with fluctuations in the size of the school-age 

population. During the projected period, the size of the 

school-age population will decline, but the post-World 

War II baby boom members will be entering childbearing age. The possibility of the private sector increasing its share of school expenditures, relative to the 

public share, also had to be evaluated. The impact of 

increasing energy costs and shortages on purchases of 

different types of transportation services were also considered, with various assumptions developed dealing 

with investment in mass transit, railroads, and highways. 

Levels of defense and space outlays were based on assumptions made about international conditions and the 

rate of space exploration.

Product purchases were considered in certain cases. 

Purchases of ordnance were based upon assumptions 

about defense replacement requirements and U.S. policies on military sales to foreign governments. Aircraft 

purchases were heavily influenced by defense assumptions, expected foreign military sales, and airline investments. Energy was the principal area where assumptions were made on a product level. In this case, the 

Data Resources, Inc., (DRI) energy model was used 

with the assumptions of the BLS macro model to project total British Thermal Unit (BTU) use by type of 

energy and by domestic or foreign source. These demand figures were used as a check on the output figures derived from the projected energy coefficients. In 

addition to total energy consumption by type, the DRI 

model also provided estimates of the direct use by 

households and governments, affecting the personal 

consumption and Federal and State and local government bills of goods. The prices from the model were 

used to project the coefficients. All of the assumptions 

inherent in the DRI energy model, therefore, became 

those used in the projected BLS energy industries. These 

included such things as price increases for domestic and 

OPEC oil, deregulation of natural gas, and the rate of 

development of nuclear and other sources of electric 

power. In general, these conditions assumed that the 

prices of natural gas and oil would increase more rapidly than the prices of coal and electricity. Coal and 

electricity were assumed to be more readily available 

through 1990.

Personal consumption expenditures

Personal consumption expenditures (PCE) are the 

value of goods and services purchased by individuals 

and nonprofit institutions. Purchases of dwellings are 

not included, although the rental value of owner-occupied dwellings is imputed to consumption outlays. The 

distribution of personal consumption expenditures to 

producing industries was accomplished in two major

steps. After total consumption was determined by the 

BLS macroeconometric model, the first step was to 

project consumption by major type of expenditure, such 

as food, housing, or medical care. There were 82 categories projected, and they were forced to sum to the 

projected consumption controls of the macro model. 

Historical data for each of these categories were available from the Department of Commerce as part of the 

National Income and Product Accounts.12 These data 

were used to develop a set of behavioral equations to 

project the 82 categories. The second step was to distribute these 82 product expenditures to the producing 

industries. This was accomplished with the use of projected bridge tables which distribute each category to 

its component industries as well as to the transportation, insurance, and trade industries. The result was the 

personal consumption expenditure bill of goods, the 

largest component of final demand.

Each historical input-output table produced by the 

Department of Commerce (1958, 1963, and 1967 existed 

for this project)” has an associated bridge table which 

distributes expenditures for the 82 consumption aggregates. Each expenditure item is assigned to one or more 

of the Bureau of Economic Analysis (BEA) industries 

(367 order). The BEA estimates these products for each 

year and benchmarks them to new bridge tables as they 

become available.

Product projections. A consumption submodel was used 

to project the 82 product categories. This model, developed by H. S. Houthakker and L. Taylor consists 

of a set of 82 demand-oriented consumption functions.14 

These equations, which were originally estimated in 

1958 constant dollars from 1929 to 1964, distribute total PCE to major product expenditure categories. Total PCE and the annual change in PCE are primary 

variables used as a proxy for disposable income. PCE 

has a high level of explanatory power in these equations. Relative prices are also used extensively. The lag 

structure of the equations allows changes in explanatory variables to be distributed over time.

For these projections, the model was reestimated in 

1972 dollars from 1929 to 1975. The new equations were 

simulated over the projected period using preliminary 

controls for purchases of durables, nondurables, and 

services from the macro model. Many of the model 

equations produced projections which were inconsistent with past trends. As time and resources permitted, 

additional research was done for these products. Some 

of the alternatives used were growth rates, time polynomials, and variations of other consumption models.

12 Survey of Current Business, July issues, Tables 2.6 and 2.7 (Department of Commerce, Bureau of Economic Analysis).

13 The Input-Output Structure of the United States.

14 H. S. Houthakker and L. D. Taylor, Consumer Demand in the

U.S., Analyses and Projections (Cambridge, Harvard University Press,

1964).

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More specifically, new estimators were generated using 

the BEA data in 1972 dollars through 1975, the latest 

available year at the time, and the model specifications 

published by Houthakker and Taylor. The equations 

used are given in appendix C. Product projections were 

then made using the preliminary macro PCE projections, the assumed population projections series, and 

trend extrapolations of relative price. In addition, the 

original period (1929-64) was used to create estimators, 

and ex post simulations were made from 1965 to 1975. 

There were three measures to evaluate the initial estimates: 1) The statistical fit of the model, 2) the ex post 

simulation results, and 3) the ex ante projections using 

the preliminary controls. The statistical fits varied, but, 

for most products, there were problems of significance 

in some of the parameters. The ex post simulations for 

almost all equations produced directional biases as well 

as errors increasing over time, even with the correct 

lagged consumption value. Ex ante projections proved 

important since some of the better fits and/or ex post 

simulations produced unacceptable conditional projections to 1990.

Finally, the sum of the projected product levels was 

brought into balance with macro consumption totals by 

allocating the difference to categories according to the 

relative change in their value. Twenty-three of the original Houthakker-Taylor equations remained in the solution set. Of those, six were add-factored for various 

reasons. Four estimators were respecifications of the 

Houthakker-Taylor model. Seven products had new 

equations specified with item-specific explanatory variables. Eleven projections came from other government 

or private projections. Twelve of the products had time 

polynomial extrapolators, and five used other extrapolators, such as population and the death rate. Exogenous projections, including growth rate extrapolators, 

accounted for the other 20 projections. Of the 82 projections, 20 involved add factors.

Industry projections. The product expenditure categories were then transformed to a set of final demands 

consistent with the input-output framework. Each of 

these categories was made up of many types of goods, 

produced by different industries. A matrix or bridge 

table was used to transform the product forecasts into 

the 162 industries used in the projections.

A bridge table distributes product aggregates to component goods and services and to margin industries. 

The product projections are expressed in purchasers’ 

values, while the bills of goods are expressed in producers’ values. The difference is the cost added to a 

particular industry’s output in getting that output from 

the point of production to the consumer, including such 

items as transportation costs and wholesale and retail 

trade markups. The bridge table accomplishes two tasks 

at once—it allocates each category or product expenditure to its producing industry, and removes the trade

and transportation margins from the product and allocates them accordingly. Bridge tables were developed 

by the BEA for all input-output years. Thus, at the time 

these projections were prepared, data were available 

for 1958, 1963, and 1967. Each bridge table had been 

prepared in current dollars. For this project, the 1963 

and 1967 tables were reestimated in constant (1972) dollars and further modified in the way imports were handled.15 First, imports were valued at domestic port value instead of foreign port value, decreasing the margin 

entries by the amount of the margins associated with 

transporting the goods between the foreign and domestic ports and increasing the producers’ value by a similar amount. Second, imports were assigned to the relevant domestic industry based on the nature of the 

product. Because of a lack of information, this was not 

possible for three areas: Military food abroad, land travel overseas, and purchases by government employees 

overseas.

A bridge table for 1973 was estimated by the BLS. 

As a first estimate, the relationships from the 1967 bridge 

table were used. Where this method produced results 

inconsistent with other data, changes were made in the 

bridge relationship. Detailed study was made of the relationship between the 1967 bridge table and the 1967 

Census of Manufactures, and like relationships were assumed for 1972. Unpublished shipments data were used 

to extrapolate these relationships to 1973. The difference was scaled back to the industries, and the estimates 

were reevaluated. In cases where the estimates were 

still inconsistent with other data, additional extrapolators were developed.

For the projections, the 1973 bridge table was used 

as an initial estimate of the projected bridge table. Feedback from the final demand-output review identified 

products which were in need of further study. “Food 

on and off premise” required extensive work, changing 

the relationships among industries producing these 

goods. In total, only about 12 of the 82 categories required changes, so the 1973 bridge table was used for 

most of the products in the projected years.

Gross private domestic investment

Gross private domest ivestment (GPDI) is composed 

of fixed investment and the change in business inventories. Fixed investment represents purchases of durable equipment and structures by business and nonprofit 

institutions along with residential investment. Change 

in business inventories represents the value of the increase or decrease in raw materials, semifinished goods, 

and finished goods held by business. In projecting the

15 The OEG treatment of foreign trade was changed in these projections to yield domestic rather than total output. Imports that are

competitive are now subtracted from final demand by industry. Previously, imports were treated as a single, negative value in the export

bill of goods. For more information, see the section of final demand.

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industrial composition of investment demand, four categories were considered: 1) Residential construction, 2) 

nonresidential construction, 3) producers’ durable 

equipment, and 4) change in business inventories. Control totals for each of these categories were derived 

from the BLS macroeconometric model and then allocated to producing industries.

Historical data series for each of the components of 

investment were developed. For residential structures, 

a detailed series from 1958 to 1976 was developed from 

data from the national income accounts. These data 

showed the movement of the detailed types of residential construction, such as single-family homes, multifamily units, and additions and alterations. For nonresidential structures, detailed data from the national income accounts showed expenditures for various types 

of construction, such as religious buildings, telephone 

and telegraph facilities, and farm buildings. In some 

cases, these detailed series had to be disaggregated using factors developed for input-output years to show 

trends for the more detailed types of construction. The 

data were then aggregated to the level of detail used 

in the Economic Growth industry model. These data 

series were developed in both current and constant 

(1972) dollars.

The process for developing the historical equipment 

bill of goods series was more complicated. As part of 

the national income accounts, product expenditures are 

published annually for equipment types, such as tractors, special industry machinery, or general industrial 

equipment. Each of these products can include goods 

produced by more than one industry. They are also expressed in purchasers’ value. As in the case of PCE, 

bridge tables are available to split these product expenditures into producing industries, and to remove the 

margins. The 1963 and 1967 bridge tables prepared by 

BEA were aggregated to Economic Growth industry 

sectors and then inflated to 1972 constant dollars. A 

1973 bridge table was estimated in constant dollars, using the 1967 relationships as a first estimate. For products where information was available, the bridge table 

relationships for a specific product were changed. These 

data were checked for consistency with other estimates 

being made, and revisions were made as necessary. By 

interpolating between the bridge tables to create an annual series of bridge tables, it was possible to convert 

these product data into a time series from 1958 to 1976 

for equipment by producing industry in producers’ 

values.

In addition, capital flows tables were used to provide 

historical data on plant and equipment. A capital flows 

table shows the flows of investment goods to the various industries which purchase them. For each industry, it is possible to examine the types of investment 

goods purchased, and to determine the relative importance of these goods among their total investment purchases. For each good, it is possible to examine the industries which purchase it, and the relative importance 

of each of the industries in making up total purchases. 

Capital flows tables are developed for input-output 

years, and at the time of this study, were available for 

1958, 1963, and 1967, in current dollars. The 1958 table 

was developed by the BLS, while the 1963 and 1967 

tables were developed by the BEA. Some inconsistencies are apparent among the methodologies used to prepare the tables, so the 1958 table was not used in this 

study. The tables were repriced to 1972 constant dollars. Using detailed bills of goods developed for 1973 

along with data on investment by industry, a capital 

flows table for 1973 was estimated in constant dollars 

based on the 1967 table. This table estimates the distribution of purchases of investment goods by each industry in 1973.

Historical data for the inventory change bill of goods 

are available only for the input-output years. Input-output conventions allocate inventory change to the producing industry, no matter which industry holds it. 

However, data available from the national income accounts are on a holder basis, not a producer basis.

There are three major components of residential construction that must be projected: 1) Mobile homes, 2) 

nonfarm residential structures, and 3) farm residential 

structures. Mobile homes, which are allocated to the 

“other transportation equipment” sector, have wholesale and retail trade and rail and truck transportation 

margins associated with them. Farm residential structures are allocated to the “all other new construction” 

sector, while nonfarm residential structures are allocated to “new residential construction.” Associated with 

farm and nonfarm residential structures are brokers’ 

commissions on their sales (allocated to “other real estate”) and net purchases of used structures (allocated 

to the “scrap, used and secondhand goods industry”). 

These sectors are aggregates of the more detailed level of the historical data.

Projected business investment in nonresidential structures was distributed chiefly to “nonresidential buildings,” “public utilities,” “oil and gas well drilling and 

exploration,” and “all other new construction.” There 

are also small purchases of “residential buildings” 

(nurses’ housing) and “mobile homes,” as well as associated margins, and a small purchase of “used 

structures.”

Investment in equipment is allocated to many different manufacturing sectors, as well as to the trade and 

transportation sectors. In some cases, services which 

are capitalized on a firm’s books are also included as 

equipment purchases. Types of equipment range from 

mining, construction, and oilfield machinery to amusement park equipment, computers, and office machinery.

The change in business inventories is very different 

from the other components of investment. There are 

entries, either negative or positive, in almost every industry except construction and services. The relative

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importance of any entry can change greatly from year 

to year. Detailed bills of goods are available only in 

input-output years.

Initial estimates of the projected bills of goods for 

structures were made at the level of the most detailed 

historical data based on past relationships. Data from 

1958 to 1976 were used to project the movement of 

these detailed categories into the future. These individual projections were aggregated and then evaluated 

against the projected controls obtained from the macro 

model. Changes were made as necessary to the detailed 

projections until they added to the control totals. These 

estimates, along with estimates of the other final demand bills of goods, were used to generate initial estimates of output by industry. Capital flows tables, which 

allocate purchases of structures and equipment by type, 

along with investment-output ratios, which relate an 

industry’s investment to its total output, were estimated 

for the projected years based on historical data. The 

projected investment-output ratios, capital flows tables, 

and outputs were used to create a bill of goods for 

structures to be checked for consistency with the initially projected construction vector. Changes were 

made as necessary to get a consistent set of tables, investment-output ratios, and projected bills of goods. 

The use of a capital flows approach allowed changes 

in industry outputs to change the investment of the 

industries.

Investment in equipment, like investment in plant 

construction, is projected by relating it to the output 

of the industries producing goods and services for sale 

to other industries and to final demand. Most industries 

require a wide variety of investment goods, and industries producing investment goods sell equipment to a 

variety of users. As a result, comparing the types of 

investment goods required against the initial estimates 

of equipment types produced is a complex process.

Initially, producers’ durable equipment was projected for detailed industries based on historical trends. As 

in the case of nonresidential structures, these estimates 

were then used to generate initial estimates of output 

by industry. At this point in the projection sequence, 

there was no assurance that the initial estimates of types 

of equipment produced were consistent with the types 

of investment goods required by the generated outputs. 

As with the nonresidential structures component of investment, investment-output ratios and capital flows tables were projected, which, with the generated outputs, 

allowed a check of the consistency of those projections. 

The projected capital flows tables, investment-output 

ratios, and initial bills of goods were adjusted until they 

were consistent. The capital flows table allowed changes 

in industry output to be reflected in the investment bills 

of goods.

Projections of net inventory change by producing 

industry were based primarily on projected industry

outputs. A constant percentage of output for each industry was used as an initial estimate of the bill of goods. 

Industries which had a perishable product were then 

adjusted to be more in line with the past levels. The 

initial projections were modified as necessary in later 

stages in the projection process. Less effort was expended on the allocation of net inventory change to 

the producing industries since this item is relatively unimportant in long-run projections.

Net exports

Net exports represent the value of total exports of 

goods and services less the value of total imports of 

goods and services. Exports and imports are handled 

separately in the input-output system and are netted out 

only at a final stage to present a conceptually consistent level of GNP.

Unlike other sectors of final demand, historical data 

on foreign trade are plentiful and detailed. Instead of 

problems of disaggregation and estimation, foreign trade 

data must be compiled or aggregated into the inputoutput industry sectors. Data on both exports and imports are obtained from the detailed merchandise trade 

statistics published annually by the Bureau of the Census. For exports, this includes Standard Industrial Classification (SIC) product codes and schedule B commodity codes. For imports, data are available by SIC-based 

produce codes and by special U.S. tariff schedule 

(TSUSA) codes. Data requirements after aggregation 

involve modification and augmentation to reflect balance-of-payments and input-output conventions.

Exports are treated as any other component of final 

demand in the input-output system; imports, on the other hand, require a unique treatment. Total imports are 

projected by an equation in the macroeconometric model. This total is then divided into two categories in the 

input-output system. The first category consists of all 

imports of final users, as well as intermediate imports 

which are competitive with domestic products.

In the input-output system, this first category of imports is shown as a negative column of demand; that 

is, subtracted from final demand in order to yield demand for domestic output rather than total output for 

each industry. In previous BLS projections and in the 

published input-output tables of the BEA prior to 1972, 

a different treatment of imports was used. Intermediate 

imports which were competitive with U.S. products 

were transferred to their corresponding domestic industries. Intermediate imports which were not competitive were allocated to the consuming U.S. industry. 

Each type of intermediate import formed a row of coefficients in the input-output table, one called “transferred imports,” the other “directly allocated imports.” 

4.11 final demand imports, whether competitive or noncompetitive, were allocated to each of the final demand 

sectors and appeared only in the cells where each final

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demand column intersected the directly allocated import row. The value of all imports (both types of intermediate plus final demand) was then subtracted from 

the export column of final demand to arrive at a net 

export figure. The result of this method was to yield 

an input-output table reflecting total, not, domestic output, since imports were not subtracted by industry. (See 

The Structure of the U.S. Economy in 1980 and 1985,

BLS Bulletin 1831, for more information on this 

method.)

As an illustration of the treatment in the input-output system of imports not subject to further processing, 

consider the automobile industry. Intermediate and final demand for automobiles includes some share that is 

met by foreign producers. By subtracting the value of 

foreign automobiles from total demand for autos, the 

demand for domestic automobiles is derived. As this is 

done for every industry for which there are competitive imports, the result is a demand for domestic goods 

which, when applied to the coefficients of the inputoutput table, produces estimates of domestic, rather than 

total, output by industry.

The projection of competitive imports by industry is 

mainly based on analysis of existing and expected shares 

of the domestic market. Trade agreements which may 

restrict imports are also taken into account.

The second category of imports encompasses intermediate products that have no domestic substitutes in 

the sense that they cannot be replaced by domestic items 

in existing production processes without altering the 

nature of the product. These imports are directly allocated to the industries which use them in their production processes. Thus, coffee, which is not produced in 

the United States, is directly allocated to the food products industry where it is ground, blended, and packaged 

before being allocated to the personal consumption expenditure category of final demand. Once the intermediate, noncompetitive imports are allocated to the user 

industries, they are transformed into coefficients. The 

coefficients are then projected in much the same way 

as domestic coefficients in the input-output table.

After imports are initially projected, the level of exports is set so as to reach a nearly zero current-dollar 

trade balance in the projected years, an assumption or 

policy target. The value of total exports is in turn distributed by industry, primarily on the basis of time 

trends and expected world conditions. It was necessary 

to rely on naive forecasting techniques to project exports by industry because long-term estimates of foreign income and prices are generally not available.

Aggregate projections. The first estimate of the aggregate level of imports and exports was derived from the 

macroeconometric model. An equation in the model 

projected constant-dollar total imports as a function of 

disposable income, lagged disposable income, relative 

prices, and capacity pressure (measured by the ratio of

actual GNP to potential GNP). Imports were then converted to current dollars, based on the assumption that 

the import deflator would grow from 1976 through 

1990 at the same rate as the private GNP deflator. A 

policy target of a close-to-zero current-dollar trade balance implied that current-dollar exports would be close 

to current-dollar imports. The export deflator was also 

assumed to grow at the same rate as the private GNP 

deflator. By applying the resulting export deflator to 

current-dollar exports, constant-dollar total exports 

were derived. (Although the export and import deflators were projected to grow by the same rate over the 

period 1976 to 1990, the indexes with 1972 as a base 

were different because of differing price rises for exports and imports between 1972 and 1976.)

This first projection of total imports and total exports 

was then distributed among the 162 industries in the 

system. A review of the industry level forecasts revealed that, while import growth rates appeared reasonable in light of past trends, export projections by 

industry appeared unrealistically high for many sectors. 

It did not seem likely that U.S. exports would match 

the high rate of growth of the initial import projections 

in order to yield a roughly equal current-dollar trade 

balance through the 1980’s. It was decided at this point 

to modify the aggregate forecast produced by the macro 

model with a micro analysis of export and import trends 

and conditions. Since the export data base was much 

more extensive than the import base, the micro analysis began with exports.

Industry projections. For most industries, a leastsquares trend was computed from 1963-74 export data 

(or some subset of this data in the case of recent growth 

accelerations or decelerations), and this trend line or 

growth rate was simply carried out to 1980, 1985, and 

1990. Where possible, the resulting export projection 

was modified based on analysis of more current (1975 

and 1976) export statistics or by relying on forecasts 

from other agencies, such as the Department of Agriculture’s (DOA) projections of agricultural exports.16 A 

more detailed description of specific export assumptions 

follows; industries not mentioned were projected based 

strictly on historical trends through 1976.

The projections of food and feed grains exports depended entirely on estimates from DOA. For wheat 

and corn, the chief export components of the food and 

feed grains industry, the long-range forecast showed a 

return to a more normal growth path following the abnormally high export years of 1973 and 1974. Exports 

of other agricultural products, chiefly soybeans and 

meat products, also followed levels projected by DOA. 

The soybean industry showed only small increases 

through the 1980’s.

16 The projection model of the Economic Research Service was run

using the BLS macro assumptions to estimate rates of change in export levels for particular products.

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Coal exports were assumed to rise slightly in the next 

decade, despite recent declines. This projected turnaround was based on the assumption that total U.S. coal 

production would rise because of energy demands, and, 

as output picked up, so would exports.

Ordnance and complete guided missile exports consist mainly of military sales. These projections were 

based on analysis of expected U.S. policy on military 

sales contracts over the coming decade.

The “rest of the world” industry is the last for which 

a specific export assumption was made. In the export 

bill of goods, the rest of the world industry represents 

receipts of income on U.S. assets abroad (about 75 percent of total rest of world payments in 1973), travel in 

the United States by foreigners (about 23 percent), and 

some small miscellaneous items such as charity donations (about 2 percent). The investment portion was 

projected by an equation based on 1960-73 constantdollar GNP. The travel portion was projected based 

on personal consumption forecasts.

After this micro analysis, total constant-dollar exports 

were summed for the years 1980, 1985, and 1990, converted to current dollars, and equated to imports. Imports were then deflated into constant dollars, and a 

new distribution of this import control total was developed. Like exports, import projections at the industry 

level were based mainly on past trends, except for those 

industries discussed below.

Imports of the forestry and fishery products category were projected to decline by the DOA due to the 

new 200-mile U.S. fishing boundary. However, these 

projections were modified somewhat to make the decline less severe.

Crude petroleum imports were projected using a ratio 

of imported crude petroleum to total crude consumed, 

which was developed by DRI. This ratio was applied 

to the projection of total crude petroleum imports to 

slow dramatically between 1977 and 1980, and to petroleum imports to slow dramatically between 1977 and 

1980, and rise only slightly through the 1990’s. This 

slowdown was based on an assumption that the United 

States will be able to develop new domestic energy 

supplies, including more production of oil from Alaska. 

Imports of natural gas and refined petroleum were projected by the same method applied to crude petroleum.

Apparel import projections assumed a slight increase 

in the ratio of imports to total output.

Projections of tire imports were based on the expectation that imports would account for an increasing 

share of total tire output, but that the import share 

would not grow as rapidly as it did between 1967 and 

1973.

Imports of miscellaneous rubber products consist 

mainly of rubber and plastic footwear. The projections 

for this industry reflect recent orderly marketing agreements with Taiwan and South Korea, the chief exporters of rubber and plastic footwear, to limit the number

of shoes imported into the United States. The agreements will remain in effect until 1981 and will cause 

imports of miscellaneous rubber products to drop 

sharply.

Leather footwear imports, on the other hand, are not 

yet subject to any restrictive trade agreement. It was 

assumed, however, that the import share of total leather 

goods output would not grow as rapidly as in the past.

Typewriter imports, too, were projected on the basis of a slowly rising market share in contrast to rapid 

market gains during the 1960’s and 1970’s. Imports were 

expected to hold about a 30-percent share of total typewriter and office equipment output throughout the 

1980’s, about as much as in 1973.

A trade agreement with Japan was recently concluded to limit the number of color television sets imported from that country. This agreement, however, 

had little impact on the aggregate import projections 

of the radio/television industry because of the small 

share (about 10 percent in 1973) of this industry’s total 

output that consists of Japanese color television sets. 

Balancing this import restriction was an assumption of 

continued growth in video tape recorder imports. Overall, a constant import share of about 30 percent of total radio and television output was assumed to hold 

through the 1980’s.

The projection of auto imports was also based on a 

constant market share assumption. For motorcycle imports, however, the market share was assumed to rise 

slightly, from 53 percent in 1973 to 63 percent by 1990.

The projection of directly allocated imports was 

based on several explicit assumptions. Noncompetitive, 

intermediate products (about 37 percent of total directly allocated imports in 1973) were assumed to represent 

a declining share of all imports, based on past trends. 

Land travel abroad (28 percent of all directly allocated 

imports in 1973) was projected as a function of income, 

lagged income, and relative prices. The projections of 

defense and nondefense purchases abroad (17 percent 

and 0.4 percent, respectively, of all directly allocated 

imports in 1973) assumed a reduction in troop strength 

abroad through 1980 to a level which will be stable 

through the decade. Nondefense expenditures abroad 

were assumed to hold steady at the 1973 level through 

1990. Government personnel consumption expenditures 

abroad (in 1973, 8 percent of directly allocated imports) 

were projected as a function of income and relative 

prices. It was assumed that current levels of civilian 

government personnel abroad would not change. Imports from the rest of the world industry are payments 

on foreign investment in the United States. A regression equation based on 1960-73 current-dollar GNP was 

used to project this industry.

After individual industry imports were projected, 

they were summed, converted to current dollars, and 

compared to total current dollar exports. The micro 

projections for both imports and exports were reviewed

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and modified several times before the targeted current 

dollar trade balance was attained. Informal feedbacks 

to the macro level projections ensured consistency at 

all levels of the projections.

State and local government

State and local government demand is defined as the 

purchases of goods and services by all State and local 

government units. Purchases include the compensation 

paid to State and local government employees as well 

as all purchases of goods and services. Purchases of 

these units are less than total expenditures, which also 

include transfer payments to persons, such as welfare 

benefits and interest and subsidy payments. State and 

local government purchases are separated by type of 

function for analytical purposes. Major categories are 

education, health, welfare and sanitation, public safety, 

and all other. Each of these functional categories are 

further distributed to a total of 20 different sublevels. 

Each of the 20 is further divided into employment, 

compensation, construction, and an all other purchases 

category.

The projection of State and local government purchases starts with overall control totals generated by 

the macroeconomic model. Next, a State and local government submodel is used to project expenditures for 3 

types of education and for 14 other functions.17 Historical data for 20 functions are maintained by BEA for 

compensation, construction, and all other purchases. 

These are separately projected based upon trends and 

special analyses. The results of these 3 systems are then 

compared and reconciled to provide acceptable levels 

for the 20 separate State and local functions. Each of 

the projected functional levels is allocated to individual industries.

The macroeconomic model estimates of projected 

State and local government purchases are consistent 

with all macro assumptions and estimates, including 

grants-in-aid. This model provides a purchase total for 

each projected year, with subtotals for education and 

for all other functions as a group. Both of these categories are also divided into compensation and all other 

purchases.

The State and local government submodel predicts 

expenditures and employment in current dollars for 17 

functions. These functions, estimated from census data 

by fiscal year, include: Elementary and secondary education, higher education, other education, highways, 

health and hospitals, sewerage, water utilities, other 

utilities, natural resources, police, fire, sanitation, public welfare, local parks and recreation, general control, 

financial administration, and other general expenditures. 

The model structure was based upon data for the years 

1961-71 but has since been updated to 1976. Equations 

for each function were estimated for general expenditures, capital expenditures, and employment. Expenditures in the model are in current dollars and apply to

all outlays, not just purchases of goods and services. 

Employment is in full-time equivalent units. The model is driven by four major groups of variables: Growth 

in personal income; demographic data; grants-in-aid; 

and an all other category that includes interest rates, 

prices, and unemployment rates.

Commerce Department data provide the primary basis for projecting functional State and local government 

purchases. Purchase data are available annually that can 

be compiled into 20 different functions. These include 

four educational functions: Elementary and secondary 

education, higher education, libraries, and other education. There are five health, welfare, and sanitation functions: Health, hospitals, sewers, sanitation, and welfare. 

Three functions are included in safety: Police, fire, and 

corrections. Other functions include: General government, highways, natural resources, parks and recreation, water and air terminals, public housing, public 

utilities, and other enterprises. These functional categories were initially projected based upon historical trends 

and expected changes.

The next step in the projections procedure was to 

reconcile the results of the macro model, the submodel, 

and the projections of the functional BEA data base. 

In order to make the results of the submodel comparable with the BEA functional series, several adjustments 

had to be made. First, the results of the submodel were 

deflated to a 1972-dollar base and converted to a calendar-year format. Next, where possible, model functions were made compatible with the data series on 

functions by estimating what the proportion of a function (such as corrections or libraries) was to the larger, 

more inclusive, model function. Model expenditures included outlays for more than purchases of goods and 

services and had to be adjusted. Where compatibility 

was obtained, model results were used. Other functions, 

such as other sectors and public housing, where the 

submodel did not provide estimates, were simply extrapolated from the BEA data series. Employment projections from the submodel were converted to compensation and converted to the desired format. Compensation was also adjusted to agree with the macro model 

controls. Construction purchases were obtained by estimating the proportion of capital expenditures that were 

equal to new and used construction purchases by function. The results were then extrapolated toward the 

projection years. As with total purchases and compensation, construction purchases were converted to constant dollars and calendar years. Ultimately, control totals were determined for the 20 functions for compensation, construction, and other purchases which were 

compatible with the controls provided by the macro 

model for education and noneducation.

17 Terry Morlan, “An Application of Micro Data for Forecasting

Aggregate State and Local Government Expenditures and Employment,” Small Area Statistics Paper, GE-41, No. 3 (Bureau of the Cen ­

sus, Aug. 1976), pp. 35-45.

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These levels of functional purchases were distributed 

to the purchases projected to be made from 162 different industries. This was accomplished by projecting 

base-period purchases for each function. Detailed purchase data by function were obtained from BEA worksheets fro 1963 and 1967. Estimates for 1973 were developed using a variety of analytical techniques. These 

years provided a limited basis for projecting detailed 

industry purchases. The projections of purchases for 

each function were then examined by annual rate of 

change and changes in the distribution pattern by industry. Where changes in a projected year seemed extreme, the projections were reexamined and revised if 

necessary.

Federal Government

The Federal sector consists of purchases of goods 

and services and of compensation paid by the Federal 

Government. Purchases are a major part of total Federal expenditures, which also include grants, transfers, 

and net interest. In the National Income and Product 

Accounts, the Federal sector is divided into the major 

components of defense and nondefense, which are further split into purchases of goods and services and compensation of military and civilian employees, all in current dollars. In constant dollars, however, only purchases of goods and services and compensation for the 

Federal sector in total are available. For these projections, the defense sector was disaggregated to two subsectors: Defense nuclear activities and other defense 

purchases. In addition, foreign military sales were examined and projected jointly with the foreign trade analyst. The nondefense sector was disaggregated into 

four subsectors: Nondefense nuclear activities, National Aeronautics and Space Administration, veterans hospital medical care, and other nondefense purchases.

Federal purchases were projected on the basis of historical purchase patterns, expected changes, and assumptions and expectations of government priorities in 

the future periods. Principal data sources were the Department of Commerce input-output studies and various unpublished records of agency purchases. Employment data were obtained from Civil Service Commission reports, BLS data, and the U.S. Budget appendixes. 

Construction data were obtained from a Department of 

Commerce series. As with other sectors, projected levels of total purchases were derived from the macro 

model. These were first broken down by functional activities, and then projected to industry purchases.

The macro model levels of projected Federal purchases are established exogenously in the process of 

balancing supply and demand GNP. This model provides values for total purchases, total compensation of 

military and civilian employees, and the number of civilian and military employees. The levels are established 

jointly by the analysts working in the macro and final 

demand areas to insure levels consistent with overall 

projections assumptions. Assumptions are of major importance in the Federal sector since, in many cases, past 

experience is not useful for projection. For example, 

the projections always assume peaceful conditions without international tensions. A contrary assumption of 

war would result in unpredictably larger Federal purchases and a much larger defense share. In these projections, defense was assumed to grow less rapidly than 

GNP, as was the nondefense sector.

Regression equations were used to derive the total 

purchases of the six subfunctions. These were modified 

based upon expected program levels in the case of defense and space. The six subfunctions were modified 

until they came to the established macro totals. Real 

compensation was also derived for each subfunction using regression equations. Historical data for defense and 

nondefense new construction from 1952-76 were used 

to derive regression equations to project purchases from 

the six new construction industries for each major component of the Federal sector; these two values were 

then allocated to the six subfunctions based on historical trends.

Purchases, excluding compensation and new construction, for each of the six subsectors were then distributed to the industries which composed the remainder of the economy. These distributions were made 

largely on the basis of historical data. Historical bills of 

goods were available for certain years for the defense, 

space, and nondefense sectors. These were examined 

for trend changes and for purchasing patterns in years 

with conditions similar to those assumed for the projected years. Industry data for recent years, available 

from the Bureau of the Census, were of particular importance. From available data, a base-1973 bill of goods 

was constructed for each of the six subfunctions.

In order to insure consistency of the data base with 

the projections, it was necessary to incorporate both 

the benchmark changes that became available since the 

last projections and the conversions to 1972 deflators 

from 1958 deflators. The 1967 input-output table was 

available on a rebenchmarked basis along with a description of the conceptual and statistical changes that 

were made. These two sources were used to rebenchmark the 1963 table and to insure that the 1973 table 

reflected the revised National Income and Product Accounts. All past tables were converted to 1972 dollars. 

Consistency in purchase data required that data after 

1972, which were published on a new SIC basis, be adjusted to a 1967 SIC basis.

Data for recent years from the Bureau of the Census 

and agency records provided recent trends. Trend data 

were modified based upon expected program changes,

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particularly for defense and space. Bills of goods were 

projected for each of the six subfunctions in 1972 dollars, based upon trends and expected program changes. 

Projected imports for the defense and nondefense sectors were shifted to the foreign trade bills of goods.

Since most of the historical defense data bases included foreign military sales, these were projected separately. Foreign military sales were assumed to rise slowly 

to 1980, and then level off in constant dollars. These 

sales were transferred to the export bill of goods.

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Chapter 4. Intermediate

Demand Projections

After final demand purchases are projected, the intermediate demand, or the additional output of each industry that is required to support the projected final 

demands, is calculated using interindustry models. 

These models provide the framework for projecting 

gross industry outputs, or the total of final and intermediate sales required of each industry. The following 

section describes the interindustry, or input-output, system used in computing the projected outputs for 1980, 

1985, and 1990.

An input-output transactions table is a rectangular 

matrix in which the entries represent the transactions 

of each sector with all other sectors. Each row of the 

matrix shows the sales of the producing industry’s output to every consuming industry, including itself, and 

final demand. The sum of all the entries in a row gives 

the industry’s output. Each column of the matrix shows 

the input to the consuming industry from each industry, including itself, necessary to produce its output. 

The sum of the purchased input plus value added (returns to capital, labor, and entrepreneurial ability) equals 

the output of the industry.

Industry classification

Two benchmark input-output studies of the BEA 

were used for this set of projected tables. Both the 1963 

and the 1967 BEA tables were available with 367 separate industries. The industries in the SIC manual which 

are contained within a sector may vary due to differences between the 1957 and the 1967 SIC, but this does 

not affect the comparability of the two tables. The 162- 

order tables used by BLS for the projections were aggregated from BEA’s 367-order industry tables. The 

current-dollar tables were aggregated directly from 

BEA’s tables, while the constant-dollar tables were repriced at the 367-order level and then aggregated into 

the 162 industry tables. The SIC content of the 162-order industry sectoring plan used in the projections was 

based on the 1967 interindustry classifications system. 

The relationship between SIC and the Economic 

Growth industry sectors is given in appendix G.

Industry conventions of the input-output

The 1963 and 1967 benchmark input-output studies 

followed essentially the same definitions and conventions, so the following description is applicable to both 

years. In the input-output industry classification system,

there are three industries which do not actually exist. 

These industries, called dummy industries, are included to simplify the treatment of certain product flows. 

Output of these dummy industries represents an aggregation of commodities or services which are produced 

in other industries. Generally, the information available 

on the consumption of these commodities is for total 

consumption only, so the products are treated as being 

sold to the dummy industries, which are assumed to 

sell them to the consuming industries. One such dummy 

industry is Economic Growth (EG) sector 157, “office 

supplies,” which buys office supplies from the producing 

industries and then sells them to the consuming industries. The other two dummy industries which perform 

similar functions are “business, travel, entertainment, 

and gifts” (EG industry 156), and “scrap, used and second-hand goods” (EG industry 158). Purchases from 

the dummy industries generate employment or output 

in the industries which actually produce the products 

and services, rather than in the dummy industries.

In addition to being a dummy industry, the scrap industry presents a special problem. An increase in scrap 

demand would, by virtue of the nature of the inputoutput model, generate output in other industries to 

produce the scrap. To eliminate this problem, and to 

make scrap generation a function of output, BEA adopted, and BLS followed, the following procedure: The 

scrap industry is dropped from the table by adding the 

scrap industry column entries to the diagonal cell of 

the industry actually generating the scrap. In addition, 

the scrap row, i.e., the input of scrap, is deleted from 

the matrix. This creates an imbalance in the column 

sum since the scrap input and output are rarely, if ever, 

equal for any one industry. To correct this, another 

row, entitled scrap and byproduct adjustment, is added 

which is precisely the negative of the imbalance.

Economic Growth industry 160, “rest of the world,” 

is modified to exclude travel receipts from foreign visitors and personal remittances, in kind to foreigners. 

This adjustment affects the industry detail of final demand in the personal consumption expenditures and export categories.

The two government sectors, State and local and 

Federal, are classified into two major categories, government enterprises and general government. All Federal, State, and local enterprises, i.e., agencies deriving 

50 percent or more of their revenue from sales to the

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public, are included in EG industries 150 through 154, 

along with their respective employment and total receipts. EG industry 151, Commodity Credit Corporation (CCC), is modified by adding all of its intermediate inputs to the nondefense Federal Government final 

demand category. The employment associated with the 

CCC and the employment involved with general government activities, such as teaching or administration, 

at both the Federal and State level, are included in EG 

industry 159, “general government industry.”

EG industry 155, “directly allocated imports,” covers U.S. payments to foreigners for merchandise, services, and factors of production. Items classified in this 

industry have no equivalent domestic products or are 

consumed in final demand. The service of domestics is 

classified in EG industry 161, “households.”

In one respect, the input-output data developed by 

BLS differ from the benchmark input-output studies of 

BEA. The change from a total output base to a domestic output base resulted in changes in the methodology 

for intermediate demand as well as in final demand. 

This difference required two changes in the transactions data of the interindustry matrix, both of which 

involved transferred imports. The transferred imports 

industry was deleted from the transactions table and, 

instead, incorporated into the final demand estimates. 

Since the input-output data are valued in producers’ 

prices, the margins on the transferred imports had to 

be subtracted from the trade and transportation industries transactions and included in the final demand 

purchases.

Valuation of transactions

Input-output relationships may be expressed either in 

producers’ value or in purchasers’ value. In other words, 

the inputs for making a product can be valued at the 

price received by the producer or the price paid by the 

purchaser. Both the BEA and BLS tables value inputs 

purchased by a consuming industry at the price the 

producer receives. Trade margins and transportation 

costs associated with these inputs appear as direct purchases by the consuming industry from the trade and 

transportation industries. The purchase price for an item 

is still contained within the matrix, but the demand is 

divided into components which are purchased 

separately.

Since the input-output table is in producers’ value, 

all trade and transportation margins must be stated as 

demand on these sectors in the final demand estimates. 

In the estimates of final demand, margins are separated 

from the estimates of purchases of goods and services. 

These estimated margins are aggregated to be used as 

the final demand estimates for the trade and transportation industries. Margin ratios associated with each 

transaction and final demand category were developed 

by BEA as part of the input-output studies. This information was used to convert final demand expenditures 

in purchasers’ value into producers’ value for the years 

covered by these projections.

If the input-output table were stated in purchasers’ 

value, the connection between producing and consuming industries would be lost. In a purchasers’ value table, the trade sectors would purchase most products 

from the producing industries and sell these products 

to the consuming industries. In producers’ value, the 

materials or services can be sold directly to the consuming industry. This method also has the added advantage of showing the relationships between the producing industry and final demand categories on a comparable (producers’ value) basis. Using a producers’ value system eliminates the sale of products to the trade 

sectors. The output of these trade sectors is, as a consequence, measured in terms of total margins, i.e., operating expenses plus profit.

/

Secondary product transfers

The transactions recorded in an input-output table 

are based on data contained in the Census of Manufactures, the transportation census, and other economic 

censuses. The Bureau of the Census assigns establishments to an industry based on the industry’s primary 

output, that is, those products or services which produce the largest portion of its revenue. However, in 

addition to primary products, many establishments also 

produce other products which are different from the 

primary output, called secondary products (or services).

Input-output work would be simplified if all output 

of a given product or service were sold by a single industry. To accomplish the same thing, an artificial sale, 

called a transfer, is introduced into the input-output table; the industry which produces the output as a secondary product is shown as selling it to the industry 

which produces it as a primary product. In this process, the output of the primary product industry is increased by the amount of this transfer since it becomes 

an input, albeit an artificial input. For example, electric 

power is produced in the “electric utility industry,” EG 

industry 126, (the primary industry) and EG industries 

152 and 154, “other Federal enterprises” and “other 

State and local government.” In this situation, the electric power output of Federal Government and State 

and local government power plants is transferred to the 

private electric utility industry for distribution to the 

consuming industries and final demand sectors. In this 

way, the final demand for a product generates production in both the primary producing industry and in the 

industries where the product is secondary.

This transfer approach is used to distribute the output of a number of industries. Three industries in the 

table, the dummy industries, receive all of their output 

as transfers from the producing industries. A table is 

compiled, based on BEA’s data, which details the transfers from one industry to another.

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An alternative treatment of transfers is used when 

secondary production is large and inherently different 

from the primary output of an industry, such as bakery 

products produced by small retail establishments. In 

these instances, the industries are redefined; the secondary products and their associated inputs are removed 

permanently from the producing industries and assigned 

to the primary industries. Therefore, the various goods, 

services, and value-added components used to produce 

the baked goods and the resulting output of those items 

are taken from the trade sector and placed in the food 

industry. Primary examples of the use of this alternative are the redefinition of trade margin output out of 

all industries other than trade, and the redefinition of 

service activities, especially auto repair, out of trade.

BLS input-output system

The projections of the Office of Economic Growth 

for 1990 involved nine sets of input-output tables: Six 

sets of historical tables for 1963, 1967, and 1973; and 

three sets of projected tables for 1980, 1985, and 1990. 

The historical tables were done in both current and 

1972 constant dollars, while the projected tables were 

done only in 1972 dollars. The projections are done in 

constant prices so that changes in output, demand, or 

input-output coefficients represent changes in quantities. This use of base-year prices does not ignore changes 

in relative prices because such changes are implicit in 

projections of input-output relationships. The substitution of one material for another, due to relative price 

change, may affect input-output coefficients in the same 

way as technological change.

There are three sets of constant-dollar historical tables, two of which are for years that have input-output 

tables developed by the Bureau of Economic Analysis. 

For those 2 years (1963 and 1967), the BEA 367-order 

tables were repriced and then aggregated to form the 

BLS tables.

Repricing the BEA tables required several steps to 

deflate each of the different parts of the tables. First, 

the transaction values were summed to obtain output 

for an industry. The outputs were deflated using unpublished 4-digit industry deflators that were developed 

as part of the gross product originating data. Transfers 

were repriced using the output deflator of the primary 

producing industry. The transfers and sales to consumption and investment were subtracted from total output 

in both current and constant dollars. Then an implicit 

deflator was constructed to reprice the intermediate 

sales and the other types of final demand. A deflated 

transactions value was then computed by adding the 

deflated components—direct sales, transfers, margins, 

and transferred imports. This repriced table was then 

aggregated to form a 162-sector table, with adjustments 

made to eliminate secondary product transfers between 

the input-output sectors being collapsed into one 

industry.

For the 1973 historical tables, BEA’s 1967 table was 

updated to the latest year for which reasonably complete data were available, and then repriced into 1972 

dollars. Developing the 1973 tables allowed for incorporation of recent structural changes which provided 

a better basis for projecting.

When an updated input-output table is developed for 

a nonbenchmark year, such as 1973, only part of the 

necessary data are available. Output levels by industry 

were estimated from Bureau of the Census data and 

other sources. These industry outputs were adjusted for 

secondary product transfers to be consistent with input-output conventions and deflated to 1972 prices. Final demand and price data were taken from Department of Commerce estimates, published annually in the 

July issue of the Survey of Current Business. Final demands were deflated and translated into industry demands. All of these data were then converted from purchasers’ to producers’ value with some adjustments for 

changing trade, transportation, and insurance margins. 

Developing an input-output table for a nonbenchmark 

historical year (or a year that does not have a complete 

set of economic censuses) is a problem of assembling 

and restructuring existing data into proper form, although estimating techniques must also be used.

The first step in developing the 1973 set of input-output tables was to estimate output and final demand for 

each industry. The existing data required a number of 

adjustments due to input-output conventions and the 

need to state input-output data in base-year prices. The 

1967 BEA 367-order table was updated by scaling the 

transaction values by the ratio of the industry’s 1973 

current-dollar output to its 1967 current-dollar output. 

Secondary product transfers were scaled by the output 

ratio of their primary industry. The scaling of the 1967 

current-dollar table yielded a first approximation of the 

1973-current dollar table. The 1973 367-order table was 

then deflated to 1972 dollars, using the same procedure 

used to deflate the 1967 BEA table. Both current- and 

constant-dollar 1973 tables were then aggregated to 162 

order.

The aggregated constant-dollar transactions table was 

divided by the independent output estimates to create 

a coefficients matrix. These direct coefficients were replaced by the independently updated estimates for 1973, 

where such estimates had been made. Estimates of 1973 

coefficients were developed using the methods described in the section on projecting coefficients. This 

updated coefficients matrix was then used to compute 

industry outputs using the Gauss-Seidel method.

The derived output, which had been computed from 

the updated coefficients matrix, was compared to the 

independent estimates of output. In this comparison, a 

difference of plus or minus 2 percent was accepted 

while larger differences were analyzed. During this 

process, problems were uncovered in virtually every 

area; final demand, deflators, output, and coefficients

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were each found to contribute to the difference in the 

measures of output. Changes in the transportation and 

trade margins that had occurred since the 1967 table 

was constructed, but had not been captured in the initial estimates for 1973, caused differences in the output 

measures.

Whenever a number of changes were made to the 

underlying data, outputs were recomputed and the analysis of output differences was redone. If the appropriate changes had been made, the total gaps, on the average, became progressively smaller, and many individual gaps were eliminated.

When time, resources, and/or data were exhausted, 

a number of industries remained where the derived output deviated by more than plus or minus 2 percent from 

the independently estimated value of output. At this 

point, an estimate was made of value added by industry, or the difference between real output and the sum 

of purchases of material and services inputs, in real 

terms. By the nature of the input-output system, total 

derived value added will always equal total final demand. Further, the procedure used by BLS in estimating the intermediate matrix and outputs is almost the 

same as the double deflation procedure used in estimating the gross product originating by industry in the 

Bureau of Economic Analysis. Thus a rough reconciliation of value added and GNP originating by industry 

could be made. This could be done only at very aggregative levels, so only a few, rather large, adjustments 

were made as a result of this analysis.

In order to insure that the intermediate demand yielded by the coefficients matrix is equal to the difference 

between output and final demand, a balancing procedure is used. This is an iterative procedure, known as 

RAS, which will balance the transactions matrix while 

independently estimated data are held constant.

If this scaling procedure is done accurately, the system will be in balance, i.e.:

X - Y = AX = T,

where X is an n by 1 vector of domestic outputs, 

where Y is an n by 1 vector of final demands, 

where A is an n by n matrix of direct coefficients, 

where T is an n by 1 vector representing the row sums of

the intermediate transaction matrix.

Projecting coefficients

The need to project input-output coefficients arises 

because of changes that that have taken place or are 

expected to take place in these coefficients. Technological change is one of the important factors underlying 

changes in coefficients from period to period. Other 

factors, such as a change in product mix or prices, can 

also cause significant changes in coefficients. Productmix problems are inherent in a system that uses fixed

classifications and aggregative industry groups. In dividing the U.S. economy into 162 sectors, broad industry groupings are created which are usually combinations of 4-digit SIC industries. These large sectors include different commodities and services, each of which 

has its own set of input requirements. If the production 

of the various commodities changes at different rates, 

thereby changing the product mix of the sector’s output, then the total input coefficients of the sector may 

also change. This can occur even if there are no technological changes in the producing industries.

Industry coefficients were projected as part of an input-output system which consisted of four interrelated 

parts: 1) The matrix of intermediate interindustry transactions, which are converted to direct coefficients; 2) 

the set of value added by industry; 3) the set of industry final demands; and 4) the set of industry outputs. 

Each part is dependent on the others, and all the parts 

must be mutually consistent. Certain coefficients may 

be projected independently, but the overall projection 

of coefficients must be made in conjunction with the 

projection of industry final demands.

When projecting input-output tables, all the problems 

involved in updating a matrix exist as well as the need 

to project changes. Industry structures, growth rates, 

and production processes may change due to factors 

unforeseen or imperfectly understood. Development of 

an input-output system for a projected year requires 

estimating all parts of the system and the integration of 

those parts into a balanced system.

The projection of input-output coefficients involved 

four different techniques. The coefficients for the energy sectors (EG industries 11, 60, 126, and 127) were 

projected using a logit share model. A reweighting 

technique was used to project the six construction industries’ coefficients. Other industry coefficients were 

projected using specific data changes for selected coefficients. The fourth method of coefficient projection 

was a general technique which focused on interindustry relationships with the added objective of achieving 

a balanced system.

The projection of the energy coefficients was based 

on the assumption that the different energy products 

(coal, refined petroleum, natural gas, and electricity) 

could be substituted for each other in the majority of 

end-use applications. It was also assumed that the distribution of constant-dollar energy input-output coefficients would be influenced by projected changes in current-dollar energy costs after an adjustment for existing 

stocks of energy-using equipment that could not be converted to alternative fuels. The total energy input into 

each manufacturing sector was defined as the sum of 

the coal, refined petroleum, natural gas, and electricity 

coefficients. This total energy input was distributed to 

alternative fuels for the projected years based upon assumptions about future energy prices. (The price assumptions for this set of projections were discussed in

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the assumption section of the methodology.) This distribution technique used price elasticities estimated from 

a pooled cross-sectional time series data base.

Energy data were obtained from the Fuels and Electric Energy Consumed tables of the 1963 and 1972 Census of Manufactures, and the 1974 Annual Survey of Manufactures. Quantity and price data were available for 

the manufacturing industries, by State. These data were 

distributed to the corresponding Economic Growth industries and converted to BTU’s. The following regressions were then run for each industry:

Q gas / P gas \

Q coal \ P coal, time f

Q coal _ / P coal \

Q elec \ Pelec, timej

Q oil - / Poil \

Q coal l P coal, time I

where Q = quantity 

and P = price.

The resulting equations were used in conjunction 

with energy prices projected by DRI, to project the 

quantity ratios to 1980, 1985, and 1990. The ratios obtained were converted from logarithms and used to project the share of total fuel, in ratio form, that was to 

be provided by each of the four energy sectors. These 

data were developed for each manufacturing industry, 

in each of the projected years. The following equations 

were used:

i / fi , / Q gas Q coal V / Q oil Q coal V Q coal1_TF

1 l \Q coal Q elec / \Q coal Q elec / QelecJ

Share of electricity

TE X = TC Share of coal

TC X = TO Share of oil Q coal

TC X“Qcoai = TG Share of gas

The resulting shares for the years 1980, 1985, and 

1990 were used to distribute the summed energy coefficients. A subsequent adjustment was made to reflect 

the necessary adjustment of the existing capital stocks. 

With the demand figures from the DRI energy model 

used as a control, the individual coefficients were adjusted to reflect changes in the total (summed) energy 

coefficients.

In the projection of the construction industry coefficients, the method used was an attempt to adjust the 

input coefficients for projected changes in the product 

mix of the industries. The six new construction industries were further subdivided into 32 types of structures 

purchased by final demand. This investment in structures was projected as part of final demand purchases. 

The types of structures purchased determined the product mix of the new construction industries, since their 

entire output was sold to final demand. Shifts in the 

product mix of the six construction industries were revealed in changes in the purchases of different types of 

structures. Using the output of a type of structure relative to the output of its construction industry, weights 

were constructed which were used to aggregate the 

1967 input coefficients for the six construction industries. This weighting was done for each projected year, 

generating different industry coefficients as the distribution of investment by final demand varied.

Other industries were projected using the changes in 

the coefficients between 1963, 1967, and 1973. The 

changes that occurred were analyzed to determine the 

cause of the change. Possible reasons for changes in 

coefficients included changing product mix, price 

changes, and/or technological changes. Research was 

done to determine the probability of past changes continuing and the possibility of new factors being introduced which would affect an industry’s output.

The fourth technique used to estimate coefficients 

was a general approach which took account of the other data and control totals at the industry level. In this 

method, changes over time in the sales of an industry 

to other sectors were analyzed; i.e., an industry was 

viewed as a row in the conventional input-output table.

The 1973 coefficients matrix was adjusted using the 

different techniques described above to generate a first 

approximation of the projected tables. The projected 

coefficients tables were combined with the projected 

industry final demands to yield output. These outputs 

were compared with independent estimates of output 

and evaluated against past sector trends in output. This 

evaluation process is described in the section on updating the matrix.

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Chapter 5. Employment Projections

The industry employment projections consist of wage 

and salary workers, unpaid family workers, and the 

self-employed. These are estimates of the number of fulland part-time jobs required to meet the projected sales of 

each industry to all final demand or intermediate users. 

Historical wage and salary employment data are based on 

the BLS establishment series of employment published in 

Employment and Earnings. Unpaid family-worker jobs and 

the number of self-employed are based on time series from 

BLS’s Office of Productivity and Technology.

The principal input to the industry employment projections was the projected gross output in each industry. These 

were obtained by multiplying total projected final demand 

purchases by the projected input-output matrices. Gross 

output includes the production needed ii* all supporting 

industries as well as that required to satisfy final users. 

Historical output data series were derived from a variety of 

sources. Manufacturing data were obtained from the Census

o f Manufactures and Annual Surveys of Manufactures.

Nonmanufacturing data were compiled from sources such 

as the Minerals Yearbook, Agricultural Statistics, and 

Business Income Receipts. These various output measures 

were benchmarked to the output data provided in the BEA 

input-output studies for 1963 and 1967 and to the matrix 

for 1973. (A detailed description of the output and 

employment data base is provided in Time Series Data for

Input-Output Industries; Output, Price, and Employment,

BLS Bulletin 2018 (1979).)

In addition to levels of output, the industry employment 

estimates required projections of output per hour and 

average annual hours worked. In each industry, the projected gross output was divided by an estimated outputper-hour ratio in order to arrive at total projected hours in 

each industry. Total hours were divided by projected 

average annual hours, yielding projected employment requirements for each industry.

Output per hour

Several alternative methods of projecting industry productivity were used: (1)A regression approach relating 

output per hour to the domestic output of the industry and 

a labor quality variable, defined as the ratio of blue-collar 

workers to all workers; (2) a least-squares time trend of the 

ratio, output per hour; (3) an adjustment method, adjusting 

the historical least-squares time trend of labor productivity 

by industry for the difference between projected and

historical output and labor-mix trends; and (4) an ad hoc 

projection of the output-per-hour ratio. While the industry 

projections did not completely conform to any particular 

means, method (3) dominated. While the specific form of 

the first three methods differed, their economic foundations were identical, following a Cobb-Douglas production 

function.

Output = A(t) + a labor + (1—a) capital services,

where A(t) is a technology variable which is approximated 

by a time trend, and the variables are expressed as natural 

logs.

Because of different assumptions about explanatory 

variables or estimating techniques, the forms of the 

respective labor-demand models varied. For example, if it is 

assumed that capital services can be approximated by a 

time trend, then the initial production function collapses to 

two inputs, a time trend and labor. Several alternative 

forms of the production functions yield the methods 

described below.

Method 1, the regression approach, expresses the demand for labor services, output per hour, as a function of 

time, output, and the ratio of white-collar workers to total 

workers (labor mix):

Output/hour = aO + al output + a2 time + a3 labor 

mix

This approach accounts for the cyclical movements in 

labor demand via the output variable and for the secular 

movements via the time and labor-mix variables. The 

equation assumes that capital stock and technology can be 

approximated by a time trend. The equation, by industry, 

is estimated with annual observations for 15 years and with 

ordinary least squares. This approach was used infrequently 

because the estimated coefficients were considered unreliable, principally due to a multicollinearity problem.

Method 2, a least-squares time trend, expresses the 

demand for labor, output per hour, as a function of time 

only:

Output/hour = a + a2 time 

where output/hour is expressed in natural logs.

This approach assumes that the long-term trends in 

industry output per hour can be approximated by a time 

trend and that these trends are unaffected by long-term 

fluctuations in output trends. This approach was also

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infrequently used. Since long-term trends in output and 

labor productivity do vary by subperiod, it is reasonable to 

assume that projected trends will also vary. While output 

fluctuations are an important explanatory variable of labor 

productivity fluctuations, this method does not suggest any 

mechanism for adjusting labor productivity trends for 

output trends which differ by subperiods.

Method 3, the adjustment approach to projecting the 

labor demand variable, output per hour, adjusts the 

historical labor demand trend for changes between the 

projected and historical output trends and for changes 

between the projected and historical labor mix trends:

Output/hour(p) = output/hour(h)

+ al [output(p) - output(h)]

+ a3 [labor mix(p) — labor mix(h)]

where p denotes projected trends, h denotes historical 

trends, a 1958-76 least-squares growth rate.

The coefficients al and a3 used in this approach are 

estimated in the following equation:

Output/hour(h) = al output(h) +a3 labor mix(h).

This approach duplicates method 1, except that crosssectional data rather than time-series data are used to 

estimate the coefficients a(l) and a(3). This approach, 

which was used most frequently, reflects several considerations. First, many empirical results of models which are 

based on time-series data alone yield results which contradict classical economic theory; for example, a marginal 

product of labor which exceeds unity. These results often 

reflect the collinearity problems of time-series data. Second, sufficient information is needed to discern the true 

coefficient of a particular coefficient; otherwise the results 

might represent spurious effects. A larger volume of data, 

such as cross-sectional data, minimizes these spurious 

effects.

The implicit assumption was that economic data are 

composites of business, seasonal, and secular cycles. A 

model which does not discern these cycles might yield 

incorrect analyses. However, the annual data base of only 

19 observations used loses much of its business cycle 

component.

Because the last equation of method 3 was estimated 

with cross-sectional data, industry-specific coefficients are 

lost, but more degrees of freedom are gained. But the 

growth model deals with industry projections. For example, 

assume that the estimated output coefficient of this 

equation, al, was 0.5. Next, suppose an industry’s output 

and labor productivity over the past several years had been 

growing, on the average, 5 percent and 2 percent, respectively, per year, but over the next year, the industry 

expects its output to grow 8 percent, or 3 percentage points 

faster than its historical rate. How fast will the industry’s

productivity grow? According to this model, 3.5 percent in 

the next year. This 3.5 percent forecast change is derived as 

follows: 2 percent (the historical productivity growth) plus

0.5 (the output coefficient) times 3 percentage points (the 

acceleration in output).

Method 4, largely ad hoc or judgmental, was necessary in 

three cases: When the historical and projected output 

trends differed sharply, energy industries being good 

examples; when the historical and projected output and 

employment series were unrelated, such as the water 

transportation and crude petroleum industries; and when 

the historical employment and output series implied a 

negative labor productivity trend, such as barber shops and 

beauty salons.

Average weekly hours

Average weekly hours for each industry were projected 

by first assuming that the hours paid for would change at 

the same rate as they would for the sector to which the 

industry belongs. The rates of change in average weekly 

hours were then projected for each sector, such as 

agriculture or manufacturing, based on the number of hours 

paid historically. For the most part, the sector level 

projections simply followed historical trends. Since a trend 

approach seemed inappropriate in the case of mining, trade, 

and other services, they were subjected to further analysis, 

with different factors used.

Industry employment

The employment projections started with the interindustry model runs that produced gross output for each 

industry in the projected years. These output levels were 

evaluated in two ways before they were accepted. First, the 

annual average rates of growth were compared with those in 

historical periods, and the shares of an industry’s output 

going to intermediate and final demand were compared 

with those in the base year 1973 and in 1958, 1963, and 

1967. Where significant variations were found, data and 

analytical reasoning were rechecked. Acceptable output 

levels for each of the 162 industries were divided in turn by 

the projected output-per-hour ratios to obtain the total 

projected hours in each industry. These total hours were 

next divided by the projected average annual hours to 

provide employment by industry requirements. The projected rates of change in industry employment were 

compared with historical average annual growth rates, and 

the projected industry employment levels were totaled and 

compared with the aggregate labor force projections used in 

the macroeconomic projections. Changes were made to 

achieve correspondence, usually in the productivity estimates. Finally, the industry employment estimates were 

circulated for comment by occupational specialists in BLS, 

and final adjustments were made.

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Chapter 6. Planned Changes

in the Projections System

A number of research efforts are now planned or underway, within the Office of Economic Growth or under its sponsorship, to develop techniques and the required additional data to improve projections of economic growth.

Macro model

For the next set of projections, work is underway to 

respecify selected blocks and reestimate the remainder 

of the existing macro model. The respecification will 

center on the production, employment, and business investment blocks. The new approach will stress the interdependence of firms’ decisions on capital and labor 

inputs to the production process, commonly called a 

factor-demand approach. These capital-labor-production tradeoffs will be modeled for five sectors—farm, 

manufacturing, nonprofit institutions and households, 

housing, and other private nonmanufacturing—using 

factor-demand equations based on marginal productivity conditions and incorporating relative prices. The 

current macro model treats employment and investment 

independently and only disaggregates production for 

farm and private nonfarm sectors.

This respecification is desirable for several reasons. 

One explanation for the recent slowdown in labor productivity trends is the shift in employment from highproductivity sectors to low-productivity sectors. The 

movement of labor from farm to nonfarm employment 

is an example of such a shift. A second reason offered 

for the slowdown is the 1973-74 jump in energy prices 

which affected labor usage and capital usage differently. A third explanation is the shortfall in research and 

development expenditures during the past decade 

which, in turn, has led to a slowdown in technological 

improvements. Testing these and other hypotheses requires a model which can specify, by sector, the mix 

or bundle of capital, labor, energy, and technological 

inputs to the production process.

A second important respecification of the existing 

model will deal with Federal transfer payments. These 

payments go to many different groups, such as individuals and State and local governments, and are under 

many different programs, such as social security and 

highway programs. Because of this diversity, industry 

employment estimates would be affected differently. 

Further, many of these programs are endogenous rather than being implemented via policy decisions.

The final substantial change in specifications for the 

next projections will occur in the residential and nonresidential construction demand blocks of the macro 

model. Residential construction will be modeled in 

terms of housing units, single-family versus multifamily units, mortgage rates, and other variables. Nonresidential construction will be modeled by function, educational versus commercial versus industrial construction. Previously, these blocks were modeled with one 

equation each.

Time and resources permitting, other respecifications 

will deal with (1) business inventories, disaggregating 

this single-demand component to separate components 

for farm, automobile, and other goods; (2) exports and 

imports, disaggregating these two demand components 

to components for farm products, petroleum, capital 

goods, and other goods; and (3) the monetary sector, 

currently dealt with by assumption, changing to behavioral, policy-oriented equations.

The data base of the macro model will be updated 

to 1978, adding 3 years to the observations. Because of 

the new factor demand and construction detail, the 

number of variables included in the macro data base 

will be expanded.

Finally, implicit in the factor-demand respecification 

is a change in the solution procedure of the model. The 

model is now balanced, or in equilibrium, when the gap 

between supply GNP and demand GNP is zero. The 

new model will be balanced when the demand for labor equals the supply of labor (or a target unemployment rate).

Factor demand in industry detail

The new factor-demand approach of the macro model will also be used at the industry level during the next 

projections. In the current methodology, estimation of 

rates of growth in output per hour and employment 

relied primarily on past trends for most industries, and, 

except for a time variable, no use was made of capital 

requirements. Further, business investment relied primarily upon past trends in investment products, for example, trucks versus lathes or stamping machines, rather than on existing capital stock in each industry. In 

the next set of projections, the approach to these two 

components, employment and investment, will stress 

the interdependence of labor and capital requirements

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in each industry. This new approach is, in part, possible because of the development of an industry-level 

capital stocks data base.18

This new approach will require several substantial 

changes in the interindustry solution procedure:

(1) The starting point for estimates of employment 

and investment will be elasticities of substitution between labor and capital in each industry. These elasticities, combined with projected industry outputs, will 

yield projected industry labor and capital requirements.

(2) The estimates of labor requirements, or labor 

hours, combined with an average workweek trend, will 

yield projected industry employment or jobs. The aggregate labor constraint upon these industry estimates 

would be the sector labor requirements developed in 

the revised macro model.

(3) The estimated capital requirements, or capital 

services, combined with the existing capital stock less 

discards, will yield projected industry investment 

trends. The aggregate constraint upon these industry 

investment trends would be sector capital requirements 

developed in the revised macro model.

(4) The estimates of industry investment, combined 

with an investment flow table, will yield projected investment by product, a final demand component.

(5) The estimates of investment by product, combined 

with the other projected final demands, will yield projected output levels, when used with the projected input-output table.

(6) A solution of this factor-demand model would 

involve iterating between alternative output, investment, and employment mixes until an internal consistency between the three elements is achieved. This internal consistency, by industry, is a capability not formally contained in the existing model.

Macro and micro relationships

The factor-demand specification outlined for both the 

macro and industry projections lends itself to an interesting possibility, that aggregate economic growth 

might be determined by the industry detail. Presently, 

aggregate growth is determined by the macro model, 

Y'hich abstracts from the economy’s detail. The existing model emphasizes those variables and processes 

which are the more important for determining the 

medium-term or 5- to 15-year growth path of the U.S. 

economy. What is an appropriate model for fore-casting such variables as total consumption, total investment, or total employment? These are currently forecast via individual econometric equations within the 

macro model; a single equation yields a forecast total 

consumption value; a second equation, total investment; 

and so on. With inclusion in a macro model, the direct 

and indirect responses of these endogenous variables to 

changes in policy instruments or other exogenous variables can be estimated. Explicit in these single-equation specifications is that the components of these aggregate variables are all perfect substitutes for one 

another.

This alternative specification would permit industry 

and product detail to determine aggregate forecasts. In 

the past, the model has depended upon the aggregate 

variables for practical reasons; i.e., the industry and 

product detail did not have sufficient observations to 

yield stable estimates of time series coefficients. These 

projections are based on annual observations, a technique which limits the degree of freedom; this is particularly critical when the number of historical observations barely exceeds the number of years being projected. These practical problems are being surmounted 

and, as a consequence, this alternative specification will 

be tested in the next set of projections.

18 Capital Stock Estimates for Input-Output Industries: Methods a Data,

Bulletin 2034 (Bureau of Labor Statistics, 1979).

29

Digitized for FRASER 

http://fraser.stlouisfed.org/ 

Federal Reserve Bank of St. Louis
Appendix A.

Macroeconomic Model:

Equations, Identities,

and Variables

Supply sector

1. ECLF = LCF * (1.0 — U)

2. EC JOBS = - 0.751 + 1.078 ECLF - 0.199U - 0.344 DM59 + 0.303 DM67 - 0.37 DM72

(-0.6) (51.1) (-4.5) (-1.7) (1.2) (-1.3)

R-squared = 0.999 

D.W. =1.458 

Estimation period: 1947-76

3. EMPE/POP = - 0.003 + 0.098 PUREC/POP

(-8.6) (75.2)

R-squared = 0.996 

D.W. =1.061 

Estimation period: 1952-74

4. In(EMPNE/POP) = - 4.469 + 1.921 In(PURNEC/POP) - 0.186 In(URBAN/POP)

(-14.2) (9.5) (-0.3)

R-squared = 0.988 

D.W. = 0.462 

Estimation period: 1952-74

4. ENFJBS = ECJOBS - (EF + EMPE + EMPNE + EFJBS)

6. AAHF = 1965.150 - 13.656 U - 9.037 U(t-1) + 27.893 FPOP + 7.623 TIME

(9.9) (-2.1) (-1.3) (3.3) (1.4)

R-squared = 0.877 

D.W. = 0.960 

Estimation period: 1948-76

7. AAHNF = 2392.730 - 7.728 U + 4.661 U (t-l) - 7.764 FLFPR - 3.365 TIME

(54.2) (-8.1) (4.7) (-5.5) (-*.8)

R-squared = 0.994 

D.W. = 1.950 

Estimation period: 1948-76

8. MHF - AAHF * EFJBS

9. MHNF = AAHNF * ENFJBS

10. MHIF = MHF/MHF(1972)

30

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Federal Reserve Bank of St. Louis
11. MHINF = MHNF/MHNF(1972)

12. KEF = KEF(t—1) + IEF — DEF

13. KENF = KENF(t-l) + IENF - DENF

14. KSF = KSF(t—1) + ISF — DSF

15. KSNF = KSNF(t—1) + ISNF — DSNF

16. KINV = KINV(t— 1) + IVCHG

17. KHS = KHS(t—1) + IR — DRES

18. IKF = (KSF + KEF)/(KSF(1972) + KEF(1972))

19. IKNF = (KSNF + KENF)/(KSNF(1972) + KENF(1972)

20. In(GNPFC/IKADJF) = 2.881 + 0.0002 U * U + 0.450 In(MHIF/IKADJF) + 0.013 T29

(27.7) (2.8) (11.3) (5.5)

R-squared = 0.957 

D.W. = 1.453

Estimation period: 1929-40,1946-74

21. In(GNPNFC/IKADJNF) = 6.065 - 0.0002 U * U + 0.805 In(MHINF/IKADJNF) + 0.020 T29

(192.1) (-5.0) (22.0) (31.0)

22. SERFCC = 0.922 + 0.855 * (EF * 13.588) - 1.716 CREEP2 + 0.122 TIME

(1.1) (24.1) (-2.1) (7.5)

R-squared = 0.995 

D.W. = 0.940 

Estimation period: 1947-74

23. SERFMC = -0.221 + 1.090 (EMIPA * 6.613) - 6.334 CREEP2 - 0.085 TIME

(-0.3) (37.6) (-3.4) (-2.5)

R-squared = 0.989 

D.W. = 1.072 

Estimation period: 1947-74

24. SEREDC = 3.770 + 0.801 (EMPE * 8.288) + 0.219 TIME

(23.0) (39.6) (7.1)

R-squared = 0.999 

D.W =1.281 

Estimation period: 1947-74

25. SERNEC = -0.707 + 0.852 (EMPNE * 8.407) + 0.247 TIME — 2.874 CREEP2

(-0.5) (12.5) (5.2) (-1.9)

R-squared = 0.999 

D.W. = 0.980 

Estimation period: 1947-74

26. GGP = SERFCC + SERFMC + SERE DC + SERNEC

27. GNPTC = GNPFC + GNPNFC + GGP

31

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Income Sector

28. CPCDA = 15.048 - 2.840 U + 1.078(PRICE+PRICE(t-l)+PRICE(t-2)) + 0.166 GNPPK

(2.7) (-3.3) (3.1)

Cochrane/Orcutt RHO = 0.523 

R-squared = 0.993 

D.W. = 0.143 

Estimation period: 1949-74

29. CDACE = -10.353 + 0.051 KSTK(t-l)

(-24.3) (125.1)

where KSTK = KEF + KSF + KENF + KSNF

R-squared = 0.998 

D.W. = 0.143 

Estimation period: 1947-74

30. CDACB = -7.089 + 0.036 KSTK(t-l) + 0.007 KSTKDl(t-l) + 0.008 KSTKD2(t-l)

(-3.1) (10.2) (5.5) (7.2)

where KSTK = KEF + KSF + KENF + KSNF

and D1 is entered from 1954 on and D2 from 1962 on.

R-squared = 0.995 

D.W. =1.442 

Eatimation period: 1947-74

31. CPTFD = 2.925 + 0.731 TRCP * (CPCDA - CDAKB)

(6.0) (48.7)

R-squared = 0.989 

D.W. = 0.824 

Estimation period: 1947-74

32. DIV = -0.424 + 1.067 DlV(t-l) + 0.106 (IFC - IFIX) * DEFI

(-1.4) (57.2) (3.6)

where IFIX = IEF + ISF + IENF + ISNF

R-squared = 0.993 

D.W. =1.472 

Estimation period: 1947-74

33. IVA = 2.751 - 97.123 ((DGNPP - DGNPP(t-l))/DGNPP(t-l)) + 0.099 IVCHG - 0.021 KINV(t-l) - 20.380 EMBGO

(1.6) (-3.3) (1.0) (-1.6) (-7.5)

R-squared = 0.890 

D.W. = 3.203 

Estimation period: 1948-75

34. IFK = CPCDA - (CPTFD + CPTST)

35. UCP = IFK - (CDAKE - CDAKB) - I V A - DIV

36. CCANCC = 1.787 + 0.025 KHS(t-l) + 0.0002 KHS(t-l) * TIME

(0.4) (3.7) (1.1)

Digitized for FRASER 

32

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Federal Reserve Bank of St. Louis
R-squared = 0.993 

D.W. = 0.253 

Estimation period: 1947-74

37. CCANCK = CCANCC * DFNCCA

38. IBTFD = 6.134 + 0.004 GNPPK + 0.026 TRG * FU + 0.774 DMKW

(23.2) (2.8) (8.5) (2.0)

R-squared = 0.984 

D.W. = 1.470 

Estimation period: 1947-74

39. IBTST = 4.284 + 0.710 (GDSTK + SERSTK + TRSTP - GAK(t-l) - 0.527 U

(4.1) (107.0) (-2.3)

R-squared = 0.998 

D.W. = 1.223 

Estimation period: 1948-75

40. IPFD = 1.466 + 0.004 (13Y5Y * DFP) + 0.002 (13Y5Y * DFP)(t-1) - 0.0004 (13Y5Y * DFPXt-2)

(9.1) (10.0) (2.8) (-0.7)

R-squared = 0.993 

D.W. = 1.127 

Estimation period: 1952-75

41. SICE = 0.431 + 0.529 SICTOT

(3.4) (167.7)

R-squared 0.999 

D.W. = 0.376 

Estimation period: 1947-74

42. SICU = 0.508 + 0.392 ((CEP + GGP) - SICE * TRU)

(5.0) (27.3)

R-squared = 0.966 

D.W. = 1.445 

Estimation period: 1947-74

43. SICO = 1.187 + 0.900 TRO * CSIC * ((CEP + GGP) - SICE)) * WB/MFI

(2.2) (49.8)

R-squared = 0.990 

D.W. = 0.808 

Estimation period: 1947-74

44. SICST = -0.070 + 0.136 (SERSTK - (ES * SICE/(ECLF+EMBLS)))

(-1.5) (129.5)

where ES = EMPE + EMPNE

R-squared = 0.999 

D.W. = 0.789 

Estimation period: 1947-74

45. SICTOT = SICU + SICO + SICST + SICFD

Digitized for FRASER 

33

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Federal Reserve Bank of St. Louis
46. IPC = -2.325 + 0.019 PI + 0.419 13M 

(-8.7) (16.3) (2.6)

R-squared = 0.989 

D.W. = 0.429 

Estimation period: 1947-74

47. PI = GNPTK - CDAKE - CCANK - IBTFD - IBTST - SD + SLSFD + SLSST - CPIVA + (CDAKE - CDAKB)

SICTOT + TRAN + DIV + IPFD + IPST + IPC

48. In(MFI) = 6.833 + 0.865 In(1.0 -(U /100.0)) + 1.052 In(GNPTK/(ECLF + EMBLS)) +1.291 In((PI + SICTOT -

(87.5) (2.3) (78.2) (5.2)

SICE)/GNPTK)

R-squared = 0.998 

D.W. =1.679 

Estimation period: 1947-74

49. PTFD = -5.865 + 0.051 PI + 0.362 PI * TRMFI

(-4.7) (2.9) (3.8)

R-squared = 0.992 

D.W. =1.373 

Estimation period: 1947-74

50. PTST = -4.431 + 0.029 PI + 0.532 PTST(t-l) - 0.253 TIME

(-2.5) (2.4) (2.2) (-1.9)

R-squared = 0.996 

D.W. = 1.705 

Estimation period: 1947-74

51. DPIK = PI - (PTFD + PTST)

52. PS = -26.329 + 0.080 DPIK - 0.321 I3Y5Y + 20.070 DFDPI/DFDPI(t-1)

(-0.8) (8.5) (-0.3) (0.6)

R-squared = 0.959 

D.W. =1.947 

Estimation period: 1947-74

53. PCEK = DPIK - PS - IPC - PTR

Demand sector

54. PCED = -80.295 + 0.190 (PCEC) + 0.293 IR (t-l) - 0.490 U + 59.916(DPIK/DPIK(t-l))/DFDPI/DFDPI(t-l))

(-3.3) (18.5) (2.3) (-0.9) (2.5)

-1098.710 IPC/DPIK 

(-5.3)

where PCEC = PCEK/DFDPI

R-squared = 0.990 

D.W. = 1.468 

Estimation period: 1947-74

55. PCEN = 50.886 + 0.319 (PCEC) + 770.141 IPC/DPIK - 0.460 U

(26.7) (69.5) (6.0) (-1.3)

Digitized for FRASER 

34

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Federal Reserve Bank of St. Louis
where PCEC = PCEK/DFDPI

R-squared = 0.999 

D.W. = 0.964 

Estimation period: 1947-74

56. PCES = -38.429 + 0.397 (PCEC) + 0.598 U + 0.050 KHS

(-11.1) (11.2) (1.2) (2.4)

where PCEC = PCEK/DFDPI

R-squared = 0.999 

D.W. =1.211 

Estimation period: 1947-74

57. IENF = -7.301 + 0.190 IFC + 0.732 IENF(t-l) + 0.0002 KENF(t-l) + 118.350 (IFC/KENF + KSNF)/U)(t-1)

(-1.9) (2.9) (4.2) (0.01) (0.8)

+0.083 (GNPNFC - GNPNFC(t-l))

(2.7)

R-squared = 0.988 

D.W. = 1.349 

Estimation period: 1947-74

58. ISNF = 0.604 + 0.017 GNPNFC + 0.618 ISNF(t-l)

(0.5) (2.3) (3.8)

R-squared = 0.967 

D.W. =1.161 

Estimation period: 1947-74

59. IVCHG = -42.234 + 0.166 (GNPFC + GNPNFC) -Q.424 KINV(t-l)KINV(t-l) + 13.182/U- 1.197 TIME

(-7.1) (6.8) (-7.0) (1.2) (-2.8)

R-squared = 0.820 

D.W. 1.742 

Estimation period: 1947-74

60. IR = -68.090 - 4.921 13Y5Y + 1.448 HOUSE + 4.643 DPIC/HOUSE/

(-7.8) -(4.1) (5.7) (3.8)

R-squared = 0.945 

D.W. =1.381

Estimation period: 1929-40,1946-74

61. M = - 6.165 + 0.027 DPIC(t-l) + 0.033 (DPIC - DPIC(t-1)) + 0.383 ((DEFM/DFDPI) - (DEFM(t-1 )/DEDPI(t-1)))

(-1.9) (2.0) (1.1) (0.3)

+ 5.123 CPSQR + 0.841 M (t-l)

(2.1) (7.9)

R-squared = 0.996 

D.W. = 1.052 

Estimation period: 1947-74

62. PURFDC = SERFMC + SERFCC + GDFDC

63. PUREC/POP = -0.184 + 0.071 ((GNPFC + GNPNEC)/POPXt-l) + 0.513 (GAC * GPCED/POP) + 0.474 SCHL/POP

(-7.7) (13.3) (1.3) (5.0)

Digitized for FRASER 

35

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Federal Reserve Bank of St. Louis
R-squared = 0.991 

D.W. =1.663 

Estimation period: 1953-74

64. PURNEC/POP = -0.089 + 0.085 ((GNPFC + GNPNFC)/(POP)(t-l)

(-1.4) (4.4)

+ 0.607 (GAC * (1.0—GPCED)/POP) + 0.003 U

(2.1) (0.9)

R-squared = 0.973 

D.W. 0.538 

Estimation period: 1953-74

Price/wage sector

65. In(DGNPP) = 0.560 + 0.867 In(ALUL(t-l)) + 0.132 In(WPICR) - 0.039 In(U)

(17.0) (40.7) (5.7) (-2.1)

R-squared = 0.994 

D.W. =1.214 

Estimation period: 1948-75

66. CEPM = 4.994 + 60.286 (((GNPFC+GNPNFC)/(MHF+MHNF))—

(4.7) (3.8)

((GNPFC+GNPNFC)/(MHF+MHNF))(t-1 ))/((GNPFC+GNPNFC)/(MHF+MHNF))(t-1) 

+119.426 ((DFDPI—DFDPI(t—l))/DFDPI(t—l) —0.799 U 

(11.8) (-4.5)

R-squared = 0.860 

D.W. =2.091

Estimation period: 1947-76

67. CPH = CPH(t-1) * C EPM

68. CEP = CPH * (MHF + MHNF)

69. ALUL = CEP/(GNPFC + GNPNFC)

70. PRICE = percent change DGNPP - CEPM

71. DEFI = -0.008 + 1.005 DGNPP

(-0.3) (34.9)

Cochrane/Orcutt RHO = 0.723 

R-squared = 0.997 

D.W. =1.661

Estimation period: 1948-74

72. DFIV= 0.212+0.810 DGNPP

(1.8) (5.5)

Cochrane/Orcutt RHO = 0.159 

R-squared =0.611 

D.W. =1.890 

Estimation period: 1948-74

73. DEFRI = -0.272 + 1.229 DGNPP

(- 1.6) (12.2)

36

Digitized for FRASER 

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Federal Reserve Bank of St. Louis
Cochrane/Orcutt RHO = 0.968 

R-squared = 0.993 

D.W. =1.836 

Estimation period: 1948-74

74. (DFDPI - DF DPI(t -1 ))/DFDPI(t -1)

= 0.003 + 0.901 (DGNPP-DGNPP(t-l))/DGNPP(t-l)) 

(1.7) (19.7)

Cochrane/Orcutt RHO = 0.189 

R-squared = 0.947 

D.W. =1.558

Estimation period: 1948-74

75. DEFX = 0.003 + 0.491 DGNPP + 0.536 DEFM

(0.2) (12.8) (23.2)

Cochrane/Orcutt RHO = 0.428 

R-squared = 0.997 

D.W. =1.991

Estimation period: 1949-74

76. DFGDS = -0.584 + 1.529 DGNPP

(-6.7) (23.2)

Cochrane/Orcutt RHO = 0.953 

R-squared = 0.998 

D.W. = 2.096 

Estimation period: 1948-74

77. DFGDF = -0.016 + 1.021 DGNPP

(-0.8) (38.8)

Cochrane/Orcutt RHO = 0.260 

R-squared = 0.990 

D.W. =1.651 

Estimation period: 1948-74

78. DFCCA = 0.028 + 0.818 DEFI + 0.163 DGNPP

(1.5) (9.4) (1.8)

Cochrane/Orcutt RHO = 0.872 

R-squared = 0.999 

D.W. =1.571

Estimation period: 1948-74

79. DFNCCA = -0.014 + 0.284 DFDPI + 0.755 DGNPP

(-0.4) (0.5) (1.2)

Cochrane/Orcutt RHO = 0.789 

R-squared = 0.996 

D.W. =1.124

Estimation period: 1948-74

80. DEFSFC = DEFSFC(t-l) * (% ch DFDPI)

81. DEFSFM = DEFSFM(t -1) *(%ch DFDPI)

37

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Federal Reserve Bank of St. Louis
82. DEFSS = DEFSS(t-l) * (%ch DFDPI)

83. DEFGA = DEFGA (t—1) * (% change in DGNPP)

84. DGNPT = weighted average of DGNPP, DEFSFC,

DEFSFM, and DEFSS

85. GNPDC = PCED + PCEN + PCES + IEF + IENF + ISF + ISNF 

+ IVCHG + IR + EXPRT -M + PURFDC + PUREC + PURNEC

86. GAP = GNPTC - GNPDC

Explanation of variables DEFGA Deflator for Federal grants-in-aid

DEFI Fixed nonresidential investment deflator,

♦denotes an exogenous variable. 1972=100

DEFM* Imports of goods and services deflator,

AAHF Average annual private farm manhours, 1972=100

establishment basis DEFRI Residential structures deflator, 1972=100

AAHNF Average annual private nonfarm manhours, DEFSFC Federal civilian compensation deflator

establishment basis DEFSFM Military compensation deflator

ALUL Unit labor cost DEFSS S&L compensation deflator

CCANCC Noncorporate capital consumption allow­ DEFX Exports of goods and services deflator,

ances, constant dollars 1972=100

CCANCK Noncorporate capital consumption allow­ DENF* Discards of PDE, nonfarm

ances, current dollars DFCCA Corporate consumption allowances deflator

CDACB Corporate depreciation allowances, constant DFDPI Disposable personal income deflator

dollars, book value definition (without DFGDF Federal purchases less compensation deflaCCA) tor 1972=100

CDACE Corporate depreciation allowances, constant DFGDS S&L purchases less compensation deflator,

dollars, with capital consumption adjust­ 1972=100

ment (CCA),(CDACB*DFCCA) DFIV Change in business inventories deflator,

CDAKB Corporate depreciation allowances, current 1972=100

dollars, without CCA (CDACE*DFCCA) DFNCCA Noncorporate consumption allowances

CDAKE Corporate depreciation allowances, current deflator

dollars, with CCA (CDACE*DFCCA) DFP Federal debt proxy (see text)

CEP Compensation of employees, private econ­ DGNPP Private GNP deflator, 1972=100

omy DGNPT Total GNP deflator, 1972=100

CEPM Percent change in current dollars compensa­ DIV Net corporate dividend payments

tion per hour in the private sector (B66) DMKW* Korean War dummy = 1 for 1951-53 (38)

CPCDA Corporate profits + capital depreciation DM59* Establishment survey definitional shift = 1

allowance — inventory valuation adjust­ from 1959

ment DM67* Establishment survey definitional shift = 1

CPH Private compensation per hour (67L, 68) from 1967

CPIVA Corporate profits + inventory valuation DM72* Establishment survey definitional shift = 1

adjustment (CPCDA+IVA-CDAKE) from 1972

CPSQR Capacity pressure, defined as (((Actual DPIC Disposable personal income, constant dolGNP/Potential GNP)-0.98)**2) lars (DPIK/DFDPI)

CPTFD Federal corporate profits taxes DPIK Disposable personal income, current dollars

CPTST* State and local (S&L), corporate profit DRES* Discards of residential structures

taxes DSF* Discards of structures, farm

CREEP2* Variable to account for unwarranted grade DSNF* Discards of structures, nonfarm

enhancement during the 1947-69 period ECJOBS Civilian employment establishment basis

CSIC* Social security coverage as a percent of paid ECLF Civilian employment, labor force basis, age

employment 16 and over

DEF* Discards of producer durable equipment EF* Average number of full- and part-time Fed­

(PDE), farm eral Government general employees

38

Digitized for FRASER 

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Federal Reserve Bank of St. Louis
EFJBS* Private farm employment, establishment ISF* Investment in nonresidential structures, farm

basis ISNF Investment in nonresidential structures, nonEMBGO* Oil embargo dummy = 1 in 1973-74 farm

EMBLS* Level of the Armed Forces, BLS basis IV A Inventory valuation adjustment

EMIPA* Military employment including reserve IVCHNG Change in the stock of business

forces (NIPA basis) I3M* Yield on 3-month government bills

EMPE S&L government employment in education I3Y5Y* Yield on 3- 5-year government bonds

EMPNE S&L government employment in noneduca­ KEF Stock of PDE, farm

tion KENF Stock of PDE, nonfarm

ENFJBS Private nonfarm employment establishment KHS Stock of residential structures

basis KINV Stock of business inventories

EXPRT* Exports of goods and services KSF Stock of structures, farm

FLFPR* Female labor force participation rate, age KSNF Stock of structures, nonfarm

16 and over LFC* Civilian labor force, 16 years and over

FPOP* Total farm population M Imports of goods and services

FU* Motor fuel usage MFI Median family income

GAC* Federal grants-in-aid to S&L government, MHF Private farm manhours, establishment basis

constant dollars MHIF Index of farm manhours, 1972=100

GAK Federal grants-in-aid to S&L government, MHINF Index of nonfarm manhours, 1972=100

current dollars (GAC*DEFGA) MHNF Private nonfarm manhours, establishment

GAP Supply GNP less demand GNP, constant basis

dollars PCED Personal consumption expenditures, durable

GDFDC* Federal purchases of goods and services less goods, constant dollars

compensation, constant dollars PCEK Personal consumption expenditures, current

GDSTK S&L government purchases of goods and dollars

services less compensation, current dollars ((PUREC+PURNEC)-(SEREDC+

PCEN Personal consumption expenditures, nondurable goods, constant dollars

SERNEC))*DFGDS PCES Personal consumption expenditures, services,

GGP Gross government product, constant dollars constant dollars

GNPDC Demand-side GNP, constant dollars PI Personal income

GNPFC Farm GNP, constant dollars POP* Total noninstitutional population including

GNPNFC Private nonfarm GNP, constant dollars Armed Forces stationed abroad

GNPPK Private GNP, current dollars ((GNPFC+ PRICE Labor price/cost spread, private economy

GNPNFC)*DGNPP) PS Personal savings, current dollars

GNPTC Total supply-side GNP, constant dollars PTFD Federal personal income tax payments

GNPTK Total supply-side GNP, current dollars PTR* Personal transfers to foreigners

(GNPPK+SERSTK+(SERFCC*DEFSFC) PTST S&L personal income tax payments

+(SERFM *DEFSFM)) PUREC S&L purchases, education, constant dollars

GPCED* Education’s share of Federal grants PURFDC Federal purchases of goods and services,

HOUSE* Number of households constant dollars

IBTFB Federal indirect business taxes PURNEC S&L government purchases, noneducation,

IBTST S&L indirect business taxes constant dollars

IEF* Investment in PDE, farm SCHL* Total school enrollment, ages 5-34

IENF Investment in equipment, nonfarm SD* Statistical discrepancy

IFC Internal funds, constant dollars (IFK/DEFI) SEMP* Ratio of full-time equivalent employees in

IFK Internal funds, current dollars the service industries to full-time equivaIKF Index of farm capital stock, 1972=100 lent private employment

IKADJF Farm index of capital adjusted for utilization 

(IKF*(1.0-U»

SEREDC S&L government education compensation, 

constant dollars

IKADJNF Nonfarm index of capital adjusted for utilization (IKNF*(1.0-U»

SERFCC Federal civilian compensation, constant 

dollars

IKNF Index of nonfarm capital stock, 1972=100 SERFMC Federal military compensation, constant

IPC Interest paid by consumers dollars

IPFC Net interest paid by Federal Government SERNEC S&L noneducation compensation, constant

IPST* S&L net interest payments dollars

IR Investment in residential structures SERSTK S&L compensation, current dollars

39

Digitized for FRASER 

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Federal Reserve Bank of St. Louis
SICE . Employer contributions for social insurance 

SICFD* Contributions for other Federal social insurance programs

SICO OASDHI contributions

SICST State and local insurance funds

SICTOT Total social insurance contributions

SICU Social insurance contributions for unemployment insurance

SLSFD* Subsidies less current surplus of Federal 

Government enterprises

SLSST* Subsidies less current surplus of S&L gov-- 

ernment enterprises 

TIME* Time trend, 1946 = 0

TRAN* Total government transfer payments to

persons

TRCP* Federal corporate profits tax rate

TRG* Federal tax rate on gasoline

TRMFI Federal tax rate on median family income

TRO* Tax rate for OASDHI

TRSTP* S&L government transfers to persons

TRU* Average employer contribution rate for un 

employment insurance

T29* Time trend, 1928 = 0

U* Unemployment rate of the civilian labor 

force, age 16 and over

UCP Undistributed corporate profits

URBAN* Total population living in urban areas

WB* Wage base for OASDHI

WPICR* WPI for crude materials for further processing (1972=100)

40

Digitized for FRASER 

http://fraser.stlouisfed.org/ 

Federal Reserve Bank of St. Louis
Appendix B. Potential

Economic Growth

Assessment System for the

United States (PEGASUS)

PEGASUS is a software system designed to formalize 

and automate the links among the various projection 

processes in the BLS Economic Growth model such as the 

aggregate economic projection, distribution of final demand 

by industry, and the determination of industry employment and output estimates. The system insures consistency 

across segments of the process and allows for rapid 

inclusion of data revisions or changes in assumptions. The 

purpose of this appendix is to present a general description 

of the capabilities of PEGASUS and a list of available 

documentation.

PEGASUS is divisible into three segments, or groups of 

programs. These are the solution segment, data base 

management, and the data display and analysis segment. 

The solution segment allows for a continuous solution of 

the entire projection model or for solution of discrete 

elements of that model. Models or processes currently 

available are as follows:

BLS macroeconomic model

Houthakker/Taylor consumption model

Investment by consuming industry

Industry final demand bridge

Input-output solution

Industry employment, hours, and productivity model

Individual portions of the process may be solved alone as 

long as exogenous data from prior steps are available in the 

data base. The solution segment of the model also allows 

for dynamic constant adjustment terms or for the override 

of all behavioral equations.

The data base management segment allows the user to 

update or otherwide modify either the PEGASUS time 

series data base or the bridge/input-output matrix data 

bases. Commands are also available to copy or print all or 

part of the various data bases.

The data display/analysis segment allows for more 

specialized presentation of data than is available in the data

base management segment. The following reports are 

currently available:

1. Aggregate analysis—12 tables presenting various aspects of the aggregate data are produced. Many 

analytical ratios and user selected compound growth 

rates accompany each table.

2. Industry summary package-final demand by major 

national income categories as well as total and 

intermediate output are produced for 3 historical and 

3 projected years for each industry. Either growth 

rates or percent distributions of output may be 

chosen by the user. Major sector aggregations are also 

presented.

3. Industry employment/output package—several categories of employment and total output series are 

presented for each industry with selected growth 

rates. Major sector aggregates are also presented.

This segment of PEGASUS also contains more analytically oriented report generators. Currently, two options are 

available.

1. Simulation analysis—actual and estimated time series, 

a plot of these series over time, and selected summary 

statistics are presented for a selected range of 

variables and years.

2. Aggregate multiplier analysis-multipliers of selected 

variables on all aggregate variables are computed for a 

specified year. A summary table presents the multipliers of all selected variables on major demand GNP 

components.

Documentation of PEGASUS is available in four volumes: 1) System Review; 2) Source Listings; 3) Historical 

Data Sources; and 4) Behavioral Equations. This material is 

available on request from the Bureau of Labor Statistics, 

Office of Economic Growth. The system itself, which is 

currently operational on the IBM 370, is available on 

magnetic tape for the cost of generating such a tape.

41

Digitized for FRASER 

http://fraser.stlouisfed.org/ 

Federal Reserve Bank of St. Louis
Appendix C. Personal

Consumption Model Equations

Variable 201 - CAR

CAR-CAR(-l) = -144.379 + 0.239 (PCE-PCE(-l))-0.089 (PCE(-l)-PCE(-2)) -0.071 (PCE(-2)-PCE(-3)) 

(.258) (8.620) (2.761) (2.536)

R-squared = 0.701 

D.W. = 2.343

CAR — new cars, net used cars, trucks, recreation vehicles and trailers

PCE — personal consumption expenditures; national income and product accounts

Variable 202 - TBA

TBA = -9015.0 + 212.624 * (YR)

TBA — tires, tubes, accessories, and parts 

YR — year (e.g., 1976=76)

Variable 203 - FNR

FNR/POP = 1.413 + 0.774 (FNR(-l)/POP(-l)) + 0.311 (PCE/POP) - 0.029 (PCE(-l)/POP(-l))

(1.963) (9.743) (111.071) (8.008)

R-squared =0.98 

D.W. =1.4

FNR — furniture and bedsprings 

POP — total population

PCE — personal consumption expenditures, national income and product accounts 

Variable 204 - APP

APP/POP = -23.822 +0.018 (PCE/POP) + 0.019 (PR-APP)-1.645 (D)

(3.972) (12.858) (1.166) (2.069)

R-squared = 0.9852 

D.W. = 0.576

APP — kitchen and other household appliances

PCE — personal consumption expenditures

POP — total population

PR-APP — relative price of APP

D — dummy variable 193041 = 1

Variable 205 — CHN

CHN/POP = 26.232 + 0.323 (CHN(-l)/(POP(-l))+ 0.004 (PCE/POP) -0.252 (PR-CHN) 

(81.975) (4.359) (7.378) (6.142)

Cochrane/Orcutt RHO = 0.461

R-squared = 0.9647

D.W. = 1.51

Digitized for FRASER 

42

http://fraser.stlouisfed.org/ 

Federal Reserve Bank of St. Louis
CHN — china, glassware, tableware, and utensils 

POP — total population

PCE — personal consumption expenditures

PR—CHN — relative price of CHN

Variable 206 - RAD

RAD/HH = 12.749 + 0.008(PCE/HH) -0.189(PR-RAD) + 138.351 (COLOR)

(0.386) (2.940) (3.512) (18.479)

R-squared = 0.9936 

D.W. = 0.8223

RAD - radio, television sets, and musical instruments 

PCE — personal consumption expenditures

HH — households

PR-RAD — relative price of RAD 

COLOR — color television sets in HH

Variable 207 — ODH

ODH/POP= -4.262+ 0.916 (ODH(-l)/POP(-l)) + 0.023 (PCE/POP)- 0.020 (PCE(-l)/POP(-l))

(1.544) (11.432) (4.134) (3.088)

R-squared = 0.9878 

D.W. =1.1641

ODH — other durable housefurnishings

POP — total population

PCE — personal consumption expenditures

Variable 208 - JRY

JRY/POP = 0.839 (JRY(— 1 )/POP(—1)) + .0070 (PCE/POP)- 0.0056 (PCE(-l)/POP(-l)) - 0.0434 (PR-JRY) 

(10.622) (4.758) (3.289) (3.445)

+ 0.034 (PR-JRY(-1))

(2.774)

R-squared = 0.9914 

D.W. = 1.52

JRY — jewelry

POP — total popluation

PCE — personal consumption expenditures

PR—JRY — relative price of jewelry

Variable 209 OPT

OPT =1.0269(OPT(-1)

OPT — opthalmic and orthopedic appliances 

Variable 210 - BKS

BKS/POP = -0.477 + 0.631 (BKS(-l)/POP(-l)) + 0.0041 (PCE/POP) - 0.0026 (PCE(-l)/POP(-l))

(1.705) (6.783) (3.419) (1.845)

Cochrane/Orcutt RHO = —0.10 

R-squared =0.9715

D.W. = 1.83

BKS — books and maps

PCE — personal consumption expenditures

POP — total population

43

Digitized for FRASER 

http://fraser.stlouisfed.org/ 

Federal Reserve Bank of St. Louis
V a r i a b l e 2 1 1 — W H G

WHG/POP = 0.839 (WHG(-1 )/POP(-1)) + 0.016 (PCE/POP) - 0.013 (PCE(-l)/POP(-l)) - 0.0193 (PR-WHG) 

(6.454) (4.015) (2.591) (0.264)

-0.028 (PR-WHG(-l))

(0.413)

Cochrane/Orcutt RHO = 0.272 

R-squared =0.9914

D.W. =2.19

WHG - wheeled goods, durable toys, sports equipment

PCE — personal consumption expenditures

POP — total population

PR—WHG — relative price of WHG

Variable 212 - FOP

FOP/POP = 70.145 + 0.143 (PCE/POP - PCE(-l)/POP(-l)) + 0.0059 (PCE(-l)/POP(-l)) + 0.784 (FOP(-l)/POP(-l)) 

(3.103) (12.946) (0.854) (8.861)

R-squared = 0.953 

D.W. =1.094

FOP — food and beverages for off-premise consumption excluding alcohol

POP — total population

PCE — personal consumption expenditures

Variable 213 — FPM

FPM/POP = 42.909 + 0.416 (FPM(-l)/POP(-l)) + 0.037 (PCE/POP - PCE(-l)/POP(-l)) + 0.0103 (PCE(-l)/POP(-l)) 

(4.236) (3.174) (7.622) (3.911)

R-squared = 0.9343 

D.W. = 1.2282

FPM - food and beverages, on-premise consumption excluding alcohol 

PCE — personal consumption expenditures 

POP — total population

Variable 214 — ALC

ALC/POP = -22.225 + 0.582 (ALC(-l)/POP(-l)) + 0.006 (PCE/POP) + 0.634 (POP 18/POP) 

(1.240) (9.712) (4.650) (2.410)

R-squared = 0.940 

D.W. = 2.030

ALC — alcoholic beverages

POP — total population

PCE — personal consumption expenditures

POP 18 — population age 18 and over

Variable 215 — FOO

FOO = 361.0 + 1965.0 * (1.02) ** ((YR) -76)

FOO — food furnished government and commercial employees 

YR — year

Digitized for FRASER 

44

http://fraser.stlouisfed.org/ 

Federal Reserve Bank of St. Louis
V a r i a b l e 2 1 6 - F F D

FFD/FPOP = -2.151 + 1.070 * (FFD(-l)/FPOP(-l)) + 0.0003 * FDPI + 0.0003 * FDPI(-1)

(1.802) (13.244) (3.191) (3.191)

R-squared = 0.9141 

D.W. = 2.2460

FFD — food produced and consumed on farms

FPOP — total farm population

FDPI — farm disposable personal income

Variable 217 - SHU

SHU = 200 + SHU(—1)

SHU — shoes and other footwear

Variable 218 — CLO

CLO/POP = 0.590 + 0.796 (CLO(-l)/POP(-l)) + 0.074 (PCE/POP - PCE(-l)/POP(-l)) + 0.013 (PCE(-l)/POP(-l)) 

(0.113) (7.409) (26.234) (2.283)

- 6.489 (D)

(3.272)

R-squared = 0.9901 

D.W. = 2.302

CLO — clothing and luggage

POP — total population

PCE — personal consumption expenditures

D — dummy representing effects of Vietnam War on clothing:

1966 = 0.501 

1967= 1.000

1968 = 0.987

1969 = 0.889

1970 = 0.625

1971 =0.136

Variable 219 - MIC

MIC — clothing issued to military

Projections — constant value over the projected period

Variable 220 - GAO

GAO — gasoline and oil

Projection process — exogenously determined

Variable 221 — FUL

FUL — fuel oil, coal, and farm wood 

Projections process — exogenously determined

Variable 222 - TOB

TOB — tobacco

Projections process — growth rate over projections period equal to USDA growth rate

45

Digitized for FRASER 

http://fraser.stlouisfed.org/ 

Federal Reserve Bank of St. Louis
Variable 223 - ABD

In ABD = -2.868 - 1.058 On (DEFM/DFDPI)) + 0.783 (In (PCE/HH)) + 0.458 (In EAB)

(1.422) (4.191) (4.699) (3.466)

R-squared = 0.901 

D.W. = 0.730

ABD - expenditures abroad by U.S. Government personnel 

DEFM — imports of goods and services deflator, 1972 = 100 

DFDPI - disposable personal income deflator, 1972 = 100

PCE — personal consumption expenditures

HH — households

EAB — employees abroad

Variable 224 - REM

REM/POP = 0.788 (REM(-l)/POP(-l)) - 0.005 (PCE/POP) + 0.005 (PCE(-l)/POP(-l)) - 0.094 (PR-REM) 

(10.447) (3.564) (3.564) (2.458)

R-squared = 0.5549 

D.W. = 1.2239

REM — remittances in kind

POP — total population

PCE — personal consumption expenditures

PR-REM — relative price of REM

Variable 225 - SDH

SDH/POP =0.156 (SDH(-l)/POP(-l)) + 0.018 (PCE/POP) - 0.009 (PCE(-l)/POP(-l)) + 3.572 (D)

(1.043) (8.482) (3.218) (0.575)

Cochrane/Orcutt RHO = 0.960 

R-squared = 0.9859

D.W. = 1.7213

SDH — semidurable house furnishing 

POP — total population 

PCE — personal consumption expenditures 

D — dummy variable, 1930-41 = 1

Variable 226 - DRG

DRG/POP = 31.787 - 1.375 (YR) + 0.020 (YR * YR) 

(3.653) (4.810) (8.639)

R-squared = 0.9930 

D.W. =0.7951

DRG - drug preparation and sundries 

POP - total population 

YR — year

Variable 227 - TLG

TLG/POP = 0.830 (TLG(-l)/POP(-l)) + 0.003 (PCE/POP) - 0.031 (PR-TLG) + 1.845 (D) 

(15.552) (4.074) (3.937) (2.853)

R-squared = 0.9950 

D.W. =1.1247

46

Digitized for FRASER 

http://fraser.stlouisfed.org/ 

Federal Reserve Bank of St. Louis
TLG — toilet articles and preparations 

POP — total population 

PCE — personal consumption expenditures 

PR-TLG — relative price of TLG 

D — dummy variable, 1930-40 = 1

Variable 228 - STY ((YR)-76)

STY — stationery and writing supplies 

YR — year

Variable 229 - TOY

TOY/POP = 0.731 (TOY(-1 )/POP(-1)) + 0.008 (PCE/POP) - 0.004 (PCE(-l)/POP(-l)) - 0.029 (PR-TOY) - 0.008 (PR-TOY(-l)) 

(6.100) (5.024) (1.990) (0.894) (0.238)

Cochrane/Orcutt RHO = 0.30 

R-squared = 0.9966

D.W. =1.62

TOY — nondurable toys and sport supplies

POP — total population

PCE — personal consumption expenditures

PR-TOY — relative price of TOY

Variable 230 - FLO

FLO/POP = - 29.049 + 0.576 (YR)

(13.154) (18.394)

R-squared = 0.9713 

D.W. = 2.263

FLO — flowers, seeds, and potted plants 

POP — total population 

YR — year

Variable 231 — CLP

CLP/POP = - 0.928 + 0.930 (CLP(-l)/POP(-l))+ 0.012 (PCE/POP) - 0.011 (PCE(-l)/POP(-l)) - 0.335 (D) 

(0.244) (9.298) (4.489) (3.862) (0.390)

R-squared = 0.9945 

D.W. = 1.76

CLP — cleaning, polishing, paper, miscellaneous 

POP — total population 

PCE — personal consumption expenditures 

D — dummy variable, 1927-46 = 1

Variable 232 — MAG 

MAG = 1.023 * (MAG(-l))

MAG — magazines and newspapers

Variable 233 - OWN

OWN/HH = 29.808 + 1.0 * (OWN(-l)/HH(-l))

47

Digitized for FRASER 

http://fraser.stlouisfed.org/ 

Federal Reserve Bank of St. Louis
OWN — owner-occupied nonfarm space rental value 

HH — households

Variable 234 — TEN

TEN/HH = 11.734 + 1.00 * (TEN(-1)/HH(-1))

TEN - tenant occupied nonfarm space rent 

HH — households

Variable 235 — FAR

FAR = FAR (-1) * (FPOP/FPOP(-l))

FAR — rental valued farm houses 

FPOP — total farm population

Variable 236 - OHO

OHO/POP = - 6.899 - 0.089 (OHO(-l)/POP(-l)) + 0.004 (PCE/POP + PCE(-l)/POP(-l)) 

(4.423) (0.646) (7.700)

Cochrane/Orcutt RHO = 0.8 

R-squared = 0.989

D.W. =2.010

OHO — other housing

POP — total population

PCE — personal consumption expenditures

Variable 237 - ELC

ELC = (DELC/DELC(-1)) * ELC(-1)

ELC — electricity

DELC — exogenously determined level of usage

Variable 238 - NGS

NGS = (DNGS/DNGS(-1)) * NGS(-1)

NGS — natural gas

DNGS — exogenously determined level of usage

Variable 239 - WAT

WAT/POP = - 0.266 + 0.662 (WAT(-l)/POP(-l)) + 0.003 (PCE/POP) - 0.001 (PCE(-l)/POP(~l)) - 0.031 (PRICE)

(0.475) (5.216) (3.095) (1.146) (2.057)

+- 0.040 (PRICE(-1))

(2.695)

Cochrane/Orcutt RHO =0.376 

R-squared = 0.99

D.W. =1.87

WAT — water and other sanitary services

POP — total population

PCE — personal consumption expenditures

PRICE — labor price/cost spread, private economy

Variable 240 - TEL

TEL/POP-TEL(-l)/POP(-l) = 0.005 (PCE/POP) - 0.003 (PCE(~l)/POP(-l)) - 0.031 (PRICE) + 0.009 (PRICE(-1)) + 1.67:

(3.299) (2.075) (2.079) (0.592) (3.999)

48

Digitized for FRASER 

http://fraser.stlouisfed.org/ 

Federal Reserve Bank of St. Louis
TEL — telephone and telegraph

PCE — personal consumption expenditures

POP — total population

PRICE — labor price/cost spread, private economy 

D — prewar dummy = 1

Variable 241 - DMS

DMS/POP = 0.963 * (DMS(-l)/POP(-l)) + 0.019 (PCE/POP) - 0.019 (PCE(-l)/POP(-l))

(88.310) (3.078) (3.078)

- 0.144 (PR-DMS) + 0.144 ((PR-DMS)(-1))

(0.710) (0.710)

R-squared = 0.9489 

D.W. =1.8711

DMS — domestic service

POP — total population

PCE — personal consumption expenditures

PR-DMS — relative price of domestic services

Variable 242 — OPO

OPO = -1839.043 + 79.486(YR) + 9.229(POP)

OPO — other household operations 

POP — total population 

YR — year

Variable 243 - REP

REP/POP = - 12.916 + 0.376 (REP(-l)/POP(-l)) + 0.018 (PCE/POP) - 0.003 (PCE(-l)/POP(-l)) 

(4.334) (4.979) (7.400) (1.833)

- 0.144 (PRICE) + 0.181 (PRICE(-l)) - 6.823 (D)

(2.022) (2.791) (4.771)

R-squared = 0.9977 

D.W. = 1.47

REP — auto repairs

POP — total population

PCE — personal consumption expenditures

PRICE — labor price/cost spread, private economy

D — prewar dummy = 1

Variable 244 - TOL

TOL = DGAO(-l) * TOL (-1)

TOL — road tolls

DGAO — exogenously determined gasoline extrapolator

R - s q u a r e d = 0 . 8 5 1 9

D . W . = 1 .9 3

Variable 245 - AIN

AIN/POP = - 2.566 + 0.647 (AIN(-l)/POP(-l)) + 0.006 (PCE/POP - PCE(-l)/POP(-l)) + 0.002 (PCE(-l)/POP(-l)) 

(1.893) (5.295) (7.597) (2.801)

49

Digitized for FRASER 

http://fraser.stlouisfed.org/ 

Federal Reserve Bank of St. Louis
AIN — auto insurance premiums less claims paid

POP — total population

PCE — personal consumption expenditures

Variable 246 - STR 

STR = 25 + STR(-l)

STR — street, electric railroad, and local bus

Variable 247 - TAX

TAX = 1.027**((YR)-73) * 842

TAX — taxicab 

YR - year

Variable 248 - CRR

CRR/POP = 4.255 + 0.0005(PCE/POP) - 0.0001 (PCE(-l)/POP(-l)) - 0.064(YR) 

(23.295) (3.698) (2.525) (7.645)

R-squared = 0.9596 

D.W. = 0.9626

CRR — commuter rail transportation 

POP — total population 

PCE - personal consumption expenditures 

YR — year

Variable 249 - IRR 

IRR= 1.015 * IRR(-l)

IRR — railway excluding transportation

Variable 250 — IBU

IBU/POP = 0.946 (IBU(-l)/POP(-l)) + 0.001 (PCE/POP) - 0.0009 (PCE(-l)/POP(-l)) 

(41.895) (2.149) (1.817)

- 0.006 (PR-IBU) + 0.002 ((PR-IBU(-l))

(1.856) (0.683)

R-squared = 0.9822 

D.W. = 1.7561

IBU — intercity bus

POP — population

PCE — personal consumption expenditures

PR-IBU — relative price of IBU

R - s q u a r e d = 0 .9 7 3 2

D . W . = 1 . 7 7 7 4

Variable 251 — IAI

IAI/POP = - 19.978 + 0.006 (PCE/POP) + 0.002 (PCE(-l)/POP(-l)) + 0.160 (YR) 

(21.436) (9.338) (8.542) (3.484)

R-squared = 0.9914 

D.W. = 1.0580

IAI — airlines

POP — total population

50

Digitized for FRASER 

http://fraser.stlouisfed.org/ 

Federal Reserve Bank of St. Louis
PCE — personal consumption expenditures 

YR — year

Variable 252 — TRO

TRO = 167 + 4.333 ((YR) -73)

TRO — other purchases intercity transporation 

YR — year

Variable 253 - SCL

SCL/POP = 2.619 + 0.586 (SCL(-l)/POP(-l)) + 0.0005 (PCE/POP) - 0.0008 (PCE(-l)/POP(-l)) 

(3.097)(6.669) (1.450) (2.413)

-0.019 (PR—SCL) + 0.008 ((PR-SCL)(-1))

(2.547) (1.018)

Cochrane/Orcutt RHO = 0.2825 

R-squared = 0.9807

D.W. = 1.3247

SCL — shoe cleaning and repair

POP — population

PCE — personal consumption expenditures

PR-SCL — relative price of SCL

Variable 254 - LAU 

LAU = .9726 * LAU(-1)

LAU - cleaning, dyeing, pressing, alteration, and laundering in establishments

Variable 255 - COT

COT = - 3016.80 + 58.2821 (YR)

COT — other clothing, accessories, and jewelry 

YR — year

Variable 256 - BBB

BBB = BBB(-l) * POP/POP(-l)

BBB — barbershops, beauty parlors, and baths 

POP — total population

Variable 257 - RTV

RTV = - 2.080 + 0.001 (PCE/POP -PCE(-l)/POP(-l)) + 0.0003 (PCE(-l)/POP(-l)) + 0.046 (YR) - 0.013 (D) 

(4.049) (3.129) (0.973) (2.096) (4.274)

R-squared = 0.9846 

D.W. =0.9189

RTV — radio and television repair 

PCE — personal consumption expenditures 

POP — total population 

D — dummy variable, 1947-50 = 1 

YR — year

51

Digitized for FRASER 

http://fraser.stlouisfed.org/ 

Federal Reserve Bank of St. Louis
MOV/POP = 0.929 (M0V'(-1 )/POP(-1)) + 0.016 (PCE/POP) - 0.016 (PCE(-l)/POP(-l)) - 0.132 (PRICE) + 0.124 (PRICE(-l)) 

(35.729) (4.378) (4.372) (1.247) (1.271)

R-squared =0.978 

D.W. = 2.370

MOV — motion picture admissions

PCE — personal consumption expenditures

POP — total population

PRICE — labor price/cost spread, private economy

V a r i a b l e 2 5 8 — M O V

Variable 259 — LEG

LEG = LEG(-l ) * POP/POP(-l)

LEG — legitimate theaters, etc. 

POP - total population

Variable 260 - SPE

SPE = -1.078 + 0.538 (SPE(-l)/POP(-l)) + 0.001 (PCE/POP) 

(2.245) (4.886) (3.333)

Cochrane/Orcutt RHO =0.817 

R-squared = 0.99

D.W. =1.68

SPE — spectator sports 

POP — total population 

PCE — personal consumption expenditures

Variable 261 — CLU

CLU — clubs and fraternal organizations 

Projections process — determined exogenously

Variable 262 — COM

COM = 2126.0 + 818.0 (POP/POP(-l)) +66.163 * ((YR)-76)

COM — commercial participant amusements 

POP — total population 

YR — year

Variable 263 — PAR 

PAR = PAR(-l) + 25

PAR = pari-mutuel net receipts

Variable 264 — REO

REO = - 16652.848 + 347.281(YR) - 0.721(YR * YR)

REO — other recreation 

YR - year

52

Digitized for FRASER 

http://fraser.stlouisfed.org/ 

Federal Reserve Bank of St. Louis
V a r i a b l e 2 6 5 - B R O

BRO — brokerage fees and investment counseling 

Projection process — exogenously determined

Variable 266 - BNK

BNK = - 2.272 + 0.651 (BNK(-l)/POP(-l)) + 0.003 (PCE/POP) - 0.001 (PCE(-l)/POP(-l)) 

(2.885) (1676.778) (5.052) (0.010)

R-squared = 0.9879 

D.W. =1.62

BNK — bank service charges

POP — total population

PCE — personal consumption expenditures

Variable 267 - IMP

IMP = - 8.422 + 0.584 (IMP(-l)/POP(-l)) + 0.010 (PCE/POP) + 4.464 (D)

(5.199) (7.781) (6.438) (4.555)

Cochrane/Orcutt RHO = 0.370 

R-squared = 0.994

D.W. =1.93

IMP — financial service charges furnished without pay

POP — total population

PCE — personal consumption expenditures

D — dummy = 1, if year is less than or equal to 1941

Variable 268 — LIF

LIF/POP = 5.046 + 0.360 (LIF(-l)/POP(-l)) + 0.003 (PCE/POP) + 0.003 (PCE(-l)/POP(-l)) 

(2.951) (2.281) (4.113) (4.113)

R-squared = 0.950 

D.W. =1.98

LIF — expense of handling life insurance

POP — total population

PCE — personal consumption expenditure

Variable 269 - GAL

GAL-GAL(-1)= 1.158- 162.272 (DE) + 40.482 (U) - 162.661 (I) + 248.011 (D)

(0.015) (4.208) (2.906) (4.388) (2.869)

R-squared = 0.7903 

D.W. = 3.01

GAL — legal services

DE — dummy, election years = 1

U — unemployment rate

I - intercept = 1, if year is less than or equal 1956

D — dummy = 1, in 1966, 0 in all other years

Variable 270 - FUN

FUN = FUN(-1) * DEATHS/DEATHS(-1)

FUN — funeral and burial expenses 

DEATHS — number of deaths

53

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Federal Reserve Bank of St. Louis
PBO/POP - PBO(-l)/POP(-l) = 0.003 (PCE/POP - PCE(-l)/POP(-l)) - 0.059 (PRICE - PRICE(-l)) + 0.296 (D)

(4.617) (2.270) (2.553)

V a r i a b l e 2 7 1 - P B O

R-squared = 0.4124

D.W. = 2.07

PBO — other personal business services 

POP — population

PCE — personal consumption expenditures

PRICE — labor price/cost spread, private economy

D — dummy = 1, if year less than or equal to 1941; 0, if greater than 1941

Variable 272 - PHY

PHY/POP = 148.711 - 4.644 (YR) + 0.050 (YR * YR) 

(8.308) (7.871) (10.449)

R-squared = 0.9853 

D.W. =1.14

PHY — physicians 

YR — year

Variable 273 - DEN

Ln DEN = 6.626 + 0.006 (YR) + 0.0003 (YR * YR)

(15.025) (0.399) (2.583)

R-squared = 0.9884 

D.W. =0.9134

DEN — dentists 

YR - year

Variable 274 - OPS 

OPS = 1.03 * OPS(-l)

OPS — other professional services

Variable 275 - PHO

PHO = - 17.005 + 0.894 (PHO(-l)/POP(-l)) + 0.012 (PCE/POP) - 0.003 (PCE(-l)/POP(-l)) 

(2.538) (12.775) (2.442) (0.497)

R-squared = 0.997 

D.W. =1.61

PHO — privately controlled hospitals and sanitariums

POP — total population

PCE — personal consumption expenditures

Variable 276 - HIN

HIN/POP = 0.686 (HIN(-l)/POP(-l)) + 0.007 (PCE/POP) - 0.003 (PCE(-l)/POP(-l)) - 0.060 (PRICE) + 0.025 (PRICE(-1)) 

(8.823) (4.191) (2.214) (5.489) (1.560)

5 4

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Federal Reserve Bank of St. Louis
Cochrane/Orcutt RHO = -0.213 

R-squared = 0.9965

D.W. =1.54

HIN — health insurance

POP — total population

PCE — personal consumption expenditures

PRICE — labor price/cost spread, private economy

Variable 277 - HED

HED= 1097.78 + 433.838 (HEW HED)

(28.366) (74.800)

R-squared = 0.9962 

D.W. =1.72

HED — higher education

HEW HED — HEW projection of private education costs — held at constant level 1984-1990

Variable 278 - EED

EED = 693.838 + 1687.85 (HEW EED)

(9.239) (26.497)

R-squared = 0.9709 

D.W. =0.8501

EED - elementary and secondary schools

HEW EED - Office of Education projections used as extrapolators

Variable 279 — OED

OED= OED(-l) * GNP/GNP(-1)

OED — other education and research 

GNP — gross national product

Variable 280 — RAW

RAW = - 8706.871 + 258.134 (YR)

(282.6) (4.53)

R-squared = 0.9936 

D.W. = 2.27

RAW — religious and welfare expenditures 

YR — year

55

Digitized for FRASER 

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Federal Reserve Bank of St. Louis
V a r i a b l e 2 8 1 — F T R

FTR/POP = 0.8 (FTR(—1 )/POP(—1)) + 0.003 (PCE/POP) - 0.030 (PRICE) 

(12.903) (3.971) (3.893)

Cochrane/Orcutt RHO = 0.032 

R-squared =0.9817

D.W. =1.85

FTR —' foreign travel by U.S. residents

POP — total population

PCE — personal consumption expenditures

PRICE — labor price/cost spread, private economy

Variable 282 — EXP 

EXP = 1.065 * EXP(-1)

EXP - expenditures in United States by foreigners

56

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Federal Reserve Bank of St. Louis
Appendix D. Investment-Output Ratios

Table D-1. Equipment

Industry 1967 1973

Projected base case Projected alternate case

1980 1985 1990 1980 1985 1990

1.00 Livestock and livestock products.............................. 0.0175 0.0167 0.0174 0.0166 0.0167 0.0172 0.0163 0.0165

2.00 Other agricultural p ro d u c ts........................................ .1559 .1235 .1539 .1449 .1481 .1520 .1424 .1466

3.00 Forestry and fishery p ro d u c ts................................... .0379 .0377 .0575 .0521 .0531 .0568 .0512 .0526

4.00 Agricutural, forestry, and fishery services............. .0951 .0762 .0879 .0839 .0847 .0868 .0824 .0839

5.00 Iron and ferroalloy ores m in in g ................................. .0626 .0308 .0959 .0993 .1008 .0947 .0976 .0999

6.00 Nonferrous metal ores m in in g ................................... .0918 .1823 .1456 .1483 .1489 .1438 .1457 .1475

7.00 Coal m in in g ...................................................................... .0608 .1447 .0958 .0953 .0973 .0947 .0936 .0963

8.00 Crude petroleum and natural g a s.............................. .0559 .0383 .0871 .0889 .0911 .0860 .0874 .0903

9.00 Stone and clay mining and quarrying....................... .0876 .2170 .1043 .1071 .1084 .1030 .1052 .1074

10.00 Chemical and fertilizer mineral m ining.................... .1501 .3608 .1852 .1785 .1809 .1829 .1753 .1792

11.00 New construction............................................................ .0286 .0339 .0374 .0446 .0388 .0370 .0377 .0384

12.00 Maintenance and repair construction....................... .0357 .0510 .0482 .0533 .0508 .0476 .0490 .0503

13.00 Ordnance and accessories............................................. .0157 .0160 .0120 .0146 .0142 .0119 .0134 .0141

14.00 Food and kindred prod ucts........................................ .0161 .0149 .0173 .0187 .0170 .0171 .0165 .0168

15.00 Tobacco m anufactures.................................................. .0081 .0167 .0080 .0082 .0080 .0079 .0077 .0080

16.00 Broad and narrow fabric, yarn, and thread mills. . .0320 .0263 .0315 .0347 .0314 .0311 .0303 .0311

17.00 Miscellaneous textile goods and floor coverings . . .0235 .0243 .0335 .0413 .0332 .0331 .0321 .0328

18.00 A p p a re l.............................................................................. .0127 .0166 .0153 .0180 .01 52 .0152 .0147 .0150

19.00 Miscellaneous fabricated textile products............... .0109 .0114 .0155 .0177 .0150 .0154 .0145 .0148

20.00 Lumber and wood products, except containers . . .0292 .0414 .0383 .0466 .0372 .0379 .0366 .0369

21.00 Wooden containers.......................................................... .0129 .0139 .0154 .0151 .0151 .0153 .0148 .0149

22.00 Household furniture ..................................................... .0208 .0263 .0270 .0266 .0270 .0267 .0262 .0268

23.00 Other furniture and fixtures ...................................... .0197 .0168 .0185 .0198 .0200 .0182 .0195 .0198

24.00 Paper and allied products, except containers .... .0625 .0403 .0600 .0587 .0594 .0593 .0576 .0588

25.00 Paperboard containers and boxes ........................... .0339 .0232 .0399 .0390 .0393 .0394 .0383 .0389

26.00 Printing and p u b lis h in g ................................................ .0314 .0288 .0311 .0304 .0309 .0307 .0299 .0306

27.00 Chemicals and selected chemical products............. .0646 .0425 .0675 .0629 .0638 .0667 .0618 .0632

28.00 Plastics and synthetic m aterials................................. .0691 .0368 .0637 .0610 .0614 .0629 .0599 .0609

29.00 Drugs, cleaning and toilet preparations.................. .0224 .0191 .0268 .0252 .0256 .0265 .0248 .0254

30.00 Paints and allied p ro d u c ts ........................................... .0197 .0175 .0290 .0222 .0225 .0287 .0218 .0223

31.00 Petroleum refining and related industries ............. .0153 .0126 .0176 .0149 .0182 .0174 .0146 .0180

32.00 Rubber and misc. plastics p ro d u c ts......................... .0456 .0434 .0483 .0469 .0474 .0477 .0461 .0469

33.00 Leather tanning and industrial leather products. . .0124 .0081 .0132 .0131 .0133 .0130 .0128 .0132

34.00 Footwear and other leather products....................... .0158 .0212 .0180 .0177 .0180 .0177 .0174 .01 78

35.00 Glass and glass products ............................................. .0371 .0425 .0435 .0426 .0433 .0430 .0418 .04 29

36.00 Stone and clay products................................................ .0347 .0451 .0433 .0422 .0427 .0428 .0415 .0423

37.00 Primary iron and steel manufacturing .................... .0378 .0255 .0430 .0419 .0426 .0425 .0412 .0421

38.00 Primary nonferrous metal manufacturing ............. .0212 .0151 .0248 .0246 .0250 .0245 .0241 .0248

39.00 Metal co n ta in e rs............................................................ .0289 .0275 .0331 .0320 .0326 .0327 .0315 .0323

40 .00 Heating, plumbing, and structural metal products .0230 .0315 .0259 .0251 .0254 .0256 .0246 .0252

41.00 Stampings, screw machine products, and bolts. . . .0273 .0274 .0302 .0291 .0295 .0298 .0286 .0293

42 .00 Other fabricated metal products................................. .0238 .0240 .0252 .0245 .0249 .0249 .0241 .0246

43 .00 Engines and tu rb in e s ..................................................... .0285 .0278 .0306 .0307 .0313 .0302 .0301 .0310

44.00 Farm machinery and e q u ip m e n t.............................. .0213 .0187 .0251 .0222 .0225 .0248 .0218 .0223

45 .00 Construction, mining, and oilfield mechinery. . . . .0272 .0265 .0234 .0245 .0249 .0231 .0241 .0247

46 .00 Material handling machinery and equipment .... .0121 .0134 .0119 .0126 .0127 .0118 .0124 .01 26

47.00 Metalworking machinery and equip m ent............... .0328 .0271 .0334 .0351 .0355 .0330 .0344 .0352

48.00 Special industry machinery and eq u ip m en t.......... .0241 .0268 .0227 .0247 .0251 .0225 .0242 .0248

49 .00 General industrial machinery and equipm ent. . . . .0278 .0305 .0311 .0314 .0319 .0307 .0308 .0316

50.00 Machine shop p ro d u c ts ................................................ .0456 .0404 .0351 .0347 .0352 .0346 .0341 .0348

51.00 Office, computing, and accounting machines. . . . .0385 .0444 .0544 .0570 .0578 .0538 .0560 .0573

52.00 Service industry m achines........................................... .0217 .0225 .0240 .0230 .0233 .0237 .0226 .0231

53.00 Electric industrial equipment and apparatus .... .0295 .0240 .0286 .0299 .0303 .0283 .0294 .0300

54.00 Household appliances..................................................... .0185 .0183 .0224 .0224 .0226 .0221 .0220 .0224

55.00 Electric lighting and wiring equipm ent.................... .0323 .0325 .0366 .0363 .0368 .0362 .0357 .0365

56.00 Radio, T V , and communication equipm ent.......... .0265 .0277 .0252 .0272 .0277 .0249 .0267 .0274

57.00 Electronic components and adcessories.................. .0509 .0654 .0544 .0559 .0568 .0537 .0549 .0563

58.00 Miscellaneous electrical machinery, equipment,

and supplies............................................................... .0264 .0328 .0295 .0278 .0282 .0292 .0273 .0280

59.00 Motor vehicles and eq uip m ent................................... .01 27 .0234 .0204 .0181 .0184 .0202 .01 78 .0182

60.00 Aircraft and parts............................................................ .0311 .0142 .0188 .0207 .0214 .0186 .0204 .0212

61.00 Other transportation equip m ent............................... .0192 .0217 .0235 .0243 .0245 .0233 .0239 .0243

62.00 Scientific and controlling instrum ents.................... .0262 .0317 .0288 .0272 .0277 .0285 .0267 .0275

63.00 Optical, ophthalm ic, and photographic equipment .0399 .0304 .0379 .0380 .0386 .0374 .0373 .0382

64.00 Miscellaneous m anufacturing...................................... .0238 .0250 .0259 .0255 .0259 .0256 .0251 .0?P~

57

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Federal Reserve Bank of St. Louis
Table P-1. Equipment—Continued

1967 1973

Projected base case Projected alternate case

1980 1985 1990 1980 1985 1990

65.00 Transportation and w arehousing.............................. .1277 .1665 .1487 .1456 .1485 .1469 .1431 .1471

66.00 Communications, except radio and TV

broadcasting............................................................... .2089 .2015 .1944 .1617 .1461 .1920 .1588 .1447

67.00 Radio and T V broadcasting........................................ .1711 .1063 .1285 .1251 .1271 .1269 .1229 .1258

68 .00 Electric, gas, water, and sanitary services............... .0753 .1076 .0911 .0883 .0897 .0900 .0867 .0889

69.00 Wholesale and retail t r a d e ........................................... .0363 .0423 .0450 .0435 .0441 .0444 .0427 .0437

70.00 Finance and insurance.................................................. .0214 .0479 .0251 .0242 .0247 .0248 .0238 .0245

71.00 Real estate and rental..................................................... .0119 .0101 .0129 .0123 .0126 .0127 .0121 .0124

72.00 Hotels, personal and repair services, except auto . .0563 .0488 .0734 .0710 .0721 .0725 .0698 .0714

73.00 Business services............................................................... .0235 .0328 .0265 .0256 .0260 .0262 .0252 .0258

75.00 Autom obile repair and services................................. .0854 .1408 .1294 .1240 .1278 .1278 .1218 .1247

76.00 A m usem ents.................................................................... .0434 .0824 .0747 .0741 .0770 .0738 .0728 .0762

77.00 Medical, educational services, and nonprofit

organizations............................................................... .0556 .0454 .0625 .0601 .0611 .0618 .0590 .0605

58

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Federal Reserve Bank of St. Louis
Table D-2. Structures

Industry 1973

Projected base case Projected alternate case

1980 1985 1990 1980 1985 1990

1 A g ricu ltu re.............................................................................. 0.0255 0.0220 0.0185 0.0179 0.0193 0.0183 0.0177 0.0193

2 Mining, except crude petroleum and natural gas .... .0537 .0841 .0544 .0503 .0554 .0537 .0498 .0556

3 Crude petroleum and natural gas...................................... .2262 .1625 .2423 .2606 .2961 .2393 .2581 .2972

4 Construction........................................................................... .0023 .0024 .0018 .0016 .0018 .0018 .0016 .0018

5 M anufacturing......................................................................... .0116 .0062 .0075 .0070 .0076 .0074 .0070 .0076

6 Transportation and warehousing...................................... .0217 .0173 .0237 .0211 .0200 .0234 .0209 .0201

7 Communications, except radio and T V broadcasting. .1159 .1144 .0695 .0572 .0492 .0686 .0566 .0494

8 Radio and T V broadcasting................................................ .0297 .0109 .0132 .01 20 .0130 .0130 .0119 .0130

9 Electric, gas, water, and sanitary services .................... .1614 .1642 .1401 .1341 .1477 .1384 .1328 .1483

10 Wholesale and retail tr a d e .................................................. .0228 .0233 .0142 .0131 .0141 .0141 .01 30 .0141

11 Finance and insurance.......................................................... .0233 .0386 .0197 .0180 .0195 .0195 .0179 .0195

12 Real estate and r e n ta l.......................................................... .0037 .0044 .0024 .0022 .0025 .0024 .0022 .0025

13 Hotels, personal and repair services, except auto . . . .0410 .0466 .0365 .0335 .0361 .0360 .0332 .0362

14 Business services.................................................................... .0083 .0087 .0061 .0057 .0062 .0060 .0057 .0062

15 Autom obile repair and services........................................ .0106 .0258 .0156 .0141 .0152 .0154 .0140 .01 53

16 Am usem ents........................................................................... .0382 .0561 .0355 .0333 .0367 .0350 .0330 .0368

17 Medical, educational services, and nonprofit

organizations.................................................................... .0985 .0621 .0518 .0474 .0425 .0511 .0469 .0426

59

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Federal Reserve Bank of St. Louis
Appendix E. Federal

Government Equations

Regression equations derived the levels of defense 

purchases and defense compensation using variables supplied from the macro model. Only total civilian compensation and total Federal purchases were available and these

had to be allocated to the defense and nondefense sectors. 

Regression equations were used for estimating defense and 

nondefense new construction. Equations used in the Federal Government sector are given below:

1) Defense civilian compensation = 122.3 + .4093 military compensation + 198.8 time 

R-squared = 0.9819

2) Total defense purchases = 16850.4 + 2.606 military compensation +125.5 time 

R-squared = 0.9426

3) Nondefense total new construction = -3825.5 + 7.845 nondefense employment

+0.0232 nondefense other purchases -69.01 time

4) Nondefense nonresidential constmction = - 1731 + 3.30013 nondefense employment

—0.013 nondefense other purchases — 35.981 time

R-squared = 0.4515

5) Nondefense highway construction = -116.344 +0.261 nondefense employment

—0.0032 nondefense other purchases+8.298

R-squared = 0.9462

6) Nondefense industrial construction = -1977.4 +4.284 nondefense employment

+ 0.039 nondefense other purchases -41.323 time

R-squared = 0.9318

7) Defense new construction = 3662.4 - 1.047 military employment +0.086 defense other purchases -130.3 time 

R-squared = 0.5452

8) Defense nonresidential construction = 727.6 - 0.276 military employment

+0.0116 defense other purchases — 14.543 time

R-squared = 0.4382

9) Defense nonresidential construction = 641.2 - 0.270 military employment

+0.0182 defense other purchases — 1.716 time

R-squared = 0.7723

10) Defense industry construction = 2794.7 - 0755 military employment

+0.0392 defense other purchases — 64.986 time

R-squared = 0.8468

Digitized for FRASER 

60

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Federal Reserve Bank of St. Louis
Appendix F Labor Demand Coefficients

Table F-1. Method 1: Dependent variable: Hours of all persons, private nonfarm nonmanufacutring industries

Industry number and title Constant

term

Coefficients of the variable Lagged

dependent

variable Time

trend

Domestic

output

6 Forestry and fishery p ro d u c ts............................................................... 1.66728 -0 .0 4 1 6 9 -0 .1 9 8 0 6 0.86170

7 Agricultural, forestry, and fishery services........................................ 1.26249 -0 .0 6 0 3 1 -0 .1 7 9 7 8 0.92448

8 Iron and ferroalloy ores m in in g ............................................................ 3.76873 0.27069 -0 .8 6 3 1 9 0.04183

9 Copper ore m in in g ..................................................................................... 1.99556 0.82155 -0 .5 5 8 6 3 0.34729

10 Other nonferrous ore m in in g ................................................................. 3.12880 -0 .0 5 8 6 9 -0 .3 3 2 1 5 0.40968

11 Coal m in in g .................................................................................................. 1.82517 0.90875 -0 .948 31 0.32907

12 Crude petroleum and natural gas.......................................................... 0.57593 0.70426 -0 .7 7 5 4 3 0.12543

13 Stone and clay mining and quarrying.................................................. 0.06670 0.65827 -0 .6 5 1 0 5 0.23609

14 Chemical and fertilizer mineral m ining................................................ 0.84549 0.17465 -0 .3 2 7 1 0 0.58558

117 Railroad transportation........................................................................... 0.67996 0.49226 -0 .5 9 9 0 0 0.37882

118 Local transit, intercity buses................................................................. 1.75689 0.02361 0.08416 0.61683

119 Truck transportation................................................................................ 2.04485 0.92657 -0 .9 5 5 0 9 0.25680

120 Water tran spo rtatio n................................................................................ 0.56897 0.91199 -0 .9 0 2 5 0 0.05849

121 A ir tran spo rtatio n..................................................................................... 1.48245 1.11758 -1 .0 8 2 2 5 0.01352

122 Pipeline transportation.............................................................................. 0.86493 0.79343 -0 .778 01 0.27593

123 Transportation services........................................................................... 1.02944 1.00750 -1 .0 4 4 3 8 0.07438

124 Communication, except radio and T V .............................. ................. 1.43850 0.79116 -0 .7 9 2 5 2 0.33270

125 Radio and T V broadcasting.................................................................... 0.11468 0.67350 -0 .7 5 0 5 6 0.30138

126 Electric u tilitie s .......................................................................................... 0.88425 0.06798 -0 .0 9 0 1 9 0.79935

127 Gas u tilitie s .................................................................................................. 1.67482 0.2 865 8 -0 .3 0 6 8 2 1.00082

128 Water and sanitary services .................................................................... 0.21148 0.04376 0.03115 0.94567

129 Wholesale tr a d e .......................................................................................... 2.45549 0.47074 -0 .4 0 6 6 3 0.74858

130 Retail tr a d e .................................................................................................. 2.71504 0.67637 -0 .4 8 2 5 9 0.53212

131 Banking .......................................................................................................... 0.22739 0.05878 -0 .0 7 6 1 3 0.98289

132 Credit agencies and financial brokers.................................................. 0.73410 0.29629 -1 .0 6 8 3 0 0.86991

133 Insurance ....................................................................................................... 0.18231 -0 .0 2 0 6 8 -0 .0 0 5 5 9 1.06115

135 Real estate..................................................................................................... 0.65615 -0 .0 0 1 4 4 0.08227 1.04864

136 Hotels and lodging places ...................................................................... 0.19363 0.06410 0.05435 0.93550

137 Personal and repair services.................................................................... 1.03371 0.22171 -0 .4 7 1 3 8 0.95412

138 Barber and beauty sh op s......................................................................... 1 03352 0.20537 -0 .2 7 0 4 0 0.96329

139 Miscellaneous business services............................................................ 0.53478 0.57546 -0 .3 2 3 9 0 0.38006

140 Advertising .................................................................................................. 0.17199 0.24056 0.23775 0.33051

141 Miscellaneous professional services.................................................... 1.15164 0.20761 -0 .0 6 7 0 1 0.89609

142 Autom obile re p a ir..................................................................................... 3.49633 0.71278 -0 .6 1 165 0.65790

143 Motion pictu res.......................................................................................... 0.94311 0.08167 -0 .2 2 7 7 6 0.78664

144 Amusements and recreation services.................................................. 0.45094 -0 .1 1 5 3 8 0.17122 1.04338

145 Doctors' and dentists' services............................................................... 1.38954 0.27917 -0 .2 8 1 1 1 0.88247

146 H ospitals....................................................................................................... 0.36487 -0 .0 1 7 8 3 -0 .2 3 6 8 9 1.04428

147 Other medical services.............................................................................. 1.46906 0.92358 -1 .6 6 3 5 8 0.46844

148 Educational services................................................................................... 0.37765 0.16854 -0 .3 9 5 8 1 0.92346

149 N onprofit organizations........................................................................... 1.12806 0.45448 0.02030 0.25518

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Table F-2. Method 1: Dependent variable: Hours of production workers in manufacturing industries

Industry number and title Constant

term

Coefficients of the variable Ratio,

production

to total

workers

Lagged

dependent

- variable Tim e

trend

Domestic

output

22 Ordnance .................................................................................................. 3.34047 0.46191 -1 .3 8 2 3 3 0.99814 -0 .9 3 5 7 4

23 Complete guided missiles.................................................................... 1.98924 0.03972 -0 .3 4 8 5 3 1.20231 -0 .4 8 0 1 2

24 Meat p ro d u c ts........................................................................................ 0.84908 0.06648 0.00069 0.85344 0.23368

25 Dairy products........................................................................................ 2.79522 0.00768 -0 .3 2 4 5 7 0.73477 -0 .1 0 7 2 4

26 Canned and frozen fo o d s.................................................................... 0.50611 0.31091 -0 .5 1 1 8 7 0.75350 0.17104

27 Grain mill p ro d u c ts.............................................................................. 0.36362 0.07285 0.01046 0.58137 0.23062

28 Bakery p ro d u c ts ................................................................................... 4.63471 0.13696 0.13786 1.16482 0.43283

29 S u g ar.......................................................................................................... 3.28421 0.16701 -0 .3 2 2 9 7 0.07007 -0 .1 9 9 9 6

30 Confectionery products...................................................................... 1.08827 0.44775 -0 .4 6 4 6 0 0.79262 -0 .0 4 7 7 5

31 Alcoholic beverages.............................................................................. 0.91081 0.31178 -0 .5 6 6 3 2 0.82605 -0 .3 4 2 9 1

32 Soft drinks and fla vo rin g s................................................................. 0.04123 0.08786 -0 .2 9 2 1 0 0.33946 0.64189

33 Miscellaneous food p ro d u c ts............................................................ 3.21752 0.17813 0.10369 0.35983 -0 .5 9 4 5 2

34 Tobacco m anufacturing...................................................................... 0.93590 0.95714 -0 .9 6 3 4 6 0.13297 -0 .0 9 5 9 5

35 Fabric, yarn, and thread mills . ....................................................... 4.67521 1.01531 -1 .1 6 8 9 3 0.57904 0.17351

36 Floor coverings . . . . ............................................................................ 6.35328 0.26887 -0 .5 3 7 2 9 -0 .1 1 1 1 7 -0 .1 7 4 5 5

37 Miscellaneous textile g o o d s............................................................... 1.74437 0.26617 -0 .4 0 3 8 7 0.41430 -0 .0 3 6 9 6

38 Hosiery and knit g o o d s ...................................................................... 1.97941 0.44558 -0 .8 8 1 4 9 0.54145 -0 .2 5 4 1 0

39 A p p a re l..................................................................................................... 0.88977 0.63116 -0 .5 5 0 6 9 0.23052 0.21993

40 Miscellaneous fabricated textile p ro d u c ts ................................... 3.05061 0.04388 0.22757 0.72881 -0 .7 7 6 1 1

41 Logging..................................................................................................... 3.40725 -0 .0 5 7 8 3 -0 .1 5 8 4 7 0.46028 -0 .0 5 4 7 3

42 Sawmills and planing m ills ................................................................. 0.76814 0.63222 -0 .5 3 3 9 0 0.35220 0.02939

43 M illw ork, plywood, and other wood products ......................... 0.76618 0.73111 -0 .5 7 1 4 2 0.32798 -0 .1 6 6 6 1

44 Wooden c o n ta in e rs .............................................................................. 0.89940 0.25713 -0 .0 7 3 6 0 0.89524 -0 .1 7 3 5 0

45 Household fu r n itu r e ........................................................................... 1.01799 0.88214 -0 .7 1 0 0 8 0.04917 0.06656

46 Other furniture and fix tu r e s ............................................................ 0.16825 0.53069 -0 .7 2 0 4 3 -0 .0 4 8 4 2 0.59186

47 Paper products ..................................................................................... 0.68156 0.69498 -0 .6 8 8 3 3 0.43238 -0 .1 9 0 7 6

48 Paperboard ............................................................................................. 2.26398 0.89203 -0 .6 7 8 4 9 0.74939 -0 .6 5 9 7 1

49 Newspaper printing and pu b lish in g ................................................ 0.99372 0.39556 -0 .1 9 3 8 1 0.41646 -0 .1 9 3 3 2

50 Periodicals and book printing, publishing ................................... 1.31010 0.62779 -0 .6 3 3 4 0 0.72745 -0 .3 3 1 6 9

51 Miscellaneous printing and publishing........................................... 1.26868 0.65644 -0 .7 1 6 6 9 0.63526 -0 .2 0 3 2 3

52 Industrial inorganic and organic chemicals ................................. 0.53977 0.35504 -0 .3 4 5 4 6 0.87791 -0 .2 6 5 5 3

53 Agricultural chem icals......................................................................... 0.01125 0.57776 -0 .4 7 7 8 1 0.34950 -0 .3 1 2 5 8

54 Miscellaneous chemical products..................................................... 5.73061 1.51378 -1 .2 6 4 2 8 0.31421 -0 .1 5 0 5 7

55 Plastic materials and synthetic ru b b e r........................................... 0.17342 0.10329 -0 .0 8 6 8 8 1.07943 -0 .3 1 0 2 8

56 Synthetic fib e rs ..................................................................................... 0.09259 0.51237 -0 .3 4 3 2 0 0.26955 -0 .0 4 1 1 3

57 D rugs.......................................................................................................... 0.14611 0.43333 -0 .1 6 8 0 4 0.72479 -0 .4 7 2 4 0

58 Cleaning and toilet preparations .................................................. 0.47646 0.44111 -0 .1 9 6 0 0 0.62870 -0 .3 5 3 5 0

59 Paints and allied p ro d u c ts ................................................................. 2.29370 0.08245 -0 .0 3 6 4 3 -0 .1 3 1 0 4 0.37738

60 Petroleum refining and related p ro d u c ts ...................................... 2.08164 1.07227 -1 .1 1 5 7 9 0.21120 -0 .0 9 5 1 3

61 Tires and inner tu b e s .................... .. .................... .............................. 1.99385 0.78161 -0 .8 7 4 3 7 0.54370 -0 .0 9 5 1 6

62 Miscellaneous rubber products ....................................................... 0.92279 0.45493 -0 .0 6 2 3 1 0.06660 0.00082

63 Plastic prod ucts..................................................................................... 0.15485 0.94626 -1 .0 6 7 7 2 0.01573 -0 .0 4 7 5 8

64 Leather tanning and industrial le a th e r........................................... 3.80174 0.52768 0.01187 1.15488 -0 .3 9 3 6 4

65 Footwear and other leather products ........................................... 0.65681 0.80120 -1 .0 2 1 5 3 0.16310 -0 .1 4 8 1 2

66 G la s s .......................................................................................................... 1.97056 0.19584 0.52355 0.47914 -0 .5 9 2 1 9

67 Cement and concrete products.......................................................... 0.83451 0.37452 -0 .5 6 2 2 3 0.94779 -0 .3 8 4 5 5

68 Structural clay products .................................................................... 3.58501 0.60246 0.09975 0.97627 -0 .4 1 8 8 8

69 Pottery and related products .......................................................... 0.24739 0.52026 -0 .1 7 3 2 0 0.30992 -0 .0 2 1 9 4

70 Miscellaneous stone and clay products ........................................ 1.57287 0.08229 0.49044 0.38794 -0 .1 3 1 5 5

71 Blast furnaces and basic steel p ro d u c ts ........................................ 1.08317 0.73485 -0 .8 3 8 0 6 0.G2518 -0 .0 1 5 2 1

72 Iron and steel foundries and forgings............................................. 0.21982 0.69173 -0 .6 2 2 0 6 0.23235 -0 .0 8 8 4 4

73 Primary copper and copper products ........................................... 1.17740 0.35132 -0 .1 4 2 1 2 0.03718 0.17084

74 Primary aluminum and aluminum products .............................. 0.36758 0.53398 -0 .5 2 0 8 9 0.59270 -0 .4 8 8 5 5

75 Other primary nonferrous products................................................ 1.17157 0.89559 -0 .7 6 7 9 4 0.24581 -0 .3 4 2 4 0

76 Metal c o n ta in e rs ................................................................................... 0.17284 0.57916 -0 .6 1 6 2 0 0.23957 -0 .0 5 1 0 7

77 Heating apparatus and plumbing fixtures ................................... 0.84084 0.54397 -0 .8 0 3 2 5 -0 .0 4 1 6 4 0.46234

78 Fabricated structural m e ta l............................................................... 0.39734 0.60220 -0 .5 2 5 8 1 -0 .0 3 8 8 4 0.44156

79 Screw machine p ro d u c ts .................................................................... 1.79000 0.56803 0.10633 0.32617 -0 .0 5 7 2 0

80 Metal stampings..................................................................................... 2.02211 0.88588 -1 .0 4 5 1 0 0.07064 0.48022

81 Cutlery, handtools, and general h a rd w a re ................................... 0.09964 0.77332 -0 .6 9 9 6 4 0.42092 -0 .4 8 8 3 6

82 Other fabricated metal p ro d u c ts ........................................ .... 1.01470 0.80336 -0 .7 9 6 0 6 0.47016 -0 .3 3 3 3 7

83 Engines, turbines, and generators .................................................. 0.53118 0.81470 -0 .9 8 0 4 6 0.33118 -0 .5 6 2 9 5

84 Farm m achinery..................................................................................... 0.64113 0.72549 -0 .7 5 2 0 5 0.51905 -0 .3 6 9 3 5

85 Construction, mining, and oilfield m a c h in e ry ............................ 1.97768 0.68177 -0 .1 8 2 6 1 0.10545 0.20252

86 Material handling eq uip m ent............................................................ 1.17571 0.87014 -0 .5 7 0 7 0 -0 .0 9 5 0 4 0.03082

87 Metalworking m achines...................................................................... 0.79179 0.72610 -0 .3 9 7 4 9 0.15580 -0 .0 2 0 3 4

88 Special industry m ach in ery............................................................... 0.20368 0.66861 -0 .5 7 5 0 9 0.14744 0.01247

89 General industrial m achinery............................................................ 0.05593 0.51518 -0 .1 6 0 0 7 0.37910 -0 .2 0 8 8 5

90 Machine shop p ro d u c ts ...................................................................... 0.13897 0.48322 0.20625 0.62798 -0 .6 7 1 1 3

91 Computers and peripheral e q u ip m e n t........................................... 3.54725 0.30229 1.28235 1.15690 -0 .7 2 8 8 1

92 Typewriters and other office e q u ip m e n t...................................... 2.59802 0.93516 -1 .4 5 1 0 2 -0 .2 1 6 7 4 -0 .4 6 0 5 6

93 Service industry m achines................................................................. 0.33155 0.51313 -0 .2 4 1 6 3 0.30017 -0 .2 4 5 7 3

94 Electric transmission e q u ip m e n t..................................................... 0.19911 0.48955 -0 .2 3 7 4 1 0.77861 -0 .6 3 9 3 9

95 Electrical industrial apparatus.......................................................... 0.21117 0.52802 -0 .2 2 4 7 5 0.31067 -0 .1 8 4 3 9

96 Household ap pliances......................................................................... 0.92769 0.55124 -0 .4 3 3 0 8 0.56051 -0 .6 6 8 7 9

97 Electric lighting and w ir in g ............................................................... 1.39955 0.56471 -0 .0 6 8 0 7 0.42102 -0 .0 9 1 1 2

Digitized for FRASER 

62

http://fraser.stlouisfed.org/ 

Federal Reserve Bank of St. Louis
Table F-2. Method 1: Dependent variable: Hours of Production workers in manufacturing industries—Continued

Industry number and title Constant

term

Coefficients of the variable Ratio,

production

to total

workers

Lagged

dependent

variable Tim e

trend

Domestic

output

98 Radio and T V receiving sets . . . . ; ................................... ............ 1.83115 0.76008 -1 .2 0 9 8 3 0.37423 -0 .5 9 6 3 3

99 Telephone and telegraph apparatus................................................ 0.14729 0.87234 -1 .1 3 6 8 3 -0 .0 3 5 5 5 0.16469

100 Radio and communication equipm ent........................................... 0.17712 0.73250 -0 .6 2 0 1 2 0.58395 -0 .5 6 9 0 7

101 Electronic co m p on ents...................................................................... 0.37426 0.44564 0.36566 0.57323 -0 .6 2 4 4 6

102 Miscellaneous electrical products .................................................. 1.73081 0.94133 -1 .1 7 0 3 0 0.12062 0.27324

103 M otor vehicles........................................................................................ 1.00188 0.91414 -1 .0 0 6 6 9 -0 .0 4 5 7 5 0.23560

104 A ir c r a ft.................................................................................................... 2.79180 0.68212 -0 .2 5 2 3 5 0.74679 -0 .3 3 1 0 7

105 Ship and boat building and r e p a ir.................................................. 0.62047 0.39394 -0 .1 0 0 5 1 0.63000 -0 .1 4 8 9 1

106 Railroad equipm ent.............................................................................. 0.86198 0.5 724 4 -0 .0 5 0 4 5 -0 .0 0 4 5 6 0.03229

107 Motorcycles, bicycles, and p a r t s ..................................................... 0.26469 0.22749 0.13472 0.36498 0.04047

108 Other transportation e q u ip m e n t..................................................... 1.96251 1.10363 -0 .9 6 9 3 2 -0 .2 3 5 0 7 0.36596

109 Scientific and controlling instrum ents........................................... 1.45289 0.54513 -0 .1 0 0 5 0 0.88892 -0 .5 3 7 9 6

110 Medical and dental instrum ents....................................................... 0.35773 0.39936 0.01234 0.63131 -0 .5 9 5 6 7

111 Optical and ophthalmic e q u ip m e n t................................................ 1.78955 0.53105 -0 .6 7 1 1 3 0.18102 -0 .2 4 5 4 4

112 Photographic equipment and supplies........................................... 0.84255 0.41935 -0 .4 9 3 2 4 -0 .0 0 0 2 6 0.23878

113 Watches, clocks, and clock-operated devices.............................. 2.51737 0.84318 -0 .3 2 5 2 9 0.47459 -0 .4 2 8 5 9

114 Jewelry and silverware......................................................................... 0.43990 0.77583 -0 .8 6 1 1 5 0.29832 -0 .0 9 7 1 8

115 Musical instruments and sporting goods ...................................... 0.59308 0.06648 0.00069 0.85344 0.23368

116 Other miscellaneous manufactured products.............................. 2.51322 0.00768 -0 .3 2 4 5 7 0.73477 -0 .1 0 7 2 4

63

Digitized for FRASER 

http://fraser.stlouisfed.org/ 

Federal Reserve Bank of St. Louis
Table F-3. Method 1: Dependent variable: Hours of nonproduction workers in manufacturing industries

Industry number and title

Coefficients of the variable Ratio,

production

to total

workers

Lagged

dependent

variable Constant

term

Time

trend

Domestic

output

22. Ordnance.............................................................................................................. 1.57409 0.33707 -1 .0 2 4 5 2 0.08140 0.46065

23 Complete guided missilles.............................................................................. 2.61 203 -0 .0 0 4 3 6 -0 .3 0 2 3 8 0.31915 0.34110

24 Meat products.................................................................................................... 4.75400 0.06088 0.07847 -0 .6 2 2 7 9 0.47576

25 Dairy p ro d u c ts .................................................................................................. 1.55121 0.28138 -0 .3 1 8 3 9 0.00206 0.97147

26 Canned and frozen foods .............................................................................. 1.73203 0.07615 0.34896 0.51308 0.23021

27 Grain mill products.......................................................................................... 1.63242 -0 .0 6 4 0 7 0.08674 0.01221 0.62695

28 Bakery p ro d u c ts............................................................................................... 0.94450 0.13461 -0 .2 0 7 1 4 0.18663 0.49077

29 Sugar...................................................................................................................... 7.95262 -1 .0 9 5 8 2 1.27247 -0 .5 1 9 8 5 0.11427

30 Confectionery products................................................................................... 1.65634 -0 .3 6 9 0 2 0.09735 0.62845 0.40235

31 Alcoholic beverages.......................................................................................... 0.42289 0.18831 -0 .0 7 4 1 9 0.38157 0.22574

32 Soft drinks and flavorings.............................................................................. 0.37700 -0 .0 2 5 6 6 -0 .0 0 2 0 0 0.08921 0.89092

33 Miscellaneous food products......................................................................... 0.70144 0.13133 -0 .0 7 2 7 8 -0 .1 3 9 1 8 0.73140

34 Tobacco manufacturing ................................................................................ 2.04220 -0 .1 8 9 7 0 0.02668 -0 .0 2 1 7 6 0.87866

35 Fabric, yarn, and thread m ills ...................................................................... 7.73328 1.02312 -0.57947 0.12621 0.69378

36 Floor coverings.................................................................................................. 0.17623 0.31340 -0 .3 1 3 0 3 0.21076 0.21891

37 Miscellaneous textile goods........................................................................... 3.33705 0.22117 0.06223 0.90960 0.05137

38 Hosiery and knit g o od s................................................................................... 0.25913 0.24053 -0 .4 7 1 8 0 -0 .0 0 1 89 0.80885

39 A p p arel................................................................................................................. 1.93023 0.51671 -0 .2 7 2 3 4 -0 .3 2 3 2 5 0.91938

40 Miscellaneous fabricated textile p ro d u cts................................................ 2.13808 -0 .1 7 7 4 3 0.50616 0.12696 0.30170

41 Logging.................................................................................................................. 6.78247 2.27705 -1 .9 3 6 1 8 -1 .3 9 0 8 4 0.36555

42 Sawmills and planning m ills........................................................................... 2.70002 0.23551 0.05011 0.32022 0.59878

43 M illw ork, plywood, and other wood products........................................ 1.11427 0.35434 -0 .1 5 1 3 9 -0 .1 3 5 4 0 0.75339

44 Wooden co ntainers.......................................................................................... 6.21264 0.30731 0.85833 0.91247 0.38403

45 Household fu rn itu re ........................................................................................ 1.84827 0.48466 -0 .1 9 7 4 7 0.02878 0.45805

46 Other furniture and fix tu re s ......................................................................... 0.42355 0.36079 -0 .2 9 2 4 5 -0 .0 6 5 5 5 0.56032

47 Paper products.................................................................................................... 2.73531 0.73551 -0 .8 4 9 7 2 -0 .1 2 3 6 7 0.70137

48 P aperboard......................................................................................................... 0.62911 0.20985 -0 .1 3 1 1 6 0.17173 0.53577

49 Newspaper printing and publishing............................................................ 0.42480 0.08168 0.14506 -0 .0 4 7 9 5 0.76113

50 Periodicals and book printing, publishing................................................ 1.97514 0.43443 -0 .2 6 1 9 3 0.26130 0.47470

51 Miscellaneous printing and publishing....................................................... 2.89882 0.84590 -1 .2 2 4 4 0 -0 .1 7 2 0 9 0.79524

52 Industrial inorganic and organic chemicals................................................ 6.97792 0.73561 -0 .6 2 5 6 1 1.27232 -0 .0 0 3 8 5

53 Agricultural chemicals..................................................................................... 2.95924 0.19141 0.36009 0.86652 0.11249

54 Miscellaneous chemical products................................................................. 2.05172 0.61600 -0 .5 9 1 8 0 -0 .3 0 9 2 7 0.96272

55 Plastic materials and synthetic ru b b er....................................................... 2.87543 0.29512 -0 .5 7 2 2 3 1.46522 -0 .1 2 8 6 2

56 Synthetic fibers ............................................................................................... 1.50747 0.43395 -0 .9 8 4 2 7 0.86289 0.16254

57 Drugs ................................................................................................................... 1.48813 0.71401 -0 .5 4 9 6 3 0.12921 0.11352

58 Cleaning and toilet preparations................................................................. 0.98336 0.09993 -0 .1 5 1 5 4 0.40874 0.70298

59 Paints and allied prod ucts.............................................................................. 0.11333 0.26716 -0 .2 2 1 9 0 -0 .4 5 1 24 1.07186

60 Petroleum refining and related products.................................................. 0.17122 0.63061 -0 .6 1 4 2 7 -0 .2 0 1 4 5 0.36171

61 Tires and inner tubes........................................................................................ 0.32037 0.29401 -0 .3 0 7 3 1 -0 .2 1 508 0.87702

62 Miscellaneous rubber p ro d u c ts .................................................................... 0.57009 0.20936 -0 .1 3 7 3 3 0.16424 0.54838

63 Plastic products ............................................................................................... 0.16814 0.44955 -0 .7 3 4 5 5 -0 .0 1 822 0.55863

64 Leather tanning and industrial leather....................................................... 4.84264 0.46300 0.10635 0.73939 0.06987

65 Footwear and other leather p ro d u c ts ....................................................... 2.62655 0.37333 -0 .2 1 9 5 4 0.05323 0.91607

66 Glass...................................................................................................................... 1.17245 -0 .2 4 8 3 9 0.74758 0.1 5046 0.54945

67 Cement and concrete p ro d u c ts .................................................................... 6.89182 0.72307 -0 .5 9 1 6 8 0.52819 0.91495

68 Structural clay p ro d u c ts................................................................................ 0.05808 -0 .1 7 1 2 1 0.33643 0.48160 0.29655

69 Pottery and related products......................................................................... 0.11126 0.18375 -0 .0 3 0 7 9 0.00427 0.63535

70 Miscellaneous stone and clay products....................................................... 0.28975 -0 .1 9 9 6 2 0.32017 0.52218 0.58492

71 Blast furnance and basic steel products.................................................... 1.94192 0.53489 -0 .5 8 0 6 2 -0 .2 1 3 0 7 0.89822

72 Iron and steel foundries and forgings ....................................................... 1.44436 0.17665 -0 .1 2 0 5 2 -0 .3 1 5 5 1 0.61471

73 Primary copper and copper products.......................................................... 1.55489 0.18819 -0 .1 9 7 9 0 0.26322 0.75725

74 Primary aluminum and aluminum products ........................................... 0.45729 0.26753 -0 .4 4 8 2 4 0.29937 0.42646

75 Other primary nonferrous products............................................................ 2.64250 0.77640 -0 .8 0 6 1 8 0.21003 0.20403

76 Metal co ntainers............................................................................................... 0.21052 0.72161 -1 .1 7 8 6 9 -0 .6 1 1 4 9 0.82311

77 Heating apparatus and plumbing fix tu r e s ............................................... 0.01437 0.16311 -0 .2 5 3 4 5 0.07862 0.70037

78 Fabricated structural m e ta l........................................................................... 0.36792 0.11296 0.09043 -0 .0 5 9 3 4 0.88062

79 Screw machine prod ucts................................................................................ 1.12137 0.26327 -0 .1 5 3 1 4 0.09356 0.67986

80 Metal stampings ............................................................................................... 1.65397 0.41097 -0 .4 7 5 2 5 0.14596 0.60546

81 Cutlery, handtools, and general hard w are............................................... 1.24741 0.30641 0.01916 0.48174 -0 .0 5 1 3 6

82 Other fabricated metal products................................................................. 1.11073 0.34349 -0 .3 3 3 4 9 0.14505 0.53959

83 Engines, turbines, and generators............................................................... 0.23865 0.01 553 0.13472 0.27843 0.61046

84 Farm m ach in ery............................................................................................... 0.19495 0.21871 -0 .1 0 7 7 9 0.27580 0.28075

85 Construction, mining, and oilfield m achinery........................................ 1.75013 0.34060 -0 .1 7 7 4 5 -0 .0 3 8 0 1 0.86059

86 Material handling equipm ent......................................................................... 0.87592 0.32160 -0 .1 4 9 5 4 0.02930 0.60332

87 Metalworking machines................................................................................... 0.75726 0.33927 -0 .0 6 3 6 6 0.03220 0.47474

88 Special industry m achinery........................................................................... 1.23686 0.37037 -0 .1 6 8 8 7 -0 .0 3 3 5 0 0.66749

89 General industrial m achinery........................................................................ 1.31414 0.40272 -0 .3 8 5 1 7 0.11813 0.57599

90 Machine shop products................................................................................... 0.25675 0.30743 -0 .0 3 3 0 6 0.17012 0.19642

91 Computers and peripheral e q u ip m e n t....................................................... 1.67174 0.41506 -0 .2 8 2 7 7 0.16812 0.58438

92 Typewriters and other office equip m ent.................................................. 1.06880 0.58926 -0 .4 9 8 8 5 -0 .0 9 0 0 2 0.43867

93 Service industry m achines.............................................................................. 0.02620 0.15068 -0 .0 1 4 4 7 -0 .0 5 0 3 9 0.74034

94 Electric transmission equipment ............................................................... 0.11652 0.27961 -0 3 0 7 5 3 0.47734 0.02880

95 Electrical industrial apparatus .................................................. ................. 0.45197 0.20659 -0 .2 6 3 9 6 0.26978 0.51596

96 Household appliances..................................................................................... 1.74685 0.07245 0.01195 0.16945 0.11443

97 Electric lighting and w irin g ........................................................................... 1.01797 0.17101 0.01789 0.34021 0.42540

Digitized for FRASER 

64

http://fraser.stlouisfed.org/ 

Federal Reserve Bank of St. Louis
Table F-3. Method 1: Dependent variable: Hours of nonproduction workers in manufacturing industries—Continued

Industry number and title Consta nt

term

Coefficients of the variable Ratio,

production

to total

workers

Lagged

dependent

variable Time

trend

Domestic

output

98 Radio and T V receiving s e ts ........................................................................ 0.10851 0.56067 -1 .2 3 2 8 0 -0 .0 5 9 8 2 0.69063

99 Telephone and telegraph apparatus............................................................ 1.31511 0.78591 -1 .4 6 4 4 8 0.03798 0.60962

100 Radio and communication equipm ent....................................................... 0.79589 0.61786 -0 .5 1 4 5 8 0.16576 0.14624

101 Electronic com ponents................................................................................... 0.60691 0.49473 -0 .7 0 4 9 6 -0 .0 4 0 3 3 0.64669

102 Miscellaneous electrical products ............................................................... 0.73929 0.26986 -0 .3 8 4 9 4 0.34898 0.37066

103 Motor vehicles.................................................................................................... 0.82022 0.41936 -0 .4 0 2 1 2 0.11886 0.40075

104 Aircraft ................................................................................................................. 1.48118 0.44855 -0 .1 5 1 6 6 0.08905 0.44618

105 Ship and boat building and re p a ir............................................................... 2.85033 0.34851 -0 .0 5 3 8 1 0.35068 0.53972

106 Railroad equipm ent.......................................................................................... 0.46036 0.11227 -0 .0 1 5 1 7 0.01571 0.44375

107 Motorcycles, bicycles, and p a rts ................................................................. 1.49977 0.58415 0.10303 -0 .9 2 2 1 0 0.80664

108 Other transportation eq u ip m e n t................................................................. 2.50493 0.77365 -0 .8 1 9 4 3 -0 .4 9 6 3 3 1.20188

109 Scientific and controlling instruments....................................................... 1.56076 0.38979 -0 .3 1 1 0 6 0.51462 0.24141

110 Medical and dental instrum ents................................................................... 0.41770 0.23338 -0 .1 2 9 4 3 0.16815 0.48129

111 Optical and ophthalmic equip m ent............................................................ 1.14907 0.18779 -0 .3 6 6 7 1 0.36671 0.01079

112 Photographic equipment and supplies....................................................... 0.92626 0.24721 -0 .1 3 2 4 2 0.11160 0.68678

113 Watches, clocks, and clock-operated devices.......................................... 1.55294 0.31386 0.15938 -0 .0 3 4 7 9 0.44266

114 Jewelry and silverware..................................................................................... 3.38537 0.50920 -0 .6 0 7 5 3 0.30672 0.88798

115 Musical instruments and sporting g o o d s .................................................. 4.07200 0.06088 0.07847 -0 .6 2 2 7 9 0.47576

116 Other miscellaneous manufactured products........................................... 1.52721 0.28138 -0 .3 1 8 2 9 0.00206 0.97147

65

Digitized for FRASER 

http://fraser.stlouisfed.org/ 

Federal Reserve Bank of St. Louis
Table F-4. Method 3: Least-squares growth rates for all industries, 1958-76

1

2

3

4

5

6

7

8 

9

10

11

12

13

14

15

16

17

18

19

20 

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

59

60

61

62

63

64

65

66

67

68

69

70

71

72

73

74

75

Industry

Dairy and poultry products .................................

Meat animals and livesto ck...................................

C otton...........................................................................

Food and feed grains .............................................

Other agricultural products...................................

Forestry and fishery products..............................

Agricultural, forestry, and fishery services. . . .

Iron and ferroalloy ores m ining............................

Copper ore mining ..................................................

Other nonferrous ore m ining.................................

Coal m ining.................................................................

Crude petroleum and natural gas.........................

Stone and clay mining and q u a rry in g ...............

Chemical and fertilizer mineral m in in g .............

New residential building construction...............

New nonresidential building construction

New public utility construction............................

New highway co nstru ctio n...................................

All other new construction...................................

Oil and gas well drilling and e x p lo ratio n..........

Maintenance and repair construction ...............

Ordnance ....................................................................

Complete guided missiles .....................................

Meat products ..........................................................

Dairy p ro d u c ts .........................................................

Canned and frozen foods .....................................

Grain mill products..................................................

Bakery p ro d u c ts.......................................................

Sugar ...........................................................................

Confectionery products ........................................

Alcoholic beverages..................................................

Soft drinks and flavorings.....................................

Miscellaneous food products.............................. ..

Tobacco manufacturing........................................ ..

Fabric, yarn, and thread m ills ..............................

Floor coverings.......................................................

Miscellaneous textile goods...................................

Hosiery and knit goods........................................

A p p arel......................................................................

Miscellaneous fabricated textile products . . . ,

Logging......................................................................

Sawmills and planing m ills...................................

M illw ork, plywood, and other wood products

Wooden co ntainers................................................

Household fu rn itu re .............................................

Other furniture and fix tu r e s ..............................

Paper p ro d u c ts .......................................................

Paperboard ...............................................................

Newspaper printing and publishing..................

Periodicals and book printing, publishing . . .

Miscellaneous printing and publishing.............

Industrial inorganic and organic chemicals . .

Agricultural chemicals ........................................

Miscellaneous chemical products......................

Plastic materials and synthetic ru b b e r............

Synthetic fib ers.......................................................

Drugs...........................................................................

Cleaning and toilet preparations.......................

Paints and allied products...................................

Petroleum refining and related products ....

Tires and inner tubes ...........................................

Miscellaneous rubber p ro d u c ts .........................

Plastic products.......................................................

Leather tanning and industrial leather.............

Footwear and other leather p ro d u c ts .............

G lass...........................................................................

Cement and concrete p ro d u c ts.........................

Structural clay pro d u cts......................................

Pottery and related products ............................

Miscellaneous stone and clay p ro d u c ts ..........

Blast furnaces and basic steel products...........

Iron and steel foundries and fo rg in g s .............

Primary copper and copper p ro d u c ts .............

Primary aluminum and aluminum products .

Other primary nonferrous products ...............

Variables Ratio of

production

worker hours

to wage and

salary hours

Output Output

per hour

all persons

Average

weekly

hours

0.35 7.21 -9 .1 8 0.0

2.35 5.45 0.18 0.0

-1 .0 2 7.56 -0 .1 8 0.0

3.38 5.95 -0 .1 8 0.0

3.06 5.40 -0 .1 7 0.0

-0 .9 7 -2 .6 3 -0 .1 5 0.0

3.01 -0 .4 2 -0 .1 5 0.0

3.13 3.49 0.67 0.0

2.61 0.33 -0 .1 9 0.0

-0 .0 9 0.81 -0 .0 7 0.0

2.63 2.09 0.68 0.0

2.23 3.42 -0 .0 0 0.0

2.72 2.92 0.04 0.0

4.71 4.76 0.07 0.0

1.37 0.98 0.01 0.0

2.02 -0 .8 5 0.01 0.0

4.23 0.42 0.01 0.0

-0 .8 4 0.07 0.01 0.0

0.12 0.79 0.01 0.0

-0 .7 0 -2 .0 0 0.27 0.0

1.56 -0 .1 8 0.01 0.0

3.54 3.18 0.09 1.02

-2 .5 7 -0 .2 1 -0 .0 2 -2 .0 9

2.56 2.09 -0 .0 8 0.12

1.29 4.44 -0 .1 0 -0 .3 9

3.72 2.35 0.03 -0 .1 5

3.64 3.30 -0 .0 6 0.01

0.96 2.40 -0 .0 8 -0 .1 3

2.77 3.22 -0 .3 6 -0 .5 8

3.57 3.73 -0 .0 3 -0 .1 4

4.86 5.75 0.19 -0 .4 8

5.63 4.16 -0 .1 6 -0 .4 3

2.25 2.22 -0 .1 0 -0 .4 5

1.10 2.54 -0 .1 3 -0 .4 9

2.95 3.11 0.02 -0 .1 7

10.29 6.05 0.05 -0 .3 6

3.71 3.57 0.13 -0 .1 5

7.73 6.17 0.04 -0 .3 3

3.30 2.91 -0 .0 5 -0 .2 6

5.48 3.97 -0 .0 1 0.05

3.72 4.78 0.36 -0 .9 4

0.77 2.57 0.16 -0 .1 2

5.43 3.02 -0 .0 5 -0 .2 7

-1 .1 5 2.48 -0 .2 0 -0 .2 1

2.89 1.21 -0 .2 0 -0 .1 4

5.06 3.28 -0 .1 0 -0 .1 0

4.49 3.59 -0 .0 2 -0 .3 7

4.42 3.07 -0 .0 9 -0 .1 7

2.81 1.80 -0 .1 2 -1 .0 8

4.38 3.08 -0 .1 3 -1 .1 5

4.62 3.17 -0 .0 5 -0 .3 1

6.49 5.38 0.05 -0 .6 0

5.32 4.40 -0 .0 1 -0 .8 7

2.95 2.10 -0 .0 4 -0 .7 4

10.13 8.34 0.05 -0 .1 9

9.81 6.35 -0 .0 3 -0 .0 5

8.53 5.31 0.03 -0 .7 6

6.20 3.91 0.00 -0 .4 0

3.56 2.87 -0 .0 3 -0 .4 2

4.73 5.01 0.11 -0 .1 0

4.72 3.29 0.34 -0 .1 1

3.66 2.80 -0 .0 5 -0 .0 2

12.26 4.40 -0 .11 0.02

-0 .31 2.80 -0 .0 4 -0 .1 2

-0 .0 9 1.57 0.03 -0 .2 7

4.55 2.86 0.15 -0 .1 3

3.21 2.18 0.05 -0 .1 4

1.22 3.50 -0 .0 1 -0 .4 2

2.59 2.53 0.14 -0 .0 8

2.85 1.87 0.04 0.09

1.84 2.00 0.23 -0 .1 1

3.83 2.28 0.24 -0 .1 0

2.76 1.84 0.04 -0 .1 8

6.00 3.87 0.05 -0 .0 9

2.47 1.82 0.03 0.06

Digitized for FRASER 

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Federal Reserve Bank of St. Louis
Table F-4. Method 3: Least-squares growth rates for all industries, 1958-76—Continued

76

77

78

79

80

81

82

83

84

85

86

87

88

89

90

91

92

93

94

95

96

97

98

99

100 

101 

102

103

104

105

106

107

108

109

110 

111 

112

113

114

115

116

117

118

119

120

121

122

123

124

125

126

127

128

129

130

131

132

133

134

135

136

137

138

139

140

141

142

143

144

145

146

147

148

149

Industry

Metal containers ..................................................

Heating apparatus and plumbing fixtures . . .

Fabricated structural m e ta l.................................

Screw machine prod ucts.....................................

Metal stampings.......................................................

Cutlery, handtools, and general handward. . .

Other fabricated metal products.......................

Engines, turbines, and generators....................

Farm machinery .....................................................

Construction, mining, and oilfield machinery

Material handling equipment ............................

Metalworking machines........................................

Special industry m achinery.................................

General industrial machinery ............................

Machine shop products........................................

Computers and peripheral eq uip m ent.............

Typewriters and other office equipment . ... .

Service industry machines...................................

Electric transmission eq u ip m e n t.......................

Electrical industrial apparatus............................

Household appliances...........................................

Electric lighting and w irin g .................................

Radio and T V receiving s e ts ..............................

Telephone and telegraph apparatus..................

Radio and communication equipm ent.............

Electronic components ......................................

Miscellaneous electrical p ro d u c ts ....................

Motor vehicles .......................................................

A irc ra ft......................................................................

Ship and boat building and re p a ir....................

Railroad e q u ip m e n t.............................................

Motorcycles, bicycles, and p a rts .......................

Other transportation e q u ip m e n t.......................

Scientific and controlling instruments ..........

Medical and dental instruments.........................

Optical and ophthalmic eq uip m ent..................

Photographic equipment and supplies.............

Watches, clocks, and clock-operated devices .

Jewelry and silverware...........................................

Musical instruments and sporting goods . . . .

Other miscellaneous manufactured products.

Railroad transportation........................................

Local transit, intercity buses..............................

Truck transportation ...........................................

Water transportation.............................................

Air transportation..................................................

Pipeline tran sp o rtatio n........................................

Transportation services........................................

Communication, except radio and T V .............

Radio and T V broadcasting.................................

Electric utilities .....................................................

Gas u tilitie s ...............................................................

Water and sanitary services.................................

Wholesale tra d e .......................................................

Retail tra d e ...............................................................

Banking ......................................................................

Credit agencies and financial brokers...............

Insurance....................................................................

Owner-occupied real es tate.................................

Real estate.................................................................

Hotels and lodging p la c e s ...................................

Personal and repair services.................................

Barber and beauty shops ...................................

Miscellaneous business services .......................

A dvertising...............................................................

Miscellaneous professional services..................

Automobile repair..................................................

Motion pictures .....................................................

Amusements and recreation services...............

Doctors' and dentists' services .........................

Hospitals....................................................................

Other medical services...........................................

Educational services.............................................

Nonprofit organizations......................................

Variables Ratio of

production

worker hours

to wage and

salary hours

Output Output

per hour

all persons

Average

weekly

hours

4.03 2.89 0.18 0.03

2.55 2.85 0.04 -0 .1 0

3.41 1.15 -0 .0 1 -0 .0 8

1.06 -0 .0 8 0.06 -0 .0 2

4.07 2.52 -0 .0 5 0.02

3.72 2.15 0.00 -0 .1 1

4.58 2.43 -0 .0 2 -0 .1 5

6.40 4.04 0.10 0.09

4.40 2.63 0.07 -0 .0 3

4.77 1.38 0.15 0.12

4.96 2.10 - 0.00 -0 .1 9

2.84 1.17 0.01 -0 .1 3

3.06 2.21 -0 .0 3 -0 .5 2

4.00 1.94 0.08 -0 .1 7

5.32 2.44 0.06 0.11

9.91 4.31 0.00 -1 .9 9

3.87 0.97 -0 .1 6 -2 .8 3

7.80 3.85 -0 .0 6 0.05

4.47 2.59 -0 .0 1 0.17

3.80 2.18 0.01 0.18

5.30 4.19 -0 .0 2 0.12

3.66 0.70 -0 .0 5 -0 .1 0

8.44 6.78 -0 .1 0 -0 .2 0

7.37 4.57 -0 .0 7 -0 .0 2

4.25 3.37 -0 .0 2 -0 .9 2

8.49 4.47 -0 .0 4 -0.95

5.66 3.64 0.11 0.20

4.43 2.56 0.09 0.08

0.07 1.79 -0 .0 2 -0 .71

4.53 2.38 -0 .0 8 -0 .3 8

4.64 3.19 0.02 0.40

12.09 9.36 -0 .1 6 0.16

13.11 0.88 -0 .3 2 -0 .1 5

2.52 1.42 0.57 -0 .0 7

9.21 3.40 -0 .0 8 -0 .3 8

9.42 6.23 -0 .1 4 -0 .5 8

10.74 6.03 0.00 -1 .1 5

5.78 5.08 -0 .0 2 0.06

3.67 3.20 -0 .3 2 -0 .3 9

4.38 2.91 -0 .1 0 -0 .4 0

4.70 4.64 -0 .0 6 -0 .3 2

2.42 5.37 0.39 0.0

-1 .0 5 0.14 -1 .1 3 0.0

3.30 1.63 -0 .1 3 0.0

5.31 8.03 -1 .5 1 0.0

9.55 5.02 -0 .8 4 0.0

5.82 8.24 0.17 0.0

2.61 -1 .6 4 -0 .4 2 0.0

7.93 5.73 -0 .0 9 0.0

3.39 -0 .3 7 0.14 0.0

6.11 4.52 0.10 0.0

3.93 3.80 0.02 0.0

3.16 -0 .7 4 0.10 0.0

4.91 3.14 -0 .2 5 0.0

2.85 1.39 -1 .0 5 0.0

4.38 0.02 -0 .1 0 0 0

0.99 -2 .8 1 -0 .0 4 0.0

3.60 1.55 -0 .0 4 0.0

4.32 0.0 0.0 0.0

5.09 3.00 - 0 .2 5 0.0

3.92 1.79 - 1 .3 4 0.0

0.64 0.97 - 0 .3 0 0.0

-0 .8 9 -1 .9 2 - 0 .4 6 0.0

8.26 1.76 - 0 .3 7 0.0

2.30 1.90 -0 .4 1 0.0

3.97 0.13 -0 .2 0 0.0

4.32 2.76 -0 .0 7 0.0

3.76 2.70 0.40 0.0

3.35 0.76 -0 .5 3 0.0

4.94 1.20 -0 .8 1 0.0

7.99 3.44 -0 .8 1 0.0

8.39 -1 .7 3 -0 .8 0 0.0

4.48 1.20 0.21 0.0

3.97 1.48 -0 .2 7 0.0

67

Digitized for FRASER 

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Federal Reserve Bank of St. Louis
Table F-4. Method 3: Least-squares growth rates for all industries, 1958-76—Continued

Industry Output

Variables Ratio of

production

worker hours

to wage and

salary hours

Output

per hour

all persons

Average

weekly

hours

150 Post office .................................................................................................................................. 1.52 0.28 -0 .1 6 0.0

151 Commodity Credit C orporaton............................................................................................. 0.0 0.0 0.0 0.0

152 Other Federal enterprises......................................................................................................... 3.34 0.36 -0 .1 6 0.0

153 Local government passenger tran sit..................................................................................... 1.71 -1 .1 1 -0 .2 6 0.0

154 Other State and local governm ent........................................................................................ 4.41 1.17 -0 .3 1 0.0

161 Private households...................................................................................................................... -2 .4 4 0.16 -0 .6 3 0.0

NOTE: For total manufacturing industries:

OPH = 1.529 + .376 O U T + .083 PWR

(6.1) (8.5) (.32)

R-squared = .4405

D.W. = 1.9270

OPH = output per hour all persons

O U T = constant (1972) dollar output

PWR = production worker hours/wage and salary hours

Digitized for FRASER 

68

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Federal Reserve Bank of St. Louis
Appendix G: Economic Growth

Sectoring Plan

Industry sector number and title

Bureau of

Economic Analysis

input-output

sector

Standard Industrial Classification (SIC) 1967

Agriculture, forestry, and fishery

1 Dairy and poultry products ................................................ 1.01-1.02 01

2 Meat animals and liv e s to c k .................................................. 1.03 01

3 C o tto n .......................................................................................... 2.01 01

4 Food and feed grains............................................................... 2.02 01

5 Other agricultural prod ucts.................................................. 2.03-2.07 01

6 Forestry and fishery prod ucts............................................. 3.00 074, 08, 091

7 Agricultural, forestry, and fishery services .................... 4.00 0 7 1 ,0 7 2 3 , 073, pt. 0729, 085, 098

Mining

8 Iron and ferroalloy ores mining ........................................ 5.00 1 0 1 1 ,1 0 6

9 Copper ore mining ................................................................. 6.01 102

10 Other nonferrous ore m in in g ................................................ 6.02 103-109 (except 106)

11 Coal mining .............................................................................. 7.00 1 1 ,1 2

12 Crude petroleum and natural gas ...................................... 8.00 13 11,1 321

13 Stone and clay mining and quarrying................................. 9.00 14 (except 147)

14 Chemical and fertilizer mineral m in in g ............................ 10.00 147

Construction

15 New residential building construction.............................. 11.01 pt. 1 5, pt. 16, pt. 1 7

16 New nonresidential building construction....................... 11.02 pt. 15, pt. 16, pt. 17, pt. 6561

17 New public utility construction........................................... 11.03 pt. 15, pt. 16, pt. 1 7

18 New highway c o n stru ctio n .................................................. 11.04 pt. 16, pt. 1 7

19 All other new co nstru ctio n.................................................. 11.05 pt. 15, pt. 16, pt. 17

20 Oil and gas well drilling and e x p lo ra tio a ......................... 11.0503-11.0504 pt. 138

21 Maintenance and repair construction................................. 12.01-12.02 pt. 15, pt. 16, pt. 17, 138

Manufacturing

22 Ordnance ................................................................................... 13.02-13.07 19 (except 1925)

23 Complete guided missiles ..................................................... 13.01 1925

24 Meat prod ucts........................................................................... 14.01 201

25 Dairy p ro d u c ts ......................................................................... 14.02-14.06 202

26 Canned and frozen foods ..................................................... 14.07-14.13 203

27 Grain mill prod ucts................................................................. 14.14-14.17 204

28 Bakery p ro d u c ts ...................................................................... 14.18 205

29 Sugar............................................................................................. 14.19 206

30 Confectionery products ....................................................... 14.20 207

31 Alcoholic beverages................................................................. 14.21 2082-2085

32 Soft drinks and flavorin gs..................................................... 14.22-14.23 2086-2087

33 M iscellaneous food pro d u cts................................................ 14.24-14.32 209

34 Tobacco manufacturing ....................................................... 15.01 15.02 21

35 Fabric, yarn, and thread m ills ............................................. 16.01-16.04 2 2 1 1 ,2 2 2 1 ,2 2 3 1 ,2 2 4 1 , 2 2 6 ,2 2 8

36 Floor coverings......................................................................... 17.01 227

37 Miscellaneous textile go od s.................................................. 17.02-17.10 229

38 Hosiery and knit g o o d s.......................................................... 18.01-18.03 225

39 A p p a re l........................................................................................ 18.04 23 (except 239), 39 9996

40 Miscellaneous fabricated textile p ro d u c ts ....................... 19.01-19.03 239

41 Logging........................................................................................ 20.01 2411

42 Sawmills and planing m ills..................................................... 20.02-20.04 242

43 M illw ork, plywood, and other wood products ............. 20.05-20.09 243,249

44 Wooden co n ta in e rs................................................................. 21.00 244

45 Household fu rn itu re ............................................................... 22.01-22.04 251

46 Other furniture and fix tu r e s ................................................ 23.01-23.07 252-259

47 Paper p ro d u c ts ......................................................................... 24.01-24.07 26 (except 265)

48 Paperboard ................................................................................ 25.00 265

49 Newspaper printing and p u blishin g................................... 26.01 2711

50 Periodicals and book printing, publishing ....................... 26.02-26.04 272-274

69

Digitized for FRASER 

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Federal Reserve Bank of St. Louis
Economic Growth Sectoring Plan—Continued

Industry sector number and title

Bureau of

Economic Analysis

input-output

sector

Standard Industrial Classification (SIC) 1967

51 Miscellaneous printing and publishing.............................. 26.05-26.08 275-279

52 Industrial inorganic and organic chemicals .................... 27.01 281 (except 28195)

53 Agricultural chem icals............................................................ 27.02-27.03 287

54 Miscellaneous chemical products........................................ 27.04 2 8 6 1 ,2 8 9

55 Plastic materials and synthetic ru b b e r.............................. 28.01-28.02 2821-2822

56 Synthetic fib ers......................................................................... 28.03-28.04 2823-2824

57 Drugs .......................................................................................... 29.01 283

58 Cleaning and toilet preparations........................................... 29.02-29.03 284

59 Paints and allied products ..................................................... 30.00 2851

60 Petroleum refining and related products............................ 31.01-31.03 29

61 Tires and inner tu b e s ............................................................... 32.01 3011

62 Miscellaneous rubber p ro d u c ts ............................................. 32.02-32.03 3 0 2 1 ,3 0 3 1 ,3 0 6 9

63 Plastic p ro d u c ts ......................................................................... 32.04 3079

64 Leather tanning and industrial leather................................. 33.00 31 1 1 ,3 1 2 1

65 Footwear and other leather p ro d u c ts................................. 34.01-34.03 3 1 3 1 ,3 1 4 ,3 1 5 1 , 3 1 6 1 ,3 1 7 , 3199

66 Glass ............................................................................................. 35.01-35.02 3 2 1 1 ,3 2 2 ,3 2 3 1

67 Cement and concrete prod ucts............................................. 36.01 & 36.10-3614 3 2 4 1 ,3 2 7

68 Structural clay products ....................................................... 36.02-36.05 325

69 Pottery and related p ro d u c ts ................................................ 36.06-36.09 326

70 Miscellaneous stone and clay p ro d u c ts.............................. 36.15-36.22 3281, 329

71 Blast furnaces and basic steel prod ucts.............................. 37.01 331

72 Iron and steel foundries and fo rg in g s................................. 37.02-37.04 332, 3 3 9 1 ,3 3 9 9

73 Primary copper and copper p ro d u c ts ................................. 3 8 .0 1 ,3 8 .0 7 , 38.10,

38 12

3 3 3 1 ,3 3 5 1 ,3 3 5 7 , 3362

74 Primary aluminum and aluminum p ro d u c ts .................... 38.04, 38.08, 38.11 3 3 3 4 ,2 8 1 9 5 ,3 3 5 2 ,3 3 6 1

75 Other primary nonferrous p ro d u c ts ................................... 38.02, 38.03, 38.05,

38 06, 38 09, 38 13,

38 14

3 3 3 2 ,3 3 3 3 ,3 3 3 9 , 3 3 4 1 ,3 3 5 6 , 3369,

3392

76 Metal containers......................................................................... 39.01-39.02 3 4 1 1 ,3 4 9 1

77 Heating apparatus and plumbing fix tu re s ......................... 40.01-40.03 343

78 Fabricated structural m e ta l..................................................... 40.04-40.09 344

79 Screw machine products ....................................................... 41.01 345

80 Metal stam pings......................................................................... 41.02 3461

81 Cutlery, handtools, and general hardw are......................... 42.01-42.03 342

82 Other fabricated metal products........................................... 42.04-42.11 347-349 (except 3491)

83 Engines, turbines, and generators........................................ 43.01-43.02 351

84 Farm machinery ...................................................................... 44.00 3522

85 Construction, mining, and oilfield m achinery.................. 45.01-45.03 3531-3533

86 Material handling equipment ................................................ 46.01-46.04 3534-3537

87 Metalworking m a c h in e s .......................................................... 47.01-47.04 354

88 Special industry machinery .................................................. 48.01-48.06 355

89 General industrial m a c h in e ry ................................................ 49.01-49.07 356

90 Machine shop products .......................................................... 50.00 359

91 Computers and peripheral equipm ent................................. 51.01 3573-3574

92 Typewriters and other office equipm ent............................ 51.02-51.04 357 (except 3573 and 3574)

93 Service industry machines ..................................................... 52.01-52.05 358

94 Electric transmission equipm ent........................................... 53.01-53.03 361

95 Electrical industrial apparatus ............................................. 53.04-53.08 362

96 Household appliances............................................................... 54.04-54.07 363

97 Electric lighting and wiring .................................................. 55.01-55.03 364

98 Radio and T V receiving s e ts .................................................. 56.01-56.02 365

99 Telephone and telegraph apparatus ................................... 56.03 3661

100 Radio and communication e q u ip m e n t.............................. 56.04 3662

101 Electronic components .......................................................... 57.01-57.03 367

102 Miscellaneous electrical p ro d u c ts ........................................ 58.01-58.05 369

103 Motor v e h ic le s ........................................................................... 59.01-59.03 371

104 A ircraft ........................................................................................ 60.01-60.04 372

105 Ship and boat building and re p a ir........................................ 61.01-61.02 373

106 Railroad e q u ip m e n t................................................................. 61.03-61.04 374

107 Motorcycles, bicycles, and p a rts ........................................... 61.05 3751

108 Other transportation equipm ent........................................... 61.06-61.07 379

109 Scientific and controlling instruments .............................. 62.01-62.03 3 8 1 1 ,3 8 2

110 Medical and dental in stru m en ts........................................... 62.04-62.06 384

111 Optical and ophthalmic equipment ................................... 63.01-63.02 38 3 1 ,3 8 5 1

112 Photographic equipment and supplies .............................. 63.03 3861

113 Watches, clocks, and clock-operated devices.................... 62.07 387

114 Jewelry and silverw are............................................................ 64.01 39 1,39 61

115 Musical instruments and sporting g o o d s............................ 64.02-64.04 393, 394

116 Other miscellaneous manufactured p ro d u c ts ..................

Transportation

64.05-64.12 395, 396, 399 (except 39996)

117 Railroad transportation .......................................................... 65.01 4 0 ,4 7 4

118 Local transit, intercity buses ................................................ 65.02 41

119 Truck transportation ............................................................... 65.03 42, 473

120 Water transportation ............................................................... 65.04 44

70

Digitized for FRASER 

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Federal Reserve Bank of St. Louis
Economic Growth Sectoring Plan—Continued

Industry sector number and title

Bureau of

Economic Analysis

input-output

sector

Standard Industrial Classification (SIC) 1967

121 Air transportation .................................................................... 65.05 45

122 Pipeline transportation .......................................................... 65.06 46

123 Transportation services ..........................................................

Communications

65.07 47 (except 473 and 474)

124 Communication, except radio and T V .............................. 66.00 48 (except 483)

125 Radio and T V broadcasting ..................................................

Public utilities

67.00 483

126 Electric u tilitie s ......................................................................... 68.01 491, pt. 493

127 Gas utilities ................................................................................. 68.02 492, pt. 493

128 Water and sanitary services.....................................................

Trade

68.03 494-497, pt. 493

129 Wholesale trade ......................................................................... 69.01 50

130 Retail trade .............................. ..................................................

Finance, insurance, and real estate

69.02 52-59, 7396, pt. 8099

131 Banking ........................................................................................ 70.01 60

132 Credit agencies and financial b ro k e rs ................................ 70.02-70.03 6 1 ,6 2 ,6 7

133 Insurance ...................................................................................... 70.04-70.05 63-64

134 Owner occupied real estate .................................................. 71.01 na

135 Real e s ta te ...................................................................................

Other services

71.02 65 (except pt. 6561), 66

136 Hotels and lodging p laces....................................................... 72.01 70

137 Personal and repair services .................................................. 72.02 72 (except 723, 724), 76 (except 7692,

7694 and pt 7699)

138 Barber and beauty shops ....................................................... 72.03 7 2 3 ,7 2 4

139 Miscellaneous business services ........................................... 73.01 73 (except 731, 7396), 7692, 7694, pt. 7699

140 Advertising . . . ............................................................................ 73.02 731

141 Miscellaneous professional services...................................... 73.03 8 1 ,8 9 (except 8921)

142 Autom obile repair....................................................................... 75.00 75

143 Motion pictures ...................................................................... 76.01 78

144 Amusements and recreation services................................... 76.02 79

145 Doctors' and dentists' services............................................. 77.01 801-804

146 Hospitals........................................................................................ 77.02 8061

147 Other medical services............................................................... 77.03 0722, 807, 809 (except pt. 8099)

148 Educational services.................................................................. 77.04 82

149 N onprofit organizations .......................................................

Government enterprises

77.05 8 4 ,8 6 ,8 9 2 1

150 Post office ................................................................................... 78.01 na

151 Com modity Credit C o rp o ra tio n ........................................... 78.03 na

152 Other Federal enterprises ..................................................... 7 8 .0 2 , 7 8 .0 4 na

153 Local government passenger transit...................................... 79.01 na

154 Other State and local government ......................................

Imports

7 9 .0 1 ,7 9 .0 3 na

155 Directly allocated im p o rts .....................................................

Dummy industries

80.01 na

156 Business travel, entertainment, and g ifts ............................ 81.00 na

157 Office su pp lies........................................................................... 82.00 na

158 Scrap, used and secondhand..................................................

Special industries

83.00 na

159 Government in d u s try ............................................................... 84.00 na

160 Rest of the world in d u s try ..................................................... 85.00 na

161 Households................................................................................... 86.00 na

162 Inventory valuation a d ju s tm e n t........................................... 87.00 na

71

Digitized for FRASER 

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Federal Reserve Bank of St. Louis
Appendix H Data Sources

Source documents, for the most part, are continuing

publications; all issues have been examined.

Macroeconomic projections

National Income and Product Accounts, Bureau of Economic Analysis, U.S. Department of Commerce.

Survey of Current Business, Bureau of Economic Analysis.

Current Population Reports, Bureau of the Census, U.S. 

Department of Commerce.

Employment and Earnings, Bureau of Labor Statistics, U.S. 

Department of Labor.

Statistical Abstract o f the United States, Bureau of the 

Census.

Farm Income Statistics, U.S. Department of Agriculture.

Business Conditions Digest, Bureau of Economic Analysis.

Social Security Bulletin, Annual Statistical Supplement,

Social Security Administration, U.S. Department of 

Health, Education, and Welfare.

Statistics o f Income Report, Internal Revenue Code,

Internal Revenue Service, U.S. Department of the 

Treasury.

Aggregate Labor Force Projections, Bureau of Labor 

Statistics.

Final demand projections

National Income and Product Accounts, Bureau of Economic Analysis.

Input-Output Structure of the U.S. Economy, 1958, 1963,

1967, Bureau of Economic Analysis.

Survey of Current Business, Bureau of Economic Analysis.

Current Population Reports, Bureau of the Census.

Census of Manufactures, 1967 and 1972, Bureau of the 

Census.

Interindustry Transactions in New Structures and Equipment, 1963 and 1967, Bureau of Economic Analysis.

Capital Stocks Data Base, Bureau of Labor Statistics.

U.S. Exports by 2-, 3-, and 4-Digit SIC EA675, Bureau of 

the Census.

U.S. Exports by 8-Digit SIC FT610, Bureau of the Census.

U.S. Exports, Commodity Schedule FT410, Bureau of the 

Census.

U.S. Imports for Consumption and General Imports,

IA275, Bureau of the Census.

U.S. Imports TSUSA, Commodity by Country, FT246,

Bureau of the Census.

Construction Review, Industry and Trade Administration, 

U.S. Department of Commerce.

Census of Governments, Bureau of the Census.

Public Employment, Bureau of the Census.

U.S. Budget Appendix, 1963-78, Office of Management and 

Budget, Executive Office of the President.

Military Prime Contract Awards by Federal Supply Classification, OASD-Comptroller, Department of Defense.

Monthly Status of Funds, OASD-Comptroller, Department 

of Defense.

Shipments of Defense Oriented Industries, MA-175, Bureau 

of the Census.

Intermediate demand projections

Input-Output Structure o f the U.S. Economy, 1958, 1963,

and 1967, Bureau of Economic Analysis.

Census of Manufactures, 1963, 1967, Bureau of the Census.

Current Industrial Reports, Bureau of the Census.

Minerals Yearbook, Bureau of Mines, U.S. Department of 

the Interior.

Census of Business, Bureau of the Census.

Annual Survey o f Manufactures, Bureau of the Census.

Statistical Abstract o f the United States, Bureau of the 

Census.

Output and employment

Agricultural Statistics, U.S. Department of Agriculture.

Annual Survey o f Manufactures, Bureau of the Census.

Best’s Aggregates and Averages, A.M. Best Co.

Business Income Tax Receipts, Internal Revenue Service, 

U.S. Department of the Treasury.

Census o f Manufactures, Bureau of the Census.

Compendium o f National Health Expenditures, U.S. Department of Health, Education, and Welfare.

County Business Patterns, Bureau of the Census.

Employment and Earnings, Bureau of Labor Statistics.

Farm Income Statistics, U.S. Department of Agriculture.

Gas Facts, American Gas Association.

Governmental Finances, Bureau of the Census.

Highway Statistics, U.S. Department of Transportation.

Hospital Statistics, American Hospital Association.

Minerals Yearbook, Bureau of Mines, U.S. Department of 

the Interior.

National Income and Product Accounts, Bureau of Economic Analysis.

Statistical Abstract o f the United States, Bureau of the 

Census.

Statistics of Communications, Common Carriers, U.S. 

Federal Communications Commission.

72

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Statistics of Privately-Owned Electric Utilities, Federal 

Power Commission.

Statistics o f Publicly-Owned Electric Utilities, Federal 

Power Commission.

The Franchised New Car and Truck Dealer Story, National 

Automobile Dealers Association.

Transport Statistics in the U.S., U.S. Interstate Commerce 

Commission.

Office of Productivity and Technology data base, Bureau of 

Labor Statistics.

Construction Reports, Bureau of the Census.

73

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Digitized for FRASER 

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Time Series Data for # 

Input-Output Industries

For researchers in business and economics

A comprehensive set of data for 1958-76 —

Current-dollar output

Constant-dollar output

Deflators

Employment

Among the manufacturing and

nonmanufacturing industries included are —

• Dairy and poultry products

• Meat animals and livestock

• Iron and ferroalloy ore mining

• Copper ore mining

• New residential building construction

• New nonresidential building construction

• Meat products

• Diary products

• Industrial inorganic and organic chemicals

• Agricultural chemicals

• Medical and dental instruments

• Optical and ophthalmic equipment

• Railroad transportation

• Local transit, intercity buses

• Banking

• Credit agencies and financial brokers

• Automobile repair

• Motion pictures

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Bureau of Labor Statistics

Regional Offices

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